Reviewerly/exHarmony huggingface dataset:
Evaluating face recognition with different texture descriptions and convolution neural network

Extracting the remarkable attributes of the image objects is an issue of ongoing research special in the face recognition problem. This paper presents two directions. The first is a comparison between the local binary patterns (LBP) and its modified center symmetric LBP drawn from localized facial expressions and due to the efficiency, K-nearest neighbor (KNN) and the support vector machine (SVM) techniques play significant roles in this research used to implement the proposed system efficiently. The second direction proposes an efficient architecture by depending on deep learning convolution neural network (CNN) to implement face recognition. Such a design consists of two parts: a convolutional learning feature model and a classification model. The first one learns the important feature,while the second part produces a score class for each sample input. Many experiments are implemented on the known dataset once for the number of nearest neighbors (K value), and then decrease the number of expression samples for each individual the other time. The cross-validation method is used to provide a true picture of the accuracy of the face recognition system. In all experiment results, the center symmetric LBP with KNN outperforms the classic LBP. While significant progress in the results accuracy recognition ratio of the CNN model compared with other methods used.
Requirement engineering problems impacting the quality of software in Sub-Saharan Africa

Poor software quality has led to tremendous financial losses, necessitating the goal of this study. This study aimed to find out the major cause of poor quality of software and propose solutions to mitigate the problem. Histogram analysis was conducted using data from software development firms’ online applications used to track all defects and issues for each project, which are logged under a unique project ID. The requirement engineering stage was found to produce the most problems that directly or indirectly impact software quality. The capability maturity model integration, prototyping, ISO 9001, Walkthroughs, and Formal Inspections were proposed as solutions that could be used to mitigate the software quality problems that arise from the requirement engineering stage in the software development life cycle.
Towards Accurate Positioning in Multiuser Augmented Reality on Mobile Devices

Multiuser Augmented Reality (MuAR) is essential to implementing the vision of Metaverse for its capability to provide immersive and interactive experiences. In such experiences, peer positions are critical to understand each other’s intentions and actions so as to guarantee the smooth cooperation among users. However, we find that the explicit peer positions provided by the current practice could be incomplete and/or inaccurate in some situations, which leads to the weakened spatial awareness. To achieve the accurate peer tracking in MuAR, we propose a novel multiple sensors information fusion method, CSA (Coordinate System Alignment), to detect and correct defective relative positions by the current practice. CSA firstly formulates problem of correcting erroneous positions into an overdetermined system, and then finds the solution by applying the simulated annealing algorithm to expedite the search process. The evaluation results show that CSA’s ability to reduce errors significantly (58.3% on average) under long-term error duration, especially its advantage in reducing the relative direction errors. The result confirms the potential of CSA to provide reliable peer tracking in MuAR. Meanwhile, it does not impose extra restrictions on users’ practice with current mobile devices in experiences.
Review of "Teaching Business Information Literacy"

Review of Teaching Business Information Literacy (ed. Snipes, Karo, Faulkner, &amp; Reiter; published by Association of College and Research Libraries, 2022).
Sanal Gerçeklik Teknolojisi ve Değişen Reklamlar: Lipton Örneği

The expansion of technology and the Internet in the 21st century, along with the increase in access power and the introduction of digital and social media sectors, has led to a shift in the understanding of advertising. Parallel to these advancements, it has been explored how quickly people are adopting smart mobile devices that have evolved with the advancement of computer technology, and how advertisements and advertisement designs can be created using these devices. As a result of the development of 3D graphics and software technologies as well as computer technologies, the evolution of virtual reality technology from the past to the present has been examined in the following step. The emergence of today's virtual reality glasses, their entry into the consumer's life, and their impact have been discussed. The reasons for the adoption of this technology by companies producing mobile technology, as well as the reasons for producing glasses suitable for their own devices, have also been discussed. It was also attempted to analyze the compatibility of these virtual glasses with mobile devices and the fact that advertising began to shift as a result of these advances. Content analysis, one of the qualitative research methodologies, was utilized to determine the effects, contributions, and changes that all of these recent technological advancements have had on the contemporary advertising environment. Using Lipton's matcha tea campaign as a case study, the purpose of this study is to investigate the relationship between virtual reality technology and modifying advertising perceptions. As a research method, document analysis, one of the qualitative research methodologies, was utilized. In this regard, Scottish tea manufacturer Lipton released their advertising for Japanese Matcha tea in 2016 in VR 360 degrees on YouTube. In the campaign, actual photographs shot in 360 degrees and modeled images were combined and displayed by mixing them with the assistance of the computer. When we analyze VR technology in terms of advertising in the future, people can watch, order, play, and even control what they want without leaving their homes; At the same time, it is anticipated that they can save time while doing these.
Pengujian Perangkat Lunak Menggunakan Metode Regression Testing pada Aplikasi Pembelajaran Matematika untuk Siswa Tingkat Smp Berbasis Android

