M.Phil / MS
Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/42
This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.
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Item A 3D Accelerometer Based Human Activity Classification(COMSATS University Islamabad Lahore Campus, 2018) Aftab Paul,; FA16-REE-009; Contributor(s): Dr. Ali Nawaz Khan, Assistant Profesor [Supervisor]; LHR TP 7475Recently, Automated Human Activity Recognition has been extensively used for long term health monitoring of healthy individuals and to provide assisted living for the elderly. Long-term health monitoring systems have been successfully implemented for the prevention of chronic diseases like heart disease, obesity, workers syndrome, and other diseases related to sedentary lifestyle. Activities of Daily Living such as sitting, standing, walking, working in office, jogging, and running etc. can be efficiently classified using sensors such as 3D accelerometers, gyroscopes, and magnetometers. Such systems have demonstrated very high classification accuracies for activities performed for longer durations of time. However, these systems are unable to detect and classify transitory activities where the subject switches from one basic activity to another. For example, if a subject stands up from the chair to walk out of the room and then goes downstairs to reach ground floor of the office building has transitions from stationary sitting to standing and then walking, walking to going downstairs and then walking again and these transitions may not be classified correctly by existing automated human activity recognition systems since the models are trained using nonrealtime segmented data for each individual activity class. This research aims to develop a system for the detection of transitory activities. A Mobile phone-based accelerometer is used to record these activities from the chest of subject through MyNeuroHealth application. Data is collected, pre-processed, and classified into different activity classes. This data is used to train Artificial Neural Network to classify transitory activities. The proposed system achieved an accuracy of more than 50% with real-time data. Furthermore, it is also observed that using two accelerometers for collecting the movement data can enhance classification accuracy to 65%. Given that little or no work has been done in this dimension of HAR, this research may be extended to improve the accuracy of HAR for real-time automated long term health monitoring systems. XItem A Research On Clock-Synchronous Sleep And Wake(Publisher COMSATS University Islambad Lahore Campus, 2016) Usama Masood; FA12-MSEE-018; Dr. Ali Nawaz Khan, Assistant Profesor [Supervisor]; LHR TP 6980A Research on Clock-Synchronous Sleep and Wake Scheduling Scheme in Wireless Sensor Networks Network Wireless Sensor Network (WSN) consist of a unique set of resources like on-board battery and wireless communication devices with limited bandwidth. WSN offers a wide range of applications for monitoring space or targets. WSN is capable of performing simple processing tasks like tracking, detection of an event, or classification and may consist of multiple nodes that can process the information and communicate with nearby nodes in real-time for environmental monitoring, event detection, surveillance, object tracking, battlefield situation monitoring, and data collection etc. However, there are certain limitations in deploying WSN efficiently such as in terms of limited power resource for a single node in WSN, limited processing capability and varying network life time. It had been shown that wireless communication to and from sensor nodes consumes significantly more battery power in comparison to power expended in sensing, computation and memory access procedures. One of the possible solutions to this problem is to communicate as sparingly as possible through efficient sleep/wake scheduling for WSN nodes to extend node and network lifetime. A major research issue in WSN is to develop an energy efficient MAC protocol that not only provides increase in network lifetime but also addresses latency. In this research, a new MAC protocol is designed using sleep/wake scheduling for WSN. Though energy consumption in WSN is unavoidable due to communication necessity and for different stages like idle listening, retransmission, channel sensing and overhearing; this proposed protocol will help in decreasing this energy consumption. Energy efficiency and latency of the proposed sleep/wake scheduling scheme is evaluated and compared with the state of the art research. An AEL (Accounting for Energy and Latency) factor is introduced which is the deciding element for active and sleep cycles of the node. This said