Browse Items (11855 total)
Sort by:
-
Talent retention, job involvement satisfaction, and commitment towards the organization in the IT sector
Even if there is presently much need for improvement, the information technology (IT) sector plays a key role in the nation's financial development. With enormous growth potential, India's IT sector is up against fierce competition. Numerous participants are competing with one another for resources and jobs inside the company. The direction of events and the manageability of the IT industry depend on capable employees and their responsibilities and participation. Additionally, there is a grouping of the representatives who possess the capacity. Between duty and association and ability maintenance, work fulfilment plays a crucial guiding role. The goal of the current study is to comprehend the effects of talent retention, job satisfaction, and organizational commitment in the IT industry. In this research, we looked at the variables factor analysis. In Bangalore, we chose to survey workers in the IT industry. To understand the results of Talent Retention, Job Involvement, and Commitment for IT Sector Employees, we collected the data using a questionnaire (Likert-scale), which we then analyzed using spss26. 2023 Author(s). -
Mapping of built-up area and change detection in bengaluru using semi-automatic classification
Built-up areas are ever-increasing in nature to cater to the growing population's needs due to the migration of people to urban areas. Indian cities are under stress due to unplanned developmental activities. Land use and the land cover pattern are critical to maintaining the balance of various resources. In this study, Spatio-temporal changes have been mapped from 1989 to 2022 for the Bengaluru urban region. Geospatial techniques have been adopted to map land use, land cover changes and urban growth. Passive remote sensing data sets, which are freely available, were used in this study. QGIS and ESRI's ArcGIS software packages analysed the satellite images. Vegetation indices such as the Normalised vegetation index (NDVI), Normalised Difference Water index (NDWI), and Normalised difference Built-up index (NDBI) have been used along with supervised and unsupervised classification techniques. Images were classified into water bodies, vegetation, built-up area and others. It has been observed that there is an increase in the built-up area decrease in vegetation and water bodies. As per this study, policymakers and society need to consider the conservation of natural resources and developmental activities for sustainable development. 2023 Author(s). -
Urban coastal resilience - An assessment
Increase in the urban area leads to the increase of impervious surfaces which is stressing urban watershed balance resulting in issues like urban flooding in cities around the world. Coastal urban areas experience the pressures of a higher water table which contributes to the rising urban flooding issues of the area. Urban resilience as a concept was developed in cities across the world which includes multiple strategies to cope with the impacts of climate change in cities by integrating engineering and ecological measures. Urban resilience for urban flooding aims to achieve the water balance of an area by balancing the increase of impervious surfaces using ample green and grey infrastructure. This paper aims to understand and evaluate the effectiveness of urban resilience measures implemented in coastal cities worldwide. 2023 Author(s). -
Prediction of Friction Stir Welding Parameters Using Response Surface Methodology
The Friction Stir Welding (FSW) technique results in mixing and densification of weld joint in a more accurate and localized manner. FSW has been used to create a more significant weld with more structural integrity. In this research work, to join AA 3103 and AA 7075 was carried out. These alloys were preferred due to their wide variety of applications varying from aluminium fabrication to the aerospace industry. AA 7075, being a costlier metal, can be partially replaced with AA 3103, which can be economically justifiable for this research. The study tries to reveal the regression model by considering the FSW parameters like speed feed and offset. Various mechanical tests, impact tests and hardness tests were used for determining the most suitable weld joint. After conducting the tests, the results were analyzed using Minitab 18 software. The mathematical equations were derived out of Response Surface Methodology, which proved to be efficient. The report thus discusses the details in the analysis and study of FSW. 2023 American Institute of Physics Inc.. All rights reserved. -
Application of smart manufacturing in business
