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This paper tries to analyze the spread and rising number of COVID-19 cases from a system dynamic point of view which may help in taking measures for decisions of policy about lock down in India. Here a model based on a causal diagram is developed. The papers talk about the need for control of unnecessary information-not any way related to treatment, disseminated to the public causing fear but there is a need to educate people in the proper way. This work will help the policy makers to act in the proper way in the coming third wave and new strains of virus handling situations. [ABSTRACT FROM AUTHOR]

The Pandemic (Covid-19) deeply impacted the Hospitality and Tourism industry across the country. Its effect disrupted human lives and pushed the country to an economic slowdown. This Pandemic brought fear of travel and dining out, on every person be it a domestic or an international traveller. Lockdowns and intra state travel ban, and the fear of being quarantined took its toll on Hospitality and Tourism Industry. In This paper researchers are making an effort to find out the extent to which this deadly Virus (COVID-19) has impacted the Travel and Tourism industry in India and also explains how our tourism sector shall cope with this extraordinary circumstance, and establish Management and Recovery strategies. Pre COVID-19, Hotels and Restaurants were relying on various techniques and marketing skills for selling Food and Beverage, but post COVID-19 the entire scenario changed and those skills went redundant. Reinventing and innovative use of technology is the call of the hour to breathe life into the Hospitality and Tourism Industry. This research paper recommends that we need to be proactive in planning as per the guests' perceptions of the hygiene and cleanliness in hotels as these will be the new normal and deciding factors in the Guests mind to visit Hospitality establishments. Additionally, a detailed study is required to adopt necessary healthcare facilities for hotel guests and employees. [ABSTRACT FROM AUTHOR]

In this paper, study and modeling of a one-phase H-bridge forty-one level inverter are done. The focal drawback for cascaded multilevel inverter is its complicated switching scheme. To bring the Total Harmonics Distortion (THD) of the output waveforms to a minimum value, it is needed to enlarge the output voltage level and for getting the large output voltage level the switching devices should be increased. With increase in switching devices the switching scheme becomes complex. Also, such arrangement subsequently increases the installation charge, makes the inverter bulky and increases the voltage losses at the load terminals. In this paper a new asymmetrical cascaded multilevel inverter concept is offered with a limited count of switching devices and DC sources. The 41-level inverter comprises of few number of different level DC voltage sources. MATLAB/Simulink tool is used to run the model and show the desired results of waveforms with FFT analysis. [ABSTRACT FROM AUTHOR]

This paper describes about various paradigms of Edge Computing (EC) for applications of Internet of Things (IoT), as the data generated by IoT is huge in amount thus the need of Big Data and Cloud was identified. Cloud Computing (CC) started to face the problem of latency, higher bandwidth, response time, security etc. and this was the moment where it was realized that EC can be a better alternative. Limitations caused due to CC were recovered by EC. This paper discusses about four important platforms of EC that is Cloudlet, Fog Computing, Mobile Edge Computing (MEC) and FemtoCloud. The working and applications are also described in the proposed work. Comparison of these four platforms is presented and important conclusions are drawn to identify the paradigm which can work on diverse platforms as well as provide efficient nodal communication. [ABSTRACT FROM AUTHOR]

Energy consumption & Environment crisis is among the biggest problem in today's world and among the biggest agenda on world forum today to overcome this problem the world is increasing its focus towards renewable source of energy. The increased use of carbon free (solar) has broadened the horizon of study into improving the productivity of solar pv fabrication technology. but still till the date the capability is not up to the mark. It is about 25%-30% today. in order to maximise their working productivity and to reduce the per unit costs in comparison to There is a need for an alternative to conventional power. energy saving and vigorous controller. In the survey paper comparative analysis of different combination of 3 converter and 3 controller (buck-boost, cuk, boost converter) for various loads has been done. In this survey paper performance of combination of converters as well as controllers is being analysed to find that which combination of controller and converter have better efficiency. [ABSTRACT FROM AUTHOR]

Data mining is a kind of data analysis technique used to analyse previously-stored crime data from various resources to identify trends in kinds and find out various patterns of crime. Governments of many countries have used this technique in recent years. The use of data mining procedure includes the examination and evaluation at the same time large chunks of pre-existing data and to the prediction of new information, which could be helpful for various organizations, whether public or private. In this process, we can easily extract new information and predict other information by using existing datasets. Multiple analytical methods and approaches have been used to predict data via data mining techniques. However, there are only a few methods that proved helpful in the criminological field. In addition, we can use data mining techniques to solve crimes swiftly and efficiently, and also it can be applied for the automatic notification of crimes. The problem is that there are many data mining techniques. So, for that reason, we have to choose the most efficient technique which will increase the efficiency of crime detection and prove the most suitable. This paper audits a large number of different information mining procedures, particularly applications used to address violations. This paper likewise illuminates different difficulties and Exploration holes in wrongdoing information mining. Likewise, the paper will likewise assist fledglings who with needing to explore wrongdoing information mining to get an understanding of the point for finding different examples and patterns in wrongdoing addressing that could be utilized properly in each circumstance. [ABSTRACT FROM AUTHOR]

Evaluating the performance of a predictive model trained on an imbalanced class distribution has encountered significant challenges as most of the widely used metrics are designed considering balanced class distribution datasets. This paper presents a study on four different biasing of target class variables in train set: (50% majority class, 50% minority class), (60% majority class, 40% minority class), (70% majority class, 30% minority class), (80% majority class, 20% minority class), and focuses on choosing the right metrics out of accuracy, precision, recall, f1 score and AUC score for a binary classification problem with a skewed class distribution. The algorithms considered are Logistic Regression, K Nearest Neighbors, Naïve Bayes. Analysis of all four biasing cases, five evaluation metrics for three algorithms have been presented in this paper. [ABSTRACT FROM AUTHOR]

