Reviewerly/exHarmony huggingface dataset:
Atmospheric Turbidity of Solar Radiation over Langtang National Park

The main aim of this project is to study atmospheric turbidity of solar radiation over Langtang National Park (28.2112° N, 85.5663° E and altitude 3862 m a.s.l.). The daily aerosol optical depth (AOD) data are derived from Aerosol robotic network (AERONET) for a period of one year 2018. Annual mean of Angstrom exponential (α), Angstrom turbidity coefficient (β) and curvature of AOD (a2) are found 1.04 ± 0.29, 0.03± 0.02 and 4.1 ± 0.9 respectively. The average value of and Linke turbidity (LT) is 2.5 ± 0.6. Result of this research work is beneficial for the further identification, impact and analysis of atmospheric turbidity factors at different places.
Ordinary Referring Names in Fictional Contexts

Ordinary proper names can be taken to be referring expressions in non-fictional contexts. But what happens when such names occur in literary works? Within the realist stance, there are two approaches to the issue. Some say that ordinary proper names retain their real world referents in literary fiction. Others argue for the view that ordinary proper names are related there to surrogate referents. It can be pointed out, however, that both approaches create a conceptual tension within the realist doctrine. Fiction-internal contexts are incompatible with any reference-based interpretation of names. The proposal of this paper is, therefore, a shift in perspective: instead of sticking to the notion of reference, the behaviour of ordinary names should be described in terms of representation.
Face Mask Detection and Door Unlocking System Using Deep Learning

Abstract: Recent viral outbreaks have disrupted people's lives and culminated in a pandemic that largely affected all of humanity. Due to COVID -19, many people are forced to stay home but many people are going outside because of many reasons. As people visit any office they must wear masks. But many people don’t wear them due to reluctance, this project is to check if the employees visiting the office wear masks or not. Making use of deep learning, we have built a system that can figure out if an individual is wearing a mask or not. This system may be used in many different locations, such as offices, malls, hospitals, and even private homes. The use of servo motors allows the door to be locked if any individual is not wearing a mask, and a buzzer can be used to warn the person to put on a mask. By using a Raspberry Pi and other existing systems, we can keep the cost of the system as low as possible, making it accessible to a wide range of people
Corporate Governance and Sustainable Development in Africa: Green Human Resource Management Approach

This paper is based on corporate governance and sustainability with a special focus on strategic and green human resource management and sustainability.The paper goes step by step to bring out the historical perspectives of corporate governance and sustainable development in Africa as well as the introduction of corporate governance and its relevance to sustainable development.Various corporate governance dimensions are well articulated to bring out how each dimension contributes to sustainable development.The study also discusses the highlights of strategic human resource management and how it connects to green human resource management in order to increase sustainability.Some anchoring theories to underpin the various topical issues have also been presented and towards the end tail, the role of women in board membership as an integral part of corporate governance is captured.It might be very difficult to have sustainable development without the full participation of women.This paper took the approach of a desk review of studies done on corporate governance and green human resource management for purposes of bringing out the sustainability component.The paper illustrates various dimensions of governance that can enhance sustainability through inclusivity, particularly of women in corporate board membership as well as public sector boards so that women can be part of strategic decision making.It further explores the use of legal rights and human rights as well as technology and innovation that can be leveraged to inculcate green human resource management practices with a view to capturing development for posterity which is critical for growth and advancement in economies in Africa.
A Study on Metaverse and Its Applications in Education

The increasing processing power of computers and the decrease in production costs have allowed the development of virtual reality technology. Thus, there has been an increase in the use of virtual reality in many fields, from education to the military. With the transition to online education due to the pandemic in 2020, the need for an education method where students and educators can interact with each other has arisen. With the increase in the integration of virtual reality applications in studies from the past to the present, user experiences have also increased. With the increasing user experience, the fields of use in education cover different education levels, from primary education to university. In this study, various virtual reality applications applied in education were examined, and the use of virtual reality technology in education, its benefits, and its contributions to student performance were discussed. It is aimed that this review and the results will guide the applications to be developed in the field.
Transformation of the ontology of education: from the classroom lesson system to smart innovations

