Reviewerly/exHarmony huggingface dataset:
Modified Picture Series through Hot Potatoes in Increasing Students’ Reading Comprehension

This article describes pictures series modified using digital text through Hot Potatoes. Classroom action research is used to discover the process of improving text reading comprehension by modifying serial images using digital text. The classroom action research used consisted of two cycles. The instrument used in this study was a written test in the form of an essay using the hot potatoes application, observation sheets and questionnaires with the help of Google forms and conversations with the help of voice messages on the WhatsApp application. The findings in this article are that in the new normal era, students are faced with new habits of learning with the help of the internet with various applications. Therefore, there is a new climate that emerges in the learning process itself, from refusing to be comfortable with online learning habits. Educators must be more creative in creating learning activities in this network, so as to improve students' learning abilities, especially reading skills.
Interpretation of Sentiment Analysis of Tweets through Artificial Intelligence

Sentiment analysis, also known as opinion mining is a sub-field of Natural Language Processing (NLP) that tries to identify and extract opinions from a given text. This project presents a software tool for sentiment analysis of tweets which combines an advanced technique of machine learning BERT (Bidirectional Encoder Representation from transformer) with sentiment analysis for analysing a given tweet. The project by using its state-of-the-art software model also briefly studies about the different sentimental patterns outputted by a given set of data while analysing the features of given text, of different text adding to various research aspects.I.
Sistem Pakar Diagnosa Penyakit Kulit Anjing Dengan Algoritma Pohon Keputusan dan Perhitungan Gini

An expert system is a computer system that is characterized by the fact that the distinction made between the problems on the knowledge described in a program and part to replicate the knowledge to solve the problem is to use existing data. In use, the expert system can be used to help a particular field but the expert system still does not eliminate or harm related parties who work in the field. Being an expert system is a software package or computer program package intended as a provider of advice and aids in solving the problems in certain specialist fields such as science, engineering, mathematics, medicine, and education. One application of expert systems is to perform a diagnosis. With the expert system aims to help users in knowing the illness suffered by pets. With the help of the program the decision tree can produce a diagnosis of the symptoms that have been selected. Data obtained directly from a veterinarian. The data used in this study were 105 data consisting of 11 illnesses and 11 symptoms. With the data already available then the decision tree will be set up by using scikit-learn. Having made the decision tree, analysis is performed by taking 10 cases were given directly by an expert or doctor. In addition to the analysis, performed well for distributing a survey to respondents who have a dog. In one survey proves about 8 people (25.8%) answered strongly agreed, and 10 (32.3%) responded agreed that help ease in knowing the illness suffered by dogs. In 10 cases of experts obtained an accuracy of 80%. The results of cross validation performed 4 times to get an average of 67.6%.
Blind Image Deblurring based on Kernel Mixture

Blind Image deblurring tries to estimate blurriness and a latent image out of a blurred image. This estimation, as being an ill-posed problem, requires imposing restrictions on the latent image or a blur kernel that represents blurriness. Different from recent studies that impose some priors on the latent image, this paper regulates the structure of the blur kernel. We propose a kernel mixture structure while using the Gaussian kernel as a base kernel. By combining multiple Gaussian kernels structurally enhanced in terms of scales and centers, the kernel mixture becomes capable of modeling nearly non-parametric shape of blurriness. A data-driven decision for the number of base kernels to combine makes the structure even more flexible. We apply this approach to a remote sensing problem to recover images from blurry images of satellite. This case study shows the superiority of the proposed method regulating the blur kernel in comparison with state-of-the-art methods that regulates the latent image.
Quantum algorithms for learning a hidden graph and beyond