Distinguishing proof of plants is a vital field in the world's environment to keep a solid atmosphere. Sure, of these plants have critical restorative properties. These days of discovering a plant isn't simple by taking a gander at its actual properties. This paper gives a scholastic data set of writing between the span of 2015–2020. It has been seen that the new age of coevolutionary neural networks (CNNs) in the space of image recognition has delivered noteworthy execution. In this paper, procedures are examined the ideas of Deep learning and different leaf recognition techniques. [ABSTRACT FROM AUTHOR]

As world has been growing dynamically paradigms of teaching has undergone drastic changes. Relationship of a teacher-student has changed to interactive classroom study which was used to be one-way communication during ancient times. User friendly and online data libraries have replaced repositories of books. Nowadays learning is available 24 hours, hazel free and easily available for students. This paper gives information about recent online system for learning, which is analyzed for the regular learner from northern part of India that cover Himachal Pradesh, Haryana, Jammu and Kashmir, Punjab along with union territories of Chandigarh and Delhi using online learning portal (OLLP) system. In this paper effective implementation of OLLP system could be analyzed which giving focuses on conduct of online courses to check qualities of OLLP system, along with in ensuring, subscribers employability and service quality. Hypothesis has been developed to explore the significance of age, level of education and place of residence with various factors involving courses through online education portals and data collected through questionnaire is analyzed. [ABSTRACT FROM AUTHOR]

The adoption of technology by law enforcement agencies in the United States has changed the way they operate. Over 70% of agencies use some type of technology, like as predictive policing, license plate scanners, in-car video, and/or social media, according to a 2011 survey of more than seventy agencies in the United States, ranging in size from 10 to 13,088 officers (with an average of 949). Body-worn cameras and drones have been employed by law enforcement officers who have observed the advancement of technology over the last two decades. All of these advancements have had a significant impact on policing techniques. This Particular paper will explore how the U.S Law Enforcement agencies can successfully incorporate Artificial Intelligence by keeping an eye on the limitations and challenges of implementing (AI). One of the major challenges that the agencies going to face is a dearth of first-hand information about Artificial Intelligence in the current setting, particularly in the U.S and its legal consideration. This paper will examine how efficiently the police force of Dubai has implemented AI systems which different foreign agencies. The paper also examines how the police of Dubai create a model framework that can be used by the Law Enforcement agencies in the U.S to incorporate a culture of using advanced AI technologies into their daily practices. [ABSTRACT FROM AUTHOR]

Through this paper, we examine the impact of telemedicine among patients and healthcare professionals during the second wave of COVID-19 pandemic in India. Using the electronic and communication technologies, telemedicine is used to transfer the information from one place to another place. The foremost utility peculiar to telemedicine is to render assistance in medical aid by referring to Information and Communication Technology (ICT). It is not safe to visit a hospital physically even in extreme emergency during a second wave of pandemic. Henceforth, telemedicine plays an important role in this situation. Use of telemedicine during a pandemic helps to improve the quality of health services and improve access to the various medicinal facilities to the people that are not easily available. We have been told the importance of using telehealth to provide us healthcare in the present scenario, specifically as a means of reducing the risk of cross contamination caused by contact. Like other countries, India also began providing digital healthcare services as means of telemedicine during the outbreak of the second wave of COVID-19 pandemic. With the increase in the surge of the second wave of COVID-19 pandemic, many telemedicine service providers in India have also expanded their service operations for the general public. In this paper, a survey is being presented based on the e-sanjeevani data regarding the continuous increase of the impact of telemedicine during the spread of the second wave of COVID-19. After performing the latest literature surveys on many papers, we analyzed the consequences of telemedicine since the inception of first wave of COVID-19 pandemic till the surge of second wave. After discussions and analysis, we conclude that the use of telemedicine continuously expands during the second wave of COVID-19. In spite of numerous issues and challenges in the domain of a telemedicine sector in India, continuous improvements have been made for its survival and existence even in the rural, background and isolated areas. [ABSTRACT FROM AUTHOR]

Mobile Health (Mhealth) apps services for health behavior rehabilitation have become a demand in healthcare and medical segments. However, Mhealth apps' poor adoption and high rate of discontinuation may occur due to risk perception of those apps. This review paper introduced perceived risks of Mhealth apps and proposed the role of the organizational facilitators that could tackle or reduce the impact of risk perception among consumers while using Mhealth apps. The review paper used a literature review from 4 databases and included 16 articles to analyse diverse risks types that may consumers perceived in the initial utilization stage for Mhealth apps. Despite few studies have deliberated the organizational facilitators (Endorsement, Awareness, loyalty, cost, facilitating condition, regulation, and data protection), there is a need to explore those facilitators in different Mhealth apps and population composition. [ABSTRACT FROM AUTHOR]

Over the years corporate governance has become a topic of global concern due to several corporate failures. This has drawn the attention of researchers, investors and regulatory institutions. Besides, the most important mechanism of corporate governance is board of director's diversity. The objective of this paper is to review the literature on how board diversity impacts dividend policy. The findings from this paper will provide evidence on whether board diversity influences the dividend policy. Board diversity entails an all-inclusive corporate board comprising a fair representation of all genders, minority groups and age brackets. Group diversity is known to result in constructive rational decisions. Other relevant matters on the impact of board gender diversity will also be discussed. [ABSTRACT FROM AUTHOR]

Competency has been defined in many different ways from different perspectives since its establishment. It can be referred to organizationally or individually. This research area has increasingly attracted researchers during the past few years. Currently, reviews in the literature on Quantity Surveyors (QS) competency are lacking. Therefore, considering the contribution by recent studies, a comprehensive review is attempted. This paper aims to provide an in-depth review of the literature on QS competency from both local and global perspectives. Within this study, the authors have reviewed the competency literature in a way that would help other researchers, academicians and professional bodies to have a closer look at the growth and development of QS competency. The authors examined various research papers, and on this basis, propose new competency elements for QS profession in the subsequent phase of the research process. In addition, certain gaps that would provide hints for further research in QS competency were identified. [ABSTRACT FROM AUTHOR]

