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Secure Bitcoin Transaction and IoT Device usage in Decentralized Application
In the recent years, there has been a boom in the number of connected devices due to developments in the field of Internet of things. This has also increased the requirements of security specification. The proposed method is introducing a secure information transmission system by using Blockchain technology. Blockchain is a relatively new technology which was introduced by stoshi nakamoto, which was also the basis for developing crypto currency [bitcoin]. Crypto currencies are made transparent and secure using their network architecture, which is a combo of a decentralized and distributed network. In this paper is try to exploit the same methodology used in crypto currencies to develope an IOT network, where the devices can talk to their peers in a secure manner. They explored all the different networks and features of developing a Decentralized application that is named as Dapp. 2018 IEEE. -
Label-Based Feature Classification Model for Extracting Information with Dynamic Load Balancing
Efficient extraction of information from various sources is very tedious. Achieving this requires very sophisticated feature classification model and ability of the system to adapt to changing environments of data and its random distributions with an efficient use of computational resources. Label-based feature classification model (LFCM) with dynamic load balancing is proposed to address an efficient model to extract information in data set. This technique is effective in data analysis to discover the new feature set. Label approach incorporates unique label concept and it avoids any data duplication using labels. Each data sample is assigned to only one label to improve the accuracy and effectiveness of the retrieval process. Based on the data relevancy and specific features that can be extracted using proposed algorithm, classification model and semantic representation of data in vector form minimizes the data loss, and dimensionality reduction plays a vital role in building an efficient model. Various graphs and results obtained from the experiments show an improvement of information extraction using this proposed labeled LFCM approach. This approach brings lots of real time challenges that are handled to bring accuracy factor as the main focus in this proposed system. Both classification and extraction uses different model to obtain the intended results. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Arts education, academic achievement and cognitive ability
Although art is often considered to be a means for maximizing human potential, the causes and consequences of artistic experiences are poorly understood. The present chapter reviews the relevant literature concerning the consequences of participating in the arts. It is clear that training in the arts improves performance on arts-specific tasks. For example, children who take music lessons perform better than their untrained peers on musical tasks such as perceiving musical key and harmony (Corrigall and Trainor, 2009). But training in the arts may also be associated with performance in non-arts domains. This chapter examines the possibility of four such associations, namely whether arts education is associated with academic achievement, general cognitive ability, language processing and visuospatial skills. In each case, the literature is evaluated in terms of the consistency of the findings and the evidence for claims of causation. Training in the arts and academic achievement Training in the arts is associated positively with academic achievement. For example, in a sample of Canadian high-school students, participation in musical activities in the eleventh grade predicted academic achievement in the twelfth grade (Gouzouasis, Guhn and Kishor, 2007). Other results point to similar associations between academic achievement and involvement in any type of arts-related activity. In one study that included more than 25,000 American high-school students, arts participation and school grades were recorded during the eighth, tenth and twelfth grades (Catterall, Chapleau and Iwanaga, 1999). At each point in time, students who were involved in the arts had better grades than other students. A similar positive association emerged in a meta-analysis of five correlational studies (Winner and Cooper, 2000). In a larger meta-analysis of 10 years of data from the American College Board (198898), Vaughn and Winner (2000) concluded that compared to students without arts training, students reporting any form of arts involvement (dance, drama, music and visual arts) obtained higher scores on the Scholastic Aptitude Test (SAT). This advantage for the arts group was evident for the verbal score, the mathematics score and the composite score. Students with drama lessons showed the strongest association, followed (in descending order) by students studying music, painting and dance. Even enrollment in theoretical classes (e.g., music or art history courses) was predictive of better SAT scores. Cambridge University Press 2014. -
Full Reference Image Quality Assessment (FR-IQA) of Pre-processed Structural Magnetic Resonance Images
