Reviewerly/exHarmony huggingface dataset:
University information environment: the case study

Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region 2019: Proceedings of 2019 XVIII Russian Scientific and Practical Conference on Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region (PTES)
Self-Organizing Map vs Initial Centroid Selection Optimization to Enhance K-Means with Genetic Algorithm to Cluster Transcribed Broadcast News Documents

A compilation of artificial intelligence techniques are employed in this research to enhance the process of clustering transcribed text documents obtained from audio sources. Many clustering techniques suffer from drawbacks that may cause the algorithm to tend to sub optimal solutions, handling these drawbacks is essential to get better clustering results and avoid sub optimal solutions. The main target of our research is to enhance automatic topic clustering of transcribed speech documents, and examine the difference between implementing the K-means algorithm using our Initial Centroid Selection Optimization (ICSO) [16] with genetic algorithm optimization with Chi-square similarity measure to cluster a data set then use a self-organizing map to enhance the clustering process of the same data set, both techniques will be compared in terms of accuracy. The evaluation showed that using K-means with ICSO and genetic algorithm achieved the highest average accuracy.
Progressive Growing of Neural ODEs

Neural Ordinary Differential Equations (NODEs) have proven to be a powerful modeling tool for approximating (interpolation) and forecasting (extrapolation) irregularly sampled time series data. However, their performance degrades substantially when applied to real-world data, especially long-term data with complex behaviors (e.g., long-term trend across years, mid-term seasonality across months, and short-term local variation across days). To address the modeling of such complex data with different behaviors at different frequencies (time spans), we propose a novel progressive learning paradigm of NODEs for long-term time series forecasting. Specifically, following the principle of curriculum learning, we gradually increase the complexity of data and network capacity as training progresses. Our experiments with both synthetic data and real traffic data (PeMS Bay Area traffic data) show that our training methodology consistently improves the performance of vanilla NODEs by over 64%.
Curvature based Sparse Manifold Learning

The idea of manifold learning is to treat data distribution via the high-dimensional embedding of the manifold graphs, in the face of mass unstructured data. The core of it is to restore its low-dimensional structure, aiming to realize the efficient and accurate data analysis results; namely, the evaluation of the algorithm improves efficiency as much as possible while ensuring the accuracy of certain data analysis. By studying the dimensionality reduction algorithm that is based on local feature mapping, we find out that there is still an improvement space for algorithm complexity in the known algorithm, and also notice that there are some connections and differences between the local neighborhood and the Euclidean space. Therefore, based on the improvement of Laplacian Eigenmap algorithm, the thesis proposes a new neighborhood partition method, and the concept of curvature is introduced in the feature description of local neighborhood. The improved algorithm (CSLEP) reduces the computational cost of redundant local neighborhoods. Meanwhile, it achieves a more accurate mapping mode of local neighborhood features.
THE DEVELOPMENT OF COGNITIVE INTEREST AMONG STUDENTS OF EDUCATIONAL INSTITUTIONS OF THE MINISTRY OF INTERNAL AFFAIRS OF RUSSIA IN THE LEARNING PROCESS

The article discusses some pedagogical conditions for the development of cognitive interest among students of higher educational institutions of the Ministry of Internal Affairs of Russia in modern conditions. The role of the teacher in the development of cognitive interest among students is substantiated
Adherencia al tratamiento en personas con alteraciones cardiovasculares: Enfoques teóricos de enfermería

The aim of this article is to describe and analyze the theoretical approaches to nursing that have been used for research on adherence to treatment in people with cardiovascular diseases.For this, a descriptive integrative review is carried out between the years 2005 -2018 in which 27 original articles are included, review, master's thesis and doctorate in nursing taking into account the descriptors adherence to treatment, nursing theories and cardiovascular health.As a result, 4 nursing theories that have been worked on in relation to adherence to treatment were identified: Deliberative Nursing Process Theory, Theory of Self-efficacy, Theory of Self-Care and Theory of Self-Care in Cardiac Failure; evidencing in literature the predominance of descriptive, methodological and intervention studies using these theoretical approaches.It can be concluded that the theoretical frameworks of nursing have allowed the investigative advance in the adherence of this population, however, with the evolution of knowledge it Adherencia al tratamiento en personas con alteraciones cardiovasculares:Enfoques teóricos de enfermería Adherence to treatment in people with cardiovascular disorders: Nursing theoretical approaches Adesão ao tratamento em pessoas com
Weakly Aligned Joint Cross-Modality Super Resolution.

