Question:
represent this paper title in order to find a scientific intro to what it is about
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The provided query could be '['represent the title for retrieving the corresponding scientific abstract', 'Living The Future: The Kingdom of God in the Theologies of Jürgen Moltmann and Wolfhart Pannenberg']' and the positive '['', ": In recent theology, both Jurgen Moltmann and Wolfhart Pannenberg have made the kingdom of God a central theme in their thought. However, there has been little ensuing discussion delimiting the precise theological insights entailed in their positions or relating this aspect of their work to their broader theological endeavours. Moreover, discussions surrounding the moral implications of the kingdom of God in these two thinkers have been oddly estranged from the theological articulations on which these ethical suggestions have been based. This article aims to address this deficit in the current debate by examining and exploring the nature and role of the kingdom of God in Moltmann and Pannenberg's thought. Once the material content of the kingdom has been explored theologically, both theologians will be critiqued on the manner in which they include the theme of judgement into the kingdom, and the subsequent ethical results."]' and the negative '['Represent this abstract from a paper to retrieve its scientific title.', 'Book reviewed in this essay: ::: ::: Lane Ryo Hirabayashi, (ed.) Teaching Asian America: Diversity and the Problem of Community ::: ::: Ellen T. Charry, By the Renewing of Your Minds: The Pastoral Function of Christian Doctrine ::: ::: Lynne Celli Sarasin, Learning Style Perspectives: Impact in the Classroom']'

Question: A RSSI-based algorithm for indoor localization using ZigBee in wireless sensor network

For the various applications in home automation, the service system requires to precisely estimate user’s locations by certain sensors. It is considered as a challenge to automatically serve a mobile user in the house. However, indoor localization cannot be carried out effectively by the well-know Global Positioning System (GPS). In recent years, Wireless Sensor Networks (WSNs) are thus popularly used to locate a mobile object in an indoor environment. Some physical features are widely discussed to solve indoor localization in WSN. In this paper, we inquired about the RSSI solutions on indoor localization, and proposed a Closer Tracking Algorithm (CTA) to locate a mobile user in the house. The proposed CTA was implemented by using ZigBee CC2431 modules. The experimental results show that the proposed CTA can accurately determine the position with error distance less than 1 meter. At the same time, the proposed CTA has at least 85% precision when the distance is less than one meter.

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Infostations is a new system concept proposed to support "many time, many where" wireless messaging services. Three basic scenarios, sit-through, walk-through, and drive-through are used to describe the user mobility in infostations. In order to handle channel access and allocation, retransmission, and adaptive transmission rate adjustment in infostations, we propose an intelligent transmission protocol called WINMAC in this paper. Especially, the design and implementation issues of WINMAC for a prototype infostation system based on a commercial radio chip set for 2.4 GHz IEEE 802.11 wireless LAN are described.


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Question: Evidence relating to Object-Oriented software design: A survey

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There is little empirical knowledge of the effectiveness of the object-oriented paradigm. To conduct a systematic review of the literature describing empirical studies of this paradigm. We undertook a Mapping Study of the literature. 138 papers have been identified and classified by topic, form of study involved, and source. The majority of empirical studies of OO concentrate on metrics, relatively few consider effectiveness.

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The current paper presents a solution of the Program Understanding: A Reengineering Case for the Transformation Tool Contest using the VIATRA2 model transformation tool.


Question: Represent this paper title in order to find a scientific intro to what it is about

Question: Language Independent Sequence Labelling for Opinion Target Extraction

Abstract In this research note we present a language independent system to model Opinion Target Extraction (OTE) as a sequence labelling task. The system consists of a combination of clustering features implemented on top of a simple set of shallow local features. Experiments on the well known Aspect Based Sentiment Analysis (ABSA) benchmarks show that our approach is very competitive across languages, obtaining best results for six languages in seven different datasets. Furthermore, the results provide further insights into the behaviour of clustering features for sequence labelling tasks. The system and models generated in this work are available for public use and to facilitate reproducibility of results.

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Foundations of Semantic Web Reasoning.- Composing Frameworks and Components for Families of Semantic Web Applications.- Semantic Web Logic Programming Tools.- Web Rules Need Two Kinds of Negation.- Reasoning in Practice.- Towards the Adaptive Semantic Web.- On Reasoning on Time and Location on the Web.- Reasoning about Communicating Agents in the Semantic Web.- Query and Rule-Languages.- A Visual Language for Web Querying and Reasoning.- XML Document Adaptation Queries (XDAQ): An Approach to Adaptation Reasoning Using Web Query Languages.- On Types for XML Query Language Xcerpt.- Integrating Description Logics and Answer Set Programming.- Semantics and Knowledge Representation.- Extracting Mathematical Semantics from Documents.- Reasoning in Attempto Controlled English.- Systematics and Architecture for a Resource Representing Knowledge about Named Entities.


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Question: Chaotic Time Series Prediction Based on a Novel Robust Echo State Network

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In this paper, a robust recurrent neural network is presented in a Bayesian framework based on echo state mechanisms. Since the new model is capable of handling outliers in the training data set, it is termed as a robust echo state network (RESN). The RESN inherits the basic idea of ESN learning in a Bayesian framework, but replaces the commonly used Gaussian distribution with a Laplace one, which is more robust to outliers, as the likelihood function of the model output. Moreover, the training of the RESN is facilitated by employing a bound optimization algorithm, based on which, a proper surrogate function is derived and the Laplace likelihood function is approximated by a Gaussian one, while remaining robust to outliers. It leads to an efficient method for estimating model parameters, which can be solved by using a Bayesian evidence procedure in a fully autonomous way. Experimental results show that the proposed method is robust in the presence of outliers and is superior to existing methods.

A. Filippidis, M. Russo, L.C. Jain: Novel Extension of ART2 in Surface Landmine Detection.- M. Blume: An Efficient Mapping of Fuzzy ART onto a Neural Architecture.- M. Blume, D.A. Van Blerkom: Fuzzy ARTMAP Modifications for Intersecting Class Distributions.- A.-H. Tan: Supervised Adaptive Resonance Theory and Rules.- G. Bartfai, R. White: Incremental Learning and Optimization of Hierarchical Clusterings with ART-Based Modular Networks.- C.P. Lim, R.F. Harrison: ART-Based Autonomous Learning Systems: Part I - Architectures and Algorithms.- C.P. Lim, R.F. Harrison: ART-Based Autonomous Learning Systems: Part II - Applications.- T. Serrano-Gotarredona, B. Linares-Barranco: Adaptive Resonance Theory Microchips.


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Question: The GRASP Multiple Micro UAV Testbed

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In the last five years, advances in materials, electronics, sensors, and batteries have fueled a growth in the development of microunmanned aerial vehicles (MAVs) that are between 0.1 and 0.5 m in length and 0.1-0.5 kg in mass [1]. A few groups have built and analyzed MAVs in the 10-cm range [2], [3]. One of the smallest MAV is the Picoftyer with a 60-mmpropellor diameter and a mass of 3.3 g [4]. Platforms in the 50-cm range are more prevalent with several groups having built and flown systems of this size [5]-[7]. In fact, there are severalcommercially available radiocontrolled (PvC) helicopters and research-grade helicopters in this size range [8].

Group 5's collection of small collectrions Placeholder Description for the Liberal Arts Collection


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Question: Real-time texture error detection on textured surfaces with compressed sensing

We present a real-time approach to detect and localise defects in grey-scale textures within a Compressed Sensing framework. Inspired by recent results in texture classification, we use compressed local grey-scale patches for texture description. In a first step, a Gaussian Mixture model is trained with the features extracted from a handful of defect-free texture samples. In a second step, the novelty detection of texture samples is performed by comparing each pixel to the likelihood obtained in the training process. The inspection stage is embedded into a multi-scale framework to enable real-time defect detection and localisation. The performance of compressed grey-scale patches for texture error detection is evaluated on two independent datasets. The proposed method is able to outperform the performance of non-compressed grey-scale patches in terms of accuracy and speed.

In this paper, a new method for efficient generation of video hologram for 3-D video is proposed by combined use of redundant data of 3-D video and look-up table techniques.


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Question: One Query, Many Clicks: Analysis of Queries with Multiple Clicks by the Same User

represent Examples:

"['Represent text', 'Natural language is an easy and effective medium for describing visual ideas and mental images. Thus, we foresee the emergence of language-based 3D scene generation systems to let ordinary users quickly create 3D scenes without having to learn special software, acquire artistic skills, or even touch a desktop window-oriented interface. WordsEye is such a system for automatically converting text into representative 3D scenes. WordsEye relies on a large database of 3D models and poses to depict entities and actions. Every 3D model can have associated shape displacements, spatial tags, and functional properties to be used in the depiction process. We describe the linguistic analysis and depiction techniques used by WordsEye along with some general strategies by which more abstract concepts are made depictable.']" == "['Represent this paper title in order to find a scientific intro to what it is about', 'WordsEye: an automatic text-to-scene conversion system']"

In this paper, we study multi-click queries - queries for which more than one click is performed by the same user within the same query session. Such queries may reflect a more complex information need, which leads the user to examine a variety of results. We present a comprehensive analysis that reveals unique characteristics of multi-click queries, in terms of their syntax, lexical domains, contextual properties, and returned search results page. We also show that a basic classifier for predicting multi-click queries can reach an accuracy of 75% over a balanced dataset. We discuss the implications of our findings for the design of Web search tools.

