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                <text>An ettective dynamic scheduler tor reconfigurable high speed computing system</text>
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                <text>Field Programmable Gate Array; Minimum Laxity First; Reconfigurable High Speed Computing System; Reconfigurable Logic Unit</text>
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                <text>High Speed Computing is a promising technology that meets ever increasing real-time computational demands through leveraging of flexibility and parallelism. This paper introduces a reconfigurable fabric named Reconfigurable High Speed Computing System (RHSCS) and offers high degree of flexibility and parallelism. RHSCS contains Field Programmable Gate Array (FPGA) as a Processing Element (PE). Thus, RHSCS made to share the FPGA resources among the tasks within single application. In this paper an efficient dynamic scheduler is proposed to get full advantage of hardware utilization and also to speed up the application execution. The addressed scheduler distributes the tasks of an application to the resources of RHSCS platform based on the cost function called Minimum Laxity First (MLF). Finally, comparative study has been made for designed scheduling technique with the existing techniques. The proposed platform RHSCS and scheduler with Minimum Laxity First (MLF) as cost function, enhances the speed of an application up to 80.30%.  2014 IEEE.</text>
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                <text>Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014, pp. 766-773.</text>
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                <text>Vucha M., MANIT, Bhopal, India, Christ University, Bangalore, India; Rajawat A., Dept. of ECE, MANIT, Bhopal, India</text>
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                <text>An Examination of the Challenges Associated with Applying Artificial Intelligence Techniques to Specific Management Problems</text>
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                <text>adaptation; agile AI systems; Artificial intelligence; challenges; continuous learning; data quality; disparate data sources; dynamic management problems; management practices</text>
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                <text>Artificial intelligence (AI) holds immense promise in revolutionizing management practices across various sectors, offering solutions to complex problems and optimizing decision-making processes. However, the application of AI techniques to management problems is not without its challenges. This examination delves into the multifaceted hurdles encountered when integrating AI into management frameworks, highlighting key obstacles and potential avenues for overcoming them.AI algorithms heavily rely on large volumes of high-quality data for effective training and decision-making. Yet, many management domains grapple with disparate data sources, inconsistencies, and incomplete datasets, hindering the performance and reliability of AI systems. Furthermore, the dynamic nature of management problems poses a significant challenge to AI implementation. Management environments are characterized by evolving trends, uncertainties, and unforeseen disruptions, rendering static AI models inadequate in adapting to changing conditions. Hence, the development of agile AI systems capable of continuous learning and adaptation becomes essential for addressing the dynamic nature of management challenges.  2024, Collegium Basilea. All rights reserved.</text>
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                <text>Nanotechnology Perceptions, Vol-20, No. S5, pp. 491-498.</text>
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                <text>Rahate V., DattaMeghe Institute of Management Studies, India; Karpagavalli G., Department of Management Studies, DayanandaSagar College of Engineering, India; Vijayalakshmi A., Department of English, ChaitanyaBharathi Institute of Technology, Hyderabad, India; Deshpande S., Department of English, ChaitanyaBharathi Institute of Technology, Hyderabad, India; Roopa M.B., Department of Business and Management, Christ University, Yeshwanthpur Campus, Bangalore, India; Bapat M.S., K.G. Joshi College of Arts and N G Bedekar College of Commerce (Autonomous), India</text>
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                <text>An Expected Model of Management Program in India</text>
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                <text>An Experimental Investigation on Flexural Strength of Ferrocement Slab Made of Slag Sand Partially Replaced with Iron Ore Tailings</text>
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                <text>Effective use of slag sand and Iron Ore Tailings and other waste obtained from the manufacturing industry and mining industry like waste foundry sand, will reduce the negative impact on the environment and also will provide opportunities for effective use of natural resources and contribute to sustainability. The aim of this research project is to study the flexural strength of ferrocement slab made of slag sand partially replaced with iron ore tailings with sustainability point of view. Investigation of 48 slab panels of 700mm 300 mm size with thickness 25 mm and 30 mm was conducted using 1 and 2 layers of weld mesh reinforcement casted with different percentage of iron ore tailings. Slabs were tested in Universal Testing Machine, which showed good results with 15% of iron ore tailings.  Published under licence by IOP Publishing Ltd.</text>
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                <text>Devasia J.; Raghunandan Kumar R.</text>
