Reviewerly/exHarmony huggingface dataset:
Road safety education for schools with ZoSS facilities in Bandung City, Jawa Barat

West Java is the province in Indonesia with the third greatest number of accidents. Accidents are caused by dangerous traffic behavior. In order to save Indonesia's productive generation, changing traffic behavior is a top concern. Several schools in accident-prone areas have been designated as Safe School Zones (ZoSS) by the government. However, it is vital to teach students and their support systems how to drive safely. This program seeks to promote road safety knowledge and behavior, support changes in traffic safety behavior, and increase traffic safety knowledge and behavior among students, teachers, and the public. On December 22, 2021, the activity was held in 5 elementary schools (SD) and 5 junior high schools (SMP), with theoretical and practical road safety training. The activities resulted in the development of young fighters' capacity, the formation of Road Safety Ambassadors and Safety Awareness Community Groups (KMSK), and the emergence of a sustainable program by advocating to the government and designating the Bandung City Transportation Office as the Adopting Father of Ambassadors and KMSK.
Pendampingan Penerapan E-Learning Sebagai Sarana Mengajar Untuk Guru MTS dan MA Miftahul Jannah

The implementation of online-based applications is deemed necessary to assist teachers as one of the supporting applications in e-learning. Based on the results of interview, observation, and implementation of community service activity carried out by Lecturers of STMIK Palangka Raya was very enthusiastically welcomed by the teachers at Miftahul Jannah Schools Palangka Raya. The application applied in the activity was Zoom. The implementation of this application is one of the teachers’ efforts in their professionalism to improve the quality of learning. The assistance in using the Zoom application in this service activity aims to increase teachers understanding in using it as a means of teaching and learning. The methods used in community service activity were practice, lectures, and demonstrations. These methods used to reduce the obstacles which have been problem for teachers in using application for teaching online. As the result, from the carried out activity, the participants, teachers, can apply the Zoom application starting from downloading, installing, and accessing it.
PERFORMANCE MEASUREMENT OF PUBLIC SERVICE AGENCY IN HIGHER EDUCATION INSTITUTIONS: A Balanced-Scorecard Model Approach

This study aims to develop a framework for measuring higher education performance as the Public Service Agency. The authors adapted one of the measurement models, namely the Balance Score Card Model. This is a qualitative study with library research type. The data collection uses literature documents related to the discussion subject. The results show that the Balanced Scorecard Model could be used to measure the performance of higher education institutions that has the mandate as the Public Service Agency. The target of the Balanced Scorecard Model is developed to measure the corporation. Corporations and public institutions have different objectives, characteristics, and philosophies. However, the model can be utilized to measure the performance of public institutions by adapting the components from each perspective. This study contributes to the development of higher education performance measurement framework serving as the Public Service Agency.
IMPLEMENTASI PROGRAM INOVASI PERPUSTAKAAN MELALUI POJOK BACA INSTAGRAMABLE DI UPT PERPUSTAKAAN PROKLAMATOR BUNG HATTA BUKITTINGGI

This study aims to describe the implementation of Proklamator Bung Hatta’s library Unit Bukittinggi innovation program in improving library services and increasing interest in visiting users through the provision of a lesehan reading area, namely an instagrammable reading corner. Sampling in this study was conducted by purposive sampling method. Data was collected by means of interviews and documentation. This data analysis technique was carried out in three stages, namely data reduction, data presentation and conclusion drawing. The results showed that: (1) the instagrammable reading corner at the Proklamator Bung Hatta’s Library Unit Bukittinggi has implemented an element of novelty because it has provided a different reading area than before; (2) the instagrammable reading corner at the Proklamator Bung Hatta’s Library Unit Bukittinggi has implemented an effective element because the purpose of making the reading area can be carried out properly as long as the instagrammable reading corner is established. (3) the instagrammable reading corner at the Proklamator Bung Hatta’s Library Unit Bukittinggi has implemented an element of usefulness because the reading corner has been able to provide great benefits for users compared to the previous reading area. (4) Instagrammable reading corner at Proklamator Bung Hatta’s Library Bukittinggi has implemented transferable or replicable elements because the indicators from the reading corner are unique and interesting so that they can be recommended for other agencies who want to create reading corners. (5) the instagrammable reading corner at the Proklamator Bung Hatta’s Library Unit Bukittinggi has implemented an element of sustainability because the instagrammable reading corner will be held continuously at the Proklamator Bung Hatta’s Library Unit Bukittinggi.
Digitalization of museums as a socio-cultural phenomenon

