Security systems and navigators have always been a necessity of human’s life. The developments of advanced electronics have brought revolutionary changes in these fields. In this paper, we will present a vehicle tracking system that employs a GPS module and a GSM modem to find the location of a vehicle and offers a range of control features. To complete the design successfully, a GPS unit, two relays, a GSM Modem and two MCU units are used. There are five features introduced in the project. The aim of this project is to remotely track a vehicle’s location, remotely switch ON and OFF the vehicle’s ignition system and remotely lock and unlock the doors of the vehicle. An SMS message is sent to the tracking system and the system responds to the users request by performing appropriate actions. Short text messages are assigned to each of these features. A webpage is specifically designed to view the vehicle’s location on Google maps. By using relay based control concept introduced in this paper, number of control features such as turning heater on/off, radio on/off etc. can be implemented in the same fashion.

Online Social Networks (OSN) are considering one of the most popular internet applications which attract millions of users around the world to build several social relationships. Emerging the Web 2.0 technology allowed OSN users to create, share, or exchange types of contents in a popular fashion. The other hand, OSN are considering one of the most popular platforms for the intruders to spread several types of OSN attacks. Creating fake profiles for launching cloning attacks is one of the most risky attacks which target Users' profiles in Online Social Networks, the attacker seek to impersonate user's identity through duplicating user's online presence in the same or across several social networks, therefore, he can deceive OSN users into forming trusting social relations with his created fake profiles. These malicious profiles aim to harvest sensitive user's information or misuse the reputation of the legitimate profile's owner, as well as it may be used as a spy profiles for other criminal parties. Detecting these fake profiles still represent a major problem from OSN Security and Privacy point of view. In this paper we introduced a theoretical framework which depends on a novel topology of a social graph called Trusted Social Graph (TSG) which used to visualize trusted instances of social communications between OSN users. Another contribution is a proposed detection model that based on TSG topology as well as two techniques; Deterministic Finite Automaton (DFA) and Regular Expression. Our proposed detection model used to recognize the stranger instances of communications and social actions that performed using fake profiles in OSN.

The presence of malicious nodes in the ad hoc and sensor networks poses serious security attacks during routing which affects the network performance. To address such attacks, numerous researchers have proposed defense techniques using a human behavior pattern called trust. Among existing solutions, direct observations based trust models have gained significant attention in the research community. In this paper, the authors propose a Self Adaptive Trust Model (SATM) of secure geographic routing in wireless sensor networks (WSNs). Unlike conventional weight based trust models, SATM intelligently assigns the weights associated with the network activities. These weights are applied to compute the final trust value. SATM considers direct observations to restrict the reputation based attacks. Due to the flexible and intelligent weight computation, SATM dynamically detects the malicious nodes and direct the traffic towards trustworthy nodes. SATM has been incorporated into Greedy Perimeter Stateless Routing (GPSR) protocol. Simulation results using the network simulator NS-2 have shown that GPSR with SATM is robust against detecting malicious nodes.

Algorithms inspired from natural phenomena are seem to be efficient to solve various optimization problems. This paper investigates a new technique inspiring from the animal group living behavior to solve traveling salesman problem (TSP), the most popular combinatorial optimization problem. The proposed producer-scrounger method (PSM) models roles and interactions of three types of animal group members: producer, scrounger and dispersed. PSM considers a producer having the best tour, few dispersed members having worse tours and scroungers. In each iteration, the producer scans for better tour, scroungers explore new tours while moving toward producer’s tour; and dispersed members randomly checks new tours. For producer’s scanning, PSM randomly selects a city from the producer’s tour and rearranges its connection with several near cities for better tours. Swap operator and swap sequence based operation is employed in PSM to update a scrounger towards the producer. The proposed PSM has been tested on a large number of benchmark TSPs and outcomes compared to genetic algorithm and ant colony optimization. Experimental results revealed that proposed PSM is a good technique to solve TSP providing the best tours in most of the TSPs.

Image fusion is a process of combining data from multiple sources to achieve refined or improved information for making decisions. It has many applications. When we use images with a similar acquisition time, the expected result is to obtain a fused image that retains the spatial resolution from the panchromatic image and color content from the multi-spectral image. In recent time different methods have been developed. These methods are both in spatial domain and in wavelet domain. Out of these two the wavelet domain based methods are more suitable as they are capable to handle the spatial distortion produced by the spatial domain. In this paper the proposed method is compared with principle component analysis, discrete cosine transform and also with biorthogonal wavelet transform in which bilateral filter and adaptive histogram is not present. This comparison is on the bases of different parameters. Biorthogonal wavelet transform is capable to preserve edge information and hence reducing the distortions in the fused image. It has two important properties wavelet symmetry and linear phase which are not present in spatial domain. The performance of the proposed method has been extensively tested on several pairs of multi-focus and multimodal images. Experimental results show that the proposed method improves fusion quality by reducing loss of significant information available in individual images.

In this paper we introduce the classical EOQ model with a linear trend of time-dependent demand having no shortages using the concept of fractional calculus. The application of fractional calculus has been already used in classical EOQ model where the demand is assumed to be constant. In this present article fractional differential calculus can be used to describe EOQ model with time-dependent linear trend of demand to develop more generalized EOQ model. Here, we want to discuss more deeply its role as a tool for describing the traditional classical EOQ model with time dependent demand.

Computer vision applications face various challenges while detection and classification of objects in real world like large variation in appearances, cluttered back ground, noise, occlusion, low illumination etc.. In this paper a Wavelet based Histogram of Oriented Gradients (WHOG) feature descriptors are proposed to represent shape information by storing local gradients in image. This results in enhanced representation of shape information. The performance of the feature descriptors are tested on multiclass image data set having partial occlusion, different scales and rotated object images. The performance of WHOG feature based object classification is compared with HOG feature based classification. The matching of test image with its learned class is performed using Back Propagation Neural Network (BPNN) algorithm. Proposed features not only performed superior than HOG but also beat wavelet, moment invariant and Curvelet.

During a change in operating condition, oscillations of small magnitude and low frequency often persist for long periods of time and in some cases even present limitations on power transfer capability. Generators in power systems are equipped with automatic voltage regulator (AVR) to control terminal voltage. It is known that AVR has a detrimental impact upon the dynamic stability of the power system. Power system stabilizers (PSS) are widely used to generate supplementary control signals for the excitation system in order to damp out low-frequency oscillations (LFOs). In this paper proportional-derivative power system stabilizer (PD-PSS) used to damping LFO after tuning the gains of the PSS by using PSO. The damping boundary condition of PSO technique is modified to improve its performance in the tuning and optimization process. Simulation studies performed on a typical single-machine infinite-bus (SMIB) system used in MATLAB Simulink program. Assessing the performance of the proposed modified PSO based PD-PSS with Speed deviation (∆ω) as an input signal using eigenvalue analysis. The proposed PSO based PD-PSS is evaluated and examined under different operating conditions and inertia constant each one of them applied with two test cases small disturbance and short circuit. A comparative study between the proposed PSO based PD-PSS, original PSO based PD-PSS, and lead-lag PSS is done in this work. The results ensure the superiority, the effectiveness, and the robustness of the proposed PSS over the other techniques.