Scientia Iranica
Volume:22 Issue: 4, 2015

This study implemented the hand gesture digit recognition function by using the Kinect motion sensor. This interactive motion-sensing technology was employed to track, record, and convert the trajectories of handwritten numerals in space into corresponding shapes of digits on the plane. Subsequently, the feature matching method was used to achieve digit recognition. In the recognition process, first binarization and Hilditch thinning algorithm were performed on the region for recognition, and the segmentation algorithm proposed by G.E.M.D.C. Bandara etc. was used to perform segmentation of the region after thinning. This paper proposes the improvement of the conditions of the arc type of the discriminant to achieve feature extraction and enhance the digit recognition rate.

This paper is intended to understand therelationship between airport access road hourly traffic and airport users’ trip characteristics. Amathematical model is developed inorder to provide a foundation for planning airport facility and enhancing existing services. From the results, it can beconcluded that significant relationships exist between airport operation and traffic volume in airport access road.It was found that the proposed model has a good prediction capability for the traffic volume in Incheon International Airport Expressway on hourly basis. This model can be used to predict the number of vehicles queued at airport entrances intersection or toll plaza, predict optimum toll lane staffing, and analyze the level of congestion on the roadway for different levels of air passenger demand in future.

To date, many vehicular ad hoc network unicast routing protocols have been proposed to support efficient packet transmission between vehicles in urban environments. However, when there is insufficient vehicle density during non-rush hour times, the vehicular ad hoc network is often intermittently connected. These unicast routing protocols therefore perform poorly when forwarding packets over this vehicular disruption tolerant network. This paper adopts the controlled replication approach in a proposed IG-Ferry routing protocol to spray a limited number of packet copies, denoted by the packet token values, to relay vehicles in a vehicular disruption tolerant network. We then identify three kinds of relay vehicles, i.e., direct buses, non-direct buses and private cars, according to their travel itineraries. Based on the proposed delay evaluation function for the three types of intermediate vehicles, the IG-Ferry packet spraying mechanism, instead of the traditional binary spraying one, can efficiently spray appropriate packet tokens to vehicles. Finally, intensive NS2 simulations are conducted using the realistic Shanghai city vehicle traffic trace, IEEE 802.11p protocol with EDCA and Nakagami radio propagation model to show that IG-Ferry outperforms three well-known VDTN routing protocols, in terms of average packet delivery ratios, end-to-end transmission delays and packet replication overheads with respect to various combinations of five communication parameters.

Some practices arising in sport club industry include: (1) most sport clubs run their business by taking membership programs and divide their memberships into several distinct classes by applying restrictions, (2) they operate in chain business mode and allow their members to enjoy their services at any aliate, and (3) they usually recruit members as many as possible to increase their revenues. Due to the limitless acceptance of customers'' subscriptions, users usually face the situation that their preferred equipments are occupied. Thus, in order to improve revenues and enhance corporate image, sport clubs can not only pay attention to the supply management of tness equipment allocation but also e orts on the demand management in terms of member recruiting limit. This study develops a mathematical model for determining the resource allocation of tness equipments and the member recruiting limit decisions for a chain tness club. The model is a constrained nonlinear integer problem, and in this paper a computational approach is proposed to solve the considered problem. Numerical results show that the proposed heuristic approach can eciently obtain compromised solutions.

The permutation flow shop problem (PFSP) has been applied to many types of problems. The PFSP is an NPhard permutation sequencing scheduling problem. A local search with simulated annealing scheme involving two phases is proposed in this investigation for solving PFSP. First, for lowering computation complexity, a simple insertion local search is applied to generate the solution of the PFSP. Second, two non-decreasing cooling temperature driven simulated annealing (SA) named steady SA and reheating SA are employed to maintain successive exploration or exploitation in the solution space. The steady SA maintains the same temperature and keeps the same search behavior and thereby allows the neighbors of the worse solutions to be explored, consequently increasing the chances of finding better solutions, while the reheating SA increases the temperature and increases the exploration ability. The most important feature of the proposed method is its simple implementation and low computation time complexity. Experimental results are compared with other state-of-the-art algorithms and reveal that the proposed simple insertion with steady SA (SI-SSA) method is able to efficiently yield the best permutation schedules.

