Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
Now showing items 946-965 of 1710
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A Method of Designing an Intelligent Public Transportation System in Metropolitan Area Using Emergent Intelligence
Metropolitan area consists of huge population density, one or more urban areas, satellite cities, rural areas and towns. It highly concentrates economic activities to attract people from rural areas and is a complex ... -
A Method of Designing Museum Services Handling System for Ubiquitous Visitors
Advances in mobile computing technologies have enabled the personal ubiquitous computing environment for ubiquitous visitors. In the case of museum services, a ubiquitous visitor is free to access his/her interested exhibit ... -
Methods for Blind Separation of Co-Channel BPSK Signals Arriving at an Antenna Array and Their Performance Analysis
(Indian Institute of Science, 2005-06-30)Capacity improvement of Wireless Communication Systems is a very important area of current research. The goal is to increase the number of users supported by the system per unit bandwidth allotted. One important way of ... -
Methods for Text Segmentation from Scene Images
(2017-09-27)Recognition of text from camera-captured scene/born-digital images help in the development of aids for the blind, unmanned navigation systems and spam filters. However, text in such images is not confined to any page layout, ... -
Microengineered Force Sensors and Haptic Feedback System for Catheter Contact Force
Minimally Invasive Surgery (MIS) pursues the highest attention in various medical procedures globally because of the reduced complicated process compared with traditional surgery, short postprocedural convalescence, and ... -
Millimeter Wave Beam Selection in Time-varying Channels with Orientation Changes and Lateral Mobility
Beamforming enables millimeter-wave (mmWave) communications to achieve high data rates in 5G and beyond systems. This requires the use of many narrow directional beams at both the transmitter and receiver to overcome the ... -
Minimization Problems Based On A Parametric Family Of Relative Entropies
(2017-08-21)We study minimization problems with respect to a one-parameter family of generalized relative entropies. These relative entropies, which we call relative -entropies (denoted I (P; Q)), arise as redundancies under mismatched ... -
MIST : Mlgrate The Storage Too
(2017-05-25)We address the problem of migration of local storage of desktop users to remote sites. Assuming a network connection is maintained between the source and destination after the migration makes it possible for us to transfer ... -
Mitigating Bias via Algorithms with Fairness Guarantees
The rapid integration of automated decision-making systems in critical domains such as resume screening, loan approval, content recommendation, and disaster containment has raised significant concerns regarding biases in ... -
ML based Intrusion Detection System for IEC 61850 MMS
Cyberattacks targeting operational technology (OT) systems, such as power grids, have evolved into highly sophisticated threats. In the last two decades state-sponsored adversaries have increasingly weaponized ... -
An MLIR-Based High-Level Synthesis Compiler for Hardware Accelerator Design
The emergence of machine learning, image and audio processing on edge devices has motivated research towards power-efficient custom hardware accelerators. Though FPGAs are an ideal target for custom accelerators, the ... -
Model Checking Temporal Properties of Presburger Counter Systems
Counter systems are a well-known and powerful modeling notation for specifying infnite state systems. In this thesis we target the problem of checking temporal properties of counter systems. We address three predominant ... -
Model Extraction and Active Learning
Machine learning models are increasingly being offered as a service by big companies such as Google, Microsoft and Amazon. They use Machine Learning as a Service (MLaaS) to expose these machine learning models to the ... -
Model Extraction Defense using Modified Variational Autoencoder
Machine Learning as a Service (MLaaS) exposes machine learning (ML) models that are trained on confidential datasets to users in the form of an Application Programming Interface (API). Since the MLaaS models are deployed ... -
Model-based Deep Learning Algorithms in Mimo Receivers : Channel Estimation & Symbol Detection
With the advent of Massive multiple-input-multiple-output (MIMO) wireless communication systems, users can now enjoy high spectral efficiency and throughput leading to a better quality of service. The efficacy of these ... -
Model-based Safe Deep Reinforcement Learning and Empirical Analysis of Safety via Attribution
During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents perform a significant number of random exploratory steps, which in the real-world limit the practicality of these algorithms ... -
Model-Checking in Presburger Counter Systems using Accelerations
(2018-04-18)Model checking is a powerful technique for analyzing reach ability and temporal properties of finite state systems. Model-checking finite state systems has been well-studied and there are well known efficient algorithms ...