Papers by Satinder Bal Gupta
Sigma mühendislik ve fen bilimleri dergisi, 2024
Biomimetics is an emerging field that allows mimicry of living organisms in nature to develop dif... more Biomimetics is an emerging field that allows mimicry of living organisms in nature to develop different techniques so as to solve hard and complex problems related to optimization. The different techniques developed in this field takes inspiration from biology or nature. Biology acts as a powerful tool for imitating, copying, learning, understanding and inspiring the development of new systems and models. The different techniques discussed in this paper include techniques based on evolutionary algorithms, neural network and swarm intelligence. All these techniques are biologically inspired and provide good accuracy. The accuracy of all these algorithms can be increased by using them in hybrid form with other techniques and using different datasets. The comparative analysis of these techniques is done using advantages, disadvantages and applications of these techniques.
Importance of Artificial Intelligence in Achieving SDGs in India
International journal of built environment and sustainability, May 31, 2024
Ìnformacìjnì tehnologìï ì zasobi navčannâ, Apr 30, 2024
Artificial Intelligence (AI) plays a multifaceted role in educating impaired people and has signi... more Artificial Intelligence (AI) plays a multifaceted role in educating impaired people and has significantly enhanced the learning experience of disabled students. AI is emerging as an influential tool that enhances accessibility, personalizes the learning process, and promotes inclusivity in educating students with disabilities. For visually disabled students, AI-powered braille devices help the children learn and rehearse braille independently. AI can be incorporated into mobile applications and learning platforms invented to help dyslexic students in India. These apps provide many features to make learning fun for learners with disabilities. The Notebook platform utilizes Machine Learning algorithms that provide students with a personalized learning experience. AACDD makes the process of learning easy for children suffering from neuro-developmental disorders. Augmenta11y app utilizes AR (Augmented Reality) to display the content in a form that dyslexic children can easily understand. DYSXA app provides many features for making learning fun for learners with disabilities. Using automation and the latest technologies, Stamurai provides speech therapy to such people at a meager cost. The authors have analyzed and discussed more AI tools developed to help disabled students with education. With the use of these tools, children with disabilities can communicate better, receive an inclusive education, be more accessible, be mentally prepared, and lead independent lives. These tools have shown promising potential in supporting children with disability. It is observed that AI holds much potential to strengthen the learning experiences of disabled students by providing them with personalized support and alleviating the difficulties they face in reading, writing, and learning a language with accuracy.
Zenodo (CERN European Organization for Nuclear Research), Jun 1, 2014
Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed ... more Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Indian Journal Of Science And Technology
Background/Objectives: At the time of acquisition and transmission noise is embedded with the ima... more Background/Objectives: At the time of acquisition and transmission noise is embedded with the images. It introduces new but unwanted information (noise) in images. The elimination of noise to analyze such data is an essential step in preprocessing. The purpose of this study is to propose a novel image denoising approach to recover original images at high noise densities without introducing unwanted artifacts. Methods: A new hybrid method based on approximation subband thresholding with pre-Gaussian filtering is presented in this study. Google Colab as a platform and python as a programming language is used for the implementation of the proposed technique. To evaluate the performance Peak Signal to Noise Ratio (PSNR) is chosen. The standard jpeg images (Cameraman, Lena, Astronaut, Cat) have been taken as an input and random noise with different noise ratios (σ =0.05,0.20,0.30,0.50) is applied to get the noisy images for the experiment. In random noise scenarios, the proposed method experimented on different grayscale standard images, and performance is compared with different existing methods. Findings: The standard images with different noise ratios are denoised by the proposed method, and the quality of images is calculated in terms of PSNR. The results obtained from the proposed method on different standard images improve PSNR (PSNR= 25.80dB, σ =0.50) at high noise levels significantly. Novelty: Gaussian filter improve the quality of images. However, when wavelet decomposition is blended with filtered image and thresholding is applied on approximation band improved the quality of images. Hence, the proposed method has a wide area of application to improve image quality in the field of character recognition, agriculture, medical science, and remote sensing.
CURRENT APPLIED SCIENCE AND TECHNOLOGY
Artificial intelligence has been categorized as a subfield of computer science wherein machines p... more Artificial intelligence has been categorized as a subfield of computer science wherein machines perform smart learning tasks with the help of data and statical methods. Agriculture is one of the oldest social activities performed by humans. It provides many crucial things like raw materials, food, and employment. Due to the increasing population, it is the need of the hour that the agriculture sector should increase production of resources to match actual demand. Many agronomic factors such as weeds, pests, water condition and availability, and climate conditions impact overall yield. At present, methods used by farmers for management are traditional and insufficient to meet increased demand. To match future demand, new innovative agriculture methos need to be adopted. Artificial intelligence techniques in smart farm monitoring can enhance the quality and quantity of yield. This paper surveys different areas in agriculture where artificial intelligence is applicable. Artificial in...