The application of machine learning to production is becoming a chief objective for businesses all around the world. Smart product-service systems enable digital business model innovation by merging digitized product and service components. The life cycle that comes with the realization of customer value is a critical component of these industrial solutions and manufacturing industry is undergoing significant changes as a result of digitalization and automation. As a result, smart services, or digital services that generate value from product data, are gaining popularity. Customers may now contribute in greater numbers in product design during the design process. Giving more people access, on the other hand, increases the security vulnerabilities associated with cloud manufacturing. Smart Manufacturing is one of the technology-driven approach to manufacturing that uses network-connected machines to monitor the process. Smart manufacturing has the ability to be used in a variety of ways, including putting sensors in manufacturing machines and collecting data on their operating state and performance. Thus, the main purpose here is to find ways to improve and automate production performance. This conceptual paper attempts to give a view of how a smart intelligence system may be used in business and how individuals and organizations can produce value. 2023 Author(s). -
The future of urban life: The technological and humanistic dimensions of cognitive cities
A smart city implies realising sustainable city growth enabled by technology-based intelligent solutions to give its citizens a good quality of life. Information and communication technologies play a crucial role as the nerve centre of the smart city for collecting and analysing data from various sources, like mobile, social media, and sensors. The Internet of things (IoT) and big data (BD) also play a critical role in smart city infrastructures, changing how we analyse patterns and trends in human behaviour. Smart cities generate massive amounts of data and therefore need many flexible ways to process data and implement solutions. Recently, cognitive analytics have attracted the attention of researchers and practitioners worldwide as a technology-based innovative solution. It is a novel approach to information discovery and decision-making which uses multiple intelligent technologies such as statistical machine learning, deep learning, distributed artificial intelligence, natural language processing and visual pattern recognition to understand data and generate insights. A cognitive smart city refers to the convergence of emerging IoT and smart city technologies to realise cyber-physical social systems, their generated big data from sensing to communication and computing, and artificial intelligence techniques for all aspects of collaborative computing in sensors, actuators and human-machine interfaces. The field of humanities typically approaches the concept of cognitive cities from a cultural, philosophical, and humanistic perspective. Humanities scholars examine how cities shape our thoughts, beliefs, values, and experiences and how they impact our collective memory and identity. They consider the role of cities as sites of cultural production and consumption and explore the social and political implications of urbanisation and technological advancement. This paper aims to highlight the connection between technology and the humanities in the context of cognitive cities. The paper will explore the technological aspects of cognitive cities and their cultural, humanistic, and philosophical implications. 2023 Author(s). -
Graph theory in security, utility, aesthetics and affordability
The theory of Domination in graphs is used in security systems. Landscaping uses planarity and crossing number. In layout designs, hamiltoincity is regulalry used. Edge-weighted graphs and Max-Flow Min-Cut models are also discussed in this paper. 2023 Author(s). -
Impact of green bonds issuance on stock prices - Evidence from India
Today, with the increasing global warming, many companies are trying to adopt sustainable ways of producing the product and preserve the atmosphere. A green bond is one such financial tool that helps companies to raise the funds for social and eco-friendly projects. Keeping this in view and the Indian market emerging as the second-largest bond market in terms of green bond issuance; this paper aims to identify the impact on stock prices due to the issuance of green bonds by the companies. We conduct an event study to understand how the stock prices are subject to volatility due to green bond issuance during the period 2018-2021. The data is collected from secondary sources like Economic Times, Business Standard, Climate Bond Initiative, and the BSE website. The event window is assumed to be [-30,30], [-15, 15] and [-7, 7] days. Using Cumulative Average Abnormal returns and t-tests we understand the volatility of stock prices due to green bond issuance. The empirical results show that green bonds have a short-term impact on stock prices. Overall, the study can be a great input for the investors to understand the behavior of stocks due to the issuance of green bonds. 2023 Author(s). -
Addressing challenges and opportunities in enhancing water quality for irrigation
