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An evaluation of workplace HIV and AIDS programme development in zimbabwe stock exchange listed companies based in harare zimbabwe
The study explores the state of workplace HIV and AIDS interventions in Zimbabwe with specific reference to programming interventions in Zimbabwe Stock Exchange newlinelisted Companies in the Harare Metropolitan Province. The scientific knowledge domain-location of the study involves Strategic Human Resource management, Human Resource Management, Business (Corporate) planning and Labour administration (integrated occupation health and safety, employee welfare and newlinewellness) and Policy development and implementation. The key consideration is that newlinethe company has an enlightened self-interest to facilitate workplace HIV and AIDS because it leads to employee welfare, wellness and longevity which translate to increased productivity in the context of in Zimbabwe Stock Exchange-listed Companies. In this background, Zimbabwe Workplace HIV and AIDS programmes are generally considered to be fragile, fragmented, under-developed, weak and unsustainable in both design and management by a wide range of stakeholders despite close to two decades of implementation since promulgation and establishment. The study tries to identify key determinants of workplace HIV and AIDS program development in Harare, assesses the current state of workplace HIV and AIDS newlineprogramme development in Harare, tries to establish the significance of senior newlinemanagement commitment on workplace HIV programme development, ascertains the newlinerelationship between having a Comprehensive Staff Welfare Program (CSWP) and workplace HIV and AIDS program development and evaluates the extent to which companies comply with workplace HIV program development standards. The study was conducted using mixed methods and data was collected using a survey questionnaire and focus group discussions. Based on the study it was found that the general state of the Workplace HIV and AIDS Programme Development is in a state newlineof serious underdevelopment. -
An Experimental Study on Improving Speaking Skills Through the Integration of Existential Intelligence for Post Graduate Learners of Business Studies
Within the field of ESP, the constrained access to discipline-specific materials has intensified the demand, emphasizing an acute necessity for refining speaking skills, particularly in conversational contexts. This reflects an evolving paradigm, emphasizing the critical need for refined and specialized speaking competencies within their scholarly domain. The dissertation examines the use of a learning module created for Postgraduate students of Business studies to improve their speaking skills. The study 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. -
An Impact of technology based constructivist teaching on acdemic achivement of IX standrad students of Bengaluru city
Modern education emphasizes on learner centered and joyful learning which is the newlineneed of the hour as well initiated by educationists and education commission. They opine that, children need to keep active throughout the teaching and learning process and encourage self-learning and independent learning. One such emerging practice is constructivist teaching. It has changed the educational practice and converted Passive Learner Centered Environment into Active Learner Centered Environment.Constructivism newlinebelieves that learning is not encouraged in zero ground but on previous experience and newlineprior knowledge. It is the beginning for construction of new knowledge. In the context of Indian school education, it is rightly accepted as one of the pedagogical practice in National Curriculum Framework 2005 and National Curriculum Framework for Teacher newlineEducation 2009. It is also duly adopted in school education and teacher education newlineprogramme of Karnataka. Apart from constructivist approach, technology and technology integration highly influence on present education system. Technology not used only for drill,practice, tutorial etc. but also for construction of knowledge. newlineIn this context, there is a need for technology integration in constructivist practice and to give new framework for learning, teaching as well as for learner centered education. newlineHence, this research is conducted to study An Impact of Technology Based Constructivist Teaching on Academic Achievement of IX Standard Students of Bengaluru City .The main objective of the study is to compare the effectiveness of Constructivist Teaching and Technology Based Constructivist Teaching on academic achievement of IX standard students in Social Science subject. newlineThe present study is experimental in nature newlinewith two equivalent group design. In this study purposive sampling technique is used. The sample comprised of 156 students studying in IX standard of two schools (Government newlineand Private School) of Bengaluru city affiliated to state board. -
An investigation into the causes of non compliance with labour laws by zimbabwean local authorities
