query: Double ErrP Detection for Automatic Error Correction in an ERP-Based BCI Speller

positive: Error-Related EEG Potentials Generated During Simulated Brain–Computer Interaction Brain-computer interfaces (BCIs) are prone to errors in the recognition of subject's intent. An elegant approach to improve the accuracy of BCIs consists in a verification procedure directly based on the presence of error-related potentials (ErrP) in the electroencephalogram (EEG) recorded right after the occurrence of an error. Several studies show the presence of ErrP in typical choice reaction tasks. However, in the context of a BCI, the central question is: ldquoAre ErrP also elicited when the error is made by the interface during the recognition of the subject's intent?rdquo We have thus explored whether ErrP also follow a feedback indicating incorrect responses of the simulated BCI interface. Five healthy volunteer subjects participated in a new human-robot interaction experiment, which seem to confirm the previously reported presence of a new kind of ErrP. However, in order to exploit these ErrP, we need to detect them in each single trial using a short window following the feedback associated to the response of the BCI. We have achieved an average recognition rate of correct and erroneous single trials of 83.5% and 79.2%, respectively, using a classifier built with data recorded up to three months earlier.

positive: ERP components on reaction errors and their functional significance: a tutorial Some years ago we described a negative (Ne) and a later positive (Pe) deflection in the event-related brain potentials (ERPs) of incorrect choice reactions [Falkenstein, M., Hohnsbein, J., Hoormann, J., Blanke, L., 1990. In: Brunia, C.H.M., Gaillard, A.W.K., Kok, A. (Eds.), Psychophysiological Brain Research. Tilburg Univesity Press, Tilburg, pp. 192-195. Falkenstein, M., Hohnsbein, J., Hoormann, J., 1991. Electroencephalography and Clinical Neurophysiology, 78, 447-455]. Originally we assumed the Ne to represent a correlate of error detection in the sense of a mismatch signal when representations of the actual response and the required response are compared. This hypothesis was supported by the results of a variety of experiments from our own laboratory and that of Coles [Gehring, W. J., Goss, B., Coles, M.G.H., Meyer, D.E., Donchin, E., 1993. Psychological Science 4, 385-390. Bernstein, P.S., Scheffers, M.K., Coles, M.G.H., 1995. Journal of Experimental Psychology: Human Perception and Performance 21, 1312-1322. Scheffers, M.K., Coles, M. G.H., Bernstein, P., Gehring, W.J., Donchin, E., 1996. Psychophysiology 33, 42-54]. However, new data from our laboratory and that of Vidal et al. [Vidal, F., Hasbroucq, T., Bonnet, M., 1999. Biological Psychology, 2000] revealed a small negativity similar to the Ne also after correct responses. Since the above mentioned comparison process is also required after correct responses it is conceivable that the Ne reflects this comparison process itself rather than its outcome. As to the Pe, our results suggest that this is a further error-specific component, which is independent of the Ne, and hence associated with a later aspect of error processing or post-error processing. Our new results with different age groups argue against the hypotheses that the Pe reflects conscious error processing or the post-error adjustment of response strategies. Further research is necessary to specify the functional significance of the Pe.

positive: Updating P300: An integrative theory of P3a and P3b The empirical and theoretical development of the P300 event-related brain potential (ERP) is reviewed by considering factors that contribute to its amplitude, latency, and general characteristics. The neuropsychological origins of the P3a and P3b subcomponents are detailed, and how target/standard discrimination difficulty modulates scalp topography is discussed. The neural loci of P3a and P3b generation are outlined, and a cognitive model is proffered: P3a originates from stimulus-driven frontal attention mechanisms during task processing, whereas P3b originates from temporal-parietal activity associated with attention and appears related to subsequent memory processing. Neurotransmitter actions associating P3a to frontal/dopaminergic and P3b to parietal/norepinephrine pathways are highlighted. Neuroinhibition is suggested as an overarching theoretical mechanism for P300, which is elicited when stimulus detection engages memory operations.

positive: Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects Braincomputer interfaces (BCIs) allow their users to communicate or control external devices using brain signals rather than the brain's normal output pathways of peripheral nerves and muscles. Motivated by the hope of restoring independence to severely disabled individuals and by interest in further extending human control of external systems, researchers from many fields are engaged in this challenging new work. BCI research and development has grown explosively over the past two decades. Efforts have begun recently to provide laboratory-validated BCI systems to severely disabled individuals for real-world applications. In this paper, we discuss the current status and future prospects of BCI technology and its clinical applications. We will define BCI, review the BCI-relevant signals from the human brain, and describe the functional components of BCIs. We will also review current clinical applications of BCI technology and identify potential users and potential applications. Lastly, we will discuss current limitations of BCI technology, impediments to its widespread clinical use, and expectations for the future.

positive: Anterior cingulate cortex, error detection, and the online monitoring of performance. An unresolved question in neuroscience and psychology is how the brain monitors performance to regulate behavior. It has been proposed that the anterior cingulate cortex (ACC), on the medial surface of the frontal lobe, contributes to performance monitoring by detecting errors. In this study, event-related functional magnetic resonance imaging was used to examine ACC function. Results confirm that this region shows activity during erroneous responses. However, activity was also observed in the same region during correct responses under conditions of increased response competition. This suggests that the ACC detects conditions under which errors are likely to occur rather than errors themselves.

negative: QR code location based reverse car-searching route recommendation model To deal with the reverse car-searching issue in large buildings and parking lots, a Quick Response Code (QR code) based reverse car-searching route recommendation model is designed. By scanning the deployed QR codes, a Smartphone can pinpoint the host location and parking location efficiently. Based on the submitted location information, the central control system can finally return the recommended routes, which facilitates a host to reach the parking location effectively. In our model, the reverse car-searching route is divided into two parts: choosing the optimal exports (elevator) and computing the shortest walking distance route. Based on the optimal export selection algorithm and regional shortest path algorithm, our model can choose the prior exports (elevator) effectively, and then recommend the optimal walking route in the buildings and parking lots. The simulation shows that this low-cost system can effectively solve the reverse car-searching problem in large buildings and parking lots, save the driver's car-searching time and improve the utilization rate of parking facilities.

negative: Ant supervised by PSO and 2-Opt algorithm, AS-PSO-2Opt, applied to Traveling Salesman Problem AS-PSO-2Opt is a new enhancement of the AS-PSO method. In the classical AS-PSO, the Ant heuristic is used to optimize the tour length of a Traveling Salesman Problem, TSP, and PSO is applied to optimize three parameters of ACO, (α, β, ρ). The AS-PSO-2Opt consider a post processing resuming path redundancy, helping to improve local solutions and to decrease the probability of falling in local minimum. Applied to TSP, the method allowed retrieving a valuable path solution and a set of fitted parameters for ACO. The performance of the AS-PSO-2Opt is tested on nine different TSP test benches. Experimental results based on a statistical analysis showed that the new proposal performs better than key state of art methods using Genetic algorithm, Neural Network and ACO algorithm. The AS-PSO-2Opt performs better than close related methods such as PSO-ACO-3Opt [9] and ACO with ABC [19] for various test benches.

negative: Using association rules for ontology extraction from a Quran corpus Ontology can be seen as a formal representation of knowledge. They have been investigated in many arti ficial intelligence studies including semantic web, softwa re engineering, and information retrieval. The aim of ontology is t o develop knowledge representations that can be shared and re used. This research project is concerned with the use of assoc iati n rules to extract the Quran ontology. The manual acquisition of ontologies from Quran verses can be very costly; therefore, we ne d an intelligent system for Quran ontology construction using patternbased schemes and associations rules to discover Qu ran concepts and semantics relations from Quran verses. Our system i s based on the combination of statistics and linguistics methods t o extract concepts and conceptual relations from Quran. In particular, linguistic pattern-based approach is exploited to extract spec ific concepts from the Quran, while the conceptual relations are found based on association rules technique. The Quran ontology wil l offer a new and powerful representation of Quran knowledge, and the association rules will help to represent the relations between all classes of connected concepts in the Quran ontology. Keywords— Ontology; Concepts Extraction ; Quran; Association Rules; Text Mining.

