Volume 12 | Issue 4

 Abstract

In today's world, robots are used in various applications such as military, medical, automobile industries etc. But if construction industries are considered then in that industries robots are not used. The robots are used to increase the efficiency and reduce the time in all the fields. It can also be used to do hazardous and dangerous jobs in any field. Nowadays, the wall painting is done manually. This process can be simplified by using robot. It is very difficult to paint the wall in upright direction which is at a very long distance from earth. Painting in an upright position is also very dangerous for the eyes. So, to overcome this difficulty we are manufacturing Wall Painting robot. The components of our project are decided. The 3D model will be drawn with the help of CATIA software. All the components are manufactured and then assembled together. The experimental testing will be carried out after the final assembly will be done. The result and conclusion will be drawn after the experimental testing. The painting chemicals can cause hazards to the human painters such as eye and respiratory system problems. Also the nature of painting procedure that requires repeated work and hand rising makes it boring, time and effort consuming. When construction workers and robots are properly integrated in building tasks, the whole construction process can be better managed and savings in human labour and timing are obtained as a consequence.

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 Keywords

3D model, CATIA software, Painting chemicals, Painting robots, Industry robots

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract:- "Jhum Cultivation" has been identified as one of the main human impacts influencing "Bio-Diversity" in Tripura, North east India. It is the main form of agriculture in the hills of Tripura. In Tripura more than 20% of Tribal families are dependent on "Jhum Cultivation" for their livelihood. "Jhum Cultivation" practice have some positive and negative effect. In "Jhum Cultivation", Burning and slashing method is followed to control of weeds, soil-borne pathogens and other diseases of crops in those areas.

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 Keywords

Keywords:- Jhum Cycle, Environment, Jhumia, Sustainability, Livelihood, Soil Health, Tribal People,Rehabilitation,Alternative Option, Shifting Cultivation,Tripura.

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Creative Commons Attribution 4.0 and The Open Definition

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TicketEase is a web-based platform meticulously engineered to streamline issue management processes within organizational contexts. The system employs advanced Machine Learning (ML) techniques to prioritize and classify employee complaints and issues, effectively addressing software, hardware, and application-related challenges. Leveraging Angular for frontend development, TicketEase ensures an intuitive user experience, while its backend infrastructure, powered by Spring Boot, Java, and Hibernate, provides robustness and scalability. Technologies such as Maven, GitHub, Postman, Swaggy, and MySQL are seamlessly integrated to facilitate efficient development, testing, documentation, and database management. By employing Random Forest, TicketEase enhances its ability to accurately categorize and prioritize incoming issues, ensuring that urgent and critical matters receive prompt attention and resolution. The algorithm's robustness and scalability contribute to the platform's effectiveness in managing a large volume of tickets while maintaining high levels of accuracy and efficiency. The platform's architecture and methodologies are meticulously designed to adapt to evolving organizational needs and technological advancements. This paper offers a comprehensive exploration of TicketEase, detailing its architecture, ML algorithms, and integration of key technologies. Through experimentation and evaluation, TicketEase demonstrates its efficacy in efficiently managing issues, offering organizations a potent tool to bolster operational efficiency and foster a culture of continuous improvement. As organizations navigate the complexities of modern work environments, TicketEase emerges as a transformative solution, poised to revolutionize issue management practices and drive organizational success.

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 Keywords

TicketEase, web-based platform, issue management, Machine Learning (ML), prioritize, classify, software, hardware, application-related challenges, Angular, frontend development, Spring Boot, Java, Hibernate, Maven, GitHub, Postman, Swaggy, MySQL, Random Forest algorithm, categorize, prioritize, robustness, scalability, architecture, methodologies, organizational needs, technological advancements, efficacy, continuous improvement, operational efficiency, transformative solution, revolutionize, dr

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 Abstract

Saline, one among the foremost popular intravenous (IV) therapies plays a serious role within the management of patients who are critically ill. Surveillance of saline bottle level is extremely important because when the bottle is emptied and therefore the needle isn't far away from the vein then the blood flows outward into the bottle. In hospitals, the nurses or caretakers are liable for monitoring the saline bottle level. Mostly, thanks to negligence and any unusual condition, the precise timing of removing the needle from the patient's vein is ignored which causes a significant casualty and should lead to death as well. Furthermore, remote monitoring may be a got to provide telehealth services. To prevent the accident due to the ignorance of caretakers and to provide remote surveillance in telehealth services, we have proposed the cost-effective smart saline level monitoring device which includes the mixture of sensor and Internet of Things (IOT) technologies. We have built this system by using load sensor and ultra-low power low cost Arduino micro controller. The load sensor converts the load of the bottle to a selected voltage. The ESP8266 micro controller generates and publishes a specific message based on the voltage received from the sensor. To publish and present the messages to the devices of subscribers like doctors, nurses or care takers. This proposed monitoring system ful-fills the reliable delivery of messages to the subscribers which is very important for healthcare. Automatically, saline bottle valve will be closed without human intervention.