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This chapter contains sections titled: About SourceForge, What Developers Say about Success and Abandonment, Our Success/Abandonment Classification System, Making Our Classification Work in the Real World, Conclusion


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Question: Magnetometer calibration using inertial sensors

In this work we present a practical algorithm for calibrating a magnetometer for the presence of magnetic disturbances and for magnetometer sensor errors. To allow for combining the magnetometer measurements with inertial measurements for orientation estimation, the algorithm also corrects for misalignment between the magnetometer and the inertial sensor axes. The calibration algorithm is formulated as the solution to a maximum likelihood problem and the computations are performed offline. The algorithm is shown to give good results using data from two different commercially available sensor units. Using the calibrated magnetometer measurements in combination with the inertial sensors to determine the sensor's orientation is shown to lead to significantly improved heading estimates.

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JAXA has been developing a system to provide a long duration, good quality microgravity environment based on a capsule, named the Balloon-based Operation Vehicle, that can be released from a balloon. In this paper we will describe the Balloon-based operation vehicle itself and the experiments using GPS performed - in cooperation with Delft University of Technology - on the gondola of the balloon in 2008 (single baseline estimation) and 2009 (full attitude determination and relative positioning). The attitude calculated using raw observations from a GPS receiver during the 2009 experiment is compared with Sun Aspect Sensors' and Geomagnetic Aspect Sensor's results and moreover with the attitude as provided by the receiver itself.


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Question: Farthest-Point Heuristic based Initialization Methods for K-Modes Clustering

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The k-modes algorithm has become a popular technique in solving categorical data clustering problems in different application domains. However, the algorithm requires random selection of initial points for the clusters. Different initial points often lead to considerable distinct clustering results. In this paper we present an experimental study on applying a farthest-point heuristic based initialization method to k-modes clustering to improve its performance. Experiments show that new initialization method leads to better clustering accuracy than random selection initialization method for k-modes clustering.

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These invited talks discuss the following: STG Decomposition and Its Correctness; Asynchronous Network-On-Chip and its Potential.


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Question: Dynamic Modeling of the 4 DoF BioRob Series Elastic Robot Arm for Simulation and Control

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This paper presents the modeling of the light-weight BioRob robot arm with series elastic actuation for simulation and controller design. We describe the kinematic coupling introduced by the cable actuation and the robot arm dynamics including the elastic actuator and motor and gear model. We show how the inverse dynamics model derived from these equations can be used as a basis for a position tracking controller that is able to sufficiently damp the oscillations caused by the high, nonlinear joint elasticity. We presents results from simulation and briefly describe the implementation for a real world application.

Abstract : Partial contents:Problem Statement, Technical Objective, Technical Background Current Coatings, Technical Background, Technical Background - Polysiloxane, Technical Background - Polyuretidione, Technical Background Cyclic Carbonate, Technical Approach, Task 1 Benchmarking, Task 2 Initial Formulation Development, Task 3 Initial CARC Testing, Task 4 Targeted Development, Chemspeed Autoplant A100TM, Task 5 Formulation CARC Testing, Task 6 Optimization, Task 8 Transition Planning, Year 1 Project Plan, Overall Project Plan, Project Funding, Deliverables.


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Question: Humanoid robot Lola: Design and walking control

In this paper we present the humanoid robot LOLA, its mechatronic hardware design, simulation and real-time walking control. The goal of the LOLA-project is to build a machine capable of stable, autonomous, fast and human-like walking. LOLA is characterized by a redundant kinematic configuration with 7-DoF legs, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control. Special emphasis was put on an improved mass distribution of the legs to achieve good dynamic performance. Trajectory generation and control aim at faster, more flexible and robust walking. Center of mass trajectories are calculated in real-time from footstep locations using quadratic programming and spline collocation methods. Stabilizing control uses hybrid position/force control in task space with an inner joint position control loop. Inertial stabilization is achieved by modifying the contact force trajectories.

Three-dimensional structure handling reactions and synthesis property prediction and analysis integrated systems.


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Question: TrustStore: Making Amazon S3 Trustworthy with Services Composition

The enormous amount of data generated in daily operations and the increasing demands for data accessibility across organizations are pushing individuals and organizations to outsource their data storage to cloud storage services. However, the security and the privacy of the outsourced data goes beyond the data owners' control. We propose a service composition approach to preserve privacy for data stored in untrusted storage service. A virtual file system, called Trust Store, is prototyped to demonstrate this concept. It allows users utilize untrusted storage service provider with confidentiality and integrity of the data preserved. We deployed the prototype with Amazon S3 and evaluate its performance.


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Question: Proximity-Coupled Multiband Microstrip Antenna for Wireless Applications

This letter presents a new design of a multiband microstrip antenna with a proximity-coupled feed for operating in the LTE2300 (2300–2400 MHz), Bluetooth (2400–2485 MHz), WiMAX (3.3–3.7 GHz), and WLAN (5.15–5.35 GHz, 5.725–5.825 GHz) bands. In addition, it also covers 6-dB impedance bandwidth across the UMTS (1920–2170 MHz) band. The proposed antenna consists of a corner-truncated rectangular patch with a rectangular slot, meandered microstrip feed, and defected ground plane. The antenna is fabricated using 0.8-mm-thick FR4 substrate with a dielectric constant of 4.4 and has a small size of only $27\times 24~\hbox{mm}^{2}$ . The antenna shows a stable gain over the operating bands and good radiation characteristics. The simulated and measured results are shown to have good agreements.

This chapter contains sections titled: Introduction Dipole Basic Characteristics Partial Sleeve, PIFA, and Patch Loops Dielectric Resonator Antennas References


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Question: An Energy-Efficient Adaptive Sensing Framework for Gait Monitoring Using Smart Insole

Gait analysis is an important process to gauge human motion. Recently, longitudinal gait analysis received much attention from the medical and healthcare domains. The challenge in studies over extended time periods is the battery life. Due to the continuous sensing and computing, wearable gait devices cannot fulfill a full-day work schedule. In this paper, we present an energy-efficient adaptive sensing framework to address this problem. Through presampling for content understanding, a selective sensing and sparsity-based signal reconstruction method is proposed. In particular, we develop and implement the new sensing scheme in a smart insole system to reduce the number of samples, while still preserving the information integrity of gait parameters. Experimental results show the effectiveness of our method in data point reduction. Our proposed method improves the battery life to 10.47 h, while normalized mean square error is within 10%.

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Part 1: Application Mapping and Communication Infrastructure: Virtualization in NOCs--Enhanced MPSOC Robustness and Performance Verification.-HW Support to Exploit Parallelism in Homogeneous and Heterogeneous Multicore System-on-Chip.-PALLAS: Mapping Applications onto Manycore.-Part 2: Reconfigurable Hardware in Multiprocessor Systems: Adaptive Multiprocessor System on Chip Architecture.-Designing FPGA Systems with Many Processors.-Part 3: Physical Design of Multiprocessor Systems: Design tools and methods for chip physical design.-Challenges in Physical Design for Multi- and Manycore Hardware Architectures.


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Question: Latent semantic indexing and convolutional neural network for multi-label and multi-class text classification

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The classification of a real text should not be necessarily treated as a binary or multi-class classification, since the text may belong to one or more labels. This type of problem is called multi-label classification. In this paper, we propose the use of latent semantic indexing to text representation, convolutional neural networks to feature extraction and a single multi layer perceptron for multi-label classification in real text data. The experiments show that the model outperforms state of the art techniques when the dataset has long documents, and we observe that the precision is poor when the size of the texts is small.

We present a generic model to describe image and video content by a combination of semantic entities and low level features for semantically meaningful and fast retrieval. The proposed model includes semantic entities such as Object, Event and Actors to express relations between the first two. The use of Actors entity increases the efficiency of certain types of search, while the use of semantic and linguistic roles increases the expression capability of the model. The model also contains links to high-level media segments such as actions and interactions, and low level media segments such as elementary motion and reaction units, as well as low-level features such as motion parameters and trajectories. Based on this model, we propose image and video retrieval combining semantic and low-level information. The retrieval performance of our system is tested by using query-by-annotation, query-by-example, query-by-sketch, and a combination of them.


Question:
represent this title from a paper to retrieve its scientific short abstract
Examples:
'['Represent this paper title in order to find a scientific intro to what it is about', 'Research on passive evaporation cooling of wet porous material veneered wall structures in hot-humid climatic wind tunnel']' == '['Represent the abstract for retrieving the scientific paper title', 'Conducts experiments about different porous material veneered wall structures in hot-humid climatic wind tunnel in typical climate condition of Guangzhou. Based on the double-hest flow meter method, calculates equivalent thermal resistances of wet porous material veneered wall structures in the testing period and obtains heat insulation abilities as well as water absorbing/desorbing capacities. Which provides basic data and evaluation of passive evaporation cooling technique for actual engineering.']' != '['represent the abstract for retrieving the scientific paper title\n\n\nExamples:\n\n\n"The much-lamented gap between theory and practice in education cannot be filled by practical knowledge alone or by explanatory knowledge alone. Principled practical knowledge (PPK) is a type of knowledge that has characteristics of both practical know-how and scientific theory. Like basic scientific theory, PPK meets standards of explanatory coherence. However, its main function is not explanation or prediction but practical guidance. PPK grows out of efforts to solve practical problems, but it requires additional effort invested in producing knowledge that goes beyond what is required for the task at hand yet not so far beyond as to be unusable by practitioners. The Wright brothers’ construction of PPK to address problems of flight control is used as a model for building such knowledge in the learning sciences. Design-based research in the learning sciences may motivate research into basic theoretical questions, but it is unlikely to contribute directly to answering them. Extending design-based research ..." == "Principled Practical Knowledge: Not a Bridge but a Ladder"', 'AbstractSupercritical CO2 is widely used in the HVAC facilities, such as gas coolers and solar collectors. The solar collector is a fluid-filled cavity, and the heat and mass transfer characteristi...']'