Deep learning-based Artificial Intelligence algorithms have surpassed human-level performance in many fields including medicine. Specifically in diagnosis using radiology images, deep neural networks empowered AI to excel by educating intricate nonlinear relationships which is a core part of the complicated radiology problems. However, these models require a massive amount of quality data for training. The accuracy of the deep learning model is based on the amount of training data and the quality of the trained data being fed. So, preprocessing the data from different capturing devices is inevitable. This study aimed to highlight some of the image quality metrics that can be used to quantify the efficiency of the chosen preprocessing pipeline. By quantifying the result of each preprocess step, the user can choose an optimal set of preprocesses that can greatly improve the image quality, leading to a high and accurate diagnosis through a deep learning model. Thus, this study detailed how the full reference image quality metrics can be used to validate the performance of sMRI preprocess tasks. 2024 IEEE. -
Exploring the genuineness of CSR in India between two different major public sector companies reliance power & shell petroleum a case study /
The past two decades have witnessed a remarkable change in the way businesses run and operate. Profit maximization no longer remains the focus of businesses. The turn of events, have pressurized firms to put serious efforts into a wide range of social responsibility activities and thus shift the corporate goals from socio-economic focus towards increasing shareholder value to the welfare of all stakeholders. This study aims at understanding how genuine the Corporate Social Responsibility (CSR) in India is by looking at two rival power company’s giants - Reliance power and Essar Power. -
Machine Learning Approach for Evaluating Industry-Based Employer Ranking and Financial Stability
Using the computational prowess of machine learning, this study presents a fresh method for assessing the relative standing and fiscal health of employers across different sectors. The research makes use of a wide variety of data, including financial reports, statistics on the labor market, employee evaluations, and indicators unique to the business, to arrive at in-depth judgements. The financial stability assessment applies a linear regression model, whereas employer ranking is predicted using a logistic regression model. Financial data, employment market dynamics, and sentiment research are used as foundational characteristics for these models. Company A is more financially stable than Company B, yet it is anticipated to be ranked lower as an employer. This highlights the difficulty of judging businesses. The implications of these results for job-seekers, investors, and businesses are varied. The study also highlights the significance of ethics, openness, and addressing biases in assessment. This study paves the way for future advancements in this crucial subject and provides a basis for data-driven, well-informed decision-making in the ever-changing landscapes of contemporary industrial evaluations. 2024 IEEE. -
Heat transport and stagnation-point flow of magnetized nanoliquid with variable thermal conductivity, Brownian moment, and thermophoresis aspects
The improvement of heat transport is a very important phenomenon in nuclear reactors, solar collectors, heat exchangers, and coolers, which can be achieved by choosing the nanofluid as the functional fluid. Nanofluids improve thermophysical properties; as a result, they have made great progress in engineering, biomedical, and industrial applications. Therefore, a numerical study has been proposed to analyze the flow and heat transport of nanoliquids over an extendable surface near a stagnation point with variable thermal conductivity under the influence of the magnetic field, due to their importance in the engineering field. Nanoliquid attributes explain the Brownian motion and the diffusion of thermophoresis. The effects of the chemical reaction and the uniform internal heat source/heat sink are also considered. The Nachtsheim-Swigert shooting procedure based on the Runge-Kutta scheme is used for numerical calculation. The impact of effective parameters on velocity, temperature, and volume fraction of the nanoparticles is shown in the graphs and reported in detail. The surface criteria are also estimated with respect to the shear stress and the rate of heat and mass transfer. The aspects of the Brownian moment and Lorentz force are positively correlated to the thermal field of the nanoliquid. Also, the variable thermal conductivity aspect favors the growth of the thermal boundary layer. 2020 Wiley Periodicals LLC -
Thermal Enhancement of Radiating Magneto-Nanoliquid with Nanoparticles Aggregation and Joule Heating: A Three-Dimensional Flow
