- C-49, Ramnagaria South, (Flat No. S-2, Prangan), ShriKishanpura, Sanganer, Jaipur, Rajasthan, India-303905
- 9887708973
- Artifical Neural Networks, Artficial Neural Networks, Machine Learning and Pattern Recognition, Artificial Neural Networks for modeling purposes, Remote Sensing and GIS Applied to Natural Resources and Population, Computer Science and Engineering, and 16 moreBig Data Analytics, High Performance Computing, Cloud Computing, Engineering, Technology, Information Systems, Computer Science, Software Engineering, Artificial Intelligence, Internet of Things (IoT), Information Security, Intellectual Property Rights, Copyright and intellectual property, Communication, Data Mining, and Sustainable Developmentedit
- Dr. Pankaj Dadheech received his Ph.D. degree in Computer Science & Engineering from Suresh Gyan Vihar University (Ac... moreDr. Pankaj Dadheech received his Ph.D. degree in Computer Science & Engineering from Suresh Gyan Vihar University (Accredited by NAAC with ‘A’ Grade), Jaipur, Rajasthan, India. He received his M.Tech. degree in Computer Science & Engineering from Rajasthan Technical University, Kota and he has received his B.E. in Computer Science & Engineering from University of Rajasthan, Jaipur. He has more than 17 years of experience in teaching. He is currently working as an Associate Professor & Dy. HOD in the Department of Computer Science & Engineering (NBA Accredited), Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT), Jaipur, Rajasthan, India. He has published 17 Patents at Intellectual Property India, Office of the Controller General of Patents, Design and Trade Marks, Department of Industrial Policy and Promotion, Ministry of Commerce and Industry, Government of India. He has published & Granted 4 Australian Patents at Commissioner of Patents, Intellectual Property Australia, Australian Government. He has also Registered & Granted 2 Research Copyrights & 19 Indian Patents. He has presented 53 papers in various National & International conferences. He has 42 publications in various International & National Journals. He has published 2 Books & 8 Book Chapters. He is a member of many Professional Organizations like the IEEE Computer Society, CSI, ACM, IAENG & ISTE. He has appointed as a Ph.D. Research Supervisor in the Department of Computer Science & Engineering at SKIT, Jaipur (Recognized Research Centre of Rajasthan Technical University, Kota). He has also guided various M.Tech. Research Scholars. He has Chaired Technical Sessions in various International Conferences & Contributed as Resource Person in various FDP’s, Workshops, STTP’s, and Conferences. He is also acting as a Guest Editor of the various reputed Journal publishing houses, Conference Proceedings and Bentham Ambassador of Bentham Science Publisher. His area of interest includes High Performance Computing, Cloud Computing, Information Security, Big Data Analytics, Intellectual Property Right and Internet of Things.edit
- Prof. (Dr). Dinesh Goyal, Prof. (Dr.) Sumit Srivastavaedit
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Agriculture is the foremost factor which is important for the survival of human beings. Farming contributes to a very big part of GDP; still, several areas exist where improvements are required. One of those is crop recommendation. Crop... more
Agriculture is the foremost factor which is important for the survival of human beings. Farming contributes to a very big part of GDP; still, several areas exist where improvements are required. One of those is crop recommendation. Crop productivity is boosted as a result of accurate crop prediction. As crop production has already started to suffer from climate change, improving crop output is consequently desirable because agronomists are impotent to select the appropriate crop(s) depending on environmental and soil parameters, and the mechanism of forecasting the selection of the appropriate crops manually has failed. Factors like soil characteristics, soil types, climate characteristics, temperature, rainfall, area, humidity, geographic location etc. affect crop forecast. This chapter focuses mainly on building a recommendation system, i.e., suggesting the kind of the crop by applying various machine learning and deep learning techniques depending upon several parameters. The system would help the farmers for the appropriate decision to be taken regarding the crop type.
