Reviewerly/exHarmony huggingface dataset:
The Oxford Handbook of the Economy of Cameroon

Abstract The [Oxford] Handbook of the Economy of Cameroon examines the reasons of Cameroon’s unsatisfactory economic performance and draws lessons from successful development experience to help tackle these issues. The Handbook provides a critical assessment of the history, patterns, and strategies of economic development in Cameroon, and outlines new approaches to economic enquiry for prosperity and social change. Through Cameroon’s governance story, the handbook analyzes the evolving conceptions of economic policy, takes stock of intellectual progress, documents the challenges of implementation, and outlines the intellectual and policy agenda ahead. In this [Oxford] Handbook of the Economy of Cameroon, an international team of leading development economists and researchers address the wide range of issues facing Cameroon and provide guiding principles on how best the country (and other developing nations) could move human, capital and financial resources from low- to high-productivity sectors in a constantly changing global economy.
RANCANG BANGUN MEDIA PEMBELAJARAN E-LEARNING DI SMK NEGERI 1 MAJALENGKA

Technology-based learning currently requires its implementation to utilize the latest innovations for the renewal of the teaching and learning process in it. The use of e-learning is one option that can be done with the current online learning. This study aims to determine the application of learning using e-learning by going through five stages of development with reference to the development of the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The results of this study are the development of e-learning at SMKN 1 Majalengka using the ADDIE development model, namely analysis, design, development, implementation, and evaluation; (b) the resulting e-learning has an online class feature that can be used to assist practical learning as well as distance learning. This online class can be used as a face-to-face online medium when the teacher cannot be present in class; (c) assessment of the feasibility of e-learning learning media; (d) e-learning gets an average assessment from media experts, so that e-learning learning media is categorized with the "Very Good" criteria and is feasible to use; (e) e-learning gets an average assessment of "4.2" from material experts, so that according to the guidelines for converting quantitative data to qualitative data, e-learning learning media is categorized with the "Very Good" criteria and is feasible to use.
Information Needs on TikTok: Between Followers and Viewers

The development of communication technology is growing rapidly along with the breadth of information and knowledge needs of the global community.The presence of the internet has brought big changes to society from various aspects of life, one of the concrete proofs is the birth of social media.Many mass media companies use social media as a medium for disseminating information.TikTok is one of the social media used to practice online journalism.One media company that uses the Tik Tok application as a platform to convey news is Kompas with the username @kompastvnews.Kompas has a special division in charge of online media, namely the digital division.This study uses message packaging theory to see how @kompastvnews actively packages information to be conveyed to the audience and wants to see the factors of the unbalanced number of viewers, likes, comments, and shares on videos uploaded on TikTok @kompastvnews.This research is qualitative with descriptive method.The results of the study show that Kompas actively takes the essence of the news that is distributed, prioritizes trending topics, can move the emotions of the audience so that the audience can get as much information as possible in the shortest possible time.
Auto-clustering of Financial Reports Based on Formatting Style and Author’s Fingerprint

We present a new clustering algorithm of financial reports that is based on the reports’ formatting and style. The algorithm uses layout and content information to automatically generate as many clusters as needed. This allows us to reduce the effort of labeling the reports in order to train text-based machine learning models for extracting person or company names, addresses, financial categories, etc. In addition, the algorithm also produces a set of sub-clusters inside each cluster, where each sub-cluster corresponds to a set of reports made by the same author (person or firm). The information about sub-clusters allows us to evaluate the change in the author over time. We have applied the algorithm to a dataset with over 38,000 financial reports (last Annual Account presented by a company) from the Luxembourg Business Registers (LBR) and found 2,165 clusters between 2 and 850 documents with a median of 4 and an average of 14. When adding 2,500 new documents to the existing cluster set (previous annual accounts presented by companies), we found that 67.3% of the financial reports were placed in the correct cluster and sub-cluster. From the remaining documents, 65% were placed in a different subcluster because the company changed the formatting style, which is expected and correct behavior. Finally, labeling 11% of the entire dataset, we can replicate these labels up to 72% of the dataset, keeping a high feature coverage.
Development and Effectiveness of Teaching Methods for Lifestyle Product Design Development Applying Divergent and Convergent Thinking

