Reviewerly/exHarmony huggingface dataset:
Study of Hardware and Software Resources for Mobile Applications of Immersive Technologies in Manufacturing

Immersive technologies (IT) create different experiences by combining the physical world with digital or simulated reality. Virtual augmented and mixed reality are the main types of immersive technologies. Since the beginning of the millennium, VR, AR and MR technologies have experienced rapid growth with significant research publications in technology and science. However, the engineering community has only minimally implemented these technologies so far. One of the challenges mechanical engineers face in understanding and using extended reality (ER) combining VR, AR, MR is the lack of hardware and software requirements specification. This document provides a literature review on mobile applications of immersive technologies in engineering production. A historical overview of the concept of applications used in industry was gradually created. Subsequently, the hardware and software pro-resources used for XR in production are presented. The article is intended to find a good fit between XR hardware and software solutions based on professional and technical knowledge in engineering fields.
No Laplacian perfect state transfer in total graphs

The total graph of a graph G, denoted by T(G), is defined to be the graph whose vertices are the vertices and edges of G, with two vertices of T(G) adjacent if and only if the corresponding elements of G are adjacent or incident. In [Discrete Mathematics, 344 (2021) 112139], Liu and Wang proved that if r+1 is not a Laplacian eigenvalue of an r-regular graph G, then there is no Laplacian perfect state transfer in T(G). They also posed the question: If r+1 is a Laplacian eigenvalue of an r-regular graph G, can T(G) have LPST? In this paper, we completely answer this question. We give new descriptions concerning the eigenvalue support and spectral decomposition of the Laplacian matrix of T(G), by use of which we show that there is in fact no Laplacian perfect state transfer in T(G) for any regular graph G.
Data sharing and data governance in sub-Saharan Africa: Perspectives from researchers and scientists engaged in data-intensive research

The data ecosystem is complex and involves multiple stakeholders. Researchers and scientists engaging in data-intensive research collect, analyse, store, manage and share large volumes of data. Consequently, capturing researchers’ and scientists’ views from multidisciplinary fields on data use, sharing and governance adds an important African perspective to emerging debates. We conducted a descriptive cross-sectional survey and received 160 responses from researchers and scientists representing 43 sub-Saharan African countries. Whilst most respondents were satisfied with institutional data storage processes, 40% indicated that their organisations or institutions did not have a formally established process for storing data beyond the life cycle of the project. Willingness to share data was generally high, but increased when data privacy was ensured. Robust governance frameworks increased the willingness to share, as did the regulation of access to data on shared platforms. Incentivising data sharing remains controversial. Respondents were satisfied with exchanging their data for co-authorship on publications (89.4%) and collaboration on projects (77.6%). However, respondents were split almost equally in terms of sharing their data for commercial gain. Regarding the process of managing data, 40.6% indicated that their organisations do not provide training on best practices for data management. This could be related to a lack of resources, chronic institutional under-investment, and suboptimal research training and mentorship in sub-Saharan Africa. The sustainability of data sharing may require ethical incentive structures to further encourage researchers and scientists. Tangible infrastructure to facilitate such sharing is a prerequisite. Capacity development in data governance for researchers and scientists is sorely needed. Significance: Data sharing is necessary to advance science, yet there are many constraints. In this study, we explored factors that promote a willingness to share, as well as constraining factors. Seeking potential solutions to improve data sharing is a scientific and ethical imperative. The standardisation of basic data sharing and data transfer agreements, and the development of a Data Access Committee will strengthen data governance and facilitate responsible data sharing in sub-Saharan Africa. Funders, institutions, researchers and scientists ought to jointly contribute to fair and equitable data use and sharing during and beyond the life cycle of research projects.
Review Paper on Quantum Computing and Quantum Cryptography

Quantum computing and quantum cryptography are two areas of research that have the potential to transform modern computing and communication. Quantum computing promises to solve computational problems that are beyond the reach of classical computers, while quantum cryptography provides a way to secure communication channels that is immune to eavesdropping. Quantum cryptography is one of the emerging topics in the field of computer industry. This article focuses on quantum cryptography and how this technology makes a valuable contribution to an intensive defense strategy of completely secure key distribution. The scope of this article covers the weaknesses of modern digital cryptographic systems, the basic concepts of quantum cryptography, the practical implementations of this technology, and its limitations. , and finally the future direction that quantum cryptography is headed. We describe the result of an apparatus and protocol designed to perform quantum key distribution, whereby two users do not share any secret information (no private or public keys are known). previously known) initially exchanges a random quantum transmission consisting of veryweakly polarized light rays. In particular, readers can explore the following topics in depth: current cryptographic schemes (symmetric and asymmetric), the difference between quantum and classical computing, challenges of quantum computing, quantum algorithms (Shor and Grover), public key cryptographic schemes affected, symmetry affected schemes, impact on hash functions and post-quantum cryptography
An In-Depth Investigation of the Complex Interplay between Entrepreneurial Leadership and Employee’s Individual Outcomes: Uncovering the Multifaceted Dynamics of Organizational Success