negative: Learning Image Descriptors with Boosting We propose a novel and general framework to learn compact but highly discriminative floating-point and binary local feature descriptors. By leveraging the boosting-trick we first show how to efficiently train a compact floating-point descriptor that is very robust to illumination and viewpoint changes. We then present the main contribution of this paper—a binary extension of the framework that demonstrates the real advantage of our approach and allows us to compress the descriptor even further. Each bit of the resulting binary descriptor, which we call BinBoost, is computed with a boosted binary hash function, and we show how to efficiently optimize the hash functions so that they are complementary, which is key to compactness and robustness. As we do not put any constraints on the weak learner configuration underlying each hash function, our general framework allows us to optimize the sampling patterns of recently proposed hand-crafted descriptors and significantly improve their performance. Moreover, our boosting scheme can easily adapt to new applications and generalize to other types of image data, such as faces, while providing state-of-the-art results at a fraction of the matching time and memory footprint.

negative: SMART VOTING SYSTEM WITH FACE RECOGNITION Manual voting system has been deployed for many yea rs in our country. However in many parts of our cou ntry people cannot attend the voting because of several r asons. In order to solve these problems there is a need of online election voting system in addition to manual voting system. The long-term goal of this project is to g reatly reduce the cost and complexity of running elections and increase th e accuracy of results by removing the direct involv ement of humans in gathering and counting of votes. The voters will be a le to give their votes at any field areas by usi ng the system if they prefer online voting In this system, the user votes using android applic ation which can be downloaded over internet. The us er has to login before giving his vote. Authentication will b e done using SMS confirmation and face recognition. Users can view parties, enter votes, can verify vote via SMS or email and can view result after result is declared.

negative: The Nature, Importance, and Difficulty of Machine Ethics The question of whether machine ethics exists or might exist in the future is difficult to answer if we can't agree on what counts as machine ethics. Some might argue that machine ethics obviously exists because humans are machines and humans have ethics. Others could argue that machine ethics obviously doesn't exist because ethics is simply emotional expression and machines can't have emotions. A wide range of positions on machine ethics are possible, and a discussion of the issue could rapidly propel us into deep and unsettled philosophical issues. Perhaps, understandably, few in the scientific arena pursue the issue of machine ethics. As we expand computers' decision-making roles in practical matters, such as computers driving cars, ethical considerations are inevitable. Computer scientists and engineers must examine the possibilities for machine ethics because, knowingly or not, they've already engaged in some form of it. Before we can discuss possible implementations of machine ethics, however, we need to be clear about what we're asserting or denying

negative: Integrating Conflicting Data: The Role of Source Dependence Many data management applications, such as setting up Web portals, managing enterprise data, managing community data, and sharing scientific data, require integrating data from multiple sources. Each of these sources provides a set of values and different sourc es can often provide conflicting values. To present quality data to users, it is critical that data integration systems can resolve conflicts and discover true values. Typically, we expect a true value to be provided by more sources than any particular false one, so we can take the value provided by the majority of the sources as the truth. Unfortunately, a false value can be spread through copying and that makes truth discovery extremely tricky. In this paper, we consider how to find true values from conflicting information when there are a large number of sources, among which some may copy from others. We present a novel approach that considers pendencebetween data sources in truth discovery. Intuitively, if two data sources provide a large number of common values and many of these values are rarely provided by other sources ( e.g., particular false values), it is very likely that one copies from the other. We apply Bayesian analysis to decide dependence between sources and design an algorithm that iteratively detects dependence and discovers truth from conflicting information. We also extend our model by considering accuracyof data sources and similarity between values. Our experiments on synthetic data as well as real-world data show that our algorithm can significantly improve accuracy of truth discovery and is scalable when there are a large number of data sources.

negative: Continental Airlines Flies High with Real-Time Business Intelligence Real-time business intelligence (BI) is taking Continental Airlines to new heights. Powered by a real-time data warehouse, the company has dramatically changed all aspects of its business. Continental’s president and COO, Larry Kellner, describes the impact of real-time BI in the following way: “Real-time BI is critical to the accomplishment of our business strategy and has created significant business benefits." In fact, Continental has realized more than $500 million in cost savings and revenue generation over the past six years from its BI initiatives, producing an ROI of more than 1,000 percent.

negative: Teenager ’ s Addiction to Smart Phones and Its Integrated Therapy Method The fundamental cause of teenagers’ addiction to smart phone is due to stress arising from family and school. Smartphone can cause many problems including musculoskeletal symptom which can develop due to staying in one position for a long time. Furthermore, starring at a small screen for an extended time can cause decreased eye sight, along with amblyopia. Smart phone addiction causes depression and anxiety which will lead to severe mental problems. This will lead to problems associated to one’s social life and human network. Fundamental treatment of cognitive and emotional elements needed to become harmonized as a whole in order to increase the effectiveness of the treatment results. The therapy has been verified to cure the behavioral and emotional aspect related to depression, sense of control, and assimilation in school. From these integrated treatment approaches, this report compared the treatment’s upsides and downsides and also, assessed the possibility the integrated treatment process. We can presume that this report provided the opportunity and support for the creation of a fundamental treatment method that can help teenagers live a healthy life by overcoming addiction to smart phones.

negative: Communication-efficient algorithms for statistical optimization We study two communication-efficient algorithms for distributed statistical optimization on large-scale data. The first algorithm is an averaging method that distributes the N data samples evenly to m machines, performs separate minimization on each subset, and then averages the estimates. We provide a sharp analysis of this average mixture algorithm, showing that under a reasonable set of conditions, the combined parameter achieves mean-squared error that decays as O(N-1 + (N/m)-2). Whenever m ≤ √N, this guarantee matches the best possible rate achievable by a centralized algorithm with access to all N samples. The second algorithm is a novel method, based on an appropriate form of bootstrap. Requiring only a single round of communication, it has mean-squared error that decays as O(N-1 + (N/m)-3), and so is more robust to the amount of parallelization.

negative: Reinforcement Learning of Coordination in Cooperative Multi-Agent Systems We report on an investigation of reinforcement learning techniques for the learning of coordination in cooperative multi-agent systems. Specifically, we focus on a novel action selection strategy for Q-learning (Watkins 1989). The new technique is applicable to scenarios where mutual observation of actions is not possible.To date, reinforcement learning approaches for such <i>independent </i> agents did not guarantee convergence to the optimal joint action in scenarios with high miscoordination costs. We improve on previous results (Claus & Boutilier 1998) by demonstrating empirically that our extension causes the agents to converge almost always to the optimal joint action even in these difficult cases.

negative: Characterization of log periodic planar dipole array antenna This paper proposes a analysis approach for characterizing the broadband Log Periodic Planar Dipole Array (LPPDA) antenna useful for C-band applications. A simplest geometry of the edge fed Log Periodic Planar Dipole Array is designed and developed. Parameters like length, width of the elements, and spacing between elements are the varied using defined scale factor (τ) and a spacing factor (σ), keeping others constant and their impact was noted down. A parametric analysis is performed. using CST software. A transmission line equivalent circuit of the proposed LPPDA is constructed. Log periodicity behaviour of the proposed antenna is checked by plotting input impedance with respect to logarithm of frequency. An antenna is fabricated and measured in laboratory.

negative: Using Suffix Arrays to Compute Term Frequency and Document Frequency for All Substrings in a Corpus Bigrams and trigrams are commonly used in statistical natural language processing; this paper will describe techniques for working with much longer n-grams. Suffix arrays (Manber and Myers 1990) were first introduced to compute the frequency and location of a substring (n-gram) in a sequence (corpus) of length N. To compute frequencies over all N(N+1)/2 substrings in a corpus, the substrings are grouped into a manageable number of equivalence classes. In this way, a prohibitive computation over substrings is reduced to a manageable computation over classes. This paper presents both the algorithms and the code that were used to compute term frequency (tf) and document frequency (df) for all n-grams in two large corpora, an English corpus of 50 million words of Wall Street Journal and a Japanese corpus of 216 million characters of Mainichi Shimbun. The second half of the paper uses these frequencies to find interesting substrings. Lexicographers have been interested in n-grams with high mutual information (MI) where the joint term frequency is higher than what would be expected by chance, assuming that the parts of the n-gram combine independently. Residual inverse document frequency (RIDF) compares document frequency to another model of chance where terms with a particular term frequency are distributed randomly throughout the collection. MI tends to pick out phrases with noncompositional semantics (which often violate the independence assumption) whereas RIDF tends to highlight technical terminology, names, and good keywords for information retrieval (which tend to exhibit nonrandom distributions over documents). The combination of both MI and RIDF is better than either by itself in a Japanese word extraction task.

