Reviewerly/exHarmony huggingface dataset:
A Deep Learning Model Enhanced with Emojis for Sina-Microblog Sentiment Analysis

In Sina-microblog comments, abundant emojis, as an important piece of information for the sentiment analysis, are used to vividly express users's opinions and feelings. To classify timely and effectively the sentiment hidden in the vast pool of the microblog comments, this paper proposes an emojis-enhanced sentiment analysis model. The model first extracts emojis from review sentences and constructs emoji sequences as an enhanced information, and then uses BiLSTMs to learn text-based representation. Furthermore, this model adopts a new attention mechanism to incorporate contextual information of sentences into emojis to learn the emoji-based auxiliary representation. Finally, the final representation is obtained by combining text representation and emoji representation through the full connection layer. Extensive experiments show the effectiveness of the proposed method on sentiment classification for Chinese microblog comments.
Differentiating between machine translation and student translation: red flags and salient lexicogrammatical features.

&lt;p align="center"&gt;&lt;span lang="EN-US"&gt;ABSTRACT&lt;/span&gt;&lt;/p&gt;&lt;p align="center"&gt;&lt;span lang="EN-US"&gt;Machine translation enables students to produce work in the target L2 which may be superior to that which they could produce otherwise.&lt;span&gt; &lt;/span&gt;The present study examines whether use of machine translation can be detected by teachers.&lt;span&gt; &lt;/span&gt;Seventeen native teachers compared and assessed the authorship of five human translations (HT) and five machine translations (MT) of Japanese news stories.&lt;span&gt; &lt;/span&gt;Native teachers were able to accurately detect the difference in 74.04% of cases due to increased passive clauses (a ratio of 1 to 2.5), and inappropriate pronoun use (a ratio of 1 to 6.5) when MT was used.&lt;/span&gt;&lt;/p&gt;&lt;p align="center"&gt; &lt;/p&gt;
Application of Multi-Camera Tracking and Positioning Technology in Substation

With the development of camera hardware technology and computer vision algorithms, visual positioning technology has been paid more and more attention. Most of the research on visual positioning technology is based on single camera and single picture. that is, only the target tracking appears in the shooting range of a certain camera, the coverage and the obtained picture information are limited. The multi-camera-based visual positioning technology can not only provide a wider field of view but also overcome the problem of target occlusion by the cooperation among the cameras. The multi-camera visual positioning technology studied in this paper mainly applies several classical algorithms in this field. The KNN-based background segmentation algorithm is used to detect moving targets, and the KCF algorithm is used to achieve continuous and reliable tracking of targets. The SURF feature detection algorithm is adopted. Target matching is achieved by matching with FLANN, and finally the position and motion trajectory of the target in the bird’s eye view are obtained based on the planar homograph. The multi-camera visual positioning technology can be used to obtain the real-time position of the personnel in the substation, which can prevent the staff from entering the charging interval, and avoid the dangerous situation that the outside personnel enters the substation illegally.
Logarithmic Fuzzy Entropy Function for Similarity Measurement in Multimodal Medical Images Registration

Multimodal medical images are useful for observing tissue structure clearly in clinical practice. To integrate multimodal information, multimodal registration is significant. The entropy-based registration applies a structure descriptor set to replace the original multimodal image and compute similarity to express the correlation of images. The accuracy and converging rate of the registration depend on this set. We propose a new method, logarithmic fuzzy entropy function, to compute the descriptor set. It is obvious that the proposed method can increase the upper bound value from log( r ) to log( r ) + ∆( r ) so that a more representative structural descriptor set is formed. The experiment results show that our method has faster converging rate and wider quantified range in multimodal medical images registration.
Practice-Oriented Training as a Mechanism of Development of Professional Potential of Students of Higher Education in Russia and Abroad: Historical and Social aspect

This article deals with the theoretical and methodological justification of practice-oriented education as a mechanism for the development of professional potential of students in higher education.The authors consider the process from the point of the historical and social aspects of this phenomenon.The historical approach made it possible to analyze the pedagogical heritage of world-renowned scientists in Russia and abroad in the field of the formation of professional competences and the development of human potential.As a result it is shown that on the basis of the analysis of goals, tasks, forms and results of the received education practice-oriented training includes two educational approaches: competence-based and practice-oriented, which are based on human activity, which leads to the development of professional potential of students.The social approach is used to analyze the organization of practical training of higher education in Russia, Europe, USA, Asia and China and the use of the mechanism of development of professional potential.Practice-oriented training can be considered as a mechanism for the development of students' professional potential, taking into account national characteristics.A sociological study conducted among students of higher educational institutions revealed the most effective forms and types of training that provide practical orientation and professional development (56% of respondents approved practical master classes).There are revealed modern social risks: new social policies in the sphere of higher education, digitalization of education, spread of clip-thinking and internet-addiction among students of higher education.
The Improvement Research of Gyroscope Temperature Control Based on self-Adaptive ANN

