In traditional market, buyers are not only moving from one place to another, but also interacting with traders to purchase their products. When a buyer interacts with a trader, he blocks some space in the corridor. Besides, while buyers are walking, they may be attracted by non-preferred traders, though they may have preferred traders. These situations have not been covered in most existing crowd simulation models. Hence, these existing models cannot be directly implemented in traditional market environments since they mainly focus on crowd members’ movement. This research emphasizes on a crowd model that includes simplified movement and unplanned purchasing models. This model has been developed based on intelligent agent concept, where each agent represents a buyer. Two traditional markets are used for simulation in this research, namely Gedongkuning and Ngasem, in Yogyakarta, Indonesia. The simulation shows that some places are visited more frequently than others. Overall, the simulation result matches the situation found in the real world.

Cloud users usually have different preferences over their applications that outsource to the cloud, based on the financial profit of each application's execution. Moreover, various types of virtual machines are offered by a cloud service provider with distinct characteristics, such as rental prices, availability levels, each with a dif-ferent probability of occurrence and a penalty, which is paid to the user in case the virtual machine is not availa-ble. Therefore, the problem of application scheduling in cloud computing environments, considering the risk of financial loss of application-to-VM assignment becomes a challenging issue. In this paper, we propose a risk-aware scheduling model, using risk analysis to allocate the applications to the virtual machines, so that, the ex-pected total pay-off of an application is maximized, by taking into account of the priority of applications. A run-ning example is used through the paper to better illustrate the model and its application to improve the efficiency of resource assignment in cloud computing scenarios.

Combined with the transmission ratio charac-teristics of forklift steering-by-wire (SBW) system, through the application of fuzzy control technology, the variable transmission ratio function is designed based on the steering handle angle and vehicle speed, and simula-tion analysis of sinusoidal steering is done at low-speed and high-speed. Simulation results show that the fuzzy variable transmission ratio control can make forklift steering light & sensitive at low-speed and steering steady & heavy at high speed, also it can improve the operation stability and reduce the driver’s load. Discuss the relationship between yaw rate and forklift handling stability, propose the yaw rate feedback control strategy based on the fuzzy variable transmission ratio control, and design a fuzzy self-adaptive PID controller. Simula-tion results show that the SBW system based on the fuzzy variable transmission ratio control with yaw rate feedback can accurately and quickly track the desired yaw rate, and reduce or even eliminate the overshoot phenomenon, improve the forklift dynamic performance.

We convert polynomial function of degree nth into imprecise form to obtain an important point called conversion point. For some particular region, we collect the finite number of data points to obtain the most economical function called imprecise function. Conversion point of the functions is shown with the help of MUPAD graph. Further we study the area of the imprecise function occurred by the multiplication of sine function to know how much variation of the imprecise functions are obtained for the respective intervals. For different imprecise polynomial we study level of the rate of convergence.

This paper presents the technique for accelerating 3-Satisfiability (3-SAT) logic programming in Hopfield neural network. The core impetus for this work is to integrate activation function for doing 3-SAT logic programming in Hopfield neural network as a single hybrid network. In logic programming, the activation function can be used as a dynamic post optimization paradigm to transform the activation level of a unit (neuron) into an output signal. In this paper, we proposed Hyperbolic tangent activation function and Elliot symmetric activation function. Next, we compare the performance of proposed activation functions with a conventional function, namely McCulloch-Pitts function. In this study, we evaluate the performances between these functions through computer simulations. Microsoft Visual C++ 2013 was used as a platform for training, validating and testing of the network. We restrict our analysis to 3-Satisfiability (3-SAT) clauses. Moreover, evaluations are made between these activation functions to see the robustness via aspects of global solutions, global Hamming distance, and CPU time.

Research projects are graduation requirements for many university students. If students are arbitrarily assigned project supervisors without factoring in the students’ preferences, they may be allocated supervisors whose research interests differ from theirs or whom they just do not enjoy working with. In this paper we present a genetic algorithm (GA) for assigning project supervisors to students taking into account the students’ preferences for lecturers as well as lecturers’ capacities. Our work differs from several existing ones which tackle the student project allocation (SPA) problem. SPA is concerned with assigning research projects to students (and sometimes lecturers), while our work focuses on assigning supervisors to students. The advantage of the latter over the former is that it does not require projects to be available at the time of assignment, thus allowing the students to discuss their own project ideas/topics with supervisors after the allocation. Experimental results show that our approach outperforms GAs that utilize standard selection and crossover operations. Our GA also compares favorably to an optimal integer programming approach and has the added advantage of producing multiple good allocations, which can be discussed in order to adopt a final allocation.

Nowadays with the increase of demand in multimedia communication, a reliable and error-free wireless communication system is the need of the hour. MC-CDMA is being investigated as a potential radio technology to provide fourth generation (4G) and fifth generation (5G) cellular mobile services. Narrowband interference (NBI) signals corrupts the subcarriers of MC-CDMA system and as a result its performance degrades. All the available NBI elimination methods uses some kind of filters and other circuitry prior to the demodulator (receiver) to filter out NBI. So addition of extra hardware to the system makes the system complex and slow. Moreover CDMA based systems are affected by digital NBI which gets superimposed with wideband spread spectrum signal. Multiuser detection could be an efficient technique to suppress NBI and multiple access interference (MAI). Computational complexity of opti-mum multiuser detector is an impediment in the way of an efficient multiuser detector. In this paper we propose a particle swarm optimization (PSO) based optimum multiuser detector to eliminate NBI. Simulation results show that performance of proposed PSO based multiuser detector is capable of eliminating NBI with much lesser amount of computational complexity.

Identification of people among each other has always been a tough and challenging task for the researchers. There are many techniques which are used for identifying a person but biometric technique is the standard one which allows us for online identification of individuals on the basis of their physiological and behavioral features. The veins based systems include finger veins, face veins, palm veins, head veins, heart veins, iris, palatal veins of the rogue etc. The multi-veins based systems use the veins of different physiological traits for identifying a person.
This paper illustrates an overview of veins based personal identification systems. The performance of different single and multi-veins based identification systems are analyzed in this paper. The features like reliability, security, accuracy, robustness and long term stability along with the strengths and weaknesses of various veins based biometric approaches were taken into considerations while analyzing the results of existing research papers published so far. At last the future research directions in the field of veins based identification systems have also been outlined.