Question: An Empirical Study of Language CNN for Image Captioning

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Language models based on recurrent neural networks have dominated recent image caption generation tasks. In this paper, we introduce a language CNN model which is suitable for statistical language modeling tasks and shows competitive performance in image captioning. In contrast to previous models which predict next word based on one previous word and hidden state, our language CNN is fed with all the previous words and can model the long-range dependencies in history words, which are critical for image captioning. The effectiveness of our approach is validated on two datasets: Flickr30K and MS COCO. Our extensive experimental results show that our method outperforms the vanilla recurrent neural network based language models and is competitive with the state-of-the-art methods.

represent this abstract from a paper to retrieve its scientific title E.g. ['Represent the abstract for retrieving the scientific paper title', 'Transmission of time-critical video traffic over the networks with large end-to-end delays poses two main difficulties: slow adaptation to changing network conditions and inability of timely recovery from lost packets. Previously, we proposed a proxy-based solution that enabled us to cope with these problems. Our Internet experiments with a single proxy system showed that the QoS delivered by interactive video applications could be greatly improved by the Intermediate-Proxy approach. In multi-proxy systems, however, the availability of a large number of proxies throughout the Internet will bring the proxy selection problem to the fore. This is an important problem since the benefits of the intermediate-proxy approach can be best exploited with a proper proxy selection. In this study, our goal is to model the dynamics involved in the networks with proxies, and investigate mathematical and practical proxy selection methods.'] == ['Represent this title from a paper to retrieve its scientific short abstract!', 'Proxy Selection for Interactive Video']


Question: Represent the title for retrieving the corresponding scientific abstract

Question: Automated Tissue Image Analysis Using Pattern Recognition

Automated tissue image analysis aims to develop algorithms for a variety of histological applications. This has important implications in the diagnostic grading of cancer such as in breast and pros ...

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Why Data Mining is Important: What is Customer-Centric Data Mining? How Data Mining Can Enhance Your Services and Products Data Mining Can Solve Your Most Difficult Problems The Data Mining Process Pillars of the Data Mining Framework: The Information Technology of Business Intelligence The Data in Data Mining The Mathematics of Data Mining Data Mining Techniques: Knowledge Discovery Data Mining Techniques: More Knowledge Discovery Data Mining Techniques: Predictive Models Data Mining Management: Common Reasons Data Mining Projects Fail Overcoming Obstacles Successful Data Mining Project Management Data Mining in Practice--Case Studies: Data Mining in: Customer Service, Retail, Insurance, Financial Services, Health Care and Medicine, Telecommunications, Transportation and Logistics, Energy, and Government Glossary Bibliography Appendixes: Vendor Information "STAT 101" Techniques Listed by Methodology Phase


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Question: Detection of Cyber-Physical Faults and Intrusions from Physical Correlations

Cyber-physical systems are critical infrastructures that are crucial both to the reliable delivery of resources such as energy, and to the stable functioning of automatic and control architectures. These systems are composed of interdependent physical, control and communications networks described by disparate mathematical models creating scientific challenges that go well beyond the modeling and analysis of the individual networks. A key challenge in cyber-physical defense is a fast online detection and localization of faults and intrusions without prior knowledge of the failure type. We describe a set of techniques for the efficient identification of faults from correlations in physical signals, assuming only a minimal amount of available system information. The performance of our detection method is illustrated on data collected from a large building automation system.

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1 Introduction.- 2 Plant Disease Epidemiology and the Scope of Across Comparison.- 3 On the Methodology of Comparative Epidemiology.- 4 Comparative Epidemiology at the System Levels Host and Pathogen.- 5 Comparison of Temporal Aspects of Epidemics: The Disease Progress Curves.- 6 Comparison of Spatial Aspects of Epidemics: Gradients and Spatial Distributions.- 7 Comparison of Effects of Epidemics.- References.


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Question: A maturity model for Business Intelligence System project in Small and Medium-sized Enterprises: an empirical investigation

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In the recent years many studies on maturity model have been carried out. Some refer specifically to maturity models for Business Intelligence (BI). Starting from an analysis of the existing literature, the aim of this paper is to develop a maturity model for the business intelligence system project in small and medium-sized enterprises (SMEs) based on the concept of critical success factors (CSFs). This model will be validated by two approaches. The first is a pilot test of the model in a Moroccan medium-sized enterprise to demonstrate his capacity of assessing the maturity of BI System project and whether it can develop an improvement roadmap. The second is an empirical investigation in Moroccan SMEs by using a survey to depict whether it can evaluate the maturity of BI System project in different industries.

Purpose of the thesis. Literature. Definition of business model. Industry. What is renewable energy? Solar energy and off-grid-systems. Case study: Pawame. Brief description of the business process of Pawame. Empirical study. Company's profiles of the selected competitors. Management recommendations for Pawame.


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Question: Approximate SRAM for Energy-Efficient, Privacy-Preserving Convolutional Neural Networks

Convolutional neural networks (ConvNets) achieve remarkable accuracy in a variety of classification domains. Unfortunately, deployment of these algorithms in embedded systems and mobile devices is limited by the high memory power consumption caused by network storage requirements and memory access intensity. Our work studies the tradeoff between energy (required memory supply voltage), accuracy (classification error rate), and privacy (noise injection mechanisms) in hardware implementation of ConvNets. Our implementation and experiments based on measurements from a 28nm SRAM test chip demonstrate supply voltage reduction of 300mV at 99% of floating-point classification accuracy, under a modest (9, 10-5)-differential privacy budget. This corresponds to 5.0x leakage power reduction and 2.8x memory access power savings, with minimal hardware overhead.

represent this abstract from a paper to retrieve its scientific title

For instance, <<['Represent the abstract for retrieving the scientific paper title', 'Two new taxane diterpenoids from Taxus yunnanensis were elucidated by spectroscopic techniques, one of which was identified as a unique taxane with 2,20-oxo group.']>>  to "['Represent this title from a paper to retrieve its scientific short abstract', 'Novel taxanes from Taxus yunnanensis']"


Question: Represent this title from a paper to retrieve its scientific short abstract

Question: Dolphin-like propulsive mechanism based on an adjustable Scotch yoke

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This paper addresses the design, construction, and motion control of an adjustable Scotch yoke mechanism generating desired kinematics for dolphin-like robots. Since dolphins propel themselves by dorsoventral oscillations following a sinusoidal path with alterable amplitudes, a two-motor-driven Scotch yoke mechanism is adopted as the primary propulsor to produce sinusoidal oscillations, where a certain combination of a leading screw mechanism and a rack and pinion mechanism driven by the slave motor are incorporated to independently change the length of the crank actuated by the master motor. Meanwhile, the output of the Scotch yoke, i.e., reciprocating motion, is converted into the up-and-down oscillations via a rack and gear transmission. A DSP-based built-in motion control scheme is then brought forth and applied to achieve dolphin-like propulsion. Preliminary tests, in a robotics context, confirm the feasibility of the devised mechanism severing as a dedicated propulsor for bio-inspired movements.

The swimming velocity of fish robots are extremely low in comparison with actual live fishes. To investigate the superior propulsive efficiency of actual fish and find measures to improve the propulsive performance of fish robots, a flexible fish robot was developed. The effects of the flexibility of tail fin on the propulsive force were investigated by using the fish robot and three-dimensional CFD. Consequently, the flexibility of tail fin is very important for fish robots to swim efficiently, because the vortex rings generated from a flexible tail fin is useful to maintain reverse Karman vortices for a long time.


Question: Face detection using convolutional neural networks and gabor filters

This paper proposes a method for detecting facial regions by combining a Gabor filter and a convolutional neural network. The first stage uses the Gabor filter which extracts intrinsic facial features. As a result of this transformation we obtain four subimages. The second stage of the method concerns the application of the convolutional neural network to these four images. The approach presented in this paper yields better classification performance in comparison to the results obtained by the convolutional neural network alone.

Detecting objects in images and videos is a difficult task that has challenged the field of computer vision. Most of the algorithms for object detection are sensitive to background clutter and occlusion, and cannot localize the edge of the object. An objects shape is typically the most discriminative cue for its recognition by humans. This paper introduces a model based object detection method which uses only shape-fragment features. The object shape model is learned from a very small set of training images. And the object model is composed of shape fragments. The model of the object is in multi-scales. The results presented in this paper are competitive with other state-of-the-art object detection methods. The major contributions of this paper are the application of learned shape fragments based model for object detection in complex environment and a novel two-stage object detection framework.