We study the problem of learning an unknown graph provided via an oracle using a quantum algorithm. We consider three query models. In the first model ("OR queries"), the oracle returns whether a given subset of the vertices contains any edges. In the second ("parity queries"), the oracle returns the parity of the number of edges in a subset. In the third model, we are given copies of the graph state corresponding to the graph. We give quantum algorithms that achieve speedups over the best possible classical algorithms in the OR and parity query models, for some families of graphs, and give quantum algorithms in the graph state model whose complexity is similar to the parity query model. For some parameter regimes, the speedups can be exponential in the parity query model. On the other hand, without any promise on the graph, no speedup is possible in the OR query model. A main technique we use is the quantum algorithm for solving the combinatorial group testing problem, for which a query-efficient quantum algorithm was given by Belovs. Here we additionally give a time-efficient quantum algorithm for this problem, based on the algorithm of Ambainis et al.\ for a "gapped" version of the group testing problem. We also give simple time-efficient quantum algorithms based on Fourier sampling and amplitude amplification for learning the exact-half and majority functions, which almost match the optimal complexity of Belovs' algorithms.
Hermann von Helmholtz and the aesthetics of the acoustics

Objective The aim of this study was to honour the 100-year birth jubilee of Hermann von Helmholtz (1821–1894), and his studies on the ‘aesthetics of acoustic’.Methods We will present original documents and historical references.Results After a brief section of biographical notes on von Helmholtz, we present the results of his acoustic studies and the analysis of his work ‘On the sensation of tone’.Conclusion von Helmholtz devoted part of his researches to acoustics, also creating new tools of his invention as his eponymy named resonators.
A Study on the 2010 and 2014 Election Pledges and Inaugural Address of the Superintendent Using Language Network Analysis Method

이 연구는 전국동시 지방선거로 2010년 선출된 민선교육감과 2014년 선출된 민선교육감의 선거공약과 취임사를 분석하였다. 분석방법은 기존의 수사학이 분석할 때 발생하는 문제점을 보완한 언어 네트워크 분석을 실시하여 선거공약과 취임사에 출현한 단어의 빈도와 연결 중심성, 매개 중심성, 아이겐벡터 중심성 분석 결과와 네트워크 지도를 제시하고, 분석결과를 논의하였다. 이 연구를 통해 2010년 보수성향 민선교육감은 학력, 인성, 창의 등이 출현빈도와 중심성이 높은 단어였고, 진보성향 민선교육감은 혁신, 혁신학교로 파악되었다. 2014년에는 교육감의 가치지향과 관계없이 안전이 출현빈도와 중심성이 높은 단어였으며, 보수성향 민선교육감은 인재, 교육환경, 행복 등이고, 진보성향 민선교육감은 교육비, 교육복지, 무상급식, 무상교복 등이었다. 민선교육감들은 가치지향에 따라 선거공약과 취임사의 주요단어가 다르게 출현하였고, 선거공약과 취임사도 연관성을 나타냈으며, 시·도별 지방교육정책에도 반영된 것으로 파악되었다.This study analyzed the election pledge and inaugural address of the election on civilian superintendent elected in 2010 and 2014 of election nationwide. In this paper, we analyzed language network analysis method, and selected language network analysis to overcome the problem of analyzing existing rhetoric. In other words, the frequency, degree centrality, betweenness centrality, eigenvector centrality analysis results and network map of the words appearing in election pledge and inaugural address were presented and the analysis results were discussed in this paper. As a result of research, the conservative superintendent of ‘education’, ‘human resources’, ‘creativity’ were high frequency and centrality, on the hand progressive superintendent was identified as ‘innovation’ and ‘innovation school’ in 2010. In 2014, ‘safety’ was a high frequency and centrality regardless of the superintendent’s value orientation. The conservative superintendent used words of ‘human resources’, ‘educational environment’ and ‘happiness’, whereas the progressive superintendent was chosen words of ‘education expenses’, ‘education welfare’, ‘free lunch’ and ‘free school uniform’. The superintendents used the key words of election pledge and inaugural address differently according to their value orientation. The election pledge and inauguration were also correlated and were also reflected in the local education policy by city and provincial office of education.
Lärares upplevelser av den återkoppling som ges när elever arbetar med digitala matematikuppgifter : En kvalitativ intervjustudie med lärare i årskurs 4–6

