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International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 648695, 15 pages
Data Processing and Algorithm Analysis of Vehicle Path Planning Based on Wireless Sensor Network
School of Software Engineering, Tianjin University, Tianjin 300072, China
Received 11 January 2013; Accepted 9 March 2013
Academic Editor: Yan Zhang
Copyright © 2013 Wenyuan Tao and Mingqin Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Optimizing the path planning to reduce the time and cost is an essential consideration in modern society, and existing research has mostly concentrated on static path planning and real-time data information in vehicle navigational applications. Using dynamic path planning to adjust and update the path information in time is a challenging approach to reduce road congestion and traffic accidents. In this paper, we present a data analysis algorithm that determines an efficient dynamic path for vehicle repair-scrap sites and navigates more flexibly to avoid obstacles, where the key idea is to design the sensor wireless network that helps to obtain data from different devices. Firstly, the data processing scheme for real-time data with regional cluster and node division can be obtained from different sensor devices through the wireless senor network. Secondly, the search space and the relevant road information are restricted to a strongly connected graph. The most important strategy for an optimal solution to find the shortest path is the search method. Finally, to validate the performance of our design and algorithm, we have conducted a simulation based on necessary traffic variables. The performance simulation results show that real-time dynamic path planning can be significantly optimized using our data processing scheme.
1. Introduction
The acceleration of an automobile digitalization has led to the era of networked cars. Nowadays, China has become the largest automobile market in the world with an annual increase of 40% in car sales. There is no doubt that cars have brought convenience to our life; however, faulty cars could cause great troubles.
In order to make effective use of resources, governments at all levels in China have built sufficient repair-scrap sites to solve the problems for faulty cars. Receiving real-time information on the state of vehicles through wireless sensor network (WSN) [1, 2] and informing car owners of the closest repair-scrap sites are effective means to solve the problem of faulty cars and reduce potential traffic problems.
The key to solving this problem lies in the quantity and location of repair-scrap sites. To ensure the lowest overall costs, the average distance to the closest repair-scrap sites should be minimized. The collection and analysis of data and the issue of vehicle routing are crucial to solve this problem.
At present, automobiles mainly rely on vehicle navigation systems to receive satellite information and show the current position, driving direction, and distance from destinations on the electronic map. They choose the best driving route within the known road network range based on the shortest path principal. Currently, mature vehicle navigation systems in the market are mostly based on static path planning. When traffic accidents and road congestions occur, static path planning is unable to change routes in time. Thus, the vehicle dynamic path planning becomes a hotspot in research. With the rapid development of WSN, path search data is no longer static. Instead, data are collected, processed, and transferred through a network formed by a large number of sensor nodes distributed in a region in a self-organized manner. The sensor nodes have the characters of low-cost, low-power dissipation and the functions of perception, data processing, storage, and wireless communication [3]. With the change from static data to dynamic data, real-time information of current traffic condition can be available. The accuracy of recommended paths increases, does so the pressure on processing data; and thus, the requirement for the algorithm of data processing is more stringent.
In the issue of path optimization, the computing time increases in proportion to the increase of nodes especially in large networks. In the path optimization of large urban networks, the number and weight of nodes and edges increase dramatically; thus, the needed calculating time and real-time renewal quantity are large and can greatly affect the calculating efficiency of path optimum algorithms.
Based on the historical traffic information, combined with the current traffic information, the vehicle dynamic path planning is able to predict future traffic flow. It can adjust and update the best driving path in time to reduce traffic accidents and road congestions effectively. In recent years, the traffic status prediction becomes increasingly important to the research of vehicle navigation.
According to the understanding of specific reality, local path planning can be divided into two types: one with completely unknown environmental information and the other one with partly unknown environmental information. With the advent of the Internet, traffic information, vehicle information, and path information can be collected through the wireless sensor network. Environmental information can usually be quickly obtained so as to make global positioning which facilitates site selection.
In this paper, we propose an optimal network design model that decides the site location among vehicle repair-scrap sites. The cost of the model is minimized, proportional to the distance. The most important step for site positioning is to determine the distance.
We assume WSN, through which a large number of original data can be obtained. Preprocessing the original data according to specific demands, we can obtain data in a standard format (without abnormal data) upon which data analysis and path matching can be conducted so as to find the best path. These methods can be applications of wireless sensor networks in home area networks [4] and smart grids [5].
Depending on the existing environment and communication technologies, our efficient path planning method avoids obstacles through rectangular decomposition [6], according to the graph theory. The path planning algorithm consists of two levels: global path planning and local path planning. As to the global path planning layer, we have collected faulty sites, the location of the candidate repair centers, and the candidate scrap fields based on wireless senor network and the planning of the government.
In accordance with the scale of candidate sites, the global regional environment will be divided into several equal units by the grid method and rectangular decomposition. Local path planning is the planning of the path between two sites. According to the start site and the end site of the local area, we can choose the optimal path around obstacles in order to obtain the shortest one. We abstract the network into a graph and then find the shortest path via real-time traffic network and traffic information.
2. Related Work
The necessity of solving vehicle routing problem convinces us to analyze carefully according to given schemes. The vehicle path information is collected through wireless sensor network; then after analyzing the data, we can find the shortest path to arrive at the destination. Thus, the previous work related to this paper consists of three main aspects: data collection through wireless sensor network, data processing by graph theory, and algorithm analysis for the shortest path.
Much work has been done on wireless sensor networks. Akyildiz et al. [7] provide a review of factors that influence the design of sensor networks. It is known that, wireless sensor networks use battery-operated computing and sensing devices. Ye et al. [8] propose S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Mainwaring et al. [9] do the in-depth study of applying wireless sensor networks to real-world habitat monitoring and other researches on wireless sensor networks [10]. Al-Karaki and Kamal [11] work on routing techniques in wireless sensor networks and data aggregation in wireless sensor networks [12]. According to these works, wireless sensor networks should care more about how to process real-time data for vehicle navigation.
On graph theory, Bryant [13] presents a new data structure to represent the Boolean functions and an associated set of manipulation algorithms. Tarjan [14] proposes an improved version of an algorithm to find the strongly connected components of a directed graph, and an algorithm to find the disconnected components of an indirect graph is presented. Some methods have been developed using graph theory [15], graph structure [16], and graph search [17–20]. Graph theory being regarded as an effective analysis tool is applied to optimization of road networks, which simplifies the problem.
In order to provide efficient vehicle path planning, a dynamic path planning method which is suitable for domestic vehicle navigation applications based on researching the dynamic road network models including arithmetic and the real-time traffic information was presented [21]. An effective transport system using global information vehicle information and communication system (VICS) and local information and communication system (IVC) was introduced [22]. The VICS, as one of the intelligent transport systems, has been developed to reduce the traffic jam; it can give real-time global information to drivers to help them find the shortest path, although the shortest path has been studied for a long time. Floyd [23] and Johnson [24] have worked on the shortest path, and there are some other related studies [25].
It can be concluded that there are two key points in the work of this paper: exploiting the vehicle navigation applications to collect real-time data information and using proper routing algorithms to minimize the total cost. As is noted above, most of these solutions are unaware of the problem that source data is so "weak" that there is only one kind of data source from GPS. Thus, in this paper we design the sensor wireless network that can obtain data from different devices such as vehicle GPS, digital camera, speed sensor, and direction sensor. As their routing algorithms cannot solve the problem of real-time path finding properly, we design a new routing algorithm based on the shortest path to deal with the real-time path finding problem.
3. Problem Definition
A minimum total cost for a repair-scrap network is needed to be built. The costs to be considered in designing repair-scrap network include construction cost and transportation cost. The following parameters and variables will be used in the proposed model: is a faulty site; is a candidate repair center; is a candidate scrap field; is the capacity of a repair center; is the capacity of a scrap field; is the number of faulty cars at faulty site i; is the proportion of faulty cars at faulty site i that is needed to be sent to repair centers; is the proportion of faulty cars that is needed to be scrapped after going through repair centers; is the distance of transporting a faulty car to repair center j from faulty site i; is the distance of transporting a faulty car to scrap field k from faulty site i; is the distance of transporting a faulty car to scrap field k from repair center j; is the cost of building a repair center of capacity m; is the cost of building a scrap field of capacity h; the proportional coefficient.
The definitions of decision variables are as follows: is the number of faulty cars being transported to scrap field from repair center .
Considering the cost of building repair centers and scrap fields and the cost of transportation, we build the following optimization model according to the features of a candidate location within the vehicle network.
The target function is Formula (2) represents the minimum total cost, including the cost of building repair centers and scrap fields as well as the cost of transportation.
The following conditions should be satisfied for formula (2): where represents whether faulty car is transported to repair center . Formula (3) ensures that all faulty cars in all faulty sites can only be dealt with by one repair center: where represents the total capacity of repair center , and represents the sum of all the faulty cars in repair center . Formula (4) ensures that the number of faulty cars transported to a repair center cannot exceed its capacity: where represents the capacity of scrap fields . represents the total number of scraped cars to scrap fields from all faulty sites, and represents the total number of scrapped cars to scrap fields from all repair centers. Formula (5) represents the number of faulty cars transported to scrap fields as well as scrapped cars which cannot exceed its capacity: where represents whether faulty car is transported to scrap field . Formula (6) ensures that all faulty cars in all faulty sites can only be dealt with by one scrap field: where represents the total number of crapped cars from repair center to scrap field , and represents the total number of cars from all repair centers to scrap field . Formula (7) represents the flowing equilibrium relationship between faulty cars into repair centers and scrapped cars out of scrap fields:
Formula (8) represents one candidate that site that should be built as a repair center, respectively. Formula (9) represents one candidate site that should be built as a scrap field, respectively: Formula (10) defines the constraints of decision variables, , , and .
This paper focuses mainly on the issue of vehicle path, as well as analyzing path in mathematical model.
Since the objective of sites location is to find the shortest path between the two given sites in predetermined workspace, we derive a minimum total cost of a repair-scrap network for the given environmental structure that involves a number of faulty sites and a number of obstacles. In this paper, the algorithm procedure is described by rectangular decomposition, the strong connection graph, and site-to-site algorithm.