The relationship between employee productivity and organisational success has become an increasingly prominent area of research.Numerous studies have demonstrated that individual employee outcomes are closely linked to business units and overall organisational performance.Creativity and innovation play a crucial role in an organisation's ability to gain and maintain a strategic advantage over competitors, particularly for Small and Medium-sized Enterprises (SMEs), which are crucial to a country's economic and social development.While leadership is essential for employee motivation and organisational development, the precise nature of the relationship between leadership style and individual employee outcomes remains unclear.This study aims to establish a comprehensive framework for understanding the impact of leadership on employee performance, exploring novel motivations for achieving individual employee outcomes that ultimately enhance employee and organisational performance.Data were collected through interviews with 26 consenting employees, employing open-ended questions and note-taking, and were analysed using a thematic approach.Data analysis revealed five fundamental key themes that emerged from the collected data from various workers of SMEs concerning individual outcomes in the organisation.The outcomes of this study provide valuable insights for managers and leaders in SMEs as they strive to enhance employee performance and organisational effectiveness.The findings offer a fresh perspective on the relationship between leadership style and employee outcomes, highlighting the importance of novel approaches that encourage individual employee growth and development.The study's significance extends beyond the SME context, as its findings provide valuable insights for businesses seeking to improve their organisational performance.
Pattern Recognition: Data Mining

The process of identifying patterns in data through techniques such as data mining, machine learning, and artificial intelligence is known as pattern recognition. This research paper provides an overview of pattern recognition in data mining, which includes the methods used to recognize patterns, their practical applications, and the challenges associated with this field of study.
Exploring the value of multi-sensory aids in co-designing assistive home devices for older adults with cognitive impairment

ABSTRACTIn this study, we aimed to investigate the benefits of co-design prompts/aids in the development of assistive devices for and with older adults who have cognitive impairment (CI), with the goal of improving their ability to live independently at home. We conducted a series of co-design workshops and utilized eight sets of multi-sensory aids to explore their values and effectiveness in engaging older adults with CI in co-design processes. Our findings revealed that the co-design aids had several benefits, including: (1) increasing the exchange of knowledge and awareness between older adults and designers; (2) eliciting insightful information through multi-sensorial aids, and (3) generating novel assistive design solutions to support seniors’ independent living at home. We discuss our findings in relation to the multi-sensorial attributes of co-design aids, which empower older adults with CI to express their opinions and actively participate in co-designing assistive devices that meet their needs/expectations.KEYWORDS: Assistive products for homeco-designcognitive impairments (CI)multisensory aidsolder adults AcknowledgementsWe would like to express our gratitude to all the seniors with cognitive impairment and their caregivers who participated in this research, as well as to our colleagues at Emory and the staff at the Cognitive Empowerment Program for their invaluable support.Disclosure statementNo potential conflict of interest was reported by the author(s).
TKJ and Graphic Design Training for Student Strengthening Facing UKK at SMK PGRI Amlapura

The Vocational High School of the Indonesian Teachers Association (SMK PGRI) Amlapura is a vocational school at the upper middle level that has four majors namely, hospitality, catering, computer network and multimedia engineering. Located in Amlapura City, Karangasem Regency, Bali Province. Based on the vocational education that is carried out, all students studying in vocational schools are required to take the expertise competency test (UKK) of each field that is in demand in accordance with the majors they choose. This UKK is carried out nationally and is a national practical test. This is what distinguishes an educational model that exists at the high school level. As for facing the National Practice Examination, schools generally provide assistance for their students.Bali State Polytechnic in this case implementing Tri Dharma Higher Education such as teaching, research and service. One of the Tri Dharma of the tertiary institution is the Commander of the Commander, where the community service aims to play a role and participate in building the welfare of the community. This service activity is carried out in accordance with existing academic culture.Bali State Polytechnic Department of Electrical Engineering Information Management Study Program is willing to accompany the students of SMK PGRI Amlapura in terms of preparing themselves to take part in UKK. This mentoring activity is a service activity. Assistance provided specifically to UKK Computer Network Engineering Program and UKK Multimedia Program. Activities in the form of exposure in theory and direct practice. The continuation of assistance is also done using WhatsApp Group media.
Preliminary Investigation on the Use of Focused Bessel-shaped Beams for Imaging of PEC Objects

