Reviewerly/exHarmony huggingface dataset:
Identifikasi Kerusakan Altenator Daihatsu Luxio dengan Metoda Fungsi Respon Frekuensi

Gasoline engines should sound soft, even tend to be minimal. But when the symptom of a rough sound emerged from the engine room, it was even more like a diesel sound that was quite loud. So that many customers have complained about the rough sound of their vehicle's engine when the engine is started, from the results of the initial inspection that was carried out as a result of the rough noise coming from the bearings on the alternator which experienced wear due to reduced lubrication in the bearings. This requires that preventive maintenance checks on the alternator are a must in the automotive world. On the basis of the above, in this paper, we will discuss the damage to the Daihatsu Luxio alternator with the frequency response function (FRF) method. Damage to the alternator can be seen at point A and point D, seen with a frequency at 1500 Hz in a damaged condition, while in good condition there is no frequency at 1500 Hz. At points B, C, E, and F have the same vibration pattern between the damaged and undamaged conditions. Visually checking results show that the bearing component at point A, it is known that the ball bearing is peeling. This results in a rough spinning of the bearing and makes the alternator make a rough noise while working.
A Cryptographic Technique for Communication among IoT Devices using Tiger192 and Whirlpool

The heterogeneous standards and operational platforms of IoT devices, introduce additional security loopholes into the network thereby increasing the attack surface for the IoT.Most of the devices used in these IoT systems are not secure by design.Such vulnerable devices pose a great threat to the IoT system.In recent times, there have been a lot of research works on improving existing mechanisms for securing IoT data at both the software and hardware levels.Although there exist cryptographic research solutions to secure data at the node level in IoT systems, there is not a lot of these security solutions that target securing both the IoT data and validating IoT nodes.The Authors propose a cryptographic solution that uses double hashing to provide improved security for IoT node data and validating nodes in IoT system.A cryptographic mechanism that is composed of the Tiger192 cryptographic hash and the whirlpool hash function is proposed in authenticating IoT data and validating devices in this paper.The use of digital ledger technology and cryptographic double hashing algorithm provided enhanced security, privacy, and integrity of data among IoT nodes.It also assured the availability of IoT data.
Proof sheet of Geoscience analysis of Moon Rock

Research School of Earth Sciences, Physical Sciences - Moon Rocks Analysis - Dr. B. W. Chappell, Mr. M. I. Vernon, Dr. W. Compston, Mrs. A. Brown, Prof. A. E. Ringwood, Dr. J. E. Lovering, Dr. S. R. Taylor, Dr. W. Compston, Mr. J. Pennington
Labeling Document Images for E-Commence Products with Tree-Based Segment Re-organizing and Hierarchical Transformer

Document images of products have been widely used in E-commence. As a kind of special data, the contents in document images are quite diverse: texts can be scattered anywhere with pictures, and both short text snippets and long text chunks exist. To predict text labels in document images, we propose a two stage approach. The first stage, named as tree-based segment re-organizing, is to resume text order and text connection through hierarchical clustering, segment reordering and segment merging. The second stage, named as hierarchical transformer, is to generate segment embeddings and predict segment labels, where segment level and document level encoder are applied. We empirically study the effects of incorporating different features and compare two kinds of attention to aggregate context, where distance and direction are measured in 1D and 2D respectively. Experiments based on a real-world dataset show that our proposed segment re-organizing method can reduce about 40% input size to the labeling model while bring negligible impact to performance. For hierarchical transformer, we empirically show that document encoder using 1D attention is more effective than 2D attention.
Website Accessibility 3 Best Universities in West Sumatra regarding Online Reputation