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 Keywords

Arduino, Internet of Things, GSM Sim 800a,Saline monitoring

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Creative Commons Attribution 4.0 and The Open Definition

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During the current era, the insurance sector has emerged as a crucial component in the economies of both developed and developing nations. It is widely acknowledged that the presence of a well-developed insurance sector is crucial for fostering the economic development of emerging economies, such as India. Insurance markets function as a crucial financial intermediary, playing a significant role in fostering economic growth within a country. Additionally, they serve as an effective mechanism for managing and mitigating risks in a more efficient manner. The objective of this research endeavor is to thoroughly examine the prevailing and emerging patterns and developments in the country of India. This study used only secondary sources and the Insurance Regulatory and Development Authority of India website. The Insurance Regulatory and Development Authority of India (IRDAI) emphasizes proactive and forward-thinking to attain its goal of universal insurance by 2047. According to the IRDAI report, India ranks 27th globally in terms of insurance density compared to other countries in the Asia Pacific region. IRDAI has been reported that the insurance density in India for the year 2022-23 stands at 92 USD. This amount is determined by taking into account both the life insurance category, which contributes 69 USD, and the non-life insurance category, which contributes 22 USD. Assessing the vast opportunities and immense potential of the Indian insurance industry on an international level. In 2021, the total premium volume reached an impressive $127 billion. During the fiscal year 2022, there was a significant increase of 10.2% in premiums within the life insurance sector. Meanwhile, the non-life segment experienced a significant 10.8% growth, mainly driven by the increased demand for health and motor insurance (ICICI Lombard, 2023). According to IRDAI, the insurance penetration rate in India for FY22 was estimated to be 4%, slightly lower than the rate of 4.2% in the previous fiscal year. The life insurance penetration rate was at 3%, while the non-life insurance penetration rate was at 1%. Based on our findings, it was discovered that the Indian insurance industry has a penetration rate of less than 5% of the country's Gross Domestic Product (GDP).

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 Keywords

Insurance, Life-Insurance, Non-Life Insurance, Insurance Sector

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Creative Commons Attribution 4.0 and The Open Definition

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Computer programs that can recognize, track, identify, or validate human faces in pictures or videos are known as face recognition programs(Yang & Han, 2020a) .This biometric security system recognizes a person by their face traits.(Yang & Han, 2020). People can be recognized in images, films, or in real time using facial recognition technology. Systems for recognizing faces employ distinct mathematical patterns to store biometric information. They are among the safest and most reliable identifying techniques available in biometric technology as a result(Grudin, 2000). To lower the possibility of unwanted access, facial data can be privatized and anonymized. The technique of recognizing or verifying a person's identification using technology based on images, videos, or in-the-moment surveillance of their face is known as facial recognition.(Kortli et al., 2020) . Facial recognition systems may generally be utilized for two kinds of tasks: identification and verification. The background of facial recognition technology. Woody Bledsoe, Helen Chan Wolf, and Charles Bisson were the pioneers of automated facial recognition in the 1960s, with their work centered on teaching computers to recognize human faces. In addition to lowering crime rates, enhancing safety and security, and minimizing human contact, facial recognition technology has benefits for society(Annual IEEE Computer Conference et al., n.d.). The following are a few benefits of facial recognition: aids in the recovery of missing persons. Safeguards companies from theft. It varies according to the kind of facial recognition we're discussing(Yang & Han, 2020b). Among the safest in the business is Apple's 3D facial recognition system. However, 2D facial recognition, which is present in the majority of phones, is not very safe. Its lack of security implies that it won't open for someone else's face, but it might still open for a photographer, while you're asleep, or when you wear makeup or sunglasses and it can't identify your presence(Zhang & Institute of Electrical and Electronics Engineers, n.d.). It will be simpler for the recognition system to discover and identify faces in clear, well-focused photographs with decent illumination. Encourage your subjects to keep their postures and facial expressions consistent when the camera is focused on them. This can improve the system's ability to match faces between various photos. Crucial elements encompass the separation between your eyes, the profundity of your eye sockets, the arc from your forehead to your chin, the form of your cheekbones, and the outline of your lips, ears, and chin(Phillips et al., 2005). Finding the facial landmarks that are essential to differentiating your face is the goal. Low image quality or inadequate lighting can affect facial recognition systems(Lu et al., n.d.). Because of obstructed camera angles, the data might not match the person's nodal points; this results in an error when matching faceprints cannot be confirmed in the database.