Question: represent this title from a paper to retrieve its scientific short abstract

Question: Discriminative Corpus Weight Estimation for Machine Translation

represent this abstract from a paper to retrieve its scientific title

Examples:

"['Represent this scientific intro in order to find the title of the paper', 'This chapter introduces a series of studies carried out with intermediate learners of Chinese regarding the reading of authentic e-materials with hyperlinked dictionaries. The study results indicate that it is practical to let intermediate students read authentic e-materials when aided by hyperlinked dictionaries, which can improve reading comprehension and vocabulary retention. Guided by the findings from these studies, good practices on how to use authentic e-materials and hyperlinked dictionaries to improve reading skills for intermediate students are introduced. It is recommended that in order to achieve optimal results when using technology, instructors need to employ systematic strategies to support and guide students in the reading process.']" == "['Represent the title for retrieving the corresponding scientific abstract', 'Electronic Strategies to Improve Chinese Reading Skills']"

Current statistical machine translation (SMT) systems are trained on sentence-aligned and word-aligned parallel text collected from various sources. Translation model parameters are estimated from the word alignments, and the quality of the translations on a given test set depends on the parameter estimates. There are at least two factors affecting the parameter estimation: domain match and training data quality. This paper describes a novel approach for automatically detecting and down-weighing certain parts of the training corpus by assigning a weight to each sentence in the training bitext so as to optimize a discriminative objective function on a designated tuning set. This way, the proposed method can limit the negative effects of low quality training data, and can adapt the translation model to the domain of interest. It is shown that such discriminative corpus weights can provide significant improvements in Arabic-English translation on various conditions, using a state-of-the-art SMT system.

represent the abstract for retrieving the scientific paper title.

Papers on: Genetic Algorithms, Connectionist Models, Case-Based Reasoning, Information Retrieval, Learning, Robotics, Planning and Scheduling, Natural Language Processing and Cognitive Linguistics.


Question: Represent this paper title in order to find a scientific intro to what it is about

Question: Macro Grammars and Holistic Triggering for Efficient Semantic Parsing

To learn a semantic parser from denotations, a learning algorithm must search over a combinatorially large space of logical forms for ones consistent with the annotated denotations. We propose a new online learning algorithm that searches faster as training progresses. The two key ideas are using macro grammars to cache the abstract patterns of useful logical forms found thus far, and holistic triggering to efficiently retrieve the most relevant patterns based on sentence similarity. On the WikiTableQuestions dataset, we first expand the search space of an existing model to improve the state-of-the-art accuracy from 38.7% to 42.7%, and then use macro grammars and holistic triggering to achieve an 11x speedup and an accuracy of 43.7%.

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Foundations of Semantic Web Reasoning.- Composing Frameworks and Components for Families of Semantic Web Applications.- Semantic Web Logic Programming Tools.- Web Rules Need Two Kinds of Negation.- Reasoning in Practice.- Towards the Adaptive Semantic Web.- On Reasoning on Time and Location on the Web.- Reasoning about Communicating Agents in the Semantic Web.- Query and Rule-Languages.- A Visual Language for Web Querying and Reasoning.- XML Document Adaptation Queries (XDAQ): An Approach to Adaptation Reasoning Using Web Query Languages.- On Types for XML Query Language Xcerpt.- Integrating Description Logics and Answer Set Programming.- Semantics and Knowledge Representation.- Extracting Mathematical Semantics from Documents.- Reasoning in Attempto Controlled English.- Systematics and Architecture for a Resource Representing Knowledge about Named Entities.


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Question: Toward a Comprehension Challenge, Using Crowdsourcing as a Tool

Human readers comprehend vastly more, and in vastly different ways, than any existing comprehension test would suggest. An ideal comprehension test for a story should cover the full range of questions and answers that humans would expect other humans to reasonably learn or infer from a given story. As a step toward these goals we propose a novel test, the Crowdsourced Comprehension Challenge (C3), which is constructed by repeated runs of a three-person game, the Iterative Crowdsourced Comprehension Game (ICCG). ICCG uses structured crowdsourcing to comprehensively generate relevant questions and supported answers for arbitrary stories, whether fiction or nonfiction, presented across a variety of media such as videos, podcasts, and still images.

Contents: Preface. Part I: Complexity Thinking. What Is "Complexity"? What Is "Science"? The Shape of Complexity. The Network of Complexity. Part II: Complexity Thinking, Education, and Educational Inquiry. Descriptive Complexity Research: Qualities of Learning Systems. Descriptive Complexity Research: Level-Jumping. Pragmatic Complexity Research: Conditions of Emergence. Complexity and Education: Vital Simultaneities. Endnotes.


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Question: Developing a human-centric agricultural model in the IoT environment

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The prevalent state of agriculture, especially in developing countries, is not efficient and organized enough to address the growing demand for food, a direct result of the increasing human population. Internet of things and cloud computing together have provided a promising opportunity to resolve the challenges posed by this increasing demand worldwide. By employing IoT and cloud services, and through precision farming tactics, the efficiency and quality of agricultural production, storage and transportation can be tremendously improved. In this paper, we present the architecture of a multilayered enabling platform for incorporating IoT technologies in the agricultural sector. This work makes important contributions by proposing a feasible human-centric IoT model for agriculture with special emphasis on developing nations.

Urban strategy, masterplan and building design for a revitalisation of the manufacturing industry in Chicago in times of transition towards advanced manufacturing.


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Question: K-means Algorithm Based on Particle Swarm Optimization Algorithm for Anomaly Intrusion Detection

K-means as a clustering algorithm has been studied in intrusion detection. However, with the deficiency of global search ability it is not satisfactory. Particle swarm optimization (PSO) is one of the evolutionary computation techniques based on swarm intelligence, which has high global search ability. So K-means algorithm based on PSO (PSO-KM) is proposed in this paper. Experiment over network connection records from KDD CUP 1999 data set was implemented to evaluate the proposed method. A Bayesian classifier was trained to select some fields in the data set. The experimental results clearly showed the outstanding performance of the proposed method.

A. Filippidis, M. Russo, L.C. Jain: Novel Extension of ART2 in Surface Landmine Detection.- M. Blume: An Efficient Mapping of Fuzzy ART onto a Neural Architecture.- M. Blume, D.A. Van Blerkom: Fuzzy ARTMAP Modifications for Intersecting Class Distributions.- A.-H. Tan: Supervised Adaptive Resonance Theory and Rules.- G. Bartfai, R. White: Incremental Learning and Optimization of Hierarchical Clusterings with ART-Based Modular Networks.- C.P. Lim, R.F. Harrison: ART-Based Autonomous Learning Systems: Part I - Architectures and Algorithms.- C.P. Lim, R.F. Harrison: ART-Based Autonomous Learning Systems: Part II - Applications.- T. Serrano-Gotarredona, B. Linares-Barranco: Adaptive Resonance Theory Microchips.


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Question: MetaCluster 4.0: A Novel Binning Algorithm for NGS Reads and Huge Number of Species

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E.g. ['Represent this scientific intro in order to find the title of the paper', 'A novel adsorbent with a diglycol amic acid frame has been synthesized for the recovery of rare earth elements. The adsorbent has the ability to selectively adsorb rare earth metal ions from soluti...'] == ['Represent this title from a paper to retrieve its scientific short abstract', 'Immobilization of Diglycol Amic Acid on Silica Gel for Selective Recovery of Rare Earth Elements']

Abstract Next-generation sequencing (NGS) technologies allow the sequencing of microbial communities directly from the environment without prior culturing. The output of environmental DNA sequencing consists of many reads from genomes of different unknown species, making the clustering together reads from the same (or similar) species (also known as binning) a crucial step. The difficulties of the binning problem are due to the following four factors: (1) the lack of reference genomes; (2) uneven abundance ratio of species; (3) short NGS reads; and (4) a large number of species (can be more than a hundred). None of the existing binning tools can handle all four factors. No tools, including both AbundanceBin and MetaCluster 3.0, have demonstrated reasonable performance on a sample with more than 20 species. In this article, we introduce MetaCluster 4.0, an unsupervised binning algorithm that can accurately (with about 80% precision and sensitivity in all cases and at least 90% in some cases) and efficientl...

These invited talks discuss the following: STG Decomposition and Its Correctness; Asynchronous Network-On-Chip and its Potential.


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Question: Sequences, Items And Latent Links: Recommendation With Consumed Item Packs

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Recommenders personalize the web content by typically using collaborative filtering to relate users (or items) based on explicit feedback, e.g., ratings. The difficulty of collecting this feedback has recently motivated to consider implicit feedback (e.g., item consumption along with the corresponding time). ::: In this paper, we introduce the notion of consumed item pack (CIP) which enables to link users (or items) based on their implicit analogous consumption behavior. Our proposal is generic, and we show that it captures three novel implicit recommenders: a user-based (CIP-U), an item-based (CIP-I), and a word embedding-based (DEEPCIP), as well as a state-of-the-art technique using implicit feedback (FISM). We show that our recommenders handle incremental updates incorporating freshly consumed items. We demonstrate that all three recommenders provide a recommendation quality that is competitive with state-of-the-art ones, including one incorporating both explicit and implicit feedback.