negative: QDFS: A quality-aware distributed file storage service based on HDFS On the basis of the Hadoop distributed file system (HDFS), this paper presents the design and implementation of QDFS, a distributed file storage service system that employs a backup policy based on recovery volumes and a quality-aware data distribution strategy. The experimental results show that QDFS increases the storage utilization ratio and improves the storage performance by being aware of the quality of service of the DataNodes. The improvements of QDFS compared with HDFS make the Hadoop distributed computing model more suitable to unstable wide area network environments.

negative: Effects of psychological and social factors on organic disease: a critical assessment of research on coronary heart disease. An extensive research literature in the behavioral sciences and medicine suggests that psychological and social factors may play a direct role in organic coronary artery disease (CAD) pathology. However, many in the medical and scientific community regard this evidence with skepticism. This chapter critically examines research on the impact of psychological and psychosocial factors on the development and outcome of coronary heart disease, with particular emphasis on studies employing verifiable outcomes of CAD morbidity or mortality. Five key variables identified as possible psychosocial risk factors for CAD are addressed: acute and chronic stress, hostility, depression, social support, and socioeconomic status. Evidence regarding the efficacy of psychosocial interventions is also presented. It is suggested that, taken as a whole, evidence for a psychological and social impact on CAD morbidity and mortality is convincing. However, continued progress in this area requires multidisciplinary research integrating expertise in cardiology and the behavioral sciences, and more effective efforts to communicate research findings to a biomedical audience.

negative: Learning Theory and Instructional Design Designing effective instruction goes beyond systematically executing various steps within an instructional design model. Among a host of considerations, effective instructional design should take into consideration the theoretical bases in which it is grounded. This is not to say that learning theory offers instructional designers answers to design problems but instead, offers clarity, direction and focus throughout the instructional design process. Merrill (2001, p. 294) explains that a “theoretical tool, in and of itself, is not an instructional design theory but defines instructional components that can be used to define instructional prescriptions more precisely.” Likewise, Merriam and Caffarella (1999, p. 250) make the point that “[learning] theories do not give us solutions, but they do direct our attention to those variables that are crucial in finding solutions.” Thus, understanding theoretical frameworks and properly incorporating them within the scope of instructional design is important for designers to effectively prepare and present instruction as well as for organizational entities to more precisely and efficiently address training-appropriate issues.

negative: Oil content, tocopherol composition and fatty acid patterns of the seeds of 51 Cannabis sativa L. genotypes The oil content, the tocopherol composition, the plastochromanol-8 (P-8) content and the fatty acid composition (19 fatty acids) of the seed of 51 hemp (Cannabis sativa L.) genotypes were studied in the 2000 and 2001 seasons. The oil content of the hemp seed ranged from 26.25% (w/w) to 37.50%. Analysis of variance revealed significant effects of genotype, year and of the interaction (genotype × year) on the oil content. The oil contents of the 51 genotypes in 2000 and 2001 were correlated (r = 0.37**) and averaged 33.19 ± 1.45% in 2000 and 31.21 ± 0.96% in 2001. The γ-tocopherol, α-tocopherol, δ-tocopherol, P-8- and β-tocopherol contents of the 51 genotypes averaged 21.68 ± 3.19, 1.82 ± 0.49, 1.20 ± 0.40, 0.18 ± 0.07 and 0.16 ± 0.04 mg 100g−1 of seeds, respectively (2000 and 2001 data pooled). Hierarchical clustering of the fatty acid data did not group the hemp genotypes according to their geographic origin. The γ-linolenic acid yield of hemp (3–30 kg ha−1) was similar to the γ-linolenic acid yield of plant species that are currently used as sources of γ-linolenic acid (borage (19–30 kg ha−1), evening primrose (7–30 kg ha−1)). The linoleic acid yield of hemp (129–326 kg ha−1) was similar to flax (102–250 kg ha−1), but less than in sunflower (868–1320 kg ha−1). Significant positive correlations were detected between some fatty acids and some tocopherols. Even though the average content of P-8 in hemp seeds was only 1/120th of the average γ-tocopherol content, P-8 content was more closely correlated with the unsaturated fatty acid content than γ-tocopherol or any other tocopherol fraction. The average broad-sense heritabilities of the oil content, the antioxidants (tocopherols and P-8) and the fatty acids were 0.53, 0.14 and 0.23, respectively. The genotypes Fibrimon 56, P57, Juso 31, GB29, Beniko, P60, FxT, Félina 34, Ramo and GB18 were capable of producing the largest amounts of high quality hemp oil.

negative: Learning to Remember Translation History with a Continuous Cache Existing neural machine translation (NMT) models generally translate sentences in isolation, missing the opportunity to take advantage of document-level information. In this work, we propose to augment NMT models with a very light-weight cache-like memory network, which stores recent hidden representations as translation history. The probability distribution over generated words is updated online depending on the translation history retrieved from the memory, endowing NMT models with the capability to dynamically adapt over time. Experiments on multiple domains with different topics and styles show the effectiveness of the proposed approach with negligible impact on the computational cost.

negative: Active Magnetic Anomaly Detection Using Multiple Micro Aerial Vehicles Magnetic anomaly detection (MAD) is an important problem in applications ranging from geological surveillance to military reconnaissance. MAD sensors detect local disturbances in the magnetic field, which can be used to detect the existence of and to estimate the position of buried, hidden, or submerged objects, such as ore deposits or mines. These sensors may experience false positive and false negative detections and, without prior knowledge of the targets, can only determine proximity to a target. The uncertainty in the sensors, coupled with a lack of knowledge of even the existence of targets, makes the estimation and control problems challenging. We utilize a hierarchical decomposition of the environment, coupled with an estimation algorithm based on random finite sets, to determine the number of and the locations of targets in the environment. The small team of robots follow the gradient of mutual information between the estimated set of targets and the future measurements, locally maximizing the rate of information gain. We present experimental results of a team of quadrotor micro aerial vehicles discovering and localizing an unknown number of permanent magnets.

negative: A fast method of fog and haze removal Fog and haze degrade the quality of preview and captured image by reducing the contrast and saturation. As a result the visibility of scene or object degrades. The objective of the present work is to enhance the visibility, saturation, contrast and reduce the noise in a foggy image. We propose a method that uses single frame for enhancing foggy images using multilevel transmission map. The method is fast and free from noise or artifacts that generally arise in such enhancement techniques. A comparison with existing methods shows that the proposed method performs better in terms of both processing time and quality. The proposed method works in real time for VGA resolution. The proposed work also presents a scheme to remove fog, rain and snow in real-time.

negative: Snapshots in a flash with ioSnap Snapshots are a common and heavily relied upon feature in storage systems. The high performance of flash-based storage systems brings new, more stringent, requirements for this classic capability. We present ioSnap, a flash optimized snapshot system. Through careful design exploiting common snapshot usage patterns and flash oriented optimizations, including leveraging native characteristics of Flash Translation Layers, ioSnap delivers low-overhead snapshots with minimal disruption to foreground traffic. Through our evaluation, we show that ioSnap incurs negligible performance overhead during normal operation, and that common-case operations such as snapshot creation and deletion incur little cost. We also demonstrate techniques to mitigate the performance impact on foreground I/O during intensive snapshot operations such as activation. Overall, ioSnap represents a case study of how to integrate snapshots into a modern, well-engineered flash-based storage system.

negative: Analysis of back-end flash in a 1.5b/stage pipelined ADC An analysis of the impact of last stage flash in a conventional pipeline ADC is performed in this paper. The performance of a pipeline ADC can be altered significantly by calibrating the comparators in the back-end flash. Also, realizing that the input to the back-end flash (in a pipeline ADC) is not uniformly distributed, this paper proposes alternative back-end flash references to improve the overall performance of the ADC. An analysis of the performance of the pipeline with large offsets in the MDAC stages is also presented in this paper.

negative: A Preliminary Taxonomy of Crowdsourcing Many firms are now asking how they can benefit from the new form of outsourcing labelled “crowdsourcing”. Like many other forms of outsourcing, crowdsourcing is now being “talked up” by a somewhat credulous trade press. However, the term crowdsourcing has been used to describe several related, but different phenomena, and what might be successful with one form of crowdsourcing may not be with another. In this paper the notion of crowdsourcing is decomposed to create a taxonomy that expands our understanding of what is meant by the term. This taxonomy focuses on the different capability levels of crowdsourcing suppliers; different motivations; and different allocation of benefits. The management implications of these distinctions are then considered in light of what we know about other forms of outsourcing.