The use and application of microcontrollers in control involving life seen increasingly widely used. The used of this microcontroller is to facilitate and assist humans in carrying out activities that involve periodic activities. However there are various types of microcontrollers in the field of technology and engineering, among them are Micro bit, Arduino, Programmable Logic Controller (PLC), Raspberry Pi and those related to micro processing. However, each microcontroller has its own unique operation in running the program to be developed. A microcontroller (MCU for microcontroller unit) is a small computer on a single metal-oxide-semiconductor (MOS) integrated circuit (IC) chip. A microcontroller contains one or more CPUs (processor cores) along with memory and programmable input/output peripherals. Program memory in the form of ferroelectric RAM, NOR flash or OTP ROM is also often included on chip, as well as a small amount of RAM. Therefore, the use of this microcontroller is very popular from day to day because it facilitates control activities in carrying out activities of daily living. The paper discusses the uniqueness of the structure, application and operation of the microcontroller on the market and used in industry, education and other fields. It is hoped that this research paper can help researchers, educators and those interested in exploring microcontrollers and it is hoped that the research paper can be referred to in improving and applying knowledge of microcontrollers understood. [ABSTRACT FROM AUTHOR]

This paper reviews the importance of graph analytics in the supply chain field from a centrality measurement perspective. In graph analytics, centrality measurement usage is vital to find the most critical nodes in a graph. The centrality helps identify the essential factors that influence suppliers or companies' management for relative measure within a networked economy. Four main issues are affecting the supply chain were addressed based on the three types of supply chain models (Traditional Supply Chain, Modern Supply Chain and e-Supply Chain), which have implemented nowadays. Several centrality measurements were indicated in this paper, referring to the previous studies that had successfully realized the supply chain models applications. The impact of centrality measurements brings a significant improvement in supplier- customer relationship, cost effectiveness, risk management and dynamic and fast-changing time-varying market conditions. [ABSTRACT FROM AUTHOR]

The capability of the Internet of Things (IoT) to electronically meter, path and monitor objects in the physical world has encouraged a flow of innovation and interest from many industries. It's probable to driving, chaotic changes across many sector offerings a myriad of potential services and applications. Smart home service, one of the symbolic developing technologies in the IoT era, has changed house equipment into being more intelligent, remote controllable, and interconnected. This paper is division of current the author's research on the adoption of IoT application for home building in Malaysia. The data and information presented in this paper were gathered from the reviews of the available relevant literature related to IoT and smart home in Malaysia. This paper addresses the major concern and challenges in IoT and smart home in Malaysia. Based on the analysis, it was found that three main challenges cited in the literature are perception of usefulness, confidentiality and privacy of consumer data, and absence of enterprise IoT applications in the country. The study is important in order to give preface idea and find the issues of current IoT and smart home technology faced amongst the community. As for Iot and smart home technology improvement in the near future, suggested tackling the current issues on home online education and working from home (WFH) especially because of the problematic pandemic Covid-19 worldwide. [ABSTRACT FROM AUTHOR]

Fraud became a global occurrence and a major source of worry. It exists across various nations and impacts most sorts of firms regardless of company magnitude revenue or business. The fundamental goal of this paper is to give a profound overview of fraudulent activities literature with the purpose of "why" fraud happens and "how" to resist it. In addition, it includes a complete overview of fraud prevention techniques. From this point, this paper focus on the role of forensic accounting and its influence on the efficient deter against fraud also concentrates on a trouble side which faces forensic accounting. As well, internal control was considered to be the greater side for formulating fraud prevention processes and procedures inside of business enterprise; therefore, any weakness of internal control leads to not control of fraud. As of this point, this review offers proof on fraud prevention, forensic accounting, and the competencies and technique of forensic accounting, and also highlights several grounds for the differing viewpoints on fraud prevention amongst experts and lawmakers. Regarding financial institutions, Researchers explain to the topic about how forensic accounting experts have a positive influence on the organization. In addition, the paper provides a broad field and also a variety of controversial subjects for upcoming forensic accounting literature review. The purpose of this review is to spark discussion and a further paper on the subject matters mentioned. Furthermore, the current paper aims to identify researching gaps in the current literature and investigate time ahead of research areas. [ABSTRACT FROM AUTHOR]

Research efforts at the items development of Goal Setting Theory with gamification have received less attention among scholars especially in mobile fitness application context. The possible reason for this deficiency is the lack of measurement analysis tool and ideas of Goal Setting Theory and gamification from mobile fitness application context. Therefore, the aim of this paper was to develop a scale of measuring Goal Setting Theory and Gamification items based on its conceptualization. Data collected from a survey of fitness centres that used the mobile fitness application, from which 349 respondents filled out questionnaires for this study. The analysed data using the structural equation model (SEM) and, specifically, the partial least square structural equation modelling for the measurement items. The results show that 30-items of this paper have passed the measurement items test requirement used for structural model testing. The research is expected to extends the knowledge frontier of Goal Setting Theory and gamification items and provides a tool for further investigation for academics and fitness practitioner. [ABSTRACT FROM AUTHOR]

Recently, many industries undergo supply chain disruptions due to the lack of consideration on resilience during supplier selection. As consequences, supply chains fail to adapt to the risks and recover from the damage within a short period. The literature on resilient supplier selection shows that there is no review paper discussing on resilience criteria and resilient supplier selection methods in the past decade. The objective of this paper is to provide a review on resilience criteria and resilient supplier selection methods. To achieve the objective, previous papers related to resilience were studied and analyzed. Then, a summary on resilient criteria and resilient suppler selection methods was presented clearly in the paper as a reference for future research. Furthermore, other suitable methods were also proposed for resilient supplier selection. [ABSTRACT FROM AUTHOR]