The paper considers the process of digitalization of Russian museums as an important project of state. The author reviews and analyses the approaches to the definition of the term digitalization in Russian sociology and studies the measure of influence of the COVID-19 pandemic on the rate of digitalization of museums based on the interim results of the national project “Culture” dedicated to digitalization of the infrastructure of the cultural sphere. Within this study the author shows the experience of the digitalization process on the example of domestic museums and as successfully implemented examples that contributed to the improvement of the digital communication process, analyzes the processes of digitizing museum expositions, introducing virtual reality mechanisms, audio guides (their analogues in the form of QR codes), and online events. Based on these technologies, the author comes to conclusion (1) about the multifaceted activities of museums, which cease to be just a place to store exhibits of historical and cultural value, and (2) that modern social demands make the issue of digitalization of museums relevant in the context of communication interaction in society. Russia has successful examples of implemented cases of digital museums, but a further continuation of this work is required, since many museums have partially implemented digitalization.
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network

This work introduces RevSilo, the first reversible bidirectional multi-scale feature fusion module. Like other reversible methods, RevSilo eliminates the need to store hidden activations by recomputing them. However, existing reversible methods do not apply to multi-scale feature fusion and are, therefore, not applicable to a large class of networks. Bidirectional multi-scale feature fusion promotes local and global coherence and has become a de facto design principle for networks targeting spatially sensitive tasks, e.g., HRNet (Sun et al., 2019a) and EfficientDet (Tan et al., 2020). These networks achieve state-of-the-art results across various computer vision tasks when paired with high-resolution inputs. However, training them requires substantial accelerator memory for saving large, multi-resolution activations. These memory requirements inherently cap the size of neural networks, limiting improvements that come from scale. Operating across resolution scales, RevSilo alleviates these issues. Stacking RevSilos, we create RevBiFPN, a fully reversible bidirectional feature pyramid network. RevBiFPN is competitive with networks such as EfficientNet while using up to 19.8x lesser training memory for image classification. When fine-tuned on MS COCO, RevBiFPN provides up to a 2.5% boost in AP over HRNet using fewer MACs and a 2.4x reduction in training-time memory.
Improving Student Participation in Online Engish Using Song Lyrics at SMAN 2 Tualang

This study aimed to determine the increase in students’ engagement in English language learning through the use of song lyrics. The study was conducted in a cycle of five sessions. The study design was a Classroom Action Research (CAR) of 35 XI MIPA 4 students at SMA Negeri 2 Tualang. The instruments of this study were observation sheets and interviews. From the findings, the researchers found an increase in students’ engagement, which was characterized by more enthusiasm in teaching and learning, like collecting more homework and being on time in online learning, asking more questions, and answering the teacher's questions. At the same time, the interview results indicated that several factors affecting the active participation in online classrooms were interesting media and easy song lyrics. The English teachers, referring to students’ perspectives, were able to improve students’ engagement and interest. To conclude, the teacher’s strategy in the use of song lyric is able to make students actively participated in the online classroom and make the teaching atmosphere more lively.
On polynomials of small degree over finite fields representing quadratic residues

Let F be a finite field of odd characteristic. It was proved by Madden and Vélez in [Pacific J. Math. 98(1982), 123–137] that except for finitely many exceptions of F, for every polynomial f(x) ∈ F[x] which is not of the form αg(x)2 or αxg(x)2, where α ∈ F, there exists a primitive root β ∈ F such that f(β) is a nonzero square in F. When this theoretical result is concretely used, it is necessary to determine such finitely many exceptions. In this paper, the possible exceptions are determined, provided the degree of f(x) is less than 9. Remark that our arguments do not hold when f(x) is of degree 9 and also the capacity at this stage of a computer is not enough to do it. Moreover, such kinds of results have been used to solve some combinatorial problems.
Pengembangan Profesionalisme Guru Melalui Pelatihan Komik Digital dengan Canva for Education

The purpose of the service activity is to provide insight and improve the professionalism of teachers in Central Java in making interesting and interactive teaching materials for students, especially in making digital comics with the Canva for Education application. In general, the difficulties experienced by teachers in making digital comics are how to make comic designs easy and attractive. The Canva for Education application is one application that can be used to overcome these problems. Teachers can create digital comics using a wide selection of available templates. The implementation of this service is carried out online using Zoom Meeting and Google Classroom. The training was attended by approximately 100 participants from various regions in Central Java. The final result of the training activity is that teachers can create digital comics published on social media Instagram. It is intended that the results of digital comics that have been made by teachers can be useful for the general public, especially students who get related material.
Statistical Depth based Normalization and Outlier Detection of Gene Expression Data