For higher education institutions, reputation is crucial because it has a broad influence. The three best universities in West Sumatra already have PR practitioners using the Internet, especially websites, as a medium of communication that help to shape the reputation. This study aims to evaluate the three websites to see the maximization of resources to ensure easy accessibility to make it easier for audiences to obtain information. This research uses a descriptive quantitative method. The researcher did the evaluation using website evaluation tools,  Taw, and aXe analysis tools. Test parameters are based on WCAG 2.0 guidelines. In this study, the researcher has identified several indicators of checking websites that violate the guidelines the most. There are several notes on accessibility problems at a moderate level that must be corrected to increase the level of web access. Then, several parts of the website must be reviewed to be replaced or improved so that they do not have the potential to become an issue on accessibility. After accessibility, privacy protection on websites can also be questioned, so trust in websites will decrease. Website developers must do their best to explain information honestly and responsibly, and interactivity can always be improved. Keywords: Website accessibility, college, online reputation ABSTRAK Bagi institusi perguruan tinggi, reputasi menjadi penting karena memiliki pengaruh yang luas. Tiga perguruan tinggi terbaik di Sumatera Barat sudah memiliki praktisi Humas dan telah memanfaatkan internet, khususnya situs web sebagai sarana komunikasi, yang telah membantu membentuk reputasi perguruan tinggi masing-masing. Penelitian ini bertujuan mengevaluasi ketiga situs web untuk melihat pemaksimalan sumber daya untuk menjamin kemudahan aksesibilitas pada situs web untuk memudahkan khalayak memperoleh informasi. Penelitian ini menggunakan metode kuantitatif deskriptif. Peneliti melakukan evalusi menggunakan tools evaluasi situs web yaitu alat analisis Taw dan aXe. Parameter uji didasarkan pada pedoman WCAG 2.0. Peneliti telah mengidentifikasi beberapa indikator pemeriksaan situs web yang paling melanggar pedoman, terdapat beberapa catatan permasalahan aksesibilitas pada tingkatan moderate yang harus diperbaiki untuk meningkatkan tingkat akses web. Kemudian, terdapat 516 kesalahan dalam tingkatan perceivable dan beberapa bagian website yang harus direview ulang untuk diganti atau ditingkatkan agar tidak berpotensi menjadi issue pada aksesibilitas. Selain Aksesibilitas, perlindungan privasi di situs web juga dapat dipertanyakan, jadi kepercayaan pada situs web akan menurun. Pengelola situs web harus melakukan yang terbaik untuk menjelaskan informasi dengan jujur  dan bertanggung jawab dan  interaktivitas dapat selalu ditingkatkan Kata Kunci: Aksesibilitas situs web, perguruan tinggi, reputasi online
Applying Virtual Reality for Systematic Gaze Pattern Evaluation in Simulated Retinitis Pigmentosa Patients

We apply virtual reality headsets with eye tracking capabilities to evaluate new training methods for patients living with loss of peripheral vision (“tunnel vision”). It can be shown that systematic gaze patterns, taught in a virtual reality environment, are able to significantly increase the effectively perceived visual area of the participants as well as reduce the number of obstacle collisions in navigation tasks.
ANÁLISE CRÍTICA DO APLICATIVO DUOLINGO PARA USO NO PROCESSO DE APRENDIZAGEM DA LÍNGUA INGLESA

The educational context has numerous tools to provide students with more meaningful learning, especially in terms of interactivity, technologies and innovation. With regard to teaching and learning languages, many apps present interesting proposals for their users and potential users. However, learning a new language is a complex task, which requires a lot of effort from those who are teaching and those who are learning. This work develops a critical analysis on the use of the Duolingo app in teaching and learning the English language and points out a comparison with another application with the same functionality. For the analysis, linguistic, pedagogical, technological aspects and usage experience were pointed out. In addition, the potential and weaknesses of the Duolingo application were addressed. In short, Duolingo offers the possibility for potential users to learn several languages, including the English language, as proposed by the application, in a fun and interactive way. However, the focus of learning is on vocabulary and repetition of sentences by version and translation; offering immediate feedback of what is right or wrong, without explaining the structure of the language, just putting it in testing. In sum, we conclude that Duolingo is an application that can serve as a complement to promote English grammar learning practices, however, it does not present activities that really encourage the student to solve problems, interact and have fun.
Communication in the Educational Process

Communication is a very important and complex process, on which the structure of human successes, miracles or disasters depends.Regardless of the approach (as an act, system, code or medium), communication is the basis of social organization and evolution, influencing the relationships, horizontally and vertically between people, being considered as the most important social competence with implications in manifesting and developing others.A society without communication cannot exist; likewise, we cannot educate without communicating, without establishing interpersonal relationships with others, without transmitting emotion, beyond words.
Model of information and methodological competencies of a vocational training teacher

The purpose of the study is to develop a model of information and methodological competencies of a vocational training teacher. The research hypothesis is as follows: if the most important components of the information and methodological competency of a vocational training teacher are identified, they will become elements of the competency model, since competence means that a person has the appropriate competency. The research methods are analysis of literary sources, modeling, the method of expert assessments, and experimental work. The study resulted as follows: the concepts of competencies and competence have been separated; the components of information and communication competencies of a vocational training teacher have been identified; the type of model is justified; the importance of the components of information and methodological competence is determined based on a functional study of the practices of teachers; the model of information and methodological competencies is presented as a structure that combines the components of information and communication competencies and indicators of the importance of their components.
Combined Head and Power Solar Systems launch with Rheem/Solarhart