As the world is evolving and technically advancing, people need a lot of gadgets to be interconnected for the smooth functioning of the system and every gadget requires a certain amount of energy. Now with so many gadgets being used energy consumption has become a major threat to the world. Some devices take a lot of time to charge, and sometimes users even forget to turn off the charging port which leads to more energy loss and thus more carbon emissions. The proposed solution is to build a device that not only charges the devices but also stores the energy. The port auto-cuts the charging when a device is fully charged and stores the extra energy. In this paper, we have gone through different papers and have analyzed the algorithm they are using and their disadvantages. This survey contains a wide range of algorithms used for energy saving by researchers so as to learn more about green IoT and energy saving. Researchers can use this survey's insightful results as a guide to developing novel systems for energy storage. [ABSTRACT FROM AUTHOR]

In electric vehicles with lithium-ion batteries (LIB), its working temperature is an important parameter that limits the lithium-ion batteries' performance, charging-discharging capacity, and lifespan. Much research has been carried out to keep the operating temperature range from 15◦C to 40◦C by a battery thermal management system (BTMS). Various BTMS methods are available: air-cooled, liquid-cooled, Phase Change Material based, heat pipe-based, and refrigeration cooling. Among these methods, liquid cooled BTMS is an efficient way that provides greater thermal performance and cooling efficiency, which helps in improving battery efficiency. The following review concisely deals with liquid coolant and what different effects are observed when Nano particles with various combinations of base fluid are used in battery management system. Here such combinations are analyzed. This paper provides information about the changes in the system according to changes made in mixture of base fluids and Nano fluids. Considering future benefits from the data obtained from other research papers, this review paper has all the information related to it. [ABSTRACT FROM AUTHOR]

The research on autonomous vehicles has increased with the flourishing of the smart city agenda and improvement in commute-related aspects. This contributes to expanding the scope of research for the detection of pedestrians, cyclists, nearby cars, and other objects on the road. This paper presents a novel approach to the recognition of stop and slow-down signals. The signals are detected based on cyclists, bikers and pedestrians crossing the street. The approach of this paper is to detect these types of signals, which will support autonomous vehicles in avoiding accidents and ensure the safety of people travelling around an autonomous car. The dataset used in this project is Joint Attention in Autonomous Driving (JAAD) and Cyclist Arm Signal Recognition (CASR). The SIFT is explored for key point feature detection and extraction. Accuracy of several classifiers such as Decision Trees, Random Forests, SVM, KNN and GNB has been obtained with the highest accuracy of 92.83% given by Random Forest. [ABSTRACT FROM AUTHOR]

College life is an exciting experience for students, but it can also be overwhelming for new students who face numerous challenges. Freshie is a mobile application-based platform that aims to help new college students in managing their academic lives. The objective of this research paper is to explore the features and benefits of Freshie and investigate its impact on new college students' academic success. The paper will discuss the challenges new college students face, including locating important places on campus, managing their time, and keeping track of events and activities. It will also outline the features of Freshie, such as event updates, timetable management, information about student societies, and more, that are designed to address these challenges. To assess the effectiveness of Freshie, a survey will be conducted among a sample of new college students to collect data on their usage and perception of the app. The data will be analyzed using statistical methods to determine the impact of Freshie on academic success. The research paper concludes that Freshie is a promising tool that can improve the academic success of new college students by providing easy access to important information and helping them manage their time effectively. However, some limitations and challenges in the implementation of the app need to be addressed to ensure its effectiveness. Overall, Freshie has the potential to make college life easier, more enjoyable, and more productive for new students. [ABSTRACT FROM AUTHOR]

Face Emotion Detection Music Player is an innovative idea that combines computer vision and machine learning techniques to create a unique and interactive music player. This Research Paper studies the uses of Convolutional Neural Networks (CNN) to detect and analyze facial emotions in real-time and dynamically create playlists based on detected emotions. The music player is designed to record facial expressions using a webcam or other suitable camera. To reliably identify facial expressions including happiness, sorrow, rage, surprise, and more, a CNN model is trained on a sizable collection of face images. The trained model demonstrated an astounding 74.46% accuracy in identifying emotions when combined with music player software running on a PC or other suitable device. The CNN model analyses the photos to determine the user's emotional state as they interact with the music player in real-time, as captured by the camera. Based on the detected emotions, the player automatically selects and plays songs from a predefined music collection that matches the user's emotional state. For example, if the user looks happy, the player can play happy and energetic songs, while if the user looks angry, it can play more calming and soothing music. Face Detection Music Player offers a personalized and dynamic music listening experience as the music selection is constantly updated according to the user's emotions. This research paper illustrates how computer vision and machine learning techniques may be used to produce interactive programs that can instantly adjust to the moods and preferences of their users. It has uses in user experience research, entertainment, and mental health, among others. [ABSTRACT FROM AUTHOR]

There are various models out there, both theoretical and experimental, which are used to predict the fatigue crack growth in metals. Machine learning based computational models have been recently developed to predict such crack growth rate in a more comprehensive manner. This paper presents a supervised machine learning model with a better accuracy than the existing machine learning models. The experimental data obtained from the fatigue test carried out on CT specimen of material SA516Gr70 is used to test and train the model. The machine learning model XGBoost, which is implemented in this paper, is not only more accurate but also less likely to over fit when exposed to unseen data. Three alternative algorithms are investigated and by the process of elimination, best one is chosen. The paper shows the results received from some of those models, which were important in order to select the best one. The metrics used to filter and tune the model's performance are R2 score and mean squared error. The procedure for finding the optimal model and its results have been discussed. [ABSTRACT FROM AUTHOR]

Over the past few years, the advancement in technology has led to the invention of Nanobots. The use of nanobots in the medical field has seen tremendous growth due to the various advantages it holds. In the medical field, nanobots seem to provide a better solution as compared to the traditional medical techniques which were followed over the past decades. The goal of this review paper is to explore the possible inculcation of nanotechnology, in the form of nanobots, in the medical sector as an integral part of numerous applications and the feasibility of its manufacturing along with future aspects. Nanobots are accompanied with several challenges like nanoscale manufacturing, high initial capital and so on. Since the onset of research into the field of nanotechnology back in the 1960s, numerous types of research work and sources are available through which theoretical as well as practical approach to the implementation of nanobots seems to be feasible in the near future. The review paper also highlights the advantages and disadvantages of using nanobots in the medical field. This review paper will address the need of researchers in the medical field giving a general overview of nanobots along with their applications and prove to be a source of further insight in this blooming field. [ABSTRACT FROM AUTHOR]