The costs to be considered include the construction cost and transportation cost, both of which are proportional to the distance. Meanwhile, the degree of crowdedness and the level of unblock for the transport path also affect path selection. According to the subjective intention of a person, you can choose the path if you want to go by the two constraints. This definition shows that the distance and the two constraints are important for the proposed global model.
4. Data Processing Scheme
Needed data are collected through wireless sensor network. Constituted by numerous cheap microsensors nodes deposited in the monitoring field, the mobile sensor network is a self-organized multihop network system. The sensor nodes have the characters of low-cost, low-power dissipation and the functions of perception, data processing, storage, and wireless communication. Data are collected through gathering, processing, and transferring the perceptive object in the area covered by network corporately.
Perceptive objects, sensor nodes, and users are three main elements of WSN. The monitoring area is the possible appearing area of the perceptive objects; perceptive objects are affairs that attract users and vary with the change of scenes. In the shortest path planning for vehicle repair-scrap sites, the perceptive objects are possible spots of faulty cars within the monitoring field. WSN usually includes sensor node, convergent node, and task management node. The convergent node has quite strong data processing and power supply ability. Normally there are one or several convergent nodes in a WSN, and a large number of common sensor nodes are distributed in the sensing field in the random or defined deployment. The sensor node is responsible for collecting information related to affairs that people are interested in, returning data along some path in the way of multihop, and finally transmitting data to task management node by the convergent node through Internet or data network with satellite. Inside sensor network, every node is not only the collector and sender of information, but also the router. Cooperating with each other, each node transmits sense data to the convergent node through multihop routing in the way of relay.
As data collection is the foundation of a research, we design the following data collection framework to obtain specific and accurate roads information.
The platform processing frame diagram (as is shown in Figure 1) consists of data collecting, data preprocessing, data analysis, and path recommendation. By gathering data through sensors, original data are obtained; after preprocessing the specific features of original data, we can get data that can be used directly for the experiment; by using algorithm of high efficiency, network data analysis and path recommendation can be realized.
To guarantee the efficiency of wireless transmission, it is inappropriate to send one datum at one time, as the sampling of the physical quantity of each node in WSN is conducted individually. Meanwhile, because of the continuity of time data, road network is divided into several sections in the design of WSN to collect original data separately. In each collection area three nodes with different functions (data node, convergent node, and task management node) are used instead of using just data node. In this way, the pressure on data transmission can be greatly reduced by simple data fusion.
As is shown in Figure 2, road network is divided into regions, with each region consisting of 3 different nodes (data node, convergent node, and task management node). After the original data are obtained from these nodes, they will be stored in the corresponding database of each region for future research. The data obtained from sensor nodes cannot be directly used in our experiment; thus, these data should be preprocessed into the data documentation format required by specific experiments in the data procession server of each region according to different experimental requirements. After the preparation of experimental data, we search the road network in the large server according to the algorithm of this paper to recommend the best path.
According to the features of WSN, we fractionize the examination area, or divide it based on the users' choice. Perceptive objects are crossings or paths that vehicles will pass. The examination area is the possible appearing place of perceptive object (from start to target place). Sensor node, convergent node, and task management node in the examination area upload real-time crossing information (such as no-left-turn or no-right-turn crossings, one-way street sections, and time periods in which the traffic of specific type of vehicle is closed) to Internet or satellite network, plan route with proposed algorithms, and then send back perceptive objects through convergent nodes for visual display.
Wireless sensor node and roadside access point are usually included in vehicle-based WSN in which the roadside access point plays two roles: convergent node and gateway to realize the interflow between WSN and backbone network. In the planning of the vehicle repair-scrap sites positioning, nodes in the network are vehicles loaded with road condition perception equipment. During the driving process, vehicles can collect samples of congestion and road condition along the way. At the same time, vehicles become the consumers of information, which requires the drivers to understand not only the current road condition but also road condition ahead so as to choose the best path. Roadside access point needed for the communication between related departments and vehicles also requires relaying support from sense data.
In this paper, data information is collected through WSN. Real-time information of traffic condition can be available by installing sensors like radar, camera, GPS navigator, and aerial detection in vehicles to monitor driving conditions, exhaust emission, and real-time road condition timely. And it will also bring convenience to drivers in making driving schedules.
5. Algorithm Analysis
Based on the data collected through WSN, we will design an algorithm for path planning by analyzing the established data model.
The problem to be considered is the shortest path planning for vehicle repair-scrap sites. In this paper, we restrict the geographical environment space to the strong connection graph. According to the sites and the obstacles, each site can be considered as a point whose coordinate is the site left-edge or right-edge center's coordinate. Once all points are scanned, all sites are covered. The core of the algorithm is to determine the strong connection graph in the environment firstly, mark the node based on the relationship between sites secondly, and find the shortest paths by traversing the nodes involved finally.
The planning of the vehicle repair-scrap sites positioning mainly contains four different types of sites: repair center, scrap field, faulty site, and obstacles (e.g., river, park). According to the relationship among the nodes, we need to determine the shortest path of each faulty site to every repair center and to every scrap field. Based on all the identified shortest paths, we can determine the optimal planning for the sites.
5.1. An Environment Model
Based on the wireless senor network and the government's plan, we obtain a detailed outline of the geographical environment. The given information helps us to determine the site's position in the given environment. Then, we can mark the faulty sites, repair centers and scrap fields, and obstacles with different symbols based on their characteristics in order to establish a map of the environment as is shown in Figure 3.
5.2. A Rectangular Model
In this paper, the known grid map is used to build each site and obstacle into a rectangular model as is shown in Figure 4. All sites and obstacles are divided into various rectangles with different length and width. The definite means are as follows: (1)find the minimum value for each site, taking all obstacles into consideration. If more than one grid point has the minimum value, then find the minimum value for the grid point and mark it as ;(2)find the maximum value for each site and obstacle. If more than one grid point has the maximum value, then find the maximum value for the grid point and mark it as ;(3)each site or obstacle is represented as a rectangle whose two diagonal end points are defined by the and .
5.3. Modeling the Paths around Obstacles
Firstly, we define the concept of the line segments and the nodes for a strong connection graph.
Let be an uniform grid graph that consists of a set of grid nodes and are integers such that and grid edges connecting grid nodes. The length of grid edges connecting adjacent nodes in is assumed to be 1.
Let be a set of mutually disjoint sites with boundaries on . Each rectangle in is a site.
Let be a set of mutually disjoint obstacles with boundaries on . Each rectangle in is an obstacle.
Let denote a partial grid of that consists of grid nodes which are not contained in the interior of any obstacle in or any site in and grid edges that are not incident to interior grid nodes of any obstacle in or any site in as is shown in Figure 5.
5.3.1. Line Segments
Each obstacle is represented as a rectangle. In order to get the shortest path from the start point to the target point, we need to construct a connection graph . The first step is to determine line segment , as finding line segments is an important step.
Each site or obstacle rectangle has four vertices that are corresponding to the four vertices located in the upper left corner, the upper right corner, the lower right corner, and the lower left corner of the site. Let be a vertex set which consists of four vertices of each site and obstacle, start point and target point on . In this paper, we define that the start point is one of four vertices, and is closer to the target point than others. Meanwhile, the target point is one of four vertices and is closer to the start point than others we have decided. The line segment is decided according to the algorithm. Figure 6 is the diagram of line segments.
Step 1. In the environment map , let be the set of line segments that form the boundaries of .
Step 2. We find any vertex from vertex set and draw the line segment in parallel with the -axis. According to the -axis coordinate, the sites in the space are sorted. If is between the abscissa of the sites, and the -axis parallel line through the point intersects with the site, then the site is marked. And if is not between the abscissa of the sites, let the site be marked as 0.
Step 3. Let the line segment be in parallel with -axis. If it is marked as 0, the line segment from to will be completed through and is parallel to the -axis. If it is marked, we need to identify the segment of the upper endpoint and the lower endpoint. Let ordinate of the upper endpoint be the minimum value of the -coordinate by upward line parallel to the -axis and through the point when the first encounters a site. Let ordinate of the lower endpoint be the maximum value of the -coordinate by downward line parallel to the -axis and through the point when the first encounters a site.
Step 4. We find any vertex from vertex set , and draw the line segment in parallel with the -axis. According to the -axis coordinate, the sites in the space are sorted. If is between the ordinate of the sites, the -axis parallel line through the point intersects with the site, and the site is marked. If is not between the ordinate of the sites, let the site be marked as 0.
Step 5. Let the line segment be in parallel with -axis. If it is marked as 0, the line segment from to can be completed through and parallel to the -axis. If it is marked, we need to identify the segment of the left endpoint and the right endpoint. Let ordinate of the left endpoint be the maximum value of the -coordinate by left line parallel to the -axis and through the point when the first encounters a site. Let ordinate of the right endpoint be the minimum value of the -coordinate by right line parallel to the -axis and through the point when the first encounters a site.
Step 6. If the vertex set is null, the line segment search is completed. The line segment set is as follows ; Otherwise, return to Step 2.
Based on the above algorithm, we can decide the final line segments. For example, the line segments are shown in Figure 7.
5.3.2. Connection Graph
After finding the set of edges, we need to search the intersection point between the edges. Let these intersection points, start point, and target point be composed of a set of nodes. The pseudocode of generate connection graph is shown in Algorithm 1.
At first, it is necessary to find the relationship between these nodes in the set, for example, the intersection point which is closed to the next intersection point in the direction of -axis and -axis. Through these nodes and the relations between these nodes, we abstract the whole environment into a strong connected graph as is shown in Figure 8.
5.3.3. The Definition of the Shortest Path
In the paper, the start point and the target point are faint. We define the Manhattan distance between and . Let be any obstacle-avoiding path from to . The detour number is defined as the total number of nodes on that are directed away from . The length of is. is a shortest path if and only if is minimized among all paths connecting and .
is a strong connection graph for and . According to the coordinates of the corner points of and obstacles in , and a given pair of the start and target points, can be used to find the optimal path. Let , be the start and target point, respectively, and , be any point in the shortest path, respectively. A direction assigned to an edge and the direction is from to . We define the detour length of with respect to target node denoted by as shown in Figure 9. Let l be the line passing through and perpendicular to.