The digitalization of the school has led to teachers increasingly using digital tools in their teaching of mathematics. In comparison with other subject, however, mathematics sees the least use of ...
Beyond the Pixels: Exploring the Effects of Bit-Level Network and File Corruptions on Video Model Robustness

We investigate the robustness of video machine learning models to bit-level network and file corruptions, which can arise from network transmission failures or hardware errors, and explore defenses against such corruptions. We simulate network and file corruptions at multiple corruption levels, and find that bit-level corruptions can cause substantial performance drops on common action recognition and multi-object tracking tasks. We explore two types of defenses against bit-level corruptions: corruption-agnostic and corruption-aware defenses. We find that corruption-agnostic defenses such as adversarial training have limited effectiveness, performing up to 11.3 accuracy points worse than a no-defense baseline. In response, we propose Bit-corruption Augmented Training (BAT), a corruption-aware baseline that exploits knowledge of bit-level corruptions to enforce model invariance to such corruptions. BAT outperforms corruption-agnostic defenses, recovering up to 7.1 accuracy points over a no-defense baseline on highly-corrupted videos while maintaining competitive performance on clean/near-clean data.
Striping input feature map cache for reducing off-chip memory traffic in CNN accelerators

Data movement between the Convolutional Neural Network (CNN) accelerators and off-chip memory is critical concerning the overall power consumption. Minimizing power consumption is particularly important for low power embedded applications. Specific CNN computes patterns offer a possibility of significant data reuse, leading to the idea of using specialized on-chip cache memories which enable a significant improvement in power consumption. However, due to the unique caching pattern present within CNNs, standard cache memories would not be efficient. In this paper, a novel on-chip cache memory architecture, based on the idea of input feature map striping, is proposed, which requires significantly less on-chip memory resources compared to previously proposed solutions. Experiment results show that the proposed cache architecture can reduce on-chip memory size by a factor of 16 or more, while increasing power consumption no more than 15%, compared to some of the previously proposed solutions.
Collision Free Motion Planning on a Wedge of Circles

We exhibit an algorithm with continuous instructions for two robots moving without collisions on a track shaped as a wedge of three circles.We show that the topological complexity of the configuration space associated with this problem is 3.The topological complexity is a homotopy invariant that can be thought of as the minimum number of continuous instructions required to describe the movement of the robots between any initial configuration to any final one without collisions.The algorithm presented is optimal in the sense that it requires exactly 3 continuous instructions.
STUDI PERBEDAAN KOMPOSISI PADA SINEMATOGRAFI DAN EFEK YANG DIHASILKAN

Abstract:Cinematography is an applied science that discusses the technique of capturing images and simultaneously combining these images into a series of images that have a story idea or delivery of one thing. This encourages researchers to make research on the study of cinematographic composition and the resulting effects. Researchers used qualitative research methods and comparative methods by distributing questionnaires. Data collected to find out the extent of interest regarding cinematography, differences in effects on cinematography and cinematographic results have a variety of uniqueness and differences in each shooting according to the technique applied. Cinematography for some people is easy to apply because they have previously done photography.
STRATEGI TATA KELOLA ADMINISTRASI PADA PERGURUAN TINGGI BERBASIS ELECTRONIC RECORDS