Technological developments have caused several significant changes in the world of education. One of them is as a learning media. Currently, students at every level of education are familiar with the use of devices as learning media. Through technology, it is easier for them to access every material so that it is easier to learn it. As a result, learning media applications that can be used in students' mobile devices to facilitate their activities are increasingly being loved lately. However, applications with various features and advantages will certainly leave gaps in application vulnerabilities and other errors. Therefore, this study aims to determine the readiness of the application when used in bulk and minimize errors that occur to maintain the integrity of the application so that it can be used properly by users using the Regression Testing method. In this study the application used was the Mathematics Learning Application for Android-Based Middle School Level Students.
PENERAPAN ANALISIS DISKRIMINAN LINIER ROBUST DALAM PENGKLASIFIKASIAN INDEKS KEPEDULIAN TERHADAP ISU KEPENDUDUKAN (IKIK)

Abstract Robust linear discriminant analysis is used to classify data that contains outlier by replacing classical parameters in linear discriminant analysis with robust parameters. This study aims to classify the Index of Concern for Population Issues (IKIK) of 34 provinces in 2020 into two categories namely target fulfilled IKIK and target not fulfilled IKIK using robust linear discriminant analysis. The independen variabels used are quantity dimensions (X_1), quality dimensions (X_2), mobility dimensions (X_3), and environment dimensions (X_4). The results obtained are 17 provinces were categorized as target fulfilled IKIK, 17 provinces as target not fulfilled IKIK. There are 2 robust discriminant functions formed, each for target fulfilled and target not fulfilled IKIK. The accuracy of the robust linear discriminant functions formed is 97,06%, the APER value of the discriminant functions is 2,94% and the PressQ value = 30,11 is greater than the value of (Chi_(3,0.05)^2) = 7.81. This shows that the discriminant functions can classify observations accurately.Keywords: classification, Index of Concern for Population Issues, robust discriminant analysis
PENENTUAN KELAY􏰁AKAN CALON PENERIMA BANTUAN 􏰂RTLH􏰃 MENGGUNAKAN LOGIKA FUZZY MAMDANI DI DESA TANJUNG GLUGUR

One of the strategies to increase the quality of basic facilities of residential districts based on livable house indicators is to repair the targetted houses using the RTLH (Rumah Tidak Layak Huni) grant. The nominees of the grant have been decided by the village officials subjectively by observing from the data of previous grants. The appropriateness of the nominees, however, must be reconsidered firmly in order to have the program done as purposed. The concept of Mamdani fuzzy logic can be used to determine the appropriateness of the candidates. The method used in this research is quantitative research by using secondary data collected by village officials of Tanjung Glugur. This research has one output variable, the appropriateness of the candidates, and four input variables: residential buildings, water needs, sanitation and waste management, and income. The Fuzzy numbers that are used are triangular and shoulder fuzzy sets, while for the defuzzification four methods are used, which are the Smallest of Maximum (SOM), Mean of Maximum (MOM), Bisector, and Centroid. By analyzing the data result, similar results are obtained from all four methods. There are 57 out of 76 candidates who are stated as successful.
Using Information Visualization Techniques for Fish Genetic Management

The use of Information Visualization techniques and research into genetics have greatly improved knowledge in medicine, health, animal breeding, and even in commerce itself. The data is often complex in structure and difficult to understand. Researchers have obtained patterns and knowledge about these data, and with this, the processes of discovery about drugs for diseases, improvement in the cultivation of crops, and in animal breeding itself for a better yield in each of these areas. The goal is, through a tool with visualization techniques, to assist in the monitoring of genetic improvement in fish breeding belonging to the genetics laboratory of a partner university. The requirements survey was carried out with Ph.D. and Ph.D. students in the Aquaculture area.
Magnetic Materials and Their Application in Water Treatment