negative: Being John Malkovich Given a photo of person A, we seek a photo of person B with similar pose and expression. Solving this problem enables a form of puppetry, in which one person appears to control the face of another. When deployed on a webcam-equipped computer, our approach enables a user to control another person’s face in real-time. This image-retrievalinspired approach employs a fully-automated pipeline of face analysis techniques, and is extremely general—we can puppet anyone directly from their photo collection or videos in which they appear. We show several examples using images and videos of celebrities from the Internet.

negative: Common-Duty-Ratio Control of Input-Parallel Output-Parallel (IPOP) Connected DC–DC Converter Modules With Automatic Sharing of Currents Input-parallel output-parallel (IPOP) connected converter systems allow the use of low-power converter modules for high-power applications, with interleaving control scheme resulting in smaller filter size, better dynamic performance, and higher power density. In this paper, a new IPOP converter system is proposed, which consists of multiple dual-active half-bridge (DAHB) dc-dc converter modules. Moreover, by applying a common-duty-ratio control scheme, without a dedicated current-sharing controller, the automatic sharing of input currents or load currents is achieved in the IPOP converter even in the presence of substantial differences of 10% in various module parameters. The current-sharing performance of the proposed control method is analyzed using both a small-signal model and a steady-state dc model of the IPOP system. It is concluded that the equal sharing of currents among modules can be achieved by reducing the mismatches in various module parameters, which is achievable in practice. The current-sharing performance of the IPOP converter is also verified by Saber simulation and a 400-W experimental prototype consisting of two DAHB modules. The common-duty-ratio control method can be extended to any IPOP system that consists of three or more converter modules, including traditional dual-active bridge dc-dc converters, which have a characteristic of current source.

negative: P300 brain computer interface: current challenges and emerging trends A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the ERP, based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility.

negative: A simple real-word error detection and correction using local word bigram and trigram Spelling error is broadly classified in two categories namely non word error and real word error. In this paper a localized real word error detection and correction method is proposed where the scores of bigrams generated by immediate left and right neighbour of the candidate word and the trigram of these three words are combined. A single character position error model is assumed so that if a word W is erroneous then the correct word belongs to the set of real words S generated by single character edit operation on W. The above combined score is calculated also on all members of S. These words are ranked in the decreasing order of the score. By observing the rank and using a rule based approach, the error decision and correction candidates are simultaneously selected. The approach gives comparable accuracy with other existing approaches but is computationally attractive. Since only left and right neighbor are involved, multiple errors in a sentence can also be detected ( if the error occurs in every alternate words ).

negative: Spatial Filtering for EEG-Based Regression Problems in Brain–Computer Interface (BCI) Electroencephalogram (EEG) signals are frequently used in brain–computer interfaces (BCIs), but they are easily contaminated by artifacts and noise, so preprocessing must be done before they are fed into a machine learning algorithm for classification or regression. Spatial filters have been widely used to increase the signal-to-noise ratio of EEG for BCI classification problems, but their applications in BCI regression problems have been very limited. This paper proposes two common spatial pattern (CSP) filters for EEG-based regression problems in BCI, which are extended from the CSP filter for classification, by using fuzzy sets. Experimental results on EEG-based response speed estimation from a large-scale study, which collected 143 sessions of sustained-attention psychomotor vigilance task data from 17 subjects during a 5-month period, demonstrate that the two proposed spatial filters can significantly increase the EEG signal quality. When used in LASSO and <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-nearest neighbors regression for user response speed estimation, the spatial filters can reduce the root-mean-square estimation error by <inline-formula><tex-math notation="LaTeX">$10.02-19.77\%$</tex-math></inline-formula>, and at the same time increase the correlation to the true response speed by <inline-formula><tex-math notation="LaTeX">$19.39-86.47\%$</tex-math></inline-formula>.

negative: CloudSpeller: query spelling correction by using a unified hidden markov model with web-scale resources Query spelling correction is an important component of modern search engines that can help users to express an information need more accurately and thus improve search quality. In this work we proposed and implemented an end-to-end speller correction system, namely CloudSpeller. The CloudSpeller system uses a Hidden Markov Model to effectively model major types of spelling errors in a unified framework, in which we integrate a large-scale lexicon constructed using Wikipedia, an error model trained from high confidence correction pairs, and the Microsoft Web N-gram service. Our system achieves excellent performance on two search query spelling correction datasets, reaching 0.960 and 0.937 F1 scores on the TREC dataset and the MSN dataset respectively.

negative: Efficient detail-enhanced exposure correction based on auto-fusion for LDR image We consider the problem of how to simultaneously and well correct the over- and under-exposure regions in a single low dynamic range (LDR) image. Recent methods typically focus on global visual quality but cannot well-correct much potential details in extremely wrong exposure areas, and some are also time consuming. In this paper, we propose a fast and detail-enhanced correction method based on automatic fusion which combines a pair of complementarily corrected images, i.e. backlight & highlight correction images (BCI &HCI). A BCI with higher visual quality in details is quickly produced based on a proposed faster multi-scale retinex algorithm; meanwhile, a HCI is generated through contrast enhancement method. Then, an automatic fusion algorithm is proposed to create a color-protected exposure mask for fusing BCI and HCI when avoiding potential artifacts on the boundary. The experiment results show that the proposed method can fast correct over/under-exposed regions with higher detail quality than existing methods.

negative:
Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography. OBJECTIVE
Brain-computer interfaces (BCIs) based on electroencephalography (EEG) have been shown to accurately detect mental activities, but the acquisition of high levels of control require extensive user training. Furthermore, EEG has low signal-to-noise ratio and low spatial resolution. The objective of the present study was to compare the accuracy between two types of BCIs during the first recording session. EEG and tripolar concentric ring electrode (TCRE) EEG (tEEG) brain signals were recorded and used to control one-dimensional cursor movements.

APPROACH
Eight human subjects were asked to imagine either 'left' or 'right' hand movement during one recording session to control the computer cursor using TCRE and disc electrodes.

MAIN RESULTS
The obtained results show a significant improvement in accuracies using TCREs (44%-100%) compared to disc electrodes (30%-86%).

SIGNIFICANCE
This study developed the first tEEG-based BCI system for real-time one-dimensional cursor movements and showed high accuracies with little training.

negative: A Large Scale Ranker-Based System for Search Query Spelling Correction This paper makes three significant extensions to a noisy channel speller designed for standard written text to target the challenging domain of search queries. First, the noisy channel model is subsumed by a more general ranker, which allows a variety of features to be easily incorporated. Second, a distributed infrastructure is proposed for training and applying Web scale n-gram language models. Third, a new phrase-based error model is presented. This model places a probability distribution over transformations between multi-word phrases, and is estimated using large amounts of query-correction pairs derived from search logs. Experiments show that each of these extensions leads to significant improvements over the stateof-the-art baseline methods.


query: FingerCode: A Filterbank for Fingerprint Representation and Matching

positive: A Multichannel Approach to Fingerprint Classification Fingerprint classification provides an important indexing mechanism in a fingerprint database. An accurate and consistent classification can greatly reduce fingerprint matching time for a large database. We present a fingerprint classification algorithm which is able to achieve an accuracy better than previously reported in the literature. We classify fingerprints into five categories: whorl, right loop, left loop, arch, and tented arch. The algorithm uses a novel representation (FingerCode) and is based on a two-stage classifier to make a classification. It has been tested on 4,000 images in the NIST-4 database. For the five-class problem, a classification accuracy of 90 percent is achieved (with a 1.8 percent rejection during the feature extraction phase). For the four-class problem (arch and tented arch combined into one class), we are able to achieve a classification accuracy of 94.8 percent (with 1.8 percent rejection). By incorporating a reject option at the classifier, the classification accuracy can be increased to 96 percent for the five-class classification task, and to 97.8 percent for the four-class classification task after a total of 32.5 percent of the images are rejected.

