Reviewerly/exHarmony huggingface dataset:
Data Mining Using Neural Network for Research Topic Classification Based on Institutional Research Roadmap

In the last five years, lecturers and students at the Faculty of Medicine at the Islamic University of Bandung have produced hundreds of studies. Still, studies on the suitability of various studies with topics according to the institution's research roadmap have not been carried out. This research aimed to classify research documents based on 12 research roadmap topics. The data used in this study are the research titles of lecturers and students in 2015-2021, amounting to 1064 data. The document extraction process uses text mining, while the document grouping process is carried out using a supervised method with an artificial neural network algorithm. At the text mining stage, preprocessing procedures are carried out in case folding, tokenization, and filtering, followed by analysis through weighting using IDF and evaluating accuracy, precision, and recall. The Neural Network Algorithm can classify by level. The classification results using the neural network algorithm show that overall from the training data, the average precision is 74.7%, recall is 74.3%, and accuracy is 74.3%. Of the 12 research topics, the training dataset obtained high accuracy, precision, and recall values found on herbal medicine, Islamic insert, industrial health, tuberculosis, and vaccination. The four topics are in line with the five institution's leading research topics. The results of dataset testing analysis found that the research topics carried out by students and lecturers of Unisba School of Medicine were distributed among the 12 research topics on the institutional roadmap with the increased trends in institutional leading research topics.
STRUCTURAL SYNTACTIC ANALYSIS OF NOUN PHRASES IN INDONESIAN

Syntax is a part of linguistics that studies how words are combined into sentences and phrases. In this study, we focus on analyzing the syntax of noun phrases in Indonesian. We use the treebank analysis technique to identify the syntactic structure of noun phrases in Indonesian. Study results show that noun phrases in Indonesian have complex and varied syntactic structures and that the context and types of noun phrases play an important role in influencing the syntactic structure of noun phrases. These findings are important for understanding how noun phrases are formed and understood in Indonesian and how it affects language processing.
A Review of the Research of Practical Activity Curriculum in Chemistry

The practical activity course of chemistry is a new form of chemistry teaching and reform, which conforms to the new curriculum standard of chemistry in basic education, the new textbook of chemistry and the idea of the new college entrance examination evaluation system.It is an important way to develop students' core quality and improve teachers' professional ability.Through literature research, the connotation, basic elements, characteristics and design framework of discipline practice activities are clarified.Subject practice curriculum belongs to integrated practice curriculum, which is a unique form of Chinese curriculum.Through analyzing the related research of integrated practice curriculum and other subjects, the author extracts the general ideas and methods of constructing practical activity curriculum.By summarizing the differences and connections between comprehensive practice curriculum and discipline practice curriculum, this paper provides theoretical and practical reference for the design and implementation of chemistry practice curriculum in the curriculum development community.
Incorporating Spatial-Visual Topology In Mobile Augmented Reality Application To Enhance Visual Realism

Augmented Reality (AR) advancements on mobile devices which have seen now overgrowing, mirrored in the increased use of portable handheld devices referring to mobile phones and tablets in recent years which led to a sub-set of AR: mobile ARs (MAR). Nevertheless, in MAR, research is still lacking, especially research that focuses on implementing instructional based MAR application with appropriate degree of visual realism to support Spatial Visualization Ability (SVA). Thus, this paper provides an overview of implementation visual realism degree incorporate with Spatial-Visual Topology (SVT) in MAR application. First, we outline two main visual realism degree that applicable to implement in MAR application, which is Physical Realism (PR) and Functional Realism (FR). Then, we identify and applied appropriate SVT in each visual realism degree that offers important insights into the development of MAR application. We then discuss the advantages and drawbacks of each SVT and draw up an evaluation among the different visual realism degree and SVT. The paper provides an overview to propose new insight of design and developing instructional based MAR application to support SVA. Finally, the aim of this paper is to provide researchers with valuable understanding in implementation visual realism degree in MAR application and SVT concept to support SVA.
Performance Evaluation of State-of-The-Art 2D Face Recognition Algorithms on Real and Synthetic Masked Face Datasets

Face recognition systems based on Convolutional neural networks have recorded unprecedented performance for multiple benchmark face datasets. Due to the Covid-19 outbreak, people are now compelled to wear face masks to reduce the virus's transmissibility. Recent research shows that when given the masked face recognition scenario, which imposes up to 70% occlusion of the face area, the performance of the FR algorithms degrades by a significant margin. This paper presents an experimental evaluation of a subset of the MFD-Kaggle and Masked-LFW (MLFW) datasets to explore the effects of face mask occlusion against implementing seven state-of-the-art FR models. Experiments on MFD-Kaggle show that the accuracy of the best-performing model, VGGFace degraded by almost 40%, from 82.1% (unmasked) to 40.4% (masked). On a larger-scale dataset MLFW, the impact of mask-wearing on FR models was also up to 50%. We trained and evaluated a proposed Mask Face Recognition (MFR) model whose performance is much better than the SOTA algorithms. The SOTA algorithms studied are unusable in the presence of face masks, and MFR performance is slightly degraded without face masks. This show that more robust FR models are required for real masked face applications while having a large-scale masked face dataset.
Modifikasi Algoritma Controlling Expansion Dalam Meningkatan Kapasitas Penyisipan Data Hiding

