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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. -
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. -
Performance evaluation of multi band disk-shaped terahertz MIMO antenna with hexagon slots on ground for future 6?G and terahertz communication system
In this paper, a four-port wideband MIMO antenna is developed for future 6 G wireless communication systems. The proposed disk-shaped antenna consists of four identical disk-shaped elements arranged uniformly around a circular structure. This uniform arrangement helps maintain geometric balance and minimizes mutual coupling. All the disk patterns are arranged equidistantly around the centrally etched flower-like structure, which ensures the symmetrical geometry of the proposed antenna. These slots are helpful in generating a super-wide bandwidth ranging from 1.81 THz to 4.1513 THz. To further enhance the efficiency of the antenna, hexagonal slots are etched on the ground plane. The hexagonally etched slots on the ground reduce signal reflection losses. The overall dimensions of the four-port MIMO antenna are 800 800 50 m , and it is designed on a silicon substrate with a relative permittivity of 11.9. The proposed antenna achieves a super-wide bandwidth ranging from 0.926 THz to 5.5411 THz and a peak gain of 7 dB. MIMO performance parameters such as diversity gain, Total Active Reflection Coefficient (TARC), Envelope Correlation Coefficient (ECC), and Channel Capacity Loss (CCL) are evaluated, and all lie within acceptable ranges. The disk-shaped antenna demonstrates super-wideband characteristics, high resolution, and a low reflection coefficient. The disk-shaped antenna operates at 1.8175 THz, 2.5911 THz, 3.286 THz, and 4.1513 THz, with reflection coefficients of ?28.02 dB, ?35.723 dB, ?37.11 dB, and ?32.35 dB, respectively. Considering to its compact size, wide bandwidth, and stable radiation characteristics, the proposed disk-shaped antenna is well suited for high-speed THz communication and beyond-6G wireless applications. Copyright 2026. Published by Elsevier GmbH. -
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. -
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. -
Evaluate Machine Learning Techniques for Early Disease of Cardiovascular Disease
Cardiovascular diseases are one of the major causes of death around the world, and their early detection is critical for effective intervention. The paper presents a systematic review of machine learning techniques used for the early prediction of cardiovascular diseases, focusing on studies carried out between 2019 and 2024. Widely used models considered in the review include Logistic Regression, Support Vector Machines, Random Forest, K-Nearest Neighbors, Gradient Boosting, and hybrid ensemble methods with the aim of ascertaining predictive accuracy, interpretability, and clinical relevance. In most of the reviewed studies, ensemble and Random Forest models attained the highest accuracies of 90% - 98%, while Gradient Boosting and SVMs were mostly above 90% in balanced datasets. Logistic Regression had a moderate accuracy of 85%-91% but remained the most interpretable, while KNN established the lowest performance of 80%-86%. Despite the promising strides, there are a number of limitations, such as imbalance in datasets, limited external validation, and small benchmark datasets, that are limiting general application in health. This systematic review highlights strengths and weaknesses of the contemporary machine learning approaches and makes it evident that clinically validated, interpretable, and generalizable models should be developed in order to assist real-world medical decision-making. 2025 IEEE. -
Revisiting wideband pulsar timing measurements
In the wideband paradigm of pulsar timing, the time of arrival of a pulsar pulse is measured simultaneously with the corresponding dispersion measure from a frequency-resolved integrated pulse profile. We present a new method for performing wideband measurements that rigorously accounts for measurement noise. We demonstrate this method using observations of PSR J2124?3358 made as part of the Indian Pulsar Timing Array experiment using the upgraded Giant Metre-wave Radio Telescope, and show that our method produces more realistic measurement uncertainty estimates compared to the existing wideband measurement method. The Author(s) 2026. Published by Oxford University Press on behalf of Royal Astronomical Society. -
Development of flexible FRP butt joints between stiff FRP panels using hybrid resin and kevlar reinforcement for advanced structural applications
