Volume 4 | Issue 4

 Abstract

The major objective of this paper is to describe the use of �T� position in Archery sport. Scientific and biomechanical implementations are helpful to understand the archers correct position in competitive archery. The basic Principle of biomechanics can be benefited to minimize the efforts and minimum use of muscles evolved in draw and T position setup, as well as bow holding. Pre draw is achieved with the help of learning proper T position under biomechanical conditions, By raising the bow hand and drawing hand above shoulder level into a high Pre draw position this lowers the bow shoulder into the correct position with the �collar bone� sitting onto the ribs and sets up the rest of the body for the draw and shooting process. The basics of biomechanics and scientific analysis help to archer to rectify errors in their shooting form.

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Archery, Shooting, Stance, Body Position, T Position

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ast link in the distribution process during which goods

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With the expansion of Internet usage, E -banking has become one of the most revolutionized components of today's economic growth. E-banking is a powerful value-added tool to attract new customers and retain the existing ones. With the proliferation of internet and computer usage, the electronic delivery of e-banking service has become ideal for banks to meet customer's expectations (Poon, 2008). Besides, it helps in eliminating costly paper handling and teller interactions in the increasingly competitive banking environment. The development of e-banking has become a priority for core advantage. The potential competitive advantage of e-banking lies in the areas of cost reduction and satisfaction of consumer needs. There are an increasing number of the

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mer needs. There are an increasing number of the

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Peripartum cardiomyopathy is a life-threatening disorder of unknown aetiology that occurs in the last month of pregnancy or in first five months post-partum with absence of determinable cause for cardiac failure and absence of determinable heart disease.The disease is relatively uncommon with an estimated rate of 1 in 3,000-4,000 deliveries and its incidence is getting increased nowadays. The diagnosis of this entity is often difficult and it requires a high degree of clinical suspicion since majority of the cases in puerperium with cardiac failure (acute LVF or cardiac arrhythymias) and are often the cause for maternal mortality. Therefore it is essential that when aetiological risk factor is present in a case or whenever clinical suspicion arises, 2D echocardiogram be suggested to diagnose peripartum cardiomyopathy. Early diagnosis facilitates immediate intervention, which will prevent maternal morbidity, mortality and it also helps to team up with an internist or cardiologist to provide effective treatment to the patient. In this regard the present study was conducted to review the role of routine 2D echo in high risk antenatal women and it also throws light on the role of this noninvasive modality to diagnose cardiomyopathy of pregnancy and puerperium. The aims and objectives of the study are to evaIuate the role of 2D ECHO in diagnosing peripartum cardiomyopathy and to assess its prognostic value for a better maternal and fetal outcome.

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 Keywords

:Peripartum cardiomyopathy, puerperium, mortality, 2D echo.

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Mobile Cloud Computing (MCC) which combines mobile computing and cloud computing, has become one of the industry buzz words and a major discussion thread in the IT world since 2009. As MCC is still at the early stage of development, it is necessary to grasp a thorough understanding of the technology in order to point out the direction of future research. With the latter aim, this paper presents a review on the background and principle of MCC, characteristics, recent research work, and future research trends. A brief account on the background of MCC: from mobile computing to cloud computing is presented and then followed with a discussion on characteristics and recent research work. It then analyses the features and infrastructure of mobile cloud computing. The rest of the paper analyses the challenges of mobile cloud computing, summary of some research projects related to this area, and points out promising future research directions.

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Mobile Cloud Computing; Mobile Computing; Cloud Computing; Research Directions.

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Recent trend of advanced manufacturing processes like Laser Cutting Machine. In Fabrication industries require more production by using automation so that required CNC machine which is more popular for mass production. Laser Cutting Machine having different critical components are them so in that mechanical side to develop CNC axes as per technology concern. In CNC axes required different parts like Runner Block, Rails, and Linear Drive Motor etc. In past there were ball screw used for making CNC axis now a day linear drive mechanism used more because it is more powerful system to positioning, efficiency. By using CAD tools like Solid Work, to make 3 D Modelling for required part and practical analysis for cost.

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Design, Analysis, Linear Drive Mechanism, CNC Axes, FEA.

