Reviewerly/exHarmony huggingface dataset:
Design and fabrication of solar powered wheelchair

As per the census, 2011 in 2016 disabled population of India was around 2.66 Cr and currently, it is about 3 Cr, talking about the physically disabled the count is 54,36,826. Around 70–75% are above 15 years of age. Conventional manual wheelchairs need to be handled by the other person ultimately they have to rely on others for their movement and daily activities which may cause mental depression among them and sometimes they hesitate to ask for help so electric wheelchair is the best option in this situation. But due to the continuous decline of fossil fuels, there is a need to find alternative renewable sources; here solar energy is a good solution. In this paper, study shows conventional wheelchairs and their conversion into an electric wheelchair which is semi-automated using sensors and controllers. This paper studies power consumption and shows that by using renewable sources of energy we can save 60–70% of the energy and once the battery is charged it will give 3–4 h of runtime. From the following research study, it can be concluded that designed wheelchair is having good features and would be very convenient and friendly to the aged people and handicapped. The device will be very useful to people suffering from disabilities and physical problems that they can take advantage of, as well as an eco-friendly device that works on renewable sources of energy. The frequency of charging is acceptable, improving the present scenario in said area of research.
Entrepreneurial Strategies for Managing Disruptive Innovations

Contemporary studies on disruptive innovations have identified entrepreneurship as veritable driver of the disruptive phenomenon. Disruptive innovation describes a new product or service that is so innovative that it disrupts the existing market and forces businesses in that market to devise new strategies for managing their business to avoid suffering huge losses and possibly going out of business. This paper integrates recent developments from entrepreneurship and innovation research streams to better understand the conditions and causal mechanisms that influence disruptive innovations. The rise and fall of firms especially in high technology industries under the dynamic effect of disruptive innovations have been a theme of inquiry that has fascinated many scholars in economics, technology and change management disciplines. This conceptual paper carried out a diagnostic review of disruptive innovations and found that disruption of existing market creates new phenomenon that ultimately delivers new value to consumers and the society. The study therefore recommended that organizations operating in today’s digital dispensation should not fear disruptive innovations but rather embrace them and devise strategies for managing the disruptions to enhance their business bottom-line.
Cryptocurrency: An Overview of its History, Technology and Future Prospects

Cryptocurrency has emerged as a novel form of digital currency that operates independently of traditional financial institutions. This research paper provides an overview of the history and technology behind cryptocurrencies, including the development of Bitcoin, the first and the most well-known cryptocurrency. We explore the decentralized nature of cryptocurrencies, their advantages and disadvantages, and the underlying blockchain technology that enables their secure operation. Additionally, we examine current and prospects for cryptocurrencies.
Using Student Performance Data for Music Score Collection Assessment and Development

ABSTRACTABSTRACTThis case study examines the use of performance data from recital programs to inform collection analysis and development for printed music scores. Analyzing performance data in comparison to library collections can highlight instrument and voice areas that are underrepresented in libraries and aligns library collections with local performance practices. Using performance data may also be used to influence stakeholders about investment in score collections and identify repertoire likely to be used by students and faculty.KEYWORDS: Collection analysiscollection developmentmusic scoresperformance datalibrary music collections Disclosure statementNo potential conflict of interest was reported by the author.Correction StatementThis article has been republished with minor changes. These changes do not impact the academic content of the article.
Polarization-Intensity Joint Imaging for Marine Target Automatic Recognition

The performance of sole optical imaging device for marine target recognition is degraded by sea fog, sea-glint, and many other disturbing factors. To enhance the ability of target recognition in marine environment, we propose a polarization-intensity joint imaging method and the corresponding processing method. We combine fine imaging of polarization in a small field of view with wide-field imaging of visible light intensity, using visible light intensity information for large-scale target surveys. After locking onto areas of interest, we utilize high-resolution polarization cameras with small fields of view for detailed inspection, and enhance and fuse the information from areas of interest using the proposed matching information processing method. Meanwhile, to deal with problems existing in the marine environment polarization-intensity joint imaging, such as details loss in DoP (degree of polarization) image, low target resolution in the large field of view intensity image, and insufficient information in a single image, etc., we extract the details of raw image from DoFP (division-of-focal-plane) polarization camera as residual compensation for DoP image super-resolution and cooperate with the RealSR algorithm to super-resolve the local target details of the intensity image in a large field of view. On the premise that PIQE (Perception-based Image Quality Evaluator) reaches the excellent score range, the images with the same resolution are fused. The automatic recognition comparison before and after processing proves that the accuracy of target recognition can be effectively improved after processing.
Feasibility of Visual Question Answering (VQA) for Post-Disaster Damage Detection Using Aerial Footage