The paper proposes a novel approach for recognizing and classifying gym exercises using human pose detection with Mediapipe and LSTM, followed by matching the accuracy of the exercises using the Hungarian algorithm and cosine similarity. The proposed approach involves the use of a combination of cutting-edge technologies, including computer vision and deep learning, to recognize and classify a range of gym exercises accurately and efficiently. This study presents several advantages of this approach, including the ability to leverage temporal information, robustness to variations in lighting, camera angle, and occlusions, and the ability to handle a wide variety of gym exercises. Experimental results demonstrate that the proposed approach achieves high accuracy and outperforms existing methods for gym exercise recognition and classification. The paper also compares the proposed approach with existing techniques, highlighting its strengths and cost-effectiveness. It concludes by outlining the methodology, including dataset collection and pre-processing, landmark extraction, LSTM model training, exercise classification, and similarity analysis. Finally, the paper discusses potential future research areas in this field. [ABSTRACT FROM AUTHOR]

The detection of chest diseases from X-ray images is a crucial aspect of medical diagnostics, playing a vital role in the early identification and treatment of respiratory conditions. This review paper gives a general overview of how machine learning algorithms are used to identify chest diseases from X-ray pictures. It emphasizes the importance of accurate and timely diagnosis of chest diseases, while acknowledging the challenges faced by conventional diagnostic methods. The review highlights the potential of machine learning as a promising approach to enhance diagnostic accuracy and efficiency in this field. It explores the utilization of both handcrafted features and deep learning-based approaches for extracting informative features from chest X-rays. Furthermore, it discusses the adoption of various machine learning algorithms, including support vector machines, random forests, and convolutional neural networks, for effective detection of chest diseases. The review paper also recognizes the significance of training and validation strategies in ensuring the robust development of models. Additionally, it addresses the potential impact of the proposed methodology on chest disease detection and patient outcomes. The review paper discusses challenges and limitations associated with this approach, such as data availability, interpretability, and ethical considerations. In summary, this extensive analysis strives to make a valuable contribution to the field by offering insights into cutting-edge machine learning techniques, recognizing existing challenges, and proposing potential avenues for future research. [ABSTRACT FROM AUTHOR]

This state-of-the-art review paper provides a comprehensive overview of meta-learning techniques for learning to learn in machine learning. Meta-learning called "learning to learn," is an approach that enables models to learn from new tasks learning quickly and efficiently, based on prior knowledge and experience. The paper discusses various meta-learning techniques, such as model-based meta-learning, metric-based meta-learning, optimization-based meta-learning, and memory-based meta-learning. The review also covers the applications of meta-learning in different domains, including natural language processing, computer vision, and reinforcement learning. Additionally, the paper discusses the benchmark datasets, challenges along with the future directions of meta-learning research, highlighting the need for developing more efficient and scalable meta-learning algorithms. Moreover, the proposed Meta-Learn framework incorporates a hierarchical structure to facilitate knowledge transfer across multiple levels of abstraction, and it also includes a memory component that enables the system to store and reuse previous experiences. Overall, this review aims to provide a comprehensive overview of Meta-Learning techniques for learning to learn in Machine Learning and proposes a novel Meta-Learn framework that could potentially enhance the performance and scalability of Meta-Learning algorithms. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak impacted drastically to education and most of educational institutions started preferring online education for students. However, after the settlement of the pandemic there is uncertainty among people about whether they should prefer online education for furthermore or start in offline mode to make it more interactive, so this paper is about an analysis of people's sentiments and emotions through Tweets about COVID-19 Education. This paper aims to study the reaction of people around the world toward online education during COVID-19. This study is conducted on the basis of the responses of students, teachers, parents, college professors, etc. We started with labeling the data into three sentiments namely positive, neutral, and negative and for validation then we used Machine learning (ML) classifiers namely, Logistic regression, Decision tree, Random Forest, Multilayer Perceptron (MLP), Naïve Bayes, Support vector machine (SVM), K-nearest neighbors (KNN), and XG-Boost. Then we performed emotion detection by considering 5 emotions namely happy, surprise, sad, fear, and angry and for validation we used ML classifiers. After applying all these ML approaches, the XG Boost ML classifier achieved the highest accuracy of 94% in classifying the tweets as positive, neutral, or negative, and 96% accuracy in classifying the tweets as happy, surprised, sad, fearful, or angry. [ABSTRACT FROM AUTHOR]

As a result of the advancement of technology, Indonesia's focus has shifted to the enhancement and simplification of everyday transactions. This is highly common in the widespread use of e-wallets as a payment method for digital transactions involving multiple verification methods, including PIN, Password, Face Recognition and others. This study was conducted by distributing questionnaires to 385 respondents from generation Z in Indonesia who utilized face recognition as a security verification method for digital transactions. The purpose of this paper is to demonstrate the security and efficacy of facial recognition in digital wallet payment verification applications as experienced by users. With the use of the TAM model's analysis, it is proved that all the variables used are significantly related, allowing one to conclude that the safety and efficacy that are possessed are adequate. This paper also supports the growth of trust factors and reasonings for the usage of face recognition in digital transaction self-verification. [ABSTRACT FROM AUTHOR]