The detour length of a node with respect to a source node and a target node , denoted by, is the sum of the detour lengths of all directed edges in any directed shortest path from to in . Let be a shortest path from to in . The length of is equal to .
5.3.4. The Shortest Path Algorithm
After having a clear definition of the shortest path, we can begin to search the shortest path from the start point to the target point with the space. In this section, the shortest path algorithm of site-to-site will be introduced pseudocode is shown in Algorithm 2.
From the start point , the algorithm generates graph by points and edges, the points in the graph are divided into two point subsets named as VISITED and CANDIDATES. Assume is the shortest path from the start point to any arbitrary point (set as the point name) in the connected graph .
In the space, the way shown in Figure 10 to find out the shortest path is as follows.
Step 1. First, assume that the subset and the set of points defined as CANDIDATES that wait to be accessed are empty, which means that all points have not been accessed by default. Then, the value of all points is initialized to be infinite, and the parent point is empty by default.
Step 2. Add point into the subset of and claim that point has been accessed. Then, choose the first waiting point as the current point, which belongs to the subset of CANDIDATES and is nearest to point .
Step 3. Access the four "Next Points" that are near to the current point in turn and calculate the value between and each one of the four points. If the sum of the value of current point and the value calculated from the current point to Next Point is below the value of "Next Point," update the value of "Next Point" as well as the parent point; otherwise, nothing is done.
Step 4. Set the first point in the subset of CANDIDATES as Next Point, update the subset of VISITED, add the Next Point to the subset of VISITED, mark the Next Point as accessed, delete the Next Point in the subset of CANDIDATES, and add the unaccessed points near the Next Point to the subset of CANDIDATES.
Step 5. Search in the CANDIDATES to continue finding the "Next Point" waiting to be accessed skip to Step 3 to continue. Therefore, this loop will not end until the current point reaches the last node in the CANDIDATES and the value of each node has been calculated. The next step is to choose a path from the start point to the target point .
Step 6. Setting the target point as the current point, we can find the parent point of the target point (denoted as the "Next Point") in order to connect the current point with the "Next Point."
Step 7. The "Next Point" is denoted as the current point and then skips to Step 6 to continue execution. The cycle will not end until the "Next Point" meets the start point.
The simple example is shown in Figures 11, 12, and 13.
5.3.5. Congestion Weight Variables
In the above algorithmic model, we take , the distance between the start point to the target point , into account when choosing the shortest path. Then the shortest path between points is decided when the comes to its minimum.
As regarded to the practical urban traffic, the road congestion and time-phrased differences of one-way or two-way streets should be estimated. We express congestion as (weight), the shortest distance between points as , and the degree of priority as %, which leads to the choice of the shortest path as follows: . and are equal magnitudes.
If , it means that the congestion weight is as important as distance, and they have the same degree of priority. (1) If the two distances are the same, we can tell from that the best passing path is when the congestion weights are at its minimum (Figure 14). (2) If the two congestion weight are the same, we can reach the best passing path from when the distance is at its minimum. (3) If both the distance and the congestion weight are different, then through the calculation of , the smallest minimum is the best path.
According to Figure 14, the distances from the start point to the target point are the same through , , or . Thus, the path can be decided just by comparing the congestion weight of these three paths, , , and , so the best travel path is path , the red one.
If , the distance is more important than the congestion weight. Then, under that condition the driver does not take time as the first priority and is not willing to burn oil for further trip; then, he can chose to wait and stick to the shorter path, the smallest minimum of .
Figure 15 shows the highest priority of distance between the start point to the target point through path , , and . Therefore, the best path can be decided by comparing the distance of these three paths and then calculating the minimum . In the given example, the distance is the smallest one, so the red path is the best travel path.
If , it refers that congestion weight is more important than distance , which means that the driver takes time as the first priority and is willing to steer clearly of the congestion road to avoid time consumption; then, the smallest minimum is the best path.
According to Figure 16, the highest priority is the weight from the start point to the target point through path , , and . As a result, comparing the weight of these three paths and then calculating the smallest minimum will lead to the best path. In this given example, , , and , the blue path is the best one.
5.3.6. Variables of One-Way or Two-Way Road
There are many one-way roads and two-way roads in urban traffic. One-way road means that vehicles travel from entrance on one side of the road and can only exit from the other side of the road, and usually there is a sign illustrating no entrance to exit; whereas two-way road refers to the road that you can enter and exit from both sides of the road freely, usually it has two lanes, four lanes, or six lanes. Some two-way roads are timed to remit the traffic pressure. In bustling parts of the city or locations that are easily congested, one-way roads and two-way roads are often restricted by time period.
As is presented in Figure 17, the red path is the shortest path in this environmental space with the assumption that all paths are passable. However, in reality, many paths are changing between one-way road and two-way road by times. For instance, from 7:00 am to 9:00 am, and from 5:00 pm to 7:00 pm roads in front of hospitals (yellow building) are one-way roads, restricting motor vehicles except buses to travel from east to west. As a result, during these two periods, the blue path is the best path for motor passengers.
6. A Simulation Study
In order to validate the arrangement of WSN, the necessity of preprocessing, and the correctness of path search algorithm in this paper the following experiment is designed.
Figure 18 compares the use of bandwidths among three WSN arrangements (original, divide region, and divide region and node) that vary with the number of sensors.
From the experimental results, we can see that the bandwidth usages of the WSN arrangements are almost the same when the number of sensors is small. The bandwidth of original WSN arrangement is rather small; however, it increases sharply with the increase of sensors. The bandwidth of divide region WSN arrangement increases slowly, while for divide region and node arrangement, it increases at the slowest speed. Thus, we can see that the WSN designed in this paper can be well adapted to the transportation field using a large number of sensors.
Figure 19 shows a comparison diagram of path-searching time by using original data and preprocessed data. The horizontal axis represents the size of data, which ranges from 200 GB to 1000 GB. The vertical axis represents time spending, which is measured in seconds.
It is obvious that using original data to search paths takes longer time than using preprocessed data. Path-searching time of original data is more than 10 seconds, which seriously affects users' experience. The preprocessed data takes less than 6 seconds in path finding which can satisfy users' demand. So preprocessed data is proved to be a right measure since path finding efficiency as well as users' experience is greatly improved in this way.
Based on divide region and node WSN arrangement, and the preprocessing of original data, we use the algorithm to find path.
Through the practical environment of traffic network and real-time traffic, we abstract the environmental space into graphic. Then, by using the algorithm of the shortest path between points in the graph, we generate an example to test the validity of this algorithm. In this example, repair centers, scrap fields, faulty sites, and obstacles are generated from sensor devices. 20 places of faulty sites and their coordinates, quantity as well as the proportion of the failed vehicles going to repair centers or scrap fields are also generated from the sensor devices. We now assume that there are 6 repair centers and 3 scrap fields with the given coordinates, and the capacities of repair centers and scrap fields are different. Based on the above algorithm for the shortest path between points, we use MATLAB 7.0 to complete some simulated experiments. Since the algorithm is random in some way, we run the example ten times and come up with the shortest path between points that avoid obstacles, as is shown in Figure 20.
Figure 20 shows that if the urban traffic network was taken into account and the path already settled, vehicles have to follow the rules of the path. There are many paths between two points. The start point and the target point have been defined by WSN, for example, the green node and red node. According to Section 5, the algorithm cares only for the shortest path between the two points rather than the start point or target point. We use the shortest path algorithm between points in accordance with transport expanse, length of path, the capacity of the points, and the degree of congestion of the roads to get the best transport path, which is illustrated in the graph. The result of the calculation presents that, on the basis of the urban traffic network, we can analyze and generate the best path information according to the information of point capacity and traffic condition gathered through the wireless sensor network. Then, drivers can choose a travel path from these best path information. If the algorithm accuracy of the solution is ensured, it will assist drivers to a great extent. Meanwhile, it is also applicable and easy to popularize.
7. Conclusion
Finding the best path that takes the shortest time is the key to a path recommendation system. This paper has proposed an algorithm based on WSN to solve the problem.
The data used in this paper are self-defined and collected through WSN. Since there are a large number of sensors in WSN, the paper proposes the following design to reduce the pressure on network bandwidth: divide the road network into several regions, while each of them has an independent server for data preprocessing to reduce pressure on the path search server. Meanwhile, the nodes in each region are divided into three types: data, convergence, and task management nodes. Data collected by adjacent nodes are sent to convergent nodes, and we just need to transmit data of convergent nodes in the network. Task management nodes are used to distribute different sensor nodes to obtain data of different types.
The original data are preprocessed into the standard format needed in the experiments. Using the proposed "site-to-site" graph algorithm and combining historical traffic information and real-time traffic information, the best path search can be conducted timely to ensure an optimal route.
Combined with historical as well as current traffic information, the algorithm can be recommended as the best path that existing recommendation algorithms cannot reach. Much work remains to be done for further improvement, such as to optimize the algorithm efficiency, to reduce the calculation interval, to experiment with more varieties of data, and to verify the correctness of this algorithm more comprehensively.
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One of my favorite things to do is reuse items for a fun new purpose. How many of us have thrown away old cookie sheets because of built-up grease, rust, or just because we want a new set? Guilty! But not anymore! After reading this article, you'll never throw away old cookie sheets again. Turn those old cookie sheets into colorful magnet boards, family message boards, and much more. You'll love how easy it is to transform an old set of cookie sheets into something unique and functional for the whole family.
Cookie sheet magnet board basics
There are many different ways to customize and personalize a magnet board made from a cookie sheet. Search online and you'll find several helpful tutorials on how to make one. Basically, though, you'll want to either paint the cookie sheet a bright color, or cover a clean cookie sheet with scrapbook paper, heavy wrapping paper, or something similar. Secure the paper to the back of the cookie sheet with hot glue. Decorate the front of the magnet board with ribbon, lettering, appliques, or other accents.
Use your finished boards to organize a family message center, keep shopping lists and coupons at the ready, display children's art and schoolwork, stay on-track with school and sporting events, or use these handy DIY décor items for decorative purposes instead.
We found some fabulous pictures online of some very pretty magnet boards that will inspire anyone to grab some scissors and get creative. Browse through our slideshow and let us know which pictures are your favorites. As you'll see, you are only limited by your imagination.

