Reviewerly/exHarmony huggingface dataset:
Design and Development of Deep Learning Based Model for Video Analysis

Abstract: In order to analyze video streams and extract particular features or patterns, such as object recognition, motion detection, facial recognition, or behavior analysis, video analysis employs computer vision and machine learning techniques. Analyzing video footage to spot suspicious activity or items and locate people or vehicles is part of the process. This approach comprises keeping an eye on and controlling traffic at crossings, on roads, and in highways. It entails reviewing video footage to find traffic jams and overcrowding and to offer prompt alerts or suggestions for crowd management
Identification of Positive and Negative Tweets

Abstract: With the development of the Internet, people can obtain and share information almost instantly from a wide array of sources, for example, online news outlets and fast-growing social networks. Over the past few decades, the explosive growth of textual data far outpaces human beings’ speed of understanding its content. Indeed, we have seen the emergence of new types of textual data that reflect social interactions in online settings. The production of this socially-generated content is accelerated by the wide adoption of social media sites, such as Facebook, Twitter, Yahoo! Answers, and Reddit. Text summarization helps in reducing the size of a text while preserving its information content. Text Summarization can be derived as shortening the source text into a version that it’s information content and overall meaning is preserved. It is very difficult for human beings to manually summarize large documents of text. Sentiment analysis on the other hand is the process of computationally identifying and categorizing opinions expressed in text to clarify someone’s’ attitude towards a topic is positive or else negative or even neutral. In this paper we will discuss the use Extractive summarization for the text summarization followed by SVM-algorithm for sentiment analysis.
An efficient lymphography disease prediction using SVM

This paper examines the exhibition of AI methods for computerized evaluation of lymphocytes.This paper proposes a Lymph Diseases Prediction utilizing Genetic Algorithm (GA).In this paper, a Computer-Aided Diagnosis framework dependent on Support Vector Machine (SVM) classifier dependent on GA highlight determination acquainted with work on the productivity of the order precision for lymph sickness conclusion.Highlight choice is a directed technique that endeavors to choose a subset of the indicator highlights dependent on the GA.We planned and carried out hereditary calculation (GA) to enhance includes subset choice for SVM characterization and applied it to the Lymph Diseases expectation.The outcomes show that our GA/SVM model is more exact.
Integration of Kraljic’s Portfolio Model and Purchasing Price Assessment-DEA in Improving Procurement Efficiency

The object of research is one of the companies engaged in aircraft catering using a variety of raw materials.Currently, the procurement department considers that all raw materials are routine raw materials, so the procurement process is carried out repeatedly by suppliers at the lowest prices without entering into contracts or cooperation (regular purchasing).In the absence of contract management, companies lose the opportunity to improve supplier compliance and negotiate price reductions.The decline in supplier performance is also a problem faced, but the procurement department has not assessed supplier performance.With these problems, it is necessary to evaluate the ongoing procurement strategy to improve the efficiency of the procurement process.This study aims to develop recommendations for procurement strategies that include relationships with suppliers and company internal policies.In this study, the preparation of procurement strategy recommendations was taken based on the results of Kraljic's Purchasing Portfolio Model (KPM) which was used to differentiate each raw material based on the level of supply risk and the effect of each raw material on company profits, and the results of the Purchasing Price Assessment-DEA (PPA-DEA) in the category of leveraged goods related to the level of efficiency in purchasing goods.KPM shows that: the group of ingredients for milk, eggs, jam, and chocolate is strategic; dyes, yeast, and coconut milk are classified as bottlenecks; flour and sugar are classified as leverage; oil, packaging, mineral water, utilities, and plastics are classified as non-critical.
Software development of applications oriented to phonological awareness in high school children: A systematic literature review

Today, the role of ICTs is a relevant factor for teaching and learning processes, mainly due to the new educational technologies that have allowed classrooms to evolve considerably in the last 20 years, as is the case at the school level or therapeutic.Specific technologies have been developed for this population; many of those technologies (i.e.hardware, software) use sensors and embedded systems.Although many studies address Phonological Awareness approaches, there have been no systematic reviews of the literature covering tools, methodologies and validations related to technology for developing phonological awareness.Therefore, this article presents a systematic review of the literature of primary studies related to Phonological Awareness and Technology, which focuses on establishing relationships between software, hardware and methodologies that work together to support the development of Phonological Awareness.In this study, 115 articles were extracted; from those, only 36 were selected after applying the corresponding inclusion and exclusion criteria.
Digital transformation model to reduce release time of goods through the blockchain technology in a customs air: A empirical research in Perú