Non-visual imaging sensors are widely used in the industry for differentpurposes. Those sensors are more expensive than visual (RGB) sensors, andusually produce images with lower resolution. To this end, Cross-ModalitySuper-Resolution methods were introduced, where an RGB image of ahigh-resolution assists in increasing the resolution of the low-resolutionmodality. However, fusing images from different modalities is not a trivialtask; the output must be artifact-free and remain loyal to the characteristicsof the target modality. Moreover, the input images are never perfectly aligned,which results in further artifacts during the fusion process. We present CMSR, a deep network for Cross-Modality Super-Resolution, whichunlike previous methods, is designed to deal with weakly aligned images. Thenetwork is trained on the two input images only, learns their internalstatistics and correlations, and applies them to up-sample the target modality.CMSR contains an internal transformer that is trained on-the-fly together withthe up-sampling process itself, without explicit supervision. We show that CMSRsucceeds to increase the resolution of the input image, gaining valuableinformation from its RGB counterpart, yet in a conservative way, withoutintroducing artifacts or irrelevant details.
[의용시스템] A Study on Effect of Sterilization by UV LED and UV Lamp for Household Ultrasonic Sterilizer Devices

Recently UV lamps used for sterilization are replaced by UV LED with development of LED technology. Also 380 nm UV LED is getting attention based on the fact that it is effective on 380-410 nm wavelength besides 253.7 nm known to be excellent for bactericidal effect. In this research, we compared and studied the effect of sterilization using UV LED and UV lamps. In this experiment, we kept watching 380 nm UV LED and 253.7 nm UV lamp for 20 minutes and studied by killing bacteria comparing with the exposed time. 380 nm UV LED did not have significant impacts on cell death but 253.7 nm UV lamp made the cells almost extinct after 10 minutes. Based on the this result, for 10 minutes we adjusted the exposure time of the UV lamp and checked every minute of the sterilization rate, while irradiation. The measurement shows it decreased by more than 90% after 5 minutes and 99.5% effective after 10 minutes on sterilization.
PENGUASAAN KATA SANDANG BAHASA JERMAN SISWA SMA NEGERI 3 SINJAI DALAM MENYUSUN KALIMAT SEDERHANA

Abstract. This study aims to determine the data and information about the level of mastery of article of German in composing simple sentences and the factors that influence the mastery of German clothing in Sinjai 3 High School students in compiling simple sentences. This research is quantitative descriptive. To collect data used a written test, and a closed questionnaire. Then the data collected was analyzed using percentage techniques. The population in this study were all students of class XI IPS SMA Negeri 3 Sinjai. The sample used in this study was total sampling consisting of 3 classes with 83 students. The results of the study showed that the mastery of German language clothing for Sinjai 3 High School students in compiling simple sentences was in the Less category (58.34%).
Spike buffer: improve deep network performance by offset mechanism

For a well-designed neural network model, it is difficult to further improve its performance. This study proposes an offset mechanism called spike buffer, which can effectively improve the performance of the designed convolutional neural networks. The spike buffer introduces an offset buffer-bit and a gradient spike function in the convolution channels to enhance the expression of effective features and suppresses the extraction of invalid features. Without significantly increasing the computational complexity of deep convolution neural networks, it can improve the feature selection performance of convolution neural networks and enhance the ability of non-linear mapping, and can be easily embedded into various convolution neural networks. Experiments show that the performance of convolutional neural networks with integrated spike buffer can be effectively improved.
Zero-Shot Image Classification Method Based on Attribute Weighting

In order to solve the defect that the attribute has the same effect during the zero-shot classification decision, the objective weighting method is introduced to learn the attribute weights. Firstly, the convolutional neural network is used to encode the image information, and the two full connected layers are used to encode the semantic attributes, and a visual-semantic joint embedding model is constructed by combining the visual branch. Then, the weight parameters of each attribute are learned by the objective weighting method. The nearest neighbor search is estimated to predict the test category labels by the attributed-based weights. The experimental results show that it makes up for the different importance of attribute to classification decision and improves the recognition accuracy of classification model. At the same time, it is proved that the selecting of embedded spaces will also affect the recognition accuracy.
Political Economy of Imperialism in Iraq