subset: commoncrawl


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I currently ride a 2006 SC Nomad with a CCDB rear shock and 66 RC2X fork and while i love the bike i'd like to get a new frame.
I like the idea of the 2Stage AM8 but haven't been able to find much info at all. Has anyone had any experience with them?
Has anyone ridden both?
Should i just stick with my current Nomad or go to a 2009 model?
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Chicago has its green river for St. Patrick's Day, but the Windy City isn't the only place you can find a shamrock-colored waterway. Cragger the Crocodile transformed the water in the Quest for Chi ride at Legoland Florida from its usual clear color to a bright shade of green. Check out the video accompanying this article for more details, as the wily croc was caught on camera in the midst of his dye job.
Craggar's sneaky move happened on the Sunday before the holiday, when he sneaked past Laval the Lion and dumped in enough dye to transform all 219,000 gallons of water in the ride. That means that the cascading waterfalls of Mount Cavora are also flowing in green, creating a perfect St. Patrick's Day photo opportunity at the park.
If you ride the Quest for Chi ride, be prepared to get very, very wet! You can blast a water cannon at other boats and spectators watching from shore, but they can do the same to you. Jump here for a full video of the ride.
Need advice or guidance from a Central Florida theme parks expert? Check out my ebooks for Kindle and Nook.


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Suri Cruise's dog found her way home and the fans are happy to see the young daughter of Tom Cruise happy once again. In Beverly Hills when a dog is lost it might be at the next mansion over, but the Chihuahua mix that goes by "Honey" and "Maple" seems to have gone a little bit farther away and the local neighbors helped recover the dog. According to Travelers Today on Tuesday, Suri Cruise is a happy young woman as her puppy was returned and right after the reunion the two went to the backyard to play.
Celebrities have the advantage of getting the word out quickly. Katie Holmes placed posters with a picture of the dog out all over the neighborhood in a plea to ask people to report the dog if found. Residents of the area (and the surrounding communities) kept an eye out for the dog and someone spotted the critter, making the reunion possible. The site SheKnows revealed that the movie star was offering $1,000 for the return of the dog and it appears it was well worth the investment.
Meanwhile, in related news on Wednesday, Katie Holmes and daughter Suri are settled into a $3.795 million home in Calabasas. The 6,200-square-foot luxury home will offer a lot of space for young Suri to play and entertain guests. Boasting six bedrooms and seven bathrooms, it is doubtful that there will be any battles for the makeup mirror.
Additional rumors are reported by KPopStarz that Katie Holmes has been dating Robin Thicke secretly for months. Katie seems very focused on motherhood and career and we believe she is still not in any romantic liaisons. Rumors may fly, but that is what keeps the PR machine well-oiled.


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I am currently using AESManaged encryption for my silverlight application. Does AESManaged encryption have a severe trade compliance issue in Bureau of Industry and Security in terms of shipping the application internationally?
Cryptography Stack Exchange is a question and answer site for software developers, mathematicians and others interested in cryptography. It's 100% free, no registration required.
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I am tempted to say that
(I am not entitled in any way to give legal advice, so do not take my word for it.)
If your software provides encryption, then you have to go to BIS, even if you're using a third-party framework that was approved by BIS, including Windows APIs.
This is what Apple's Mac App Store requires, even though Mac developers are using Mac OS X built-in encryption approved by BIS; so I trust Apple's lawyers here.


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I have an image in which the intensity of Red decreases from left to right (similar to the image below). Is it possible for me to compare the intensity of red at two different points?
I need to the values of the intensities of red at equally spaced distances for a science project.In the above picture, is it possible to generate a set of intensity values at every section marked by a thin line? (NOTE: by intensity, I mean the percentage of Red at the point in the image. I would say the intensity is high if the percentage of red is 98% & very low if percentage of red is say 1%)
Is there a script that I can use (in Gimp for example) or can anyone tell me how I can create my own using Python or Scilab? Other tools and languages are also welcome but these two are the ones I'm familiar with.
Thanks. Please comment if my question is not clear enough. I'll try to improve it based on your comments.


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Julianna Fischer
Feb. 3, 2012
DALLAS (SMU) - The No. 10 SMU equestrian team opened the spring season by defeating No. 3 Texas A&M, 6-4, Friday morning at BuckBranch Farm. The Mustangs took the meet by winning the final point as sophomore Julianna Fischer earned an 80-79 win on the flat. Fischer also picked up a point with a 76-71 victory over fences. With the win, the Mustangs move to 6-4 on the season.
"This was a big win for our team to start the semester," head coach Haley Schoolfield said. "It was a nail biter and a really hard-fought win. I'm proud of how Julianna handled the pressure; she put in a great ride and brought home the win. Our team has really worked hard and pushed each other, and you could definitely see that today."
SMU opened the day with a 4-1 advantage in equitation over fences. All-American Jordyn Pettersen won a point with her 73-64 win. Sophomore Renick Townsend and freshman Emma Roberts also scored for the Mustangs with wins of 77-72 and 78-60, respectively.
SMU lost the flat, 2-3, but Roberts earned her second point of the competition with an 83-82 win, assuring the Mustangs at least a tie against the Aggies. Fischer secured the win for SMU wither her 80-78 showing.
The Mustangs compete in the WEF Invitational Feb. 10 in Wellington, Fla. SMU returns to BuckBranch on March 2 to square off against South Dakota State.