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Frequent pattern mining and association rule mining are foundational in data mining, enabling the discovery of hidden relationships and patterns within large datasets. This comprehensive survey, provides an expanded overview of the key algorithms, their evolution, comparative strengths and weaknesses, and major research trends. The report covers traditional, advanced, and emerging methods, with a focus on both static and dynamic data environments, scalability, utility-based mining, parallelization, and domain-specific adaptations. Real-world applications, open challenges, and future research directions are also discussed.

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Frequent pattern mining,Association rule mining,intrusion detection

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The growing demand for seamless data sharing across diverse platforms has highlighted the need for robust integration solutions, particularly in environments dealing with both structured and unstructured data. Current systems primarily address structured data integration, leaving a significant gap in handling unstructured file-based data. This paper proposes a novel model designed to integrate, query, and share unstructured data, focusing on news feeds as a case study. We explore how integrating heterogeneous data sources can be optimized, highlighting the importance of grid technology and unified access interfaces.

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Data Integration, Unstructured Data, News Feeds, Grid Technology, SEO

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Our work on the synthesis of 1, 5-0benzothiazepines, we report herein the synthesis of six new 2, 3-dihydro-1, 5-benzothiazepines1-2 having a methoxyl group at various positions in the phenyl ring at position 2 or 4, alone or alongwith other groups.

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aminothiophenol , sulphydryl, chalkones, isotopic , methoxybenzalacetophenone

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As the globe seeks low-carbon energy, solar electricity is the most plentiful resource. This century's problem is harnessing energy. Photovoltaics, solar heating and cooling, and CSP are common solar energy uses. Different technologies, proportions of the solar resource, site requirements, and production capacities distinguish these solar energy systems. Every solar energy application needs accurate solar resource data. Small rooftop installations and huge solar power plants are affected. Because huge installations might cost over $1 billion, solar resource knowledge is very important. The best fuel supply quality and dependability information must be accessible before such a project. To predict the daily and annual performance of a proposed solar heating and cooling system or power plant, this project needs reliable data about the solar resource available at specific locations, including historic trends with seasonal, daily, hourly, and (preferably) subhourly variability. Without this data, manufacturers and dealers cannot provide reliable financial analysis. sun energy system performance assessments need sun radiation data. The National Solar Radiation data source in India includes stored hourly, daily, and monthly data for various capital cities and districts for 60 years. Since simulating systems for 60 years is computationally intensive, it is easier to use typical data in performance analyses by simulating a computer program for as many years to any location, any time, any day, and any month and year of the country only by knowing its latitude and longitude. Flat Plate Collectors are the easiest and most common way to convert solar energy into heat. Solar radiation hits the darkened collector absorber surface via clear cover plates and is absorbed as thermal energy. Air or liquid movement removes thermal energy from the absorber, delivering heat for use or storage. A C-language computer program has been developed to predict the performance of a flat plate collector that stores heat in water called a Solar Water Heater. The program takes into account beam radiation, diffuse radiation, global radiation, total solar flux, declination, incident angle, outlet fluid temperature, and instantaneous efficiency. Simulation of flat plate collector for solar water heaters produces rapid results and optimizes cost and efficiency. This research simulates a flat plate collector for a solar water heater using a C-language software designed to forecast solar collector system performance based on location and time of day. Program calculates instantaneous beam and diffuse radiations for the collector's location, number of days (n value) for any date in the year, angle of incidence of beam radiation on the collector, total solar flux incident on the collector, transmissivity - absorbtivity product, incident flux absorbed by the absorber plate, collector heat removal factor, overall loss coefficient, water outlet temperature, and instantaneous. The modeling tool estimates solar collector system performance and can size solar hot water systems for varied applications. The study includes parametric investigation of the effect of selective surfaces, number of covers, spacing, collector tilt, fluid inlet temperature, incident solar flux, and dust on top covers on solar water heater performance and validation of computational results with experimental results from literature and Chickballapur. The customized comparison approach may correlate the generalized program with solar collector performance for solar water heaters at any location without tests, ensuring precision and correctness.

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Flat plate Collector, Solar water Heater, Computer program in C-language.