The rapidly changing quality of irrigation water is a pressing issue that needs to be addressed in order to understand and predict the long-term effects on soils and crops in a world that is facing increasing water stress. The use of irrigation in agriculture is becoming increasingly reliant on sources of water that are poorly understood and largely unmonitored. This trend has led to a decline in water and soil quality in many areas. While soil salinization and reduced crop productivity have traditionally been the main concerns when it comes to the quality of irrigation water, there is now evidence that geogenic contaminants, such as trace elements and an increase in the use of wastewater, are also affecting irrigation water quality. The ability to measure extremely small concentrations of biologically-active organic contaminants, including plasticizers, pharmaceuticals, personal care products, and steroid hormones, in various irrigation water sources allows us to evaluate their uptake and occurrence in crops. However, it does not address questions related to food safety or the potential health effects on humans. Additionally, natural and synthetic nanoparticles are now known to be present in many water sources, which may alter plant growth and impact food standards. 2023 Author(s). -
Identification of the Functional Limitation of Marine Loading or Unloading Arm; A Case Study
Marine loading or unloading arms are used to transfer product from tanker vessels that often carries products like petroleum or chemicals from or to the tankers. Cochin Port has dedicated Tanker jetties for handling petroleum with Marine Loading Arms installed for safe handling of cargo. However, my studies in Cochin Port Trust have shown that it has a potential threat to tackle while it is taken for the maintenance process. The case study aids in understanding of the working of marine unloading arm installed in the port and to identify the functional or safety limitations of the existing model installed. This case study also proves that a small change in the design can bring about a big change in the safety of the people working with the equipment. The identified parameters have been studied for providing the necessary alterations of the design which could be implemented on the upcoming project of constructing the marine unloading arm in Cochin Port Trust. To support faster and safety loading/unloading requirement these hydraulically operated marine loading arms are fitted with emergency release couplings and emergency release system. Marine Loading Arms are operated by using the hydraulic system. During maintenance procedure while checking the Emergency Release System (ERS) functionality, accidental release of Emergency release coupling can cause fatality. Hence a fool proof design is suggested with an extra locking arrangement. The studies conducted till now and the reviews conducted contributed in the analysis of the development and validation of the design. A design of a locking machanism for preventing the fatality is created and analysed for suggesting it to the industry so that it could be incorperated in the upcoming project of constructing the marine loading and unloading arm. 2023 American Institute of Physics Inc.. All rights reserved. -
Experimental investigation of boundary shear stress in meandering channels
Laboratory experimentation for bed shear stress distribution has been carried out in two sets of meandering channels. The channels have cross-over angles of 110 and 60 constructed by 'sine-generated' curves over a flume of 4?m width. Variations in bed roughness were studied for the meandering main channel. Bed shear stress distribution across a meandering length for the 110 and 60 channels was examined for different sinuosities and roughnesses. The boundary shear stress study illustrated the position of maximum shear along the apex section and across the meandering path. These variations were observed for different flow depths. A comparison of the bed shear among the three experimental channels was conducted, and the results were analyzed. 2023 Author(s). -
Structural analysis of log periodic and monopole antennas considering cyclonic, interference effects
The Broadband High Frequency (HF) Transmit and Receive Antenna System are used as Surface Waveover the Horizon Radars (SWOTHR) for surveillance application. HF Transmit & Receive antenna systemconsists of transmit antenna and receive antenna array operating in HF band 2 to 30?MHz, which have tobe installed near sea shore. The antennas are of Monopole and Log periodic Dipole wire mesh antenna (LPDA). The height of Monopole and LPDA depends on wavelength ? of antenna. For HF band, the height range of receive is from 5 to 25m and transmit is from 10m to 100m. In this study, 10m high monopole for receive and 55m high 60m long Log periodic antenna for transmit are considered. Structural analysis and design of these antennas is critical due to installation at sea coasts. Based on the application, receive antennas are designed as array type consisting of 64 numbers monopoles as 32 doublet's and transmit antennas are 2 numbers of LPDA. If the same height structures installed side by side as an array, wind interference is caused by the obstruction caused by a structure in the path of wind. The antennas are installing on sea coast subjected to cyclonic storms. Dynamic effect of cyclonic and interference of wind is studied. Wind loads are calculated as per IS: 875 part 3:2015. Antennas are analyzed using FEM software STAAD Pro Advanced Connect Edition. Both antennas are analyzedfor self-weight, wind loads considering cyclonic and interference factors. Natural frequency of structure is determined using modal analysis to examine the problems of wind induced oscillations and dynamic effects of wind. 2023 Author(s). -