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Arizona Begins Conference Play Against Washington
The Wildcats and Huskies kick off conference play at Hillenbrand Stadium this weekend
Cats Set to Participate in Judi Garman Classic
Arizona heads to Fullerton, Calif. to take on Virginia Tech, Notre Dame, Penn State, Michigan and Oklahoma
Cats Host Broncos For Three-Game Series
Arizona softball welcomes Boise State for a three game series Thursday and Saturday
Arizona Set for Mary Nutter Collegiate Classic
The 14th-ranked Wildcats travel to Palm Springs for dates with No 2. Olkahoma, Long Beach State, Ohio State, Loyola Marymount and No. 11 LSU
UA Hosts Hillenbrand Invitational
Hillenbrand Stadium will be the host of the 2013 Hillenbrand Invitational Feb. 15-17
2013: Tranferred to Arizona ... Must redshirt season per NCAA transfer rules.
2012 (UCLA): Fox was one of five Bruins to start all 56 games, leading the squad with four sacrifice hits, ranking second with 10 stolen bases and hitting .251 with four home runs and 22 runs batted in ... added nine doubles, 18 walks and 27 runs scored ... had nine multiple-hit games and six multi-RBI contests ... recorded three hitting streaks of at least five games, including a seven-gamer between March 24-April 5 in which she hit .500 (11-for-22) with five RBI, seven runs, two doubles, two steals and a homer ... went 2-for-2 with a two-run homer against Oregon State on April 1 ... had three hits and three runs in the first game of a doubleheader at Cal Poly (March 27) and added two more hits in the nightcap, swiping a base in each contest ... drove in a pair at UC Santa Barbara (March 24) ... had a six-game hitting streak from March 3-10, batting .438 (7-for-16) with 10 runs batted in, including an RBI in each of the last four contests of the streak ... recorded her second-career, two-homer game against Michigan State on March 7, driving in a personal-best five ... had a three-run triple versus Charleston Southern (March 10) ... began the season on a five-game hitting streak, batting .474 (9-for-19) with three RBI and three steals ... went 2-for-3 in the season opener against Kentucky (Feb. 9) and 3-for-3 two days later versus the Wildcats ... had two hits, two RBI and two steals at Loyola Marymount on Feb. 14 ... hit a two-run homer against Fresno State (Feb. 25) ... went 3-for-3 with two doubles and two runs against Stanford on April 10 ... posted two hits against Missouri (Feb. 26) and two runs versus Arizona (May 4).
2011 (UCLA): Was named to the All-Pac-10 First Team and the All-Freshman squad after placing tied for second on the team with 11 home runs, solo second with 45 runs batted in, a .608 slugging, eight sacrifice hits and six stolen bases, tied for first with 29 walks and third with a .342 batting average, 96 total bases and a .445 on base percentage ... had 10 multiple-RBI games, which was second on the club, and 11 multi-hit contests ... one of three Bruins to start all 55 games, all at shortstop ... posted hits in three games at the Gainesville Regional, going 2-for-5 with a run scored against Jacksonville on May 21 ... went 3-for-8 (.375) in the Arizona series (May 6-8) with a solo homer in game one ... smashed a three-run homer on April 21 against Washington, going 2-for-3, and was walked three times on April 22 ... belted her second grand slam of the season in the first inning of an April 15 win at Arizona State ... went 2-for-4 with two RBI and a double versus Loyola Marymount on April 6 ... posted an eight-game hitting streak from March 12-April 2, batting .450 (9-for-20) with 13 RBI (at least one in each of the last seven contests of the streak), seven runs scored, three homers and eight walks ... had three RBI on a two-run homer and an RBI groundout, also scoring and walking twice on April 2 against Oregon State ... went 2-for-2 with two runs scored and a two-run homer versus Ohio on March 24 ... posted her second, nine-game hitting streak of the season (Feb. 25-March 11), batting .500 (14-for-28) with six RBI, nine runs scored, two homers and three stolen bases ... hit a three-run homer against BYU on March 12 ... posted her first-career, two-homer game against San Diego State on March 5, belting a two-run shot and a solo bomb ... went 2-for-3 with an RBI on a bases-loaded walk against BYU (March 4) ... went 7-for-17 (.412) at the Cathedral City Classic with four runs scored ... had a pair of singles, two runs scored, an RBI and her first collegiate stolen base against Ohio State (Feb. 27) ... went 2-for-3 with a sacrifice bunt earlier in the day versus Northwestern ... posted two singles and scored a run against Oklahoma (Feb. 25) ... hit a grand slam at Northridge on Feb. 23 ... had hits in each of her first nine collegiate games, batting .480 (12-for-25) with two homers, 11 RBI and 10 runs scored ... went 3-for-3 with two doubles, an RBI and a walk against Arkansas on Feb. 18 ... posted two singles and drove in a run versus Utah on Feb. 19 ... hit her first collegiate homer, a solo shot, on Feb. 11 against North Dakota State ... added a three-run bomb on Feb. 12 against UCF, also scoring twice and drawing a walk ... scored three times and had an RBI double with a walk in the season opener versus Utah State (Feb. 11) ... drove in a pair on a bases-loaded walk and an RBI single against NDSU (Feb. 12).
High School: Fox was a two-sport standout at Mt. Carmel High School in San Diego, Calif. ... played four years of varsity softball and soccer ... earned all-league, all-county and all-section honors each season ... as a senior, was the CalHiSports CIF Division II Player of the Year and first-team All-Valley League, North County Times and Union Tribune All-Section ... hit .454 in 2010 with seven home runs, 38 runs batted in, 13 doubles and 10 stolen bases ... was named an Under Armour All-American as a sophomore and senior ... as a junior, set single-season, school records for homers (10), RBI (49), on base percentage (.576) and slugging (.971), adding a .491 batting average, 16 doubles and 12 steals ... helped the Sundevils to four CIF Division II and league titles ... coached by Cesar and Ruby Chavez ... played club with San Diego Renegades.
Personal: Born Kellie Lynn Fox on Oct. 30, 1991 in San Diego, Calif. ... parents are Jennifer and Michael Fox ... has an older sister Kristie, who played softball for Arizona, and a younger brother, Kory ... says she chose UCLA because it is the best school not only in academics but also has a long lasting tradition in sports ... favorites include the television show "One Tree Hill", singer Taylor Swift, eating sushi and the San Diego Chargers ... lists her biggest athletic thrill as winning CIF titles all four years and being honored as an Under Armour All-American ... majoring in women's studies.
Career Stats: Year Avg GP GS AB R H 2B 3B HR RBI TB SLG% BB HBP SO GDP OB% SF SH SB ATT 2011 .342 55 55 158 35 54 9 0 11 45 96 .608 29 2 29 2 .445 2 8 6 8 2012 .251 56 56 171 27 43 9 1 4 22 66 .386 18 0 18 1 .319 2 4 10 11 Totals .295 111 111 329 62 97 18 1 15 67 162 .492 47 2 47 3 .382 4 12 16 19
Career Single-Game Highs: At bats: 6, vs. Stanford (4/8/11) Runs: 3, vs. Utah State (2/11/11) 3, at Cal Poly (3/27/12) Hits: 3, Four Times (last vs. Stanford, 4/10/12) RBI: 5, vs. Michigan State (3/7/12) Doubles: 2, vs. Arkansas (2/18/11) 2, vs. Stanford (4/10/12) Triples: 1, vs. Charleston Southern (3/10/12) Home Runs: 2, at San Diego State (3/5/11) 2, vs. Michigan State (3/7/12) Total Bases: 8, at San Diego State (3/5/11) 8, vs. Michigan State (3/7/12) Walks: 3, vs. Washington (4/22/11) Stolen bases: 2, at Loyola Marymount (2/14/12) Sac hits: 1, 12 Times (last at Washington, 4/14/12) Sac flies: 1, Four Times (last vs. Michigan State, 3/7/12) Hit by pitches: 1, vs. Sacramento State (3/11/11) 1, at Florida (5/22/11)


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The SideWinder X6 Keyboard is a virtual command center giving you powerful programming and versatility to enhance your work or game play. It includes the following features:
You can switch between three banks of six programmable macro keys to assign up to 18 macros per profile. You can record any sequence of keystrokes—even standard chat messages and set your macros to repeat. Macros are stored on your hard drive and can be easily shared.
For details on working with macros, see How do I create macros?


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The University of Oregon's storied home for softball, Howe Field is widely regarded as one of the most historic and scenic settings for collegiate softball on the West Coast.
Built in 1936, it is located near the heart of the picturesque campus and is named after former University of Oregon professor Hubert C. Howe who served as the first faculty representative for the athletic department.
Converted to a softball facility in 1987, its nearby proximity to other historic UO athletic landmarks is fitting with Hayward Field and McArthur Court hosting the Duck track and field and basketball programs since 1919 and 1927, respectively.
Gorgeous Douglas Fir trees surround the venue, and its convenient location near the corner of 18th Avenue and University Street attracts students, citizens and softball denizens who stroll to contests against many of the nation's top teams that hail from the Pacific-10 Conference.
The venue has evolved with the times and has welcomed renovated dugouts and a new backstop (1996), a new scoreboard (1998), and permanent light standards (2009). Three bleacher sections were improved in 1995 to increase the venue's capacity to 3,000.
The infield and outfield playing surfaces have also been updated with modern maintenance engineering to encourage action in nearly any conditions. Batting cages are available behind the the right center field fence, and pitching warm-up areas are adjacent to each foul line. Locker rooms, a treatment center, equipment room, meeting room and weight room are accessible next door in McArthur Court.
Prior to the arrival of the softball team, the venue first hosted Duck men's baseball games from 1936-1981. It cost approximately $10,000 when built, and that season was christened by the second of UO's 10 Pacific Coast Conference Northern Division titles from 1935-55.
As the new home for women's softball in 1987, field dimensions were reconfigured to meet college specifications, with the right and left field walls moved to 190 feet, and center field at 200 feet.
UO students that present valid campus ID cards receive free admission to all softball events, and numerous ticket specials through the Duck Ticket Office (1-800-WEB-FOOT / 541-346-4461) attract families and groups.
Parking is available next to the venue, with metered restrictions in effect Monday-Saturday, 8 a.m. - 6 p.m., and some 24-hour restricted spots in posted areas nearby.
To see the venue's location on campus, click here, and more ticket information is available above on the main www.GoDucks.com front page TICKET link.
Fans should look for an announcement on www.GODUCKS.com or call the rain out number, 541-346-6148 , to check if a game is postponed or canceled due to weather.
Named after University of Oregon professor Hubert C. Howe, Howe Field was originally built for UO's baseball team in 1936. The field was converted in 1987 to accommodate the softball team. In 1995 three bleacher sections were built to increase its capacity to 3,000, a new backstop and dugouts were added in 1996 while a new scoreboard was installed in 1998.