Governance administration referred to in this research is how institutions organize, manage, and store data/records relating to the implementation of the administrative activities of Higher Education institutions, starting from the leadership down to the student level. The corporate governance is an activity that needs to be done effectively and efficiently in order to support productivity college. So far, the administration at the College still done conventionally. This is evident from the number of files and archives college piled up in the room and a filing cabinet. Thus, to find back the document that has been stored in cabinets require considerable time, besides that it must dismantle all the documents that have been previously arranged. The research method uses a qualitative approach, Draft Action Research utilizes quantitative data with qualitative data such as method mix focused on applied technology. Based on the research results obtained by the collected records in IKIP Mataram records are divided into several groups. By performing data reduction, grouping the records contained in the IKIP Mataram look that good governance based administration of electronic records has been applied properly. There are nine groups of records obtained in this study in which each group of records managed by each institution and the IKIP Mataram. Use of Electronic Records in the administration and other administrative activities at the IKIP Mataram very effective. All data on their activities and archives stored neatly in the respective chambers, structured data classification, and search data is quite efficient.Use of Electronic Records that can be controlled systematically to records from the time of creation or receipt, processing, distribution, organization, storage, retrieval up to destruction. Application of Electronic Records in higher education is relevant to the development and advancement of Science and Technology today, the program is a major concern so as to form a permanent administrative governance, especially at the IKIP Mataram.Keywords: Strategy, Governance, Electronic Records
A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks

With the advent of deep learning, the number of works proposing new methods or improving existent ones has grown exponentially in the last years. In this scenario, “very deep” models were emerging, once they were expected to extract more intrinsic and abstract features while supporting a better performance. However, such models suffer from the gradient vanishing problem, i.e., backpropagation values become too close to zero in their shallower layers, ultimately causing learning to stagnate. Such an issue was overcome in the context of convolution neural networks by creating “shortcut connections” between layers, in a so-called deep residual learning framework. Nonetheless, a very popular deep learning technique called Deep Belief Network still suffers from gradient vanishing when dealing with discriminative tasks. Therefore, this paper proposes the Residual Deep Belief Network, which considers the information reinforcement layer-by-layer to improve the feature extraction and knowledge retaining, that support better discriminative performance. Experiments conducted over three public datasets demonstrate its robustness concerning the task of binary image classification.
Le condizioni ricavabili dal Regolamento generale sulla protezione dei dati per le applicazioni nazionali di tracciamento dei contatti: alcune considerazioni

In order to manage the COVID-19 pandemic, several EU Member States have decided to use contact tracing apps, which can display different characteristics: some of them rely on Bluetooth technology, while others on GPS location; some of them adopt a decentralised approach in data collection, while others a centralised approach. The present Insight focuses on the conditions that such apps must follow in order to be respectful of the General Data Protection Regulation (GDPR). First of all, it is necessary to choose a suitable legal basis for the processing, remembering that when sensitive data (such as health data) are collected the range of possibilities is even narrower. Depending on such choice, the processing is subject to different limits. Secondly, there are many principles which must be followed in any case, such as purpose limitation, data minimisation and storage limitation. Finally, the data subject must be put in a position to exercise his rights, and the data controller must fulfil obligations such as carrying out an impact assessment and adopting adequate security measures. Taking into consideration such conditions, it seems clear that according to the GDPR some contact tracing apps are more preferable than others, depending on their characteristics. In conclusion, it is possible to state that the GDPR balances public health and data protection by suggesting a graduality principle: the less privacy-invasive solution must be chosen, and it can be incremented only if the purposes cannot be sufficiently achieved. It is the only way to build trust in the users and therefore guarantee the effectiveness of the measures.
EFFECT OF ORGANIZATIONAL JUSTICE AND CONFLICT MANAGEMENT ON LOYALTY OF VOCATIONAL HIGH SCHOOL TEACHERS IN CENTRAL JAKARTA INDONESIA