The Gyroscope is a important part of the navigation system. The stabilization of temperature capability is crucial to azimuth and attitude system. In this paper, apply to gyroscope temperature control system from A self-Adaptive ANN, the core components of the temperature control system is TMS320F2811. Adopt adaptive optimization PID algorithm and other soft hardware design, both realize a suit of temperature collection and controlled design proposal.
The Theory of the Generalised Real Numbers and Other Topics in Logic

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Factors related to self-care activities adherence of older adults with diabetes

Diabetes mellitus treatment is complex and involves several activities. Its goal is to control the disease and prevent complications. The success of this treatment includes adherence to self-care. This study aimed at identifying factors related to self-care activities adherence in community older adults with diabetes. Cross-sectional, observational and analytical study with a quantitative approach to data, conducted with 140 older people. We used the following instruments: Mini-Mental State Examination for cognitive assessment, socio-demographic and clinical characterization instrument, Brazilian Functional and Multidimensional Assessment Questionnaire to verify the self-reported morbidities, Abbreviated Geriatric Depression Scale to investigate the presence of depressive symptoms and Diabetes Self-Care Activities Questionnaire to assess activities adherence related to self-management of people with diabetes. The results of this study indicated that self-care activities with higher adherence were: “taking the indicated number of diabetes pills” (6.6 ± 1.2), “taking insulin injections as recommended” (6.2 ± 2.0), “drying the spaces between the toes after wash them” (4.6 ± 3.2) and “following a healthy diet” (4.5 ± 2.7). The self-care activities with smallest adherence were: “performing specific physical activities (walking, swimming, etc.)” (0.9 ± 1.9), “performing physical activities for at least 30 minutes” (1.2 ± 2.2), “evaluation of blood sugar as times as recommended” (1.2 ± 2.3), “sweets intake” (1.3 ± 1.7) and “evaluation of blood sugar” (1.4 ± 2.3). Regarding smoking, 88.6% were not smokers. Factors related to self-care measures were: gender, indicating greater adherence of women, education level, and number of morbidities, suggesting that adherence to the feet care domain is directly proportional to education and number of morbidities. However, this same domain was inversely proportional to depression, indicating that there was greater adherence in those people without depressive symptoms. The factors associated with the adherence to self-care activities observed in this research contributed to the planning of strategies to prevent diabetes mellitus complications and promote improvements in the life and health of the older adults in the community.
Problem-Based Learning Model Assisted by Lift The Flap Book: Enhancing on Reading Motivation of 3rd Grade Students

The development of language, especially reading, needs to develop starting from early grade students in primary schools because it is one of the language skills. The purpose of this research was to determine the effect of the model of problem-based learning assisted by the lift flap book on the ability to tell of first-grade students in primary schools. The design chosen is quasi-experimental with a non-equivalent control group. The experimental group was given treatment, while the control group was without treatment. The population used in this research is third-grade students of Group 5 of Puren Public Primary School in Depok sub-district. The research subjects are 54 students with the details of 28 control class students and 26 experimental class students. Third-grade students at Puren Public Primary School and Ngringin Public Primary School are as research samples. Sampling uses a purposive sampling technique because sampling is based on certain objectives. Data were obtained through direct observation to school with observations of reading motivation which was analyzed with the t-test variants. The results show that the tarithmetic is 3.488, ttable with reference to the formula (a/2); (df) equals (0.05/2); (54) equals 0.025; 54, then the value of ttable = 2.00488, thus tarithmetic &amp;gt; ttable 3.814 &amp;gt; 2.005. Therefore, Ho is rejected while Ha is accepted, meaning that learning with problem-based learning assisted by the lift flap book influences students' reading motivation.
Psychological Structure of Humanities Students Conflictological Competence

This article presents the results of empirical research aimed at identifying the psychological structure of students in the Humanities conflictological competence.Сonflictological competence is a type of professional competence, which includes the readiness and ability to manage conflicts in the professional activity.In the course of the study it was revealed that conflictological competence is an integrative property, including adaptive, personal, operational, volitional, anti-aggressive, functional, active, cognitive indicators.These indicators are combined into four components: adaptiveoperational, cognitive, functional-active, personal-regulative.It is established that in general, students of Humanities are characterized by rather high level of formation of these components, but their volitional self-regulation, adaptive capabilities, skills of active listening and reflection need development.
Functional Programming in Pattern-Match-Oriented Programming Style