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                <text>IOP Conference Series: Materials Science and Engineering, Vol-872, No. 1</text>
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              <elementText elementTextId="185249">
                <text>All Open Access; Gold Open Access</text>
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(43.7%), and Turn-taking (40.5%). Fast learners increased by an average of 26.9%, and slow learners saw an average increase of 49.6% from their pretest scores. Additionally,&#13;
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The results through the post-achievement test showed that the researcher-developed learning module had a statistically significant influence on overall English language&#13;
production in the participants. In educational psychology, Multiple Intelligence has garnered substantial research attention for its application in ESL/EFL and broader school curricula, particularly in teaching English and various subjects. However, the integration of Existential Intelligence within the context of ESP remains unexplored. Its potential significance and&#13;
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The research attempts to contribute to the growing field of English for Specific Field ix for Business students by situating the study within the Pune district of Maharashtra by&#13;
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uses Task based Language Teaching (TBLT) approach and excerpts from Literature for pedagogical instruction, employing Dialogic Inquiry Model (DIM) as a framework and
using Existential Intelligence as a guiding lens. Language and Intelligence are closely intertwined. Educational Psychologist Howard Gardner posed a challenge to the conventional notion of Intelligence which supported higher IQ based tests by introducing the Theory of Multiple Intelligences. Gardner's Intelligence framework initially comprised of seven types. In 1999, he introduced Existential Intelligence (EI), expanding the model to include EI as a half intelligence, but due to its abstract nature and lack of clear brain localization, it has posed challenges for precise quantification. Furthermore, Howard Gardners Intelligence Reframed (1999) was used as the primary text for the study. By contextualizing the study within Higher Education's Business studies domain, it examines how existential principles influence the development of speaking skills. Additionally, it explores how these principles contribute in shaping aspiring business entrepreneurs, providing added motivation to instill a sense of purpose which will enhance their managerial attributes. The research argues that infusing unexplored existential elements into the curriculum can stimulate critical thinking among Business Studies students, resulting in notable improvements in specific speaking dimensions like Fluency, Turn-Taking, Presentation and Negotiation skills (FTPN). Moreover, it highlights the pivotal role of this integration in reshaping ESP curricula to better cater to the unique needs of learners in this discipline. The research comprised of two cohorts of students. The first cohort consisted of first- year postgraduate students pursuing Business Studies at Sinhagad Institute of Management (SIOM), Pune while the second cohort included students from CHRIST Deemed to be University) Pune Lavasa Campus, resulting in a cumulative total of approximately 68 participants. The study extended over a 15-day duration to facilitate the completion of a comprehensive 30-hour module for both the phases separately. The study employs a mixed-method approach by combining qualitative and quantitative analysis. For the qualitative study, the analysis involved researchers observations and an examination of Achievement tests questionnaires employing the Likert scale. For quantitative analysis, a series of six Task-Based Language Teaching (TBLT) activities
were conducted, encompassing pre and post achievement tests, each of which was assessed based on the study's objectives. The assessment tool utilized is the Communicative Skills Rating Scale (CSRS) by Spitzberg and Cupach (2002), featuring a four-tier evaluation system: self, partner, observer, and external evaluations. Data was collected via Audio-Visual methods for documentation purposes and to cross-reference any overlooked data during the concurrent evaluation process. The collected data underwent a systematic analysis to investigate how applying EI principles can improve conversational speaking skills. The efficacy of the learning module was evaluated based on the proficiency demonstrated in TBLT activities concerning FTPN skills. TBLT activities were administered both prior to and subsequent to the completion of each unit. The assessment of the effectiveness of classroom pedagogy (independent variable) was gauged through the researcher's observations and achievement test questionnaires. Simultaneously, the evaluation of participants' specific conversational skills (dependent variable) was evaluated and analyzed through the course of experimental study using CSRS evaluation scale. Data was analysed using Descriptive statistics through Excel and it was verified using R programming. The research delineates apparent improvements in FTPN within the DIM framework upon the integration of this intervention. Noteworthy enhancements also included a heightened motivation levels across the sample population. Both fast and slow learners exhibited advancements, with a more pronounced improvement observed among the latter group. Additionally, significant strides were observed in non-verbal proficiencies, notably in body posture, and refined listening and responsive non-verbal skills, which was a byproduct of the intervention. Also, a Gender-based