Ankit Thakkar

Ankit Thakkar
Nirma University | NU · Institute of Technology

PhD
Associate Professor, Computer Science and Engineering Department, Nirma University

About

52
Publications
7,728
Reads
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816
Citations
Introduction
WSN, IoT, Swarm and Evolutionary algorithms, Applications of Soft Computing, Information Fusion, Classification, Security, Machine learning and deep learning
Education
March 2011 - November 2014
Nirma University
Field of study
  • Optimization of Sensor Network
June 2007 - May 2009
Nirma University
Field of study
  • Computer Science & Engineering
June 1998 - May 2002
Hemchandracharya North Gujarat University
Field of study
  • Computer Science

Publications

Publications (52)
Article
Information fusion is one of the critical aspects in diverse fields of applications; while the collected data may provide certain perspectives, a fusion of such data can be a useful way of exploring, expanding, enhancing, and extracting meaningful information for a better organization of the targeted domain. A nature-inspired evolutionary approach,...
Article
Full-text available
Automatic Human Action Recognition (HAR) using RGB-D (Red, Green, Blue, and Depth) videos captivated a lot of attention in the pattern classification field due to low-cost depth cameras. Feature extraction in action recognition is an important aspect. As compared to Depth Motion Maps (DMM), Depth Motion Maps–Local Binary Pattern (DMM–LBP) provides...
Article
Full-text available
With the increase in the usage of the Internet, a large amount of information is exchanged between different communicating devices. The data should be communicated securely between the communicating devices and therefore, network security is one of the dominant research areas for the current network scenario. Intrusion detection systems (IDSs) are...
Article
Full-text available
The prediction of a volatile stock market is a challenging task. While various neural networks are integrated to address stock trend prediction problems, the weight initialization of such networks plays a crucial role. In this article, we adopt feed-forward Vanilla Neural Network (VNN) and propose a novel application of Pearson Correlation Coeffici...
Article
The surge of constantly evolving network attacks can be addressed by designing an effective and efficient Intrusion Detection System (IDS). Various Deep Learning (DL) techniques have been used for designing intelligent IDS. However, DL techniques face an issue of overfitting because of complex network structure and high-dimensional data sets. Dropo...
Chapter
Stock market investments have been primarily aimed at gaining higher profits from the investment; a large number of companies get listed on various stock exchanges to initiate trading through the stock market. For the potential expansion of market tradings, several companies may choose to get listed on multiple exchanges which may be domestic and/o...
Chapter
Data security is regarded to be one of the crucial challenges in this fast-growing internet world. Data generated through internet is exposed to various types of vulnerabilities and exploits. Security mechanisms such as Intrusion Detection System (IDS) are designed to detect various types of vulnerabilities and attacks. Various Machine Learning (ML...
Article
Full-text available
Human Action Recognition (HAR) has gained considerable attention due to its various applications such as monitoring activities, robotics, visual surveillance, to name a few. An action recognition task consists of feature extraction, dimensionality reduction, and action classification. The paper proposes an action recognition approach for depth-base...
Article
Full-text available
Human Action Recognition (HAR) involves human activity monitoring task in different areas of medical, education, entertainment, visual surveillance, video retrieval, as well as abnormal activity identification, to name a few. Due to an increase in the usage of cameras, automated systems are in demand for the classification of such activities using...
Article
The stock market has been an attractive field for a large number of organizers and investors to derive useful predictions. Fundamental knowledge of stock market can be utilized with technical indicators to investigate different perspectives of the financial market; also, the influence of various events, financial news, and/or opinions on investors’...
Article
We are at the brink of Internet of Things (IoT) era where smart devices and other wireless devices are redesigning our environment to make it more correlative, flexible, and communicative. IoT is now evolving to Internet of Everything, as it incorporates and builds a system that includes wireless networks, sensors, cloud servers, analytics, smart d...
Article
Full-text available
The goal of securing a network is to protect the information flowing through the network and to ensure the security of intellectual as well as sensitive data for the underlying application. To accomplish this goal, security mechanism such as Intrusion Detection System (IDS) is used, that analyzes the network traffic and extract useful information f...
Article
Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as developing smart home, smart cities, healthcare applicat...
Article
Investment in a financial market is aimed at getting higher benefits; this complex market is influenced by a large number of events wherein the prediction of future market dynamics is challenging. The investors’ etiquettes towards stock market may demand the need of studying various associated factors and extract the useful information for reliable...
Article
The financial market consists of various money-making strategies wherein trading through a stock market is an important example. The complex non-linear behaviours of volatile stock markets attract researchers to study inherent patterns. As the primary motivation for investment in such markets is to gain higher profits, potential stocks are given co...
Article
Stock market trading has been a subject of interest to investors, academicians, and researchers. Analysis of the inherent non-linear characteristics of stock market data is a challenging task. A large number of learning algorithms are developed to study market behaviours and enhance the prediction accuracy; they have been optimized using swarm and...
Article
Full-text available
In the current age of machine intelligence, computer literacy has been achieved in terms of its knowledge and ability of utilization at various stages. As compared to the urge of demanding for high computer functionalities as well as performance, the concern towards the cost in attaining such goals has been limited. The developers try to empower a...
Article
Full-text available
Due to a large number of tradings in the stock market, it generally experiences fluctuations throughout the day. Such oscillations influence market capitals of the companies listed on a stock exchange. Hence, in order to take suitable trading steps, prediction of the future stock price as well as trend direction becomes a crucial task. National Sto...
Article
Full-text available
The research in the field of Cyber Security has raised the need to address the issue of cybercrimes that have caused the requisition of the intellectual properties such as break down of computer systems, impairment of important data, compromising the confidentiality, authenticity, and integrity of the user. Considering these scenarios, it is essent...
Article
The growth of data and categories of attacks, demand the use of Intrusion Detection System(IDS) effectively using Machine Learning (ML) and Deep Learning (DL) techniques. Apart from the ML and DL techniques, Swarm and Evolutionary (SWEVO) Algorithms have also shown significant performance to improve the efficiency of the IDS models. This survey cov...
Article
Travelling is a combination of journey, transportation, travel-time, accommodation, weather, events, and other aspects which are likely to be experienced by most of the people at some point in their life. To enhance such experience, we generally look for assistance in planning a tour. Today, the information available on tourism-related aspects on t...
Article
Personality is a combination of various characteristics and qualities of an individual. It may be affected by the growth and evolution of one's values, attributes, relationships with the community, personal memories of life events, habits, and skills. Behaviours and decisions of an individual are largely directed by his/her personality. Identificat...
Chapter
Emotion detection is crucial in several applications including voice-based automated call centers and machine-to-human or machine-to-machine conversation systems. This area of research is still in its infancy stage. In this article, we present an overview of emotion recognition from various types of sensory and bio-signals and provide a review of e...
Chapter
An increasing demand of connected devices in the field of IoT put forth the requirement of timely availability of data for the delay sensitive applications. To mitigate such requirements, fog computing plays a key role in IoT world. Fog computing supports the applications and services that do not fit with the cloud paradigm. It acts as a bridge bet...
Chapter
Travelling salesman problem (TSP) is one of the optimization problems which has been studied with a large number of heuristic and metaheuristic algorithms, wherein swarm and evolutionary algorithms have provided effective solutions to TSP even with a large number of cities. In this paper, our objective is to solve some of the benchmark TSPs using a...
Chapter
Humans share emotions which they exhibit through facial expressions. Automatic human emotion recognition algorithm in images and videos aims at detection, extraction, and evaluation of these facial expressions. This paper provides a comparison between various multi-class prediction algorithms employed on the Cohn-Kanade dataset (Lucey in The extend...
Conference Paper
Digital media becomes an effective way of communication which is available round the clock to everyone including humans and machines. This put the requirement for machines to differentiate between human and machine as far as access of the website or its relevant services is concerned. CAPTCHA (Completely Automated Public Turing test to tell Compute...
Conference Paper