Throughout the history of functional programming, recursion has emerged as a natural method for describing loops in programs. However, there does often exist a substantial cognitive distance between the recursive definition and the simplest explanation of an algorithm even for the basic list processing functions such as map, concat, or unique; when we explain these functions, we seldom use recursion explicitly as we do in functional programming. For example, map is often explained as follows: the map function takes a function and a list and returns a list of the results of applying the function to all the elements of the list. This paper advocates a new programming paradigm called pattern-match-oriented programming for filling this gap. An essential ingredient of our method is utilizing pattern matching for non-free data types. Pattern matching for non-free data types features non-linear pattern matching with backtracking and extensibility of pattern-matching algorithms. Several non-standard pattern constructs, such as not-patterns, loop patterns, and sequential patterns, are derived from this pattern-matching facility. Based on that result, this paper introduces many programming techniques that replace explicit recursions with an intuitive pattern by confining recursions inside patterns. We classify these techniques as pattern-match-oriented programming design patterns. These programming techniques allow us to redefine not only the most basic functions for list processing such as map, concat, or unique more elegantly than the traditional functional programming style, but also more practical mathematical algorithms and software such as a SAT solver, computer algebra system, and database query language that we had not been able to implement concisely.
PENELITIAN EVALUASI PENDIDIKAN

To know the intricacies of something needed in a study, it was done to get an answer from the occurrence of something using scientific methods. In the world of research, there are at least two types of research, namely qualitative and quantitative. The following will be discussed about the evaluation research, in the world important research evaluation education is conducted in order to measure progress and further develop in a better direction. In principle, evaluation studies to make decisions by comparing data or information collected against criteria, standards, or benchmarks used as comparators for the data obtained. While evaluation is a systematic and ongoing process to determine the quality (value and meaning) of something, based on certain considerations and criteria in the framework of decision making.&#x0D; Among the evaluation models referred to IS; CIPP evaluation Model, UCLA Model evaluation, Brinkerhoff Model and Stake Model or Countenance Model. Meanwhile, evaluation research can be divided into two types, namely formative evaluation, and summative evaluation. The standard procedures in evaluation research are as follows; Clarification of reason to evaluate (explain the reasons why evaluation is held), choose Evaluation model, identify related parties, determination of components to be evaluated, identify evaluation questions, Compiling design evaluation and schedule of activities, collection, and analysis of data, reporting of evaluation results.&#x0D; &#x0D; Keywords: research, evaluation, and education
Research on Business Models Innovation Path for Electrical Power Substitution under “Three Types and Two Networks”

The popularization and application of electrical power substitution have produced great economic and social benefits.Whereas in the realistic development process, innovative business models are also required in order to promote the deep development of electrical power substitution.In 2019, the strategy of "three types and two networks" is proposed by the State Grid Corporation of China, which could provide the technology, platform and value base for the business models innovation of electrical power substitution.In the construction process of "three types and two networks" strategic system, Through SWOT analysis of the business model, we can further accelerate the sustainable development of electrical power substitution through innovating the existed business models.
The Utilization of Mobile Learning in Junior High School Physics Science Learning in Rural Area of Sikka, East Nusa Tenggara, Indonesia

People are the widely used mobile technology for their activities in various sectors.This technology also is widely considered for use in education; included in science learning.On the other hand, almost all people in many regions in Indonesia are connected through the internet network.However, the use of mobile technology for learning is still the islands around the Flores area.This study aims to determine how high school students respond after attending mobile learning.This research is a quantitative descriptive study with a sample of 58 students from three different schools at Sikka of East Nusa Tenggara in Indonesia.Students are involved in mobile learning in material physics within two weeks.Learning active ies include reading learning subjects, practicing questions, discussion in forums, posting ideas, quizzes, and final examinations.During this learning, the teacher used Edmodo, like a learning management system.Students filled the questionnaire measuring their response to the use of technology.The USE questionnaire was used to measure this response.The results of this study indicate that students in this region have the right level of acceptance of mobile learning.As a follow-up, it needs to be promoted by local government policies on schools for this mobile learning.
Machine Learning Assisted Optical Network Resource Scheduling in Data Center Networks

Parallel computing allows us to process incredible amounts of data in a timely manner by distributing the workload across multiple nodes and executing computation simultaneously. However, the performance of this parallelism usually suffers from network bottleneck. In optical switching enabled data center networks (DCNs), to satisfy the complex and time-varying bandwidth demands from the parallel computing, it is critical to fully exploit the flexibility of optical networks and meanwhile reasonably schedule the optical resources. Considering that the traffic flows generated by different applications in DCNs usually exhibit different statistical or correlative features, it is promising to schedule the optical resources with the assistance of machine learning. In this paper, we introduce a framework called intelligent optical resources scheduling system, and discuss how this framework can assist resource scheduling based on machine learning approaches. We also present our recent simulation results to verify the performance of the framework.
OpenCL-code generation framework for MobileNets with depthwise separable convolution and merged layers