The use of cold-formed steel for primary load bearing members in low and medium rise buildings has become an increasingly popular form of construction. The design of connections between these members is crucial to the overall structural integrity of such buildings. However, for beam-to-column joint design, recent codes of practice show ambiguity in the mechanical behaviour. Further research is required to investigate the strength, stiffness and ductility prediction of such connections. This paper addresses these concerns by proposing simplified formulas for the moment-rotation behaviour of light steel frames with bolted top-seat flange cleat joints. A finite element study is presented which is validated against laboratory experimental tests on cold-formed steel arrangements. The validated model is used within a parametrical study to investigate several additional geometrical parameters that are not included in the experimental works. An exponential equation has been proposed for large deformation of top-seat flange cleat joint under monotonic vertical load. The predictions using the equations are compared to the design codes (BS EN1993-1-8) and experimental data. From the comparison, the proposed equation can improve the BS EN1993-1-8 prediction from 168.08% difference compared to experimental results, to 7.09% difference. The new proposed model gives a safe design for top-seat flange cleat joint in cold-formed steel light frame construction.

A novelmultiple objective fitness function (OFF) is proposed for transmission parameter optimization in dynamic spectrum access. The proposed scheme consists of two phases: Four OFFs are individually designed in the first phase, where the spectrum band index is additionally considered unlike the conventional OFFs. In the second phase, then, the individual OFFs are combined to form a multiple OFF, where the individual OFFs may be differently stressed depending on the transmission scenario of interest. In simulation results, finally, the proposed multiple OFF is found to provide the optimal parameter set for transmission under various types of scenarios.

In this paper, we investigate the bi-objective grid patrol routing problem (BGPRP) in which multiple patrol vehicles have to cooperatively patrol several nodes for a given specific time during a certain planning horizon in a grid map. The BGPRP is an NP-hard problem and an extended application of periodic vehicle routing problem (PVRP). However, unlike PVRP, in addition to minimizing the total routing distance, the considered BGPRP also aims to maximize the routing coverage of lanes. The BGPRP involves both the combination and permutation of nodes simultaneously. In this paper, an efficient encoding scheme is developed to tackle both the combination and the permutation of nodes simultaneously, and then we apply an immune based evolutionary approach for solving the BGPRP with the objective of minimizing total routing distance. Finally, an integer programming approach is utilized to maximize the routing coverage of lanes. Numerical results of multiple patrol vehicles in a grid map show the performance of the approach.

Advances in information and communication technology have made mobile devices very easy for people to share and exchange information. However, such exchanges of data may require privacy, or users may not want that data to be publically accessible. Data exchange security has therefore also become very important in the development of such devices, and, indeed, in mobile wireless network environments, in which the secure exchange of data between mobile devices has become an important issue. This study proposes a novel approach for the secure exchange of data between discrete mobile devices. Cryptographic techniques, including advanced encryption standard, triple data encryption standard, and data encryption standard, are enforced in a data exchange process, and a popular android-based mobile device is used to test the designed mechanism for secure data exchange. The experiment results show the encryption/decryption time of each cryptographic technique working on the android-based mobile device. A comparison of the experiment results also shows which cryptographic technique is appropriate for data exchange between discrete android-based mobile devices. The contribution of this work is to explore the above data security issue, and to recommend an appropriate cryptographic technique for data exchange between discrete mobile devices.