The work presents a proposal to incorporate the use of engineering tools such as blockchain, BPM and a communication plan in the customs services company located in Callao-Peru.For this, a reference framework is proposed by several authors that contemplates a theoretical and conceptual framework of the issues to be addressed.Likewise, the processes of the customs regime, the strategic aspects, process map and the execution for the approach of the problem are indicated.The re-export area is chosen in the same state (Regime 20) where the critical processes will be analyzed, and an optimized improvement model will be proposed.For this work, software such as Bizagi, Arena Simulation and excel data (Datamart) are used.An indicator scheme is developed and the value of the KPIs is displayed.At the end, the conclusions are drawn.
Classification System for the Level of Spread Covid-19 Cases in Bandung Regency Using the Naive Bayes Method

COVID-19 is a disease caused by a new type of corona virus, namely SARS-CoV-2.The most common symptoms of COVID-19 victims are fever, dry cough, and fatigue.This virus has spread to almost all countries, including West Bandung Regency.Transmission of this virus can be directly transmitted from one person to another, of course this is what causes the number of COVID-19 cases to continuously increase.So far, the use of COVID-19 vaccines is being developed, some of which are still in the experimental stage.However, a vaccine that is truly effective against the COVID-19 virus has not yet been found.Therefore, this study aims to classify the level of COVID-19 cases in Bandung Regency to predict the spread of the corona virus and suppress the number of COVID-19 cases so that it does not continue to increase.The method used in this research is to use one of the data mining algorithms, namely the Naive Bayes algorithm as a classification.
How do Gender and Social-Interaction Environment Affect Fraud Perception?

The trend of women choosing a profession in the accounting field is increasing.Based on data from the American Institute of Certified Public Accountants (AICPA) it turns out that 50 percent of accounting graduates are women.The increase affects the development of the number of women who pursue the accounting profession.In 1996 it was recorded that 25 percent of public accountant certificate holders in America were women.Audit quality is needed so that auditing standards become audit guidelines.The phenomenon in the world of auditor practice is still showing various reductions in audit quality (reduced audit quality).There are 2 gender models, (1) equality and complementary contribution models, (2) Sex Role Stereotypes and Managerial Stereotypes.The first model assumes that there are no differences between men and women as professionals in management and that of women, thereby describing equal access.The second model between men and women have different abilities so that they need differences in managing and different in assessing, recording, and combining to produce a synergy.The purpose of this study was to examine the effect of gender and social interaction on perceptions of fraud among government auditors.Questionnaires were used for data collection.The research sample is auditors at the Inspectorate of South Kalimantan Province.A sample of 100 auditor respondents was used to prove the hypothesis.The results of the study state that auditor gender diversity has a significant effect on the perception of fraud, where female auditors have a higher perception of fraud.This means that female auditors have higher ethical behavior so that there is a tendency for female auditors to have higher perceptions of fraud.Social interaction also has a positive and significant effect on the perception of fraud.This means that the auditor in good association, in a religious environment will have a positive ethical view so that he will view fraud as something wrong and illegal.
A Literature Review on Quality Management in the Food Industry

The purpose of this paper is to analyze the quality management practices of the food industry in the past 30 years from 1993 to 2022 based on literature review.102 articles from 53 journals were chosen for the detailed literature review.The focus of attention was solely on the articles related to quality management in the food industry.This study investigated the research time and journals distribution of quality management in the food industry and summarized the research streams.This review describes the application and progress of quality management practice in the food industry, including the global research in this field in recent years, which is mainly concentrated in Europe and Asia.The article is divided into three research streams, and a detailed overview is given.The research results include the determinants of implementing quality management practices, the reasons why researchers have proposed multiple models and frameworks in the food industry through the years, and the importance of tools and techniques used in the implementation of quality management.
The Influence of Employee Perceived CSR on Job Performance: through the mediation of Job Satisfaction and Employee Engagement

