Journal of Advances in Computer Engineering and Technology
Volume:4 Issue: 4, Autumn 2018

Communication has become inevitably part of our day to day activities, in academic, business, banking, and other sectors. It has therefore become so important to implement good and efficient communication system. A reference point according to this research is the wireless sensor networking (WSN) system, and most important thing in communication is to be free from interference, attenuation, crosstalk, and fading. Any of these factors is a serious problem in communication system. To solve these problems, mobile and fixed nodes networks were considered for efficient operation of WSN when ZigBee technology was employed and designed using the OPNET when certain network parameters: Throughput (bits/s), load (bits/s), and end-to end delay (second) parameters from fixed and mobile networks were compared and considered for smooth operation of WSN that is free from interference, attenuation, crosstalk and fading. The network investigation and performance analysis of fixed and mobile networks were based on tree, star and mesh topologies between the two systems. After considering all the parameters for various analyses, the fixed network was considered the most suitable over the mobile network for WSN.

Biometric recognition is an automatic identification method which is based on unique features or characteristics possessed by human beings and Iris recognition has proved itself as one of the most reliable biometric methods available owing to the accuracy provided by its unique epigenetic patterns. The main steps in any iris recognition system are image acquisition, iris segmentation, iris normalization, feature extraction and features matching. EER (Equal Error Rate) metric is considered the best metric for evaluating an iris recognition system.In this paper, different parameters viz. the scaling factor to speed up the CHT (Circle Hough Transform), the sigma for blurring with Gaussian filter while detecting edges, the radius for weak edge suppression for the edge detector used during segmentation and the gamma correction factor for gamma correction; the central wavelength for convolving with Log-Gabor filter and the sigma upon central frequency during feature extraction have been thoroughly tested and evaluated over the CASIA-IrisV1 database to get an improved parameter set. This paper demonstrates how the parameters must be set to have an optimized Iris Recognition System.

Wireless body Area networks (WBANs) include a number of sensor nodes placed inside or on the human body to improve patient health and quality of life. Ensuring the transfer and receipt of data in sensitive data is a very important issue. Routing algorithms should support a variety of service quality such as reliability and delay in sending and receiving data. Loss of information or excessive data delay can lead to loss of human life. A proper routing algorithm in WBAN networks provides an efficient route with minimum delay and higher reliability for sensitive data. In this context, a routing algorithm, as it is proposed, categorizes patient data into sensitive and non-sensitive. Sensitive packets are transmitted to the destination through the shortest route to have less delay and non-sensitive packets are transmitted from other routes. Simulation shows that the proposed algorithm performs better, in terms of the throughput than the DMQoS and RL-QRP this superiority; as a result, decreases the latency of the end.

this research explores the manipulation of biomedical big data and diseases detection using automated computing mechanisms. As efficient and cost effective way to discover disease and drug is important for a society so computer aided automated system is a must. This paper aims to understand the importance of computer aided automated system among the people. The analysis result from collected data contributes to finding an effective result that people have enough understanding and much better knowledge about big data and computer aided automated system. moreover, perspective and trustworthiness of people regarding recent advancement of computer aided technologies in biomedical science have been demonstrated in this research. however, appearance of big data in the field of medical science and manipulation of those data have been concentrated on this research. Finally suggestions have been developed for further research related to computer technology in manipulation of big data, disease detection and drug discovery.

Multivariable liquid level control is essential in process industries to ensure quality of the product and safety of the equipment. However, the significant problems of the control system include excessive time consumption and percentage overshoot, which result from ineffective performance of the tuning methods of the PID controllers used for the system. In this paper, fuzzy logic was used to tune the PID parameters to control a four-coupled-tank system in which liquid level in tanks 1 and 2 were controlled. Mass Balance equation was employed to generate the transfer function matrix for the system, while a Fuzzy Inference System (FIS) file is created and embedded in fuzzy logic controller blocks, making tuning rules for the PID. Matlab R2009b simulation of the system model shows that the rise time (RT), settling time (ST), peak value (PV) and percentage overshoot (PO) for the developed DF-PID controller were 1.48 s, 4.75 s, 15 cm and 0% respectively for tank-1; and 0.86 s, 2.62 s, 10 cm and 0% respectively for tank-2, which are the smallest and best values when compared with other PID tuning methods namely: Ziegler-Nichols, Cohen-Coon and Chien-Hrones-Reswick PID tuning methods.

Policy evaluation is a process to determine whether a request submitted by a user satisfies the access control policies defined by an organization. Modality conflict is one of the main issues in policy evaluation. Existing modality conflict detection approaches do not consider complex condition attributes such as spatial and temporal constraints. An effective authorization propagation rule is needed to detect the modality conflicts that occur among the applicable policies. This work proposes a modality conflict detection model to identify the applicable policies during policy evaluation, which supports an authorization propagation rule to investigate the class-subclass relationships of a subject, resource, action, and location of a request and a policy. The comparison with previous work is conducted, and findings show the solution which considers the condition attribute (i.e. spatial and temporal constraints) can affect the decision as to whether the applicable policies should be retrieved or not which further affect the accuracy of the modality conflict detection process. Whereas the applicable policies which are retrieved for a request can influence the detection of modality conflict among the applicable policies. In conclusion, our proposed solution is more effective in identifying the applicable policies and detecting modality conflict than the previous work.