Deep convolutional neural networks are increasingly used in various parallel embedded platforms such as mobile GPUs, AMD APUs, and FPGAs. At the same time, many new models have been developed for embedded platforms, such as MobileNet. In order to balance accuracy, speed and resource requirements and achieve cross-platform versatility, we have developed a software framework for in-depth research. Generated an OpenCL code that takes full advantage of parallel resources and improves the parallel efficiency of OpenCL code. Another advantage is that it optimizes and consolidates the network and compiles offline, making the entire application most efficient. MobileNets uses nonlongitudinal separable convolution (deep separable convolution) instead of standard convolution. Experiments with MobileNet have shown that the OpenCL code generation framework can significantly improve the efficiency of use.
Accurate segmentation of bladder wall and tumor regions in MRI using stacked dilated U-Net with focal loss

Automatic and accurate segmentation of bladder walls and tumors in magnetic resonance imaging (MRI) is a challenging task, due to significant bladder shape variations, strong intensity inhomogeneity in urine and very high variability across tumors appearance. To tackle such issues, we propose to leverage the representation capacity of an improved U-Net networks using stacked dilated convolutions. The proposed structure includes stacked dilated convolutions to increase the receptive field without incurring gridding artifacts. In addition, we embed stacked dilated convolution network into the U-Net architecture, thus enabling extracting multi-scale features for segmentation of multi structures with different shapes and scales. Finally, we apply a focal loss function to make all classes contribute equally to the loss function in our model. Evaluations on T2-weighted MRI show the proposed model achieves a higher level of accuracy than state-of-the-art methods, with a mean Dice similarity coefficient of 0.95, 0.81 and 0.66 for inner wall, outer wall and tumor region segmentation, respectively. These results demonstrate a strong agreement with reference standards and a high performance gain compared with existing methods.
Abstract: Unsupervised Anomaly Localization Using Variational Auto-Encoders

An assumption-free automatic check of medical images for potentially overseen anomalies would be a valuable assistance for a radiologist. Deep learning and especially Variational Auto-Encoders (VAEs) have shown great potential in the unsupervised learning of data distributions. In principle, this allows for such a check and even the localization of parts in the image that are most suspicious.
Klasifikasi Topik Multi Label pada Hadis Shahih Bukhari Menggunakan K-Nearest Neighbor dan Latent Semantic Analysis

Hadith is the second source of Islamic law after Al-Quran, making it important to study. However, there are some difficulties in learning hadith, such as to determine which hadith belongs to the topic of suggestions, prohibitions, and information. This certainly obstructs the hadith learning process, especially for Muslims. Therefore, it is necessary to classify hadiths into the topic of suggestions, prohibitions, information, and a combination of the three topics which also called as multi-label topic. The classification can be done with the K-Nearest Neighbor, it is one of the best methods in the Vector Space Model and is the simplest but quite effective method. However, the KNN has a lack in dealing with high vector dimension, resulting in the long time computing classification. For that reason, it is necessary to classify Sahih Bukhari's Hadiths into the topic of recommendations, prohibitions, and information using the Latent-Semantic Analysis - K-nearest Neighbor (LSA-KNN) method. Binary Relevance method is also employed in this research to process the multi-label data. This research shows that the performance of LSA-KNN is 90.28% with the computation time is 19 minutes 21 seconds and the performance of KNN is 90.23% with the computation time is 37 minutes 06 seconds, which means that the LSA-KNN method has a better performance than KNN
Perancangan Arsitektur Sistem Informasi Pondok Pesantren Dengan The Open Group Architecture Framework (Togaf)

Islamic boarding school is a place of learning in which there are very many facilities and services. Good mastery of language, creativity, religion, leadership and all kinds of knowledge must already exist in the boarding school. The current condition of many Islamic boarding schools does not yet have a specific and integrated information system architecture in Islamic boarding schools in accordance with the needs and objectives of Islamic boarding schools, the cause is because Islamic boarding schools have not yet focused on the process of developing their information systems. Therefore we need an information system in Islamic boarding school. In this study the author raised the information system design of Islamic boarding school by using TOGAF (The Open Group Architecture Framework) with the Architecture Development Method (ADM) method. The output that can be achieved from the design of Islamic Boarding School Information System is to produce a model and basic framework (blue print) in developing integrated boarding school information systems to support the needs of Islamic Boarding Schools.