The world in the 21st century is changing both materially and mentally. Productive relations in education no longer correspond to the development of the productive forces of "smart" technologies. The purpose of this article is to analyze the social and didactic aspects of modern and future trends in the field of education from the point of view of its development from the ontological traditions of the classroom system to the ontology of smart education innovations. The main factors and needs leading to innovative changes in the education system are considered: the adequacy of technologies used in the economy, everyday life of people and in education; accessibility and comfort of educational processes; the need to move from the standards of the content of education to its variability, while maintaining basic training; removing the classes, a rigid schedule, horrifying stories about exams and strict limits on the duration of training; avoidance of multidiscipline; the primary role of the student; the emergence and development of new teacher functions; individualizations and personification of learning using artificial intelligence. It is shown that the totality of modern and promising innovations conditioned by social needs and technological factors leads to the evolution of the education system from the concepts of the traditional classroom system not only to smart tools of learning activities that improve the quality of the educational process, but also to a new promising educational paradigm of smart education.
A blueprint for the short course "Selected Engineering Issues"

It is proposed to supplement the existing university courses "Introduction to Engineering" with a brief overview of the author's project-based learning course "Selected engineering issues". As an example, a five-day course plan is given. The course is intended for a general understanding of the specifics, structure and problems of engineering activities, and, according to the plan, should improve the mastering of the material of the Introduction to Engineering courses. The course has the format of a collective educational and project process, which is implemented in the cognitive infrastruc- ture of the situation center on the resources available to the organizers. Such a center can be set up outside the class- room using participants' smartphones. The cognitive environment is ensured by the presence of a support team consist- ing of a coordinator, a methodologist, a tablet keeper and a game technician. The functions of the support team can be performed by one specially trained teacher capable of reflexive perception of the learning situation. A constructor of course options is proposed, which includes various types of implementation processes. A variant of a metaphorical cog- nitive engineering map as a set of pictures and comments to them is proposed. The need for separate consideration of the setting tasks stages, working on bugs and opportunities for students to quickly access network resources and team- work technologies is noted. The author's "4C" approach (collective, cognitive, configurative, convergent) is used in combination with a cross-technology system that provides multidisciplinarity. The concept of mutual adjustment of students' cognitive profiles and teaching formats of academic subjects (visual, audio, kinesthetic, tactile) is also used. The use of the listed author's tools ensures the originality of the proposed solutions.
Applications of AI in game plug-ins detection

With the development of the machine learning and computer games, more and more artificial intelligence technologies are applied in the game field. From IBM's Deep Blue's victory over chess king Kasparov in 1997 to AlphaGo's victory over Go world champion Lee Sedol in 2016, AI technology has played a pivotal role, thus making artificial intelligence famous. However, the applications of AI against the game plug-ins have been rarely reported. Thus, this paper will introduce some AI algorithms used in game plug-ins detection and some application cases.
Less is More: Learning Simplicity in Datacenter Scheduling

In this paper, we present a new scheduling algorithm, Qin2, for heterogeneous datacenters. Its goal is to improve performance measured as jobs completion time by exploiting increased server heterogeneity using deep neural network (DNN) models. The proposed scheduling framework uses an efficient automatic feature selection technique, which significantly reduces the training data size required to train the DNN to levels that provide satisfactory prediction accuracy. Its efficiency is especially helpful when the DNN model is re-trained to adapt it to new types of application workloads arriving to the datacenter. The novelty of the proposed scheduling approach lies in this feature selection technique and the integration of simple and training-efficient DNN models into a scheduler, which is deployed on a real cluster of heterogeneous nodes. Experiments demonstrate that the Qin2 scheduler outperforms state-of-the-art schedulers in terms of jobs completion time.
Spam Mail Classifier

Abstract: Email is the worldwide use of communication application. It is because of the ease of use and faster than other communication application. However, its inability to detect whether the mail content is either spam or ham degrade its performance. Nowadays, lot of cases have been reported regarding stealing of personal information or phishing activities via email from the user. This project will discuss how machine learning help in spam detection. Machine learning is an artificial intelligence application that provides the ability to automatically learn and improve data without being explicitly programmed. Binary classifierwill be used to classify the text into two different categories: spam and ham. The algorithm will predict the score more accurately. The objectiveof developing this model is to detect and score word faster and accurately.
Опитът в електронното обучение на студенти и преподаватели като фактор за формиране на отношения и нагласи към неговите възможности и ограничения (уроци от пандемията COVID-19)