Magnetic materials have recently emerged as a new class of materials that are being used for water treatment purposes, which offer the use of magnetically separable photocatalysts and adsorbents. After significant advancements in the emerging field, several synthesis routes have been designed for the fabrication of efficient magnetic materials with suitable properties for water treatment applications. This chapter gives a compact and precise knowledge of the magnetic phenomenon, types of magnetism and magnetic materials, their synthesis and how they have been used in various ways to treat the polluted water. The characteristic tools and the methodology involved in determining the properties of magnetic materials have been explained for the reader’s convenience. Two major classes of magnetic materials, i.e., iron-based magnetic materials and titania-based magnetic materials, have been discussed briefly with several case studies included as well. Furthermore, a critical analysis of the recent advancements and prevailing challenges has been given, and significant solutions have been proposed for researchers.
Kontribusi Parental Beliefs dan Self-Regulated Learning terhadap Pemahaman Bacaan Siswa SMP di Bali

The research examined the contribution of parental beliefs and students’ self-regulated learning simultaneously toward students’ reading comprehension of junior high school in Bali. The separate examination has also been carried out namely the contribution of Balinese parental beliefs on students' reading comprehension and the contribution of students’ self-regulated learning on reading comprehension. The sample of this research consisted of 71 junior high school students and Balinese parents living in Kabupaten Karangasem, Bali. This research sample was obtained using the nonprobability sampling method through convenience sampling technique. The research used questionnaires taken from Reading Comprehension Measuring Tools in order to measure students' reading comprehension, The Parental Beliefs Questionnaire to measure parents' beliefs and Motivated Strategies for Learning. The research data were analyzed using multiple regression analysis and simple regression analysis conducted using SPSS 23 and qualitative analysis. The results showed that parental beliefs and students' self-regulated learning simultaneously influenced students’ reading comprehension in Bali. Students’ self-regulated learning also had a significantly positive effect on reading comprehension. However, Balinese’s parental beliefs did not directly contribute to reading comprehension.
Hybrid bayesian convolutional neural network object detection architectures for tracking small markers in automotive crashtest videos

Automotive crash tests are an important aspect of everyday safety, where accurate measurements and evaluations play a crucial role. In order to automate this process, we implement a bayesian hybrid computer vision model to detect two different kinds of target markers. These are commonly used in crash tests, by e.g. automotive manufacturers, to aid the localisation of the car’s positional data by attaching these markers at different positions to the vehicle. A tracking algorithm is subsequently used to add contextual time information to the marker objects. The extracted information can then be used in downstream tasks to calculate important metrics for the crash test evaluation, e.g. the speed, momentum, acceleration and trajectory at particular parts of the car during different stages of the crash test. The model consists of a pre-trained Faster-RCNN for the region proposals with the addition of a bayesian convolutional neural network to estimate a statistical uncertainty on the model’s classifications. This uncertainty estimation can be used as a tool to improve safety in uncertain edge cases in videos where lighting conditions and light reflections are not optimal. Our pipeline achieves an average recall and precision of 0.89 and 0.99, respectively, when applied to test data. This outperforms the recall of state of the art models like the Faster-RCNN Resnet-152 by more than 28\% while delivering slightly better precision, increasing robustness in most of the tested use-cases.
Implementasi RUBECO dalam Pembelajaran Daring Guna Membangun Pemahaman TPACK Guru di SD Muhammadiyah Kleco

&lt;p class="Normal1"&gt;&lt;em&gt;&lt;span lang="IN"&gt;Teachers as a source of learning for students must be able to improve education through the times by applying information and communication technology in education. This study aims to find out how the implementation of RUBECO in online learning is to build an understanding of teacher TPACK at SD Muhammadiyah Kleco and the supporting and inhibiting factors. This research was conducted with a qualitative descriptive research method. This qualitative descriptive study describes the research data that has been obtained. Data collection techniques used in the form of interviews, observation, and documentation. The teacher understands the learning technology in the form of the RUBECO application, uses the RUBECO application as an online learning medium, and understands the function of the RUBECO application for online learning. Teachers have an understanding of all components of TPACK, namely and the importance of TPACK for online learning so that the implementation of RUBECO is able to build teacher understanding of TPACK. Teachers understanding of TPACK has been seen in online learning using the RUBECO application. The implementation of RUBECO is supported by several factors so that it can be carried out properly and smoothly. Several inhibiting factors were also encountered in the implementation of RUBECO but they could be overcome and these inhibiting factors were not significant obstacles. This TPACK capability contributes so that teachers continue to develop TPACK abilities in learning and create quality learning.&lt;/span&gt;&lt;/em&gt;&lt;/p&gt;
Effect of Collaborative Strategic Reading (CSR) on Students’ Reading Comprehension of Narrative Text