The purpose of this study is to comprehensively describe and describe the effect of organizational justice and conflict management on loyalty of vocational school teachers in central Jakarta indonesia. This research was conducted to Private Vocational High Schools (SMK) in central Jakarta. Research methods This study uses a quantitative research survey method, as for analyzing data using path analysis. Path analysis technique in this study is to determine the causal relationship between variables or the direct influence of exogenous variables on endogenous variables. Endogenous variables in this study are teachers loyalty, while the exogenous variables in this study are organizational justice and conflict management. Data collection was carried out through questionnaire filling. Based on the calculation results obtained by path analysis 1) the direct effect of organizational justice on teachers loyalty, the value of the path coefficient of 0.425 and tcount of 6.6964, meaning that organizational justice has a direct positive effect on teachers loyalty can be accepted increasing organizational justice resulting in increased teachers loyalty. 2) the direct effect of conflict management on the teachers loyalty, path coefficient of 0.225 and tcount of 3.378. Means, the direct influence of conflict management on teachers loyalty, the value of the path coefficient of 0.425 and tcount of 6.6964. 3)organizational justice has a direct positive effect on teachers loyalty can be accepted. That is, increasing organizational justice results in increased teachers loyalty.
Shaping the Next Normal – Explorative Expert Survey Among Teachers

The Covid 19 pandemic has fundamentally changed the importance of digital HEI teaching. The digitisation of a course of study poses many challenges for teachers. This paper presents the results of a survey of lecturers at the DHBW (Baden-Wuerttemberg Cooperative State University). Challenges and opportunities were examined in order to derive recommendations for good digital teaching for the future. This paper is based on three pillars: (a) recommendations for good online teaching, (b) a list of the institutional support requirements, and (c) a foresight on the future of digital teaching. In summary, it can be seen that teaching concepts have changed fundamentally as a result of the Covid-19 pandemic. While some courses have been converted to online frontal teaching, other formats promote the self-learning process of students by emphasising self-study, with teachers moving away from the classic role of knowledge mediators and increasingly acting as coaches. This can be seen as an effort to make the best possible use of the new conditions created by the pandemic in order to move higher education teaching from pure knowledge transfer to competence transfer. The aim of the present analysis is to promote the digitization of courses in the long term and to make lasting improvements. The results should help teachers to design their courses efficiently and in a way that is appropriate for the target group and to improve the quality of teaching in the long term.
WHATSAPP GOES TO CLASSROOM : USING WHATSAPP TO FOSTER STUDENTS’ SPEAKING SKILL IN SPEECH

Language learning by using technology has a great impact to improve language skills due to teenagers have close relationship with social network. Social network has opened up new opportunities of interaction and collaboration between teachers and learners. One of trends using social networking is WhatsApp.  WhatsApp offers various features including audio and video enable the users to take benefit for learning. WhatsApp is not only sending text message but files and message broadcasting. Even with WhatsApp, the learning and information sharing happen at the comfort when students are bad especially in Speaking Skill on Speech Subject. Students often feel not comfortable when they are delivering speech in front of many people due to some of them  are not accostomed to speak on stage. In this case, they can begin to show their performance in speech by using whatsApp through WhatsApp group. In addition it can save teacher’s time in assesment. This article aims to study the use of WhatsApp in English language classroom to optimize the function of the mobile phone for students’ speech. It can be said that the integration of WhatsApp into their education will be easy, fun, and useful.
ARIMA MODELS UNTUK MEMPREDIKSI TINGKAT PERCERAIAN DI LOMBOK TIMUR

Selong Religious Court Office is one office whose duties take care of various cases, one of which is divorce cases. Divorce in East Lombok changes every year. Based on data from Selong Religious Court, divorce annually in East Lombok increased. To find out whether divorce matters in two the coming year will experience an increase as well or rather has decreased then an analysis of time series (forecasting) with using the ARIMA (Autoregressive Integrated Moving Average) method. The aim is to find out which time series model is right for forecasting divorce rates and also to find out how many results from divorce forecasting in East Lombok Regency 2020-2021. Based on the analysis results got that the best model is ARIMA (3,1,3) with an MSE value of 220.6. From the forecasting results it is known that the total number of divorce predictions for 2020 are January (124), February (984), March (100), April (123), May (96), June (104), July (122), August (93), September (107), October (120), November (92), December (111). Whereas forecasting for 2021 is January (118), February (91) March (114), April (115), May (91), June (117), July (112), August (91), September (119) , October (108), November (93), December (121).