Reviewerly/exHarmony huggingface dataset:
Survey on Graph DB for Impact Analysis in Payment Platforms

Abstract: Impact analysis is the process of analyzing and predicting the consequences of any changes in the system. This analysis is important because it helps to determine which components get impacted when a component goes down or fails and how the system responds to this change. Payment platforms are a composition of several different components such as CBS, databases and SMS G/W, UPI switches. These components are dependent on each other and work together to perform successful transactions. A graph database (Graph DB) is a database that uses graph structures for storing data. Instead of using tables or documents to represent and store data, it makes use of nodes, edges, and relationships. The nodes of the graph contain the data, and the edges between the nodes show how the data are related to one another. Hence, a graph database can be easily used to represent various components of the payment platform and the relationships between them. Graph database makes it easy to understand the effect of change in one of these components on another.
Mall Loyalty: Application Built on AI System

Abstract: Every time we visit a mall, everyone has different purposes. Some visit for shopping of clothes, footwear, or even groceries while few visit for the purpose of eating in the food court. With the increase in the number of people who are moving towards online shopping, there is a need for a system that increases the footfall of people in shopping malls. Hence, we propose a system that works towards achieving this very goal. The project aims at creating a new kind of user experience for customers visiting shopping malls. As customers will be offered personalized service they will get attracted to the mall.
Data Exploring the Impact of Chatting App Features on User Engagement and Satisfaction: A User-Centred Design Approach

Abstract: This research paper explores the impact of chatting app features on user engagement and satisfaction using a usercentered design approach. The study involved conducting interviews with users to identify their preferences for features and conducting user testing to evaluate the impact of specific features on user engagement and satisfaction. The results show that certain features such as privacy and security, design and usability, multimedia sharing, emojis and stickers, and group chats and collaboration have a significant impact on user engagement and satisfaction. The paper concludes by discussing the implications of these findings for the design of chatting apps and providing recommendations for future research in this area.
Pelatihan Pembuatan Kuis Interaktif Menggunakan Ispring Suite dan Kahoot Bagi Guru-Guru SMAN 2 Gerung Lombok Barat

This community service activity is in the form of interactive quiz-making training using the Ispring and Kahoot platforms. This service activity aims to a) Provide an overview of the use of the Ispring suite and Kahoot! software applications. to create interactive quiz questions that can be used as an interesting and fun evaluation tool for students, and b) Provide training on how to create interactive quiz questions using the Ispring Suite and Kahoot! software applications. for teachers at SMAN 2 Gerung West Lombok. The method used is lectures to explain the material, followed by questions and answers and practice. The team also gave tests (pretest and posttest). From the results of the activity, a product is produced in the form of an interactive quiz made using the Ispring or Kahoot applications. In addition, there is an increase in teachers' understanding of the material provided. This can be seen from the percentage of correct answers in the pretest of 32.63%, and the results of the posttest showed the percentage of correct answers to be 64.67%. Based on the results of the activity, it can be concluded that this community service activity is felt to be very useful in increasing the knowledge and skills of teachers on how to make interesting interactive quizzes so as to increase student enthusiasm and interest when participating in learning evaluation activities
Analysis the Feasibility and Constraints of Implementing Next-Technology Mobile Networks in Bangladesh with its outcomes on Human Body

As the range of customers in cellular era will increase at a geometrical rate, the call for and complexity of the provider is rising, making sure within side they want for cellular operators to shift the provider using difficulty to their core technology with the intention to switch extra information with excessive speed. The 5G cell networks is that the consequences of this paradigm shift and is currently being deployed in advanced nations regardless of the reality that they may be capable of put in force 6G cell networks. However, maximum of the growing nations in addition to Bangladesh ( Middle-earnings country) are, or will be, the usage of 3G or 4G cellular networks very lately for which the general position is not but complete. In this study, we are now exploring how a lot emphasis can be positioned on setting up the 5G cell networks in Bangladesh in addition to health effect of 4G and upcoming 5G cellular networks. We first take note of display that there may be capability for tackling foremost technological demanding situations in Bangladesh while putting in place the 5G cellular networks. The numerous protection factors of 5G cellular networks were provided that is an ongoing hassle and Bangladesh goes to technologically ready to deal with many protection issues of it. At the same time, it has been proven that the context of the usage of 5G networks in Bangladesh is relevant at present. As a result, putting in place the 5G networks in Bangladesh will take now not than expected. Finally, the outcomes of the usage of 4G, 5G cellular networks on human health had been presented.
A matrix for making sense of digital competences in formal engineering education curricula

