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An IoT-Based System for Fault Detection and Diagnosis in Solar PV Panels
This abstract describes an IoT-based system for fault detection and diagnosis in solar PV panels. The proposed Fuzzy logic-based fault detection algorithms aims to improve the performance and reliability of solar PV panels, which can be affected by various faults such as shading, soiling, degradation, and electrical faults. The system includes wireless sensor nodes that are deployed on the panels to collect data on their electrical parameters and environmental conditions, such as temperature, irradiance, and humidity. The collected data is then transmitted to a central server for processing and analysis using machine learning algorithms. The system can detect and diagnose faults in real-time, and provide alerts and recommendations to maintenance personnel to take appropriate actions to prevent further damage or downtime. The system has several advantages over traditional manual inspection and maintenance methods, including reduced downtime, lower maintenance costs, and improved energy efficiency. The proposed system has been validated through experimental tests, and the results show that it can accurately detect and diagnose faults in solar PV panels with high reliability and efficiency. 2023 EDP Sciences. All rights reserved. -
Efficiency of Indian Banks with Non-Performing Assets as Undesirable Outputs
The performance evaluation of any banks is of utmost importance for bank management, investors, and policymakers. Due to globalization, all the banks are working in a competitive environment. Several risk factors affect the operational efficiency of banking system. This study aims to evaluate the efficiency of Indian banks with NPAs as uncontrolled variables. Due to the nature of NPAs, these are assumed as undesirable outputs in the DEA modelling. The results reveal that public sector banks experienced more input losses due to NPAs compared to private banks. The private banks experienced more loss in inputs due to the scale of operation. The Wilcoxon Signed-Rank test shown that the impact of NPAs and scale of operation are statistically significant at 0.05 level. 2023 American Institute of Physics Inc.. All rights reserved. -
Character recognition for Malayalam palm leaf manuscripts: An overview of techniques and challenges
Kerala is a small, ocean-facing state in South India and has been home to several ancient civilizations in the past. The yesteryears have rewarded the state with great cultural heritage, monuments, historic artifacts and the like. Palm leaf manuscript is one such antiquity. Before paper became common, palm leaf was the medium for writing in Kerala. Such manuscripts capture the glory of our past and deals with different domains such as arts, astrology, medicine, science, religion and spirituality. Palm leaf manuscripts have value both as a cultural asset and as a knowledge repository. Palm leaf manuscripts are organic and degrades with age. The environmental conditions can also accelerate its degradation. A viable solution in preserving the knowledge contained in these manuscripts is Handwritten Character Recognition (HCR). Digitized manuscripts have infinite life. Character recognition in Indian languages, including Malayalam, is considered a complex process mainly due to the size of character set, the similarity of characters and the presence of compound characters. This paper surveys existing works in the field of HCR relevant to Malayalam palm leaf manuscripts. 2023 Author(s). -
Exploring Explainable Artificial Intelligence for Transparent Decision Making
Artificial intelligence (AI) has become a potent tool in many fields, allowing complicated tasks to be completed with astounding effectiveness. However, as AI systems get more complex, worries about their interpretability and transparency have become increasingly prominent. It is now more important than ever to use Explainable Artificial Intelligence (XAI) methodologies in decision-making processes, where the capacity to comprehend and trust AI-based judgments is crucial. This abstract explores the idea of XAI and how important it is for promoting transparent decision-making. Finally, the development of Explainable Artificial Intelligence (XAI) has shown to be crucial for promoting clear decision-making in AI systems. XAI approaches close the cognitive gap between complicated algorithms and human comprehension by empowering users to comprehend and analyze the inner workings of AI models. XAI equips stakeholders to evaluate and trust AI systems, assuring fairness, accountability, and ethical standards in fields like healthcare and finance where AI-based choices have substantial ramifications. The development of XAI is essential for attaining AI's full potential while retaining transparency and human-centric decision making, despite ongoing hurdles. 2023 EDP Sciences. All rights reserved. -
Artificial intelligence: A new model for online proctoring in education
As a result of technological advancements, society is becoming increasingly computerized. Massive open online courses and other forms of remote instruction continue to grow in popularity and reach. COVID-19's global impact has boosted the demand for similar courses by a factor of ten. The ability to successfully assign distant online examinations is a crucial limiting factor in this next stage of education's adaptability. Human proctoring is now the most frequent method of evaluation, which involves either forcing test takers to visit an examination centre or watching them visually and audibly throughout tests via a webcam. However, such approaches are time-consuming and expensive. In this paper, we provide a multimedia solution for semi-automated proctoring that does not require any extra gear other than the student's computer's webcam and microphone. The system continuously monitors and analyses the user based on gaze detection, lip movement, the number of individuals in the room, and mobile phone detection, and captures audio in real time through the microphone and transforms it to text for assessment using speech recognition. Access the words gathered by speech recognition and match them for keywords with the questions being asked for higher accuracy using Natural Language Processing. If any inconsistencies are discovered, they are reported to the proctor, who can investigate and take appropriate action. Extensive experimental findings illustrate the correctness, resilience, and efficiency of our online exam proctoring system, as well as how it allows a single proctor to simultaneously monitor several test takers. 2023 Author(s). -