Research on Corporate Social Responsibility (CSR) has developed tremendously over the past four decades, especially regarding affective organizational commitment, organizational behavior, and many other variables.However, research on how employee perception on organizational CSR activities and how it relates to job performance are still scant in nature.This study aims to answer these gaps.This study uses quantitative approach using Social Exchange Theory as the underlying argument.Purposive sampling is used in this study with aim on Greater Jakarta area (Jabodetabek), and the questionnaire was distributed using WhatsApp application.As many as 105 respondents returned the distributed questionnaire, in which only 93 is deemed to be worthy of further analyses.Four variables are used to be the focus of this study, namely Employee perception on CSR, Job Performance, Employee Engagement and Job Satisfaction.The study found that Employee perceived CSR directly affect Job Performance.The variable of Employee Engagement partially mediated the relationship between Employee perceived CSR and Job Performance.While Job Satisfaction did not mediate the relationship between Employee perceived CSR towards Job Performance.This study manages to provide contribution in the literature of CSR especially in the perspective of Employee perception on CSR and in the context of developing countries.
Improving Knowledge of COVID-19 for Elementary School Students using Gamified Software

Gamification focuses on applying game mechanics to non-gaming contexts for audience participation and incorporates little fun from routine activities other than generating motivational and perceptual benefits.Businesses, schools, universities, and many other types of organizations have harnessed the potential of gamification.Digital health services also take advantage of emerging trends such as remote monitoring of the elderly during the COVID-19 pandemic.As we read all this information, nothing is made especially for kids.This paper aims to apply gamification in COVID-19 learning and measure the increase in children's knowledge, especially from 6 to 8 years.We performed two measurements; The first is an internal context measurement to test whether the system follows the original design or not.The second is on students.Thirty-five students at several schools participated in the implementation and were surveyed using their automated activity logs and then conducted a seven-day monitoring survey.The results showed a significant increase in the total increase in the average score from the first experiment compared to the best experiment, namely 1.26 times in the corona jump, 2.00 times in the corona quiz, and 1.10 times in the corona labyrinth.On the other hand, we found a 28.57% decrease (10 of 35 children) in quitting the game.This condition proves that children need a lot of scenarios and content to enjoy the gamification process in the long term to achieve all abilities and need to take advantage of game mechanics skills and psychological effects.
Analysis of TIX ID Application User Satisfaction Reviewed from E-Service Quality Using Importance-Performance Analysis (IPA) Method

This research is a type of descriptive research with a quantitative approach.The purpose of this study is to determine the user satisfaction of TIX ID application in terms of e-service quality which consists of seven dimensions, namely efficiency, fulfillment, system availability, privacy, responsiveness, compensation, and contact which will be seen based on the level of importance and level of performance that has been given.The data analysis method used in this study is Importance-Performance Analysis (IPA).This study was conducted with all Indonesian citizens with a minimum age of 18 years old that have used or using the TIX ID application, with a total sample of 413 respondents.Based on the Cartesian Diagram of Importance-Performance Analysis (IPA), the TIX ID application does not have attributes that are in the main improvement priority (Quadrant I), seven attributes that must be maintained (Quadrant II), seven attributes with low priority (Quadrant III), seven attributes with low priority (Quadrant III), and two attributes with a level of performance that exceeds the level of importance (Quadrant IV).The satisfaction level of users of the TIX ID application based on e-service quality is 95.26%.Based on the result of descriptive analysis, it is shown that the value of the user expectations (importance) is greater with 88.67% compared to the value of perceptions/reality (performance) with a percentage of 84.58%.There are seven attributes that have the highest gaps that are included in Quadrant III.In addition, all 16 attributes on the dimensions of the e-service quality variable in this study all have negative value gaps, so that all attributes still do not fully meet user expectations.
Toward Optimum Transformer Model for Sequence-to-Sequence Data Transformation under Low-resource Computation Constraint

Accurate language translator applications running on low-resource computing devices such as smartphone is very instrumental to support tourism industry.The main challenge to achieve such objective is how to optimize performance of machine translation model targeted to limited resource of computing devices.Vanilla transformer model has been well known as one of state-of-theart neural machine translation model.However, the drawback of this model is its large number of parameter models which might not be suitable for low-resource computing devices.This paper presents study findings in efforts to optimize 2 encoder-decoder stack depth of vanilla transformer by exploring several activation functions using fine-tuning approach.The pre-trained transformer model is fine-tuned using parallel corpus Bahasa Indonesia-Sundanese language to address machine translation task.The experiment results found that Sigmoid gives the highest model performance (0.993 average training accuracy and 0.987 average testing similarity) and GeLU gives the lowest model performance (0.987 average training accuracy and 0.980 average testing similarity) of the tested vanilla transformer models.
3D Zombie Hunting Game using VR