In this paper we present the development of a matrix used to assist study boards and stakeholders in embedding digital competences into their engineering curricula. The matrix was developed by reviewing existing frameworks of digital literacy and competency at the citizen, upper secondary and higher educational levels and modifying them to suit the context of problem- and project-based learning (PBL) in engineering education. The matrix draws together three categories of digital competences (general academic competences, problem-based learning competences, and discipline specific competences) and an interdependent taxonomy of digital competences (user competences, development competences and reflexive competences), resulting in a matrix of nine distinct types of digital competences. The resulting matrix makes accessible the concepts of digital competences enabling different stakeholders in the curriculum design process (study boards, industry advisory bodies, students etc.) to make meaningful contributions to the curriculum development process.
Using measures of psychophysiological and neural activity to advance understanding of psychological processes in politics

Innovation implies successful introduction. Measures of psychophysiological and neural activity have been introduced to political science but the fact they are still rarely used, particularly in mainstream political science, indicates that this introduction has not been successful. Instead, the status quo in political science is to rely on self-reported measures of feelings, beliefs, and opinions. A recent review of research on ``emotion and politics'' in the Annual Review of Political Science underlines this point as it contains very few references to work using measures of psychophysiological and neural activity. We identify three problems with this status quo. First, unconscious (or preconscious) affective processes cannot be measured with self-reports because we are mostly unaware of these processes. Second, the complex interplay between affective and cognitive processes at the neural level cannot be characterized by relying on typical (survey) experimental outcome measures. Third, on socially sensitive topics, people may be motivated to self-report in socially desirable ways. As such, self-reports may even be misleading. In sum, political psychology largely concentrates on more conscious reflections at the expense of potentially relevant preconscious or unconscious explanations or mechanisms. The goal of this chapter is to inspire the next generation of political psychology research to move beyond self-reports and adopt theories and methods that help us to better characterize the affective-cognitive processes of political decision-making. To this end we provide an overview of work using psychophysiological measures (skin conductance, heart rate variability, and facial electromyography (fEMG)), eye-tracking, and neuroimaging measures (electroencephalography (EEG), functional and structural magnetic resonance imaging).
Structural analysis and susceptibility inversion based on ground magnetic data to map the chromite mineral resources: A case study of the Koh Safi Chromite Ore Deposit, Parwan, Afghanistan

Abstract The Koh Safi Chromite Ore Deposit is located in Afghanistan's northern-northeastern end of the Kabul-Kandahar ophiolite zone. Sedimentary formations, delayed volcanic, and ultramafic rock groups, including peridotites and serpentinites, could all have been found in the Koh Safi area, where structural discontinuities with the two trends of northwest-southeast and east-west can be identified. High-grade serpentinite units have many chromite deposits, whereas peridotite has a lot of medium-grade deposits. This paper performs a ground magnetic data analysis based on structural analysis and 3-D susceptibility inversion. The boundaries of structural faults and anomalous bodies are likely delineated in a northwest-to-southeast orientation using a series of derivative maps, including Total Horizontal Derivative, Analytical Signal, and Theta Map. For inversion, many regularization norms that included the range of smooth, intermediate, and compact models were used to examine a particular susceptibility value that occurred in a model cell. The sparse and blocky norms [0,1,1,1] were suggested for our inversion in field data based on synthetic data to determine an appropriate norm. A 3-D inversion of ground magnetic data shows that the highly magnetic zone supposed to be the host rocks seems to be where chromite occurs in the study area.
Assessing Innovative Activity and Commercialization in SMEs – A Study of SMEs in Punjab

Small and medium Enterprises are vital in the economy of any country. They generate employment, business besides supporting big industries. Improvement in the services and products of SMEs ensures their survival and transformation to the bigger institutions, In Pakistan Majority of enterprises are SMEs and are pivotal in strengthening the national economy. How they are improving their working at par with market needs is the subject touched upon very little in Pakistani environment. This study aims at mapping the innovation practices in the SMEs irrespective their sector in terms of commercialization so as to ascertain their strategies for better service and production delivery which is significant in their survival. For the purpose. 250 SMEs, selected through purposive random sampling with the help of SMEDA, Provincial Industries Departments, SECP and Lahore Chamber of Commerce and Industry, around the country were studied. Data was collected through an online questionnaire, based on the work Tim Mazzarol et al (2011), comprising 40 items. 12 respondents were interviewed through semi-structured interviews. This study is of articulation in nature and data was analyzed SPSS and Envivo. The results indicated the patterns and preferences of SMEs towards innovation and commercialization by giving a bleak picture in SMEs. The findings suggest massive change of policies in SMEs to make them real booster of economy.
Corporate Governance and Organizational Performance of Referral Hospitals in Kenya: A Case of Kenyatta National Hospital