In this contribution, preliminary analyses are performed on the use of focused beams for imaging of PEC targets. In particular, the data collected in case of Bessel-shaped beam as incident field are processed by means of the well-known physical optics approximation and also by a recently introduced qualitative method, which exploits sparsity regularization and solves the related inverse source problem. A preliminary example against 2D scalar geometry and a C-shaped PEC cylinder is reported and discussed.
Software Metric Analysis of Open-Source Business Software

Over the past decade, open-source software use has grown.Today, many companies including Google, Microsoft, Meta, RedHat, MongoDB, and Apache are major participants of open-source contributions.With the increased use of open-source software or integration of open-source software into customdeveloped software, the quality of this software component increases in importance.This study examined a sample of open-source applications from GitHub.Static software analytics were conducted, and each application was classified for its risk level.In the analyzed applications, it was found that 90% of the applications were classified as low risk or moderate low risk indicating a high level of quality for open-source applications.
Video Surveillance for Indoor Office Environment Based on Object-Level Anomaly Detection

Abstract Traditional methods of Abnormal Behavior Detection (ABD) process the surveillance video on frame-level, which ignores object-level abnormal behavior patterns. To address the problem, this paper presents Object-Level Anomaly Detection model (OLAD), which aims to model various normal behavior patterns of different objects and the normal interaction patterns between them. Specifically, OLAD introduces an encoding-embedding network to transform object-level information into the feature space. By integrating such information, OLAD processes both frame-level and object-level cues in the video for ABD. In addition, we construct our own dataset Northking2022 especially for office scenes because of the lack of public datasets for indoor office environments. Experimental results show that OLAD gains better performance on both the public benchmark and Northking2022.
Developing English Vocabulary Mastery of Students at SMPIT Ibnu Sina Makassar through Word Card Games

This study is to describe two main points, namely (1) the development of English vocabulary mastery of 7th-grade students of SMPIT Ibnu Sina, Makassar using word card games, and (2) the aspects of vocabulary that hinder their English vocabulary development. Pre-experimental research method with pre and post-test design was used to quantitatively describe the impact of the treatment given through the use of word card games in developing students' vocabulary mastery comprising three aspects, namely (1)vocabulary forms in spelling and pronunciation, (2) denotative meaning of vocabulary, and (3) vocabulary usage focusing on the use of Present and Past Tense sentence patterns both in oral and written forms and the hindering aspects of their vocabulary mastery development which are then described qualitatively. The grade 7 students of SMPIT Ibnu Sina, Makassar totalling 28 students were the population of this study using the census sampling technique. To collect data, a vocabulary test was administered in three forms of questions, namely (1) spelling and pronunciation, (2) matching for vocabulary meaning, and (3) multiple choice and making simple sentences. The results showed that (1) the word cards could develop the English vocabulary mastery of students in terms of vocabulary form, vocabulary meaning, and vocabulary use empirically indicated by the mean score of pre-tests as 58.13 taken into an average category and post-tests is 79.72 classified into a good category and (2) the aspect that hinders students' vocabulary mastery is pronunciation and sentence construction. These findings are simply considered that word card games can be implemented to bridge the development of students’ vocabulary mastery coming along with teaching English structures.
Bi-LSTM-CRF-based named entity recognition for power administration

A large number of semi-structured and unstructured texts have been accumulated during the operation of power administration. Scientific mining of the value behind these texts plays a key role in the digital transformation of power grid companies. In this paper, we adopt Bi-LSTM-CRF model for power administrative entity recognition, firstly classify and label the power administrative texts, and then adopt the above mentioned model for power administrative entity recognition, and compare it with HMM, CRF and BiLSTM models experimentally. The final experimental results prove that the Bi-LSTM-CRF model entity recognition has the highest accuracy rate and is more effective in identifying entities in electric power administration.
Cloud Computing –Security Issues and Threats

