Reviewerly/exHarmony huggingface dataset:
Corporate Learners' Perceptions of Extended Reality Technology as a Learning Aid in the Workplace

Virtual and augmented reality have grown in popularity as learning tools in the workplace in recent years. This study looks at how corporate learners perceive the use of extended reality technology in the workplace. Corporate learners utilise a variety of learning technologies, and their opinions of these resources have an impact on their adoption and learning process. A mixed-methods study was conducted using an online survey and follow-up interviews with the financial services participants (N = 106). The study was guided by the second-generation activity theory and the technology acceptance model (TAM). Findings showed that learners valued immersive technology because it increased teammate involvement and knowledge. However, issues with technological accessibility and incorporation into corporate learning programmes were also raised. According to this study, immersive technology may help with workplace learning, but its advantages and challenges should be taken into account as well. Extended reality (XR) technology offers notable advantages in learning by elevating enjoyment and facilitating a smoother learning experience, which greatly impacts learners' attitudes. However, its implementation in education presents challenges, primarily due to the increased need for resources. Additionally, the learning curve associated with XR technology poses hurdles for both educators and learners. Limited accessibility to virtual reality gear further complicates matters, potentially hindering proficiency and accessibility for learners trying to navigate this technology.
An Evaluation Model of Preschool Teacher Talent Training Based on Big Data Technology

The key to improving the quality of preschool education lies in high-quality preschool teachers, and high-quality preschool teachers in turn depend on high-quality teacher education. A pilot project to “strengthen the training of kindergarten instructors” was recommended by the Ministry of Education. This research studies the resident training mode implemented by pilot normal colleges and universities, uses big data technology to collect the required data, and uses neural networks to evaluate the talent training mode of preschool teachers, and finally completes the following work: 1) This article introduces the research progress of the talent training mode of preschool teachers at home and abroad; 2) Introduced are the RBF neural network's fundamental ideas and algorithmic stages, and the evaluation index system for the training of preschool teachers is established; and 3) Experiment to determine the best model parameters, then feed the test data into the model you trained, and compare the output against expert evaluations.
Viability of Man and Machine as Co-Workers in the Hotel Industry

This study examines the feasibility of fostering symbiotic relationships between humans and machines in the hotel industry and explores effective strategies for managing their collaboration to maximize benefits. The chapter follows a rigorous methodology, conducting a systematic literature review using scientific databases, analyzing published and unpublished articles and data from various organizations. Key focus areas include the “hospitality industry,” “man and machine,” and “machine as co-workers.” Findings demonstrate that strategic management and implementation of human-machine relationships can enhance organizational performance and yield substantial benefits. Addressing inherent challenges and intricacies is vital for a favorable outcome. The study presents a theoretical framework elucidating the impact of human-machine interaction on organizational outcomes.
Design of a web-based application for managing evidence data at the East Aceh District Prosecutor's Office

The prosecutor's office is a government institution that has the authority to delegate, prosecute perpetrators in court and carry out the decisions and decisions of criminal judges. Evidence is the object of a criminal act. Administrative processing of evidence at the East Aceh District Prosecutor's Office uses office computer applications so that the data stored is not well structured and is not centralized. This makes it difficult for evidence officers to recapitulate data quickly and efficiently. Apart from that, the risk of data loss or administrative errors is also prone to occur due to the absence of an authentication process for office computer application users for handling such evidence. The aim of this research is to build an evidence data processing application to facilitate the activities of evidence and confiscated property management section officers to manage data effectively.
Infusing external knowledge into user stance detection in social platforms

Stance detection for user reviews on social platforms aims to classify the stance of users’ reviews toward a specific topic. Existing studies focused on the internal semantic features of reviews’ texts, but ignored the external knowledge associated with the review. This paper retrieves external knowledge related to the key information of each review by mapping it to a knowledge graph. Thereafter, this paper infuses the external knowledge into deep learning model for stance detection. Considering that infusing external knowledge may bring noise to the model, this paper adopts the personalized PageRank method to filter the introduced irrelevant external knowledge. Infusing external knowledge can improve the classification performance by providing background knowledge. In addition to considering the textual features of reviews when constructing the stance detection model, this paper employs a gated graph neural network (GGNN) approach to fuse the structural information between reviews to capture the interactions of reviews. The experiments show that the model improves 1.5% –6.9% in macro-average scores compared to six benchmark models in this paper. By combining the textual features and structural information of reviews and introducing external knowledge, the model effectively improves the stance detection performance.
Generating intelligent agent behaviors in multi-agent game AI using deep reinforcement learning algorithm

