Mohsin Jamil

Delay-Sensitive routing schemes for underwater acoustic sensor networks

Underwater Acoustic Sensor Networks (UASNs) offer their practicable applications in seismic monitoring, sea mine detection, and disaster prevention. In these networks, fundamental difference between operational methodologies of routing schemes arises due to the requirement of time-critical applications; therefore, there is a need for the design of delay-sensitive techniques. In this paper, Delay-Sensitive Depth-Based Routing (DSDBR), Delay-Sensitive Energy Efficient Depth-Based Routing (DSEEDBR), and Delay-Sensitive Adaptive Mobility of Courier nodes in Threshold-optimized Depth-based routing (DSAMCTD) protocols are proposed to empower the depth-based routing schemes. The performance of the proposed schemes is validated in UASNs. All of the three schemes formulate delay-efficient Priority Factors (PF) and Delay-Sensitive Holding time ( DSH T ) to minimize end-to-end delay with a small decrease in network throughput. These schemes also employ an optimal weight function ( W F ) for the computation of transmission loss and speed of received signal. Furthermore, solution for delay lies in efficient data forwarding, minimal relative transmissions in low-depth region, and better forwarder selection. Simulations are performed to assess the proposed protocols and the results indicate that the three schemes largely minimize end-to-end delay along with improving the transmission loss of network.

4G: The future mobile technology

With the rapid growth of user demands, and the limitations of third generation (3G) mobile communication systems, it is expected that fourth generation (4G) mobile systems are likely to reach the consumer market in another 4-5 years. 4G systems are expected to become a platform capable of providing increased bandwidth, higher data rates, and greater interoperability across communication protocols, and user friendly, innovative, and secure applications. This system will primarily focus on seamlessly integrating the existing systems like GSM, wireless LAN, and Bluetooth. This paper describes modulation scheme, different technologies, and network architectures that support 4G mobile systems. Challenges and some applications will also be presented. At last recommendations will be followed by conclusion.

Modeling mobility and psychological stress based human postural changes in wireless body area networks

Proposed model gives mobility behavior of human body in WBAN.5 different postures of human body (i.e. standing, walking, running, sitting and laying).Posture transition according to markov model.Proposed model shows different mobility behavior in each posture.Mobility model is implemented in 2 routing schemes and 9 performance parameters. Mobility models play a vital role on the performance accuracy of simulations in Wireless Body Area Networks (WBANs). In this article, we propose a mobility model for the movement of nodes according to the posture patterns formed either because of psychological stress or any kind of mobility. During routine activities, body exhibits different postures like, standing, sitting, laying, etc. We form a mathematical model for the movement of nodes according to the posture pattern. In walking and running postures, the nodes placed on the limbs move in a defined trajectory repeatedly. In these postures, the nodes placed on trunk of the body are minimally mobile. On the other hand, in sitting and laying positions, the movement of limbs is nondeterministic. However, we can locate an area in which the nodes presence is most probable. Postures change from one state to another depending upon probabilities. During movement, the distance between nodes and sink is changed. As energy consumption, delay, and path loss depend on distance, so they also change due to mobility. We implement the proposed mobility model in multi-hop and forwarder based routing techniques. In multi-hop routing technique, nodes send data to the sink using neighboring nodes. Whereas, in forwarders based scheme, two forwarders are selected in each round to transmit, alongwith their own data, the received data of neighboring nodes. Simulation results show that forwarder based routing schemes has increased stability period, network lifetime and throughput.

Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy

Computer-assisted analysis of electroencephalogram (EEG) has a tremendous potential to assist clinicians during the diagnosis of epilepsy. These systems are trained to classify the EEG based on the ground truth provided by the neurologists. So, there should be a mechanism in these systems, using which a systems incorrect markings can be mentioned and the system should improve its classification by learning from them. We have developed a simple mechanism for neurologists to improve classification rate while encountering any false classification. This system is based on taking discrete wavelet transform (DWT) of the signals epochs which are then reduced using principal component analysis, and then they are fed into a classifier. After discussing our approach, we have shown the classification performance of three types of classifiers: support vector machine (SVM), quadratic discriminant analysis, and artificial neural network. We found SVM to be the best working classifier. Our work exhibits the importance and viability of a self-improving and user adapting computer-assisted EEG analysis system for diagnosing epilepsy which processes each channel exclusive to each other, along with the performance comparison of different machine learning techniques in the suggested system.

Human tracking by a mobile robot using 3D features

Detection and Tracking of human being is a very important problem in Computer Vision. Human robot interaction is a very essential need for service robots where robots are required to detect and track human beings in order to provide the required service. In this paper we present an improved novel approach for tracking a target person in crowded environment. We used multi-sensor data fusion approach by combining the data of stereo camera and laser rangefinder (LRF) to perform human tracking. The system gathers the features of human upper body, face and legs in the target person selection phase and then the robot will start following the target person. Camera is used for upper body and face detection while laser rangefinder is used for gathering legs data. Template matching and triangulation is done in order to get the dimensions of upper body and face. Target person tracking is done using Cam shift tracker. Thus our method presents a novel approach that uses all these techniques to track a target person in a crowded environment.

