Shamim Al Mamun

A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair

This paper presents the design and implementation of a low-cost solar-powered wheelchair for physically challenged people. The signals necessary to maneuver the wheelchair are acquired from different muscles of the hand using surface electromyography (sEMG) technique. The raw sEMG signals are collected from the upper limb muscles which are then processed, characterized, and classified to extract necessary features for the generation of control signals to be used for the automated movement of the wheelchair. An artificial neural network-based classifier is constructed to classify the patterns and features extracted from the raw sEMG signals. The classification accuracy of the extracted parameters from the sEMG signals is found to be relatively high in comparison with the existing methods. The extracted parameters used to generate control signals that are then fed into a microcomputer-based control system (MiCS). A solar-powered wheelchair prototype is developed, and the above MiCS is introduced to control its maneuver using the sEMG signals. The prototype is then thoroughly tested with sEMG signals from patients of different age groups. Also, the life cycle cost analysis of the proposed wheelchair revealed that it is financially feasible and cost-effective.

Multi-priority and trusted multi-path selection algorithm for ad-hoc network

This paper presents a multi-priority and multi-path selection algorithm for heterogeneous traffic for wireless ad-hoc networks. The main objectives are achieving higher throughput, better resource utilization through load balancing and relinquish network congestion. The proposed algorithm has considered signal-to-interference plus noise ratio (SINR), available link bandwidth, link delay (transmission delay and queuing delay), trust value of a node and traffic class (such as real time and non-real time traffic) to select optimal path. The performance of the proposed Multi-Priority and Trusted Multi-Path Selection (MTMS) algorithm has been evaluated by OPNET Modeler 14.5 simulator. It is found that in terms of average throughput (bit/second) and link delay proposed MTMS algorithm outperforms ad-hoc on-demand distant vector (AODV) and dynamic source routing (DSR).

Applying Ant Colony Optimization in software testing to generate prioritized optimal path and test data

Software testing is one of the most important parts of software development lifecycle. Among various types of software testing approaches structural testing is widely used. Structural testing can be improved largely by traversing all possible code paths of the software. Genetic algorithm is the most used search technique to automate path testing and test case generation. Recently, different novel search based optimization techniques such as Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Artificial Immune System (AIS), Particle Swarm Optimization (PSO) have been applied to generate optimal path to complete software coverage. In this paper, ant colony optimization (ACO) based algorithm has been proposed which will generate set of optimal paths and prioritize the paths. Additionally, the approach generates test data sequence within the domain to use as inputs of the generated paths. Proposed approach guarantees full software coverage with minimum redundancy. This paper also demonstrates the proposed approach applying it in a program module.

Outage capacity analysis of cluster-based forwarding scheme for Body Area Network using nano-electromagnetic communication

The emergence of nano-electromagnetic communication becomes appealing for potential applications in nano-scale Body Area Network. In this work a new energy aware communication model for nano-electromagnetic communication in Terahertz Band is developed based on clustering scheme for the performance improvement of BAN. The proposed conceptual network model is used to determine channel capacity. A closed-form expression for outage probability is also derived. The approach is extended to determine outage capacity for maintaining a constant rate with a specified outage probability. Simulation shows that in term of capacity, proposed scheme outperforms the random forwarding scheme.

Trust and energy aware Cluster modeling and spectrum handoff for cognitive radio ad-hoc network

This paper presents an energy aware cluster based architecture where trust aware model is used to improve energy efficiency and spectrum handoff framework is used to reduce handoff rate and thereby improve throughput. The main objectives are trustworthy node selection, cluster head detection, transmission power reduction and increasing successful data transmission by performing handoff. A set of cognitive radio nodes form a cluster based on minimum normalized distance and sensed common free channels. Cluster Head Election Cost (CHEC) is used to determine Cluster Head and Secondary Cluster Head. It also reduces delay for different network sizes compared to random handoff process. The performance of the proposed model has been evaluated through numerical simulations. Simulation results show that the proposed scheme can effectively maximize the throughput of the Secondary User and reduce average handoff probability.