Wireless Sensor Network is made of tiny energy-constrained nodes with a limited amount of communication, computation and storage capabilities. Also, it is inconvenient to change batteries of the sensor nodes due to large-scale deployment in hostile environments. Hence, network longevity becomes the prime concern for WSNs. This paper presents Distan...
Conference Paper
A key issue for any Wireless Sensor Network (WSN) is to design energy efficient protocols to prolong the lifetime of WSN. This is indeed a necessary and important requirement, as sensor nodes are battery operated. Also, it is difficult to recharge or replace batteries of nodes because of their dense deployment in a hostile region. Cluster based dat...
Chapter
Wireless Sensor Network (WSN) consists of energy constraint sensor nodes, and it is difficult to replace or recharge batteries of these nodes when they operate in hostile environments. Hence, prolonging the lifetime of WSN nodes is an important issue for any WSN. Cluster based routing techniques improve the lifetime of WSNs, wherein longer stabilit...
Article
Full-text available
Energy efficient protocol design is a prime concerned for wireless sensor networks. Many techniques have been developed to extend the lifetime of Wireless Sensor Networks. This paper focuses on energy conservation in wireless sensor network using hierarchical routing techniques. In a hierarchical routing, few nodes elect themselves as cluster heads...
Article
Designing of scalable routing protocol with prolonged network lifetime for a wireless sensor network (WSN) is a challenging task. WSN consists of large number of power, communication and computational constrained inexpensive nodes. It is difficult to replace or recharge battery of a WSN node when operated in a hostile environment. Cluster based rou...
Article
Full-text available
Wireless Sensor Network (WSN) is mainly characterized by its limited power supply. Hence, protocols designed for WSNs should be energy efficient. Cluster based routing helps to improve the network lifetime. Centralized Low-Energy Adaptive Clustering Hierarchy (LEACH-C) is an energy efficient cluster based routing protocol that has shown improvement...
Chapter
Energy efficiency is one of the important issues in the Wireless Sensor Networks (WSN). In this paper, a decentralized Alive Nodes based Low Energy Adaptive Clustering Hierarchy (AL-LEACH) is presented, that considers number of alive nodes in the network to elect the cluster heads. Alive nodes are used to dynamically compute weights of random numbe...
Article
Designing of multi-hop Wireless Sensor Network (WSN) depends upon the requirements of the underlying sensing application. The main objective of WSNs is to monitor physical phenomenon of interest in a given Region of Interest using sensors and provide collected data to sink. WSN is made of large number of energy, communication and computational cons...
Conference Paper
Now a days, security is a major concern for any organization. It is very difficult to have enough faith in any person as far as security of the organization is concerned. Due to these reasons, face recognition gets popularity in the security domain. Many conventional methods are available to do the face recognition. In this paper, we have discussed...
Article
Designing a protocol stack for wireless sensor network (WSN) is a challenging task due to energy, computational, communication and storage constraints. Energy spent for communication between sensor nodes dominates the energy spent for the computation [1]. Multi -hop short range communication between wireless sensor nodes is energy efficient compare...
Conference Paper
Full-text available
Texture analysis is significant field in image processing and computer vision. Shape and texture has groovy correlation and texture can be defined by shape descriptor. Three individual approach Zernike moment, which is orthogonal shape signifier, Gabor features and Haralick features are utilized for texture analysis. Another approach is applied by...
Article
Full-text available
Designing a protocol stack for wireless sensor network (WSN) is a challenging task due to energy, computational, communication and storage constraints. Energy spent for communication between sensor nodes dominates the energy spent for the computation [1]. Multi-hop short range communication between wireless sensor nodes is energy efficient compared...
Conference Paper
Adhoc sensor networks are being considered for many novel applications. There are many challenges while designing the sensor based adhoc network but main constraint is the power consumption done by the sensor nodes. Many solutions have been proposed to save the power of the senor nodes which are based on routing and other methodology. Most of the s...
Article
Full-text available
Object detection and segmentation are critical task for many computer vision applications; they provide classification of the pixels into either foreground or background. In this paper, a new algorithm of objects detection and segmentation is proposed. Traditional approaches to object detection only look at local pieces of the image, whether it wil...

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