This study includes a brief survey of the literature on silver nanoparticles synthesized by green methods. Where the green chemistry method was used to prepare silver nanoparticles, and the survey showed that different types of plants are promising for environmentally friendly treatment methods, properties, and possible uses as alternatives to silver nanoparticles. The paper lists the basic classes of nanomaterials and the advantages of the synthesis of nanoparticles extracted from fungi and bacteria. More details on the specific properties and bandgap energies of the nanomaterials can be found in the manuscript. The energy bandgap of AgNPs was formulated as a function of shape and size. The modeling theory was founded on the aggregation energy of Ag nanoparticles with respect to the crystal structure; We find that the energy bandgap of AgNPs depends on the particle shape and size. According to this model, as the particle size of nanostructured materials decreases, the energy gap is found to increase. The energy gap increases according to the results of this paper. This paper is based on various observations and supports the validity of Ag nanoparticles. [ABSTRACT FROM AUTHOR]

In this paper, In this paper, the photovoltaic characteristics of an N749-TiO2 heterojunction solar cell has been studied and calculated based on a quantum model for electron transfer from N749 black dye to TiO2. For this purpose, the energy levels of the heterojunction N749/ TiO2. device surrounded by ethanol solvent as polar media are assumed to be continuum levels. The photovoltaic characteristics of the N749/ TiO2. device is calculated at standard conditions; i.e., T=300k and 100 mW/cm2 irradiation. Current-voltage (J-V) characteristics of the device were calculated in two carrier concentrations at room temperature The photovoltaic fill factor and efficiency parameters of the device were found to be 0.281 and 2.293 %for carrier concentration 2.5 × 10 18 1 c m 3 compared with 0.275 and 2.293% for carrier concentration 1.5 × 10 18 1 c m 3 respectively. The higher efficiency of the N749/ TiO2. device at concentration 2.5 led to suggest use application of N749-TiO2., low-cost, and high-performance solar cells. [ABSTRACT FROM AUTHOR]

The fuzziness approach is useful when finding a solution to a programming problem with some element of uncertainty. Using standard programming techniques, an optimal value for coefficients may be difficult to compute. The quality of fuzziness makes the programming method especially useful in situations where the coefficients are fuzzy-shaped representations of real-world occurrences and cannot be determined accurately. There have been many attempts in recent years to solve the problem of fractional programming. But not be bounded that many papers or studies have been written about the fuzzy quadratic fractional programming problem. This paper first introduces a development method for solving quadratic fractional programming (QFP) problems depending on separating the quadratic objective function. Secondly, to solve a fully fuzzy quadratic fractional programming (FFQFP) problem in which all the variables and parameters of the problem are decagonal fuzzy numbers, we proposed a new nonlinear membership function of decagonal fuzzy numbers with a new ranking function technique to obtain the optimal fuzzy solution to the (FFQFP) problem as well as, development of the algorithm simplex method, in which the new data of tableau are made available with both to help of the new ranking function and the arithmetic's decagonal operations to find the optimal decagonal fuzzy solution. Finally, the applied part of this paper includes an example that shows the steps to finding a fuzzy optimal solution to the presented problem. [ABSTRACT FROM AUTHOR]

The paper considers a homogeneous isotropic Timoshenko beam of finite length. Hinged support conditions are used as boundary conditions. The initial conditions are assumed to be zero. At the initial moment of time, an arbitrary non-stationary distributed load is applied to the beam. At the right end, a sensor (sensors) is installed, which, in the course of the corresponding experiment, take readings of the beam deflection at points. The methodology for solving the direct problem is based on the principle of superposition, in which displacements and contact stresses are connected by means of integral operators in the space variable and time. At the same time, the cores of the latter are the so-called influence functions. These functions are fundamental solutions to systems of differential equations of motion of the beam under study. Their construction is a separate task. The influence functions are found using the Laplace transform in time and expansions in Fourier series in terms of the system of eigenfunctions. In the inverse problem, it is assumed that the dependence of the load on time is known; it is required to restore the law of its distribution over the beam. As a result, the task of identifying a non-stationary load is reduced to solving one integral equation of the Voltaire type, which is incorrect for J. Hadamaru [1]. In this paper, the problem in solving the integral equation is eliminated using numerical methods together with regularization according to Tikhonov [2], [3]. The results of calculations obtained in the work testify to the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

Two renovation plasters with blended binder based are presented in this paper. The porosity of plaster was increased by the application of expanded perlite. This lightweight aggregate was used alone as well as in combination with ordinary silica sand. Binder of plaster composed also of two kinds, pure lime were supplied by ceramic powder. This pozzolanic material led to improvement of mechanical properties and therefore should compensate for their lowering caused by plaster lightening. Physical properties such as basic physical, mechanical and durability characteristics were determined, and the results are discussed in this paper. The plaster with lightweight aggregate reached desired high porosity and appropriate water transport characteristics to be applicable in the field of building renovation, while the combination of silica sand with lightweight aggregate showed the water absorption coefficient slightly lower than the requirements of the standard. [ABSTRACT FROM AUTHOR]

According to Indonesia's National Guidelines on Green Buildings (Kemen PUPR No,21,2021) called Penilaian Kinerja Bangunan Gedung Hijau (BGH), green buildings are mandatory for new and existing buildings. As environmental concerns grow, the Government uses these ratings to control energy consumption. A government initiative aims to increase demand for environmentally friendly buildings. This paper evaluates BGH's green building rating system for project certification in two Indonesian cities, Jakarta and Padang Paser Utara. Jakarta is the capital of Indonesia, the largest and one of the most populous urban city in Indonesia. Moreover, the new Indonesia capital city, Nusantara, will be built in Penajam Paser Utara, East Kalimantan. Using the results of this research, recommendations and suggestions can be given related to the design of green buildings both in Jakarta and Penajam Paser Utara. Evaluations will be conducted on simple residential buildings. The results of these studies indicate that designers and architects may have difficulty incorporating this rating systems into their designs. An evaluation of BGH ratings and sustainability analysis can be performed with building information modeling and a conceptual framework is presented toward the end of this paper. A rating system's success depends heavily on discussion among all stakeholders, including architects, engineers, environmentalists, governments, and communities. Indonesian experts in the building sector should take part in and contribute to this project. [ABSTRACT FROM AUTHOR]