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Anatoly Levchenko was launched to Mir together with the Main Expedition EO-03 crew of Musa Manarov, and Vladimir Titov. Soyuz TM-4 maneuvered through orbits of 168 x 243 km, 255 x 296 km, and 333 x 359 before docking with Mir at 12:51 GMT 23 December. Levchenko returned aboard Soyuz TM-3 with A Aleksandrov (launched aboard Soyuz TM-3) and Yuri Romanenko (Soyuz TM-2). The spacecraft landed on December 29, 1987 09:16 GMT near Arkalyk.
Levchenko was a prospective Buran pilot sent on the short mission to familiarise himself with spaceflight. Immediately after his return he was put at the controls of an aircraft to check if the experience had impaired his flying skills in any way.
AKA: Okean (Ocean ); Soyuz TM-4 (Levchenko).
First Launch: 1987.12.21.
Last Launch: 1987.12.29.
Duration: 7.92 days.


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ila gift box
ila gift box
£6.00 (£5.00 excl. VAT)
Present your ila gift in style with one of our glossy pink gift boxes. Supplied flat packed with shredded pink tissue paper, they are easy to assemble (no glue required).
A beautiful wrapping option delivered straight to your door.
Size: 210x70x70 mm.
Products not included.


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What I Pine For Rewrite:I sit in the back of Lisas Car, my legs tucked under my chin away from the prying eyes of the neighbourhood children. Im Maggie Simpson, Aged ten, a Reserved Girl who doesnt mix very well, Lost in a world of fate.The Children at school act like I dont exist, Like a soulful speck of dust floating forever in a vacant landscape, Even the teachers treat me with care, I have to have special lessons so everyone thinks Im thick which I the case I guess.Im not like other Children
Maybe it would have been better if I had died that day I fell from the top of the Climbing Frame. Be free of this pain and exclusion. Thats how I got this horrid illness. I had been climbing then suddenly like a hand had pushed me I was thrown back and landed with a smack on the hard concrete. I had passed out.I remember the rest clearly even it had happened so long ago, when I had come round I had found myself trapped. Unable to hear
From that day forward inste


text:
& Conditions
Blossom Occasions Ltd
ll Equipment are hired from us
hiring service needs to be paid by the Client.
All our Customer needs to agree &
abide by our Terms and Conditions which is stated below and are as follows:
All Crockery, Culteries, Table Linen, Cloth Linen and Chaircovers/sashes are hired from Blossom Occasions LTD via our suppliers by Our Clients -unless stated otherwise. There is a holding fees is required against Damages,Theft and/or missing items of any such at the earliest convenience and the Holding fees depends on your hired items and the size and Location of your Event/Party.
An INITIAL PART PAYMENT deposit of the Agreed cost needs to be paid by BACS along with the Holding fees of 10% of the total order/hire as soon as the first invoice is received by you via the Accounts Team- Payment would need to be made as advised on your invoice.
The Outstanding balance payment for the list of items on your contract and/or Final Incurred Payments requested after Amendments and/or Additional orders have been placed/Late Payment incurred fees must be paid in full 4weeks before the Event and at the date requested by the Accounts Department. (Cheques only accepted 6weeks by prior event) and A holding fees against damages and Lost of properties is required with a first payment requested by Blossom Occasions LTD.
The standard hire period is three days. This allows for collection/delivery on the day prior and return on the day following your function.
For late returned equipment or extended hire add 50% for 4-5 days and 100% for 5-7 days.
The delivery and collection service will be charged according to time, mileage and value of order. Charges are based on driver having convenient access to a ground floor location.
A washing up service are compulsory and would be charged separately and on a different entity for All Crockery, Cutlery, Glassware and Stainless steel and Laundry services for Table Linen, Chair Covers, Napkins and Sashes.
A Holding Deposit is charged by the nunber of hired items ordered and is a compulsory fee required against any losses and/or damages on all hired out properties before and during your Event. The Holding deposit would be refundable at the end of your event, Once all our hired properties have been checked
. If there are any loss and/or damages to our properties hired out to you, Blossom Occasions LTD would notify you after your events depending on the time the Client allocates for clearing up - however if no clearing up has been allocated, Blossom Occasions LTD would notify you as soon as possible depending on the Staff availability as per the time of a check taking place.
To avoid any disagreements, Please always state to us, if you need a clearing up Staff and allocation time which would be charged according to the volume and the size of your event/clearing staff hired out.
Any losses or damages to Blossom Occasions LTD's properties hired out to the Client would be deducted from the agreed holding fees. For your record, Damages and/or loss to properties would be charged according to our Suppliers' Original buying price-
Linen & Ice Buckets–£20:00 per Linen & Ice Bucket; Napkins- £4:50 each; Charger plates - £4:00 per Plate; Baskets and Tongs -£10:00 per item; Crockery and Cutleries- Separately charged by Event planning team for your event; Table Number Stand- £3:00 per Stand; Other Table Number Stand- £3:00 per Stand; Chair Covers- £2:00 per Cover and Sashes-£2:00 per Sash, Cake Stand -£75:00, Cake Knife/Fork- £35:00, Glasses & Tumblers- £4:00 each.
Blossom Occasions LTD are not obliged and would not be at your event to oversee your event, unless this has been requested and the cost is dependent upon the number of Guests and travelling time and location.
(Late Payment and Cheques)
Cheques only accepted 6 weeks prior to your event.
Late Payment is not acceptable and if this happen you would incur a 1.5% on any outstanding balance and would be charged after 15:00pm UK Time if the requested payment is not made and this applicable to all forms of payments
. To avoid incurring extra charges, please make payments on time or in advance.
We accept payments by
Cheque, BACS, Cash
or payment via Blossom Occasions'
PayPal Account
(Please note: Payments made via Paypal would incur extra cost and should be paid off by the CUSTOMER/ CLIENT). And please note, We do not store ANY OF YOUR details nor do we share customer details with any third party)
Make Cheque payable to
"Blossom Occasions Ltd"
Payment by
BANK DETAILS can be requested as an option of payment when orders have been placed.
NB: Please Always Quote the booking reference on the Agreed Contract/Invoice, when making payment exactly as it's been stated.
If you need further Assistance,
Please phone 01245450407
Please email us on the address stated above to confirm any form of payment has been made or credit.
Terms and Conditions
EVENT COVERAGE, PROPERTY AND EQUIPMENT Supplied.
Full On site Coverage service is charged by the hours we are present at your event and its charged depending on the Number of Guests attending/attended, the Location and travel visibility.
All Hired equipment remains the property of
Blossom Occasions Ltd"
The customer is responsible for all equipment hired, from the time of collection (or delivery) until its return. The hirer is responsible for equipment delivered to unattended premises.
The customer is responsible for returning equipment to the containers/hampers provided. We do not search the premises when we collect equipment.
Broken, lost and damaged equipment and linen will be charged at the full replacement cost. Replacement charges are per item. This also applies to containers.
Equipment will be checked on return following washing. OUR COUNT IS FINAL.
No responsibility will be accepted for injury or damage caused by use and handling of the equipment.
The charge does not include insurance against theft, loss or damage.
Orders may only be reduced up to 10 days prior to Event date.
No consideration will be given to shortage or damage to equipment unless informed by the Client within 24hours of delivery.
There will be no refund on Item for over ordering and/or Number of Guests.
We reserve the right to substitute any items due to circumstances beyond the suppliers control. However if you insist to have this items, there will be additional cost charged on each item(s).
Linen Hire
Linen orders must be confirmed 21 days prior to event.
Linen sizes may vary slightly as some shrinkage does occur and colours may vary due to batch and usage.
Linen must not be pinned or stapled.
Linen does not include charges of laundry on the agreed cointract, this is charged separately.
Ensure damp linen is left to dry before being packed into bags. Mildew will form on damp linen within a few hours.
A full replacement cost will be charged for lost linen
A full replacement cost will be charged for linen damaged beyond laundering, or by burning
Spare linen supplied with your order will form part of your order and be treated as such and additional incurred cost would apply.
On Discounted Package Deals - Blossom Occasions would not at any time exchange or substitute for an alternative and No Refund would be given at any time. The discounted package deal if you have taken one needs to be made in full and failure to comply with our T & C policy may result to criminal negligence. However, if you insist on items to be added onto the items agreed upon, a charge will apply and this would be invoiced to you at the end of our final count.
Pre-order Service Returns & Exchange
Please note that this document applies only to goods bought as Pre-order via our Order form.
Our Ingredient Statement
"Blossom Occasions
are committed to using the finest foods and ingredients available to us in all our hampers and foodie gifts. All the foods we use carry the statutory ingredient label. Our customers should be aware when ordering that we do not offer foods in our range that are specifically suitable for allergy sufferers or diabetics. We can however undertake bespoke orders for customers where required, by negotiation and with a minimum of 7 days to two weeks prior notice.
All foods including cakes, gourmet slices, scones, muffins, brownies, flapjacks, cookies and birthday cakes could either contain nuts or contain traces of nuts. All our foods are made in environments that use nuts.
For ingredient information of specific food products used or to arrange a bespoke hamper, please contact our customer service department via email:
prior to ordering. We cannot accept return of food gifts after dispatch as taken place.
Please view additional information on product substitutions your rights to cancel under the EU Distance Selling
Directive 2000 and all other matter related to Terms & Conditions
by clicking the word-
Ordered Goods or Hampers would normally take 1-4 for delivery within the UK & MORE outside the UK .
Any of the orders can not be exchanged and are non-refundable.
The price of the Goods shall be that stipulated on the Website. The price excludes VAT & delivery charges- the delivery charges is included at the end.
The total purchase price, including delivery charges, if any, will be displayed in the Buyer's shopping Invoice prior to confirming/paying for the order via our Customer Service department via email/telephone.
After the order has been placed and agreed,
Blossom Occasions Ltd"
-The Seller shall confirm by email the details, description and price for the Goods together with information on the right to cancel if the Buyer is a Consumer.
In the case of consumer sales, payment of the price plus delivery charges must be made in full before dispatch of the Goods.
In the case of other sales, payment of the price minus delivery charges shall be due within the due date on the receipt of the invoice supplied by the Seller.
Interest on overdue invoices shall accrue from the date when payment becomes due from day to day until the date of payment at a rate same as the Bank of England from time to time in force.
Blossom Occasions Ltd
reserves the right to periodically update prices on the Website along with the T & C Policy, which cannot be guaranteed for any period of time. We shall make every effort to ensure prices are correct at the point at which the Buyer places an order. And we verbally inform Customer and/or Clients by telephone and in writing through our Facebook, Twitter pages which are both connected to our website of the changes that has occured on our website and T & C POLICY which is updated from time to time.
Blossom Occasions Ltd
reserves the right to withdraw any goods from the Website at any time.
Blossom Occasions Ltd
shall not be liable to anyone for withdrawing any Goods from the Website or for refusing to process an order.
Where Goods may only be purchased by persons of a certain age, the buyer will be asked when placing an order to declare that they are of the appropriate legal age to purchase the Goods(In the
, When purchasing Alcoholic drinks, you need to be 18 years of age and over and in the
, you need to be 22 years of age and above).
Blossom Occasions Ltd
discovers that the Buyer is not legally entitled to order certain Goods,
Blossom Occasions Ltd
shall be entitled to cancel the order immediately, without notice.
CANCELLATION RIGHTS -Online Shopping only!
1. What are my cancellation rights? We hope you will be pleased with your purchase(s) online. However, should you wish to, you have the right to cancel the contract at any time up to the end of 7 working days from the day after you receive the goods under the Selling Regulations, providing that:
i) the instructions below are followed;
ii) the goods have not been used or modified in any way;
iii) they are returned to
Blossom Occasions Ltd
via Royal Mail at your cost with the original packaging
Blossom Occasions
via Royal Mail receives the goods back in a resalable condition.
2. How do I cancel my order? To exercise your right of cancellation, you must immediately send an email to
stating your order acknowledgment number (which can be found in your order acknowledgment e-mail) and that you wish to cancel your order.
3. How/when will the money be refunded to me if I cancel my order, and the goods have not yet been dispatched? If you exercise your right of cancellation BEFORE the goods have been dispatched, then the order will be cancelled. The amount you have paid will be refunded to your debit/credit card within 30 days at no additional cost to you.
4. How/when will the money be refunded to me if I don't take delivery of the goods? If you exercise your right of cancellation AFTER the goods have been dispatched, and you fail to take delivery of the goods,
Blossom Occasions
shall refund or re-credit you within 30 days for any sum that has been paid by you or debited from your credit card for the goods, less any expenses incurred for failed delivery (typically the delivery charge to you, plus a charge by our couriers to return the goods back to us, based on weight.
5. What is your returns policy for goods I have taken receipt of? If you exercise your right of cancellation as stated in paragraph A) above in relation to all or any part of the order, and you take delivery of the goods, you will be responsible for returning the cancelled goods to
Blossom Occasions Ltd
via Royal Mail at your own expense. You must take reasonable care to ensure the goods are not damaged in the meantime or whilst they are in transit being returned back to us. You must return the goods in the original packaging and in a resalable condition. We advise that you use a service that requests signatures on delivery to ensure that there are no problems in relation to lost goods in transit. The goods must be returned to us within 7 days of receipt to qualify for a full refund. We are able to arrange a collection of the goods and a return to us using our courier service but there will be a charge, typically £19.95.
6. Where should I return the goods to? The cancelled goods should be returned to
Blossom Occasions Ltd
on the address stated on Invoice
Please ensure you send your order number with your goods as we will not be able to process any returns without it.
7. What is the time limit for returning the goods? The cancelled goods must be returned to us within 7 working days of informing us of your cancellation.
8. How/when will the money be refunded to me if I take delivery of the goods? Once you have notified
Blossom Occasions Ltd
that you are cancelling the contract, and after the cancelled items have been received in good resalable condition by us within 7 days of the cancellation, we will refund or re-credit you within 30 days for any sum that has been paid by you or debited from your credit/debit card.
9. What happens if I cancel all or part of the order, but the goods returned back to
Blossom Occasions Ltd
have been
returned in a damaged condition? If the cancelled goods are not received back by us in a good resalable condition (packets must be unopened & unused),
Blossom Occasions
may charge you a sum not exceeding the value of the goods and all incidental costs involved in supplying them to you, including packing, administration and delivery charges.
10. Can I exchange all or part of my order? If you have ordered something in error then we are happy to exchange it for something else s long as the goods fill all of the same criteria above for returns. We can exchange the goods using our courier at a typical charge of the actual charge is based on weight and we can calculate this for you. Alternatively you can return the goods back to us at your own expense via your choice of postage, however
Blossom Occasions Ltd
will not be liable for lost of Goods and place a fresh order for the new goods.
11. What if my goods are delivered damaged? The procedure for accepting a delivery is outlined in the Delivery Options section. If the goods are damaged on receipt, you have 2 working days from receipt of goods to inform us and we will then take the appropriate action. We will be unable to provide any refund or replacement after this.
12. Payment for goods ordered with/via
Blossom Occasions Ltd
to other Suppliers needs to be paid at the time of Order.
Blossom Occasions Ltd
is not a charity Organisation.
Important Information
Any Items hired from a Third party other than Blossom Occasions LTD is and will not be any of our responsibility, whether Blossom Occasions LTD's staff are on site or not. And it is not Blossom Occasions LTD's duty or responsibility to clear and/or keep any third party's items during and after your Event.
Blossom Occasions LTD's
are available on hire to provide services to your Guests & Audience if we are running your event for you. The staff depending if the number of staff meets your party requirement, are to clear up at the end of your event, however Blossom Occasions LTD charges for this Service.
Ask for more details at the time of booking your EVENT.
Your privacy is guaranteed:
We will never give, lease or sell your personal information. Period!
safe secure shopping:
All personal information that you submit is encrypted and secure.
This site is tested and certified daily to pass the FBI/SANS Internet Security Test.
Satisfaction Guarantee
If you are not 100% happy with your
Blossom Occasions Ltd
online shopping experience, we will offer you a credit note.
However, Food Items; Jewellery and Body Products would not be exchanged or refunded at anytime.
Blossom Occasions Ltd
"Live the Diamond Lifestyle"
For all the Party requirement you need!
Hall & Table Decoration
Event Management & Planning Solutions
Gift & Basket Hamper Specialist
Wedding Management & Planning
Party Management & Planning
Party Organizer/Planner & Creative Party Designer
Crocerky & Cutlery Hire
Holiday Villa Rentals