The growing influence of America in the global economy coupled with her protectionist policies in the recent time have put pressure to comity of transitional states especially African and Middle East. The invasion of Iraq by America is the driven factor of former’s oil deposits that had been a source of interest to America. Meanwhile, Americans had over the years accused Iraq of harboring Weapons of Mass Destruction, an antic for her imperialist expedition. However, it is against this backdrop that the study geared toward appreciating co-factor variables of imperialism that had influenced American’s interest on Iraq and the attendant implication to the economies of two actors. The paper utilized mixed method approach and analyzed using analytic induction. The theoretical framework of analysis was anchored on the economic radical theory, a strand of Marxian theory of economic structuralism. The finding of the study reveals that despite the established Westphalia Treaty of 1648 on the sovereignty of nation states, Americans had devoid odds and invaded, plundered the economy of Iraq. The paper strongly recommends among others; sanctioning of America for neglecting the world standing order on sovereignty of states. Also, Iraq needs to be compensated by America through reconstruction and rehabilitation.
PELATIHAN KOMPUTER BAGI MASYARAKAT PENYANDANG DISABILITAS

Disable Person Organization Mitra Sejahtera (DPO Mitra Sejahtera) is an organization for disable people and found by Christian Public Health Foundation (YAKKUM) in Yogyakarta, especially in some areas in Gunung Kidul, Bantul, and Kulon Progo, Special Region of Yogyakarta. This organization focuses on empowering and advocation activity of its member and society surrounding the organization. DPO Mitra Sejahtera has a problem that its member has limitation in the usage of basic computer and office application, such as word processor and spreadsheet processor. Thus, Faculty of Information Technology, Duta Wacana Christian University conducted training for member of DPO Mitra Sejahtera. This training was held on March, 25-26 2019 in the DPO Mitra Sejahtera Head Office. The training gives a good result. Participants feels that the training is useful for them to help them understanding the basic function of word processing and spreadsheet processing.
Perancangan Desain Komunikasi Visual Dalam Bentuk Kampanye Instagram “Apresiasi Kerja Desainer”

The working fee of graphic designers is still being felt to be very low because there is no appreciation from business owners and also from the public. To increase the appreciation, there have been many campaigns regarding the appreciation of the work of graphic designers on social media Instagram with positive reviews, but many graphic designers said that there is still no change. The author then tried to analyze some of the shortcomings of these campaigns and tried to add new strategies. The author hoped that the new campaign with the new communication strategy could deliver better message to the business owners and public. The author used brand audit, brand awareness, and brand management theory from Keller (2013), Kartajaya (2016) and also social movement theory from Aspen Institute Roundtable (2013) to do the campaign strategy researches. The outcome of this artwork is a conceptual campaign with a complete communication strategy guide. Keywords
Article Review - Potensi Game Edukasi Dalam Upaya Pelestarian Batik Indonesia

Educational game has potential in transferring knowledge. educational game makes it easy to deliver knowledge to students. one of the elements in the game, namely character, has a role in conveying the message. fun educational games make it so effective when it used in batik preservation. where batik is very diverse and it is not easy to learn the meaning and philosophy in it. the meaning and philosophy of batik in Indonesia deserves to be introduced to our next generation. with a learning process that is full of culture. This article discusses the potential of educational games in the learning process of preserving batik culture in Indonesia.
Practical Grammar Compression Based on Maximal Repeats

This study presents an analysis of RePair, which is a grammar compression algorithm known for its simple scheme, while also being practically effective. First, we show that the main process of RePair, that is, the step by step substitution of the most frequent symbol pairs, works within the corresponding most frequent maximal repeats. Then, we reveal the relation between maximal repeats and grammars constructed by RePair. On the basis of this analysis, we further propose a novel variant of RePair, called MR-RePair, which considers the one-time substitution of the most frequent maximal repeats instead of the consecutive substitution of the most frequent pairs. The results of the experiments comparing the size of constructed grammars and execution time of RePair and MR-RePair on several text corpora demonstrate that MR-RePair constructs more compact grammars than RePair does, especially for highly repetitive texts.
Donor Collectors Route Optimisation using Genetic Algorithm Method

Searching for a route to take donation in terms of time and the shortest route is a must for the management because it can save time and effort. In order to make donations more efficient, a system is needed to provide recommendations for taking donation routes, one of which is using a Genetic Algorithm (GA) method. The GA can be applied in optimizing schedules, routes, and spaces. The results show that after testing two different routes with different maximum generation values of 50, 100, 500 and 1000, a maximum generation value of 50 can give optimal results.
CFS: An effective statistical texture descriptor

&lt;p class="IETAbstractText"&gt;Coarseness is an effective description for texture analysis and many approaches capture this property of texture in different methods. In this research, we propose a new texture descriptor (CFS) that works based on coarseness and the fineness similarity score. For tuning of its configuration, we collect coarse and fine textures based on human visual perception at first. After that, we relabel the "coarse" and "fine" categories of the gathered textures during the configuration of the operator in a proposed framework. We concatenated the features of two pyramid representations with the CFS information of the original texture (PCFS). In addition, we combine the PCFS information with our last proposed feature selection approach to improve the efficiency of the CFS. We evaluated the proposed feature extraction method with classification of one of the well-known data set, Outex. Experimental results depict satisfactory performance of the CFS with very low-dimensional feature length.&lt;/p&gt;
Research on the Construction of Teaching Quality Index of Teachers in Higher Vocational Colleges