The present work focuses on developing a flexible fiber-reinforced polymer (FRP) butt joint between stiff FRP panels (adherends). The goal is to ensure the joint is flexible, moisture-resistant, and abrasion-resistant, while maintaining the original FRP strength and facilitating the casting of complex and modular shapes. To achieve this, an elastomeric resin system comprising polyurethane and polyurea in an optimized ratio of 10:6 (by weight) was formulated for the flexible joint region, whereas isophthalic polyester resin was used in the stiff FRP panels. The joint was reinforced using a hybrid layup of three layers of plain-weave Kevlar fabric, with glass fiber chopped strand mat (CSM) interleaved between the Kevlar layers, over an overlap length of 50mm on both panel edges. Mechanical characterization revealed that the hybrid resin alone exhibited an average tensile strength of 16.3MPa; however, no slip was observed for the 50mm overlap of the reinforced joint, and failure occurred in the adherend. Furthermore, the joint exhibited favorable performance under abrasion, water immersion, low-temperature fatigue, and drop-weight impact testing. These results confirm that the proposed hybrid Resin-Kevlar reinforced joining approach offers a reliable pathway for fabricating flexible, durable, and high-strength FRP joints suitable for advanced structural applications. The Author(s) 2026. -
Balconing An Intersection of Morbidity and Language
[No abstract available] -
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. -
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. -
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. -
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. -
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. -
Exploring the Extent of Technology Acceptance and Workplace Behavior of Employees in the Transport Sector of Bahrain
The research objectives of the study are to establish the level of technology acceptance, the factors influencing it and the impact of technology acceptance on work-related behaviours with commendation objectives to analyse the level of technology acceptance, to determine the factors and to make recommendations. According to this studys hypothesis, the level of technology acceptance has a positive impact on job satisfaction and job performance with perceived ease of use and perceived usefulness as the determinants. This research adopts a positivist philosophy and an exploratory research method, which entails a deductive approach based on questionnaires to survey 69 transport sector employees in Bahrain as the source of data. Credibility of data also shows a positive correlation between technology acceptance with job satisfaction, ease of use and organizational performance. The study focuses on the perceived usefulness and ease of use of the technology pointing out the need for the employees to be involved in the integration of the technologies in order to improve performance and to address stress at workplace. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Alcohol-Attributable Liver Disease in India, 20002021: Comparative Analysis Across Alcohol Policy Regimes Using GBD 2021
Alcohol use is ranked among the leading causes of liver disease in the world, and the most dreadful consequences of this condition are cirrhosis and hepatic cellular carcinoma (HCC). India has an eclectic policy environment, with bans, regulation, liberal paradigms, and the influence of such policies on the epidemiological process is inadequately studied. Based on the Global Burden of Disease (GBD) 2021 data of nine states (20002021), this study focuses on disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) due to alcohol-related cirrhosis and HCC. States were classified as prohibited (Bihar, Gujarat, Nagaland), regulated (Karnataka, Kerala, Tamil Nadu), and liberal (Goa, Punjab, Sikkim). Liberal states had the highest burdens, with Sikkim leading by approximately (410 per 100,000), followed by Goa (360 per 100,000) and Punjab (290 per 100,000), all above prohibited state averages. In Bihar, there was 27% reduction of DALY, whereas Kerala had the highest increase of 44%. More than 90% of total variation in DALYs was attributed to YLLs, with men also experiencing larger overall burden, ranging between 45 and 811 times during midlife. The panel regression displayed low cohort-level variance (R2= 0.41) but strong state-level effects (R2= 0.98), that signify a high level of heterogeneity. These results show that in addition to policies, variations in implementation, fiscal priorities, and social contexts determine the burden experienced in India, which further points to the need to implement evidence-supported, targeted interventions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Effects of DESI and GW observations on f(T) gravitational baryogenesis
Baryogenesis refers to the physical process responsible for generating the observed baryon asymmetry in the early universe. The presence of a nonzero baryon number density suggests a surplus of matter over antimatter. In this study, a novel approach is proposed to verify the direct consequences of late-time observations on gravitational baryogenesis. The incorporation of two key data sets, DESI and gravitational wave observations, makes the analysis more intriguing. In the teleparallel framework, the methodology connects the primordial time to the late time. The intermediating epochs are also investigated with the help of the deceleration parameter. Our results show that the net remaining asymmetry yields a baryon-to-entropy ratio in excellent agreement with observations. 2025 The Authors. -
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. -
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 -
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.