The current research; which I carried out in Mashonaland East Province of Zimbabwe between 2012 and 2014 was prompted by the surge newlinein labour related disputes in sub-national governments in Zimbabwe as well as the evident poor levels of compliance to labour laws by local authorities which also happen to be a poorly rated sector of the economy in terms of service delivery. In carrying out the study, I was guided by the following newlineresearch objectives: to identify the challenges being faced by Zimbabwean newlinelocal authorities in complying with the labour laws, to establish the extent to which non compliance affects labour relations in local government in Zimbabwe, to ascertain the impact of non-compliance on service delivery and finally to assess the government monitoring aspect. The targeted population for the study comprised all the ten local authorities and ministry of local government employees from the province. The study mainly newlineemployed the exploratory research design and I found that non-compliance with labour laws by Zimbabwean local authorities was not only as a result of the quality of labour relations and management systems (internal controls and corruption) but also lack of governmental financial support, political newlineinterference, skills migration (brain drain), increased poverty (economic meltdown) and high unemployment rate. In light of the research findings, I recommend that the government formulates deliberate policies to re-engage the international community as this will help attract foreign direct investment; thereby reducing poverty, unemployment, skills migration and corruption. I also recommend an increase in the financial support by government to its sub national governments. There should also be total newlinedecentralization of all sub national governments to ensure efficiency and newlinenon-interference with local authorities operations. -
An Investigation of Multifractality and Herd Behaviour in Indian Capital Market During Macro-Political Events : An Empirical Evidence Through Econophysics Approach
The financial markets worldwide exhibit several complex and dynamic features in them. Among them, Multifractality is one of the most significant features of complex systems, and it has been identified and examined in the financial markets in recent years. Besides, studies in the past confirm that there exists a linkage between multifractality and herding behaviour in financial markets during extreme events. The current study attempts to investigate the presence of Multifractality caused by herding behaviour in the segments of the Indian capital market during the macro-political events. For this, the macro- political events were classified into three broad categories pre-scheduled events, intensified geopolitical events and uncertain macro-political events. Further, two major segments of the Indian capital market, namely, the equity and the Forex segment, were examined. The study employed the Multifractal Detrended Fluctuation Analysis approach to examine the Multifractality caused by herding behaviour during macro-political events. In addition, the study also measured the volatility surface and quantified the information uncertainty present in the selected segments of the Indian capital market. The findings suggest that the macro-political events impact the multifractality and herding behaviour in the examined segments of the Indian capital market. However, the degree of the multifractality caused by the herding behaviour traced in the market segments is event-specific. It differs based on the type of macro-political event. The overall analysis suggests that the pre-scheduled macro-political event's impact was higher for both equity and forex segments of the Indian capital market. Further, a high degree of multifractality caused by herding behaviour was traced in the Nifty segments during the intensified geopolitical events. On the other hand, uncertain macro-political events had no impact on the multifractality caused by the herding behaviour in equity and forex segments. The study results provide some significant implications for various market participants for investment decision-making and portfolio risk diversification during the macro-political events in India. -
An Investigative approach to hard machining of inconel 718 with coated carbide tool
Super alloys sustain good strength at high temperature and pressure conditions. Such newlinematerials have high demand in Aerospace industry, Marine industry, and Nuclear power plants. They have a great demand in Nuclear and Aerospace applications because of it retain its properties at temperature over 700 C. Machinability of nickel based super - alloys is extremely poor, mainly due to their low thermal conductivity, build up edge and self-hardening, which leads to high dynamic cutting forces. They are difficult to machine because of its high shear strength, work hardening and precipitation hardening. High abrasive particles in its microstructure and tendency forming chip to weld to tool and form Built Up Edge (BUE) make it more difficult to machine. Friction between tool and material and its low thermal conductivity newlineresults in high temperature generation. They have Nickel (Ni), Chromium (Cr), Ferrous (Fe) or Cobalt (Co) as base contains. Small amount of Al, Ti, Nb, Ta, W, Mo added to these alloys to sustain at high temperature. Chromium is important