analysis revealed an overall positive trend in both male and female students, yet a comparatively greater enhancement was evident among male students in assimilating and applying these interventions. The analysis of data obtained from the CSRS tool shows statistically significant influence on overall English anguage production of the participants in terms of FTPN variables. Moreover. progress tests provided statistically significant evidence for the efficacy of the researcher- developed learning module based on TBLT and DIM approach integrated using EI subsets. Each phase of participants underwent separate experimentation and assessment of their proficiency both before and after the intervention. The pre-achievement test revealed inadequate speaking skills and a lack of basic conversational understanding in both cohorts. Phase 1 (SIOM) showcased noticeable improvement, with a growth in Fluency (39.7%), Presentation (32.1%), Negotiation (37.3%), and Turn-Taking (38.5%) using the CSRS tool. Fast learners improved by an average of 24.1%, while slow learners showed a significant average increase of 51% from their pretest scores. Moreover, there was a 15.7% increase in motivation levels during the intervention. Group 2 (CUL) exhibited improvements in Fluency (36.35%), Presentation (35.8%), Negotiation
(43.7%), and Turn-taking (40.5%). Fast learners increased by an average of 26.9%, and slow learners saw an average increase of 49.6% from their pretest scores. Additionally,
there was an 18.2% spike in motivation levels during the intervention. Overall, the analysis of CSRS data and progress tests strongly supports the effectiveness of the
researcher-developed learning module based on existential principles. It significantly enhanced oral participation and achievement of learning outcomes across both groups.
The results through the post-achievement test showed that the researcher-developed learning module had a statistically significant influence on overall English language
production in the participants. In educational psychology, Multiple Intelligence has garnered substantial research attention for its application in ESL/EFL and broader school curricula, particularly in teaching English and various subjects. However, the integration of Existential Intelligence within the context of ESP remains unexplored. Its potential significance and
applicability within higher education for business students could be substantial. This intelligence category, rooted in philosophy, mysticism, aesthetics, and related domains,
aligns closely with the fundamental realms of interest for MBA students. Its introduction could offer profound implications for their learning experience and academic endeavors.
The research attempts to contribute to the growing field of English for Specific Field ix for Business students by situating the study within the Pune district of Maharashtra by
analysing only FTPN which further offers scope for exploration. </text>
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                <text>Construction of bricks using waste materials is one among the many ways to address the problems encountered in infrastructure. In the present study, various industrial and mining wastes have been used to manufacture stable bricks. These wastes include red mud (RM) from Hindalco, and iron ore tailings (IOT) from BMM Ispat, Bellary. Both RM and IOT were combined in different proportions with ground-granulated blast furnace slag (GGBS) and waste lime. In first series, IOT was replaced in the range of 45% to 60% with increments of 5%, and RM was replaced in the range of 15% to 30% with increments of 5%. In the second series, RM was replaced in the range of 45% to 60% with increments of 5%, and IOT was replaced in the range of 15% to 30% with increments of 5%. Tests were performed as per the Indian and ASTM standards on both the raw material and the developed composites. These tests include liquid, plastic limit, particle size, XRF, XRD, and SEM on raw materials, while tests performed on composites were compressive strength, water absorption, efflorescence, porosity, apparent specific gravity, and bulk density. Results of the study indicate that addition of IOT up to 55% is acceptable as brick material.  Springer Nature Singapore Pte Ltd 2020.</text>
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                <text>Lecture Notes in Civil Engineering, Vol-72, pp. 9-19.</text>
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                <text>ISSN: 23662557</text>
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                <text>Beulah M., Department of Civil Engineering, Christ (Deemed to be university), Bangalore, 560074, Karnataka, India; Sarath Chandra K., Department of Civil Engineering, Christ (Deemed to be university), Bangalore, 560074, Karnataka, India; Mohan M.K., Department of Civil Engineering, Christ (Deemed to be university), Bangalore, 560074, Karnataka, India; Clifford Dean I., Department of Civil Engineering, Christ (Deemed to be university), Bangalore, 560074, Karnataka, India; Gayathri G., Department of Civil Engineering, ACS College of Engineering, Bangalore, 560074, Karnataka, India</text>
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                <text>An Expert System for Diabetes Diagnosis</text>
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                <text>V  Smitha</text>
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                <text>Expert system is a computer system that emulates the decision making ability of a human expert. That is it acts in all respects like a human expert. It uses human knowledge to solve problems that would require human intelligence. The expert system represents expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems.