Based on the study of other social evaluation indexes, this paper studies the management and control of teaching quality by using the research methods of system science, aiming to find a calculation method that can comprehensively reflect the overall quality characteristics of the teaching system.On this basis, the paper puts forward the construction scheme of Higher Vocational Education Teachers' teaching quality index, which includes five dimensions such as student attendance data, student evaluation data, supervision data, peer evaluation data, management organization inspection data and several observation indexes.At the same time, a comprehensive empirical analysis is made on the 2019 teachers' teaching quality index of our school.The average teaching quality index of teachers is 86.0, indicating that the quality is in a good state.
To the 60th Anniversary of Oleg Yur’evich Sheshukov

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PENERAPAN METODE INKUIRI UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA SISWA KELAS V SD NEGERI 023905 KEBUN LADA

The purpose of this study was to improve the mathematics learning outcomes of class V students of SD Negeri 023905 Kebun Lada by applying the inquiry method. This research is Classroom Action Research (CAR) which consists of 2 cycles and each cycle consists of: 1) planning, 2) implementation, 3) observation, and 4) reflection. Data collection techniques are carried out by observing activities and learning outcomes tests. The results showed an increase in learning outcomes of Class V students of SD Negeri 023905 Kebun Lada. It can be seen from the results of the implementation of teacher activity learning that it increased from 70% with a fairly good category in the first cycle to 85% with a good category in the second cycle, while from the observation the implementation of student learning activities increased from 65% to the poor category in the first cycle 85% in the good category in cycle II. Furthermore, classical learning completeness of students has increased from 63.64% in the first cycle to 90.91% in the second cycle.
Location based Anomalies Detection on Geographical Map using Data Mining Techniques

Road traffic is the most important issue not only for the Indian government but also for common people. Most of the road accidents and crimes are happening in Nashik City on specific locations that are represented in the form of a black spot. These black spots can help in identifying the road Accidents and Crime area using this system. We apply data mining algorithms such as the Eclat algorithm on the road Accident and Crime dataset as an attempt to locations this problem. In the Data mining Association rule, clustering is that identify the causes of Accident & Crime. In this project, we first applied the Eclat algorithm to group the Accidents & Crime locations into three levels such as first level, second level and, third level Accident & Crime location. The rules show different factors associated with road Accidents & Crimes at different locations. For all this, we provideAccident & Crime data that are issue from the Nashik city commissioner office.
PREDICTIVE ANALYSIS FOR LEUKEMIA SURVIVAL USING AI BOTS

A Chatbot is an Artificial Intelligence (AI) software that conducts a conversation with users via text-based method without any human intervention at the server side. In this project we implemented only limited features like text-based chatting which is designed only for the people who are dealing with Leukemia. People can ask about anything and everything related to leukemia symptoms and the bot will provide the necessary precautions based on their queries. People can communicate with the chatbot which makes the computers closer to human-level understanding. The Chatbot collects the keywords and will start the conversation by asking queries to the users and provide the suggesting remedies. KEYWORDS- Chatbot, Leukemia, Cancerbot.
Actors’ Collaboration to Manage Disasters in Cilacap District Central Java Province Indonesia

The province of Central Java has areas spreading to 35 Districts/Cities, of those Districts/Cities, there is an area which based on Indonesia's Disaster Risk Index (IRBI) year 2016 has a quite high risk index, that is Cilacap District which occupies the 17th position nationally and first number for the position of 35 Districts/Cities located in Central Java within score number 132 (categorized as highly vulnerable class).Risk disasters occur in Cilacap District covering earthquake, tsunami, flood, landslide, tidewater, whirlwind and drought.Within such conditions, it is needed some actors' collaborations to manage disaster that can hit the Cilacap District at any time.This research aims to describe actors' collaboration to implement disaster management in Cilacap District Central Java Province.Research method which was used was a qualitative method by seeing the phenomena of actors' collaboration to implement disaster management.Result of the research shows that from the mapping of actors can be seen that there are a core actor and supporting actors in the process of implementation of disaster management in Cilacap District.Then, the actors involved in the operation do collaboration by means of communication, coordination, and cooperation under the control of Regional Disaster Management Agency (BPBD) as the leading sector.