alloying element in order to obtain the hot corrosion resistance property. Due to these factors the tool wear is extremely high and increasing the tool life by minutes is an enormous success. To overcome this situation, various newlinematerials have been developed for Inconel 718 machining. Though Ceramic tools, Silicon newlineCarbide whiskers, reinforced alumina tools, carbide tools have been used to machine Inconel 718 but they have failed to produce good surface, better accuracy and minimum tool wear. The present study is to improvise the surface roughness, reduce tool wear and create better machining parameters for extensive use of the material. Taguchi methodology, Grey Relational Analysis (GRA) and Response Surface Methodology (RSM) have been used to analyze the cutting parameters and determine better response parameters for the machining characteristics of Inconel 718. -
Analysis of some important fulid flow problems using differential geometry based methods
In this thesis we have studied MHD and EMFD flow of viscous and inviscid fluid for different cases when magnetic field and velocity are variably or constantly inclined. In particular magnetic and velocity vector are orthogonal. The pattern of streamlines and magnetic lines are derived in every problem and the effect of density and magnetic permeability on the variation of pressure is studied. The problems studied in this thesis give further investigation on the analytical solution of magnetohydrodynamic and electromagnetic fluid dynamic flow. The problems that studied analytically in this thesis have possible application in theoretical analysis of fluid dynamics and the analytical findings in this thesis can be applied in engineering fields such as aeronautics, plasmas, liquid metals and salt water or electrolytes. We have studied five problems here in this thesis. These problems are to find analytical solution of different types of fluid flows in the presence of magnetic field. Here we give a brief summary about the problems discussed in detail in this research work. (i) GEOMETRY OF CONSTANTLY INCLINED VISCOUS MHD FLOWS newlineProblems on incompressible MHD flow of viscous and inviscid fluids having newlinefinite or infinite electrical conductivity have been investigated by many researchers newlineusing different transformation methods. Transformation method is applied from newlineone plane to another plane for studying the flows by reducing the order of the equation. In this problem we have studied a viscous MHD flow having infinite electrical conductivity when the magnetic field is inclined to the velocity vector in a constant angle. Hodograph transformation is applied to shift variables from the physical plane to the hodograph plane. Streamlines and magnetic lines are analyzed along with determining the solutions to the flow problems. Finally the newlinepressure variation is analyzed graphically. Flow pattern along with pressure variation, also studied in this problem for an orthogonal MHD flow. -
Animal-Assisted Therapy : Effect on Neuropsychological Functioning, Depression and Emotion Regulation
The mere presence of a dog in a therapeutic setup is known to bring about positive newlineoutcomes, so when incorporated into therapy, dogs can bring multifarious benefits that are not entirely tapped upon. There also exist cultural differences in the perception towards and acceptance of animals which limits the generalisability of western literature. This research aimed to study the effect of animal-assisted therapy, with therapy dogs, on depression, emotional newlineregulation and neuropsychological functioning of individuals. A pretest-posttest experimental research design was used wherein 42 participants were matched and randomly divided into experimental and control groups. Both the groups received therapeutic interventions once a week, for 45 minutes, over a period of 2 months, however, only the experimental group received animal-assisted therapy. Beck Depression Inventory-II, Difficulties in Emotion Regulation Scale newlineand NIMHANS Neuropsychology Battery were used to gauge the level of depression, emotion newlineregulation and neuropsychological functioning before and after the intervention. The findings reveal that both the experimental and control group saw a significant improvement in their level of depression and emotion regulation, however, only the experimental group showed a significant improvement in all the measured domains of neuropsychological functioning. No newlinesignificant changes were observed in the domains of neuropsychological functioning of the control group. The results help validate the animal-assisted therapy interventions provided to improve the individuals neuropsychological functioning, and emotion regulation and alleviate depression. Further implications are identified and discussed as per the results. -
Anomaly detection in online social media