Diabetes is a knotty disease and very common in the modern world. Diabetes is a serious disease that affects almost every organ in the body like heart, eyes, kidney, skin, nerves, blood vassals, foot etc. If left the disease unchecked it will make serious complications including death. Though the disease can not possible to cure completely, it can be well managed or control and can lead a very healthy life. Early diabetes diagnosis plays a crucial role in diabetic control, and can prevent further medical complications.

This paper presents the design and development of medical expert system for Diabetes disease and it support diagnosis, give information about complications and act as diabetes trainer. It used rule based approach to collect data and forward chaining inference technique. This system provides a user interactive, menu driven environment. Symptoms and risk factors associated with diabetes are taken as the basis of this study. In case of diagnosis the system will ask a bunch of questions about the symptoms and risk factors to the expert system user and user should give yes or no answer. According to the answer the system will make judgment about the possibility of illness, how much severe it is like slight chance, moderate chance, high chance, very high chance, diabetic or not. If the user wants to know the details of diabetes complications he can select the complication option from the menu. It can also used in teaching practice.

The system is drawn up with CLIPS expert system building tool version 6.3 and in Windows/Dos environment.</text>
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                <text>An exploration into body image experiences and

 views among the third gender

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                <text>Liya  Maria Celine </text>
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                <text>An exploration of 'pull' and 'push' motivational factors among transgender entrepreneurs</text>
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                <text>entrepreneurship; India; motivation; self-employment; transgender individual entrepreneur</text>
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                <text>To date, studies have focused on the men and women entrepreneurs and the gender difference in motivations among cisgender entrepreneurs. The study aims to determine whether a transgender individual entrepreneur is motivated through a push motivational factor or a pull motivational factor. This study employs a qualitative approach uses face-to-face interviews and a semi-structured interview with a sample size of 16 transgender entrepreneurs in India. It was found that the participants in this study were motivated by both push and pull factors. The motivational factors, which add to the knowledge of already existing push and pull factors, were to forego begging and commercial sex work, to break stereotypes, to create a business opportunity for other transgender individuals, to earn respect from society, to prove entrepreneurship is non-binary, to be a role model for other transgender individuals and to the society. In contrast, the push motivational factors were the limited opportunities, support received from society, the hijra guru, media, government support, family, friends, landlords, NGOs and another push motivational factor was the exhibitions conducted exclusively for the transgender individual entrepreneurs.  2025 Inderscience Enterprises Ltd.</text>
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                <text>Sarah P.; Chellaswamy K.P.</text>
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                <text>International Journal of Business and Globalisation, Vol-39, No. 1, pp. 67-82.</text>
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                <text>Python libraries are used in this chapter to create data science models. Data science is the construction of models that can predict and act on data, which is a subset of machine learning. Data science is an essential component of a number of fields because of the exponential growth of data. Python is a popular programming language for implementing machine learning models. The chapter discusses machine learning's role in data science, Python's role in this field, as well as how Python can be utilized. A breast cancer dataset is used as a data source for building machine learning models using Python libraries. Pandas, numpy, matplotlib, seaborn, scikitlearn, and tensorflow are some Python libraries discussed in this chapter, in addition to data preprocessing methods. A number of machine learning models for breast cancer treatment are discussed using this dataset and Python libraries. A discussion of machine learning's future in data science is provided at the conclusion of the chapter. Python libraries for machine learning are very useful for data scientists and researchers in general.  2023, IGI Global. All rights reserved.</text>
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