Regression Test List Sharding in a Distributed Test Environment
One of the major issues during the regression test of the new version of Real Time Operating System (RTOS) is the time involved in test case execution. The main reason being a single embedded system device under test (DUT) is used to execute the test list containing several test cases. This traditional method of regression test also leads to wasted productivity of the other devices at hand that could be otherwise used during this regression test. Hence, in this paper, we propose a technique that aims at reducing the overall regression test cycle time of a newer version of a Real Time Operating System (RTOS) by employing a method known as "test-list sharding"in a distributed test environment. In the proposed work, multiple DUTs are connected to the test server via a communication network. The test server executes the test list containing several test cases and performs the test-list sharding, that is, distributing test cases to different DUTs and executing them in parallel. After the test is executed on the DUT, the test results are sent back to the test server which will summarize all the results. In the proposed work, the sharding is done by distributing the test cases without overloading or under loading any of the DUTs. Test list is sharded in such a way that the same tests are not sent to multiple DUTs. The main advantage of the proposed method is that the test sharding can be easily scalable to accommodate any number of devices that can be connected to the test server. Also, the test list sharding is done in a dynamic way so that the tests are distributed to an idle DUT that has completed a test execution and ready for another test to execute. The comparison study of executing a sample test list sequentially on a single DUT and distributed test system with multiple DUTs is performed. Results obtained showed the performance gain in terms of test cycle time reduction, scalability, equal load distribution and effective resource utilization. 2023 EDP Sciences. All rights reserved. -
Growth of online social networking and artificial intelligence in digital domain
In this millennium years of technology, machinery is evolving daily. There is plethora of things being affected by this evolution. One of which is our practices of social networking which is largely veering to the internet. Internet social networking has become one of the biggest buzzwords. From a child to an old person, everyone is on these social networking sites and applications. Within the span of 5 to 10 years these so-called Internet social networking sites and applications have taken over the real social gathering or meetings. Now with single click you can buy or sell goods and services at any place and any time. People can connect to one another even when far from home. The pandemic times and demonetization are the two instances that made everyone switch to and accustomed to the aspects of social networking. In the particular research paper, the researcher will put forth how data privacy and security is one of the biggest concerns in this social networking. Secondly, the researcher will understand the role of Artificial Intelligence in Online Social networking and whether it is helpful or not. 2023 Author(s). -
Parametric analysis of control parameters for investigating the machinability of inconel 718 using ceramic inserts of round type
Inconel 718 is a nickel-chromium based super alloy and has high corrosion and thermal resistance, high hardness, and high thermal strength at elevated temperatures which makes it difficult to cut. Due to these mechanical properties, it is being used in toughest conditions and hence the tool life is extremely short. This hard to cut metallic alloy has a wide scope in the field of bio medical industry, aerospace industry, bearing industry, steam turbine and nuclear applications and the demand has rapidly been increased in the recent years. Ceramic insert is one such cutting tool being used in the machining of this metal and study is still being conducted to increase the machinability. This paper investigates the machinability characteristics for determining the machinability of Inconel 718 using ceramic insert based on Grey Relation Analysis (GRA) and signal to noise (S/N) ratio. The input parameters such as feed rate, cutting speed and depth of cut are taken into consideration to obtain the suitable response parameters such as minimal surface roughness and low tool wear rate to improvise the machining characteristics of this superalloy. Ceramic inserts had even been cryogenic treated to provide better machining conditions on the Inconel 718. 2023 Author(s). -
Blockchain Technology: Applications and Challenges in Computer Science
In the growth of computer science blockchain technology has emerged as a disruptive force that is enhancing various area of software and the way data is managed, stored, and safeguarded. This essay offers a thorough examination of the uses and difficulties of blockchain technology in computer science. In this essay, blockchain technology has shown itself to be a game-changing innovation with numerous computer science applications. It has the enormous potential to completely transform sectors including finance, supply chain management, healthcare, voting systems, and IoT devices. The software technology is completely achieved with blockchain technology and the main security issue is solved with energy use and scalability. The new opportunities are examined and addressed with this innovation sector for creating effective solutions. 2023 EDP Sciences. All rights reserved. -