As online shopping becomes more active due to the development of digital and communication technology, brands that release lifestyle products are launching new products at a fast cycle.Designers related to this situation are experiencing difficulties and burdens in developing creative designs repeatedly.Therefore, the purpose of this study was to design a teaching method that enables designers to build their own design methodology in realizing creative design.As for the research contents, the first, the role and effect of divergent thinking and convergent thinking for design development are investigated through theoretical review.The second, based on the theoretical review, a teaching method that uses both divergent and convergent thinking at the same time is developed.Specifically, fine art production and design development sheets were used to apply divergent and convergent thinking.The third, the teaching method is applied to learners, and surveys are conducted and results of the developed teaching methods were derived.As a result of the research, it was found that the developed teaching method helps creativity and expressiveness during design development, and greatly helps in motive creation, color and expression technique planning.In addition, the conclusion that it helps designers who need to design a new design in a short cycle more easily come up with ideas and decide design elements, examine the design process, and design systematically without losing intention can be built.
Virtual Keyboard Design of Lampung Script Based on Android

Lampung script fonts, in general, can only be used for typing on a computer system and have not been developed for typing on Android-based smartphones. Therefore, efforts to modernize and build typing using Lampung script for smartphone needs are very much needed on mobile phones so they can be used flexibly. This research makes a virtual keyboard / android keyboard application that can do typing using Lampung script. The virtual keyboard layout is designed by adopting several layouts found on the QWERTY keyboard by displaying all Aksara letters on one virtual keyboard display and grouping Aksara letters in a more attractive composition. To test the Lampung virtual keyboard script, the researchers used the usability testing method, namely aspects of effectiveness, efficiency, and user satisfaction, by 25 respondents. Through this test, an assessment of the effectiveness of the typing test on the success rate of respondents in doing the task was obtained, which was 75%. Evaluation of the typing efficiency aspect using time calculation gets the average result on the WPM score analysis, which is 34 WPM. This result is still below the average typing speed of people, which is 38 WPM. Testing on the aspect of user satisfaction using the system usability scale (SUS) method gets a SUS value of 76, and this result is included in the Acceptable/Good category Acceptable/Good so that users can type Lampung script through Android phones. The conclusion is that it can produce an optimal, efficient virtual keyboard layout and provide comfort for the user while using it with Android. It also could introduce the Lampung script to the younger generation.
The Development and Inheritance of Authorial Stance in Interdisciplinary Studies

This study investigates the stance features from a discourse perspective by examining bioinformatics, a recent emerging discipline developed from the established disciplines of biology and computer science. This analysis is based on a purpose-built corpus, containing 300 empirical research articles in the fields of bioinformatics, biology and computer science. The cross-corpus comparison shows that the bioinformatics contains significant differences in stance features from the two-parent disciplines, while displaying some similar academic practices. Specifically, the bioinformatics corpus contains significantly more cognitive expressions and fewer hedging expressions than the biology corpus. Bioinformatics discourse is also found to use fewer reference expressions and is more likely to include attitudinal expressions than the computer science corpus. Bioinformatics discourse also displays a number of nuanced differences in terms of the specific stance expressions when compared with the two parent disciplines. The results contribute to our understanding of the relationship between parent disciplines and an interdiscipline with respect to stance construction.
Statistical Analysis of Survey Result on Higher Vocational English Teaching Materials and Textbook

In order to have precise information about different expectations and satisfaction degrees of teachers and students on current English textbooks, this paper makes a report and analyzes the statistics, getting general data description by frequency analysis and comparison information by 2 independent samples t test with SPSS 23 based on the information collected from the survey conducted in advance, in hopes of providing data basis for further researches on textbook construction.
Arabic Dialogue Processing and Act Classification using Support Vector Machine

Text classification is the technique of grouping documents according to their content into classes and groups.As a result of the vast amount of textual material available online, this procedure is becoming increasingly crucial.The primary challenge in text categorization is enhancing classification accuracy.This role is receiving more attention due to its importance in the development of these systems and the categorization of Arabic dialogue processing.In the research, attempts were made to define dialogue processing.It concentrates on classifying words that are used in dialogue.There are various types of dialogue processing, including hello, farewell, thank you, confirm, and apologies.The words are used in the study without context.The proposed approach recovers the properties of function words by replacing collocations with standard number tokens and each substantive keyword with a numerical approximation token.With the use of the linear support vector machine (SVM) technique, the classification method for this study was obtained.The act is classified using the linear SVM technique, and the anticipated accuracy is evaluated against that of alternative algorithms.This study encompasses Arabic dialogue acts corpora, annotation schema, and classification problems.It describes the outcomes of contemporary approaches to classifying Arabic dialogue acts.A custom database in the domains of banks, chat, and airline tickets is used in the research to assess the effectiveness of the suggested solutions.The linear SVM approach produced the best results.
Answering Why? An Overview of Immersive Data Visualization Applications Using Multi-Level Typology of Visualization Task

