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Automated vehicles become gradually available for restricted environments. Fully Automated Vehicles (FAV) operate without a driver and need to cooperate and interact with other road users of any kind. This article illustrates an interaction framework, which allows a human user outside the car to interfere with the FAVs guidance. This is achieved by communicating a desired maneuver, where the external user is asked to choose among a set of possible maneuvers. This set of maneuvers is communicated by the FAV to the user and has been checked for execution feasibility by the FAV, based on its perception. To this end, the environment is represented as an occupancy grid and a path search without distinct goal is performed. A small set of paths will be selected and communicated to the external user in an abstract level. This article presents the planning framework, as well as basic implementations for suited path search algorithms. The conclusion addresses unsolved challenges.

Good path planning technology of mobile robot can not only save a lot of time, but also reduce the wear and capital investment of mobile robot. Several methodologies have been proposed and reported in the literature for the path planning of mobile robot. Although these methodologies do not guarantee an optimal solution, they have been successfully applied in their works. The purpose of this paper is to review the modeling, optimization criteria and solution algorithms for the path planning of mobile robot. The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot. Finally, future research is discussed which could provide reference for the path planning of mobile robot.

This paper discusses the integration of automatic robot path planning into the computational design environment. A path planning software interface is presented that allows to support fabrication-aware design of robotically assembled structures with discrete elements. Using the large-scale Robotic Fabrication Laboratory (RFL) as test-bed, the software interface is validated through three experiments, in which building members need to be guided around obstacles and which are fabricated using two cooperative robotic arms. Specific focus of this paper is the investigation of strategies to narrow the path search by adjusting design and path planning parameters in order to achieve a calculation time that is suitable for design applications. A close integration of automatic path planning and design is presented, which does not only enable the negotiation between design intention and fabrication feasibility, but allows for an understanding of the constraints present in robotically fabricated spatial structures. Thus, this research contributes to expand these structures’ design and fabrication space.

One approach to solve detailed routing is net-bynet using a fast A*-based path search algorithm to handle long connections. The path search is restricted to certain areas imposed by the global router, which we call tunnels. Since a tunnel forces the path to follow its shape, a tunnel with many detours produces a path whose cost is far higher than the distance. This makes the path search algorithm to suffer heavy performance penalties. Thus, this work proposes new methods to preprocess the tunnels and use the gathered information during the search, providing a more realistic lower bound for the heuristic function of the path search algorithm. The experiments compared Hetzel's algorithm [1] using distance and our method. The results showed a time improvement of 64% in average.

In the event of a disaster, most of the current evacuation path search algorithms are based on minimizing the travel cost to each shelters. Since the shelters usually have limited capacities, the vehicle evacuation time may be lengthened to search the alternate shelter if the first chosen shelter is full. A new algorithm is presented in this study which will minimize the vehicle evacuation time by searching a shelter with consideration of its capacity. Link based Dijkstra which is most widely used path search algorithm is utilized and the traffic shall be assigned according to the dynamic transportation network load model. The dynamic network loading model is used to express how a group of vehicles is moving an actual network through the moving cell model that best describes the traffic flow characteristics of the group of vehicles. The suggested algorithm is applied to the example traffic to compare the results where the shelter capacity has been considered in determining the path information and the results where it has not been considered. This study observed and concluded that the total vehicle evacuation time is practically reduced where the shelter capacity has been considered in determining the evacuation path.