In both developed and developing economic context, an important concern in recent years has been corporate governance due to empirical evidence that organizational performance is significantly affected by corporate governance. Tthis study seeks to determine the effects of corporate governance on the performance of referral hospitals in Kenya with a case of Kenyatta National Hospital. The study objectives included how board composition, stakeholder engagement, transparency and structural considerations affect the performance of Kenyatta National Hospital. The study benefits various groups including the government especially the Ministry of Health, top management of referral hospitals and their stakeholders among others. Theoretically, the study was grounded on agency theory, upper echelon theory and stakeholder theory. A descriptive survey design was adopted; both qualitative and quantitative data was gathered. The target population was 248 staff of Kenyatta National Hospital of which a sample was obtained by the use stratified random sampling method. A combination of both the questionnaire method and secondary data collection sheet were utilized to gather both primary and secondary data respectively, which were subjected to both descriptive and inferential techniques of data analysis. The findings established a positive significant correlation between Board composition, Stakeholder engagement, transparency and Structural considerations has a favorable and significant association with the effectiveness of the Balanced Scorecard for organizations. The Pearson correlation value was more than 0.5, which is an unmistakable sign of a strong association between the variables. Strong Pearson coeﬃcients were obtained from the analysis, and it is clear that each predictor variable has an impact on organizational performance. The model between dependent variable had an R squared of 0.697 meaning that is 69.7% of influence on performance of organizations could be attributed to the independent variables. The regression results produced a value for the multiple regression model that showed that all values had a positive factor. Findings revealed that there was an association between employee performance and Board composition, Stakeholder engagement, transparency and Structural considerations. Leaders should be able to balance between organizational needs and stakeholders’ expectations to achieve a good corporate governance practice of public hospitals. Structures can be influenced by mandate of the organization and the board compositions by the technicality of the role being played by an organization. Policy recommendations include: establishing an independent board of directors to oversee the management of an organization, enhancing shareholder participation in decision-making through mechanisms such as proxy voting; and encouraging ethical behavior and a culture of compliance throughout the organization.
A systematic narrative review of pathways into, desistance from and risk factors of financial-economic cyber-enabled crime

Financial-economic cyber-enabled crime (hereinafter: financial cybercrime) has increased dramatically over the past years. However, research on financial cybercrime is still underdeveloped and highly heterogeneous, especially regarding the processes of initiation to and desistance from crime. This paper synthesizes existing knowledge on pathways into, desistance from, and risk factors related to financial cybercrime, and identifies research gaps. Adhering to PRISMA-ScR guidelines, we executed a systematic search and identified 37 eligible documents published as of February 2022, indicating two initiation points into financial cybercrime: involvement in traditional crime, and experiencing strain. Through social learning, individuals then learn the necessary skills and knowledge and engage in financial cybercrime, after which the decision to desist is influenced by a cost-benefit analysis, the use of neutralization techniques, and maturing. As for risk factors, we identified 33, with being male, unemployed, having low self-control and deviant peers, and wanting to earn money quickly being of potential importance. Regarding research gaps, there is a dearth of research related to the initiation and desistance processes of financial cybercrime, and the identified studies lacked a robust research designs, with 76 percent being of low or medium quality. More quality research is needed to address these issues.
A language of episodic thought? (commentary on Quilty-Dunn et al.)

We propose that episodic thought (i.e., episodic memory and imagination) is a domain where LoTH could be fruitfully applied. On one hand, LoTH could elucidate the structure of what is encoded into and retrieved from long-term memory. On the other hand, LoTH can help make sense of how episodic contents come to play such a large variety of different cognitive roles.
Penggunaan Konjungsi dalam Teks Deskripsi Siswa Kelas VII SMP Negeri 41 Padang