text:
by thomas weston
i am just looking for a driving job i will stay out as long as i can,but nobody will hire me i have 4 yrs driving t/t started out hauling grain in New Mexico and Texas and now nothing except temp-driving job that lasted one month from Wisconsin to California twice on I-80 and I-15 and you know how Wyoming highway's are,but no call's you fill out application and they say ...sorry... well it looks like i'm going back to haul grain again in TX.
I have a friend who's been driving for 10 yrs in five states hauling grain all year and company's told him he has no experience in driving in snow or mtn's well Texas has both from Amarillo to Dalhart there are two way's to get there all on mtn road's....what can i say oh just my luck........thank you......thomas
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text:
Ronald H. Edwards
Position: DT
Height: 6-3 Weight: 320 lbs.
Born: July 12, 1979 in Columbus, OH
High School: Klein Forest
College: Texas A&M (school history)
Drafted by the Buffalo Bills in the 3rd round (76th overall) of the 2001 NFL Draft.
Weighted Career AV (100-95-...): 39 (2371st overall since 1950)
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text:
Score +2
Thread Details
$15 less than the nearest price at amazon.
For reference - Here is the link [amazon.com] to item on amazon.
Good reviews other than few people who said the fabric worn out after an year or so, but still usable with socks.
4 Comments
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It worked good on calf muscles too.
OK to sit too, but not effective.
My take - $35 is GREAT and costco's return policy makes it easy.


text:
on orders $75+
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Free shipping on all orders over $75, even the BIG STUFF that weighs a ton. No code. No hassle.
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text:
Oklahoma City , Okla. ?C The Arizona menˇ?s and womenˇ?s diving teams completed the second day of competition at the 2007 Zone ˇ®Eˇ? Diving Championships Friday, at Oklahoma Community College.
Junior Matt Bisordi finished 15th in the 1-meter competition for the men with 596.6 points, while he also finished 15th in the 3-meter competition last night with 536.80 points.
Freshman Mike Guilfoil finished 18th in the 3-meter with 537.50 points, as he placed 13th in the 1-meter last night with 544.95 points.
In the well for the women, senior Megan Macdonald finished 26th in the 1-meter event with 215.1 points, while sophomore Allison Scaife finished 29th (213 points). In the 3-meter competition last night, MacDonald placed 16th with 496.75 points.
The Wildcats will finish competition at the diving regionals tomorrow with the 10-meter platform event. NCAA qualifiers will then be announced at the conclusion of the meet.