High-throughput automated fluorescent imaging and screening are important for studying neuronal development, functions, and pathogenesis. An automatic approach of analyzing images acquired in automated fashion, and quantifying dendritic characteristics is critical for making such screens high-throughput. However, automatic and effective algorithms and tools, especially for the images of mature mammalian neurons with complex arbors, have been lacking. Here, we present algorithms and a tool for quantifying dendritic length that is fundamental for analyzing growth of neuronal network. We employ a divide-and-conquer framework that tackles the challenges of high-throughput images of neurons and enables the integration of multiple automatic algorithms. Within this framework, we developed algorithms that adapt to local properties to detect faint branches. We also developed a path search that can preserve the curvature change to accurately measure dendritic length with arbor branches and turns. In addition, we proposed an ensemble strategy of three estimation algorithms to further improve the overall efficacy. We tested our tool on images for cultured mouse hippocampal neurons immunostained with a dendritic marker for high-throughput screen. Results demonstrate the effectiveness of our proposed method when comparing the accuracy with previous methods. The software has been implemented as an ImageJ plugin and available for use.

We propose a new pathfinding technique called xTrek that combines conventional pathfinding and influence fields; that is, we are introducing a new influence-sensitive pathfinder or influence-aware pathfinder. The leading idea of influence-aware pathfinding is to avoid unwanted regions and/or converge to desired regions of the search space during the path search. As shown throughout the paper, this region avoidance/convergence is more striking using our technique than in other field-aware pathfinders as, for example, risk-adverse pathfinders and constraint-aware navigation pathfinders. Furthermore, our technique constrains the search space even more than such state-of-the-art influence-aware pathfinders, aiming to reduce the memory space consumption, to speed up pathfinding computations, and at the same time to have better control on the paths to be discovered.

BackgroundChallenges in developing a good de novo transcriptome assembler include how to deal with read errors and sequence repeats. Almost all de novo assemblers utilize de Bruijn graph, which has a complexity linearly growing with data size while suffers from errors and repeat. Although one can correct errors by inspecting topological structure of the graph, it is an uneasy task when there are too many branches. There are two research directions: improving either graph reliability or path search precision. We focused on improving the reliability.ResultsWe present TraRECo, a greedy approach to de novo assembly employing error-aware graph construction. The idea is similar to overlap-layout-consensus approach used for genome assembly, but is different in that consensus is made through the entire graph construction step. Basically, we built contigs by direct read alignment within a distance margin and performed junction search to construct splicing graphs. While doing so, however, a contig of length l was represented by 4×1 matrix (called consensus matrix), of which each element was the base count of aligned reads so far. A representative sequence is obtained, by taking majority in each column of the consensus matrix, to be used for further read alignment. Once splicing graphs were obtained, we used IsoLasso to find paths with noticeable read depth. The experiments using real and simulated reads showed that the method provides considerable improvements in sensitivity and reasonably better performances when comparing both sensitivity and precision. This could be achieved by making more erroneous reads to be participated in graph construction, which, in turn, improved the depth information quality used for the subsequent path search step. The results for simulated reads showed also challenges are still remaining since non-negligible percentage of transcripts with high abundance were not recovered by the assemblers we considered.Conclusionde novo assembly is mainly to explore not-yet-discovered isoforms and must be able to represent as much reads as possible in an efficient way. In this sense, TraRECo provides us a potential alternative to improve graph reliability, even though the computational burden can be much higher than single k-mer de Bruijn graph approach.

The necessary conditions for the diagnosability of control systems with a complex structure are given. It is shown that the topological conditions for detectability and localization of the fault signal do not depend on the class of operators of the dynamic model of the control system and are checked by using path search algorithms in directed graphs.

This paper presents an efficient convolutional neural network (CNN)-based multiple path search (MPS) algorithm to detect multiple spatial-temporal action tubes in videos. With the pass information and the accumulated scores generated by forward message passing, the new algorithm reuses these information to simultaneously find multiple paths in backward path tracing without repeating the search process. Moreover, to rectify the potentially inaccurate bounding boxes, we also propose a video localization refinement scheme to further boost the detection accuracy. Simulations show that the proposed algorithm provides competing performance compared with the main state-of-the-art works on the widespread UCF-101 dataset with yet lower complexity.

In this paper, the term network pruning is used to describe the process of extracting an appropriate subnetwork from a larger network for efficient and accurate path search. There is sparse...