Online Social Media (OSM) is a platform where users post opinions, discussions, product reviews, random thoughts, advertisements, comment exchanges and status updates.These platforms help in text mining applications such as prediction of election results, newlinestudying global mood trends, public perception of a national concern or an issue, mining of public health knowledge, detecting epidemics and business analytics. These newlineapplications also present some research challenges like personal data stealing, community phishing, hate speeches, spreading misconceptions, cyber bullying and terror attack planning. Some of these challenges are anomalies or outliers which don t conform with the majority ones. The anomalies focused in this research work are behavioral and content anomalies. Data preprocessing for textual data from OSM plays an important role for creation of the Vector Space Model (VSM) which is used as an input for behavioral and content anomaly models. The contents posted by the public in OSM is written using natural language and sometimes may not follow the formal communication mode. It has lexical, newlinesemantic and syntactic ambiguities and becomes a challenging task to extract accurate information and discover logical patterns during the text mining process. Some of the commonly used methods for text mining are, Bag of Words (BoW), N-grams and Term newlineFrequency-Inverse Document Frequency (TF-IDF). Few limitations of these techniques newlineare, high dimensional sparse feature vectors, missing contextual meaning, presence of newlineweak features and Part of Speech ambiguity. In this research study, an improvised Feature Engineering model is proposed which is a combination of Forward Scan Trigrams and weighted TF-IDF to address the creation of an efficient Vector Space Model (VSM). This proposed model is used with an improvised Feature Hashing technique to address the removal of weak features. -
Antecedents and Consequences of Green Marketing Orientation in Automobile Industry : A Customer-Based Corporate Reputation Mediation Model
This dissertation presents a study that explores the influence of social cost and green innovation on environmental justice and their impact on green marketing. It also examines the role of customer-based corporate reputation as a mediator between customer cost-benefit (CCB) and customer loyalty. The research was conducted using a sample of 382 hybrid and electric vehicle owners in three major cities in India. The findings indicate that green innovation, social cost, and environmental justice significantly contribute to green marketing orientation. Moreover, green marketing orientation positively affects corporate reputation, which subsequently enhances customer loyalty and purchase intention. The study underscores the significance of implementing newlinesustainable and responsible business practices and developing effective green marketing strategies to gain a competitive edge in environmentally conscious markets. newlineThe outcomes of this study have practical implications for automobile companies, newlineoffering insights on how to enhance corporate reputation and customer loyalty through green newlinemarketing strategies. Additionally, future research may explore the moderating effects of cultural and contextual factors on the relationship between antecedents, green marketing orientation, and desired outcomes. newlineOverall, this research contributes to the existing body of knowledge on green newlinemarketing and corporate reputation. It emphasizes the need for automobile companies to adopt a more sustainable and responsible approach in their business practices, aligning with the growing environmental concerns and expectations of consumers. -
Antecedents and Outcomes of Employee Engagement : A Study on Employees in Travel Organizations
Employee engagement is becoming very vital in the recent years because organizations with engaged employees tend to out-perform than employees who are disengaged. The outcomes of engaged employees are higher performance, lower turnover, increased profitability and many more. However there are some industries ignorant and neglect the importance of having engaged employees. Hence it is necessary to conduct more research on employee engagement which create more awareness to the organizations about the prominence of focusing on employee engagement and also augment to the existing literature. The study was conducted on a sample size of 433 employees working in travel organizations set up in Bengaluru and tested the relationship of psychological climate and psychological capital (antecedent variables) has on employee engagement and in turn its newlinerelationship with organizational citizenship behavior and intent to stay (outcome newlinevariables). The study also tested the mediating relationship of employee engagement newlinebetween the antecedent and outcome variables. Results indicated that psychological newlineclimate and psychological capital has a significant and positive relationship on employee engagement and with respect to outcome variables it was determined that higher the engagement level it leads to higher level of organizational citizenship behavior and intent to stay. Results of the study also indicated that employee engagement mediates the relationship between the antecedent and outcome variables. -
Antecedents of Behavioural Intention : Study of Indian Consumer Perceptions Towards P2P Lending Using Technology Adoption Model