Normalization and outlier detection belong to the preprocessing of gene expression data. We propose a natural normalization procedure based on statistical data depth which normalizes to the distribution of gene expressions of the most representative gene expression of the group. This differ from the standard method of quantile normalization, based on the coordinate-wise median array that lacks of the well-known properties of the one-dimensional median. The statistical data depth maintains those good properties. Gene expression data are known for containing outliers. Although detecting outlier genes in a given gene expression dataset has been broadly studied, these methodologies do not apply for detecting outlier samples, given the difficulties posed by the high dimensionality but low sample size structure of the data. The standard procedures used for detecting outlier samples are visual and based on dimension reduction techniques; instances are multidimensional scaling and spectral map plots. For detecting outlier genes in a given gene expression dataset, we propose an analytical procedure and based on the Tukey's concept of outlier and the notion of statistical depth, as previous methodologies lead to unassertive and wrongful outliers. We reveal the outliers of four datasets; as a necessary step for further research.
MENINGKATKAN LITERASI DIGITAL SISWA PADA MATA PELAJARAN IPA DENGAN MENGGUNAKAN MULTIMEDIA INTERAKTIF DI MTSN 3 ROKAN HULU

Writing this article aims to improve students' digital literacy by using interactive multimedia in science learning, focusing on the structure and function of plant tissue at MTsN 3 Rokan Hulu. This study consisted of two meetings using innovative technology in the form of interactive multimedia with different sub-materials, namely (1) the structure and function of plant tissues in roots, stems and leaves, (2) the structure and function of plant tissues in flowers, fruits and seeds. Aspects of digital literacy that will be assessed in this study include: accessing, analyzing and evaluating, creating, reflecting, and communicating. This research is a qualitative research with descriptive method. Samples were taken by simple random sampling technique. The sample is class VIII students at MTsN 3 Rokan Hulu as many as 32 students. The results showed that learning science on the structure and function of plant tissue by using interactive multimedia could improve the digital literacy of junior high school students with an overall percentage difference of 4.00% from meeting 1 (70.33%) to meeting 2 (74.33%). . Thus, it can be concluded that the use of interactive multimedia can improve the digital literacy of students at MTsN 3 Rokan Hulu in terms of the structure and function of plant tissues. In the end, it is hoped that similar research can be carried out related to efforts to increase digital literacy with other materials.
Pemanfaatan Office 365 Dan Teknologi Cloud Bagi Guru TK ABA Kadipolo di Masa Pandemi Covid-19

This community service activity was carried out to provide assistance to TK ABA Kadipolo teachers, this is regarding changes in academic activity models due to conditions were caused by the Covid-19 pandemic. The implementation of community service activities is carried out in 3 stages, starting from pre-activities, then continued with activities carried out in the form of online and offline training related to the use of office 365 and Cloud Computing Technology. As well as the evaluation stage which is carried out by obtaining feedback testimonials from participants. The material in training activities using office 365 online by accessing the office.com page and cloud computing technology as a storage used in training is One Drive. In general, community service activity funded by LPM Universitas AMIKOM Yogyakarta in the 2020 on TDPT program was carried out well and provided new insights for participants about the application of cloud computing technology.&#x0D;
Information system for ontological modelling the subject areas

Objectives. The creation of ontologies of subject areas is considered. The goal is to develop a mathematical model of ontology and the information system for ontological modeling. The task is to reduce the complexity of ontological modeling. Methods. As research methods, the theory of hybrid intelligence systems, the theory of sets, elements of mathematical logic, methods for developing the information systems, comparative analysis of information systems, informal analysis of information system were used. Results. Mathematical model of ontology using the concept of metaobject is developed. Ontological modelling based on this model involves specification, conceptualization and formalization. A glossary of terms is being built at the specification stage. At the conceptualization stage, objects in the subject area and their hierarchy are defined, and then connections between objects are identified. In the formalization stage, the metaobjects and the relationships between metaobjects that correspond to objects and the relationships between objects were defined. This is considered as the ontology of the subject area. During the actualization stage, the parameters of subject area objects and their values, classes, subclasses, and instances of classes were defined. Parameters, parameter values, classes, subclasses, and instances of classes are implemented in ontology as metaobjects of relative types. An information system with a unique architecture has been developed, namely a hybrid intelligence system for the automation of ontological modelling. Conclusion. The article conducts a comparative analysis of the developed information system with the systems used today for creation of ontologies. The analysis showed that the information system developed by paper author in most parameters is not inferior to considered systems and at the same time easier to use and expand. The mathematical model of ontology and the information system for ontological modeling of subject areas, developed by author, are tested in practical creation of ontology on ecology. On the basis of the conducted comparative analysis and informal analysis of practical use, it is concluded that ontological modeling with the help of the information system developed by author reduces the labor intensity and decreases the time of ontologies creation.
Parallel Instance Filtering for Malware Detection