This article studies the effect of nanoparticle aggregation on the 3D flow of titanium nanoliquid based on ethylene glycol (C 2H 6O 2- TiO 2) due to an exponentially elongated surface. Thermal analysis is carried out considering linear thermal radiation, Joule heating, and mechanisms of the heat source/sink, while the aspect of the homogeneous single-order chemical reaction is included in the analysis of the solute. The variable magnetic field is also accounted. The modified Maxwell model (MaxwellBruggeman) is implemented to estimate the effective conductivity of the nanoliquid. The displayed equations are moderated in quantities without dimensions. The 2-point nonlinear boundary value problem (BVP) is solved by the shooting procedure. The importance of effective parameters is described through graphs. Numerical data are presented to study the friction factor, the heat transfer rate, and the mass transfer rate. It has been established that the aggregation of nanoparticles significantly improves the thermal field. Furthermore, the effect of magnetism is more in ordinary fluid than in nanofluid. 2020, King Fahd University of Petroleum & Minerals. -
Humanizing the Workplace Through STARA: Examining the Roles of Perceived Usefulness and Perceived Organizational Support
This manuscript examines the transformative role of Smart Technology, Artificial Intelligence, Robotics, And Algorithms (STARA) in influencing the trajectory of the future of work, emphasizing the imperative of humanizing the workplace to ensure the longevity of business sustainability. Centred on primary data, a comprehensive literature review scrutinizes modular integrations and explanations, focusing on key variables such as Perceived Usefulness and Perceived Organizational Support. The research employs a conceptual framework to delineate the interplay between STARA, Perceived Usefulness, and Perceived Organizational Support. Methodologically, the research design and data collection methods are detailed, emphasizing the modular integration of measurement instruments. The results are presented, amalgamating crucial findings on the influence of STARA on repercussions for the future of work, emphasizing the incorporation of STARA to foster a more human-centric work environment for business sustainability. Practical suggestions are outlined for companies, accentuating integration opportunities. The conclusion emphasizes the importance of STARA in shaping the future of work, setting the stage for forthcoming research efforts in this dynamic domain. STARA, Future of Work, Perceived Usefulness, Perceived Organizational Support, Workplace Innovation, Business Sustainability. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Empowering Gender Equality in Business Sustainability: A STARA (Smart Technologies, Artificial Intelligence, Robotics, and Algorithms)-Centric Exploration of Socio-Technological Innovation for Modern Business Environments
Technological paradigms worldwide are evolving at a breakneck pace. Workplaces are evolving, organizations are shifting, and businesses are seeking to sustain themselves based on technological development. In recent times, STARA (Smart Technologies, Artificial Intelligence, Robotics, and Algorithms) has emerged as an all-inclusive technological framework that seems a promising benefactor for businesses to thrive through technological adoption. But business sustenance is not all about driving profits. As much as they need to be digitally ready, they are still very much human, with their existence depending on their underlying workforces. Numerous socio-cultural aspects, gender inequality being one of them, plague business sustainability. The following paper seeks to explore corporate socio-technological landscapes. It seeks to substantiate ways gender inequality can be tackled via conscious STARA adoption while holistically ushering the way for business sustainability and success. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Human Resource Professionals Perceptions on the Future of Work
Technology is revolutionizing the manner in which human resources are governed in establishments worldwide. As an increasing number of businesses adopt digital instruments to monitor employee performance, optimize procedures, and enhance communication, HRM must persistently innovate to keep pace with these alterations. The utilization of contemporary technology enables HR departments to become more proficient, streamline procedures, and make more astute decisions. Intelligent Technology, Synthetic Intelligence, Robotics, and Algorithms (STARA) technologies can be groundbreaking in this aspect, empowering establishments and their corresponding HR departments to exponentially flourish with their human resource relative initiatives. The objective of this investigation is to scrutinize the perspectives of HR Professionals on STARA awareness and their vision regarding the prospective influence of its integration on the future of work. Through the utilization of a mixed-data-based exploratory analysis, the researcher examines the facets of STARA awareness, STARA advantages, implementation challenges, and future scopes of STARA relative technologies to expedite HRM and organizational superiority. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Supermarkets and Rural Inequality in India: A Case Study of Reliance Fresh