The centralized methods for connection allocation in a circuit-switched network-on-chip (NoC) based on time-division multiplexing (TDM) may pose serious performance and scalability issues in large-scale networks due to the 1) limited path search speed, 2) increasing allocation request rate at central unit and 3) the increasing communication cost between the central unit and NoC nodes. This paper tackles this problem by proposing a combined centralized-distributed approach that splits the original NoC into multiple non-overlapping logical partitions, each of them served by a dedicated NoC-Manager unit. The NoC-Manager employs fast trellis-search shortest path algorithm enabling local path search inside the associated NoC partition, while a set of NoC-Managers jointly combine the partial results in a distributed manner in order to find the most likely global path. This approach attempts to combine the benefits of distributed and centralized systems, whilst the experimental results demonstrate its high potential regarding performance and scalability improvement.

Computer has been widely used and fully researched along with the progress of electronic technology. We are no longer satisfied with simple calculation in computer application, but expect they can replace the human brain to accomplish complex work. So the artificial intelligence has emerged. There is a very classic research topic in the history of artificial intelligence — Intelligent Planning. IJCAI has hold the meetings about intelligent planning and scheduling once every two years since 1998 and the article about intelligent planning has accounted for a quarter in AAAI-99 and IJCAI-99. This paper will solve the problem of path search of intelligent car through graphplan to search path more and more intelligently, So we can save time and improve efficiency. The technology of graphplan has been proposed by Blum and Furst in 1995 and caused a great sensation in the history of intelligent planning. It is no longer taking the theorem, formula for planning and studying, but using the “Graph” instead. So some action can be executed in parallel and efficiency of plan can be greatly improved by using the method of graphplan to solve the problem.

Logistics distribution path optimisation model design is the key to ensure the smooth flow of logistics distribution path network, the logistics distribution path optimisation is designed to improve the efficiency of logistics distribution, a logistics distribution path optimisation model is proposed based on artificial intelligence algorithm. A logistics distribution path search model based on rough set theory is established. Ant colony search method is used to design the artificial intelligence algorithm of logistics distribution path optimisation. Adaptive weighting method is used to extract and schedule the information of logistics distribution path, and the shortest path optimisation method is used to optimise the route planning of logistics distribution, which can reduce the path overhead and time cost of logistics distribution. The efficiency of logistics distribution is improved. The simulation results show that this method is used to construct the logistics distribution path model, which reduces the time cost and the road cost of the logistics distribution, and improves the throughput of the logistics distribution significantly.

With the advent of mobile robots in commercial applications, the problem of path-planning has acquired significant attention from the research community. An optimal path for a mobile robot is measured by various factors such as path length, collision-free space, execution time, and the total number of turns. MEA* is an efficient variation of A* for optimal path-planning of mobile robots. RRT*-AB is a sampling-based planner with rapid convergence rate, and improved time and space requirements than other sampling-based methods such as RRT*. The purpose of this paper is the review and performance comparison of these planners based on metrics, i.e., path length, execution time, and memory requirements. All planners are tested in structured and complex unstructured environments cluttered with obstacles. Performance plots and statistical analysis have shown that MEA* requires less memory and computational time than other planners. These advantages of MEA* make it suitable for off-line applications using small robots with constrained power and memory resources. Moreover, performance plots of path length of MEA* is comparable to RRT*-AB with less execution time in the 2D environment. However, RRT*-AB will outperform MEA* in high-dimensional problems because of its inherited suitability for complex problems.

In this paper, we develop a new path search algorithm which considers all the degrees of freedom and apply it on our calculated five-dimensional potential energy surface (PES) of 236U. Asymmetric and symmetric fission paths and barriers are obtained.