Natural disasters are a major source of significant damage and costly repairs around the world. After a natural disaster occurs, there is usually a significant amount of damage, and with that, there are also a lot of costs involved with repairing and aiding all the people involved. In addition, the occurrence of natural phenomena has increased significantly in the past decade. With that in mind, post-disaster damage detection is usually performed manually by human operators. Taking into consideration all the areas one has to closely look into, as well as the difficult terrain and places with hard access, it becomes easy to understand how incredibly difficult it is for a surveyor to identify and annotate every single possible damage out there. Because of that, it has become essential to find new creative solutions for damage detection and classification in the case of natural disasters, especially hurricanes. This study focuses on the feasibility of using a Visual Question Answering (VQA) method for post-disaster damage detection, using aerial footage taken from an Unmanned Aerial Vehicle (UAV). Two other approaches are also utilized to provide comparison and to evaluate the performance of VQA. Our case study on our custom dataset collected after Hurricane Sally shows successful results using VQA for post-disaster damage detection applications.
Effective Contract in Higher Education: Intentions and Outcomes

The issue of the academic contract in the Russian higher education is associated with the salary systems reform in social sector and scientific field according to the adoption of the Decree of the President of the Russian Federation from May 7, 2012 No. 597 “On Measures for the Implementation of the State Social Policy”. Institutional project of the effective contract was aimed to solve two problems. Firstly, to raise the level of wages. Secondly, to its orientation to increase performance (i.e. outcomes-based payment). Over the past ten years in practice an effective contract evolved from innovation to university routine. On the other hand, researchers moved from substantiating approaches and elaborating methodologies to analyzing the experience of implementing an academic contract and then to evaluating its outcomes. The purpose of this study is to show the outcomes of the implementation of the effective contract project in the higher education system in two directions. Firstly, the achievement of target indicators for increasing the level of salaries of university teachers. Secondly, stimulating more efficient activities. Data from the Monitoring of higher education institutions effectiveness in 2021 is used in the study, and it includes data on 1222 universities. There is information on the average salary of university teachers (excluding part-time workers and civil contract staff) for 2020 for each educational institution, as well as on the ratio of teaching staff salary to the average salary in the region’s economy for 2016-2020. It was revealed that the task of introducing an effective contract for the increasing of salaries is generally being fulfilled but with significant difficulties due to the economic factors. The stimulating impact of an effective contract on the activities of university teachers is realized in conjunction with the solution of the tasks of increasing the effectiveness of the functioning of the universities themselves.
The Position of the University in the Infrastructure, Which Supports Technological Entrepreneurship

The article’s goal is to eliminate the contradiction between the need for university activities to support and develop technological entrepreneurship and the lack of a sequence of steps leading to the achievement of the desired result. This contradiction is proposed to be resolved by identifying the position of the university in the infrastructure supporting technological entrepreneurship. The paper highlights three main infrastructural positions of the university, called “Supplier of Talents”, “Platform of Academic Technological Entrepreneurship” and “Technological Entrepreneurial Hub”. The first focuses on the development of creative thinking of students seeking to develop high-tech products and support their entrepreneurial intentions. The second focuses on the achievements of university researchers, based on which promising high-tech start-ups are launched and profitable small innovative enterprises are developed. The third relies on mediation and facilitation to coordinate communications between key parties for promoting high-tech business. In this position, the university is an access point to the main success factors of a technological entrepreneurial project. It is more than others capable of stimulating the economic development of the region. One university can hold several positions. Each of the listed positions is endowed with functional characteristics corresponding to their purpose and performs the tasks assigned to them. Starting from an infrastructural position close to the university, it becomes possible to clearly define the criteria that the university needs to have to effectively fulfill these tasks. And the presence of criteria makes it possible to identify dominant problems, adapt university resources, and bring social practices and educational technologies into line.
Study Stream Website using Java Spring Boot

Earlier students were facing issues to learn new courses by using multiple web applications such as Udemy, Coursera etc. or to attend live sessions in the different applications such as Google Meet, Zoom etc. Students always wanted a software in which this all the features are available which will help them to stay committed towards their learning the skills. This proposed web application will provide the students to overcome all the problems faced by them in this web application such as they can be provided with courses here and they also can attend the live sessions. This web application is developed over Spring Boot - a powerful Java framework which is used to develop the stand alone web applications and can be easily deployed over the web application as it contains all the pre-defined Java frameworks
Reimbursement Application Using Rest API Methods and Android-Based Flutter Framework (Case Study: PT. Protonema)