Fintech is a rapidly developing area of the financial services business where tech-focused startups and other new players are upending how the sector has historically operated. One of the emerging fintech areas under digital lending is Peer to Peer lending or (P2P) lending; Consumers and authorities are both showing interest in this alternative lending innovation. Results of a literature review show that India is still in the early stages of P2P lending research. The study examines the association between behavioural intention to use P2P lending in India and technological and personal adoption factors. The study model was developed with the help of a literature review and tested using data from 536 respondents who completed an online survey and was tested using covariance-based structural equation modelling (SEM). The results confirm that personal innovativeness, performance expectancy, hedonic motivation, effort expectancy, social influence, and perceived risk are the antecedents of the adoption of P2P lending, except for facilitating conditions and price value. In addition, gender moderates the relationship between performance expectancy, hedonic motivation, personal innovativeness, and intention to adopt P2P lending. The study also throws light on the perceptions of both users and non users in terms of the antecedents. The study's conclusions significantly impact the P2P lending industry and provide practical insights for developers, platforms and regulators to improve and enhance the service. The study suggests looking at other moderating factors like age, voluntariness, experience, and actual usage behaviour for further research. Overall, the research contributes to the academic literature by confirming the predictive power of the extended unified theory of acceptance and use of technology (UTAUT). It highlights personal innovativeness after performance expectancy and motivation as an important factor in predicting the usage of P2P lending. Finally, the study lists managerial implications in the domains of technological adoption, which will assist in the P2P lending long-term success in India. -
Antecedents of psychological capital and its consequences on affective commitment and psychological wellbeing
Jharkhand Education Board stakeholders face the problem of dealing with the educational environment, thereby escalating a teacher's morale. To address this situation, a positive mindset in education, particularly among teachers, is desirable. Hence, based on positive psychology discipline, conservation of resource theory, and broaden and build theory, the study was carried out using a sequential explanatory mixed-method study design. The research questions addressed in the study were as follows: To what extent can the categories of proactive personality, emotional intelligence, servant leadership, and perceived organizational support predict PsyCap of teachers? To what extent will PsyCap predict the categories of affective commitment and psychological wellbeing? I considered both quantitative and qualitative methods; hence, this study had two phases. In the first phase, the data was gathered from 722 teachers using the survey instruments. The statistical analyses performed were Confirmatory Factor Analysis and Structural Equation Modeling with the software SPSS 20.0 and AMOS 20.0. For teachers of rural Jharkhand, the study found that psychological capital has three dimensions. Besides proactive personality, emotional intelligence, and servant leadership also impact psychological capital. Further, psychological capital affects affective commitment and psychological wellbeing. In the second phase, this study examined the way and the reason behind the functioning of the antecedents of psychological capital using qualitative content analysis. The results offered a comprehensive understanding and identification of the antecedents that form rural teachers' psychological capital. Implications of the research include recommendations for recruiting teachers with higher levels of psychological capital and professional development through in-service teachers' training with a specific focus on psychological capital. -
Antecedents of Psychological Capital and Its Consequences on Affective Commitment and Psychological Wellbeing
Jharkhand Education Board stakeholders face the problem of dealing with the educational environment, thereby escalating a teacher's morale. To address this situation, a positive mindset in education, particularly among teachers, is desirable. Hence, based on positive psychology discipline resource theory conservation, and broaden and build theory, the study was carried out using a sequential explanatory mixed-method study design. The research questions addressed in the study were as follows: To what extent can the categories of proactive personality, emotional intelligence, servant leadership, and perceived organizational support predict PsyCap of teachers? To what extent will PsyCap predict the categories of affective commitment and psychological wellbeing? We considered both quantitative and qualitative methods; hence, this study had two phases. In the first phase, the data was gathered from 900 teachers using the survey instruments. The statistical analyses performed were Confirmatory Factor Analysis and Structural Equation Modeling with the software SPSS 20.0 and AMOS 20.0. For teachers of rural Jharkhand, the study found that psychological capital has three dimensions. Besides proactive personality, emotional intelligence, and servant leadership also impact psychological capital. Further, psychological capital affects affective commitment and psychological wellbeing. In the second phase, this study examined the way and the reason behind the functioning of the antecedents of psychological capital using qualitative content analysis. The results offered a comprehensive understanding and identification of the antecedents that form rural teachers' psychological capital. Implications of the research include recommendations for recruiting teachers with higher levels of psychological capital and professional development through in-service teachers' training with a specific focus on psychological capital. -