Stegonography is the art of hiding messages in other media. Stegonography is widely used to send secret messages without being known by other people by using digital media in the form of image files so that besides the sender and recipient no one knows or is aware that there is a secret message in it. Several researchers have developed these methods such as Difference Expansion, Reduced Difference Expansion, Quad Difference Expansion and Controlling Expansion. These methods have been able to recover and improve data embedding but during the running process there are several problems that often occur, namely overflow and underflow of pixel values. To overcome the above problems, we modify the Controlling Expansion algorithm by minimizing the condition of the pixel difference value and reducing the final pixel difference value after inserting the data bit and using the Location Map on the new pixel value and during secret data extraction. The experimental results show that the proposed method can increase the data storage capacity and the PSNR of stego images is higher than the previous method.
Investigating the Influence of Chief Executive Officer Characteristics on Accounting Software Technology Use among Jordanian Firms

This study aims to examine the influence of chief executive officer (CEO) characteristics (i.e., CEO innovativeness, CEO information system (IS) knowledge, and CEO trust in technology) on accounting software technology use in Jordanian companies from different industrial sectors. Data were gathered through a structured questionnaire distributed to CEOs/owners of small, medium, and large companies in Jordan. The Partial Least Squares Structural Equation Modeling (PLS-SEM) technique was employed on 315 usable questionnaires received. The finding reveals that CEO IS knowledge and CEO trust in technology have a significant positive impact on accounting software use. Surprisingly, CEO innovativeness has an insignificant impact on accounting software use due to the prevalence of avoiding uncertainties in undertaking a new system. The outcomes of this study can assist the government in devising relevant policies and support initiatives to encourage firms to adopt accounting software technology. Similarly, CEOs can benefit significantly from gaining a deeper understanding of the principal factors influencing accounting software use.
AUTOMATED ATTENDANCE SYSTEM USING FACE RECOGNITION

Attendance is compulsory in every school or university for keeping a record of the student attending the class. The biometric is applied in the system proposed, which uses face recognition for ease of attendance taking. The automated attendance system uses the proposed face recognition to overcome the weaknesses of manual and traditional attendance systems that cause learning time to be delayed, handwriting that confuses the lecturer and also the concentration of the student to be affected. This paper aims to identify the method used for detection and recognition to develop and evaluate the system. Therefore, the Viola-Jones algorithm is used in detection of student faces and Local Binary Pattern Histogram is used for recognition when it compares the student face with the images in the database. The system flow starts with capturing the image of the student in class, detecting their faces, processing the image for a better image and then extracting the feature. The results have shown the accuracy of face detection is more than 90% because some of the faces cannot be detected due to the different angles, while the accuracy for face recognition varies between 18% to 80% due to the different numbers of images trained for each person.
Bengkel Inggris Program For Enhancing English Potencial

The era of rapidly developing scientific and technological progress has opened up opportunities for international communication through English. The study was conducted to analyze the potential of elementary school students in English skills in Klambir Lima Kebun Village. Realizing this reality, the "Bengkel Inggris" program is offered to be one of the solutions. The program further investigates the causes of their difficulties in English. In addition, the " Bengkel Inggris " program is not only a place to learn English but also a place for consultation about English. As a result, there was an increase in both classes as seen from the scores on the pre-test, cycle 1 test and cycle 2 test. In the basic English class, the scores are 65, 73.5 and 89.5 while in the intermediate English class the scores are 65.83, 73 and 88.75. Therefore, it was concluded that English Workshop is a program to improve the English learning achievement of elementary school children in Klambir Lima Kebun.
Utilizing Microsoft Teams to Enhance Students’ Competence in Writing Recount Text

Students’ writing competence is one of language skills that should be improved. This study aimed at describing the utilization of Microsoft Teams and finding out whether it can enhances the students’ competence in writing historical recount text. The design of action research used the modification of Kemmis and McTaggart’s model. The research finding showed that the total of the successful students in learning for the first cycle was 41,94%, while for the second cycle was 87.1%. It means that the utilization of Microsoft Teams can enhance the students’ competence in writing historical recount text.
[The directionality of measurement bias: a directed acyclic graph-based structural perspective].