Drawing upon insights from growing strand of value chain literature, this article examines primary data collected from farmers supplying cauliflower and spinach to Reliance Fresh in the outskirts of Jaipur to understand the implication for farmer households of emergence of supermarket in a smallholder-dominated setting. The article finds that as a lead firm, Reliance Fresh is adopting flexible models of sourcing, devoid of any resource provision, to procure fresh produce of required quality and standards. In such a context, the barrier to participation of smallholders in supermarket-driven agri-food system varies across crops, depending on resource intensity of crops. Participation of smallholders, poorly endowed with human and physical capital, is limited in resource-intensive crop, such as cauliflower, because of high entry barrier in terms of requirement of assets. In contrast, entry barrier is low for smallholders in labour-intensive crop such as spinach, but competition among them, endowed with family labour, bid the rent down to the minimum. Gini decomposition exercise indicates that the emergence of supermarket-driven agri-food system has adverse distributional consequence in rural agrarian setting. Promotion of wholesale market with better infrastructure and encouragement of farmer federation as institutional innovations are suggested for inclusive agri-food marketing system. 2020 Institute of Rural Management. -
The FPTC act, 2020 a blinkered vision
In the name of empowering farmers, the Farmers' Produce Trade and Commerce (Promotion and Facilitation) Act, 2020 has displayed a blinkered vision of an integrated supply chain-by undermining the importance of Agricultural Produce Market Committee markets in a competitive and inclusive agri-food market system. By overlooking many important aspects, the law has taken a quantum leap in the wrong direction. 2021 Economic and Political Weekly. All rights reserved. -
Brand equity seen through advertising proceedings and analysis on brand attitude and brand experience /
Brand equity had been viewed from various perspectives. In general brand equity is defined as marketing effect which has been uniquely attributed to brand the product. Brand equity leads to two general motivation. One is financial base motivation to estimate the value of a brand. The second motivation creates a strategy based motivation to improve the market status and productivity. -
Comparison of TDD and PAIR programming for improving software quality
These days, programming improvement groups utilizing coordinated procedures have started widely adopting Test-driven development and Pair Programming. Test-driven development (TDD) is a transformative way to deal with improvement, which joins test-first improvement where you compose a test before you compose simple enough creation code to satisfy that test and refactoring. Pair Programming is a sort of communitarian programming where two individuals are working at the same time on a similar programming task. In this paper the TDD and Pair Programming is applied for a dataset, collected from a group of users and compared. For our research, we executed structured experiments with five set of pair programmers and ten individual programmers. Both groups developed programs in Java. The outcome acquired demonstrates the strategy helps in expanding the software quality. IAEME Publication. -
Machine learning based Unique Perfume Flavour Creation Using Quantitative Structure-Activity Relationship (QSAR)
Artificial intelligence played a vital role in brings revolutionary changes in the field of perfumery. It is much evident with events including the success of Philyra, exhibitions showcasing the ideas of this concept. Machine learning made it user friendly and more comfortable for the users by means of suggestive interaction. Machine learning also benefited the perfumers in helping them to choose the best combinations and likely successful outcomes. With growing concern about a healthy lifestyle, the thoughts about having an artificial intelligence to predict the user friendliness could be a huge success. This definitely would require a huge database comprising a large detail about diseases and the causes and combinational results of the various chemicals used in perfumery. This system may not be a completely successful one but would be reliable to a better extent. It would gain a positive response from various governmental health departments and would be encouraged by the consumers. Also, another possible development would be Artificial intelligence that is able to predict how long a perfume can last. This would let the consumer choose the one that suits the need. Through this idea we could now get a clear idea about the progress that we have made till this day. Further we can also be driven into vague ideas about how the future of Artificial intelligence would likely grow into. Machine learning and deep learning is a major pillar of artificial intelligence with larger application. Coming to our domain of discussion, artificial intelligence changed the way that things were in the past centuries about fragrance. This article proposed Quantitative structure-activity relationship (QSAR) method is used to predict the best perfume flavour. The proposed system also reduces mean absolute error (MAE). The proposed QSAR is also reducing the chemical composition and increase the perfume quality. 2021 IEEE. -
IOT Based Smart Agriculture System