Identifying hazardous locations on highways is a fundamental step in safety improvement programs and projects since it provides decision makers with a basis for allocating budgets and other resources in a cost-effective manner. Extensive research has been conducted to identify such locations. However, most studies have ignored the spatial characteristics of crash occurrences and the relative significance of injury severity. In this study, we develop a procedure for identifying hazardous locations on expressways based on geographically weighted regression(GWR)and equivalent property damage only (EPDO). GWR is a spatial regression method that can reflect spatial dependency and heterogeneous relationships between crash occurrences and other explanatory variables. EPDO is a comprehensive measure of crash occurrences weighted by the level of injury severity. We apply this procedure to a case study in Gyeongbu Expressway in Korea. The findings from our case study show that the procedure can identify hazardous locations on roadways while reflecting crash frequency and injury severity simultaneously with the comprehensive measure.

Performance degradation assessment and prediction of hydraulic servo systems has attracted increasing attention in recent years. This study proposes a performance degradation assessment and prediction method based on mean impact value （MIV）, Mahalanobis distance (MD), and Elman neural network. First, a state observer based on radial basis function (RBF) is designed to calculate the residual error between the actual and estimated outputs, andtypical time-domain features, such as root mean square (RMS), peak value, and kurtosis, are extracted. Second, the MIV analysis based on BP neural network is applied to evaluate the sensitivity of each extracted feature, and the selected optimal features are employed to construct the Mahalanobis space for normal states. Third, the MD between the most recent state and the constructed space of normal state is calculated, which can be normalized into a confidence value so as to assess the performance. Finally, an Elman neural network is used to predict the degradation trend. The proposed method is proven to be effective by a simulation model with the commonly occurring faults.

Today’s software systems demand increasing tremendously for sophisticated software engineering processes. However, there are a multitude of different development and each have various advantages and disadvantages, some of which relate to the problem domain or the development context. Computer software development processes have to pass from many faces to complete the development. There are many ways to solve a single problem in software development. Sometimes, in Structural engineering, developer is not able to decide which process will suit to that particular problem or we can say that selecting a good process is a big issue in Structural Process Software engineering. The problem of selecting a good candidate method is a big issue in structural process engineering. The solution of such kind of problem can be found in the work to be done, and the task to be performed by the Operational process rather than process structure. This paper introduces the notion of process operationality and proposes ‘process architecture’ to represent this operationality. Thus, Structural Process Engineering (SPE) becomes Operational Process Engineering (OPE). Operationally close process architecture is selected, adapted, enhanced, and restricted as needed. The task of construction handles the putting together of process features and structuring the new process.

Arti cial Neural Networks (ANNs) are applied to many complex real-world problems, ranging from image recognition to autonomous robot control. However, to design a neural network that can implement special task, it is necessary to select an appropriate biological neuron model, meanwhile, good learning algorithm should be adopted to achiee the expected goal. euroevolution is a form of machine learning that uses Evolutionary Algorithms (EAs) to train ANNs. EAs, for the learning algorithm used by neural networks, can provide alternative and complementary solution, which can avoid the frequently happened issues of getting stuck in local minimum«during the iteration process made by gradient-based learning algorithms. In this paper, a method using Hybrid PSO-based Learning Algorithm (HPLA) to evolve the connection weights and network parameters of Binary-Weights Neural Network (BWNN) will be introduced. The extracted knowledge from trained BWNN can then be used to construct high-speed shift-and-add based Color Space Converter (CSC) hardware architecture. The experimental results in this research also show that the performance of implemented hardware architecture is good at RGB to YCbCr color space converting, and it also has the advantages of high-speed and lowcomplexity.

For social organizations, formal communication transmits goals, policies, and directions, while informal communications are supplement to the formal structure filling organizational gaps and maintaining the linkages. This communication model has been researched and named opinion dynamics for some years. However, the relations between formal and informal structures have not been fully revealed. To tackle this problem, this paper builds a hierarchical command and control (C2) organization network, introduces the basic opinion dynamics model and proposes the coupled network composed of formal and informal network. To study the communication impact of informal network on formal network, various numbers of groups and parameter settings (tolerance and influence) of the two networks are studied compared to standalone formal organizations. Experiment results show that informal organization has communication converging impact on opinion evolutions in military C2 network.