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 Keywords

Students live Behavior Monitoring, Criminal Investigation Tracker, Attendance System

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The current study investigates the significant influence of Adverse Childhood Experiences on emotional intelligence (EI) and spiritual intelligence (SI), which are essential aspects of human functioning that greatly contribute to overall well-being. Adverse childhood experiences refer to a variety of potentially traumatic events or hardships that individuals may face throughout their early years, such as abuse, neglect, dysfunction in the household, and other sources of stress. Adverse Childhood Experiences can hamper the development of emotional intelligence by negatively affecting key components such as empathy, self-awareness, and emotional regulation. This, in turn, impairs individuals' capacity to manage relationships and effectively cope with stressors. Moreover, ACEs have an impact on spiritual intelligence as well, hindering people's ability to transcend, create meaning, and find existential contentment. A person's sense of resilience, purpose, and connection can all be disrupted by childhood trauma, which can cause spiritual pain and existential angst. This dissertation sheds insight on the long-lasting effects of Adverse Childhood Experiences on Emotional Intelligence and Spiritual Intelligence. Through the clarification of these connections, it emphasizes the value of trauma-informed strategies for people who faced adverse effects in their childhood and the demand for interventions that foster recovery, growth, and resilience.

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 Keywords

Adverse childhood experiences, Emotional Intelligence, Spiritual Intelligence, Psychological Development, Coping mechanisms.

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Creative Commons Attribution 4.0 and The Open Definition

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Infact the idea of using ethanol has really been around since the 18? ? century, it has recently become increasingly popular as a result of the diminishing supply of fossil fuels, high fuel prices, air pollution, global warming. For IC engines, ethanol is a possible alternative fuel. Due to its renewable nature, seeming ability to replace gasoline, ethanol is one of the most significant substitute fuels for petroleum gasoline. In IC engines, ethanol can be blended with fossil fuels without requiring any modifications. So, based on the significance of using ethanol blend with biodiesel in an IC engine, a performance evaluation of using ethanol blend with biodiesel tests were carried out in accordance with the BIS. The tests were conducted using ethanol blends at various ratios, such as E0, E5, E8, E10, and E12,. The load was varied from no load to full load for normal biodiesels. A maximum BP of 4.567 kW was observed from W.V.O. (B100), BSFC of P.P. [B95E5] higher than other fuels ratios i.e., 0.578 kg/kW/hr, BTE of [B92E8] was 24.87% as compared with other fuels blends.

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Key words: Ethanol blend, Performance, Brake Specific Fuel Consumption, Brake Thermal Efficiency.

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 Abstract

:- Risk management and project success are linked. Project management literature describes a four-step risk management process: identification, estimate, reaction planning, and execution. These periods frequently require risk management control. Effective construction project management requires identifying work activities, their linkages, and estimating resource requirements and activity durations. The research assessed construction professionals' understanding of planning tools and practices utilised on building sites. A chosen group of project managers, engineers, architects, contractors, and subcontractors engaged in project planning and implementation received questionnaires. Using SPSS for Windows, pie charts and frequency tables were used to analyse the data. Professionals lack actual understanding of building planning tools and processes, according to the report. These tools and techniques should be used in all building projects, emphasising the need for regular and adequate training on information technology's use in construction, particularly in project planning and execution.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Risk management, Project success, Construction project management, Planning tools and practices, Information technology in construction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the constantly evolving realm of urban security, the incorporation of machine learning (ML) technologies into existing Closed-Circuit Television (CCTV) networks emerges as a game-changing solution. Inspired by real- world challenges where traditional surveillance methods often falter, our project sets out to redefine urban safety through innovative technological interventions. Our approach harness the potential of ML, involving the YOLOv8 (YOU ONLY LOOK ONCE) algorithm, to conduct real-time analysis of video feeds, swiftly identifying suspicious activities, anomalies, crowd congestion, weapons, and known criminal faces. By seamlessly integrating ML-generated insights with conventional surveillance techniques, we aim to elevate the public safety, enhance law enforcement efficiency, prevent crimes, and streamline operational processes. Additionally, our system leverages facial recognition capabilities to identify wanted individuals from a database of known criminals, further crime prevention efforts. Moreover, we incorporated a work monitoring module, for tracking employee presence, work utilization, and non-violent scenarios to optimize workplace safety. This initiative marks a significant milestone in urban security, laying the groundwork for safer and smarter cities in the future.