Machine learning algorithms are widely used in the area of malware detection. With the growth of sample amounts, training of classification algorithms becomes more and more expensive. In addition, training data sets may contain redundant or noisy instances. The problem to be solved is how to select representative instances from large training data sets without reducing the accuracy. This work presents a new parallel instance selection algorithm called Parallel Instance Filtering (PIF). The main idea of the algorithm is to split the data set into non-overlapping subsets of instances covering the whole data set and apply a filtering process for each subset. Each subset consists of instances that have the same nearest enemy. As a result, the PIF algorithm is fast since subsets are processed independently of each other using parallel computation. We compare the PIF algorithm with several state-of-the-art instance selection algorithms on a large data set of 500,000 malicious and benign samples. The feature set was extracted using static analysis, and it includes metadata from the portable executable file format. Our experimental results demonstrate that the proposed instance selection algorithm reduces the size of a training data set significantly with the only slightly decreased accuracy. The PIF algorithm outperforms existing instance selection methods used in the experiments in terms of the ratio between average classification accuracy and storage percentage.
Determining the design parameters for manufacturing a shell and tube heat exchanger with minimum cost using The Bees Algorithm

The shell and tube heat exchanger is one of the commonly used heat exchangers. Minimizing the cost required to manufacture these heat exchangers is one of the main objectives for designers and users. This study determined the necessary design parameters for a shell and tube heat exchanger to be manufactured with minimum cost using The Bees Algorithm (BA). These design parameters are the shell side inside diameter, the tube side outside diameter, and the baffle spaces. The system mathematical model is created to find the optimum values of these parameters, the necessary boundary conditions are determined, and an optimization study is carried out. The cost obtained by BA $ 11187.86 compared with GA $ 11190.17 and SPQ $ 18429.4 from the literature. It is observed that The Bees Algorithm (BA) gives successful results in the design of shell and tube heat exchangers.
Non-directive teaching to develop the personality of 4-and 5-yearsold children

Theresearch aims to demonstrate the validity of the non-directive teaching system in the development of the personality of children of 4 and 5 years of initial education. The study collects the contributions of the humanistic theory of Carls Rogers and the personality traits approach. The research was carried out in a study sample, made up of 270 children of 4 and 5 years of initial education of the Garatea Urbanization. The instruments used were: Differential semantic scale to record the development of the children's personality before and after the application of the non-directive teaching system, and as an instrument to record the process of its application was the Assessment Scale. The type of research design is experimental; with a group before and after;and for its statistical operation, it has been used: the mean, the average, the standard deviation and the non-parametric test: the Wilconson test. The results show a significant difference between the pre-test and the post-test; In the mean of the pre-test, 11.24% was reached, while the mean of the post-test was 22.01%. Likewise, the hypothesis was verified with a significance level of 5%. We consolidate that the non-directive teaching system is valid for the development of personality, manifested in the five major trait factors: agreeableness, neuroticism, openness to experience, extroversion and conscientiousness.
Feature Learning for Nonlinear Dimensionality Reduction toward Maximal Extraction of Hidden Patterns

Dimensionality reduction (DR) plays a vital role in the visual analysis of high-dimensional data. One main aim of DR is to reveal hidden patterns that lie on intrinsic low-dimensional manifolds. However, DR often overlooks important patterns when the manifolds are distorted or masked by certain influential data attributes. This paper presents a feature learning framework, FEALM, designed to generate a set of optimized data projections for nonlinear DR in order to capture important patterns in the hidden manifolds. These projections produce maximally different nearest-neighbor graphs so that resultant DR outcomes are significantly different. To achieve such a capability, we design an optimization algorithm as well as introduce a new graph dissimilarity measure, named neighbor-shape dissimilarity. Additionally, we develop interactive visualizations to assist comparison of obtained DR results and interpretation of each DR result. We demonstrate FEALM's effectiveness through experiments and case studies using synthetic and real-world datasets.
Expressive, Variable, and Controllable Duration Modelling in TTS

Duration modelling has become an important research problem once more with the rise of non-attention neural text-to-speech systems. The current approaches largely fall back to relying on previous statistical parametric speech synthesis technology for duration prediction, which poorly models the expressiveness and variability in speech. In this paper, we propose two alternate approaches to improve duration modelling. First, we propose a duration model conditioned on phrasing that improves the predicted durations and provides better modelling of pauses. We show that the duration model conditioned on phrasing improves the naturalness of speech over our baseline duration model. Second, we also propose a multi-speaker duration model called Cauliflow, that uses normalising flows to predict durations that better match the complex target duration distribution. Cauliflow performs on par with our other proposed duration model in terms of naturalness, whilst providing variable durations for the same prompt and variable levels of expressiveness. Lastly, we propose to condition Cauliflow on parameters that provide an intuitive control of the pacing and pausing in the synthesised speech in a novel way.