Centre for Sustainable Energy Systems - Chris Munday, Prof. Andrew Blakers, Denis Smedley, Klaus Weber, Matthew Stocks & others
Adversarial Example Devastation and Detection on Speech Recognition System by Adding Random Noise

The automatic speech recognition (ASR) system based on deep neural network is easy to be attacked by an adversarial example due to the vulnerability of neural network, which is a hot topic in recent years. The adversarial example does harm to the ASR system, especially if the common-dependent ASR goes wrong, it will lead to serious consequences. To improve the robustness and security of the ASR system, the defense method against adversarial examples must be proposed. Based on this idea, we propose an algorithm of devastation and detection on adversarial examples which can attack the current advanced ASR system. We choose advanced text-dependent and command-dependent ASR system as our target system. Generating adversarial examples by the OPT on text-dependent ASR and the GA-based algorithm on command-dependent ASR. The main idea of our method is input transformation of the adversarial examples. Different random intensities and kinds of noise are added to the adversarial examples to devastate the perturbation previously added to the normal examples. From the experimental results, the method performs well. For the devastation of examples, the original speech similarity before and after adding noise can reach 99.68%, the similarity of the adversarial examples can reach 0%, and the detection rate of the adversarial examples can reach 94%.
Relevant Search and Recommendation with Taxonomies and Graphs

Traditional search methods such as full text search indexes are tough to scale and provide noisy search results. Researchers and scholars expectations for high quality, relevant search becomes higher and higher. Even consumers are becoming more search savvy and turning to social media and specialty sites in pursuit of more relevant searches and recommendations. This presentation explores how the use of standards based taxonomy formats and native graph technologies can enable leaner search engines to provide semantic search and recommendations. How this is being implemented in the Knowledge Discovery platform as well as the pros and cons of this approach will be discussed. Non-traditional recommendation use cases, such as suggesting peer reviewers for new submissions, will also be touched upon. A prototype implementation will be demoed.
Phenomenologizing Filipino Medical Technology Students Experiences in the Enriched Virtual Mode of Learning

Filipino Medical Technology students encountered challenges with the Enriched Virtual Mode during the COVID-19 pandemic. This phenomenological study followed purposive sampling in selecting twelve (12) Filipino Medical Technology students from a higher-education institution engaged in Enriched Virtual Mode. They answered online forms and participated in a semi-structured one-on-one interview. Recorded interviews were transcribed, read and re-read by the researchers. Colaizzi’s method was applied to obtain the essence of the phenomenon under investigation and through this, researchers were able to analyze 83,543 words from data collection. Significant statements and their condensed meanings were arranged into codes and themes. A repertory grid was also utilized to facilitate cool and warm analyses. This resulted into the emergence of five (5) interesting typologies of challenges experienced by respondents: Balancing feelings of isolation and need for participation, Balancing quantity and quality of submissions, Balancing time and demands, Balancing connection and disconnection and Balancing wellness and workload. These challenges are overcome through coping mechanisms which include: Interaction and Engagement, Determination and Commitment, Prioritization and Time Management, Communication and Discernment and Relaxation and Enjoyment. Findings provide a valuable lens wherein Filipino medical technology students’ experiences in the Enriched Virtual Mode of learning could be viewed and understood.
Information as a Part of Communicative Process and Its Meaning in Media Communication

The paper is devoted to theoretical approaches to the scientific understanding of information and its significance in media communication are presented. They are based on the author's definition of the concept of information space in the framework of journalistic practices; on the analysis of modern concepts of media information, including its definition, structure, form and communication factors.
Determinants of Micro and Small Enterprise Growth in Southern Ethiopia

The contributions of micro and small enterprises to create employment opportunity and fostering gross domestic product have been empirically examined.However, the determinants of their growth are different and there are inconsistent findings from the existing research.Thus, the study was conducted to identify micro and small enterprise growth determinants in Southern Ethiopia.The study applied explanatory research design and enterprise managers were taken as a sampling unit.A multi-stage sampling technique was used and the data were collected through questionnaires.The collected data using questionnaire were analyzed using Multiple Linear Regression Model to identify the factors that determine the micro and small enterprise growth.Therefore, the result indicated that among significant independent variables, educational level, work experience, and enterprise age were statistically significant at less than 0.1% significance level.Likewise, social networking and training were statistically significant at less than 1% significance level.Similarly, working area, group collateral, household asset, and attitude were also statistically significant at less than a 5% significance level.Furthermore, all significant variables have a positive relationship with enterprise growth.
Penggunaan Teknologi Informasi Untuk Mengelola Data Masjid Al-Jihad – Pematangsiantar