Recently, due to the increased penetration of smart devices and the development of geographic information system (GIS) technology, various route guidance services for pedestrians have been developed. However, until now, pedestrian navigation services for the people with reduced mobility (people who experience discomfort in transportation) including wheelchair users, the elderly, and pregnant women have not been provided. In this study, we present a walking disturbance index methodology for searching an optimized path for the people with reduced mobility by defining the factors that affect the walking of the people with reduced mobility and deriving the weights of these factors. In future research, we expect to be able to provide a navigation system that gives an optimized path for the people with reduced mobility using this method.

Fire is one of the disasters that often occur in everyday life. There has been much research done to build a fire Simulator. In this paper, we propose a fire Simulator that is applied optimal path search algorithm to arrange the quick evacuation. This simulator considers the structure of a building and the location where the fire has initially occurred, applying it to the simulator. Especially when implementing the training simulation for firefighters, optimized evacuation path for the required virtual rescuer awaiting rescue was informed to implement more realistic firefighting training simulator. For the simulation for the test, fixed data was set to apply the shortest path search algorithm and flame smoke spread algorithm. As a result of the test, the optimized path was derived through avoiding the flame occurred from flame smoke spread algorithm and following the shortest path search algorithm. Keyword: Fire Simulator, optimal path, Greedy method, Binary programming

This study focuses on the major factors influencing the passenger flow assignment in the service network of Urban Rail Transit (URT). A passenger path search method was modeled. It also took full consideration of travelers’ route choice behavior in the service network of URT. Then the figure of service network was built, and assignment indicators of arc segments were set up and quantized. Finally, the traditional K-shortest paths algorithm had been improved based on the case study of calculating and analyzing line A. The results confirm passengers’ traveling behavior can be reflected better by service network.

In this paper, a multi-step model related to freight movements in urban areas is formalised to solve a Vehicle Routing Problem with Time Windows (VRPTW). In modelling terms, the VRPTW is formulated to consider the optimum paths between all the customers combined to determine the best vehicle routes. The optimum path search with a selective mono-criterion approach is tackled. A model for forecasting the link cost is calibrated. Some procedures (traffic assignment, real-time system measurement, reverse assignment) for estimating system performance in terms of travel cost are also proposed. In terms of procedures, the VRPTW is solved with a genetic algorithm and two different crossover operators are reported and used simultaneously. A real case application is made, comparing the results of the proposed procedure with the routes of a truck (

In China, provinces are the basic units for carrying out the highway emergency material reserve layout. From the perspective of resource distribution, this paper applies the modern location theory, operation research, the optimal path search and other technologies to establish the provincial highway emergency material layout optimization goal and to construct the related algorithm. Furthermore, Jilin Province is taken as an example to prove the validity and reliability of the algorithm. This paper tries to offer the theoretical guarantee for the provincial research of emergency materials reserve network and to provide the guideline for the related management and development.

An effective logic built-in self-test scheme aiming at reducing the area overhead of IC testing and improving the fault average is proposed, which combines strategies of linear feedback shift register (LFSR)-reseeding with test vectors applied by circuit-under-test itself (TVAC). LFSR-reseeding technology is first applied to decrease the size of test set and the number of interior feedback wires, while TVAC technology is applied to decrease the number of stored seeds. An efficient LFSR-reseeding algorithm and a modified quick judgment method for path search are proposed. Experimental results for ISCAS 85 benchmarks demonstrate that the proposed method reduces the number of interior feedback wires more than 50% on average and can achieve full fault coverage with much less groups as well as area overhead compared with previous TVACs.

For the problem of poor processing efficiency of iso-parameter tool path planning algorithm, this paper proposed a non iso-parameter trajectory planning algorithm. First established a mathematical model of five-axis machining toroid cutter, then analyzed the toroid cutter and machining surface partial differential geometric properties, proposed one kind of iso-scallop path search algorithm. Finally, using the above algorithm developed an application of trajectory planning for free-form surface and generated tool paths for such surface. The trajectories generated verified the algorithm is practicable.