Smart agriculture is an emerging concept, because IOT sensors are capable of providing information about agriculture fields and then act upon based on the user input. In this Paper, it is proposed to develop a Smart agriculture System that uses advantages of cutting edge technologies such as Arduino, IOT and Wireless Sensor Network. The paper aims at making use of evolving technology i.e. IOT and smart agriculture using automation. Monitoring environmental conditions is the major factor to improve yield of the efficient crops. The feature of this paper includes development of a system which can monitor temperature, humidity, moisture and even the movement of animals which may destroy the crops in agricultural field through sensors using Arduino board and in case of any discrepancy send a SMS notification as well as a notification on the application developed for the same to the farmer's smartphone using Wi-Fi/3G/4G. The system has a duplex communication link based on a cellularInternet interface that allows for data inspection and irrigation scheduling to be programmed through an android application. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas. 2018 IEEE. -
Hardware in loop network simulators - An insight overview
Network simulation is a method of using software or a tool which can be used to mimic the network conditions that exist in pre-defined places. This kind of simulation allows the developers, designers, researchers and the network planners to intelligently plan, design, develop and test their applications or research work in changing network conditions. With varying network conditions either because of wireless nature or because of user mobility, it is very difficult to simulate the exact network conditions with the existing network simulators. These network simulators are flexible, re-usable and reliable. But they have a limitation of not being able to replicate the actual network conditions in the laboratories. This calls for a system in the loop or hardware in the loop concept to be extended to the network simulators. The idea of system in the loop is not new. In this paper, an overview with the fundamental understanding of the hardware-in-loop concept for network simulators, their applications and a review of the existing hardware-in-loop network simulators with their advantages and disadvantages is presented. 2024 World Scientific Publishing Company. -
Vulnerability of urban ecology of Bangalore: An examination of its contention with the politics of land administration
Through a critical examination of questions on the politics of land tenures, the study brings out two interpretations on the conflicts of land and water governance: (1), the concerted efforts and the physical processes of scaling the water terrain in parallel to the political missions of administering the land; and (2), how the scalar rearrangements of land at a local scale intersect with water, revealing the new structuration of land fragmentation and water. It demonstrates that the State has been instrumental in the process of the scalar deterioration of the urban wetlands in Bangalore since 1873. The comprehensive study of these political realignments of land and water, using the data from the Records of Rights obtained from the land revenue records of the Office of the Land Survey Settlement and Records Department under the Government of Karnataka, reveals the vulnerability of urban ecology as a corollary to land administration. Pieter Van den Broeck, Asiya Sadiq, Ide Hiergens, Monica Quintana Molina, Han Verschure and Frank Moulaert 2020. -
Psychological Profile of Suicide Survivors: Retrospection on Decisions of Suicide
The event of Suicide is one that has been studied and documented in several studies abroad and in India. But, to approach the event of Suicide from the perspective of the ??attempted or ??survivor is rare. The purpose of this research is to understand the meaning the act of suicide holds, emotions and thoughts, of the attempter, leading up to the suicidal decision and to trail them till the decision manifests into action. It would provide an in depth perspective of the experience of this event. The research attempts to find not only the meaning behind these events but to also put together a psychological profile by observing the common thoughts, emotions and meaning attributed to the attempt. The research will make use of the method of narratives, over a period of sessions, which would provide the life stories of the individual, as well as the event, in itself. The research is conducted on ten women participants in age range of 18 ?? 35 years. The participants are selected based on the criteria, specified. The research is qualitative in nature. Interpretative Phenomenological Analysis (IPA) will be used to analyze and interpret the data collected. Data analysis shows that the psychological profile, of a suicide survivor consists of cognitions that are predominantly, restrictive and negative in nature, experience of negative emotions especially that are related to the traumatic event and suicide as a meaning fulfilling action. The research would attempt to provide a profile which would not only help in understanding the meaning and life events of such an individual but would also help in training of mental health professionals. Keywords: Suicide, psychological profile, meaning of suicide, suicide decision, cognitions and suicide, emotions and suicide, understanding suicide, causative factors of suicide.