positive: Automatic recognition and analysis of human faces and facial expressions: a survey Humans detect and identify faces in a scene with little or no effort . However, building an automated system that accomplishes this task is very difficult . There are several related Subproblems : detection of a pattern as a face . identification of the face, analysis of facial expressions, and classification based on physical features of the face . A system that performs these operations will find many applications, e .g . criminal identification, authentication in secure systems, etc . Most of the work to date has been in identification . This paper surveys the past work in solving these problems . The capability of the human visual system with respect to these problems is also discussed . It is meant to serve as a guide for an automated system . Some new approaches to these problems are also briefly discussed . Face detection Face identification Facial expressions Classification Facial features

positive: The theory of signal detectability The problem of signal detectability treated in this paper is the following: Suppose an observer is given a voltage varying with time during a prescribed observation interval and is asked to decide whether its source is noise or is signal plus noise. What method should the observer use to make this decision, and what receiver is a realization of that method? After giving a discussion of theoretical aspects of this problem, the paper presents specific derivations of the optimum receiver for a number of cases of practical interest. The receiver whose output is the value of the likelihood ratio of the input voltage over the observation interval is the answer to the second question no matter which of the various optimum methods current in the literature is employed including the Neyman Pearson observer, Siegert's ideal observer, and.Woodward and Davies' tlobserver.lV An optimum observer required to give a yes or no answer simply chooses an operating level and concludes that the receiver input arose from signal plus noise only when this level is exceeded by the output of his likelihood ratio receiver. Associated with each such operating level are conditional probabilities that the answer is a false alarm and the conditional probability of detection. Graphs of these quantities, called receiver operating characteristic, or ROC, curves are convenient for evaluating a receiver. If the detection problem is changed by varying, for example, the signal power, then a family of ROC curves is generated. Such things as betting curves can easily be obtained from such a family. The operating level to be used in a particular situation must be chosen by the observer. His choice will depend on such factors as the permissable false alarm rate, a priori probabilities, and relative importance of errors. With these theoretical aspects serving as sn introduction, attention is devoted to the derivation of explicit formulas for likelihood ratio, and for probability of detection and probability of false alarm, for a number of particular cases. Stationary, band-limited, white Gaussian noise is assumed.. The seven special cases which sre presented were chosen from the simplest problems in signal detection which closely represent practical situations. Two of the cases form a basis for the best available approximation to the important problem of finding probability of detection when the starting time of the signal, signal frequency, or both, are l l&TlOUn. Furthermore, in these two cases uncertainty in the signal can be varied, and a quantitative relationship between uncertainty and ability to detect signals is presented for these two rather general cases. The variety of examples presented should serve to suggest methods for attacking other simple signal detection problems and to give insight into problems too complicated to allow a direct solution.

positive: Textural Features for Image Classification Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes some easily computable textural features based on graytone spatial dependancies, and illustrates their application in categoryidentification tasks of three different kinds of image data: photomicrographs of five kinds of sandstones, 1:20 000 panchromatic aerial photographs of eight land-use categories, and Earth Resources Technology Satellite (ERTS) multispecial imagery containing seven land-use categories. We use two kinds of decision rules: one for which the decision regions are convex polyhedra (a piecewise linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89 percent for the photomicrographs, 82 percent for the aerial photographic imagery, and 83 percent for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

positive: Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor” representations for image analysis, segmentation, and compression. These transforms are conjoint spat iahpectral representations [lo], [15], which provide a complete image description in terms of locally windowed 2-D spectral coordinates embedded within global 2-D spatial coordinates. Because intrinsic redundancies within images a re extracted, the resulting image codes can be very compact. However, these conjoint transforms are inherently difficult to compute because t e elementary expansion functions a re not orthogonal. One o r t h o g o n k i n g approach developed for 1-D signals by Bastiaans [SI, based on biorthonormal expansions, is restricted by constraints on the conjoint sampling rates and invariance of the windowing function, as well as by the fact that the auxiliary orthogonalizing functions are nonlocal infinite series. In the present “neural network” approach, based upon interlaminar interactions involving two layers with fixed weights and one layer with adjustable weights, the network finds coefficients for complete conjoint 2-D Gabor transforms without these restrictive conditions. For arbitrary noncomplete transforms, in which the coefficients might be interpreted simply as signifying the presence of certain features in the image, the network finds optimal coefficients in the sense of minimal mean-squared-error in representing the image. I n one algebraically complete scheme permitting exact reconstruction, the network finds expansion coefficients that reduce entropy from 7.57 in the pixel representation to 2.55 in the complete 2-D Gabor transform. In “wavelet” expansions based on a biologically inspired log-polar ensemble of dilations, rotations, and translations of a single underlying 2-D Gabor wavelet template, image compression is illustrated with ratios up to 20: 1. Also demonstrated is image segmentation based on the clustering of coefficients in the complete 2-D Gabor transform. This coefficient-finding network for implementing useful nonorthogonal image transforms may also have neuroscientific relevance, because the network layers with fixed weights use empirical 2-D receptive field profiles obtained from orientation-selective neurons in cat visual cortex as the weighting functions, and the resulting transform mimics the biological visual strategy of embedding angular and spectral analysis within global spatial coordinates.

negative: ReTiCaM: Real-time Human Performance Capture from Monocular Video We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from just a single RGB video. We propose a novel two-stage analysis-by-synthesis optimization whose formulation and implementation are designed for high performance. In the first stage, a skinned templatemodel is jointly fitted to background subtracted input video, 2D and 3D skeleton joint positions found using a deep neural network, and a set of sparse facial landmark detections. In the second stage, dense non-rigid 3D deformations of skin and even loose apparel are captured based on a novel real-time capable algorithm for non-rigid tracking using dense photometric and silhouette constraints. Our novel energy formulation leverages automatically identified material regions on the template to model the differing non-rigid deformation behavior of skin and apparel. The two resulting nonlinear optimization problems per-frame are solved with specially-tailored data-parallel Gauss-Newton solvers. In order to achieve real-time performance of over 25Hz, we design a pipelined parallel architecture using the CPU and two commodity GPUs. Our method is the first real-time monocular approach for full-body performance capture. Our method yields comparable accuracy with off-line performance capture techniques, while being orders of magnitude faster.

negative: Comorbidity of anxiety and unipolar mood disorders. Research on relationships between anxiety and depression has proceeded at a rapid pace since the 1980s. The similarities and differences between these two conditions, as well as many of the important features of the comorbidity of these disorders, are well understood. The genotypic structure of anxiety and depression is also fairly well documented. Generalized anxiety and major depression share a common genetic diathesis, but the anxiety disorders themselves are genetically hetergeneous. Sophisticated phenotypic models have also emerged, with data converging on an integrative hierarchical model of mood and anxiety disorders in which each individual syndrome contains both a common and a unique component. Finally, considerable progress has been made in understanding cognitive aspects of these disorders. This work has focused on both the cognitive content of anxiety and depression and on the effects that anxiety and depression have on information processing for mood-congruent material.

negative: The neuropsychopharmacology of fronto-executive function: monoaminergic modulation. We review the modulatory effects of the catecholamine neurotransmitters noradrenaline and dopamine on prefrontal cortical function. The effects of pharmacologic manipulations of these systems, sometimes in comparison with the indoleamine serotonin (5-HT), on performance on a variety of tasks that tap working memory, attentional-set formation and shifting, reversal learning, and response inhibition are compared in rodents, nonhuman primates, and humans using, in a behavioral context, several techniques ranging from microiontophoresis and single-cell electrophysiological recording to pharmacologic functional magnetic resonance imaging. Dissociable effects of drugs and neurotoxins affecting these monoamine systems suggest new ways of conceptualizing state-dependent fronto-executive functions, with implications for understanding the molecular genetic basis of mental illness and its treatment.

negative: Vicious and virtuous cycles in ERP implementation: a case study of interrelations between critical success factors • A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.

negative:
Nivolumab in previously untreated melanoma without BRAF mutation. BACKGROUND
Nivolumab was associated with higher rates of objective response than chemotherapy in a phase 3 study involving patients with ipilimumab-refractory metastatic melanoma. The use of nivolumab in previously untreated patients with advanced melanoma has not been tested in a phase 3 controlled study.

METHODS
We randomly assigned 418 previously untreated patients who had metastatic melanoma without a BRAF mutation to receive nivolumab (at a dose of 3 mg per kilogram of body weight every 2 weeks and dacarbazine-matched placebo every 3 weeks) or dacarbazine (at a dose of 1000 mg per square meter of body-surface area every 3 weeks and nivolumab-matched placebo every 2 weeks). The primary end point was overall survival.