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Creative Commons Attribution 4.0 and The Open Definition

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Crowd Management, Violence detection, Weapon detection, Work Monitoring, sound alert and email alert

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 Abstract

The matter of dalit suppression has been of great concern towards constructing an ideal Indian nation. It has been a curse for the Indian nation since the beginning of the caste system. The outcaste or the so-called dalits have been oppressed and discriminated against in the hands of upper caste people of the society. Although some steps have been taken for their upliftment after the colonial era, still they're in a suppressed state. Still there is a change to come to build up a castle and class less Indian nation where nobody will be oppressed. There is the need for a change in the mindset of both the upper caste people and the dalits themselves to come. This paper tries to bring a link between Mulk Raj Anand's ''Untouchable" and Odia writer Manglu Charan Biswal's play "Bhukha (The Starved)" on dalit cause.

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 Keywords

Dalit, untouchable, starved, hunger, out-castes, oppressed, discrimination, change, hopeful.

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Creative Commons Attribution 4.0 and The Open Definition

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The escalating urban population in India has given rise to a surge in traffic congestion within cities, posing challenges for ambulances to navigate through densely populated streets. This issue is exacerbated by a general lack of public awareness regarding the critical importance of yielding to emergency vehicles. To address this problem, our research focuses on training the YOLOv8 model for effective ambulance identification amidst other vehicles on the road. YOLO, distinguished for its efficacy in object detection, notably excels in swift processing speeds and exceptional accuracy. This project emphasizes the utilization of YOLOv8, which demonstrates an 84.62% precision, a 75.93% recall, and an F1-score of 79.98% for ambulance detection and the application of deep learning methodologies for image segmentation, aiming to enhance emergency vehicle navigation in congested urban environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Emergency vehicles, YOLOv8, object detection, deep learning, image segmentation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper describes a system for predicting student performance and recommending courses using predictive analytics. The system utilizes machine learning models such as Linear Regression, Support Vector Regression (SVR), and Random Forest to accurately forecast student performance based on historical academic data, study habits, and course preferences. Moreover, it generates personalized course recommendations specific to each student's profile, academic goals, and learning needs. Experimental evaluation demonstrates the effectiveness of the proposed approach in predicting performance and providing relevant course suggestions, which can significantly enhance academic outcomes and student satisfaction.

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student, performance, prediction, recommendation, machine learning, linear regression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The primary focus of the present study is to study the correlation between academic stress and academic achievement of Under Graduate students. The study was conducted by following descriptive survey method, in which a sample of 60 students (30 girls and 30 boys) were selected through equal number stratified random sampling procedure from Govt. Degree College, Sundargarh, Odisha. The tool used in the study for data collection was Academic Stress Scale developed by Rajendran and Kaliappan in 1990. After collecting data, product movement coefficient of correlation was applied to interpret the results. The study disclosed that there is negative correlation between academic stress and academic achievement of Undergraduate students.

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academic stress, academic achievement, undergraduate students

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Creative Commons Attribution 4.0 and The Open Definition

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The present study delves into the notion of cruelty as a basis for divorce in the Hindu Marriage Act and English Law. It first examines the definition, categories, legal provisions, and procedures for pursuing a divorce based on cruelty in each legal system. Next, it presents a comparative analysis that highlights the similarities and differences between the two legal systems. Lastly, the study addresses the impact on society, difficulties in establishing cruelty, potential future implications for legal systems, and recommendations for individuals who are thinking about filing for divorce based on cruelty.

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Creative Commons Attribution 4.0 and The Open Definition

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Cruelty, divorce, Hindu marriage Act, English law, society, Family law

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Creative Commons Attribution 4.0 and The Open Definition

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In the dynamic landscape of retail, the challenge of uncertain inventory decisions poses significant obstacles, leading to suboptimal stocking strategies, missed sales opportunities, and increased operational costs. This approach presents a novel approach to mitigate this challenge by integrating deep learning techniques, specifically convolutional neural networks (CNNs) implemented through Keras, with traditional machine learning algorithms such as Singular Value Decomposition (SVD). Leveraging image data, the CNN model accurately predicts demographic attributes like gender and age from customer images, augmenting the predictive capabilities of traditional methods. By harnessing these insights, retailers can optimize their inventory management strategies to stock items tailored to the preferences of diverse customer segments. The findings suggest that this integrated approach enhances inventory management efficiency, leading to improved customer satisfaction and cost savings. This approach contributes to advancing the state-of-the-art in retail inventory management, offering a promising avenue for retailers to adapt to evolving consumer demands in an increasingly competitive market