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With the ecological imbalance in the nature due to exploitation of natural sand from rivers, there is much need to utilize the industrial wastes in concrete as a part to replace the natural sand deficiency and also as to develop sustainable environment in construction industry. High strength and durability properties being the key components of High-performance concrete can be produced by using some admixtures like fly ash and silica fume. In the present study, fly ash and silica fume are taken as steady replacement of 15% and 10% respectively for cement. Bottom ash is introduced in place of sand at the variations of 0%, 10%, 20%, 30%, 40% and 50%. Glass fibers of 1% are added as extra ingredient as to improve some properties. The properties of strength, drying shrinkage and water absorption are studied for the M60 grade concrete designation. The results showed that the concrete with 40% bottom ash had the optimum strength.

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Bottom ash, drying shrinkage, fly ash, silica fume, strength

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In the upcoming years, cloud computing, a new and developing technology, is anticipated to drastically alter the IT industry. Leading enterprise companies like Amazon, Microsoft, and Google now offer a wide range of cloud services in the form of specialised, dependable, and reasonably priced web applications. Numerous people and organisations from a variety of fields, including business, education, and health, are drawn to these services. Our goal in this paper is to familiarise cloud users with the most well-known Cloud Service Providers (CSPs). We additionally present a comparative analysis of these CSPs based on various service-related criteria. Before moving their business, people and organisations can use the study presented in this paper to make important decisions about the costs and advantages of cloud technology.

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Cloud computing, Cloud Service Providers, SaaS, PaaS, IaaS

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The last few years have seen artificial intelligence systems transform education at an unprecedented rate. Such systems have far-reaching implications-they bring opportunities and challenges-and their development must adhere to ethical principles that make learning contexts inclusive, equitable, and effective. This conceptual review offers a discussion on the possibility of Bayesian networks as a framework for modelling and addressing complex interconnectivity between ethical considerations, societal impacts, and technical feasibility within AI-driven educational systems. Bayesian networks allow stakeholders to see dependencies and trade-offs that lie underneath informed decision-making and responsible design of AI. It therefore focuses on empowering diverse groups, including women, fully to take an active role in lobbying for ethical development of AI, discussing salient topics in attention to issues like bias, privacy, accountability, and accessibility. This paper gives a theoretical footing from which it is possible to integrate ethical decision-making into AI system design and underlines the need for multidisciplinary education. The study is going to be a roadmap for researchers, educators, and policymakers interested in the development of ethical AI for education.

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Bayesian, Ethics, AI, Education, Empowerment, Equity, Feasibility, Framework, Inclusion, Policy.

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 Abstract

Nymithikinaam kaamyaanaam cha saamidheninaam Vidhana Vivaranam

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Nymithikinaam kaamyaanaam cha saamidheninaam Vidhana Vivaranam

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The Open Government Data initiatives look to promote transparency and accountability of public sectors besides enhancing citizen engagement through free availability public sector data. However, through the integration of cloud computing technologies, the effective use and scalability of OGD initiatives have been very much enhanced. This review paper examines trends and patterns in the adoption of cloud computing for open government data platforms, cognizant of international case studies, technological and policy frameworks that support these efforts, and challenges related to security of data, privacy, interoperability, and governance. The review highlights the advantages of cloud infrastructure, which include scalability, real-time access, cost efficiency, and seamless data sharing, as reasons that have made OGD more accessible to developers, researchers, and citizens. Other emerging trends of OGD include hybrid cloud models, the role of artificial intelligence in processing OGD, and the open data platforms of smart cities. The future discussion will cover research aspects in overcoming technical and policy challenges to make cloud-based OGD solutions more effective

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Open Government Data, Cloud Computing, Transparency, Accountability, Data Security, Hybrid Cloud, Smart Cities, Policy Frameworks, Scalability, Data Governance

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This study examines the role of mass media in the success of the Biogas Programme in Karnataka, which focuses on sustainable energy adoption and rural development. The paper explores how various forms of media, such as television, radio, newspapers, and online platforms, have contributed to promoting and educating people about biogas technology. By sharing knowledge, raising awareness, and educating rural communities, mass media have encouraged participation and adoption. The research combines qualitative media content analysis and quantitative surveys of Biogas Programme beneficiaries, revealing that mass media have positively influenced perceptions and attitudes towards biogas, leading to increased acceptance and implementation. Challenges, such as language barriers and access limitations, are also identified. The study's implications extend globally to other sustainable development initiatives, highlighting the vital role of mass media in their success. Ultimately, the Biogas Programme's achievement is linked to effective communication through mass media, emphasizing collaboration between governments, media, and local communities for successful sustainable development.

