International Journal of Engineering and Management Research
Not a member yet
1311 research outputs found
Sort by
A Study of The Effect of Public and Private Debt on Zambia’s Economic Growth
No full textPublic and private debt plays a critical role in bridging government financing gaps especially in developing countries like Zambia with low economic growth (World Bank, 2017). Notwithstanding this fact, public debt can however be viewed as a doubled-edged sword. Public debt has become an important problem for most countries over the last decades. Despite acquiring this level of debt, most of the country’s population has continued to live in excess poverty and only a few are successfully employed. The study utilized descriptive and correlational designs and sought to determine the relationship between the independent variables (private and public debt) and economic growth, investment and social progress index .The study utilised economic secondary data from 1964 to 2020 a period of 56years. The result found that public debt has negatively affected the rate of growth in the Zambian economy over the period of study. This implies that an increase in public debt will decrease economic growth. However, public debt impact on investment was found not significant at p value 0.05, despite the coefficient indicating a weak positive correlation. The association between private debt, investment, economic growth by GDP and NGDP was found to be positively correlated and significant p-values (0.0092<0.05). However, it was revealed that increasing the amount debt especially public debt affects and reduces the level of economic growth. The study revealed that private debt increases investment and domestic saving which means that they positively impact economic growth. Private debt by individuals and corporations was found to have positive effects on some social progress indicators such as literacy, carbon emission per capita, electricity access and GDP per capital growth. Finally, it was recommended that a scrutinizing agency should be established before the acquisition of debt. As this would help in reducing the acquisition of debts which have little significance in improving the economy
An Assessment of the Economic Effect of Industry Clusters on Economic Development in Zambia - A Case Study of the Lusaka South Multi Facility Economic Zone
No full textThis paper sought to assess the economic effect of industry clusters in the Lusaka South Multi Facility Economic Zone (LS MFEZ) on economic development. The objectives of the study were: to investigate the factors that promote economic growth in LS MFEZ, to determine the economic contribution of the industry clusters in LS MFEZ and, to investigate the constraints faced by the firms operating in LS MFEZ. The major findings of the study were that the firms operating in the LS MFEZ were influenced by aspects related to reduced costs of operations, access to advanced technologies and reduced transaction costs. The study observed that the LS MFEZ contributed to the creation of employment for both skilled and unskilled labor. Further, the study revealed that operations in the LS MFEZ promoted the growth of the transport sector and strongly contributed to local and international trade. The study was also informed of various constraints faced by the firms operating in the LS MFEZ and these included huge capital requirements, inadequate infrastructure, and lack of other essential services such as electricity among others. The research recommended skill trainings for local workers as well as a policy that supports the financing and infrastructure development for the industry clusters
A Review on Sentiment Analysis of Twitter Data Using Machine Learning Techniques
No full textTwitter, a microblogging network, has grown into an ongoing repository of real-time user-generated data, providing a valuable dataset for sentiment analysis. It is an approach that determines the emotional state of data or language. People\u27s opinions may help organizations and governments to acquire information and make decisions based on their perceptions. For instance, when you want a greater understanding of customer sentiment, you can begin by looking at customer feedback underneath what they bought or comments under your company\u27s post on any social media platform. Sentiment analysis determines that a particular text expresses negative, pleasant, or neutral feelings. It\u27s a type of analysis of texts that employs NLP and machine learning. Sentiment analysis employs NLP, analysis of text, computational linguistics, and biometrics to systematically detect, extract, measure, and investigate emotional states and subjective information. This paper provides a thorough review of Twitter Data Sentiment Analysis Using ML Techniques. It covers traditional ML algorithms like random forest, Logistic regression, Naive Bayes, SVM, and decision tree, classifiers, as well as complex deep learning algorithms like RNN, LSTM and CNN and as well as hybrid models like ConvBidirectional-LSTM and CNN-LSTM. Finally, the limitations of Twitter sentiment analysis are examined to suggest future directions
Optimization of Concrete Mix Design for UPVC Tube Encased Columns: A Study
No full textThis study focuses on assessing the load-carrying capacity of UPVC tubes filled entirely with concrete by subjecting them to axial loading until failure occurs. A total of eighteen UPVC tubes, each with a diameter of 150mm as well as a thickness of 7.11mm, as well as effective lengths ranging from 500mm to 700mm were used. M20 grade concrete sourced from two different mixes with aggregate sizes of 6.3mm as well as 10mm was placed inside the tubes to create UPVC concrete-filled tube (CFT) column samples. These column specimens were then tested for axial loading using a UTM with a capacity of 1000kN, as well as load-displacement as well as stress-strain curves were recorded. The failure mode observed in all columns was local buckling, with increased strength noted as the length of the column increased, particularly in the mix with 6.3mm coarse aggregate compared to 10mm coarse aggregate. The experimental setup also included a study on the efficacy of Polyvinyl Chloride (PVC) confinement in short plain circular concrete columns, utilizing various diameters of PVC tubes (110mm to 250mm) with two confinement methods: full confinement as well as confinement with cut ends. The results indicated a significant increase in the ultimate load capacity of the columns with external PVC tube confinement, with enhancement ratios ranging from 4.16% to 15%. Additionally, the study revealed that UPVC CFT columns exhibited an approximate 1.6% increase in compressive strength compared to theoretical values