&lt;span&gt;The utilization of games in training the reinforcement learning (RL) agent is to describe the complex and high-dimensional real-world data. By utilizing games, RL researchers will be able to evade high experimental costs in training an agent to do intelligence tasks. The objective of this research is to generate intelligent agent behaviors in multi-agent game artificial intelligence (AI) using deep reinforcement learning (DRL) algorithm. A basic RL algorithm called deep Q network is chosen to be implemented. The agent is trained by the environment's raw pixel images and the action list information. The experiments conducted by using this algorithm show the agent’s decision-making ability in choosing a favorable action. In the default setting for the algorithm, the training is set into 1 epoch and 0.0025 learning rate. The number of training iterations is set to one as the training function will be repeatedly called for every 4-timestep. However, the author also experimented with two different scenarios in training the agent and compared the results. The experimental findings demonstrate that our agents learn correctly and successfully while actively participating in the game in real time. Additionally, our agent can quickly adjust against a different enemy on a varied map because of the observed knowledge from prior training.&lt;/span&gt;
Delving Into Writing Anxiety of Rural College EFL Learners: A Quantitative Study

Anxiety in foreign language writing burdens EFL learners before, during, and after producing scientific written texts. This current research aimed to explore the types, levels, and causes of anxiety toward writing research reports and the final thesis of rural college EFL learners and the emerging causes of their writing apprehension. 103 EFL learners in two rural colleges in Indonesia participated in the quantitative study by employing the Second Language Writing Inventory (SLWAI) and the Causes of Writing Anxiety Inventory (CWAI). The results reveal that cognitive anxiety was the highest type and level of rural college EFL learners' writing apprehension. Independent t-test shows that female EFL learners dominate male learners regarding writing anxiety. Furthermore, junior learners were more anxious than seniors. The learners with writing training had lower anxiety than those without writing experiences. Moreover, the learners taking the Research Method course were anxious about writing a research report. However, no significant difference was found between each variable. The most dominant emerging factors deal with problems with linguistic matters, fear of lecturers or supervisors' negative feedback, self-regulation in writing, writing evaluation, and inadequate training in writing. In conclusion, current classroom practice in rural colleges needs to be aware of and take academic action towards such circumstances.
SoftBloC: An IoT Security and Privacy Architecture for a Cashierless Retail Store

The constantly shifting needs and expectations of customers in respect of seamless shopping experience has continued to drive retail store businesses to evolve their approaches. Advancing the previous self-checkout technology is the cashierless retailing solution which aims to reduce the number of human resources present in retail stores at any time and eliminate queues at checkout points. While cashierless retailing improves the customer experience, the most challenging aspect of its implementation and adoption is security and data privacy, specifically Internet of Things (IoT) devices and network security, and data privacy protection. In this paper, we leveraged deep learning, computer vision (image recognition), cryptography and blockchain technologies to devise a new security and privacy architecture. The eventual solution design, tagged SoftBloC (Software Defined Blockchain Cryptography), has been architected to combine these technologies with the IoT data routing technique (Low Energy Adaptive Clustering Hierarchy, LEACH) to provide security and privacy architecture for a cashierless retail store. We adopted a layered approach to delineate and analyse the key security and privacy concerns, whilst offering effective solutions to mitigate these concerns.
Services of Regional Universal Scientific Libraries: Problems and Approaches to Their Presentation on Websites