RESULTS
At 1 year, the overall rate of survival was 72.9% (95% confidence interval [CI], 65.5 to 78.9) in the nivolumab group, as compared with 42.1% (95% CI, 33.0 to 50.9) in the dacarbazine group (hazard ratio for death, 0.42; 99.79% CI, 0.25 to 0.73; P<0.001). The median progression-free survival was 5.1 months in the nivolumab group versus 2.2 months in the dacarbazine group (hazard ratio for death or progression of disease, 0.43; 95% CI, 0.34 to 0.56; P<0.001). The objective response rate was 40.0% (95% CI, 33.3 to 47.0) in the nivolumab group versus 13.9% (95% CI, 9.5 to 19.4) in the dacarbazine group (odds ratio, 4.06; P<0.001). The survival benefit with nivolumab versus dacarbazine was observed across prespecified subgroups, including subgroups defined by status regarding the programmed death ligand 1 (PD-L1). Common adverse events associated with nivolumab included fatigue, pruritus, and nausea. Drug-related adverse events of grade 3 or 4 occurred in 11.7% of the patients treated with nivolumab and 17.6% of those treated with dacarbazine.

CONCLUSIONS
Nivolumab was associated with significant improvements in overall survival and progression-free survival, as compared with dacarbazine, among previously untreated patients who had metastatic melanoma without a BRAF mutation. (Funded by Bristol-Myers Squibb; CheckMate 066 ClinicalTrials.gov number, NCT01721772.).

negative: Marginal improvement of AUFLS using ROCOF This paper proposes a scheme that integrates rate of change of frequency (ROCOF) and under frequency (UF) elements to design more effective load shedding response. A new load block activation algorithm is also introduced that improves the overall load shedding (LS) performance. The combination of ROCOF and UF criteria is used to overcome the LS block discrimination problem and to provide a flexible and decentralised solution to mitigation. The proposed method is verified through simulations on the IEEE 39-bus test system.

negative: Size matters: word count as a measure of quality on wikipedia Wikipedia, "the free encyclopedia", now contains over two million English articles, and is widely regarded as a high-quality, authoritative encyclopedia. Some Wikipedia articles, however, are of questionable quality, and it is not always apparent to the visitor which articles are good and which are bad. We propose a simple metric -- word count -- for measuring article quality. In spite of its striking simplicity, we show that this metric significantly outperforms the more complex methods described in related work.

negative: Smart agent based prepaid wireless energy meter Prepaid meter (PM) is getting very popular especially in developing countries. There are many advantages to use prepaid meter as opposed to postpaid meter both to the utility provider and to the consumer. Brunei Darussalam has adopted PM but it is not intelligent and not wireless enabled. Reading meters and topping up balance are still done manually. Utility provider does not have information on the usage statistics and has only limited functionalities in the grid control. So accordingly a novel software agent based wireless prepaid energy meter was developed using Java Agent Development Environment (JADE-LEAP) allowing agent from utility provider to query wireless energy meter for energy values of every household. These statistics can be used for statistical computation of the power consumed and for policy and future planning.

negative: OPRM1 and EGFR contribute to skin pigmentation differences between Indigenous Americans and Europeans Contemporary variation in skin pigmentation is the result of hundreds of thousands years of human evolution in new and changing environments. Previous studies have identified several genes involved in skin pigmentation differences among African, Asian, and European populations. However, none have examined skin pigmentation variation among Indigenous American populations, creating a critical gap in our understanding of skin pigmentation variation. This study investigates signatures of selection at 76 pigmentation candidate genes that may contribute to skin pigmentation differences between Indigenous Americans and Europeans. Analysis was performed on two samples of Indigenous Americans genotyped on genome-wide SNP arrays. Using four tests for natural selection—locus-specific branch length (LSBL), ratio of heterozygosities (lnRH), Tajima’s D difference, and extended haplotype homozygosity (EHH)—we identified 14 selection-nominated candidate genes (SNCGs). SNPs in each of the SNCGs were tested for association with skin pigmentation in 515 admixed Indigenous American and European individuals from regions of the Americas with high ground-level ultraviolet radiation. In addition to SLC24A5 and SLC45A2, genes previously associated with European/non-European differences in skin pigmentation, OPRM1 and EGFR were associated with variation in skin pigmentation in New World populations for the first time.

negative: Capacitance and Force Computation Due to Direct and Fringing Effects in MEMS/NEMS Arrays An accurate computation of electrical force is significant in analyzing the performance of microelectromechanical systems and nanoelectromechanical systems. Many analytical and empirical models are available for computing the forces, especially, for a single set of parallel plates. In general, these forces are computed based on the direct electric field between the overlapping areas of the plates and the fringing field effects. Most of the models, which are based on direct electric field effect, consider only the trivial cases of the fringing field effects. In this paper, we propose different models which are obtained from the numerical simulations. It is found to be useful in computing capacitance as well force in simple and complex configurations consisting of an array of beams and electrodes. For the given configurations, the analytical models are compared with the available models and numerical results. While the percentage error of the proposed model is found to be under 6% with respect to the numerical results, the error associated with the analytical model without the fringing field effects is ~50 %. The proposed model can be applied to the devices in which the fringing field effects are dominant.

negative: Non-Foster impedance matching of electrically small antennas When the size of an antenna is electrically small, the antenna is neither efficient nor a good radiator because most of the input power is stored in the reactive near-field region and little power is radiated in the far-field region. As demonstrated in [1]- [2], the radiation quality factor of small antennas is definitely high. In other words, the input impedance of small antennas is considerably reactive. To reduce the radiation quality factor in the whole or partial frequency range of interest, it is important to increase the radiation resistance and/or reduce the reactance of the antenna. Hence, it is necessary to modify the antenna to reduce the reactance of the antenna and/or add impedance matching networks (MNs) to maximize the transfer of power from a resistive source to the highly reactive antenna.

negative: A restart CMA evolution strategy with increasing population size In this paper we introduce a restart-CMA-evolution strategy, where the population size is increased for each restart (IPOP). By increasing the population size the search characteristic becomes more global after each restart. The IPOP-CMA-ES is evaluated on the test suit of 25 functions designed for the special session on real-parameter optimization of CEC 2005. Its performance is compared to a local restart strategy with constant small population size. On unimodal functions the performance is similar. On multi-modal functions the local restart strategy significantly outperforms IPOP in 4 test cases whereas IPOP performs significantly better in 29 out of 60 tested cases.

negative: Robust Curb Detection with Fusion of 3D-Lidar and Camera Data Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes.

negative: Successful lean implementation: Organizational culture and soft lean practices Lean management (LM) is a managerial approach for improving processes based on a complex system of interrelated socio-technical practices. Recently, debate has centered on the role of organizational culture (OC) in LM. This paper aims to contribute to this debate by examining whether plants that successfully implement LM are characterized by a specific OC profile and extensively adopt soft LM practices. Data were analyzed from the High Performance Manufacturing (HPM) project dataset using a multi-group approach. The results revealed that a specific OC profile characterizes successful lean plants; in particular, when compared to unsuccessful lean plants, they show a higher institutional collectivism, future orientation, a humane orientation, and a lower level of assertiveness. While a high level of institutional collectivism, future orientation, and humane orientation are common features of high performers in general, a low level of assertiveness is typical only of successful lean plants. In addition, successful lean plants use soft LM practices more extensively than unsuccessful lean plants (i.e., lean practices concerning people and relations, such as small group problem solving, employees’ training to perform multiple tasks, supplier partnerships, customer involvement, and continuous improvement), while they do not differ significantly in terms of hard LM practices (i.e., lean technical and analytical tools). For managers, the results indicate that, in order to implement LM successfully, it is fundamental to go beyond LM technicalities by adopting soft practices and nurturing the development of an appropriate OC profile.