A Comparative Study of Machine Learning and Deep Learning Algorithms to Predict Crop Production
Agriculture is a field that plays an essential part in strengthening a country's economy, especially in agrarian countries like India, where agriculture and crop productivity play a large role in the economy. The research focuses on comparing machine learning and Deep learning algorithms in predicting total crop yield production. The parameters considered for the study are State name, District name, Year, Season, Crop, Area and Production. The dataset is resourced from the data.gov.in website. Random forest from Machine Learning and Sequential model from Deep learning are compared, and the performance metric considered for the study is R2 score. The objective is to assess how well the independent variable predicts the variance in the dependent variable. Random Forest algorithm achieved an R2 score of 0.89, whereas Deep Learning Sequential algorithm gave an R2 score of 0.29. 2023 American Institute of Physics Inc.. All rights reserved. -
Non-Fungible Token (NFT): Bubble or Future in the World of Block Chain Technology
The introduction of blockchain technology entering into human existence, which is a reinforcement of the cryptocurrency space, is both a concern and an opportunity. The main motivation underlying such an invention is conditional transparency and the unmatched ability to protect people against data destruction. The collecting drive of NFTs is profitable and also has sparked curiosity, with everyone vying for the first piece of the package, increasing the future Value of an NFT, as it is a very new topic about NFT using block-chain technology. It is something quite about a flurry of blockchain technological stories that leave us wondering. In this research paper, we explained the new emerging Non-Fungible Token (NFT), its uses, and implications. 2023 American Institute of Physics Inc.. All rights reserved. -
Leveraging Robotic Process Automation (RPA) in Business Operations and its Future Perspective
Robotic Process Automation (RPA) is used to automate the business process operations including its capabilities to mimic the routine tasks, which requires less human intervention. RPA has seen crucial take-up practically throughout the last few years because of its capacity to reduce expenses and quickly associate heritage applications. Fundamentally RPA would perform automated tasks much like as an individual to accomplish objectives productively and adequately. This article analyses the features in current business conditions to comprehend the movement of RPA and automated interaction has carried to substitute the businesses with automated tasks. RPA is an innovative technology which utilizes software programming to execute enormous capacity assignments that are routine and time-consuming in the business cycle. RPA streamlines by playing out those undertakings proficiently as it reduces cost and saves assets of an association as programming works till the finishing of the assignment. This study aligns with the descriptive approach and leveraging Robotic Process Automation into business operations. This article also addresses the different players in the RPA Technological segment. This study also discussed and suggested selecting RPA Vendors in a future perspective. 2023 American Institute of Physics Inc.. All rights reserved. -
FOPID controller tuning: A comparative study of optimization techniques for an automatic voltage regulator
This study evaluated a fractional order proportional-integral-derivative (FOPID) controller optimization with a fractional filter for an automated voltage regulator (AVR) system. For the suggested controller, a variety of different parameters can be changed. For the purpose of creating the optimum PID controller for an automated voltage regulator system, comparative analysis using multiple optimization methodologies is carried out. The Salp Swarm Algorithm (SSA), Ant Lion Optimization (ALO), and Particle Swarm Optimization algorithm (PSO) are the techniques that are being examined in this study. The settling time, rising time, and overshoot performance indices is being used. The transient responsiveness of the AVR system was increased by each of the recommended optimization techniques in a different way, and early results were optimistic. The comparison with the most ideally tuned FOPID controllers for the AVR system also serves to support the superiority of the suggested controller. 2023 Author(s). -