Increasing consumer attention to environmental damage especially for food packaging has intrigued researchers to explore bio-based active packaging. Lignin is a polyphenol compound that is the potential to be used as an antimicrobial agent. Numerous availability of lignin particularly as waste from pulp and paper factory makes it promising as bio-based antimicrobial for food packaging. Therefore, this research aims to utilize lignin from Acacia mangium pulp mill waste in the form of lignin biofilms and its activity as an antimicrobial agent in food packaging by combining it with starch and Poly(Lactic Acid) (PLA) and forming it into biofilms for paper coating materials. The isolated lignin was tested for physical characteristics, such as moisture content, ash content, FTIR, DSC, TGA, and antimicrobial activity. Lignin was then applied to biofilms using the method of dissolution and rheomix. This work showed that the moisture content of lignin isolates is 10.28%, and the ash content is about 1.06%. Meanwhile, thermal degradation of lignin isolate occurred at a temperature of 340 °C, and Tg2 occurs at a temperature of 166 °C. The characteristic of lignin functional groups has phenolic-siringyl, guaiacyl, and ether compounds. This research also showed that lignin isolates from black liquor from pulp mills had antimicrobial activities. Isolated lignin with ethanol-water as solvent showed optimum antibacterial activities at a concentration of 0.1 g/ml lignin with inhibition zones of 0.6 cm against Escherichia coli, 0.7 cm against Salmonella typhi, and 0.35 cm against Streptococcus aureus. The best antimicrobial activity of starch/lignin biofilm was obtained at a concentration of 1.5% lignin with an inhibition wne of 0.63 cm against S.typhi, and in starch/PLA//lignin biofilms was obtained at 2% lignin with an inhibition zone of 0.3 cm and 0.6 cm against E.coli and S.typhi. [ABSTRACT FROM AUTHOR]

An accurate analytical model of the physical assembled structure is predominantly importance for engineers and designers to be used in predicting the dynamic behaviour of the structure. Powerful tools such as finite element analysis (FEA) and experimental modal analysis (EMA) can be used to determine the dynamic behaviour of the assembled structure. The assembled structure such as automotive structure is normally joined by a number of jointing types such as spot welds, bolts, and adhesive. However due to advancement of the jointing method, the laser jointing method have been significantly used in the automotive industries. However, it is challenging and cumbersome to accurately model a structure that are assembled by a combination of complex types of joints such as laser stitch welds. This is because stitch welds have been discovered as joining method that tends to present the local effect such as structure geometrical irregularities, heat affected zone (HAZ) on the welded areas and also the residual stress that occurs from the laser welding process. In addition, it is challenging to only rely on the prediction of the dynamic behaviour using FE method because predicted results are often found inconsistent with the experimental data. The inconsistencies of the results due to invalid assumptions of laser stitch welds are the significant motivation to the main goal of this paper by investigating the accuracy of the finite element model of the laser stitch welded structure. In this paper, the prediction of the dynamic behaviour of the structure are merely to address the local effects due to the laser stitch welds such as geometrical irregularities, HAZ and residual stress that influence the initial prediction of the laser stitch welded structure by producing highly accurate prediction model as close to experimental data. The inclusion of the local effects to the initial FE model are performed in the sensitivity analysis to identify the most sensitive parameters of the laser stitch welded structure. The FE model updating method was employed with corresponding to the measured result for reconciliation purpose. The results revealed that the inclusion of the local effects due to the welding process can significantly improve the prediction of the dynamic behaviour of the laser stitch welded structure and the implementation of the sensitivity analysis was successful in correcting the source of error by improving the correlation of the predicted results with experimental counterpart. [ABSTRACT FROM AUTHOR]

Path planning plays a major role in autonomous navigation. Different curve fitting methods are used in creating path for autonomous vehicles. Among those Bezier curves are widely used to create path especially in roundabouts due to their special properties. The primary factor that affects the shape and curvature of the Bezier curve is the control points. Researchers have established equations for calculating the control points for a Bezier curve travelling through selected points. The two critical elements that determine the control points are the random points selected for control point calculation and the segmentation factor (t) for each of the points selected. The values of segmentation factor (t) is assigned randomly to each point. As the segmentation factor change new control points are calculated which makes a change in the shape of the curve but the curve will pass through the selected points. So, this paper presents the change in the shape of the curve as the segmentation factor (t) changes. Additionally, it demonstrates the change in segmentation factor (t) for each point selected to fit the curve within the required space and to adjust t value for connecting two different Bezier curves to create a single curve with continuous curvature. This paper also presents an equation for finding the t value for each of the points selected to avoid overfitting and underfitting of the curve. [ABSTRACT FROM AUTHOR]

The paper studies Sard's problem on construction of optimal quadrature formula in the space L 2 (2 , 0) by Sobolev's method. This problem consists of two parts: first calculating the norm of the error functional and then finding the minimum of this norm by coefficients of quadrature formulas. Here the norm of the error functional is calculated with the help of the extremal function. Then using the method of Lagrange multipliers the system of linear equations for coefficients of the optimal quadrature formula in the space L 2 (2 , 0) is obtained. Further, Sobolev's method of construction of optimal quadrature formulas in the space L 2 (2 , 0) , which based on the discrete analogue D2[β ], is described. Finally, at the end of the paper the rate of convergence of the optimal quadrature formula in the space L 2 (2 , 0) is presented. [ABSTRACT FROM AUTHOR]

In the numerical solution of Initial Value Problems (IVP) for ordinary differential equations, computational methods serve to approximate the determination of functions representing the solution of these problems. The problem of finding the most convenient numerical expressions for a function and its connection with methods for improving such approximations plays an important role in practical calculations. It is of great interest to consider the so-called discrete methods, i.e. methods that determine the solution for discrete values of the independent variable. Discrete methods are currently the most widely used. One of the discrete methods is difference formulas for the numerical solution of the IVP. In this paper, in the Sobolev space where all derivatives up to the mth order participate in the norms of functions, we consider the problem of constructing optimal difference formulas. In the optimization of difference formulas, i.e. when constructing optimal difference formulas in function spaces, an important role is played by the extremal function of a given difference formula. In this paper, the extremal function of the difference formula is explicitly found in the Sobolev space. Next, the square of the norm of the error functional of difference formulas is calculated. Minimizing this norm with respect to the coefficients of the difference formulas, a system of equations is obtained. In addition, the existence and uniqueness of a solution to the resulting system are proved. [ABSTRACT FROM AUTHOR]