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Biogas Programme. Karnataka. Mass media. Success. Sustainable energy. Rural development. Communication. Awareness dissemination. Information sharing. Energy adoption. Waste management. Environmental conservation. Television. Radio. Newspapers. Online platforms.

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Content marketing has become an increasingly crucial strategy for businesses across the board in a bid to engage their customers and foster brand loyalty. However, this exponential increase in online content has reached a point of saturation, whereby consumers are overwhelmed by the deluge of information at their disposal. This paper reviews challenges and opportunities in connection with content marketing in this age of content saturation. It highlights the role of big data in coming up with efficient content strategies that help block out the noise and get through to target audiences. Big data analytics can be utilized in analyzing consumer behavior, preferences, and trends to generate highly personalized and relevant content. The paper further reviews some big data tools and techniques for use in optimizing content creation, distribution, and performance measurement. Furthermore, it identifies and points out the successful case studies of firms that did an exemplary job in harnessing big data to improve their content marketing efforts. Indeed, the research concludes that infusing big data in content strategy formulation is not just useful; it is a requirement to maintain competitive advantage within the jammed digital marketplace.

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Content marketing, content saturation, big data, consumer behavior, personalized content, big data analytics, content strategy, digital marketing, content creation, data-driven marketing.

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AI and robotics have had good integration into disaster response and recovery over the past two years. The research paper focuses on the advancements of AI-powered robots in handling a wide array of disaster scenarios, from natural disasters like earthquakes, floods, and hurricanes to artificial crises involving industrial accidents and terrorist attacks. It reviews state-of-the-art technologies that allow robots to move through treacherous landscapes, perform search and rescue, transport medicine, and participate in restoring infrastructure. They include machine learning algorithms for real-time data processing, autonomous navigation, human-robot interaction, and multi-robot coordination. The paper also explains some challenges and limitations of AI-robotics systems, including ethics issues, logistics, and standardized protocols for deployment. We discuss how case studies and experimental results may point to the potential for AI-powered robots in transforming disaster response and recovery into life-saving and economically remedial activities.

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AI-powered robots, disaster response, disaster recovery, search and rescue, autonomous navigation, machine learning, human-robot interaction, multi-robot coordination, ethical considerations, deployment logistics.

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This study examines the intricate historical fabric of medieval Assam and the crucial influence Persian sources had in influencing the history of medieval period. The article centers on how Persian documents offer distinctive perspectives on the political, cultural, and social aspects of Assam in the Middle Ages, as historical strands intertwine throughout history. Through meticulous analysis, this study aims to shed light on lesser-known facets of Assamese history, revealing the nuanced ways in which Persian influence intersected with and enriched indigenous developments in the region. By exploring Persian sources, the study uncovers how Persian literary, administrative, and historical texts offer unique insights that complement and enhance the indigenous records, leading to a more comprehensive understanding of the medieval Assam. By bringing these obscured aspects to light, the research not only enriches our understanding of Assam's past but also highlights the broader implications of cross-cultural exchanges in the shaping of historical narratives.

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Assam, Persian Documents, Medieval Period, Political Dynamics

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Stock market prediction is one of the toughest tasks in finance and attracts much attention from academia and industry due to huge economic potential. Traditional econometric models dominated the field until recent developments in machine learning introduced new methodologies that capture complex market dynamics. Of these, the RF algorithm has excelled in large data volumes, the ability to model nonlinear relations, and ranking feature variable importance. The paper presents a review on the application of Random Forests in stock market prediction, covering the theoretical foundations of Random Forest, advantages over traditional methods, reviews of empirical studies proving their effectiveness, and challenges and future research directions. It synthesizes how recent literature can help researchers and practitioners use random forests to guide and improve the accuracy of predictions and robustness associated with stock market analysis.

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Creative Commons Attribution 4.0 and The Open Definition

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Stock market prediction, random forest algorithm, machine learning, finance, predictive modeling

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