In the parking lot parking path optimization, the traditional evaluation index is the shortest distance as the best index and it does not consider the actual road conditions. Now, the introduction of a more practical evaluation index can not only simplify the hardware design of the boot system but also save the software overhead. Firstly, we establish the parking lot network graph RPCDV mathematical model and all nodes in the network is divided into two layers which were constructed using different evaluation function base on the improved hierarchical A * algorithm which improves the time optimal path search efficiency and search precision of the evaluation index. The final results show that for different sections of the program attribute parameter algorithm always faster the time to find the optimal path.

Since Time Division Multiplexing (TDM) Circuit Switching (CS) has the advantage of fixed low communication latency by transmitting data over pre-established connection, it has been a popular approach to provide guaranteed service. The challenge of the CS is the fast and dynamic connection allocation particularly for networks with high connection request rates. In this paper, a high performance connection allocator for TDM CS is presented, which enables parallel multiple path search in all directions. To enhance the path search speed, the Register-Exchange technique is adopted that saves the entire survivor path sequences during search. Hence, since the backtrack is omitted, the path search time is reduced by half compared to previous forward-backtrack approaches, which can also contribute to the success rate. Our approach is compared to the state of the art centralized and distributed approaches under uniform random traffic as well as real-application benchmarks. The experiment results showed our approach can provide up to 22% higher success rate and 2X greater allocation speed against centralized approaches, and up to 33% higher success rate and 18X higher allocation speed against distributed approach.

In this paper, the signal reception environment of the satellite communications was analyzed on urban, suburban and rural environment. The correct analysis of received environment is very important in the satellite communications because the presence of various attenuation factors. Analyze attenuation factor through the simulation and that apply to each receiving environment. The urban and suburban various received sensitivity is determined according to building height and density. Moreover, attenuation occurs in rural areas due to the mountainous and vegetation. In this paper, we analysis of variety receiving environment according to movement of the ground station and the satellites can be utilized to provide stable multimedia services. Key Words : Satellite communication, Propagation, attenuation, Diffraction attenuation, Path search algorithm * 준회원, 충북대학교 전파통신공학과 ** 준회원, IM Technology *** 준회원, 국방과학연구소 **** 정회원, 충북대학교 전파통신공학과, 교신저자접수일자 2013년 1월 11일, 수정완료 2013년 2월 7일게재확정일자 2013년 2월 8일Received: 11 January 2013 / Revised: 7 February 2013 /Accepted: 8 February 2013

Determining the noncircular critical slip surface is the key problem in slope stability analysis. Essentially, this problem is a path search, and therefore, ant colony optimization is an ex...

In this paper, we designed and implemented path search system using GPS information in photo. The system extracts EXIF information included in a photo to get path information and performs path search by applying the shortest path algorithm with the use of GPS information out of information, which was extracted in this way. And then it shows the obtained path information on web by utilizing Yahoo Map API. For this, the system is designed using a method of extracting location information in a photo and path sorting through applying the shortest path algorithm. UI(User Interface) was implemented using Yahoo Map API. Based on that, we implemented path search service using photo file that is included GPS information.

According to the features of distribution network, this paper designed the implementation scheme of load transfer decision assistant system. Based on the load transfer path search method and expert system method to analysis the load transfer path, the economic index and safety index evaluate function was established by the switching times , the grid loss, impulse current, load rejection and off-limit value. Through the economic security indicators, the feasibility and risk of load transfer scheme was determined.

Acquisition of unaided weak Global Positioning System (GPS) signals requires long coherent integration time and thus all the possible navigation data bit combination paths have to be searched. In this paper, to improve the computational efficiency, the Improved Fast Modified Double-Block Zero Padding (IFMDBZP) algorithm using the Optimal Path Search Method (OPSM) is proposed instead of the FMDBZP algorithm using the All Paths Search Method (APSM). The proposed method consists of unlikely data bit combination path elimination by applying the Viterbi algorithm during each coherent integration step to improve the FMDBZP algorithm. The analyses show that the proposed OPSM can reduce the computation calculations and save memory space without suffering any loss compared to the APSM. And the longer the coherent integration time is, the more benefit one can gain from the proposed method. The simulation results also show that the IFMDPZP algorithm using the proposed OPSM has the same acquisition performance as the APSM.