Design and analysis of repetitive controllers for grid connected inverter considering plant bandwidth for interfacing renewable energy sources

The plant bandwidth plays a vital role in the design of any feedback controller. Its importance is more for repetitive controller (RC) based systems because it is required to provide higher gains at desired frequencies. This paper discusses design of the repetitive controller (RC) for a LCL filter based grid connected inverter with special emphasis on plants bandwidth. The relation between plant bandwidth and the capacitor value of the LCL filter is also investigated. The effectiveness of the repetitive controller for different plant bandwidths is tested in the presence of different utility voltage harmonics and uncertainty in utility impedance. The results show that a suitable value of the capacitor in LCL filter must be selected in order to provide enough bandwidth for the repetitive controller to be effective.

A Novel Dual-Loop Control Scheme for Payload Anti-Swing and Trolley Position of Industrial Robotic 3DOF Crane

In this paper, we propose a novel dual-loop control scheme (DLCS). We did not see such investigation of DLCS in the previous research work. DLCS scheme is a combination of classical PID and advanced state feedback control techniques. The proposed technique is used to control swing angle and trolley position of a 3DOF crane. Extensive simulations have been carried out using MATLAB / Simulink and practically validated on a Quanser 3DOF crane system. Experimental results indicate that the proposed DLCS control scheme improves crane operation by damping the payload oscillations. The scheme also smoothen the trolley motion. Our suggested technique provides better performance in terms of payload oscillations comparing to the classical PID.

An appraisal of nodules detection techniques for lung cancer in CT images

Abstract Lung cancer has a five-year survival rate of 17.7% which increases to 54.4% when it is diagnosed at early stages. Automated detection techniques have been developed to detect and diagnose nodules at early stages in computer tomography (CT) images. This paper presents a systematic analysis of the recent nodules detection techniques with the goal to summerize current trends and future challenges. The relevant papers are selected from IEEEXplore, science direct, PubMed, and web of science databases. Each paper is critically reviewed in order to summarize its methodology and results for further analysis. Our analyses reveal that several methods show potential progress in the field but still require an improvement to overcome many challenges like, high sensitivity with low false positive (FP) rate, detection of different nodules based on their size, shape, and positions, integration with electronic medical record (EMR) and picture archiving and communication system (PACS), and providing robust techniques that are successful across different databases. To overcome these challenges and developing a robust computer aided detection (CADe) system, it is believed that collaborative work is required among the developers, clinicians and other relating parties in order to understand particular issues and needs of a CADe system and develop automatic techniques to overcome these challenges with high processing speed, low cost of implementation and with software security assurance.

Classification of left/right hand movement from EEG signal by intelligent algorithms

Brain Computer interface (BCI) shown enormous ability to advance the human way of life. Furthermore its application is also targeting the disabled ones. In this research, we have implemented a new approach to classify EEG signals more efficiently. The dataset used for this purpose is from BCI competition-II 2003 named Graz database. Initial processing of the EEG signals has been carried out on 2 electrodes named C3 & C4; after that the bi-orthogonal wavelet coefficients, Welench Power Spectral Density estimates and the average power were used as a feature set for classification. We have given a relative study of currently used classification algorithms along with a new approach for classification i.e. Self-organizing maps (SOM) based neural network technique. It is used to classify the feature vector obtain from the EEG dataset, into their corresponding classes belong to left/right hand movements. Algorithms have been implemented on both unprocessed features and processed reduced feature sets. Principal component Analysis (PCA) has been used for feature reduction. Measured data revealed that the maximum classification accuracy of 84.17% on PCA implemented reduce feature set has been achieved using SOM based classifier. Furthermore, the classification accuracy has been increased about 2% by simply using bi-orthogonal Wavelet transform rather than Daubechies wavelet transform.

Harmonics in Adjustable Speed Drives: Causes, Effects, and Solutions

At present, it is unusual to operate machines at fixed speed throughout their operating lives. The need to adjust speed depends upon the load demand, load fluctuations, or for improving machine efficiency. This realization of the need of adjustable speed drives (ASDs) has led to rapid growth in this area. The emergence of semiconductor based control devices in the early 70 s contributed greatly to the development in ASDs. However, all the positives had to have a negative side; one of them in the form of the harmonics, which continue to provide food for thought to drive engineers. This paper aims to provide a panoramic view of the problem of harmonics caused by ASDs, starting with the brief introduction to harmonics, proceeding to its ill effects in power systems to some of the solutions that are being employed to overcome these harmonics.