The geometry of orbits of families of smooth vector fields is an important object of mathematics due to its importance in applications, in the theory of dynamic systems and in the foliation theory. The paper devoted to the applications of the geometry of orbits of vector fields in four dimensional Euclidean space in theory of differential equations. It is shown that orbits generate singular foliation ever regular leaf of which is a surface of negative Gauss curvature and zero normal torsion. In addition, the invariant functions of the considered vector fields are used to find solutions of the two-dimensional heat equation that are invariant under the groups of transformations generated by these vector fields. In this paper smoothness is smoothness of the class C∞. [ABSTRACT FROM AUTHOR]

We consider A(z)−analytic functions in case when A(z) is anti-analytic function. This article introduces Lp classes of A(z)−analytics functions by p ≥ 1. In this paper, we introduce for a non-tangential boundary value of the A(z)−analytic function. Thus, this paper proves Fatou's theorem on non-tangential values for A(z)−analytic functions. [ABSTRACT FROM AUTHOR]

In the paper considers a discrete model of SIRD, constructed on the basis of discrete Lotka-Volterra dynamical systems operating in a three-dimensional simplex with a degenerate skew-symmetric matrix. The sets of ignition and the end of the epidemic have been found, and the sets where the population is dying out have been found. The paper also provides a numerical analysis of the proposed model. [ABSTRACT FROM AUTHOR]

Uncertainty because of randomness or fuzziness has a pivotal role in our livelihood. These uncertainties can be stochastic or non-stochastic. To deal with stochastic uncertainties or uncertainties due to randomness, this paper aims to develop an ORESTE approach that deals with the information in the form of probabilistic dual hesitant fuzzy elements (PDHFEs). This paper also introduced a series of new distances for PDHFEs with equal and unequal lengths. To show the developed method's efficacy, a sustainable supplier selection (SSS) problem has also been taken as an example. The suggested approach also enables decision-makers to take the degree of agreement and disagreement into account, which makes it superior to previously developed methods. [ABSTRACT FROM AUTHOR]

This paper presents a review of better performance for the photovoltaic system using different technologies and parameters by considering many factors to get the best design and simulation that could fit the Iraqi atmosphere. These factors are the best energy production by using optimum tilt and azimuth angle, considered the most important parameters for getting the maximum solar radiation and eventually getting the preferable performance which depends on the mathematical model that fits each country. The economic profit for a PV system that the reviewer analysis in each paper for maximizing the solar contribution to a particular load, in addition to the impact of how weather conditions such as temperature, solar radiation intensity, etc. have an impact on solar cell efficiency and productivity.; all these factors besides the stability of the solar cell, the relation of the Self Consumption (SC) Degree of Autarky (DA) and economic-efficiency that effect on the PV system performance. The various orientation enables us to obtain many possibilities that serve the required study. [ABSTRACT FROM AUTHOR]

An experimental study to increase productivity and thermal efficiency in solar collectors by optimizing them with a parabolic trough coupled to Fresnel lenses. Fresnel lenses are of great interest as an efficient sun-gathering device due to their high concentration and low heat loss. This paper aims to examine for the first time the addition of Fresnel lenses to a parabolic trough (PTC), which can be considered a promising heat-concentrating technology for solar-powered systems. The test was carried out in Iraq - the city of Diwaniyah (31.99° N, 44. 93° E). The study showed that the use of Fresnel lenses led to an increase in production efficiency. Experiments showed that the total production efficiency is (26.5% and 40.9%) for CSS with PTC and CSS with PTC with Fresnel lenses, respectively, compared with the traditional stator. and thermal efficiency (47.5%,60.1%,70.9%) for CSS, CSS with PTC, and CSS with PTC with two Fresnel lenses on PTC, respectively. This paper proposes the use of spot-type concentrating lenses in concentrated solar collectors to improve the performance of solar distillation. [ABSTRACT FROM AUTHOR]

Variable selection is an important topic in linear regression analysis. In practice, a large number of predictors are usually introduced at the initial stage of model construction to mitigate potential model biases. On the other hand, to enhance the ability to predict and select important variables, regularization techniques are one of the great and proven methods for dealing with a large number of variables. In previous years, statisticians made great efforts in developing regularization procedures to solve the problems of V.S. These actions automatically facilitate Variable selection (V.S) by setting specific coefficients to zero and reducing coefficient estimates, providing useful estimates even if the model contains a large number of variables. In this paper, two methods of regularization were proposed to estimate and select the appropriate variables at the same time in the multiple regression model, which are the Standard Error Adjusted Adaptive LASSO (SEA-LASSO) and Minim ax Concave Penalty (MCP) method and selection of the best. The paper problem focuses on using the best regularization method that works on estimation and appropriate selection of important variables at the same time and addressing the problem of multiple linearity using the SEA-LASSO and MCP method. To get the real model. This paper aims to evaluate the performance of the method (SEA-LASSO) and method (MCP) in terms of the process of estimation and appropriate selection of important variables and treatment the problem multicollinearity through the simulation study. A simulation study was conducted to compare between these two methods, which included different cases of the factors and testing the effect of the levels of these factors on the performance of these two ways, as well as determining the value of the control parameter () and the criterion for selecting the best value for it and the basis on which to evaluate the performance of the two methods. The simulation results showed that (SEA-LASSO) method is superior to (MCP) method in terms of percentage of operation to reach the real model measured by (PCT), and it is also better in terms of mean squares error (MSE) because it achieves less (MSE) in most cases. A simulation study was used with the program R. [ABSTRACT FROM AUTHOR]