AEL factor defines the minimum duty cycle among the network nodes and is specified prior to nodes deployment depending upon application requirements. In the proposed protocol, the nodes adjust their duty cycles according to this AEL factor depending upon traffic load, their position and their connectivity in the network. The effect of this AEL factor on energy efficiency and delay is evaluated for different network densities in this research thesis. While incorporating sleep/wake scheduling for energy efficiency, delays are added in the network to route packet from node towards sink. Therefore, it is necessary to address latency for MAC protocol especially for delay constrained applications. This research thesis focuses on sleep/wake scheduling scheme ensuring energy efficiency, decreased latency and increased network lifetime by selecting an appropriate AEL value. The research includes the comparison of the proposed protocol with state of the art research and has shown significant percentage improvements in energy efficiency and delay from S-MAC and Anycast protocolItem Output Feedback FTC Scheme For Linear Parameter(Publisher COMSATS University Islambad Lahore Campus, 2016) Izhar Ul Haq; , FA13-MSEE-006; Dr. Mirza Tariq Hamayun, Assistant Profesor [Supervisor]; LHR TP 6820The proposed research has been carried out for an Active Fault Tolerant Control (FTC) of Linear Parameter Varying (LPV) systems using output feedback mechanism. Output feedback is a practical approach due to the fact that all the plant states are not accessible or measurable, therefore estimating the unknown states and maintaining the closed loop stability in an LPV framework is closer to the control of nonlinear systems. At the same time, it utilizes the mature nature of linear control theory. In this research, LPV observers in LMI framework have been designed for affine LPV plant, using two different LPV approaches namely affine and polytopic, in order to estimate the unknown states. These estimated states are used as a feedback to LPV controller. Integral sliding mode controller in LPV framework has been designed along with control allocation scheme to control the controlled states as well as to counter for actuators faults and failures. It has been assumed that Fault Detection and Isolation unit, also called FDI, is providing updated actuator faults or failures information to the control allocation (CA) scheme. Detailed performance and stability of the proposed control scheme has been checked in fault-free case, i.e. nominal condition, as well as in the situation when actuator fault occurs. To validate the proposed output feedback FTC mechanism, an LPV model of longitudinal plant of aircraft, taken from the literature, has been considered as a benchmark in the simulation. The simulation results show that the system is quadratically stable and give good tracking capability by the LPV controller-observer pair in nominal as well as in actuator’s fault or failure situation.Item Model Identification And Control Of A Lab Based(Publisher COMSATS University Islambad Lahore Campus, 2018) Anila Barkat,; FA14-REE-011; Dr. Mirza Tariq Hamayun, Assistant Profesor [Supervisor]; LHR TP 6847Inverted pendulum control system has vast applications in the field of control system. Every system which is inherently unstable can be controlled like inverted pendulum is controlled. To design a Robust Control system for Inverted pendulum to investigate the behaviour of rapid change in scheduled parameters is aim of this thesis. The designed mechanism has a monitoring and calibrating VI (Virtual Instrument) which is constructed in LabVIEW. This VI send a step input to the inverted pendulum and obtain the transient response of the system from that response system’s model is identified. This model helped in control designing part because model of every system represents its characteristic. Then LPV controller is designed to cater for the parameters variations to enhance the performance and robustness. Moreover, the designed robust controller is implemented on the hardware platform to show its effectiveness. The identified mathematical model is validated by comparing the simulation and real time simulation results with LQR and PID controller.Item Design Of Hemispherical Antenna For Breast Cancer(Publisher COMSATS University Islambad Lahore Campus, 2017) Iqra Asghar,; SP15-REE-005; Dr. Asim Ali Khan, Assistant Profesor [Supervisor]; LHR TP 6824Microwave imaging has proven to be successful for medical imaging applications including breast cancer, lungs cancer, brain stroke detection, cardiac imaging etc. Microwave imaging has the ability to detect malignancy present at depth of tissue, providing non-invasive imaging, measuring