Scientific libraries are active social institutions that promptly respond to the challenges of the external environment, changing preferences of readers and users, their needs for different library, information, socio-cultural demands in online and offline spaces, for self-realization of creative and educational potential. Among scientific libraries a special place is occupied by regional universal scientific libraries (RUSL), which take an active part in the formation of educational, cultural, scientific and economic potential of their territories; ensure the creation of a unified regional information and library space; provide services to the population taking into account regional needs and specifics of the region’s development. The projects reflected in the “IFLA Bank of Ideas”, “Library Creativity Bank”, on the Library Map of the World, in the final materials of the All-Russian contests of library innovations, international contests of marketing projects of IFLA libraries, and in the professional press testify to the innovative practice of the RUSL. The results of the analysis of the websites of 50 regional universal scientific libraries of Russia (the main innovators in library services in the regions) are presented, the purpose of which was to identify the problems of reflection of library and information and other services in the web space. The study analyzed free and paid services offered in online and offline modes and ranked their most common types. The results showed gaps in the presentation of library and information and other services on websites (lack of a unified approach to the presentation of services by type and a complete list of all library and information and other services, difficult search for paid services, lack of a section “Services” and visual support for the provision of additional services, etc.), as well as showed a panorama of opportunities to better reflect them for different categories and segments of users. It is concluded that the solution of the above problems will allow public libraries to raise the level of awareness of users and demonstrate the fullest range of stationary, non-stationary and remote services provided on a paid and free basis.
Centralization of the library network in the Penza region (second half of the 1970s - early 1980s)

The subject of the study is the process of centralization of the network of state mass libraries in the Penza region. The research was carried out on the basis of analysis and generalization of documents of the State Archive of the Penza region (the Penza Regional Executive Committee Cultural Management Fund) using the principles of historicism and scientific objectivity and consistency. The author gives a brief overview of domestic (Soviet and post-Soviet) and foreign historiography on the problem of research. Special attention is paid to the preparatory work for the centralization of the library system in the region, in particular, familiarization with this practice in other regions; interaction and support of local Soviet-party bodies; the results obtained from the reorganization of the network. The scientific novelty consists in the fact that for the first time a study of the formation of centralized library systems in the Penza region has been undertaken. In the second half of the 1970s, state mass libraries in the region began to unite into a single library structure - a centralized library system that functioned on the basis of a single administrative and methodological manual, a common staff, centralization of the processes of formation and circulation of funds, their profiling and the possibility of mutual use. By centralizing libraries, the authorities hoped to strengthen political propaganda through the book's reading, expand the functions of library institutions in the information and reference field of serving citizens and providing them with more diverse services, eliminate parallelism in their activities, improve the management model and use of allocated funds, promote better implementation and optimization of library processes. The effectiveness of the centralization of libraries decreased from the prevailing attitude at that time that it should be carried out without additional financial investments.
Estimating surface utilization factors for BIPV applications using pix2pix on street captured façade images

Abstract While techniques for assessing solar potential, particularly on roofs, are well-established, estimating solar potential on building facades often requires more work due to the complexity of urban features and the elaborate design of building facades. Existing methods to assess the solar potential of building facades often neglect the characteristics of individual facades. This study presents an image-based method for a more accurate estimation of the PV potential of facades. The proposed method is composed of four steps: (1) data acquisition, preprocessing, and manual labeling, (2) training a pixel-wise semantic image segmentation model based on Generative Adversarial Networks (GANs), (3) color content analysis of segmented images, and (4) estimating the annual solar energy potential. We apply the proposed workflow to several buildings in Zurich, Switzerland, and evaluate segmentation quality and resulting changes in façade surface utilization factors. In a comparative analysis between the widely used web-based solar potential assessment tools, Sonnenfassade, Global Solar Atlas and the simulation software Climate Studio, we demonstrate the downstream impact of surface utilization factors on resulting solar potentials. Considerable deviations in façade availability for BIPV deployments among the various tools as compared to our segmentation approach indicate the potential impact of the proposed method on policy-making and the benefits for BIPV design and planning.
Airport Transit Hotel Concept Based on Human Sleep Algorithm as a Solution to Sleep Quality Problems in Business Travelers

Abstract Air transportation is an adequate accommodation in energy and time, but in its operation, delays still occur. This condition makes airplane passengers physically and psychologically exhausted, so they need a place to rest. Sleep is a human need to restore energy. This human biological clock is affected by the quality and quantity of their sleep, which are affected by external conditions. Sleeping difficulty also disturbs the productive rhythm of business travelers who are required to be mobile and time efficient simultaneously. In this final project, the Layover-Break approach will answer to this problem. The architectural object in the form of a transit hotel will accommodate the need for a short break for business travelers, by applying the Sleep in Transit method and questionnaire tools and DepthmapX in transforming the formal concept of design to conditions on the site. The design area is at Juanda Airport, Surabaya, East Java. This condition encourages the existence of an architecture that accommodate a person’s rest in a short time but can provide excellent sleep quality by modifying architectural things that can stimulate a person’s restful sleep. The design can be a solution to the application of people’s needs for rest, to accommodate temporary transit activities with an emphasis on the effectiveness and fulfillment of sleep as an experience.
Positive Definiteness of the Sample Covariance Matrix of Multi-poisson Distribution