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Question: 3D Reconstruction of Temples in the Special Region of Yogyakarta By Using Close-Range Photogrammetry

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Object reconstruction is one of the main problems in cultural heritage preservation. This problem is due to lack of data in documentation. Thus in this research we presented a method of 3D reconstruction using close-range photogrammetry. We collected 1319 photos from five temples in Yogyakarta. Using A-KAZE algorithm, keypoints of each image were obtained. Then we employed LIOP to create feature descriptor from it. After performing feature matching, L1RA was utilized to create sparse point clouds. In order to generate the geometry shape, MVS was used. Finally, FSSR and Large Scale Texturing were employed to deal with the surface and texture of the object. The quality of the reconstructed 3D model was measured by comparing the 3D images of the model with the original photos utilizing SSIM. The results showed that in terms of quality, our method was on par with other commercial method such as PhotoModeler and PhotoScan.

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Introduction Overview, R.R. Hoffman and A.B. Markman Angels of Regard: Psychology Meets Technology in the Perception and Interpretation of Non-literal Imagery, R.R. Hoffman and A.B. Markman The Communication of Topographic Perspectives and Forms Human Factors in the Interpretation of Physiology by Symbolic and Numerical Representations within an Expert System, D.P. Argialas and G. Ch. Miliaresis Scenes into Numbers: Facing the Subjective in Landform Quantification, R.J. Pike Seeing the Invisible On the Psychophysics of Night Vision Goggles, W.R. Uttal and R.W. Gibb Human Perception of Sensor-Fused Imagery, E.A. Essock Seeing the Dynamics Components of Expertise in the Perception and Interpretation of Meteorlogical Charts, R.L. Lowe The Role of Remote Sensing Displays in Planetary Atmospheric Research, A.D. Del Genio The Skilled Interpretation of Weather Satellite Images: Learning to See Patterns and Not Just Cues, H.M. Mogil


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"['Represent this text!', 'Gas Sensor MEMS Platform for Harsh Conditions']" == "['Represent this scientific intro in order to find the title of the paper', 'We present a novel approach to the fabrication of MEMS devices, which can be used for gas sensors operating in harsh environment in wireless and autonomous information systems. MEMS platforms based on ZrO2/Y2O3 (YSZ) and alumina membranes are applied in these devices. The methods of fabrication of these ceramic MEMS devices are considered. It is shown that the application of such membranes permits a decrease in MEMS power consumption at 450 0 C down to ~75 mW at continuous heating and down to ~ 1 mW at pulse heating of gas sensor. The application of the platforms is not restricted by gas sensors: they can be used for fast thermometers, bolometric matrices, flowmeteres and other MEMS devices working under harsh environmental conditions.']" != "['Represent the abstract for retrieving the scientific paper title', 'Abstract : Partial contents:Problem Statement, Technical Objective, Technical Background Current Coatings, Technical Background, Technical Background - Polysiloxane, Technical Background - Polyuretidione, Technical Background Cyclic Carbonate, Technical Approach, Task 1 Benchmarking, Task 2 Initial Formulation Development, Task 3 Initial CARC Testing, Task 4 Targeted Development, Chemspeed Autoplant A100TM, Task 5 Formulation CARC Testing, Task 6 Optimization, Task 8 Transition Planning, Year 1 Project Plan, Overall Project Plan, Project Funding, Deliverables.']"

Question: Automatic Composition of Semantic Web Services Based on Fuzzy Predicate Petri Nets

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Web service composition is a challenging research issue. This paper presents an automatic Web service composition method that deals with both input/output compatibility and behavioral constraint compatibility of fuzzy semantic services. First, user input and output requirements are modeled as a set of facts and a goal statement in the Horn clauses, respectively. A service composition problem is transformed into a Horn clause logic reasoning problem. Next, a Fuzzy Predicate Petri Net (FPPN) is applied to model the Horn clause set, and T-invariant technique is used to determine the existence of composite services fulfilling the user input/output requirements. Then, two algorithms are presented to obtain the composite service satisfying behavioral constraints, as well as to construct an FPPN model that shows the calling order of the selected services.

Argument-Based Reasoning.- Personality-Based Practical Reasoning.- Argumentation Based Resolution of Conflicts between Desires and Normative Goals.- A Constrained Argumentation System for Practical Reasoning.- An Argumentation Framework Based on Strength for Ontology Mapping.- Contextual Extension with Concept Maps in the Argument Interchange Format.- Argumentation and Dialogue.- Command Dialogues.- Argumentation and Artifact for Dialogue Support.- Co-ordination and Co-operation in Agent Systems: Social Laws and Argumentation.- Annotation and Matching of First-Class Agent Interaction Protocols.- Strategic and Pragmatic Issues.- Argumentation- vs. Proposal-Based Negotiation: An Empirical Case Study on the Basis of Game-Theoretic Solution Concepts.- Argumentation-Based Information Exchange in Prediction Markets.- An Argumentative Approach for Modelling Coalitions Using ATL.- A Dialogue Mechanism for Public Argumentation Using Conversation Policies.


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Question: Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus

This paper presents the first empirical results to our knowledge on learning synchronous grammars that generate logical forms. Using statistical machine translation techniques, a semantic parser based on a synchronous context-free grammar augmented with �operators is learned given a set of training sentences and their correct logical forms. The resulting parser is shown to be the bestperforming system so far in a database query domain.


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Question: Towards Robustness for Cyber-Physical Systems

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While the importance of robustness in engineering design is well accepted, it is less clear how to design cyber-physical systems (CPS) for robustness. With the objective of developing a robustness theory for CPS, we introduce a notion of robustness for cyber systems inspired by existing notions of input-output stability in control theory. We show that the proposed notion of robustness captures two intuitive goals: bounded disturbances lead to bounded deviations from nominal behavior, and the effect of a sporadic disturbance disappears in finitely many steps. For cyber systems modeled as finite-state transducers, the proposed notion of robustness can be verified in pseudo-polynomial time. The synthesis problem, consisting of designing a controller enforcing robustness, can also be solved in pseudo-polynomial time.

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Part 1: Application Mapping and Communication Infrastructure: Virtualization in NOCs--Enhanced MPSOC Robustness and Performance Verification.-HW Support to Exploit Parallelism in Homogeneous and Heterogeneous Multicore System-on-Chip.-PALLAS: Mapping Applications onto Manycore.-Part 2: Reconfigurable Hardware in Multiprocessor Systems: Adaptive Multiprocessor System on Chip Architecture.-Designing FPGA Systems with Many Processors.-Part 3: Physical Design of Multiprocessor Systems: Design tools and methods for chip physical design.-Challenges in Physical Design for Multi- and Manycore Hardware Architectures.


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Question: Mesh editing with poisson-based gradient field manipulation

In this paper, we introduce a novel approach to mesh editing with the Poisson equation as the theoretical foundation. The most distinctive feature of this approach is that it modifies the original mesh geometry implicitly through gradient field manipulation. Our approach can produce desirable and pleasing results for both global and local editing operations, such as deformation, object merging, and smoothing. With the help from a few novel interactive tools, these operations can be performed conveniently with a small amount of user interaction. Our technique has three key components, a basic mesh solver based on the Poisson equation, a gradient field manipulation scheme using local transforms, and a generalized boundary condition representation based on local frames. Experimental results indicate that our framework can outperform previous related mesh editing techniques.

Parameters-based voxelization of NURBS volumes and their Boolean operation such as union,intersection and difference are discussed mainly.Thisis anew kind of voxelization algorithm which can more exactlyexpress the volume.The methods forconstruction of NURBS volumes include skinning,sweeping and swinging etc.


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Question: Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

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Few-shot learning is challenging for learning algorithms that learn each task in isolation and from scratch. In contrast, meta-learning learns from many related tasks a meta-learner that can learn a new task more accurately and faster with fewer examples, where the choice of meta-learners is crucial. In this paper, we develop Meta-SGD, an SGD-like, easily trainable meta-learner that can initialize and adapt any differentiable learner in just one step, on both supervised learning and reinforcement learning. Compared to the popular meta-learner LSTM, Meta-SGD is conceptually simpler, easier to implement, and can be learned more efficiently. Compared to the latest meta-learner MAML, Meta-SGD has a much higher capacity by learning to learn not just the learner initialization, but also the learner update direction and learning rate, all in a single meta-learning process. Meta-SGD shows highly competitive performance for few-shot learning on regression, classification, and reinforcement learning.

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This chapter contains sections titled: Introduction System Description and Problem Formulation Sequential Monte Carlo Methods Joint Single-Target Tracking and Classification Multiple-Target Tracking and Classification Sensor Selection Simulation Results Conclusion Appendix: Derivations of (14.38) and (14.40) References


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Question: X-LiSA: Cross-lingual Semantic Annotation

The ever-increasing quantities of structured knowledge on the Web and the impending need of multilinguality and cross-linguality for information access pose new challenges but at the same time open up new opportunities for knowledge extraction research. In this regard, cross-lingual semantic annotation has emerged as a topic of major interest and it is essential to build tools that can link words and phrases in unstructured text in one language to resources in structured knowledge bases in any other language. In this paper, we demonstrate X-LiSA, an infrastructure for cross-lingual semantic annotation, which supports both service-oriented and user-oriented interfaces for annotating text documents and web pages in different languages using resources from Wikipedia and Linked Open Data (LOD).