International Conference on IT, 2007
The exponential growth of information source on the web and in turn continuing technological prog... more The exponential growth of information source on the web and in turn continuing technological progress of searching the information by using tools like Search Engines gives rise to many problems for the user to know which tool is best for their query and which tool is not. At this time Metasearch Engine comes into play by reducing the user burden by dispatching queries to multiple search engines in parallel and refining the results of these search engines to give the best out of best by doing superior job on their side. These engines do not own a database of Web pages rather they send search terms to the databases maintained by the search engine companies, get back results from all the search engines queried and then compile the results to be presented to the user. In this paper, we describe the working of a typical metasearch engine and then present a comparative study of traditional search engines and metasearch engines on the basis of different parameters and show how metasearch engines are better than the other search engines.
Analysis of Some Popular AI & ML Algorithms Used in Agriculture
2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)
A Comparative Analysis of Machine Vision Algorithms for Insect Pests Classification
December 2022
Insect pests are the one of the important biological factors, that has become an important cause ... more Insect pests are the one of the important biological factors, that has become an important cause of crop yield degradation. However, their identification and detection in the early stages is a very significant task to minimize the overall losses. The conventional techniques with naked eyes to identify the pests is very exigent and require domain specific expertise. It is extremely time-consuming and tedious task to identify the pests in the initial stages with conventional methods. To minimize these issues, some highly developed methods are required to detect insect pests accurately in agriculture. The continuous emergence of machine vision in image processing helps in this regard. This paper presents a comprehensive review to identify the insect pests in the early stages with the help of machine vision techniques. Based on this, a comparative analysis of different classifiers has also been presented.
Smart Farming: An IOT Based Automation
Ambient Communications and Computer Systems
Frontiers in Plant Science
Castor (Ricinus communis L.) is an important nonedible industrial crop that produces oil, which i... more Castor (Ricinus communis L.) is an important nonedible industrial crop that produces oil, which is used in the production of medicines, lubricants, and other products. However, the quality and quantity of castor oil are critical factors that can be degraded by various insect pest attacks. The traditional method of identifying the correct category of pests required a significant amount of time and expertise. To solve this issue, automatic insect pest detection methods combined with precision agriculture can help farmers in providing adequate support for sustainable agriculture development. For accurate predictions, the recognition system requires a sufficient amount of data from a real-world situation, which is not always available. In this regard, data augmentation is a popular technique used for data enrichment. The research conducted in this investigation established an insect pest dataset of common castor pests. This paper proposes a hybrid manipulation-based approach for data au...
Journal of Advanced Research in Computer Engineering, 2007
The world wide web (www) is growing rapidly and to search some information on WWW search engines ... more The world wide web (www) is growing rapidly and to search some information on WWW search engines are used. These search engines rely on web crawlers to acquire large collections of pages for indexing and analysis. Approximately 40% of current internet traffic is due to these web crawlers retrieving pages for indexing and analysis. The frequency with which a crawler requests documents from the server for search engine affects the load on the websites and other resources like network bandwidth etc. If this frequency is high, the load on these resources will be high. Increase in the load results in lowering the performance of other Web users accessing the server, which may not be acceptable to them. In this paper, we make a comparative study of different load reducing policies on different parameters and also suggest various directions for future research in the area of reducing load on these limited resources.
Frontiers in Plant Science, 2023
Castor (Ricinus communis L.) is an important nonedible industrial crop that produces oil, which i... more Castor (Ricinus communis L.) is an important nonedible industrial crop that produces oil, which is used in the production of medicines, lubricants, and other products. However, the quality and quantity of castor oil are critical factors that can be degraded by various insect pest attacks. The traditional method of identifying the correct category of pests required a significant amount of time and expertise. To solve this issue, automatic insect pest detection methods combined with precision agriculture can help farmers in providing adequate support for sustainable agriculture development. For accurate predictions, the recognition system requires a sufficient amount of data from a real-world situation, which is not always available. In this regard, data augmentation is a popular technique used for data enrichment. The research conducted in this investigation established an insect pest dataset of common castor pests. This paper proposes a hybrid manipulation-based approach for data augmentation to solve the issue of the lack of a suitable dataset for effective vision-based model training. The deep convolutional neural networks VGG16, VGG19, and ResNet50 are then adopted to analyze the effects of the proposed augmentation method. The prediction results show that the proposed method addresses the challenges associated with adequate dataset size and significantly improves overall performance when compared to previous methods.