Immersive Analytics (IA) is a fast-growing research field that concerns improving and facilitating human sensemaking and data understanding through an immersive experience. Understanding the suitable application scenario that will benefit from IA enables a shift towards developing effective and meaningful applications. This paper aims to explore tasks and scenarios that can benefit from IA by conducting a systematic review of existing studies and mapping them according to the multi-level typology for abstract visualization tasks, which is also known as the What-Why-How framework. The study synthesized several works to answer the Why within the context of multiple levels of specificity. Finally, the limitations and future works are discussed.
Principles of politeness used and violated by Acehnese-speaking Khatibs in their Friday prayer sermons

This research focused on the politeness of the preachers (henceforth, Khatibs) in delivering sermons. The objective was to find out how politeness principles were applied in the Acehnese language sermons delivered by the Khatibs in Friday prayer processions in Aceh Besar, Indonesia. The data for this research was 15 Friday sermons given at seven sub-districts in Aceh Besar. This study used naturally occurring data from the Friday sermons collected over two months by recording them at 15 mosques within the area of Aceh Besar. Data were transcribed and analyzed using Grice’s maxim theory. The results showed that out of the six politeness maxims, only two maxims, the sympathy maxim, and the tact maxim were found and identified to be applied in the Friday prayer sermons. The sympathy maxim was dominantly used by the Khatibs with 52 occurrences or 68.4% of data, while the tact maxim was found to be used in 24 occurrences or 31.6% of data. Meanwhile, the approbation maxim, the agreement maxim, the modesty maxim, and the generosity maxim were not found in the data. This might be attributed to the nature of the discourse of the sermons as one-way dialogues. It can be concluded that Friday prayers only used the sympathy maxim and tact maxim of politeness because of the one-way communication of Friday sermons. The reasons for the absence of the other four politeness maxims are contextually discussed in this paper.
Detecting Harmful Activity in Pilgrimage Using Deep Learning

CCTV surveillance is the most extensively used intelligent latest innovation. The use of surveillance cameras has risen dramatically because of the convenience of monitoring from anywhere and the reduction of crime rates in public areas. In this paper, we introduce the idea of bad vibe activity detection from live videos to enhance the security and safety of pilgrims. The proposed bad vibes activity recognition model is intended to be addressed in the most efficient manner possible using cutting-edge technologies such as TensorFlow and Keras. TensorFlow was chosen because the project could be deployed to a mobile environment in the future with the possibility of extension of other areas such as airport security, bus stain, and public areas that may deserve special attention for security checks. We choose MediaPipe Holistic for employee bad vibe recognition in the model.
Feature extraction of linear separability using robust autoencoder with distance metric

This paper proposes a robust autoencoder with Wasserstein distance metric to extract the linear separability features from the input data. To minimize the difference between the reconstructed feature space and the original feature space, using Wasserstein distance realizes a homeomorphic transformation of the original feature space, i.e., the so-called the reconstruction of feature space. The autoencoder is used for features extraction of linear separability in the reconstructed feature space. Experiment results on real datasets show that the proposed method reaches up 0.9777 and 0.7112 on the low-dimensional and high-dimensional datasets in extracted accuracies, respectively, and also outperforms competitors. Results also confirm that compared with feature metric-based methods and deep network architectures-based method, the linear separabilities of those features extracted by distance metric-based methods win over them. More importantly, the linear separabilities of those features obtained by evaluating distance similarity of the data are better than those obtained by evaluating feature importance of data. We also demonstrate that the data distribution in the feature space reconstructed by a homeomorphic transformation can be closer to the original data distribution.
Vehicle Detection Using Machine Learning Model with the Gaussian Mixture Model (GMM)

Motion tracking apps are used for a lot of different things, like finding traffic jams and counting the number of cars going through a traffic light. The datasets come from many places on the internet, like YouTube and public dataset archives. There are about 20 videos that are tagged with the words "traffic" and "traffic camera video" and run for 10 to 30 seconds. The Gaussian Mixture Models (GMM) method is the proposed model. It separates the background from the tracked object, which is needed to do motion tracking. Then, the GMM method groups pixel data based on the background color of each pixel. After the cluster is made, the input is matched as a distribution, with the most common distribution used as the background. The analysis was done using MATLAB2019B. The results of this study show that the GMM method can adapt to the background. This is shown by the fact that testing of some of the given conditions went well.
A Qualitative Study of the Learning Management Experience of Grandparents in Families