The shift to “emergency remote teaching” forced by the COVID-19 pandemic has posed a huge challenge to most of the teachers and students in higher education institutions worldwide. Our research focus in previous publications was aimed at establishing the impact of e-learning experiences during the COVID-19 pandemic of separately teachers and students at Sofia University (Bulgaria) on their evaluations of e-learning strengths and weaknesses, as well as their attitudes towards this e-learning in general. As a sequel, in the present paper an attempt is made to compare the perspectives of the two groups towards e-learning, influenced by their experience. The survey of teachers and students’ opinions was conducted through online surveys at the end of the summer semester of the 2019/2020 academic year, when, due to the pandemic, approximately 4 months of the learning process was provided entirely online. Participants in the study were 383 teachers and 1239 students from all 16 faculties of the Sofia University. Findings from the data analysis revealed the presence of statistically significant dependencies between teachers and students’ experiences in online learning and their views of theoretically and practically proven advantages and disadvantages of e-learning. The results in the two groups appeared to be almost similar, which gave us reason to claim that richer experience in e-learning is a significant prerequisite for the formation of positive attitudes towards e-learning in both students and teachers, and vice versa, lack of experience or insignificant experience negatively affects their evaluations of e-learning.
STUDI KEPUSTAKAAN: KEAMANAN INFORMASI DI PERPUSTAKAAN DIGITAL

Are all the information stored in digital libraries, both information in the form of collections or user personal data, guaranteed security? This article discusses the threats to information security in digital libraries and their prevention. This study uses a qualitative method with a research library technique, namely research that refers to previous studies, several expert opinions, and other reliable sources obtained by the author by digitally reviewing the research results. The research conducted shows that information security threats in digital libraries do not attack programs or applications that are used to manage information only, but also physical objects to store the information. Examples of information security threats to digital libraries are malware which consists of various types. The easiest way to keep information that is stored safely is by backing up (duplicating information). However, backup alone is not enough. It is necessary to improve the performance of librarians or other training managers by including various national and international events. Not only human resources, but various devices used in digital libraries also need to be updated so that the system that is run is not easily disturbed. In addition, digital libraries should in some time hold simulations of conceding information, so that when such unexpected incidents occur, libraries can take appropriate steps so that the impact that occurs is not more widespread.
SURVEI NEED ASSESSMENT BIMBINGAN TEKNIS TENAGA PERPUSTAKAAN TAHUN 2020 DI INDONESIA

Bimbingan Teknis Tenaga Perpustakaan (Bimtek), literally translated as Technical Training for Library Technician, is an activity carried out by the National Library of Indonesia through the Librarian Development Center (P3) unit as an effort to fulfill their responsibilities as a supervisory board. With a target of thousands of participants from all provinces in Indonesia, The Bimtek spent a lot of energy and cost, therefore it would be fruitless when the implementation was far from the target. To avoid this, organizers need to finalize the planning as best as possible, one of which is by assessing the need for Bimtek materials that are in accordance with the interests and needs of the participants. Through this research, the authors conducted a need assessment for the first time at the P3 unit Bimtek involving librarians and library technicians on a national scale.. The research was conducted using a descriptive quantitative approach and survey method of 2.080 Library Technician respondents in Indonesia, the questionnaire was built by adopting the Indonesian National Work Competency Standards in the field of Libraries. The results show that the most chosen Key Functions by the respondents is Library Information and Communication Technology.
Dynamic Trust Continuous Evaluation-based Zero-Trust Access Control for Power Grid Cloud Service

Abstract The development of power grid cloud service puts forward higher requirements for remote secure access. To realize fine-grained access control of remote secure access of power grid cloud service, this paper proposes a zero-trust access control model for power grid cloud service based on dynamic trust continuous evaluation. The experimental results show that the model proposed in this paper can effectively implement continuous trust evaluation for remote access of PowerCloud services, and achieve zero trust access control, with an exception detection accuracy rate of 97.2% and the incremental learning accuracy rate of over 97% when the behavior model of remote access changes.
Utilization of GPM Satellite and PERSIANN Satellite Data for Estimated Monthly Rainfall in South Sumatera