Journal of Artificial Intelligence and Capsule Networks (ISSN: 2582-2012), 2022
Insect pests are the one of the important biological factors, that has become an important cause ... more Insect pests are the one of the important biological factors, that has become an important cause of crop yield degradation. However, their identification and detection in the early stages is a very significant task to minimize the overall losses. The conventional techniques with naked eyes to identify the pests is very exigent and require domain specific expertise. It is extremely time-consuming and tedious task to identify the pests in the initial stages with conventional methods. To minimize these issues, some highly developed methods are required to detect insect pests accurately in agriculture. The continuous emergence of machine vision in image processing helps in this regard. This paper presents a comprehensive review to identify the insect pests in the early stages with the help of machine vision techniques. Based on this, a comparative analysis of different classifiers has also been presented.
Advanced Computational Intelligence: An International Journal (ACII), 2016
Present work considers the minimization of the bi-criteria function including weighted sum of mak... more Present work considers the minimization of the bi-criteria function including weighted sum of makespan and total completion time for a Multiprocessor task scheduling problem.Genetic algorithm is the most appealing choice for the different NP hard problems including multiprocessor task scheduling. Performance of genetic algorithm depends on the quality of initial solution as good initial solution provides the better results. Different list scheduling heuristics based hybrid genetic algorithms (HGAs) have been proposed and developedfor the problem. Computational analysis with the help of defined performance index has been conducted on the standard task scheduling problems for evaluating the performance of the proposed HGAs. The analysis shows that the ETF-GA is quite efficient and best among the other heuristic based hybrid genetic algorithms in terms of solution quality especially for large and complex problems.
International journal of engineering research and technology, Mar 27, 2021
Soft Computing can be defined as a science of thinking, reasoning that helps to deal with complex... more Soft Computing can be defined as a science of thinking, reasoning that helps to deal with complex systems. Its main aim is to develop intelligent machines in order to solve realworld problems. It differs from the conventional hard computing as it can handle uncertainty, imprecision easily. It includes use of different techniques such as machine learning, artificial neural networks etc. that can be used together for solving complex problems that are difficult to tackle using conventional models of mathematics. These techniques play a vital role in identifying hidden patterns from the data and doing the classification for making intelligent decisions. This paper reviews some of the soft computing techniques and its applications.
Int. J. Next Gener. Comput., 2020
Educational Data Mining (EDM) is a process in which data mining is applied on students’ data obta... more Educational Data Mining (EDM) is a process in which data mining is applied on students’ data obtained from any educational institution. The importance of data mining is increasing in this field as it can help both in the improvement of education system and in the growth of students by making predictions. Many techniques are used for doing classification and predictions regarding different aspects of education. In this paper, the data mining techniques that are used in education have been discussed with their applications.
Optimization of Simulated Annealing Parameters for Bi-Criteria Multiprocessor Task Scheduling Using RSM - Grey Methodology
Simulated Annealing (SA) has been shown as an exceptional method for finding an optimal solution ... more Simulated Annealing (SA) has been shown as an exceptional method for finding an optimal solution to the combinatorial optimisation problems. In the present work, optimal combinations of different simulated annealing parameters have been identified by using the RSM-based grey relational analysis (GRA) for Bi-criteria multiprocessor task scheduling problem. Parameter selection is needed as SA is a meta-heuristic that doesn't specify all the necessary information for the optimised results. The experiments include 135 sets of data corresponding to samplings obtained from Response surface methodology (RSM) small factorial experimental design for three numeric parameters i.e. initial temperature, Re-anneal interval & weight of objective function with two categorical factors i.e. temperature function & move function respectively. The multiprocessor task scheduling problem of standard LU decomposition with 14 tasks and 4 processors has been considered for simulated annealing parameter...
Advances in Applied Science Research, 2014
Scheduling of a task on a multiprocessor system represented by a directed acyclic graph for minim... more Scheduling of a task on a multiprocessor system represented by a directed acyclic graph for minimizing the different performance measures is a prominent problem in parallel processing. As judgment of an optimal schedule for multiprocessor task scheduling problem is a NP hard problem and different researchers have resorted for devising efficient heuristics. List scheduling heuristics belong to one of the categories used for multiprocessor task scheduling problem. Present work considers the comparative analysis of five commonly used list scheduling heuristics based on makespan and total completion time of the schedule for homogeneous multiprocessors. A defined Performance Index (PI) is used for the comparative analysis of different heuristics and it has been proved that the Insertion Scheduling Heuristic (ISH) Algorithm and Earliest Time First (ETF) Algorithm provides the best results for trade-off between the makespan and total completion time of the schedule.
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, 2020
The utilization of Information Communication Technology for learning and teaching is mandatory no... more The utilization of Information Communication Technology for learning and teaching is mandatory now a day's for the overall development of the students as well the teachers. Research reveals that ICT is useful in developing higher order skills and increasing student's interest in Mathematics. In this paper, the authors discussed some tools of ICT that are helpful in learning and teaching mathematics and making mathematics an interesting subject for the learners.
Uploads
Papers by Satinder Bal Gupta