Every activities carried out by the Board of Mosques has been regulated and set forth in the Regulation of the Minister of Religious Affairs No. 54 of 2006 concerning a form of organizational structure of organizational management and work procedures of “Badan Kesejahteraan Masjid” (BKM). With the regulation that has been set by the Government, then every mosque jama'ah is willing and ready to accept the mandate and duties directed by the Government in terms of the management of the Mosque. For the processing of mosque data, it is time to utilize information and technology so that data management and information delivery about the Mosque can be done quickly and appropriately. In order for the data collection to be done easily, it is necessary to build information and technology facilities and infrastructure through internet services for faster and more precise access to information. So with this service, to provide Information Sharing about mosques to Jama'ah Mosque can be done from anywhere and anytime as long as the internet connection network is connected with smarthphone media and Computers
Did you find it? Visual search tends to be faster when applying saliency-aware subtle scene modulation in VR-based realistic scenario

Visual search as a daily task becomes particularly challenging when the time to find the target is limited. In a pilot study, we investigate whether a subtle modulation of visual content considering the scene saliency map can improve visual search performance in terms of the search time and proportion of failure to find the target within a limited time. To do so, a set of naturalistic omnidirectional images were displayed in virtual reality (VR) with a search target being overlaid on the visual scene at a random location. During the experiment, each of five participants performed a visual search task in this virtual environment with an ultimate goal to find the search target as soon as possible within 20 seconds. By subtle modulation of the visual content we intended to redirect the observer’s attention from salient regions of the scene, and, that way, enable the participant to find the search target faster. The scenes were modified applying blur, where blurring strength was spatially varied based on the saliency maps computed for the displayed omnidirectional images before the experiment. Specifically, the most salient regions of the scenes were blurred using a convolution of the original image with a Gaussian kernel. The maximal strength of blur was varied via different standard deviations of the Gaussian filter, defining three different experimental conditions. The mean search time, as well as the proportion of trials where participants failed to find the target, were compared among different strength values of a blur. Using linear mixed-effect model analysis, a significant decrease of search time as well as a significant reduction of the proportion of failed trials, as a function of blur strength, were found. Thus, this pilot study shows a possibility to improve visual search performance in realistic 3D scenes by applying a subtle saliency-aware scene modulation.
The Hyper-Lexi phantom feature selection based on Topic Vector Lex-Sense Convolution Neural Network for Detection of Fake News in Social Media

Current social media contain a lot of information discussion and spreading based on trending hashtags. During the phenomena, the trustworthiness of information leads rumors to produce wrong information spreading over communal social resources. Identifying fake information in tweets/tags is difficult because wrong tags prediction failed in feature selection and classification. Due to unambiguous word frequency in feature selection, the classification failed to predict misleads count terms to reduce the classification accuracy. To resolve this problem, we propose a Hyper-Lexi phantom feature selection (HLPFS) based on Topic vector Lex sense (TVLS) be optimized with a convolution neural network to predict the fake tweets information in social media. Initially, the preprocessing was carried to fake redundant data to predict the topic-relevant model using the Topic vector summarization rate (TVSR). This selects the geometric features of discussion forums content. Based on that topic relevance process, the Reliable entity content hit rate (RECHR) observe positive recurrent information difference between the tweets lexical weights. Hyper-Lexi phantom feature selection (HLPFS) selects the importance of fake difference metrics among reliable terms to reduce dimension based on the entity rate. Then selected features are classified with Adaptive decision in convolution neural network optimized with Relu activation function. The proposed system produces high performance in predicting fake information in social media as well as other methods. The results improve the precision rate as well recall providence to improve the classification accuracy.
Unsupervised Selective Manifold Regularized Matrix Factorization.

Manifold regularization methods for matrix factorization rely on the cluster assumption, whereby the neighborhood structure of data in the input space is preserved in the factorization space. We argue that using the k-neighborhoods of all data points as regularization constraints can negatively affect the quality of the factorization, and propose an unsupervised and selective regularized matrix factorization algorithm to tackle this problem. Our approach jointly learns a sparse set of representatives and their neighbor affinities, and the data factorization. We further propose a fast approximation of our approach by relaxing the selectivity constraints on the data. Our proposed algorithms are competitive against baselines and state-of-the-art manifold regularization and clustering algorithms.