Measurement bias (MB) has been described in causal structures but is still not entirely clear. In practice, the correctness of substitution estimate (SE) of effect is a prerequisite for causal inference, usually based on a bidirectionally non-differential misclassification between the measured exposure and the measured outcome. Based on a directed acyclic graph (DAG), this paper proposes a structure for the single-variable measure, where its MB is derived from the choice of an imperfect, "input/output device-like" measurement system. The MB of the SE is influenced both by the measurement system itself and by factors outside the measurement system: while the independence or dependence mechanism of the measurement system still ensures that the MB of the SE is bidirectionally non-differential; however, the misclassification can be bidirectionally non-differential, unidirectionally differential, or bidirectionally differential resulted from the factors outside the measurement system. In addition, reverse causality should be defined at the level of measurement, where measured exposures can influence measured outcomes and vice versa. Combined with temporal relationships, DAGs help elucidate MB's structures, mechanisms, and directionality.测量偏倚（MB）的因果结构已有阐述但仍不完全明确；实践上，暴露与结局间效应的替代估计值（SE）的正确性是因果推断的前提，通常基于测量的暴露与测量的结局间双向无差别的错分。本文提出了基于有向无环图（DAG）的单个变量测量的结构，其MB来源于对不完美的、类似“输入/输出设备”的测量系统的选择。SE的MB受到测量系统本身和测量系统外因素的双重影响：虽然测量系统的独立性或依赖性机制仍可确保SE的MB表现为双向无差别的错分，然而测量系统外因素对SE的MB则可表现为双向无差别、单向或双向有差别的错分。此外，反向因果关系是定义在测量水平上，测量的暴露可以影响测量的结局，反之亦然。结合时序关系，DAGs有助于阐明MB的结构、机制和方向性。.
Pengembangan E-LKPD Berbasis Discovery Learning pada Materi Teks Negosiasi Siswa Kelas X SMAN 1 Sarolangun Provinsi Jambi

This study aims to describe how the design of the E-LKPD model is based on discovery learning, how to develop E-LKPD based on discovery learning and analyze the feasibility of discovery learning-based E-LKPD on negotiation text material to be developed at SMA Negeri 1 Sarolangun. This type of research is development research that adopts 4D development (Define, Design, Developmet, Disseminate) with modifications, without disseminate stage (deployment). The research and development steps are problem identification and analysis, product design, development, and validation. Research instruments in the form of teacher interview sheets, student needs analysis questionnaires, material expert validation sheets, media experts analyzed using a likert scale. The results showed that: (1) a discovery learning-based E-LKPD has been designed with development on aspects of negotiation text material, (2) after the design is carried out, then a discovery learning-based E-LKPD is developed on the negotiation text material through liveworksheets, (3) the feasibility of developing a discovery learning-based E-LKPD which is assessed by the material expert is in the very valid category (91.2%) or is declared suitable for use and according to media experts The developed E-LKPD is in the valid category (87.5%) or declared eligible for use. Thus, it can be concluded that discovery learning-based E-LKPD can be used in the learning process in high school.
ANALISIS PERBANDINGAN MANAJEMEN BANDWIDTH ANTARA METODE SIMPLE QUEUE DAN QUEUE TREE PADA KOPERASI KARYAWAN INDOCEMENT

The mobility of internet users is now increasingly being used, many providers currently provide various variations of the bandwidth used for their users. Koperasi Karyawan Indocement requires the use of bandwidth aimed at making the internet network connection stable and reducing the error rate in the network connection. Bandwidth management regulates bandwidth limitation so that it is evenly distributed to each client between the simple queue and queue tree&#x0D; methods, the problem faced by the Koperasi Karyawan Indocement is that there is no bandwidth limit applied. This study aims to solve the problems faced in Koperasi Karyawan Indocement by&#x0D; comparing bandwidth management between the simple queue and queue tree methods. Where from the results of this study will be applied which method is better for allocating bandwidth&#x0D; evenly.
Electric Network Frequency Detection Using Least Absolute Deviations

Electric Network Frequency (ENF) is a fingerprint in multi-media forensics applications. ENF is a weak signal that is difficult to be detected. This difficulty stems from the existence of colored wide-sense stationary Gaussian noise in ENF as well as due to many unknown random parameters. However, several ENF detectors have been proposed, motivating the related research. In this paper, a novel Least Absolute Deviations-based ENF detector is proposed that is coined as LAD-Likelihood Ratio Test (LAD-LRT). The performance of the LAD-LRT detector is thoroughly analyzed concerning test statistic distribution and threshold selection. The aim is to develop a detector that detects ENF more accurately in short-length recordings than the state-of-the-art Least-Squares (LS)-LRT and naive-LRT detectors. Thorough evaluation using benchmark audio recordings demonstrate the effectiveness of the proposed detector.
Aspects of Sabah's Tour Operators on Sabah Crocker Range Park as a New Dark Tourism Destination