In this paper a method for goods distribution optimization in urban areas is reported considering the time-dependent networks. Goods distribution optimization refers to the best tour optimization for each fright vehicle. A first step in the route design is the definition of the best path from the actual client to all others client. The traffic conditions change during the day; hence the link cost is a variable that depends on the time. The path topology and the path cost are also time-dependent and the path search must be generalized considering the time variability. In the paper a model, a solution procedure and a test in a small system are reported.

International audience; The airborne launch vehicle, studied in this article, has to find an appropriate route to reach the mission goal, considering environment requirements and system constraints, for mission safety and efficiency. A method for three-dimensional waypoint generation based on an improved version of the A* algorithm with avoidance of detected obstacles is presented in this article. As the mission proceeds, the information about the environment is regularly updated. This information is considered in the mission plan, yielding a revised sequence of waypoints, to reach one or multiple goal points, depending on their order of priority. The output of the algorithm is twofold: a dynamic waypoint generation and a shortest route refined regularly. Diverse obstacles such as turbulence zones, no-fly zones, storms, etc., are considered in the flight plan as soon as they are detected. Their locations and shapes are introduced into the path search space. The improved A* capabilities are tested via simulation in different scenarios.

The paper proposes a method that uses topological information to guide the path search in any 2D workspace. Our method generates topological paths taking into consideration the constraints of the workspace. Then, a path planner based on the A * , called Homotopic A * (HA * ), guides the path search in the workspace using the generated topological paths. Simulated and real results with an Autonomous Underwater Vehicle (AUV) are presented showing the feasibility of the proposal. Comparison with well-known path planning algorithms has also been included.

Navigation mesh is an important representation method for 3D game scene, and its generation technology directly influenced the game role's pathfinding efficiency. Firstly introduced several common representation methods for 3D game scene, and proposed an automatic generation method of navigation mesh using the Delaunay triangulation technology. Secondly, realized the path connection table according to the connectivity between discrete navigation mesh nodes, and finished the game role's path planning based on this connection table. At last, in view of the specific requirements of the game pathfinding, put forward some improvements from path search efficiency and path smooth.

Due to many limitations and deficiencies in the onshore weather routing, the onboard weather routing based on ant colony optimization (ACO) is proposed in this paper. Firstly, this work analyses the similarities and differences between weather route optimization and TSP, proposes a more appropriate heuristic function which makes ants tend to search for grids nearer to the destination. Secondly, an onboard weather routing algorithm based on ant-cycle model is established, including constraint criteria, path search strategy and smoothing strategy. At last, the history meteorological data was used to simulate the forecast information, and the feasibility and rationality of the model and algorithm is verified based on an experimental ship. As the simulation shown, the final optimal route solved in this paper can be in line with the actual situation of navigation and having practical significance.

The wiring of small mechanical and electrical equipment is one of the bottlenecks in rapid R&D and reliability. The path optimization is the essence of wiring. The paper proposed a new automatic wiring method based on improved A* algorithm, which adapts to three-dimensional path search. The cost for bending and processing was introduced into evaluating function, the rigidity factor was also introduced to improve search efficiency. The wiring module for virtual assembly is developed by UG API implementation. The results show that the method is effective.

The shortest path problem is one of the most classical algorithm issues in graph theory, aiming to find the shortest path between the two nodes in a network. It is widely used to solving the path search problems in the relevant application, including network routing algorithm, artificial intelligence, game design, and so on. This paper introduces three basic algorithms and compares them theoretically by analyzing the time and space complexity. Then, the paper discusses their performances and summarizes the best application range. At last it introduces applications of shortest path algorithm.