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Distributed Power Generation and Energy Storage Systems (DPG-ESSs) are crucial to securing a local energy source. Both entities could enhance the operation of Smart Grids (SGs) by reducing Power Loss (PL), maintaining the voltage profile,... more
Distributed Power Generation and Energy Storage Systems (DPG-ESSs) are crucial to securing a local energy source. Both entities could enhance the operation of Smart Grids (SGs) by reducing Power Loss (PL), maintaining the voltage profile, and increasing Renewable Energy (RE) as a clean alternative to fossil fuel. However, determining the optimum size and location of different methodologies of DPG-ESS in the SG is essential to obtaining the most benefits and avoiding any negative impacts such as Quality of Power (QoP) and voltage fluctuation issues. This paper’s goal is to conduct comprehensive empirical studies and evaluate the best size and location for DPG-ESS in order to find out what problems it causes for SG modernization. Therefore, this paper presents explicit knowledge of decentralized power generation in SG based on integrating the DPG-ESS in terms of size and location with the help of Metaheuristic Optimization Algorithms (MOAs). This research also reviews rationalized cos...
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Background: A simple and sensitive quantitation analytical technique by liquid chromatography–tandem mass spectrometry (LC-MS/MS) is essential for fedratinib in biological media with kinetic study in healthy rabbits. Objective: The main... more
Background: A simple and sensitive quantitation analytical technique by liquid chromatography–tandem mass spectrometry (LC-MS/MS) is essential for fedratinib in biological media with kinetic study in healthy rabbits. Objective: The main objectives of the present research work are to LC-MS/MS method development and validate procedure for the quantitation of fedratinib and its application to kinetic study in rabbits. Methods: Separation of processed samples were employed on zorbax SB C18 column (50mm×4.6 mm) 3.5µm with a movable phase of methanol, acetonitrile and 0.1% formic acid in the ratio of 30:60:10. The movable phase was monitored through column at 0.8 ml/min flow rate. The drug and ibrutinib internal standard (IS) were evaluated by monitoring the transitions of m/z -525.260/57.07 and 441.2/55.01 for fedratinib and IS respectively in multiple reaction monitoring mode. Results: The linear equation and coefficient of correlation (R2) results were y =0.00348x+0.00245 and 0.9984, r...
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Edge-Based Online Learning (EBOL), a technique that combines the practical, hands-on approach of EBOL with the convenience of Online Learning (OL), is growing in popularity. But accurately monitoring student engagement to enhance teaching... more
Edge-Based Online Learning (EBOL), a technique that combines the practical, hands-on approach of EBOL with the convenience of Online Learning (OL), is growing in popularity. But accurately monitoring student engagement to enhance teaching methodologies and learning outcomes is one of the difficulties of OL. To determine this challenge, this paper has put forth an Edge-Based Student Attentiveness Analysis System (EBSAAS) method, which uses a Face Detection (FD) algorithm and a Deep Learning (DL) model known as DLIP to extract eye and mouth landmark features. Images of the eye and mouth are used to extract landmarks using DLIP or Deep Learning Image Processing. Landmark Localization pre-trained models for Facial Landmark Localization (FLL) are one well-liked DL model for facial landmark recognition. The Visual Geometry Group-19 (VGG-19) learning model then uses these features to classify the student’s level of attentiveness as fatigued or focused. Compared to a server-based model, the proposed model is developed to execute on an Edge Device (ED), enabling a swift and more effective analysis. The EBOL achieves 95.29% accuracy and attains 2.11% higher than existing model 1 and 4.41% higher than existing model 2. The study’s findings have shown how successful the proposed method is at assisting teachers in changing their teaching methodologies to engage students better and enhance learning outcomes.