There are difficulties faced by students in learning reading of the narrative text, such as difficulties to find details, translating new words, finding main ideas, and making inferences. This research was conducted to see the effect of Collaborative Strategic Reading (CSR) on students reading comprehension of narrative text by applying ‘preview’ for brainstorming, ‘click and clunk’ for translating new words, ‘get the gist’ for finding details, and main ideas, and ‘wrap up’ for making inferences. It is a quasi-experimental research with experimental and control groups. The sample was the eleventh-grade students of SMA Negeri 3 Palangka Raya. XI MIPA 3 and XI MIPA 2 classes were the experimental and control groups, and each consists of 37 students. Reading comprehension tests were used to collect the data. Since the data were normally distributed, the hypotheses were tested by using the independent sample t-test. The hypothesis testing results show that the obtained sig (2-tailed) was 0.027 and smaller than the probability value of sig. 0.05 (Sig. 0.027 &lt; Sig. 0.05). Therefore, Ha was accepted and Ho was rejected. In other words, CSR significantly affects students’ reading comprehension of narrative text.
Immersive English Online Teaching Model Using Original Film as Teaching Resources

The traditional English teaching mode generally consists of reciting words, phrases and texts with high intensity, mechanically memorizing grammar and doing a lot of exercises. This way not only causes the majority of students lack of practical ability to use English, but also difficult to stimulate students’ interest in learning. In this study, an immersive on-line teaching mode of audio-visual film English is constructed. Compared with the general on-line teaching mode, the model has a learning state feedback module based on convolutional neural network and support vector machine. Teachers can pay attention to students’ learning state in time and adjust teaching strategies according to their learning state. Three classes of the same school and grade were selected for comparative experiment. Offline teaching, traditional online teaching and improved online teaching were adopted in one semester respectively. The effectiveness of the improved method was proved by analyzing the class status and final grades of students in the whole semester. Through network training and practical tests, compared with the students who adopt traditional online teaching, the students who adopt this mode have greatly improved their learning state and final exam scores. At a time when the epidemic is still lingering, this mode can provide a positive reference for the development of online teaching.
Multiliterasi: Pilihan Terbaik dalam Pembelajaran Cerita Pendek

This article discusses the importance of learning short stories in a multiliteracy perspective. As a multiliteracy learning model that is able to stimulate and develop student creativity. This study aims to critically describe the current obstacles to learning short stories in the Indonesian language and literature education study program at the Madiun Residency, the weaknesses and opportunities for improvement with the multiliteracy learning model. This study uses a qualitative form with a descriptive-interpretative approach. This approach is considered capable of describing opinions or views that exist in the object of research. The results of this study include: 1) learning short stories in the Indonesian language and literature education study program at the Madiun Residency currently has several obstacles, namely the unbalanced literature courses in the curriculum in the Indonesian language and literature education study program at the Madiun Residency, 2 ) students' interest in literature courses, especially writing short stories, is very low which is influenced by student background factors, view factors of learning literature, especially poetry, are not important, and the low culture of reading literature for students, and 3) the need for a multiliteracy learning model from interview data illustrates that teaching staff really need learning models that are new, practical, and easy to understand.
STRUKTUR NASKAH DRAMA ROH KARYA WISRAN HADI

The structural approach is an initial approach in a literary research. The purpose of this research is to describe the structural elements and describe the relationship between any elements in the drama script Roh by Wisran Hadi. The source of this research is the drama script Roh by Wisran Hadi written in June 1998 in Pagaruyung, West Sumatra. The script of this play has four acts with 29 pages. The drama script Roh is one of the best scripts by Wisran Hadi and won the 2nd place award in the 2003 DKJ competition. The drama script Roh by Wisran Hadi was published in the Sobrat drama script collection. Published by PT. Grasindo Jakarta 2003. The results of this study are in accordance with the initial objectives, the process of obtaining data is carried out through various stages, starting from the stage of recording data, classifying data and analyzing data. This research was conducted to prove that within the intrinsic elements of Wisran Hadi's dramae Roh, there is a concrete and significant relationship so that a literary work can be enjoyed in every verse of the written word
Multi-Point Path Planning Algorithm for a Mobile Robot With Composite Moving Costs

Abstract Multi-point path planning problem is a classic problem of the mobile robot. The present research is concerned with solving the shortest path. In some realistic applications, the shortest path length is not always the significant concerned value of path planning. This article proposes an extended generalized cost concept to constitute the updated path planning strategy. The generalized costs are the combination of straightly moving and turning costs. A genetic algorithm is used to solve optimal path-planning problems. The different weight between the two kinds of costs and how the different parameters affect the optimal path solution is discussed. The generalized cost concept extends the application of path planning to diversified physical quantities. When estimating the composite optimal costs of the path planning problem, we only need to solve the path planning problem with simplex straightly moving costs or simplex turning costs.