text:
planetarium. by sugarmintsWatch
©2014-2016 sugarmints
Hello, I am new to your artwork, and you really made an impact. This picture shows the meaning of a whole song into just one frame. I love all the colors that blend together, it just makes the picture seems to be alive, and I like that. The technique you used on the moon is just amazing, and the light just makes the silhouette pop out, though nothing is moving. I have nothing negative to say about this piece of artwork.
If you like night scenes, the song Unfragment is good if you haven't heard it before now.
Good luck!
If you like night scenes, the song Unfragment is good if you haven't heard it before now.
Good luck!
The Artist thought this was FAIR
2 out of 2 deviants thought this was fair.
Wow, this is just beautiful!
I adore your skies, they remind me of Shivering Isles from Elder Scrolls IV: Oblivion
I saw this on Tumblr today. And just had to comment you on here seeing you have a DA page. This one is amazing. All of your artwork is amazing and beautiful. But this one specifically attracted me most because (not to sound cheesy as I type this), (⌒_⌒; ) but right after I'd get out of school I'd go to the playground where they had that same exact thing (I don't know the name for that dome thing) and sit on there and watch the sky a lot. I lived in Alaska so the skies were always beautiful around the evening. I miss it! Except it also reminded me how I fell down inside of it as well. Wasn't a pretty fall. xD
Oh I LOVE this! <3 It's so nice! I can see the cover influences done in your style. It's done so well! <3 And I love her songs! >_<
Me too, she has such nice ballads! I dont know if she still have new songs though, haven't really kept up with her but her old ones are really good. *-*
Yeah I still have her old stuff! <3 I love her old stuff! I don't think she still sings though? :/ I remember her getting married, but not sure if she stopped singing after she got married or not >_< I love her old old stuff a lot more than her newer stuff though >_< What's your fav song(s) from her?!
Yeah her old stuff are all very good, I have all of her old songs too! And omg she got married? Lol I haven't been keeping up with Jpop news...who did she get married to? And I like a lot of her ballads like Planetarium, Kingyo Hanabi, Pocket, Tears and Kurage Nagareboshi *_*...too many to name!
haha I actually didn't know she got married till after the fact! >_< And yeah she announced at a concert that she was pregnant! (after she got married) I don't know who she got married to! I just googled it and they said she's married to a guy named Su? I don't know who he is or if he's famous too or not >_< oooo I do like her ballads too. But I like her upbeat ones more! I guess my top favs would be Cherish, Sakuranbo, Himawari (: Kingyo Hanabi, Planetarium and Smily are up there too XD I like a lot of her old albums though >_<
Oh wow really? She has a child too o.o Damn~ Ah yeah her upbeat ones are cute as well, but I think I'm more of a ballad person hehe XD
A beautiful and amazing peice of work @_@
Another stunning piece, the colors and the space scene are all very well done and beautiful
@.@ Pretty
Whoa so pretty! I love the jungle gym silhouette!
What parts are wonky? I don't see anything weird-looking. It's simple but full of meaning and impact! It jumps out at me and-- *can't find words equal enough to it to describe how amazing it is*
Ahh I'm not too satisfied with the person and the dome thing she's sitting on, but thank you very much! ><
Thank you! And I agree with the pollution it's hard to see a clear sky especially if you live in a big city.
Lots of atmosphere... Engaging and beautiful. Improve whatever you see fit.
Oh, I wish I could see the planets like this
Great scenery, makes me wanna be there.
looks beautiful~! *^_^*
This is gorgeous ♥ I love it.
It's very pretty. However, your last artworks look a lot alike ... Same colors & always the sky ...
Thanks. I have an obsession with skies and these colours, I will do something different for the next one though.
i lovee your scenery ;v;
they look so beautiful~
they look so beautiful~
I think it's perfict
oh my god. i think this is may new fav.


text:
New York New York
Eric's vacation to see Anna debut at Carnegie Hall
This book was put together because of my passion for genealogy. I have been researching my ancestors for about 30 years. With contributons from various family members, I have put together a collection of stories and photos. Please enjoy.
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The Quintana Negrete Family Trees
Published April 12, 2010
The Quintana Negrete Family Tree
Published June 11, 2009
Blurb Sites


text: The website we linked to earlier today regarding the UT 2003 demo was actually a fake - I've seen removed the news post for obvious reasons. I'm not too red faced, thankfully a few other news sites fell for the prank as well. Hopefully we will see the real demo announced before much longer though!


text:
Nov. 6, 2012
Coach Mora addresses media after Tuesday's practice
The 17th/19th-ranked Bruins (7-2, 4-2) took the field this morning to begin preparations for the Pac-12 Conference game at Washington State. The contest will kick off at 7:36 p.m. and be televised by ESPN2.
Some Bruin notes from the NFL's ninth weekend- Arizona - DL David Carter saw action for the Cardinals and had one tackle; Carolina - PK Justin Medlock was in action, but did not connect on a field goal this week , DL Nate Chandler made a tackle; Cleveland - LS Christian Yount saw action ; Denver - WR Matthew Willis played for the Broncos Rahim Moore was credited with three tackles, including one for loss ; Indianapolis - LB Justin Hickman made a tackle for the Colts ; Jacksonville - RB Maurice Jones-Drew was not active this week, due to injury, TE Marcedes Lewis caught four passes for 41 yards, LB Kyle Bosworth saw action but was not credited with a tackle; San Diego - OT Mike Harris saw action for the Chargers ; Tennessee - LB Akeem Ayers totaled eight stops, including a sack for the Titans, CB Alterraun Verner recorded three tackles ; Washington - TE Logan Paulsen caught five passes for 59 yards in a starting role Kai Forbath kicked a pair of field goals, connecting from 47 and 25 yards out ; Minnesota - P Chris Kluwe kicked three times for a 48.3-yard average ; New England - WR Matthew Slater had a bye this past week; Dallas - DL Kenyon Coleman registered a tackle for the Cowboys.
A pair of home contests in the Rose Bowl remain for the Bruins, including a date with USC on Nov. 17 (either Noon or 5 p.m. start time to be announced Nov. 11) and with Stanford on Nov. 24 (tba). For ticket information call 310-UCLA-WIN or visit uclabruins.com/tickets.


text:
City police shot and wounded an armed suspect early Monday evening in an East Baltimore neighborhood. The shooting, which occurred around 4:00 p.m. between the Madison and Biddle Street neighborhoods of the Eastern District of Baltimore, came on the heels of the man trying to run police down.
At about 4:15 p.m. police officers witnessed a man driving a black Toyota. They said that he and the vehicle fit the description of a man and automobile that were involved in multiple armed robberies on Monday. He then led police on a chase that ended in the 2800 block of Chase Street, where police witnessed him tossing something from the car.
Police said that they then ordered the man out of the car, to which he responded by driving the car at them, resulting in their opening fire with their weapons. The suspect then drove off again and was able to make it to Loneys Lane and East Monument Street, where they were then able to place him under arrest. He was then transported to a hospital for treatment, however, his condition was unknown at the time of publication.
The man, who is still unidentified, is suspected of robbing, or attempting to rob the Forman Mills and Food Depot in the 2500 block of Belair Road, the CVS store in the 3300 block of Belair Road and Rainbow located in the 3900 block of Erdman Avenue.


text:
Use tree in a sentence
- A rude table was set there under a great tree, and around it three gentlemen were talking. [9]
- Angelo; not a tree, not a shrub, not a spire of grass, on its perpendicular side. [4]
- Chopping down a tree with a leaden axe is necessarily a slow process. [6]
- We saw a tree that bears grapes, and just as calmly and unostentatiously as a vine would do it. [5]
- There was another tree of striking aspect, a kind of pine, we were told. [5]
- Ned climbed a tree and arranged the halter, then came down and noosed his man. [5]
- The jungle seemed to contain samples of every rare and curious tree and bush that we had ever seen or heard of. [5]
- They waited some time longer under the tree, happy in the afterglow of this wonderful experience. [9]
- Her bench beneath the venerable tree was empty, and with drooping head she approached the beloved resting-place, which she must leave forever on the morrow. [10]
- The bench under the great tree was vacant, and the garden was empty. [9]
- How he put the body in the tree, and prayed over it and left it there, was all told; and then he paused. [11]
- If Philotas imagined that he could pluck the daughter of Archias like a ripe fruit from a tree, he would find himself mistaken. [10]
- When we were snugly lodged in the tree and curtained with foliage, the king was satisfied, but I was doubtful. [5]
- There was a seat under a tree, beside a still lake burnished by the moon. [9]
- He and the other gentlemen were gazing at the oleander tree whence, before any one approached it, a groan of pain was heard. [10]
This page helps answer: how do I use the word tree in a sentence? How do you use tree in a sentence? Can you give me a sentence for the word tree? It may also be related to learn English, student elementary education, worksheet, and home school.
Example sentences with the word tree, a sentence example for tree, and tree in sample sentence.


text:
The book is approx 10x8 inches (25x20 cms) and comprises of over 90 photographs taken throughout 2010 in and around Queensberry Bay Holiday Park.
Queensberry Bay is a small privately owned holiday park near Powfoot village on the Scottish side of the Solway Firth. No clubhouse, no entertainment just peace and relaxation. An animal rescue centre is adjacent to the site allowing visitors to see at close range highland cattle, llamas, horses, sheep, emus and other animals.
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Queensberry Bay 2011 Published October 10, 2011
Queensberry Bay Published January 31, 2011