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Question: Real Time Image Saliency for Black Box Classifiers

In this work we develop a fast saliency detection method that can be applied to any differentiable image classifier. We train a masking model to manipulate the scores of the classifier by masking salient parts of the input image. Our model generalises well to unseen images and requires a single forward pass to perform saliency detection, therefore suitable for use in real-time systems. We test our approach on CIFAR-10 and ImageNet datasets and show that the produced saliency maps are easily interpretable, sharp, and free of artifacts. We suggest a new metric for saliency and test our method on the ImageNet object localisation task. We achieve results outperforming other weakly supervised methods.

Images, Windows and Operators. Methodical Fundamentals. Algorithmic Fundamentals. Coordinate Transformations and Geometrical Operators. Gray Scale Transformations and Point Operators. Window Functions and Local Operators. Global Operators. Glossary. Index.


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Question: Paraphrasing: Generating parallel programs using refactoring

Refactoring is the process of changing the structure of a program without changing its behaviour. Refactoring has so far only really been deployed effectively for sequential programs. However, with the increased availability of multicore (and, soon, manycore) systems, refactoring can play an important role in helping both expert and non-expert parallel programmers structure and implement their parallel programs. This paper describes the design of a new refactoring tool that is aimed at increasing the programmability of parallel systems. To motivate our design, we refactor a number of examples in C, C++ and Erlang into good parallel implementations, using a set of formal pattern rewrite rules.

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Translation validation was introduced as a technique to formally verify the correctness of code generators that attempts to ensure that program transformations preserve the semantics of input program. In this work, we adopt this approach to construct a validator that formally verifies the preservation of clock semantics during the Signal compiler transformations. The clock semantics is represented as a first-order logic formula called clock model. We then introduce a refinement which expresses the preservation of clock semantics, as a relation on clock models. Our validator does not require any instrumentation or modification of the compiler, nor any rewriting of the source program.


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Question: Activity recognition using biomechanical model based pose estimation

represent the abstract for retrieving the scientific paper title
For example, '['Represent the abstract for retrieving the scientific paper title', "You can't always get what you wantYou can't always get what you wantYou can't always get what you wantBut if you try sometimes, you just might findYou get what you needMick Jagger, Keith Richards—1969 ::: ::: Patient satisfaction has become an important metric for hospitals to report. It is used for various hospital ranking platforms such as that published by US News and World Report as well as for good old-fashioned community marketing. Eventually, patient satisfaction may be incorporated into one of the many outcome measures which are being proposed to adjust payment to hospitals. ::: ::: I think striving to improve patient satisfaction is a good idea. However, measuring an ephemeral qualitative impression such as satisfaction can be unreliable, since gratification depends on the perception of the beholder. Additionally, it can …"]' should be close to '['Represent the title for retrieving the corresponding scientific abstract', "You Can't Always Get What You Want"]'

In this paper, a novel activity recognition method based on signal-oriented and model-based features is presented. The model-based features are calculated from shoulder and elbow joint angles and torso orientation, provided by upper-body pose estimation based on a biomechanical body model. The recognition performance of signal-oriented and model-based features is compared within this paper, and the potential of improving recognition accuracy by combining the two approaches is proved: the accuracy increased by 4-6% for certain activities when adding model-based features to the signal-oriented classifier. The presented activity recognition techniques are used for recognizing 9 everyday and fitness activities, and thus can be applied for e.g., fitness applications or 'in vivo' monitoring of patients.

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The growing popularity of tablet PCs and intelligent pen-centric computing have increased the importance of freehand sketch recognition algorithms. This paper shall investigate the use of information fusion technique with Support Vector Machines (SVMs) chain for modeling and understanding the spatial and temporal information of sketch sequences. The approach for sketch recognition lies in the proposed dynamic and probabilistic framework based on combining SVMs-chain by the spatial and geometric features for systematically modeling the dynamic and stochastic behaviors of sketch.


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Question: Slip-compensated path following for planetary exploration rovers

A system that enables continuous slip compensation for a Mars rover has been designed, implemented and field-tested. This system is composed of several components that allow the rover to accurately and continuously follow a designated path, compensate for slippage and reach intended goals in high-slip environments. These components include visual odometry, vehicle kinematics, a Kalman filter pose estimator and a slip-compensated path follower. Visual odometry tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs. The kinematics for a rocker–bogie suspension system estimates vehicle motion by measuring wheel rates, and rocker, bogie and steering angles. The Kalman filter processes measurements from an inertial measurement unit and visual odometry. The filter estimate is then compared to the kinematic estimate to determine whether slippage has occurred, taking into account estimate uncertainties. If slippage is detected, the slip vector...

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Experimental evaluations have demonstrated the effect of dynamic compensation on the trajectory tracking accuracy of industrial manipulators. High gear ratios reduce the compu tational complexity o...


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Question: Towards real-time community detection in large networks

The recent boom of large-scale online social networks (OSNs) both enables and necessitates the use of parallelizable and scalable computational techniques for their analysis. We examine the problem of real-time community detection and a recently proposed linear time- O(m) on a network with m edges-label propagation, or "epidemic" community detection algorithm. We identify characteristics and drawbacks of the algorithm and extend it by incorporating different heuristics to facilitate reliable and multifunctional real-time community detection. With limited computational resources, we employ the algorithm on OSN data with 1 x 10(6) nodes and about 58 x 10(6) directed edges. Experiments and benchmarks reveal that the extended algorithm is not only faster but its community detection accuracy compares favorably over popular modularity-gain optimization algorithms known to suffer from their resolution limits.

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In this chapter learning, evolution and the structural change of multi agent systems are investigated using actual examples of social and economic systems.


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Question: AWARD: Approximation-aWAre Restore in Further Scaling DRAM

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DRAM further scaling becomes more and more challenging, making restore operation an serious issue in the near future. Fortunately, a wide range of modern applications are able to tolerate error or inexactness, providing a new dimension to mitigate the slow-restore issue. And thus, we can trade-off acceptable QoS loss in those applications to accelerate restore operations, and further to achieve performance and energy improvements. In this extended research abstract, we briefly explore DRAM restore-based approximate computing, and present a preliminary evaluation on impacts of quality-of-service (QoS) degradation and performance speedup. We show that restore-based approximate computing is a challenging work, and dedicated error correction/tolerance techniques are needed to balance QoS and performance.

32-bit BUS Abstract- Energy consumption isone ofthemostcritical constraints inthecurrent VLSIsystem designs. Inaddition, fault tolerance ofVLSIsystems isalso oneofthemostimportant re- Processor L ECC/ ECGCLow (SimpleSalar Power EDC EDC Power M m (ipScar Encoder!Encoder! Encoder!Encoder!/ em quirements inthecurrentshrunkVLSI technologies. Thispaper Architecture)Decoder Decoder Decoder Decoder presents lowpowerandfault tolerant busencoding methods considering coupling effects ofbusinterconnects. Experiments using SPEC2000benchmark programs showthattheproposed Aredundant bitExtra code bitAredundant bit methodscaneffectively reducesignal transitions withfault tolerance. Moreover, theresults showthattheoptimization ofbus Fig1 Thearchitecture whichexploits thecombination ofECC.EDC code interconnects pitch canincrease theeffectiveness oftheencodingandlowpower code method. I.INTRODUCTION


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Question: Chabot: Retrieval from a Relational Database of Images

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Selecting from a large, expanding collection of images requires carefully chosen search criteria. We present an approach that integrates a relational database retrieval system with a color analysis technique. The Chabot project was initiated at our university to study storage and retrieval of a vast collection of digitized images. These images are from the State of California Department of Water Resources. The goal was to integrate a relational database retrieval system with content analysis techniques that would give our querying system a better method for handling images. Our simple color analysis method, if used in conjunction with other search criteria, improves our ability to retrieve images efficiently. The best result is obtained when text-based search criteria are combined with content-based criteria and when a coarse granularity is used for content analysis. >

In this research investigation, the author has detailed the Theory Of One Step Universal Evolution Of Any Real Positive Number.


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Question: Aspect identification and sentiment analysis based on NLP

This paper proposes method for aspect identification and sentiment analysis. This paper deals with the problem of sentence level. We use semantic syntax tree to extract NP nodes, a method based on slack to identify aspect and mini-support function to narrow aspect; to analyze the sentiment for the aspect we use dictionary-based method. Experimental results show that the proposed approach achieves the state-of-the-art.

As the demand for global information increases significantly, multilingual corpora has become a valuable linguistic resource for applications to cross-lingual information retrieval and natural language processing. A Web-based English-Chinese bilingual parallel corpus of automatic Construction Technology solved the shortage of bilingual English-Chinese Parallel Corpus. First, some web pages which may be set translation dig of from a particular source, and then from the web pages focused on the external characteristics according to the similarity to extract the candidate web pages in parallel pairs, use of content-based methods on parallel web pages for each of these candidates assessed. In the assessment of the candidate pairs of parallel web pages, this paper design ECVS models of bilingual text similarity assessed based on the classic vector space model.


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Question: Sparse matrix solvers on the GPU: conjugate gradients and multigrid

Many computer graphics applications require high-intensity numerical simulation. We show that such computations can be performed efficiently on the GPU, which we regard as a full function streaming processor with high floating-point performance. We implemented two basic, broadly useful, computational kernels: a sparse matrix conjugate gradient solver and a regular-grid multigrid solver. Real time applications ranging from mesh smoothing and parameterization to fluid solvers and solid mechanics can greatly benefit from these, evidence our example applications of geometric flow and fluid simulation running on NVIDIA's GeForce FX.