Artificial Intelligence & Automation: Opportunities and Challenges
Artificial Intelligence (AI) and Automation innovation are growing at a steady rate that are changing organizations and bringing efficiency and adding to the economic development. The utilization of AI and robotization will likewise help improve different areas from wellbeing to horticulture. Furthermore, utilizing Automation and Artificial Intelligence would, follow the schedule, transform the idea of work and the working environment itself. For sure, machines will actually do large numbers of the undertakings typically done by people, just as supplement manual work and play out certain errands that an individual wouldn't have the option to do. Consequently, AI and mechanization have a great deal to bring to organizations and enterprises worldwide. This research paper comes up with a rundown through the blooming of Artificial Intelligence and Automation. We explored the existing potentiality of cognitive emerging technologies. This paper outlines the discussion about artificial intelligence and automation technologies and an overview of the applications. 2023 American Institute of Physics Inc.. All rights reserved. -
An Investigation to the Hardness of the Cutting Tool During Machining Inconel 718 due to the Cryogenic Effect
The machining of superalloy Inconel 718 has seen a rapid demand in industries due to the superiority factor of its composition which makes it corrosion resistant, wear resistant and abrasive resistant. Due to these advanced features of this alloy, the cutting tool to be used to machine becomes a challenging one. There have been several cutting tools being used in the machine but wear of the tool and high surface roughness has been observed. Two cutting tools Tungsten Carbide RYMX 1004-ML TT3540 and Ceramic AS20 has been identified but the hardness on it is failed due to the machining conditions. The cryogenic treatment of these tools can see a remarkable change in machining and bring low surface roughness and reduce tool wear. 2023 American Institute of Physics Inc.. All rights reserved. -
Can Artificial Intelligence Accelerate and Improve New Product Development
Today, AI have successfully set up a good foundation in a broad scope of business processes. Associations including AI for product headway processes have uncovered more huge yields on hypotheses, better viability in their cycles, and effective utilization of resources. A sensible headway framework is paramount for capable product development, especially for complex endeavours. AI thinking is in like manner improving new product development. AI is probably going to experience clients in numerous areas. New yield evolution as in collaboration utilizes its capital and capacities to make another item or work on a current one. Product development is viewed as one among the fundamental cycles for progress, endurance, and recharging of associations, especially for firms in, by the same token, quick-moving or cutthroat business sectors. AI assists people's lives by expanding connections creating and multiplying items that can work with individuals' daily exercises in quite a large number of areas. Consequently, the impact of involving Artificial Intelligence for new developments is to induce things simpler. This paper attempts to outline the acceleration of new product development with the help of artificial intelligence technology. This study addressed the tailored AI in product improvement and product development transformation. Lastly, this article points out how AI accelerates product development and future outlook. 2023 American Institute of Physics Inc.. All rights reserved. -
An Novel Cutting Edge ANN Machine Learning Algorithm for Sepsis Early Prediction and Diagnosis
Early detection and diagnosis of sepsis can significantly improve patient outcomes, but current diagnostic methods are limited. The problem addressed in this paper is the early detection and diagnosis of sepsis using machine learning algorithms. Sepsis is a life-threatening condition that can rapidly progress and cause organ failure, leading to increased mortality rates. Early detection and treatment of sepsis are critical for improving patient outcomes and reducing healthcare costs. However, sepsis can be challenging to diagnose, and existing methods have limitations in terms of accuracy and timeliness This research proposes a new cutting-edge Optimized Artificial Neural Network machine learning algorithm for sepsis early prediction and diagnosis. The proposed algorithm combines different data sources, including patient vital signs, laboratory results, and clinical notes, to predict the likelihood of sepsis development. The algorithm was evaluated on a large dataset of patient records and achieved promising results in terms of accuracy, Precision and Recall. The proposed algorithm can potentially serve as a valuable tool for clinicians in the early detection and diagnosis of sepsis, leading to better patient outcomes. 2023 American Institute of Physics Inc.. All rights reserved.