A Study of Financialization of Commodity Markets in India
For numerous financial institutions, Commodity Futures (CF) has emerged as a widespread asset class since the 2000s. From 2000 to 2010, the estimation of the number of commodity index traders quadrupled, also, the number of hedge funds tripled. Recently, it has been noticed that in India, there occurs a vast inflow of investment toward the CF. Simultaneously, there occurs a problem of extremely higher prices along with volatility in commodity prices in India. However, studies on the financialization of the Commodity Market (CM) in India are not sufficient. This study was presented for analyzing the role of the financialization of CMs in India. Analyzing the association betweenCMs and equities markets in India is the major intention behind this study. Here, the Indian- MCX of India, the NSE of India, and the S&P500 Index are the sources from where the data has been gleaned. The outcome has been evaluated by utilizing a vector autoregression. The output demonstrated that no positive interdependence was exhibited by the correlation betwixt MCX Comdex returns and CNX Nifty. Consequently, a higher percentage of the mean value was attained by the commodity of daily returns of metal of commodity of agriculture. 2023 EDP Sciences. All rights reserved. -
Cryptography: Advances in Secure Communication and Data Protection
In the innovative work secure communication and data protection are being main field, which are emerged by cryptography as a fundamental pillar. Strong cryptographic methods are now essential given the rising reliance on digital technologies and the threats posed by bad actors. This abstract examines the evolution of secure communication protocols and data protection techniques as it relates to the advancements in cryptography. The development of post-quantum cryptography is the most notable development in cryptography discussed in this study. As quantum computers become more powerful, they pose a serious threat to traditional cryptographic algorithms, such as RSA and ECC. Designing algorithms that are immune to attacks from quantum computers is the goal of post-quantum cryptography. Lattice-based, code-based, and multivariate-based cryptography are only a few of the methods that have been investigated in this context. 2023 EDP Sciences. All rights reserved. -
Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema
Pneumonia is a dangerous disease that can occur in one or both lungs and is usually caused by a virus, fungus or bacteria. Respiratory syncytial virus (RSV) is the most common cause of pneumonia in children. With the development of pneumonia, it can be divided into four stages: congestion, red liver, gray liver and regression. In our work, we employ the most powerful tools and techniques such as VGG16, an object recognition and classification algorithm that can classify 1000 images in 1000 different groups with 92.7% accuracy. It is one of the popular algorithms designed for image classification and simple to use by means of transfer learning. Transfer learning (TL) is a technique in deep learning that spotlight on pre-learning the neural network and storing the knowledge gained while solving a problem and applying it to new and different information. In our work, the information gained by learning about 1000 different groups on Image Net can be used and strive to identify diseases. 2023 EDP Sciences. All rights reserved. -
Skewed Food Policies, Distorted Inter-crop Parity, and Nutri-cereal Farmers - An Empirical Analysis
Farmer profitability, cost of food production, and associated issues of nutri-cereals are analysed by leveraging a large database spanning a 35-year period. The skewed food policies being followed in India are highlighted here. An unacceptably high distortion in inter-crop parity was found, which led to loss of profitability, increased costs, and lower prices for the nutri-cereals. The policymakers must take corrective measures in several aspects, including technologies, prices, input provision, processing, storage, and distributional policies to promote the production and consumption of nutri-cereals in India. 2023 Economic and Political Weekly. All rights reserved. -
Some results on b-chromatic topological indices of some graphs
Graph coloring is assigning weights, integers, or colors to edges, vertices, or both in a graph subject to certain conditions. Proper coloring C of graph G refers to assigning weights, integers, or colors to the vertices, edges, or both so that adjacent vertices or adjacent edges get a different color. A b-coloring follows proper vertex coloring with subject to an additional property that each color class should have at least one vertex with a neighbor in all the other color classes. The notion of Chromatic Zagreb index and irregularity index was introduced recently. This paper introduces the concept of b-Chromatic Zagreb indices and b-Chromatic irregularity indices. Also, we compute these indices for certain standard classes of graphs. 2023 Author(s). -
Irreducible tensor approach to study ? + d ? d + ? 0
The study of photoproduction of mesons plays an important role in understanding the properties of strong interactions. Pion photoproduction on deuterons has been studied theoretically for several decades. At the VEPP - 3 storage rings, tensor analysing powers in ? + d ? d + ?0 have recently been measured. In light of these advances, we suggest adopting an irreducible tensor technique to explore the reaction ? + d ? d + ?0 at close to threshold energies. Our method, which is model-independent, works well for predictions regarding spin observables. By describing the differential cross section in terms of multipole amplitudes, the angular dependence of the cross section will be studied. 2023 Author(s). -