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The Internet of Things (IoT) ushers in a new era of communication that depends on a broad range of things and many types of communication technologies to share information. This new age of communication will be characterised by the... more
The Internet of Things (IoT) ushers in a new era of communication that depends on a broad range of things and many types of communication technologies to share information. This new age of communication will be characterised by the following characteristics: Because all of the IoT’s objects are connected to one another and because they function in environments that are not protected, it poses a significantly greater number of issues, constraints, and challenges than do traditional computing systems. This is due to the fact that traditional computing systems do not have as many interconnected components. Because of this, it is imperative that security be prioritised in a new approach, which is not something that is currently present in conventional computer systems. The Wireless Sensor Network, often known as WSN, and the Mobile Ad hoc Network are two technologies that play significant roles in the process of building an Internet of Things system. These technologies are used in a wid...
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In recent times, text summarization has gained enormous attention from the research community. Among the many uses of natural language processing, text summarization has emerged as a critical component in information retrieval. In... more
In recent times, text summarization has gained enormous attention from the research community. Among the many uses of natural language processing, text summarization has emerged as a critical component in information retrieval. In particular, within the past two decades, many attempts have been undertaken by researchers to provide robust, useful summaries of their findings. Text summarizing may be described as automatically constructing a summary version of a given document while keeping the most important information included within the content itself. This method also aids users in quickly grasping the fundamental notions of information sources. The current trend in text summarizing, on the other hand, is increasingly focused on the area of news summaries. The first work in summarizing was done using a single-document summary as a starting point. The summarizing of a single document generates a summary of a single paper. As research advanced, mainly due to the vast quantity of inf...
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COVID-19 is likely to pose a significant threat to healthcare, especially for disadvantaged populations due to the inadequate condition of public health services with people's lack of financial ways to obtain healthcare. The primary... more
COVID-19 is likely to pose a significant threat to healthcare, especially for disadvantaged populations due to the inadequate condition of public health services with people's lack of financial ways to obtain healthcare. The primary intention of such research was to investigate trend analysis for total daily confirmed cases with new corona virus (i.e., COVID-19) in the countries of Africa and Asia. The study utilized the daily recorded time series observed for two weeks (52 observations) in which the data is obtained from the world health organization (WHO) and world meter website. Univariate ARIMA models were employed. STATA 14.2 and Minitab 14 statistical software were used for the analysis at 5% significance level for testing hypothesis. Throughout time frame studied, because all four series are non-stationary at level, they became static after the first variation. The result revealed the appropriate time series model (ARIMA) for Ethiopia, Pakistan, India, and Nigeria were Mo...
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As the number of connected devices grows, the internet of things (IoT) poses new security challenges for network activity monitoring. Due to a lack of security understanding on the side of device producers and end users, the majority of... more
As the number of connected devices grows, the internet of things (IoT) poses new security challenges for network activity monitoring. Due to a lack of security understanding on the side of device producers and end users, the majority of internet of things devices are vulnerable. As a result, virus writers have found them to be great targets for converting them into bots and using them to perform large-scale attacks against a variety of targets. The authors provide deep learning models based on deep reinforcement learning for cyber security in IoT networks in this chapter. The IoT is a potential network that connects both living and nonliving things all around the world. As the popularity of IoT grows, cyber security remains a shortcoming, rendering it exposed to a variety of cyber-attacks. It should be emphasized, however, that while there are numerous DL algorithms presently, the scientific literature does not yet include a comprehensive catalogue of them. This chapter provides a c...
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Handwritten prescriptions and radiological reports: doctors use handwritten prescriptions and radiological reports to give drugs to patients who have illnesses, injuries, or other problems. Clinical text data, like physician prescription... more
Handwritten prescriptions and radiological reports: doctors use handwritten prescriptions and radiological reports to give drugs to patients who have illnesses, injuries, or other problems. Clinical text data, like physician prescription visuals and radiology reports, should be labelled with specific information such as disease type, features, and anatomical location for more effective use. The semantic annotation of vast collections of biological and biomedical texts, like scientific papers, medical reports, and general practitioner observations, has lately been examined by doctors and scientists. By identifying and disambiguating references to biomedical concepts in texts, medical semantics annotators could generate such annotations automatically. For Medical Images (MedIMG), we provide a methodology for learning an effective holistic representation (handwritten word pictures as well as radiology reports). Deep Learning (DL) methods have recently gained much interest for their cap...