dielectric contrast between tissues. This imaging procedure provides an effective substitute of mammography, ultrasound or MRI as all these screenings provide unreliable and uncomfortable detection. In this thesis, microwave imaging system has been simulated for breast tumor detection. The designed microwave imaging system includes the use of holographic imaging. For the design of holographic imaging array, two-dimensional (2D) and three-dimensional (3D) breast models have been designed in MATLAB. Holographic array simulations have been carried out in MATLAB. To efficiently reconstruct an image, inverse scattering algorithm has been applied in holography imaging array. The building block of microwave imaging is to design a suitable antenna that must efficiently transmit and receive electromagnetic signals. An efficient compact double layer antenna has been designed in HFSS for the breast malignancy detection system. The antenna provides good impedance matching, wide bandwidth, stable and symmetric radiation pattern for near field imaging. To improve the performance of imaging system, the antenna was simulated in an array configuration. To overcome the drawbacks of array system, a novel array topology has been simulated in HFSS. The designed array system consists of separate transmitters and receivers for imaging, to provide low cost, reliable and effective detectiItem Mechine And Learning Based IoT Instruion Detection(Publisher COMSATS University Islambad Lahore Campus, 2018) Muhammad Saad Sarfraz Khan; , SP16-REE-006; Dr. Abbas Javed, Assistant Profesor [Supervisor]; LHR TP 6439In today’s world, technological advancements are gradually increasing, so small scale to large scale companies use the internet for business purposes. Other than that Internet of Things (IoT) is a current trend in the world. Most companies try to improve their companies by making them smart premises since this will give a lot of advantages; some are increasing customer satisfaction, saving time, control expenses, monitoring, and many more. So, with the rise of these technological advancements, diverse types of security issues like DDoS, malware, virus, worms, and many other issues occurs as well because of the software or device vulnerabilities. These are harmful to organizations’ sensitive data due to the violation of integrity, confidentiality, and availability. IoT devices have been extensively implemented in many different applications in recent years, such as smart homes, medical, heavy industry, agriculture, networks, security, transportation, etc. An adversary can capture the network traffic of IoT devices and analyze it to reveal user activities even if the traffic is encrypted. Due to the increasing number of cyber-attacks, we need IoT security solutions. The majority of the attacks are extended versions of previously known attacks and bypass the conventional firewall system. An Intrusion Detection System (IDS) performed an incredibly significant part to figure out the novel types of attacks by analyzing the network traffic. Machine Learning (ML) and Deep Learning (DL) based techniques such as Random Forest (RF), Support Vector Machine (SVM), J48, Naïve Bayes (NB), Logistic Regression (LR), etc. are used as a classifier to categorize the network traffic as normal and attack class. The objective of this research is to compare the impact of different Feature Selection (FS) techniques such as Information Gain (IG), Chi-Square, Correlation-based Feature Selection (CFS) subsets evaluator, Classifier based attributes, and other techniques on the accuracy, computational time and confusion matrix of ML & DL based techniques and identify the attack categories. FS methods and classifiers have been implemented on four different data sets NSL KDD, UNSW-15, CIC IDS2017, and TON_IoT and a comparative assessment of the outcome is presented. By applying our proposed comparative model, we will be able to trace out the malicious attacks i.e., DoS, DDoS, routing attacks, Man-in-The-Middle (MITM), etc. in the realm of IoT networks. This model detects the attacks with high accuracy and consumes less time as compared to the other methods.Item A Research On Feasibility Of Intra Vehicle(Publisher COMSATS University Islambad Lahore Campus, 2018) Naeem Mirza,; FA13-MSEE-016; Dr. Ali Nawaz Khan, Assistant Profesor [Supervisor]In Intra Vehicular Wireless Sensor Network (IVWSN), Engine Control Units (ECUs) gathers information about the vehicle from the sensors over wireless channels. This information is then transferred to On-Board Unit (OBU) through Controller Area Network (CAN) in order to monitor and maintain vehicular operations. CAN bus is widely used wired media for communication between ECU and sensors by several car