Distance based properties of the semi splitting block graph of graph
The bounds on the radius and diameter of the semi splitting block graph (SB(G)) of graphs are investigated. The diametral paths and self-centeredness of semi splitting block graph of any connected graph are analyzed. The graphs where the diameter of G and SB(G) are the same are characterized and the number of blocks in the diametral path of such graphs is analyzed. 2023 Author(s). -
Deep learning for intelligent transportation: A method to detect traffic violation
Smart transportation is being envisaged as an important parameter in building smart cities. Although conceptualized to have major advantages, lack of intelligent systems makes more vulnerable for disasters. The number of fatality due to road accident has increased up to 12% in 2022 as that of previous year says the WHO report. There are large number of new vehicles plying on roads which makes space constraint for the commuters. This makes a large number of traffic violations happening in urban areas. The smart cities insist and tries to adopt AI based methods for identifying traffic violations. Computer Vision are predominant solution in detecting traffic violation. This paper proposes a Deep learning method using famous YOLOV technique for object detection for effectively determining the traffic violation. The violations such as signal cross are concentrated in this research. The experimental results prove that the proposed technique has 95.1% of classification accuracy in detecting signal crosses. 2023 Author(s). -
Early strength of concrete amended with waste foundry sand - A potential for early open to traffic (EOT) pavements
The most predominant and widely practiced methods for waste disposal are Landfill, Incineration, and composting. There is a scarcity of land for waste disposal and because of increasing land cost, recycling and utilization of industrial by-products and waste materials has become an attractive proposition to waste disposal. There are several types of industrial by-products and waste materials. The utilization of such materials in concrete not only decreases the overall cost of construction but also helps in reducing disposal concerns. One such industrial by-product is waste foundry sand (WFS). The annual production is about 3 million tons from different industries in India. In the metal casting process, foundry industries dispose of huge quantities of waste sand into landfills, causing a harmful impact on the environment. The silica-based spent foundry sands from iron, steel, and aluminum foundries are evaluated in the risk assessment. This paper mainly focuses on achieving concrete for EOT (Early Open to Traffic) rigid pavements with WFS along with the use of accelerator and super-plasticizer. Effects of WFS on concrete properties such as compressive strength and split tensile strength are presented. Two types of mix proportions were investigated in this study. FDOT (Florida Department of transportation) and IRC (Indian Road Congress) recommendations were adopted for mix proportions using 5% & 10% of WFS replaced partially for M-Sand. 1-day compressive strength for FDOT mix with 10% WFS was 30MPa & for IRC mix with 10%, WFS was 20?MPa. The 3-days strength for mixtures with 10% WFS was 45MPa & 47MPa for FDOT & IRC mix proportions, respectively. Though the strength decreased with the inclusion of WFS, the 1-day and 3-days strength achieved for mixtures with 10% WFS surpassed the minimum strength requirements as per the slab replacement guidelines. Normally the pavement will be open to traffic after three to four days of laying asphalt, this method of using foundry sand enables the pavements to be open to traffic inless than a day. 2023 Author(s). -
Environmental hazards and disasters - A response towards mitigating disaster management
In today's world, our entire planet is under tremendous strain from various natural catastrophic events such as earthquakes, tsunamis, drastic weather changes, hurricanes, global warming, diminishing of glaciers, occurrences of landslides, etc. Such a difficult situation is encountered due to the overhasty extraction of non-renewable natural resources of our planet and the growing rate of presence of humans in the world. It affects the environment to a great extent. Such ventures lead the entire globe towards disastrous events which are irreversible and prepare us to face the worst situation. Hence, the policymakers should develop sophisticated policies focused on advanced disaster management technologies and adopt new methodologies. Several integrated research on disaster prevention programs is already being conducted, even though continuous exploration in this field aligned with all possible consequences is very important. The conclusions and suggestions from research papers will be carefully analyzed to drive the most effective approach to handling such atrocious situations. 2023 Author(s). -
A LSTM based model for stock price analysis and prediction
The share market in India is exceedingly unpredictable and volatile, with an infinite range of factors regulating the share market's orientations and tendencies; hence, forecasting the upswing and downturn is a difficult procedure. Because of several essential aspects, the principles of share market have always been unclear for shareholders. This study aims to significantly reduce the likelihood of analysis and forecasting with Long Short-term Memory (LSTM) model approach that is both resilient yet easy is still suggested. LSTM is a complete Learning Model that is a Predictive Method. Conversely, advancements in technology have opened the way for more efficient and precise share market forecasting in current times. Using the provided historical data sets, the results showed that the LSTM model has considerable potential for forecasting. 2023 Author(s).