Rainfall data are widely used to predict regional rainfall. Limited rainfall data is a problem that has an impact on decreasing accuracy, one of which is in the area of South Sumatra. This can be overcome by using satellites. However, to utilize satellitebased rainfall data, it is necessary to carry out an analysis to determine the accuracy of rainfall data. This research aims to evaluate rainfall data from the GPM satellite and PERSIANN satellite with validation and calibration analysis so that the value of rainfall data from the Satellite is close to the measurement result and can be used to estimate monthly rainfall. In this study, the data used were measured monthly rainfall in the field, GPM, and PERSIANN obtained from 9 South Sumatra districts for 2019 until 2021. The research method was validated using correlation coefficient, Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). Calibration is done using a combination method, a solver algorithm in Microsoft Excel, and manually. The estimated monthly rainfall analysis is carried out using the isohyet method with the IDW interpolation method. The research results were obtained based on the validation and calibration of monthly rainfall data showing that data from the GPM showing it is closer to the results of field rainfall measurements than the data obtained from PERSIANN satellite. Based on the results of research on satellite data that has been calibrated, it can be used to estimate monthly rainfall in the South Sumatra Region
2D-FACE ALIGNMENT WITH CYCLEGAN FACE AGING IMAGE-TO-IMAGE TRANSLATION

Face alignment is one of the pre-processing processes where the face plays a crucial part in image tasks and computer vision. As part of the pre-processing step, it is the first step taken before implementing an image processing task. By aligning face, it is expected to improve the network model performance, because good input data is now represented in the network model. This research aims to see whether pre-processing the input data can improve the network model performance. A 2D-face alignment technique is used to align all the input images. All the input image that is already being aligned is used as the input image for the CycleGAN face aging image-to-image translation model. In this work, the CycleGAN network model is used to translate an image of a young face to their older version and vice versa. The result obtained shows that if the network model is presented with a properly aligned face, it can translate the image into a younger or older version better than when presented with a non-aligned face.
EFFECTIVENESS ON TRAINING METHOD USING VIRTUAL REALITY AND AUGMENTED REALITY APPLICATIONS IN AUTOMOBILE ENGINE ASSEMBLY

Training and education have become increasingly crucial in obtaining new skills in a variety of fields, especially in assembly and disassembly operations. The main issue in mechanical engineering, particularly in the assembly department, was that automobile engine components assembly was found to be complicated and challenging to assemble using an existing method, where they only rely on a video-based method. The purpose of this paper is to create interactive Virtual Reality (VR) and Augmented Reality (AR) applications that allow users to efficiently assist and complete the assembly tasks. In this work, the authors designed and developed a fully immersive VR application using an HTC Vive headset and two AR applications (marker-less AR application and marker-based AR application) using EPSON MOVERIO BT-300 (AR Smart Glasses). Fourteen engineering students from Universiti Putra Malaysia were selected for the experiment. They were divided into four groups: video-based group, VR-based group, marker-less AR group, and marker-based AR group. They are required to complete all four experiments (video-based experiment, VR-based experiment, marker-less AR experiment, and marker-based AR experiment). The results showed that the marker-less AR application is the best impressive method (37% better), the VR application is the second impressive method (23% better) followed by the marker-based AR application is the third impressive method (3% better) compared to the existing video-based guideline. Therefore, the students favored AR and VR applications rather than the existing method to be used in automobile engine assembly tasks.
A Convex Hull-Based Machine Learning Algorithm for Multipartite Entanglement Classification

Quantum entanglement becomes more complicated and capricious when more than two parties are involved. There have been methods for classifying some inequivalent multipartite entanglements, such as GHZ states and W states. In this paper, based on the fact that the set of all W states is convex, we approximate the convex hull by some critical points from the inside and propose a method of classification via the tangent hyperplane. To accelerate the calculation, we bring ensemble learning of machine learning into the algorithm, thus improving the accuracy of the classification.
Teachers implementing new primary school digital technology areas: What are we teaching now?

New digital technology areas were added to the New Zealand primary school technology curriculum in 2020. These areas aim to grow students who are not just passive users of technology but, instead, students who understand how computers work, who are digital creators, informed by design processes and critical thinking. The new digital areas of the technology curriculum appear to have created tension between the expectations of teachers and their relative capabilities. Examining three primary teachers' implementation of the new digital areas, this project utilised a participatory action research (PAR) methodology to review teachers’ journey of adoption. Findings indicated that implementing the curriculum areas was not as complex as teachers first imagined and that unplugged activities (those without devices) played a significant role in the new digital technology areas’ successful implementation in the classroom. The main themes that appeared from the data included levels of teacher knowledge, teacher confidence and curriculum learning area integration.