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The discipline of computer vision is becoming more popular as a research subject. In a surveillance-based computer vision application, item identification and tracking are the core procedures. They consist of segmenting and tracking an... more
The discipline of computer vision is becoming more popular as a research subject. In a surveillance-based computer vision application, item identification and tracking are the core procedures. They consist of segmenting and tracking an object of interest from a sequence of video frames, and they are both performed using computer vision algorithms. In situations when the camera is fixed and the backdrop remains constant, it is possible to detect items in the background using more straightforward methods. Aerial surveillance, on the other hand, is characterized by the fact that the target, as well as the background and video camera, are all constantly moving. It is feasible to recognize targets in the video data captured by an unmanned aerial vehicle (UAV) using the mean shift tracking technique in combination with a deep convolutional neural network (DCNN). It is critical that the target detection algorithm maintains its accuracy even in the presence of changing lighting conditions, ...
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ABSTRACT
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The internet of things (IoT) is a revolutionary technology that links living and non-living devices all around the world. As a result, the frequency of cyber-attacks against IoT deployments is expected to rise. As a result, each system... more
The internet of things (IoT) is a revolutionary technology that links living and non-living devices all around the world. As a result, the frequency of cyber-attacks against IoT deployments is expected to rise. As a result, each system must be absolutely secure; otherwise, consumers may opt not to utilize the technology. DDoS assaults that recently attacked various IoT networks resulted in massive losses. There is only one way to detect stolen data from software and malware on the IoT network that is discussed in this chapter. To categorize stolen programming with source code literary theft, the tensor flow deep neural system is offered. To communicate raucous information while simultaneously emphasizing the value of each token in terms of source code forgery, tokenization, and measurement, the malware samples were gathered using the Malign dataset. The results show that the methodology proposed for analyzing IoT cyber security threats has a higher classification efficiency than cur...
This paper considers the issue of the search and rescue operation of humans after natural or man-made disasters. This problem arises after several calamities, such as earthquakes, hurricanes, and explosions. It usually takes hours to... more
This paper considers the issue of the search and rescue operation of humans after natural or man-made disasters. This problem arises after several calamities, such as earthquakes, hurricanes, and explosions. It usually takes hours to locate the survivors in the debris. In most cases, it is dangerous for the rescue workers to visit and explore the whole area by themselves. Hence, there is a need for speeding up the whole process of locating survivors accurately and with less damage to human life. To tackle this challenge, we present a scalable solution. We plan to introduce the usage of robots for the initial exploration of the calamity site. The robots will explore the site and identify the location of human survivors by examining the video feed (with audio) captured by them. They will then stream the detected location of the survivor to a centralized cloud server. It will also monitor the associated air quality of the selected area to determine whether it is safe for rescue workers...
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Consumer expectations and demands for quality of service (QoS) from network service providers have risen as a result of the proliferation of devices, applications, and services. An exceptional study is being conducted by network design... more
Consumer expectations and demands for quality of service (QoS) from network service providers have risen as a result of the proliferation of devices, applications, and services. An exceptional study is being conducted by network design and optimization experts. But despite this, the constantly changing network environment continues to provide new issues that today’s networks must be dealt with effectively. Increased capacity and coverage are achieved by joining existing networks. Mobility management, according to the researchers, is now being investigated in order to make the previous paradigm more flexible, user-centered, and service-centric. Additionally, 5G networks provide higher availability, extremely high capacity, increased stability, and improved connection, in addition to quicker speeds and less latency. In addition to being able to fulfil stringent application requirements, the network infrastructure must be more dynamic and adaptive than ever before. Network slicing may ...