negative: Narcissism and Romantic Attraction A model of narcissism and romantic attraction predicts that narcissists will be attracted to admiring individuals and highly positive individuals and relatively less attracted to individuals who offer the potential for emotional intimacy. Five studies supported this model. Narcissists, compared with nonnarcissists, preferred more self-oriented (i.e., highly positive) and less other-oriented (i.e., caring) qualities in an ideal romantic partner (Study 1). Narcissists were also relatively more attracted to admiring and highly positive hypothetical targets and less attracted to caring targets (Studies 2 and 3). Indeed, narcissists displayed a preference for highly positive-noncaring targets compared with caring but not highly positive targets (Study 4). Finally, mediational analyses demonstrated that narcissists' romantic attraction is, in part, the result of a strategy for enhancing self-esteem (Study 5).

negative: Control structure design for complete chemical plants Control structure design deals with the structural decisions of the control system, including what to control and how to pair the variables to form control loops. Although these are very important issues, these decisions are in most cases made in an ad hoc fashion, based on experience and engineering insight, without considering the details of each problem. In the paper, a systematic procedure for control structure design for complete chemical plants (plantwide control) is presented. It starts with carefully defining the operational and economic objectives, and the degrees of freedom available to fulfill them. Other issues, discussed in the paper, include inventory and production rate control, decentralized versus multivariable control, loss in performance by bottom-up design, and a definition of a the ‘‘complexity number’’ for the control system. # 2003 Elsevier Ltd. All rights reserved.

negative: Creating a Labeled Dataset for Medical Misinformation in Health Forums The dissemination of medical misinformation online presents a challenge to human health. Machine learning techniques provide a unique opportunity for decreasing the cognitive load associated with deciding upon whether any given user comment is likely to contain misinformation, but a paucity of labeled data of medical misinformation makes supervised approaches a challenge. In order to ameliorate this condition, we present a new labeled dataset of misinformative and non-misinformative comments developed over posted questions and comments on a health discussion forum. This required extraction of candidate misinformative entries from the corpus using information retrieval techniques, development of a codex and labeling strategy for the dataset, and the creation of features for use in machine learning tasks. By identifying the nine most descriptive features with regard to classification as misinformative or non-misinformative through the use of Recursive Feature Elimination, we achieved a classification accuracy of 90.1%, where the dataset is comprised 85.8% of non-misinformative comments. In our opinion, this dataset and analysis will aid the machine learning community in the development of an online misinformation classification system over user-generated content such as medical forum posts.

negative: Evaluating visual analytics with eye tracking The application of eye tracking for the evaluation of humans' viewing behavior is a common approach in psychological research. So far, the use of this technique for the evaluation of visual analytics and visualization is less prominent. We investigate recent scientific publications from the main visualization and visual analytics conferences and journals that include an evaluation by eye tracking. Furthermore, we provide an overview of evaluation goals that can be achieved by eye tracking and state-of-the-art analysis techniques for eye tracking data. Ideally, visual analytics leads to a mixed-initiative cognitive system where the mechanism of distribution is the interaction of the user with visualization environments. Therefore, we also include a discussion of cognitive approaches and models to include the user in the evaluation process. Based on our review of the current use of eye tracking evaluation in our field and the cognitive theory, we propose directions of future research on evaluation methodology, leading to the grand challenge of developing an evaluation approach to the mixed-initiative cognitive system of visual analytics.

negative: Game theoretic approach on Real-time decision making for IoT-based traffic light control 1Department of Computer Engineering, Chung-Ang University, Seoul, Korea 2Department of Computer Science, Universidad Autônoma de Madrid, Spain Correspondence Jai E. Jung, Department of Computer Engineering, Chung-Ang University, Korea. Email: j3ung@cau.ac.kr David Camacho, Department of Computer Science, Universidad Autonoma de Madrid, Spain. Email: david.camacho@uam.es Funding information Chung-Ang University Summary Smart traffic light control at intersections is 1 of the major issues in Intelligent Transportation System. In this paper, on the basis of the new emerging technologies of Internet of Things, we introduce a new approach for smart traffic light control at intersection. In particular, we firstly propose a connected intersection system where every objects such as vehicles, sensors, and traffic lights will be connected and sharing information to one another. By this way, the controller is able to collect effectively and mobility traffic flow at intersection in real-time. Secondly, we propose the optimization algorithms for traffic lights by applying algorithmic game theory. Specially, 2 game models (which are Cournot Model and Stackelberg Model) are proposed to deal with difference scenarios of traffic flow. In this regard, based on the density of vehicles, controller will make real-time decisions for the time durations of traffic lights to optimize traffic flow. To evaluate our approach, we have used Netlogo simulator, an agent-based modeling environment for designing and implementing a simple working traffic. The simulation results shows that our approach achieves potential performance with various situations of traffic flow.

negative: Pulsed voltage converter with bipolar output voltages up to 10 kV for Dielectric Barrier Discharge For pulsed power applications special pulsed voltage converters are needed. This paper presents an approach for a pulsed power converter, which generates bipolar output voltages up to 10 kV with extremely fast voltage slopes and high repetition rates. The topology is based on a H-bridge with a 10 kV dc-link. The output voltage and current of the pulsed voltage converter are adapted for the operation with Dielectric Barrier Discharge. To avoid the use of spark gaps due to their limited lifetime and thus to the lifetime of the converter, series stacked MOSFETs are used to realize a switch with a high blocking voltage. A balancing network for the series stacked MOSFETs is introduced as well as an adequate gate drive circuit. A matching method for the capacitive load is described, to achieve a maximum voltage slope at this capacitive load. To validate the theoretical considerations a prototype and measurements are presented.

negative: Odor Recognition in Multiple E-Nose Systems With Cross-Domain Discriminative Subspace Learning In this paper, we propose an odor recognition framework for multiple electronic noses (E-noses), machine olfaction odor perception systems. Straight to the point, the proposed transferring odor recognition model is called cross-domain discriminative subspace learning (CDSL). General odor recognition problems with E-nose are single domain oriented, that is, recognition algorithms are often modeled and tested on the same one domain data set (i.e., from only one E-nose system). Different from that, we focus on a more realistic scenario: the recognition model is trained on a prepared source domain data set from a master E-nose system <inline-formula> <tex-math notation="LaTeX">${A}$ </tex-math></inline-formula>, but tested on another target domain data set from a slave system <inline-formula> <tex-math notation="LaTeX">${B}$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">${C}$ </tex-math></inline-formula> with the same type of the master system <inline-formula> <tex-math notation="LaTeX">${A}$ </tex-math></inline-formula>. The internal device parameter variance between master and slave systems often results in data distribution discrepancy between source domain and target domain, such that single-domain-based odor recognition model may not be adapted to another domain. Therefore, we propose domain-adaptation-based odor recognition for addressing the realistic recognition scenario across systems. Specifically, the proposed CDSL method consists of three merits: 1) an intraclass scatter minimization- and an interclass scatter maximization-based discriminative subspace learning is solved on source domain; 2) a data fidelity and preservation constraint of the subspace is imposed on target domain without distortion; and 3) a minipatch feature weighted domain distance is minimized for closely connecting the source and target domains. Experiments and comparisons on odor recognition tasks in multiple E-noses demonstrate the efficiency of the proposed method.

negative: Real Time Drowsy Driver Identification Using Eye Blink Detection HUMAN COMPUTER INTERFACE (HCI) systems are designed for use in assisting people in various aspects. Driving support systems such as navigating systems are getting commoner by the day. The capability of driving support systems to detect the level of driver’s alertness is very important in ensuring road safety. By observation of blink pattern and eye movements, driver fatigue can be detected early enough to prevent collisions caused by drowsiness. The analysis of face image are widely used in security systems, face recognition, criminal focusing etc. In this specific study a non recursive system have been designed to detect shutting of eyes of the person driving an automobile. Real time detection of driver’s eyes is processed using image processing in MATLAB to detect whether the eye remains closed more than the fixed duration thus indicating condition of fatigue and raise an alarm which could prevent a collision. The driving support systems have been found lacking in detecting the influence of drug or alcohol causing great degree of risks to the commuters. This study has found that eye blink patterns are starkly different for persons under the influence of drugs and can be easily detected by the system designed by us.

negative: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks Recurrent neural network (RNN) models are widely used for processing sequential data governed by a latent tree structure. Previous work shows that RNN models (especially Long Short-Term Memory (LSTM) based models) could learn to exploit the underlying tree structure. However, its performance consistently lags behind that of tree-based models. This work proposes a new inductive bias Ordered Neurons, which enforces an order of updating frequencies between hidden state neurons. We show that the ordered neurons could explicitly integrate the latent tree structure into recurrent models. To this end, we propose a new RNN unit: ON-LSTM, which achieve good performances on four different tasks: language modeling, unsupervised parsing, targeted syntactic evaluation, and logical inference1.