The discrete-dipole approximation (DDA) is a method for calculating the scattering of light by an irregular particle. The DDA has been used, for example, in calculations of optical properties of cosmic dust. In this method the particle is approximated by interacting electromagnetic dipoles. Computationally the DDA method includes the solution of large dense systems of linear equations where the coefficient matrix is complex symmetric. In this work, the linear systems of equations are solved by various iterative methods. QMR was found to be the best iterative method in this application. It converged in only a few more iterations than the full generalized minimal residual (GMRES) method. When the discretization of the particle was refined, the number of iterations remained constant even without preconditioning. The matrix–vector product in the iterative methods can be computed with the fast Fourier transform or the fast multipole algorithm. These algorithms make it feasible to solve dense linear systems of ...


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Question: Real-time anomaly detection and localization in crowded scenes

In this paper, we propose a method for real-time anomaly detection and localization in crowded scenes. Each video is defined as a set of non-overlapping cubic patches, and is described using two local and global descriptors. These descriptors capture the video properties from different aspects. By incorporating simple and cost-effective Gaussian classifiers, we can distinguish normal activities and anomalies in videos. The local and global features are based on structure similarity between adjacent patches and the features learned in an unsupervised way, using a sparse auto-encoder. Experimental results show that our algorithm is comparable to a state-of-the-art procedure on UCSD ped2 and UMN benchmarks, but even more time-efficient. The experiments confirm that our system can reliably detect and localize anomalies as soon as they happen in a video.

Wireless sensor networks (WSNs) involve the deployment of small, inexpensive, and limited capability devices to gain information about a given location. This project focuses on intrusion detection in any environment to test the limitations and capabilities of WSNs. Specifically, the goal is to detect any intrusive behavior with a limited number of human resources. The capstone team developed a simulation testbed program using C# to duplicate real life surveillance scenarios. The simulation technique can be applied in a variety of settings including agricultural monitoring, disaster relief, public utilities, security surveillance (commercial and private), traffic control, and military operations. The overall motivation behind designing this project involved reducing the number of personnel needed to monitor any given area and gain intelligent information to make informed decisions.


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Question: A ZVS Pulsewidth Modulation Full-Bridge Converter With a Low-RMS-Current Resonant Auxiliary Circuit

This paper presents the description and analysis of a phase-shift-modulated full-bridge converter with a novel robust passive low-rms-current resonant auxiliary circuit for zero-voltage switching (ZVS) operation of both the leading and lagging switch legs. Detailed time-domain analysis describes the steady-state behavior of the auxiliary circuit in different operating conditions. An in-depth comparative study between a fully specified baseline converter and the equivalent converter using the proposed resonant auxiliary circuit is presented. For a similar peak auxiliary current to ensure ZVS operation, a minimum of 20% reduction in rms current is obtained, which decreases the conduction losses. Key characteristics and design considerations are also fully discussed. Experimental results from a 750-W prototype confirm the predicted enhancements using the proposed resonant auxiliary circuit.

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List of Figures. List of Tables. Preface. 1. Introduction. 2. Basic Transmission Line Theory. 3. Evaluating the Transient Response of Linear Networks. 4. Mosfet Current-Voltage Characteristics. 5. Figures of Merit to Characterize the Importance of on-Chip Inductance in Single Lines. 6. Effects of Inductance on the Propagation Delay and Repeater Insertion Process in RLC Lines. 7. Equivalent Elmore Delay for RLC Trees. 8. Characterizing Inductance Effects in RLC Trees. 9. Repeater Insertion in Tree Structured Inductive Interconnect. 10. Dynamic and Short-Circuit Power of CMOS Gates Driving Lossless Transmission Lines. 11. Exploiting On-Chip Inductance in High Speed Clock Distribution Networks. 12. Accurate and Efficient Evaluation of the Transient Response in RLC Circuits: The DTT Method. 13. On the Extraction of On-Chip Inductance. 14. Conclusions. Bibliography. Appendices. Index. About the Authors.


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Question: Automatic reconstruction of personalized avatars from 3D face scans

We present a simple algorithm for computing a high-quality personalized avatar from a single color image and the corresponding depth map which have been captured by Microsoft's Kinect sensor. Due to the low market price of our hardware setup, 3D face scanning becomes feasible for home use. The proposed algorithm combines the advantages of robust non-rigid registration and fitting of a morphable face model. We obtain a high-quality reconstruction of the facial geometry and texture along with one-to-one correspondences with our generic face model. This representation allows for a wide range of further applications such as facial animation or manipulation. Our algorithm has proven to be very robust. Since it does not require any user interaction, even non-expert users can easily create their own personalized avatars. Copyright © 2011 John Wiley & Sons, Ltd.

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A maximum a posterior probability zero disparity filter (MAP ZDF) ensures coordinated stereo fixation upon an arbitrarily moving, rotating, re-configuring hand, performing marker-less pixel-wise segmentation of the hand. Active stereo fixation permits real-time foveal hand tracking and segmentation over a large visual workspace, allowing investigation of unrestricted natural human gesturing. Hand segmentation is shown to be robust to lighting conditions, defocus, hand colour variation, foreground and background clutter including non-tracked hands, and partial or gross occlusions including those due to non-tracked hands. The system operates at approximately 27fps on a 3GHz single processor PC.


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Question: Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

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The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos. Existing studies have adopted strategies of sliding window over the entire video or exhaustively ranking all possible clip-sentence pairs in a pre-segmented video, which inevitably suffer from exhaustively enumerated candidates. To alleviate this problem, we formulate this task as a problem of sequential decision making by learning an agent which regulates the temporal grounding boundaries progressively based on its policy. Specifically, we propose a reinforcement learning based framework improved by multi-task learning and it shows steady performance gains by considering additional supervised boundary information during training. Our proposed framework achieves state-of-the-art performance on ActivityNet'18 DenseCaption dataset and Charades-STA dataset while observing only 10 or less clips per video.

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Contents: The Information Society - The Digital Divide - The Digital Practice Perspective - The Digital Practice of Weak Tie Development - The Digital Practice of Maintaining Family Ties via Mobile Phone - The Digital Practice of Maintaining Digital Enclaves - The Digital Practice Perspective and Social Policy: Improving the Social, Cultural, and Civic Quality of the Digital Environment - Conclusion: Smart Mobs, Flash Mobs, Flash Robs and the Revolutionary Potential of the Digital Environment.


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Question: A new collaborative filtering algorithm using K-means clustering and neighbors' voting

The Collaborative Filtering is the most successful algorithm in the recommender systems' field. A recommender system is an intelligent system can help users to come across interesting items. It uses data mining and information filtering techniques. The collaborative filtering creates suggestions for users based on their neighbors' preferences. But it suffers from its poor accuracy and scalability. This paper considers the users are m (m is the number of users) points in n dimensional space (n is the number of items) and represents an approach based on user clustering to produce a recommendation for active user by a new method. It uses k-means clustering algorithm to categorize users based on their interests. Then it uses a new method called voting algorithm to develop a recommendation. We evaluate the traditional collaborative filtering and the new one to compare them. Our results show the proposed algorithm is more accurate than the traditional one, besides it is less time consuming than it.

We propose an approach to embed time series data in a vector space based on the distances obtained from Dynamic Time Warping (DTW), and to classify them in the embedded space. Under the problem setting in which both labeled data and unlabeled data are given beforehand, we consider three embeddings, embedding in a Euclidean space by MDS, embedding in a Pseudo-Euclidean space, and embedding in a Euclidean space by the Laplacian eigenmap technique. ::: ::: We have found through analysis and experiment that the embedding by the Laplacian eigenmap method leads to the best classification result. Furthermore, the proposed approach with Laplacian eigenmap embedding shows better performance than k-nearest neighbor method.


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Question: Fusion of radar, LiDAR and thermal information for hazard detection in low visibility environments

Nowadays, mobile robots are widely used to support fire brigades in search and rescue missions. The utilization of those robots - especially under low visibility conditions due to smoke, fog or dust - is limited. Under these circumstances, environmental perception is still a huge challenge. In this work, we present an approach on using LiDAR, radar and thermal imaging in order to detect hazards that are potentially harmful to the robot or firefighters. We show the benefits of fusing LiDAR and radar before projecting temperatures recorded with a thermal imaging camera onto the range scans. Additionally, a hotspot detection method using the tempered range scans is presented. We demonstrate the functionality of our approach by teleoperating a robot through a smoky room.

Purpose of Review ::: The rapid development of remote sensing technology has made dense 3D data available from airborne laser scanning and recently also photogrammetric point clouds. This paper reviews methods for extraction of individual trees from 3D data and their applications in forestry and ecology.


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Question: Cannabidiol (CBD) as an Adjunctive Therapy in Schizophrenia: A Multicenter Randomized Controlled Trial

Objective:Research in both animals and humans indicates that cannabidiol (CBD) has antipsychotic properties. The authors assessed the safety and effectiveness of CBD in patients with schizophrenia.Method:In an exploratory double-blind parallel-group trial, patients with schizophrenia were randomized in a 1:1 ratio to receive CBD (1000 mg/day; N=43) or placebo (N=45) alongside their existing antipsychotic medication. Participants were assessed before and after treatment using the Positive and Negative Syndrome Scale (PANSS), the Brief Assessment of Cognition in Schizophrenia (BACS), the Global Assessment of Functioning scale (GAF), and the improvement and severity scales of the Clinical Global Impressions Scale (CGI-I and CGI-S).Results:After 6 weeks of treatment, compared with the placebo group, the CBD group had lower levels of positive psychotic symptoms (PANSS: treatment difference=−1.4, 95% CI=−2.5, −0.2) and were more likely to have been rated as improved (CGI-I: treatment difference=−0.5, 95% CI=−0....