manufacturers but it requires very careful sensor deployment and wiring. In this research thesis, we have achieved low cost and energy efficient communication between (1) sensor nodes and ECU using CAN bus and (2) OBU and ECU within Vehicular Ad Hoc Network (VANET) using Bluetooth low energy (BLE) CC2540/CC2541 modules that can be readily employed in densely urban environment for wireless inter vehicular (up to 50m range) as well as wireless intra vehicular (up to 10m range) communication. The BLE system was invented for the purpose of transmitting small packets of data at once, while consuming less power than Basic Rate & Enhanced Data Rate (BR & EDR) and IEEE 802.15.4 standard based ZigBee devices. A typical communication scenario involves either a Peripheral/ Central or Broadcaster/ Observer device pair. For our tests, we have chosen the Peripheral/ Central modes as they provide greater flexibility to configure application parameters and allow bidirectional communication. We have included comparison between BLE and CAN bus for communication between (1) ECUs and sensors and (2) ECU and OBU, in terms of energy efficiency, throughput, latency and coverage area. Furthermore, wireless communication between ECUs and sensors had been aItem Dynamic Adjustments Of Threshold Temperatures(Publisher COMSATS University Islambad Lahore Campus, 2019) Muhammad Ibtesam; , FA15-REE-004 Contributor(s); : Dr. Naeem Shahzad, Assistant Profesor [Supervisor]; LHR TP 5432This research work addresses the issues of thermal emergencies in real-time embedded system using scheduling based algorithms. The algorithms considers execution of periodic task sets including both independent and dependent tasks over homogeneous multi-core processors without violating deadlines. We propose two algorithms in this work. The first one adjusts the thermal threshold values based on the processor utilization to reduce thermal peaks and thermal spatial gradients for independent periodic task sets. The second algorithm is a DVFS enabled load-balancing algorithm for execution of dependent periodic task sets to reduce the temperature peaks and spatial gradients. The proposed algorithms are evaluated in a simulation environment using a scheduling and thermal model for synthetic and bench marks techniques. The used hardware platform comprises four and eight cores. The results show that GTAI with 74ºC threshold reduces average temperature up to 6ºC and maximum temperature spatial gradient was reduced by 33% as compared to benchmarks techniques. The DVFS enabled DFS was able to decrease peak temperature by 31% and temperature spatial gradients by almost 50% in a 4-Core system.Item A HYBRID MAC LAYER PROTOCOL FOR HETEROGENEOUS WIRELESS BODY AREA NETWORKS(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2019) Hina Bushra; CIIT/FA14-REE-007/LHR; Dr. Ali Nawaz Khan; LHR TP 5627The rapid advancements in wireless communication technologies and micro-electronics systems have fostered the development of small and intelligent micro-components that incorporate sensing devices and wireless communications into a single miniature circuit which is wearable or implantable inside the human body for medical and healthcare applications. These components when deployed over or across the body of subject communicate wirelessly to constitute Wireless Body Area Networks (WBANs). Since several WBAN nodes are sharing the wireless channel to report their collected data back to a base-station or sink node, the medium access mechanism must be robust, scalable, and energy efficient. Furthermore, it may also adapt to different data-rate requirements for different sensors in a heterogeneous WBAN. In this research, Adaptive Sleep and Dynamic GTS allocation algorithms in WBAN have been implemented and compared with the proposed protocol entitled Adaptive Dynamic MAC that takes into consideration number and type of sensors, variable data-rates and energy requirements through managing sleep/wakeup intervals for WBAN nodes and implementing adaptive schedules for communication within the network. Network performance is compared on the basis of network lifetime, throughput and channel utilization through analytical model that is also verified in a customized simulator. Simulation results are gathered by observing network performance under variable network energy conditions, change in the position of gateway node, and effect of heterogeneous sensor nodes on mentioned performance parameters. It has been shown that Adaptive Dynamic MAC performs better than Dynamic GTS Allocation framework in all mentioned parameters. Furthermore, proposed algorithm has better network lifetime and throughput characteristics in comparison to baseline Adaptive Sleep algorithm.