Antimagic labeling and its variations in graphs
Graph theory is a branch of discrete Mathematics with its results having significant applications in many areas of computing, social, and natural sciences. Graph labeling is one of the fascinating areas of graph theory with wide-ranging applications. The concept was first introduced in the 1960s where the vertices and edges are assigned real values or newlinesubsets of a set subject to certain conditions. The labeling dealt in the thesis is edge labeling basically, that is, assigning a label to the edges of the graph. Depending on the conditions applied in labeling give way to magic, super-magic, antimagic labelings. Hartsfield and Ringel introduced the notion of antimagic labeling in the year 1990. In this thesis, three variations in graph labeling are dealt namely, equitable antimagic labeling, equitable difference labeling and extension of equitable irregular labeling with an introduction of k-equitable irregular labeling. For a given graph G = (V,E), an equitable antimagic labeling (EAL) of G is a bijective edge-labeling f: E(G) and#8594; {1,2,3,...,m = |E(G)|} such that |W_f (u)-W_f (v)| and#8804; 1 for any pair of adjacent vertices u and v of G, where W_f (v) is the sum of the labels of the edges incident with the vertex v. A graph admitting an EAL is called an equitable antimagic graph (EAG). In Chapter 2, we initiate a study of this new edge labeling of graphs. A diand#64256;erence labeling of a graph G is realized by assigning distinct integer values to each vertex and then associating with each edge, the absolute diand#64256;erence of those values assigned to its end vertices. That is, it is an injective function f: V(G) and#8594; N together with function f^*: E(G) and#8594; N deand#64257;ned by f^* (uv)=|f(u)-f(v)|for any edge uv in G. The function f^* is called the weight function induced by f. An irregular labeling f: E(G) and#8594; N with the property that S_f (u) and#8800; S_f (v) for any two vertices u and v of G, where S_f (u) denotes the sum of the labels of the edges incident with the vertex u. The sum S_f (u) is called the vertex sum of u under f. -
Application of Hydrogel in Paddy Field for Soil Moisture Retention and Yield Optimization
Agricultural sustainability is essential to enhance food and water security, particularly in the context of climate change. To ensure food security and to protect water resources, agricultural and irrigation practices need to be amended with innovative technology that conserves water and increases productivity. In the recent past, applications of hydrogels in agriculture have received substantial attention among researchers as well as among farmers. Paddy is the core crop for the vast newlineparts of the world. The present study elaborates on various aspects of hydrogels such as classifications, ideal properties for agricultural application, analysis of soil characteristic changes for pre and post crop newlineseason, irrigation water quality analysis for crop season. BPT 5204 and NDLR 07 varities of paddy had been experimented in this study. newlineVerification of hydrogel degradation was conducted using Fourier transform infrared (ft-ir) spectroscopy. The experimental methods for determining hydrogel properties were given specific attention to properties such as swelling, retention, slow release, and degradation which are vital for agricultural sustainability. Hydrogel experiments have demonstrate significant improvement in water consumption, water use newlineefficiency, crop growth and yield parameters. The reduction in water footprint in major crops such as paddy and wheat through hydrogel might establish a shift towards sustainable irrigation practices if adopted on a large scale. Integrating innovative solutions with environmental-friendly newlinehydrogels in the coming decades will contribute to the pursuit of achieving newlinesustainable development goals. The application of hydrogel as soil conditioners was identified as a possible solution. to increase water use efficiency in irrigation and optimization of crop yield. The study points towards developing a framework for the evaluation of the suitability of hydrogel for agricultural applications when get scaled up to regional level. -
Artificial Intelligence - Based Steganography Model for Social Media Data Set