Progress in Alzheimer's Disease. Etiology and Pathogenesis of Alzheimer's Disease. Familial Alzheimer's Disease and Biology of Presenilins. Animal Models of Alzheimer's Disease. Glycosaminoglycans (GAGs) in Alzheimer's Disease. Clinical Evaluation of Alzheimer's Disease. Progress in the Treatment of Alzheimer's Disease. Novel Drug Treatment of Alzheimer's Disease: Beyond Cholinesterase Inhibitors. New Treatment on the Horizon in Alzheimer's Disease. Progress in Parkinson's Disease. Etiology and Pathogenesis. Familial Parkinson's Disease. Clinical Topics in Parkinson's Disease. Progress in the Treatment of Parkinson's Disease. Dopamine Agonists. Mechanism and Treatment of Motor Complications. Treatment of Depression and Cognitive Dysfunction in Parkinson's Disease. Surgical Treatment of Parkinson's Disease. New Treatment on the Horizon in Parkinson's Disease. Dementia With Lewy Bodies. Familial Frontotemporal Dementia and Related Disorders.


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The provided query could be '['Represent the title for retrieving the corresponding scientific abstract', 'Ozone generation by micro-plasma devices: Feasibility study']' and the positive '['', 'Feasibility use of microplasma for ozone production has been investigated. Two different configurations of microplasma devices have been considered: atmospheric pressure micro-hollow discharge (MHD) and capillary plasma electrode discharge (CPED). Modelling of ozone formation and input energy distribution in microplasma devices have been performed and evaluated. Preliminary experiments confirm suggestion that microplasma devices may be used for improving the ozone concentration (g/Nm) and ozone yield (g/kWh) in pure oxygen and dry air, respectively.']' and the negative '['Represent this abstract from a paper to retrieve its scientific title', 'A review with 6 refs. The topics include plasma formation and characterization, mol. processes, plasma deposition, and plasma-activated catalysis.']'

Question: Automatic Chessboard Detection for Intrinsic and Extrinsic Camera Parameter Calibration

There are increasing applications that require precise calibration of cameras to perform accurate measurements on objects located within images, and an automatic algorithm would reduce this time consuming calibration procedure. The method proposed in this article uses a pattern similar to that of a chess board, which is found automatically in each image, when no information regarding the number of rows or columns is supplied to aid its detection. This is carried out by means of a combined analysis of two Hough transforms, image corners and invariant properties of the perspective transformation. Comparative analysis with more commonly used algorithms demonstrate the viability of the algorithm proposed, as a valuable tool for camera calibration.

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Images, Windows and Operators. Methodical Fundamentals. Algorithmic Fundamentals. Coordinate Transformations and Geometrical Operators. Gray Scale Transformations and Point Operators. Window Functions and Local Operators. Global Operators. Glossary. Index.


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Question: Integer programming formulations for the elementary shortest path problem

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Given a directed graph G=(V,A) with arbitrary arc costs, the Elementary Shortest Path Problem (ESPP) consists of finding a minimum-cost path between two nodes s and t such that each node of G is visited at most once. If negative costs are allowed, the problem is NP-hard. In this paper, several integer programming formulations for the ESPP are compared. We present analytical results based on a polyhedral study of the formulations, and computational experiments where we compare their linear programming relaxation bounds and their behavior within a branch-and-cut framework. The computational results show that a formulation with dynamically generated cutset inequalities is the most effective.

Two of the most challenging problems in network design are the Quadratic Assignment Problem (QAP) and the Steiner network problem. One of the key objectives of this paper is to show the strong link between these two network design problems. Dynamic flows in QAPs are modelled as stochastic processes. The underlying flow topology is represented as a Steiner tree queueing network topology. Customers and goods flow over tandem links of the Steiner network. A heuristic for the Stochastic Quadratic Assignment Problem SQAP is developed for solving this flow network topology problem and computational experience is presented.


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Question: A new fingerprint matching approach using level 2 and level 3 features

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Fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, Level 1 (pattern), Level 2 (minutiae points) and Level 3 (pores and ridge shape). Although high resolution sensors (~ 1000dpi) have become commercially available and have made it possible to reliably extract Level 3 features, most Automated Fingerprint Identification Systems (AFIS) employ only Level 1 and Level 2 features. As a result, increasing the scan resolution does not provide any matching performance improvement. We develop a matcher that utilizes Level 3 features, including pores and ridge contours, in conjunction with level 2 features (minutiae) for matching. The aim is to reduce the error rates, namely FAR (False Acceptance Rate) and FRR (False Rejection Rate) in the existing minutiae based systems. The hierarchical matcher has been tested on two diverse databases in public domain. The obtained results are promising and verify our claim.

The paper proposes two complementary methods for change analysis and feature extraction: A time evolution analysis of satellite images and using the correlation coefficient together with conditional information.


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Question: A brief survey of blackhole detection and avoidance for ZRP protocol in MANETs

Within Mobile Ad-Hoc Network(MANETs) unusual categories of routing protocols have been determined. It is a group of wireless system. MANET is other susceptible to a variety of attack than wired system. Black hole attack is further meticulous intimidation to MANETs. The routing protocols of MANET is less protected and therefore consequenced the system with malicious node. There are various routing protocols being used for MANETs. All routing protocols have been briefly discussed, however, Zone Routing Protocol (ZRP) is discussed in detail. Black hole is a major security threat for MANETs. Hence, in this paper, the various techniques used for detection and avoidance of Black hole attack in MANETs using ZRP routing protocol have been discussed.

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Without any infrastructure MANETs need to utilize the broadcast or multicast modes to transfer efficiently packets between wireless nodes. However, broadcast may easily cause a broadcast storm in the wireless networks, which will lead to network congestion and make the normal packets cannot be transferred. This paper tries to combine the advantages of location-aware distributed cluster algorithm and MAOVD schemes to improve the transmission efficiency and the throughput of MANET in geographic routing protocols. We also identify the problems in broadcast storm and bandwidth wasting problems that could be improved by using the design of our LDCA routing protocol for wireless ad-hoc networks. —Mobile ad-hoc networks, MANET, MAODV, multicast.


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Question: Preliminary investigations of an inductive power transfer system for the rotor power supply of an electric traction drive

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To give you a sense - "['Represent the abstract for retrieving the scientific paper title', 'We probe the energy landscape of the 3D Edwards-Anderson spin glass in a magnetic field to test for a spin glass ordering. We find that the spin glass susceptibility is anomalously large on the lattice sizes we can reach. Our data suggest that a transition from the spin glass to the paramagnetic phase takes place at B(c) approximately 0.65, though the possibility B(c) = 0 cannot be excluded. We also discuss the question of the nature of the putative frozen phase.']" should be close to "['Represent this title from a paper to retrieve its scientific short abstract', 'Zero-temperature responses of a 3D spin glass in a magnetic field.']"

The paper is devoted to the substitution of slip rings through an inductive power transfer system (IPT) for field winding supply in wound rotor traction drives. By an inductively coupled rotational transformer, the rotor-side energizing of the excitation windings can be provided isolated and free of wear. For preliminary investigations, an analytical model of the inductive link and the compensation network has been set up. Based on this, possible types of compensation networks regarding an optimal integration into an electric traction drive were carried out and compared among themselves by parameter studies. Using an experimental prototype system and on the basis of accompanying FEM calculations, the analytical model has been validated and the system tested both stationary and transient.

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Abstract : Test and development activities were conducted in the following nine areas: (1) Evaluation of a breadboard multiplexing system driving a fly-by-wire actuator; (2) Evaluate actuation system of six-degree of freedom motion base; (3) Evaluation of general purpose actuator test stand;; (4) Various design concepts were explored for the improvement of branch isolation techniques; (5) Evaluation of a Vickers Inc. integrated servopump actuator package; (6) Investigation of limit cycle characteristics of a General Electric 666A actuator; (7) Literature search and recommendation for a laboratory contamination measurement system choice; (8) Fabrication of a portable flow measurement stand and (9) Design and fabrication of a transducer range and balance panel.


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Question: Hierarchical power management for asymmetric multi-core in dark silicon era

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Asymmetric multi-core architectures integrating cores with diverse power-performance characteristics is emerging as a promising alternative in the dark silicon era where only a fraction of the cores on chip can be powered on due to thermal limits. We introduce a hierarchical power management framework for asymmetric multi-cores that builds on control theory and coordinates multiple controllers in a synergistic manner to achieve optimal power-performance efficiency while respecting the thermal design power budget. We integrate our framework within Linux and implement/evaluate it on real ARM big.LITTLE asymmetric multi-core platform.

We prototyped a dynamically adaptable hybrid electronic/optical interconnect using commodity switches and measured its reconfiguration delay. By reconfiguring the network at runtime to avoid congestion we accelerated the execution of parallel workloads in a real testbed.