One of the most exciting topics in the IT business nowadays is cloud computing. The cloud computing resource paradigm has changed the geography of computing. Computing's promises of cost reductions, enormous scalability, lower dependency on third parties, and increased trust have attracted both businesses and individuals. This increases the power of information technology. Cloud computing has grown significantly recently in the field of information technology. Concerns over information security are growing as more and more people and businesses store information in the cloud. Many companies, including Microsoft, which is considered a software development powerhouse, are working on developing cloud services. Customers are reluctant to change their business practices ignoring the excitement around it, to the cloud. Protection is one of them. All three aspects are covered by a comprehensive cloud security plan to ensure the foundation is solid. Each can be viewed through a different lens or perspective on cloud security. For your company to use the cloud to grow securely, a solid plan must decrease risk (security controls), defend against threats (secure coding and deployment), and overcome obstacles (adopt cultural and technical solutions).
Research on the Management of Building Construction Based on Face Recognition

In order to improve the attendance management level of construction personnel, a face recognition algorithm based on additive angular boundary loss was proposed to further improve the accuracy of face recognition. First, the recognition algorithm based on additive angular boundary loss was selected as the face recognition algorithm. Then, ResNet50 neural network was selected for face feature extraction. Experimental results showed that the face recognition algorithm based on additive angular boundary loss can maintain high recognition accuracy, and the recognition accuracy on LFW and YTF datasets reaches 99.8% and 98.3%, respectively. After optimization, the accuracy of ResNet50 neural network is also improved when extracting feature information. The above experimental results verify the rationality of the improvement of the recognition algorithm and feature extraction network, which has certain reference value and significance.
Application of Deep Learning Algorithm in Crack Detection of Green Building Materials

Aiming at the problem of low detection precision of traditional crack detection, Faster R-CNN was taken as the basic network, the features of block3 and Block5 in its backbone network VGG-16 network were fused, and two cascaded R-CNN networks with IoU thresholds of 0.5 and 0.6 respectively were used as the detection network to detect the cracks of green concrete. Simulation results showed that the proposed method reduces the loss of structural information by fusing the features of Block3 and Block5. By cascading the two R-CNN networks with different IoU thresholds, the classification and location of regional suggestion boxes are more accurate, and the precision of crack detection is improved. The average detection precision is 98.29%, and the detection speed is 12. 26fps. Compared with traditional detection algorithms based on SSD and YOLO-V3, the average detection precision and detection speed are improved to varying degrees, which has certain effectiveness and superiority.
Error Correction Method of Business English Translation Based on Convolutional Neural Network

In order to correct business English translation errors, this paper puts forward a method of business English translation error correction based on convolutional neural network and English pronunciation feature recognition. The blind convolution network spectrum parameter detection method is used to detect the pronunciation spectrum features of business English translation, and the scalar time series of pronunciation output audio parameter sequence and translated text semantic feature sequence are established. Combined with the noise intensity detection and signal scale decomposition method of business English translation pronunciation audio time series, the detailed signal energy parameters of business English translation pronunciation audio time series are extracted, and the convolution neural network classification method is used to classify the features. The interference component of single audio feature sequence of English translation pronunciation is removed by high-frequency wavelet threshold detection, and the modulation and demodulation of single audio feature sequence of English translation pronunciation are realized by using translation dictionary set and semantic context matching. The spectral analysis and error correction model of business English translation pronunciation audio time series is established, and the output stability of business English translation pronunciation audio time series is detected by threshold detection on each scale. According to the difference between output signal and pronunciation standard signal, the accuracy of English translator is detected and identified. The simulation results show that the accuracy of business English translation error correction with this method is high, the detection performance is good, and the output accuracy of English translators is improved.
PENINGKATAN MOTIVASI DAN HASIL BELAJAR MATERI RUANG DIMENSI TIGA DENGAN PENDEKATAN KONTEKSTUAL PESERTA DIDIK KELAS XII SEMESTER GANJIL SMAN 1 POLEWALI

The success of this study was indicated by an increase in students' learning motivation above 75%, an increase in learning outcomes above the KKM, and a minimum percentage of classical learning mastery of 75%.This research is classroom action research. The learning used in this research is contextual. The subjects of this study were class XII students at SMA Negeri 1 Polewali for the 2021/2022 academic year, namely 36 students. Data was collected through documentation, interviews, tests, observations, and questionnaires. The collected data were analyzed using descriptive analysis and calculating the average value and percentage.Based on the research results, the percentage of learning motivation from cycle I to cycle II increased from 63.04% to 76.33% or 13.29%. There was an average increase in student learning outcomes from 72.01 to 75.32 or 3.31 points. The students' classical learning completeness increased from 68.75% to 79.41% or 10.66%.