본 연구는 현상학적 방법을 통해 조손가정 조부모의 학습관리 경험이 어떠한지 살펴보기 위해 수행되었다. 분석 결과, 손자녀 학습지도, 학부모로서 학교행사 참여, 손자녀의 교우관계, 학습습관 및 생활태도, 학부모 및 학교 네트워크의 5개 주제가 나타났으며, 이 다섯 가지의 주제에 따른 14가지 하위주제(손자녀 학습지도에 대한 능력 부족, 교우관계 형성 어려움에 대한 걱정, 기초학력부족에 대한 염려 등)가 도출되었다. 본 연구는 현상학적 연구를 통해 조손가정 조부모의 손자녀 양육과정에서의 학습관리 경험을 구체적으로 밝혔으며 교육적ㆍ사회적ㆍ심리정서적 지원방안을 모색하고 제안하였다는 점에서 의의가 크다. 연구결과를 토대로 시사점과 제언이 제시되었다.This study was conducted to examine the learning management experience of grandparents in their families through a phenomenological method. As a result of the analysis, five topics (learning guidance for grandchildren, participation in school events as parents, peer relationships with grandchildren, study habits and lifestyle, and school networks) appeared, and 14 sub-topics were derived according to the themes. The significance of this study is that the grandparents' experience of learning management in the process of raising their grandchildren was specifically revealed through phenomenological research, and that educational, social, and psycho-emotional support measures were proposed. Implications and suggestions were presented based on the research results.
Aplikasi Pemesanan Lapangan Olahraga Usman Harun Sport Center Berbasis Android dengan Metode First Come First Serve Menggunakan Android Studio dan Firebase

Usman Harun Sport Center is one of the Sport Centers under the auspices of the Jakarta Marine Base Marine Cooperative Primary which is engaged in business, in the form of Sports Field Rental. Until now, Field Orders are still done manually. The method used by the management of the Usman Harun Sport Center is currently inefficient. Therefore, this study has the objectives of (1) Designing a field booking application that can be easily and quickly accessed by customers via gadgets, (2) Designing a field ordering application that can be used by employees to update field availability status information, and (3) Designing a field booking application that can provide an overview of the facilities offered by the Usman Harun Sport Center. From this goal, the authors built and designed an Android-based Usman Harun Sport Center Sports Field Booking Application with the First Come First Serve Method Using Android Studio and Firebase. The final result of this research is to improve the quality and service for Prospective Customers for the Usman Harun Sport Center Sports Field.
Aplikasi Simulasi Berkendara dengan Metode Fuzzy Logic Menggunakan Phonegap

Android-Based Car Driving Simulation Application is an application used to obtain information about driving and caring for a car using smartphone support media. This is based on the increase in car accidents from year to year. The lack of information and the lack of knowledge of car drivers about driving information has made the author make a Car Driving Simulation application for the needs of visitors in using and accessing this application. Remembering technology is like a gadget that is no longer difficult to obtain, in fact it is possible for all people to have it. The application is designed with a smartphone that uses the Android operating system. Applications are made based on information needs for motorists. This application has gone through the stages of testing on four Android smartphone devices. This application is made using Phonegap with HTML and CSS programming languages and runs on the Kitkat version of the Android operating system as a minimum requirement.
Toward an Atlas of Canonical Cognitive Mechanisms

Abstract A central goal in Cognitive Science is understanding the mechanisms that underlie cognition. Here, we contend that Cognitive Science, despite intense multidisciplinary efforts, has furnished surprisingly few mechanistic insights. We attribute this slow mechanistic progress to the fact that cognitive scientists insist on performing underdetermined exercises, deriving overparametrized mechanistic theories of complex behaviors and seeking validation of these theories to the elusive notions of optimality and biological plausibility. We propose that mechanistic progress in Cognitive Science will accelerate once cognitive scientists start focusing on simpler explananda that will enable them to chart an atlas of elementary cognitive operations. Looking forward, the next challenge for Cognitive Science will be to understand how these elementary cognitive processes are pieced together to explain complex behavior.
On the Importance of Denoising when Learning to Compress Images

Image noise is ubiquitous in photography. However, image noise is not compressible nor desirable, thus attempting to convey the noise in compressed image bitstreams yields sub-par results in both rate and distortion. We propose to explicitly learn the image denoising task when training a codec. Therefore, we leverage the Natural Image Noise Dataset, which offers a wide variety of scenes captured with various ISO numbers, leading to different noise levels, including insignificant ones. Given this training set, we supervise the codec with noisy-clean image pairs, and show that a single model trained based on a mixture of images with variable noise levels appears to yield best-in-class results with both noisy and clean images, achieving better rate-distortion than a compression-only model or even than a pair of denoising-then-compression models with almost one order of magnitude fewer GMac operations.