A first-person shooter game with full shooting is called 3D VR Zombie Hunter. The game’s setting will be a 3D indoor environment model, which will be created in accordance with the game’s specifications and improve the appeal and realism of the setting. The mapping of the VR-Box joystick is used in this game to assist with shooting, reloading, and player movement. The joystick has a total of 6 buttons, including the major 4 buttons and a joystick that can be moved 360 degrees. The game’s shooting and reloading functions are performed by the supporting 2keys. The addition of a joystick will make the VR-Box experience even more maneuverable. Bluetooth will be used to link mobile head sets and joystick buttons for long-range wireless connectivity and to activate key gaming features. The gadget will translate the joystick buttons you press to enable in game functionality. Players will have an immersive and interactive first-person shooter experience with the 3D VR Zombie Hunter game. Players will be able to direct the movement and actions of their virtual character in the game by using a VR-Box joystick with Bluetooth connectivity and a variety of buttons for various in-game tasks. The game will be more realistic and immersive thanks to the use of a 3D indoor environment model. It will be interesting to see how players’ gaming experiences are improved by the joystick’s mapping to the VR-Box and mobile headset.
Reflexión sobre el uso de las wikis como herramientas de aprendizaje cooperativo

This paper presents the utilization of two different wikis, used as learning and grading tools in two school years (2019-2020 and 2021-2022) in the course Metropolitan Mobility and Transport Terminals, from the Civil Engineering Degree, specialization in Transport and Urban Services. Through the development of wikis, students share the responsibility of building knowledge, which is motivating for them and results in a more active learning. In addition, improved results are attained through the interaction among students, in relation to those which would be achieved individually. Via the design of these activities, the lecturer of the course and author of this work ensures the acquisition of both specific competencies for the course and some of the more relevant transversal competencies for the professional practice. In addition, students are approached to their future professional activity making them face existing real-world problems related to the subject taught during lectures.
Learning Asian Languages Using Online Platforms during Pandemic Times: Evidence from Indonesian Youth

Asian languages such as Mandarin, Japanese, and Korean have become popular among Indonesian youth, as more people are interested in acquiring the foreign languages.However, due to the ongoing COVID-19 pandemic, face-toface learning approach has been restricted.This leaves a window of opportunity for online platforms to fill the gap by providing the means to learn Asian languages for the Indonesian young generation who tend to consume pop culture products from China, Japan, and Korea.This article examines the experience of Indonesian youth in learning the mentioned Asian languages using online platforms during pandemic times.An online survey conducted in March 2022 with a sample of study consists of 310 research participants aged 16 to 30 years old, and 14 of them agreed to take part in the interview sessions.The findings suggest that the Indonesian young population continue to show substantial interest in learning Asian languages, especially Korean (85%), followed by Japanese (68%) and Mandarin (51%).Around 84% of participants were satisfied using online platforms to learn foreign languages.Nevertheless, learning foreign languages online is not always smooth sailing, as internet connection often hinders learners to maximize their excellent experience with the process.
Automatic Classification Method for Oracle Images based on Deep Learning

There are some problems in oracle image classification, such as high image-feature extraction error and low classification accuracy, which leads to low efficiency. Therefore, we designed an automatic classification method for oracle images based on deep learning. The clustering center of an oracle image is determined using k-means algorithm. The obtained oracle image block is used as parallel input to extract a dictionary. The oracle image features are output through a feature mapping function for feature extraction. The CS algorithm is used to reduce the dimension of the oracle image, and the oracle feature compressed sensing signal is sparse under a certain basis for preprocessing of image features. The center of six feature points in the features is used to describe the center of the feature points of the whole oracle image, to determine the position change state of the feature points, and to characterize the key features of the image to achieve the target alignment of oracle image feature points. Based on this, the image feature data are learned using a transfer learning model. The automatic classifier was constructed through a convolution neural network. Experimental results show that the proposed method can effectively reduce the error of image feature extraction and improve the classification accuracy. At the application level, the research results of this paper have brought great improvement to the performance of oracle image classification technology. At the theoretical level, this research introduces k-means and CS algorithms to oracle image classification technology based on deep learning and makes an effective exploration in the direction of this technological progress.