Steganography, one of the data security mechanisms under our investigation, shields legitimate messages from hackers and spies by employing data hiding. Data protection is newlinecurrently the top priority due to the signifcant advancements in information technology due to high-security concerns. Traditional techniques for maintaining data confdentiality include steganography and cryptography; the distinction is that steganography does not naturally arouse suspicion, whereas cryptography does. Traditional linguistic steganographic methods suffer from limitations in automation, accuracy, and the volume of concealed text. The robustness and undetectability properties of these approaches also require improvement. Third-party vulnerability is often too high for conventional techniques to handle. Artifcial intelligence is increasingly replacing traditional model creation in steganography. Despite the fact that steganography ensures security, information sent over online social networks (OSN) is plainly not safe. Steganography along newlinewith encryption can make a difference with regard to privacy of information in transit. newlineThe research study aims to build algorithms or models and assess steganography s robustness, security, undetectability, and embedding ability. Two distinct types of data newlineconcealing employed for investigation: text and image. The results were encouraging newlinewhen we initially tested our Laplacian model using image steganography and compared newlinewith benchmark methods. The second experiment, which is based on AI, generates the cover text using secret information, examines the security and robustness of steganography. The study compared suggested text steganography model, 3-bit data concealing, with other existing techniques in order to ascertain the undetectability factor. The frst experiment used MATLAB tools, and the second used the markovify python module, RNN (Recurrent Neural networks), and the Huffman tree. Further format-based steganography methods utilized in the following experiment. -
Artificial Intelligence Based Computational Framework for Identification and Classification of Interstitial Lung Diseases Using HRCT Images
Interstitial Lung Diseases (ILDs) refer to a wide array of respiratory disorders characterised via infection and scarring of the lung's interstitial tissue. These conditions affect the space within the air sacs, compromising the lungs' ability to expand and contract properly. ILDs manifest with a range of symptoms, including persistent cough, shortness of breath, and fatigue. Diagnosis of ILDs often involves imaging methods, mainly High-Resolution Computed Tomography (HRCT), to assess lung abnormalities. ILDs can have lasting effects on respiratory function, leading to progressive fibrosis. The primary obstacle in identifying ILDs lies in the diverse array of symptoms they present, making it challenging to distinguish them from other pulmonary disorders. The HRCT is a commonly employed method in ILD diagnosis. These images provide a detailed depiction of lung tissue, revealing its size, shape, and any notable abnormalities or changes. Moreover, HRCT plays a crucial role in monitoring disease progression over time. Deep Learning (DL) excels in detecting patterns in intricate medical images that may pose challenges for traditional methods. Moreover, DL algorithms exhibit the ability to identify subtle changes in medical images indicative of pathology, and they can automate object detection tasks. The application of DL in medical contexts can enrich the precision and rapidity of diagnoses. In this research aimed at improving the accuracy of artificial intelligence AI-based ILD identification, we harnessed the benefits of deep learning, employing full-training, Transfer Learning (TL), and ensemble voting techniques. Our approach involved the construction of three Convolutional Neural Networks (CNNs) from scratch for ILD detection. Additionally, we customized models named InceptionV3, VGG16, MobileNetV2, VGG19, and ResNet50 for both full-training and TL strategies. This comprehensive methodology aimed to take benefits of DL architectures to enhance the precision of ILD identification in medical imaging. Both the first dataset consisting of HRCT images and the second dataset comprising Chest X-ray were employed in our study. However, during the initial training phase of the TL models, we utilized pre-trained ImageNet weights. To enhance performance, modifications were made to the classification layers of all five models for both TL and full-training processes. To further improve training outcomes, a soft-voting ensemble approach was employed. The ensemble, combining the predictions of all three newly developed CNN models (ILDNetV1, ILDNetV2 and ILDNetV3), and ILDNetV1 achieved the highest test accuracy at 98.14%. Additionally, we incorporated machine learning (ML) models, including Logistic Regression, BayesNet, RandomForest, Multilayer Perceptron (MLP), and J48, using statistical measurements derived from HRCT images. Our study introduces a novel AI-based system for predicting ILD categories. This system demonstrated superior performance on unseen data by leveraging the results from the newly constructed CNNs, transfer learning, and ML models. This comprehensive approach holds promise for advancing ILD category prediction, providing a more robust and accurate tool for medical diagnosis and decision- making.