negative: The Pendubot: a mechatronic system for control research and education 1 In this paper we describe the Pendubot, a mechatronic device for use in control engineering education and for research in nonlinear control and robotics. This device is a two{link planar robot with an actuator at the shoulder but no actuator at the elbow. With this system , a number of fundamental concepts in nonlinear dynamics and control theory may be illustrated. The pendubot complements previous mechatronic systems, such as the Acrobot 3] and the inverted pendulum of Furuta 4].

negative: Extensional Versus Intuitive Reasoning : The Conjunction Fallacy in Probability Judgment Perhaps the simplest and the most basic qualitative law of probability is the conjunction rule: The probability of a conjunction, P(A&B), cannot exceed the probabilities of its constituents, P(A) and .P(B), because the extension (or the possibility set) of the conjunction is included in the extension of its constituents. Judgments under uncertainty, however, are often mediated by intuitive heuristics that are not bound by the conjunction rule. A conjunction can be more representative than one of its constituents, and instances of a specific category can be easier to imagine or to retrieve than instances of a more inclusive category. The representativeness and availability heuristics therefore can make a conjunction appear more probable than one of its constituents. This phenomenon is demonstrated in a variety of contexts including estimation of word frequency, personality judgment, medical prognosis, decision under risk, suspicion of criminal acts, and political forecasting. Systematic violations of the conjunction rule are observed in judgments of lay people and of experts in both between-subjects and within-subjects comparisons. Alternative interpretations of the conjunction fallacy are discussed and attempts to combat it are explored.

negative: Global Ridge Orientation Modeling for Partial Fingerprint Identification Identifying incomplete or partial fingerprints from a large fingerprint database remains a difficult challenge today. Existing studies on partial fingerprints focus on one-to-one matching using local ridge details. In this paper, we investigate the problem of retrieving candidate lists for matching partial fingerprints by exploiting global topological features. Specifically, we propose an analytical approach for reconstructing the global topology representation from a partial fingerprint. First, we present an inverse orientation model for describing the reconstruction problem. Then, we provide a general expression for all valid solutions to the inverse model. This allows us to preserve data fidelity in the existing segments while exploring missing structures in the unknown parts. We have further developed algorithms for estimating the missing orientation structures based on some a priori knowledge of ridge topology features. Our statistical experiments show that our proposed model-based approach can effectively reduce the number of candidates for pair-wised fingerprint matching, and thus significantly improve the system retrieval performance for partial fingerprint identification.

negative: Graph-wavelet filterbanks for edge-aware image processing In our recent work, we proposed the construction of critically-sampled wavelet filterbanks for analyzing functions defined on the vertices of arbitrary undirected graphs. These graph based functions, referred to as graph-signals, provide a flexible model for representing many datasets with arbitrary location and connectivity. An application area considered in that work is image-processing, where pixels can be connected with their neighbors to form undirected graphs. In this paper, we propose various graph-formulations of images, which capture both directionality and intrinsic edge-information. The proposed graph-wavelet filterbanks provide a sparse, edge-aware representation of image-signals. Our preliminary results in non-linear approximation and denoising using graphs show promising gains over standard separable wavelet filterbank designs.

negative: A new approach to unwrap a 3-D fingerprint to a 2-D rolled equivalent fingerprint For many years, fingerprints have been captured by pressing a finger against a paper or hard surface. This touch-based fingerprint acquisition introduces some problems such as distortions and deformations in the acquired images, which arise due to the contact of the fingerprint surface with the sensor platen, and degrades the recognition performance. A new touch-less fingerprint technology has been recently introduced to the market, which can address the problems with the contact-based fingerprint systems. In this paper, we propose a new algorithm for unwrapping the acquired 3-D scan of the subject's finger into a 2-D rolled equivalent image. Therefore, The resulting image can be matched with the conventional 2-D scans; it also can be used for matching unwrapped 3-D fingerprints among themselves with the 2-D fingerprint matching algorithms. The algorithm is based on curvature analysis of the 3-D surface. The quality of the resulting image is evaluated and analyzed using NIST fingerprint image software.

negative: Fingerprint Template Protection: From Theory to Practice One of the potential vulnerabilities in a biometric system is the leakage of biometric template information, which may lead to serious security and privacy threats. Most of the available template protection techniques fail to meet all the desired requirements of a practical biometric system like revocability, security, privacy, and high matching accuracy. In particular, protecting the fingerprint templates has been a difficult problem due to large intra-user variations (e.g., rotation, translation, nonlinear deformation, and partial prints). There are two fundamental challenges in any fingerprint template protection scheme. First, we need to select an appropriate representation scheme that captures most of the discriminatory information, but is sufficiently invariant to changes in finger placement and can be secured using available template protection algorithms. Secondly, we need to automatically align or register the fingerprints obtained during enrollment and matching without using any information that could reveal the features, which uniquely characterize a fingerprint. This chapter analyzes how these two challenges are being addressed in practice and how the design choices affect the trade-off between the security and matching accuracy. Though much progress has been made over the last decade, we believe that fingerprint template protection algorithms are still not sufficiently robust to be incorporated into practical fingerprint recognition systems. Anil K. Jain Department of Computer Science & Engineering, Michigan State University, East Lansing, MI 48824, USA and Department of Brain & Cognitive Engineering, Korea University, Seoul. e-mail: jain@cse.msu.edu, Karthik Nandakumar Institute for Infocomm Research, A*STAR, Fusionopolis, Singapore. e-mail: knandakumar@i2r.astar.edu.sg, Abhishek Nagar Department of Computer Science & Engineering, Michigan State University, East Lansing, MI 48824, USA. e-mail: nagarabh@cse.msu.edu

negative: Estimating Fingerprint Deformation Fingerprint matching is affected by the nonlinear distortion introduced in fingerprint impressions during the image acquisition process. This nonlinear deformation causes fingerprint features such as minutiae points and ridge curves to be distorted in a complex manner. In this paper we develop an average deformation model for a fingerprint impression (baseline impression) by observing its relative distortion with respect to several other impressions of the same finger. The deformation is computed using a Thin Plate Spline (TPS) model that relies on ridge curve correspondences between image pairs. The estimated average deformation is used to distort the minutiae template of the baseline impression prior to matching. An index of deformation has been proposed to select the average deformation model with the least variability corresponding to a finger. Preliminary results indicate that the average deformation model can improve the matching performance of a fingerprint matcher.

negative: An efficient audio fingerprint search algorithm for music retrieval The conventional audio fingerprinting system by Haitsma uses a lookup table to identify the candidate songs in the database, which contains the sub-fingerprints of songs, and searches the candidates to find a song whose bit error rate is the lowest. However, this approach has a drawback that the number of database accesses increases dramatically, especially when the database contains a large number of songs or when a matching sub-fingerprint is not found in the lookup table due to a heavily degraded input signal. In this paper, a novel search method is proposed to overcome these difficulties. The proposed method partitions each song found from the lookup table into blocks, assigns a weight to each block, and uses the weight as a search priority to speed up the search process while reducing the number of database accesses. Various results from our experiment show the significant improvement in search speed while maintaining the search accuracy comparable to the conventional method.

negative: Multibiometric Cryptosystems Based on Feature-Level Fusion Multibiometric systems are being increasingly de- ployed in many large-scale biometric applications (e.g., FBI-IAFIS, UIDAI system in India) because they have several advantages such as lower error rates and larger population coverage compared to unibiometric systems. However, multibiometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. One method to protect individual templates is to store only the secure sketch generated from the corresponding template using a biometric cryptosystem. This requires storage of multiple sketches. In this paper, we propose a feature-level fusion framework to simultaneously protect multiple templates of a user as a single secure sketch. Our main contributions include: (1) practical implementation of the proposed feature-level fusion framework using two well-known biometric cryptosystems, namery,fuzzy vault and fuzzy commitment, and (2) detailed analysis of the trade-off between matching accuracy and security in the proposed multibiometric cryptosystems based on two different databases (one real and one virtual multimodal database), each containing the three most popular biometric modalities, namely, fingerprint, iris, and face. Experimental results show that both the multibiometric cryptosystems proposed here have higher security and matching performance compared to their unibiometric counterparts.