Collective Research Review on Chaotic Based Encryption Algorithms, Speech Encryption Algorithms and Cryptographic Requirements
No full textChaotic cryptography has been a recent development by researchers due to its interesting properties such as non-linear behavior, sensitivity to initial conditions, ergodicity, mixing, confusion and diffusion etc. This paper is a brief review of various standard encryption algorithms, cryptographic requirements for design of chaotic based cryptosystem and chaos-based speech encryption algorithms. This study also gives various statistical tests needs to be considered for conformity about suitable randomness of the binary sequences generated using either hardware or software means for cryptographic applications as key sequence
Editable Neural Radiance Fields Convert 2D to 3D Furniture Texture
No full textOur work presents a neural network designed to convert textual descriptions into 3D models. By leveraging the encoder-decoder architecture, we effectively combine text information with attributes such as shape, color, and position. This combined information is then input into a generator to predict new furniture objects, which are enriched with detailed information like color and shape.[1] The predicted furniture objects are subsequently processed by an encoder to extract feature information, which is then utilized in the loss function to propagate errors and update model weights. After training the network, we can generate new 3D objects solely based on textual input, showcasing the potential of our approach in generating customizable 3D models from descriptive text.[2
Investigating the Effects of Admission-Related Stress on College Faculty in the Pondicherry Region
Get PDFThis study explores the impact of admission-related stress on college faculty members in the pondicherry region, focusing on both psychological and professional dimensions. Utilizing a mixed-methods approach, the research involved surveying and interviewing faculty across various colleges to identify key stressors and assess their effects on faculty well-being and job performance.
Findings indicate that a significant proportion of faculty experience high levels of stress during the admissions period, which adversely affects their mental health and professional efficiency.
Key factors contributing to this stress include increased administrative workload, heightened expectations from students and parents, and inadequate institutional support. Additionally, demographic variables such as age, experience, and departmental affiliation influence stress levels, with younger and less experienced faculty reporting higher stress.
The study also highlights effective coping mechanisms and institutional policies that can mitigate stress, suggesting the need for comprehensive support systems and stress management resources.
These insights aim to inform policy recommendations to improve faculty well-being and enhance the overall educational environment
Application of Multimodal Deep Learning in Sentiment Analysis for Recommendation Systems
Get PDFThis paper proposes a sentiment analysis method for recommendation systems based on multimodal deep learning. In modern internet applications, the accuracy of recommendation systems and user satisfaction are crucial. Therefore, this study designs and implements an innovative multimodal deep learning model that integrates text, image, and user behavioral data for sentiment analysis tasks. Extensive experimental validation using multiple public datasets demonstrates that the proposed method not only significantly outperforms traditional approaches in accuracy but also makes substantial advancements in enhancing user satisfaction and recommendation effectiveness
Strategic Integration of Artificial Intelligence and FinTech Innovations in Renewable Energy Management
Get PDFThe intersection of Artificial Intelligence (AI) and Financial Technology (FinTech) with renewable energy heralds a transformative era in energy systems worldwide. This paper explores the pivotal role of these technologies in facilitating the efficient integration and management of renewable energy sources. As global energy paradigms shift towards sustainable models, the deployment of AI enhances predictive analytics, grid management, and energy storage systems, thereby optimizing the reliability and efficiency of renewable energy. Concurrently, FinTech innovations emerge as crucial enablers, offering novel funding mechanisms and investment frameworks through blockchain and smart contracts, which ensure transparent and efficient financial transactions in the energy sector. This paper provides a comprehensive review of current technologies, highlights key applications, and discusses the integration strategies of AI and FinTech that enhance the scalability and effectiveness of renewable energy solutions. Moreover, it addresses the regulatory and ethical considerations that accompany technological advancements, ensuring a balanced perspective on fostering innovation while mitigating risks. By presenting case studies and future predictions, the paper aims to underline the potential for AI and FinTech to revolutionize energy systems, setting a blueprint for stakeholders to navigate the complexities of renewable energy integration
Acculturation in Knowledge Intensive Banking: Multi-Dimensional Consequences for Employee Vitality in Job Demands Resource Perspective
Get PDFAs the industry is getting revolutionized, the knowledge and information is bound to play a central and critical role in shaping the organizational competitiveness and ability to be agile and resilient. The employee based acculturation, getting accustomed to new ways of working, employee based indulgence in open innovation and employee based leverage of social media; seems to count in improving and shaping the employee based productivity in banking perspective. The research seeks to empirically ascertain the relationship between acculturation of employees and employee vitality in rural branches and relies on pre validated scales for construct operationalization. The sample of 309 respondents was leveraged and research hypothesis were found to be true