PT. Protonema is a company engaged in the field of information technology, namely as a consulting partner in Jakarta. This company has provided various kinds of facilities to employees to support their work and simultaneously to improve their quality of life who are concerned about the importance of self-development and provide health insurance. Employees can submit claims to obtain these facilities by attaching receipts as further evidence that the company reimburses the costs that have been incurred, this is often referred to as reimbursement. Submission of reimbursement by employees based on the current process has problems, such as the absence of notification of claims submitted by employees whether the claim is accepted or rejected and still using Microsoft Word which is eventually printed into this archive, it is feared that it will be lost or forgot to save it because scattered archives. The purpose of writing this research is to produce an Android-based reimbursement submission application at PT. Protonema with the REST (Representational state transfer) API (Application Programming Interface) method as a data exchange medium and supported by MySQL so that data processing is precise and safe because it is stored in a database and other supports, namely the Flutter framework, are used to design Android applications. In making this software using the waterfall model and data collection techniques, namely observation, interviews and literature study. From this research, it can be concluded that an Android-based reimbursement application using the REST API method and supported by MySQL can help PT. Protonema in managing employee reimbursement applications more efficiently and effectively. By using this application, employees can submit reimbursement requests easily and quickly via their cellphones, and the data obtained will be recorded correctly and safely in the database. The use of the Flutter framework also helps in designing the appearance and functionality of applications that are easier to use and accessible to employees. Therefore, this application can be an effective solution to increase the efficiency and effectiveness of employee reimbursement management at PT. Protonema.
Physicians’ Perspectives on a Multi-Dimensional Model for the Roles of Electronic Health Records in Approaching a Proper Differential Diagnosis

Many healthcare organizations have adopted Electronic Health Records (EHRs) to improve the quality of care and help physicians make proper clinical decisions. The vital roles of EHRs can support the accuracy of diagnosis, suggest, and rationalize the provided care to patients. This study aims to understand the roles of EHRs in approaching proper differential diagnosis and optimizing patient safety. This study utilized a cross-sectional survey-based descriptive research design to assess physicians' perceptions of the roles of EHRs on diagnosis quality and safety. Physicians working in tertiary hospitals in Saudi Arabia were surveyed. Three hundred and fifty-one participants were included in the study, of which 61% were male. The main participants were family/general practice (22%), medicine, general (14%), and OB/GYN (12%). Overall, 66% of the participants ranked themselves as IT competent, most of the participants underwent IT self-guided learning, and 65% of the participants always used the system. The results generally reveal positive physicians' perceptions toward the roles of the EHR system on diagnosis quality and safety. There was a statistically significant relationship between user characteristics and the roles of the EHR by enhancing access to care, patient-physician encounter, clinical reasoning, diagnostic testing and consultation, follow-up, and diagnostic safety functionality. The study participants demonstrate positive perceptions of physicians toward the roles of the EHR system in approaching differential diagnosis. Yet, areas of improvement in the design and using EHRs are emphasized.
Research and Optimization of a Lightweight Refined Mask-Wearing Detection Algorithm Based on an Attention Mechanism

To address the current problems of the incomplete classification of mask-wearing detection data, small-target miss detection, and the insufficient feature extraction capabilities of lightweight networks dealing with complex faces, a lightweight method with an attention mechanism for detecting mask wearing is presented in this paper. This study incorporated an “incorrect_mask” category into the dataset to address incomplete classification. Additionally, the YOLOv4-tiny model was enhanced with a prediction feature layer and feature fusion execution, expanding the detection scale range and improving the performance on small targets. A CBAM attention module was then introduced into the feature enhancement network, which re-screened the feature information of the region of interest to retain important feature information and improve the feature extraction capabilities. Finally, a focal loss function and an improved mosaic data enhancement strategy were used to enhance the target classification performance. The experimental results of classifying three objects demonstrate that the lightweight model’s detection speed was not compromised while achieving a 2.08% increase in the average classification precision, which was only 0.69% lower than that of the YOLOv4 network. Therefore, this approach effectively improves the detection effect of the lightweight network for mask-wearing.
An Experimental Study on the Implementation of a STEAM-Based Learning Module in Science Education