This conceptual research paper focuses on the potential growth of Sabah's Crocker Range Park as a new dark tourism destination from the aspect of Sabah tour operators.The study is essential to support the planning of Sabah's government in developing dark tourism in Sabah's Crocker Range Park, which was reported in News Straits Times in 2021.The objectives of this study are to know the potential growth segment of Sabah's Crocker Range Park as a new dark tourism destination by identifying the key features of dark tourism attractions available in Sabah's Crocker Range Park from the tour operators' point of view and determining the best destination marketing tools for dark tourism products in Sabah for the domestic tourist market.Further study of dark tourism is required to fully comprehend its potential impacts.This unique destination is ideal for tourists seeking emotional connections, off-the-beatenpath experiences, and valuable first-hand knowledge, which also can be an economic booster for the local community.
Exploring Design Thinking as a Software Accessibility Awareness Raising Methodology in Computing Courses

ABSTRACTDespite many advances in the area of software accessibility, thereare still many problems to be overcome that prevent a greateravailability of accessible software. One of these problems is thataccessibility is usually not included in the curriculum of computingcourses. This educational gap causes software development professionalsto leave college or university without understanding howthe software they develop can be adapted to guarantee its use bypeople with different needs and how to implement these adaptations.This work proposes and evaluates an accessibility teachingmethodology based on Design Thinking with the main objectiveof increasing accessibility awareness among students. The resultsindicate that the proposed methodology was effective and managedto significantly increase students’ accessibility awareness, makingthem more sensitive and empathetic about the topic. The resultsalso showed that the students approved of the methodology andconsidered it interesting and engaging.
STUDI TINGKAT KINERJA PEGAWAI DINAS PERPUSTAKAAN DAN ARSIP PROVINSI KALIMANTAN TENGAH

This study aims to determine the level of performance of employees of the Central Kalimantan Province Library and Archives Service, seen from the dimensions: (1) Service Orientation, (2) Integrity, (3) Commitment, (4) Discipline, and (5) Cooperation. The type of research used is descriptive quantitative. The population in this study were employees at the Central Kalimantan Province Library and Archives Service, totaling 18 people with Echelon III and IV status, where all populations were samples (total sample). The data collection technique is a questionnaire / questionnaire. The results showed that in general the performance level of employees at the Central Kalimantan Province Library and Archives Service was in the "Fair enough" category. The results of this study answered and strengthened the phenomena that the researchers found in the initial study, where in reality the high or low results of employee performance appraisals based on PKP did not necessarily reflect the actual conditions in the field. Discipline of employees (librarians) is still a real problem that must be immediately addressed by the Central Kalimantan Province Library and Archives Service in an effort to improve the quality of service for users.
O impacto da duração do episódio de avaliação na robótica evolutiva: uma análise qualitativa

Abstract In evolutionary robotics, the combination of geneticalgorithms, neural networks, and mobile robots is widespread.Recent studies revealed that the length of the agent evaluationepisode and the manner in which it is varied during evolutiondirectly affects the evolution performance and the behaviorgenerated. The length of the episode influences both the accuracyof the fitness function as well as the quality of the generatedbehaviors. However, more investigation is still needed to bettercomprehend the full impact of different episode duration. Thegoal of this paper is to analyze and characterize the behaviorsgenerated in robots evolved under varying the length of theevaluation episode. The agents all aim at solving locomotionproblems. Results showed that reducing the episode length helpsto develop initial behaviors that may perform fairly well, but aregenerally not fully developed. Longer evolutionary episodes tendto produce more static stay-at-a-fixed-position robotic behaviors,preventing further development. On the other hand, experimentsthat gradually increase episode duration over the course ofevolution avoid the optimal static standing location, allowingmore efficient behaviors to develop at the end of evolution.Key Words—Artificial intelligence, Adaptive robotics, Evolutionaryalgorithms
MPI Parallel Barnes-Hut variants

ABSTRACTThe =-body problem appears in numerous fields, from stellar simulationsto, more recently, AI applications. The Barnes-Hut (BH)method is a tree-based method that allows better scalability whendealing with this problem. In this work several variants of the BHmethod are proposed which use MPI to distribute the workload.
Zeig Dich: Dataset para Reconhecimento de Tipos de Fonte de Jornais Históricos Teuto-Brasileiros

ABSTRACTThis paper addresses the challenge of typeface recognition, withinthe broader scope of optical character recognition of historicalGerman-Brazilian periodicals. A dataset of words containing annotationsof font types and transcriptions for training neural networksfor typeface and text recognition is presented. By enabling wordleveltypeface and text recognition, the authors plan to later developtechniques for high-precision OCR of historical prints typeset inheterogeneous font styles. The value of this dataset is proven by theexcellent results obtained by artificial neural networks trained on it.The authors also recognize that even better results can be obtainedby exploring new ways of organizing the dataset prior to training,and that the results can also be improved through modifications inthe architecture of the nets used.