This research was carried out for two reasons, maely first to describe the types of conjuctions used in the description texts for class VII students of SMP 41 Padang. The second describe s how the use of conjuctions in the description text of class VII students of SMP 41 Padang. This type of research is qualitative with a describe method. This research was conducted at publick junior high school 41 Padang. The data of this research are sentences that use conjunctions in the description text og class VII students of SMP 41 Padang. The source of the data in this study was the descriptive text of class VII students of SMP 41 Paadang. Data is analyzed by classifying, analyzing, and discussing data based on theory technique. Based on the result of the research that has been done on the description text of class VII students of SMP 41 Padang, it can be conclude that first there at three types of conjuctions used in the description text of class VII students of SMP 41 Padang, namely coordinating conjunctions found as many as 133 conjunctions , subordinating conjunctions founs as many as 158 conjunctions , and conjuctions between sentences found 1 conjunctions. Both the use of conjuctions in the description text of class VII students SMP 41 Padang, found 36 inappropriate uses of coordinating conjunctions, 82 inappropriate uses of subordinating conjunctions , and 1 inappropriate use of inter sentences conjuctions. The percentage of inaccurary in the use of conjunctions in the descriptive text of class VII students of SMP 41 Padang is as follows. The percentage of inaccurary in the use of coordinating conjunction is 27,06% in the medium category, the percentage of inaccuary in the use of subordinating conjunctions is 51,89% in the high category. This is because students do not understand the use of conjunctions properly, besides that there are still many errors in writing conjunctions such as shortening the writing of conjunctions.
Naive Bayes and Wordcloud for Sentiment Analysis of Halal Tourism in Lombok Island Indonesia

Lombok is one of the halal tourist destinations in Indonesia and has been recognized by the world. To examine these assumptions based on sources from tourist opinion, it is necessary to carry out a sentiment analysis whether their presence is as expected. Google Maps is a platform that can show the location of the island of Lombok along with written reviews from tourists who have visited. The collection of review data is done through the Web Scraping technique on the Google Maps Review, then the data is processed using RapidMiner. The algorithm used is Naive Bayes, an algorithm that uses probability or the concept of opportunity in classification. A word cloud visualization is also displayed to bring up words that tourists often say. 1493 data were obtained after Web scraping and cleansing had been labeled with positive and negative sentiment categories. Preprocessing is carried out which includes tokenize, filter token by length, transform case, stopword, and stemming, then classification using the Naive Bayes algorithm. From the results of testing the Naive Bayes algorithm model, an accuracy rate of 74.75%. Word Cloud visualization also found the top words included "indah", "wisata". “pantai”, “alam”, “gunung”, and “masjid”.
Single-image super-resolution via dynamic multi-task learning and multi-level mutual feature fusion

In recent years, deep neural networks have exhibited promising performance in the single-image super-resolution (SISR) task by designing complex network structures from the low-resolution (LR) images to the high-resolution (HR) images and learning the mapping function. However, the SISR task is a widely known ill-posed problem. Since it may map one LR image input to multiple HR images, there are always undesired structural distortions in the recovered SR images. We creatively propose a SISR network with dynamic multi-task learning and multi-level mutual feature fusion (DMMFSR), alleviating structural distortion problems while maintaining more edge structure. Specifically, we utilize a DML block (DMLB) to train low-frequency and high-frequency image information extraction networks so the two networks can mutually promote each other. In addition, we also use a multi-level mutual feature fusion block to fuse image and edge features at different levels. Extensive experiments demonstrate the effectiveness of our proposed DMMFSR. Meanwhile, our model achieves comparable peak signal-to-noise ratio and structural similarity scores on multiple SR benchmarks compared with state-of-the-art SR methods.
Indoor Navigation and Tourist Guide Using Augumented Reality

The suggested project is based on augmented reality concepts for indoor route innovation. When travelling to a remote location, you can use a g-map to navigate outside, but when it comes to the interior, you are left in the dark and helpless. Here is our service that allows you to travel within a faraway city to an open area where you can receive our aid with the improvement of augmented reality. Our app uses augmented reality (AR) images to point users in the right direction inside. For instance, if you received confirmation from a college while travelling there, you don't need to wait for the inside navigation to be completed. It was secured by us. Our suggested strategy will enable you to move freely within the college grounds.
Speech to Sign Language Converter &amp; Vice Versa Using Machine Learning

Taking into account the complications faced by pupils of speech and hearing impaired, we would like to present a tool that connects the gap in communication and facilitate better interaction. In situations where a spoken person is untrained with sign language, the need is unavoidable for a sign language interpreter in order to setup an interchange of expounding. We propose a system that allows two-way conversation between deaf people and people with other voices. In this paper, we present an efficient prototype in two stages. In the early stages, sign language gestures are fed into the system in real time using the device's computer vision capabilities. These gestures are then recognized using our Deep Neural Network while the fine-tuned hand detection with edge detection algorithm interprets it as text as well as audio. The second stage is to convert the audio to text and optionally display the relevant hand gestures for the same The system can recognize more than 300 sign words in Indian Sign Language. .Key Word: Concurrent Neural Networks, Natural Language Processing, Machine Learning, Sign Language Converter, Computer Vision