Over the last decade, there has been notable academic interest in the multidisciplinary studies of science education with the emergence of STEAM. Accordingly, this study aimed to conduct an experimental study to explore the effectiveness of a STEAM-based space-themed learning module in science education taught to primary school students. The sample of the study was 6th- and 7th-grade students from the Central Anatolia Region of Turkiye. The experimental group consisted of 180 students, whereas the control group consisted of 94 students. The STEAM-based learning module was applied to the students in the experimental group, and the traditional lecture-based approach was applied to students in the control group. The traditional education and intervention lasted eight weeks. The chi-square test and one-way ANOVA were used to analyze the differences and associations between the variables. The results indicated that gender and academic achievement level were the two key factors determining the effectiveness of the STEAM-based learning module. The comparison of the pre-test and post-test scores indicated that the scores of the female students who participated in the module increased the most. This suggested that girls benefited more from the STEAM-based learning module than boys. Further, the lecture-based approach led to a decrease in some high-achieving students. The findings have implications for educational policymakers, curriculum developers, and syllabus designers.
Adversarial Interactive Cartoon Sketch Colourization with Texture Constraint and Auxiliary Auto‐Encoder

Abstract Colouring cartoon sketches can help children develop their intellect and inspire their artistic creativity. Unlike photo colourization or anime line art colourization, cartoon sketch colourization is challenging due to the scarcity of texture information and the irregularity of the line structure, which is mainly reflected in the phenomenon of colour‐bleeding artifacts in generated images. We propose a colourization approach for cartoon sketches, which takes both sketches and colour hints as inputs to produce impressive images. To solve the problem of colour‐bleeding artifacts, we propose a multi‐discriminator colourization framework that introduces a texture discriminator in the conditional generative adversarial network (cGAN). Then we combined this framework with a pre‐trained auxiliary auto‐encoder, where an auxiliary feature loss is designed to further improve colour quality, and a condition input is introduced to increase the generalization ability over hand‐drawn sketches. We present both quantitative and qualitative evaluations, which prove the effectiveness of our proposed method. We test our method on sketches of varying complexity and structure, then build an interactive programme based on our model for user study. Experimental results demonstrate that the method generates natural and consistent colour images in real time from sketches drawn by non‐professionals.
Study on mobile applications for irrigation in agriculture field

Water is a crucial input for agriculture, for good crop production. In today’s scenario, application of technology in agriculture field is very much needed as the time and resources are becoming limitation and costly. Mobile applications are becoming handy for any kind of work which can be done using mobile, internet and various softwares. This study is based on a detailed study of Mobile applications for irrigation scheduling for farmers’ field. The result of study reveals that real time use of Mobile application on agricultural field helps farmers to be aware about irrigation methods, irrigation water amount, crop water requirement, irrigation time etc. Also, real time application of Mobiles, connect farmers with current global scenario. Mobile applications are found effective Information Technology measure for extension of information and service provider for farmers of Digital India.
Federated Learning Strategies Over Wireless Channels

Machine learning over distributed data collected by many clients has important applications in use cases where data privacy is a key concern or central data storage is not an option. Federated learning has introduced solutions for these scenarios, unlike the client-server approach, where all the training data is centralized in the server side, the clients, in a federated learning approach, perform machine learning updates locally over their data and the central server merely aggregates the resulting models without accessing the client’s local data. Article reviews the characteristics and learning objectives of the federated learning setting and gives an overview of the base algorithms that have been developed for FL, compare between FEDAVG and Consensus algorithm and shows the drawbacks and advantages of Consensus algorithm.
An empirical analysis for software robustness vulnerability in terms of modularity quality

Abstract Modern software architectures such as microservices provide a high degree of scalability, changeability, and maintainability in application development. Furthermore, enabling controlled failure of microservices can provide abstract‐level solutions to design more resilient applications. In this paper, we introduce modularity vulnerability to analyze the vulnerability of a modular software design model under the failure of m top‐rank modules by the proposed structural metrics. The study analyzes the modularity quality coefficient (MQC) under the failure of the critical modules identified using the proposed parameter‐based greedy strategy. We conduct a comprehensive analysis of the software design generated by well‐known models and online datasets and provide a perspective for reasoning about the correlation between modularity metrics. The results show that the failure of the modules with the highest cluster factor (CF) value leads to a maximum decrease in the software modularity quality. Finally, we show a linear correlation between CF and the variations of the MQC, implying stability in the software modularity analysis (SMA) problem.