A new approach for road networks ¿ A vehicle XML device collaboration with big data

Large amount of money is lost to manipulate traffic system or road congestion worldwide every year. By providing the travel time for a specific road, traffic congestion can be minimized. Many approaches has been taken such Automatic Vehicle Identification, Loop Detectors etc. But this methods are costly. In this paper, A system is proposed that provides traffic intensity level information to the user according to recent traffic data analysis. To minimize the traffic congestion, the paper proposal is to use big data concept in this arena. This proposal develops a structure of a simple XML device which is installed on a vehicle to trace and provide information of traffic intensity. It can estimate travel times in a road network accurately. Further, according to this system anyone can develop application for business process development and increase information transfer to the local user.

Terrain Recognition for Smart Wheelchair

Research interest in robotic wheelchairs is driven in part by their potential for improving the independence and quality-of-life of persons with disabilities and the elderly. However the large majority of research to date has focused on indoor operations. In this paper, we aim to develop a smart wheelchair robot system that moves independently in outdoor terrain smoothly. To achive this, we propose a robotic wheelchair system that is able to classify the type of outdoor terrain according to their roughness for the comfort of the user and also control the wheelchair movements to avoid drop-off and watery areas on the road. An artificial neural network based classifier is constructed to classify the patterns and features extracted from the Laser Range Sensor (LRS) intensity and distance data. The overall classification accuracy is 97.24 % using extracted features from the intensity and distance data. These classification results can in turn be used to control the motor of the smart wheelchair.

Innovative approach in web application effort & cost estimation using functional measurement type

Software cost models and effort approximations support project supervisors to distribute resources, control budgets and agenda and develop modern practices, leading to projects completed on time and within financial plan. If cost and effort are determined suspicious in software projects, suitable occasions can be missed; whereas expectant predictions can be affected to some resource losing. In the context of web development, these issues are also vital, and very challenging given that web projects have short schedules and very fluidic opportunity. Since software projects are continually changed in nature, earlier projects may not necessarily cover all aspects of a new project when used as a basis for cost estimation. Preliminary software estimation models are constructed on regression analysis or mathematical sources. This paper aims to propose an approach to develop the correctness of software effort and cost estimation using the structure of data set of a web application. All the measures collected, apart from total effort, were introduced using the original web hypermedia applications to ensure that functional measurement types were precisely measured.

Interference Temperature Constraint-based Radio Resource Allocation for the Network Coded Cognitive Cooperative Network (NCCCN)

Demand for higher data rate wireless applications has led to scarcity in radio frequency spectrum. Spectrum access achieves near-optimal spectrum utilization efficiency with the advent of cognitive radio technology. In cognitive radio network (CRN), each cognitive user, also called secondary user (SU), senses and uses radio spectrum opportunistically while regulating the interference constraint. This article focuses the radio resource allocation considering interference temperature constraints for the network coded cognitive cooperative network (NCCCN). Analog network coded (ANC) Orthogonal-Frequency-DivisionMultiplexing (OFDM) improves the capacity of the cognitive cooperative network (CCN). Moreover, CCN enhances the spectrum utilization efficiency. Power allocation optimization problems have been formed that maximize the data transmission rate of NCCCN under the total transmit and peak-interference powers or the total transmit and average-interference powers. The spectral efficiency of the proposed network is compared with the spectral efficiency of CCN without ANC. Simulation results show that the proposed NCCCN enhances spectral efficiency in compared to the CCN without ANC.

Single Laser Bidirectional Sensing for Robotic Wheelchair Step Detection and Measurement

Research interest in robotic wheelchairs is driven in part by their potential for improving the independence and quality-of-life of persons with disabilities and the elderly. Moreover, smart wheelchair systems aim to reduce the workload of the caregiver. In this paper, we propose a novel technique for 3D sensing of the terrain using a conventional Laser Range Finder (LRF). We mounted this sensing system onto our new six-wheeled robotic step-climbing wheelchair and propose a new step measurement technique using the histogram distribution of the laser data. We successfully measure the height of stair steps in a railway station. Our step measurement technique for the wheelchair also enables the wheelchair to autonomously board a bus. Our experiments show the effectiveness and its applicability to real world robotic wheelchair navigation.