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Deep Learning, Convolution neural network(CNN),Inventory optimization, Consumer demands

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Creative Commons Attribution 4.0 and The Open Definition

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The assessment of light motor vehicle (LMV) fitness is crucial for ensuring vehicle safety, reliability, and optimal performance in the automotive industry. In this project, we propose a novel approach using machine learning algorithms to detect and classify LMV fitness levels based on a comprehensive analysis of vehicle data. Our methodology involves extensive data collection from onboard sensors, maintenance records, and driver behavior logs, followed by preprocessing, feature engineering, and model development stages. We explore a range of machine learning algorithms, including traditional methods and deep learning architectures, to build robust models capable of accurately predicting LMV fitness levels [3]. Through rigorous evaluation and validation, our models demonstrate promising performance metrics, with high accuracy, precision, recall, and area under the ROC curve (AUC-ROC). The integration of these models into real-world LMV monitoring systems offers practical benefit for proactive maintenance, safety enhancement, and regulatory compliance. Further research avenues include the integration of IoT devices, enhancement of model interpretability, dynamic model updating, scalability optimization, incorporation of external factors, and validation studies for regulatory compliance. Overall, our project contributes to advancing automotive health monitoring and underscores the importance of leveraging machine learning for LMV fitness detection in the automotive industry

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 Keywords

machine learning, image processing

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Creative Commons Attribution 4.0 and The Open Definition

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As urbanisation accelerates globally, the demand for efficient parking solutions becomes increasingly critical. This research conducts a systematic literature review to comprehensively explore the transformative potential of stack-type multi-level car parking systems and their implications for future urban planning. The study fulfils three primary research objectives: evaluating the efficiency and space utilisation of stack-type systems, analysing their economic viability, and understanding their environmental impact. The results reveal that stack-type parking systems demonstrate superior efficiency metrics, economic viability, and reduced environmental impact compared to traditional structures. The comparative analysis underscores their transformative potential, while acknowledging structural complexities and scalability issues as challenges. The discussion delves into the implications for urban planning, recommendations for policymakers, and avenues for future research, emphasising the importance of public acceptance and smart technology integration. The conclusion highlights the need for continuous exploration, innovation, and interdisciplinary collaboration to successfully integrate stack-type parking solutions into the dynamic tapestry of future urban landscapes.

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REVOLUTIONISING URBAN PARKING

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Network embedding successfully maintains the network structure by assigning network nodes to low dimensional representations. A considerable amount of progress has recently been achieved in the direction of this new paradigm for network research. In this study, we concentrate on classifying, analyzing, and pointing out the future directions for network embedding techniques research. We begin by summarizing the purpose of network embedding. We talk about network embedding and how it relates to traditional graph embedding methods in a cognitive radio context. Following that, we give a thorough overview of a variety of network embedding techniques in a methodical way, including advanced information preserving network embedding techniques, network embedding techniques with side information, and approaches that preserve structure and properties. Additionally, many methods of network embedding assessment as well as certain practical online tools, such as network data sets and software, are explored. In our last section, we cover the foundation for utilizing these network embedding techniques to create a successful system and identify some possible future paths.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Network Embedding , Beyond 5G Internet of Things , Machine learning , 5G

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Demand of higher education increasing day by day and the enrolment of students in higher education becomes top priority in this modern era. NPE 2020 has also given priority to quality higher education. Mainly higher education focuses to quality research and better education. Due to limited books and materials many students are facing problem to access better education. Keeping in view this problem, Open Educational Resources (OER) was introduced This OER reduces so many problems of students like high tuition costs, high price of books etc. This study was conducted on the perception of Teachers of Higher Education Institutions towards OERs. The objective of this study is perception of higher education teachers towards availability and use of OER in teaching learning processes. This study employed descriptive survey design under quantitative method and the investigator selected random sampling technique to collect sample using questionnaire through online Google form. Data analysis made through percentage method. The findings of this study reveals around 80% of higher education teachers strongly agreed of being aware of OERs and they are able to use it in their classes and also they are agreed of the importance of OERs in present classroom situations to improve the quality in education. Out of the total teachers 35% have disagreed on the facilities and scope provided by their institute to use OERs in teaching learning system.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Open Educational Resources, Perception, Copyright, Creative Commons, Technology, ICT.

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Creative Commons Attribution 4.0 and The Open Definition