Reinforcement learning is applicable to a robot manipulator required to search for a path adaptable to an unknown environment. Searching for an optimal path in configuration space (C-space), i.e., joint angle space, however, takes much convergence time and memory resources. We propose two ways to overcome this problem. One is restructuring C-space by using Self-Organizing Maps (SOM). Another is doing reinforcement learning at multistage, stage 1 of which searches a path in C-space without considering obstacles, so does stage 2 with considering them near path 1, reducing searched space and convergence time. We propose further reducing searched space by adjusting the path in stage 2 to that in stage 1 through dynamic programming (DP) matching.

Movement strategies are one of the primary mechanisms underlying animal survival. Despite the impressive amount of studies on animal movement during successive stages in the life history in birds, little is known about the characteristics of movements during the post-fledging dependence period. Such a period represents a crucial phase of the life history during which individuals can show important displacements around the natal nest. Mere we present path search strategies employed by radio-tagged fledgling Eagle Owls Bubo bubo during the post-fledging dependence period (1962 locations from 41 tagged owlets). During the post-fledging dependence period, individuals show dynamic movement behaviours that might be related to the development of individuals' mobility and cognitive abilities. Immediately after leaving the nest, individuals focused their activities close to the nest, but after a few weeks individuals travelled further and faster, up to the moment that they started to disperse. At the time that the...

On-line balancing of mass and energy in a large-scale plant is today an absolutely feasible operation given the development state of the current data-acquisition systems. However, whilst the computing power is available, not all stream data are available in real-time and the programmed version of the instrumentation flow sheets in form of a graph cannot be used directly. They need to be modified so as to match the available information. Two cases are discussed: the dynamic case, where all units are seen as dynamic components and the steady-state case, where each unit is assumed to operate at steady-state. The analysis is done purely on a graph basis. The resulting algorithms are extremely simple and only require a depth-first path search algorithm. The idea is the essential part. Applying the algorithms yields simplified graphs, which contain in the dynamic case only computable quantities and the computation sequence. In the steady-state case one obtains a set of over-determined or dynamic nodes and a set of nodes that can be computed following sequence of computing computable unknown connections.

In this paper a method of set head path optimization while SMD mounting based on modeling of this path search as a transit transportation problem and realization of appropriate spreadsheet model MS Excel Solver is presented.

Pure Peer to Peer (P2P) network requires enhancing transportation of chunk video objects to the proxy server in the mesh network. The rapid growth of video on demand user brings congestion at the proxy server and on the overall network. The situation needs efficient content delivery procedure, to the video on demand viewer from the distributed storage. In general scenario, if the proxy server does not possess the required video stream or the chunk of that said video, then the same can be smoothly and rapidly streamed to the viewer. This paper has shown that multitier mesh shaped hybrid architecture composed of P2P and mesh architecture increase the number of requests served by the dynamic environment in comparison with the static environment. Optimized storage finding path search reduces the unnecessary query forward and hence increases the size of content delivery to the desired location.

SummaryWe have developed an algorithm, “MOLE,” for the rapid, fully automated location and characterization of molecular channels, tunnels, and pores. This algorithm has been made freely available on the Internet (http://mole.chemi.muni.cz/) and overcomes many of the shortcomings and limitations of the recently developed CAVER software. The core of our MOLE algorithm is a Dijkstra's path search algorithm, which is applied to a Voronoi mesh. Tests on a wide variety of biomolecular systems including gramicidine, acetylcholinesterase, cytochromes P450, potassium channels, DNA quadruplexes, ribozymes, and the large ribosomal subunit have demonstrated that the MOLE algorithm performs well. MOLE is thus a powerful tool for exploring large molecular channels, complex networks of channels, and molecular dynamics trajectories in which analysis of a large number of snapshots is required.