Abstract Studying the positive definiteness of the covariance matrix of discrete samples helps to determine whether the dimensionality of the samples can be reduced, which is beneficial for optimizing the number of samples and designing optimal plans for sampling surveys. This paper aims to provide a method to determine the variable numbers of the sample subjecting to Poisson distribution. Methods . It is based on the theory of I -linear combination and its properties which are the author’s previous studying results. Results . study shows the covariance matrix of multi-Poisson distribution is positively defined and the probability of the sample covariance matrix of multi-poisson distribution is about 1 when the sample capacity is very large. Conclusion . The dimension size of the sample data matrix of multi-poisson distribution can be reduced when the sample capacity n is no more than the dimension size p .
Low-light Image Enhancement Method Based on Illumination Curve Adjustment

Abstract This paper presents an advanced low-light image enhancement approach based on Zero-Reference Deep Curve Estimation. The technique enhances images through: (1) the integration of the Dynamic Stochastic Resonance equation for enhanced contrast and brightness, leveraging adjustable parameters for optimal image quality, and (2) application of an Anisotropic Diffusion function for image denoising and smoothing, preserving edges and texture details while effectively removing noise. This adaptive algorithm tailors diffusion intensity to local image features, further refining the resulting image quality. Experimental results confirm the efficacy of our approach in improving visual quality and noise removal in low-light images.
Rotational Speed Measurement of a Shaft Using Infrared Sensor with NI Data Acquisition system and LabVIEW

Abstract Rotational speed measurement is the process of determining the number of rotations completed in a unit time. Generally, it is measured in Hertz, radians per second and rotations per minute (RPM). Rotational speed measurement is very critical parameter in condition monitoring, speed control, and supervision of rotational equipment like generators and turbines. This paper presents an alternate method of measuring the speed of a shaft using one of the cheapest infrared sensors available in Nepalese market. The principle of measurement of speed is on the basis of reflected and absorbed infrared light which is acquired using data acquisition unit of National Instrument. The signal processing has been carried out in a LabVIEW program and speed of shaft has been verified using the other optical sensors.
Optimizing SIFT algorithm parameters for better matching UAV and satellite images

Abstract Image registration has been increasingly employed in various applications such as target identification, 3D mapping, and motion tracking. The main idea of Image registration is aligning two or more images of the same scene captured from different viewpoints, at different times. Scale-invariant feature transform, SIFT, is considered one of the most robust algorithms used in image registration for extracting and matching features under different conditions. Using SIFT algorithm default parameters in Matching UAV and satellite Images provides unreliable results due to the nature of aerial images because the dynamic range is quite low. The number of extracted features depends on the image content and the selected parameters. In this paper we tuned SIFT parameters to get the best performance with aerial images, to increase the number of features (SM) and the correct match rate (CMR) which increases the efficiency of the process of registration. The algorithm is validated by matching a large number of aerial images taken by mini-UAV with satellite images for the same region.
ANALISIS KEAKTIFAN SISWA SEKOLAH DASAR DENGAN MODEL PROJECT BASED LEARNING PADA PEMBELAJARAN IPA

This study aims to analyze the activity of elementary school students using the Project Based Learning model in learning science in Class IV MI Muhammadiyah 6 Sekapuk. The type of research used in this research is qualitative research with a descriptive approach. The research was conducted at MI Muhammadiyah 6 Sekapuk. The subjects in this study were 3 grade IV students. Data collection techniques in this study using data triangulation. The data analysis technique used is qualitative data analysis techniques which include data collection, data reduction, data presentation, and drawing conclusions. The results of the research and discussion obtained by the researcher show that when the teacher applies the Project Based Learning model, the activity of the students increases because they like the existence of the project learning model, which makes them more active and do not tend to be silent during learning. Student K has fulfilled 3 of the 7 indicators of student activity, Student I has fulfilled 4 of the 7 indicators of student activity, and Student A has fulfilled 6 of the 7 indicators of student activity. Of the 7 indicators of student activity, the indicator for student participation in the implementation of learning tasks is the indicator that is most mastered by students.