Reviewerly/exHarmony huggingface dataset:
ORGANIZATION OF EDUCATIONAL ENVIRONMENT AT THE PEDAGOGICAL UNIVERSITY FOR THE IMPLEMENTATION OF THE NEW UKRAINIAN SCHOOL REFORM

The article deals with the concept of the educational environment - a set of conditions that affect the development and formation of abilities, needs, interests, consciousness of the future teacher is a set of material factors, interpersonal relations of subjects of education and specially organized psychological and pedagogical conditions of personality formation. Emotionally favorable state of the educational environment is determined by the formation of individual intellectual level, focused on academic preparation, organization of life, stimulation of student's personal development. The state of an emotionally favorable environment is determined by cultural values, institution, its traditions, positive image./The main indicators and criteria of the emotionally favorable emotional environment of the university are the emotional-positive mood; empathy; mobility; satisfaction with the choice of future profession, emotional and sensual unity; environmental friendliness. Creating a favorable climate in an emotionally-supportive educational environment is an important component of pedagogical work, as psychologically healthy, creative, confident future teachers are of particular value for the implementation of the educational reform of the New Ukrainian School.
Text Classification Based on LDA and Semantic Analysis

The quality of text features directly affects the text classification effect, in order to get the text features which have the high contribution to the text classification in class, this paper proposes a text classification method based on LDA model and category semantic similarity method. The method selects text document topic features by the LDA model and calculates the semantic similarity between these features and categories combined with the word vector model. According to the size of similarity, the weight of the text feature is obtained, and the text classification feature selection and text classification are realized. Finally, the feasibility, validity and correctness of the algorithm are verified by experiments.
Meningkatkan aktifitas dan hasil belajar peserta didik melalui model pembelajaran Teams Games Tournament (TGT) menggunakan media “ATM BCA”

Learning models or media that are appropriate to the characteristics of the material, and students can increase the effectiveness of learning. Models that can involve students can improve understanding of the material and the same conditions also apply to media that are by the characteristics of the material. Teams Games Tournament (TGT) learning model using the media "ATM BCA" through the steps: (1) Information, (2) Grouping, (3) Planning, (4) Acting, (5) Organizing, (6) Presenting and Reward, (7) Evaluating is an effort to achieve that goal. This research is action research carried out in two cycles, each cycle consisting of two meetings. The results of this study indicate that the activities and learning outcomes of students have increased significantly. DOI: 10.17977/um022v4i22019p074
Desain Transmitter Portabel Untuk Komunikasi Data

Digital data is one of the data or information that is often misused, therefore this research begins by studying various literatures related to the encryption system used in cryptographic techniques. And based on the literature that was read, made a series of design and encryption system design program based on Thonny Python. The results of the design are then realized by creating a series of file encryption systems through the application program. The results obtained from this study are the encryption system created in Thonny Python has been able to randomize the original information in this case in the form of a file and is able to transmit the encrypted data with various limitations. This study discusses digital data communication systems using HF radio waves with its main device as a complete communication radio with antenna and power supply, and is equipped with a Raspberry as an enhancement to digital data processing and FSK Modulator as an interface between Raspberry and HF radio that functions as a digital signal modifier that out of Raspberry becomes an analog signal as input for HF radio.
Forensik Internet Of Things pada Device Level berbasis Embedded System

&lt;p&gt;Perangkat Internet of Things (IoT) merupakan perangkat cerdas yang memiliki interkoneksi dengan jaringan internet global. Investigasi kasus yang menyangkut perangkat IoT akan menjadi tantangan tersendiri bagi investigator forensik. Keberagaman jenis perangkat dan teknologi akan memunculkan tantangan baru bagi investigator forensik. Dalam penelitian ini dititikberatkan forensik di level internal device perangkat IoT. Belum banyak bahkan belum penulis temukan penelitian sejenis yang fokus dalam analisis forensik perangkat IoT pada level device. Penelitian yang sudah dilakukan sebelumnya lebih banyak pada level jaringan dan level cloud server perangkat IoT. Pada penelitian ini dibangun environment perangkat IoT berupa prototype smart home sebagai media penelitian dan kajian tentang forensik level device. Pada penelitian ini digunakan analisis model forensik yang meliputi collection, examination, analysis, dan reporting dalam investigasi forensik untuk menemukan bukti digital. Penelitian ini berhasil mengungkap benar-benar ada serangan berupa injeksi malware terhadap perangkat IoT yang memiliki sistem operasi Raspbian, Fedberry dan Ubuntu Mate. Pengungkapan fakta kasus mengalami kesulitan pada perangkat IoT yang memiliki sistem operasi Kali Linux. Ditemukan 1 IP Address komputer penyerang yang diduga kuat menanamkan malware dan mengganggu sistem kerja perangkat IoT.&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;&lt;p class="Abstract"&gt;&lt;em&gt;The Internet of Things (IoT) is an smart device that has interconnection with global internet networks. Investigating cases involving IoT devices will be a challenge for forensic investigators. The diversity of types of equipment and technology will create new challenges for forensic investigators. In this study focused on forensics at the IoT device's internal device level, there have not been many similar research that focuses on forensic analysis of IoT devices at the device level. Previous research has been done more at the network level and cloud level of IoT device's. In this study an IoT environment was built a smart home prototype as a object for research and studies on forensic level devices. This study, using forensic model analysis which includes collection, examination, analysis, and reporting in finding digital evidence. This study successfully revealed that there was really an attack in the form of malware injection against IoT devices that have Raspbian, Fedberry and Ubuntu Mate operating systems. Disclosure of the fact that the case has difficulties with IoT devices that have the Kali Linux operating system. Found 1 IP Address of an attacker's computer that is allegedly strongly infusing malware and interfering with the work system of IoT devices.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;strong&gt;&lt;br /&gt;&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;
A survey on readiness of cloud based queuing management system implementation to mobile users

&lt;span lang="EN-GB"&gt;Queuing Management System (QMS) has been used in medical facilities to manage crowd systematically and reduce customer dissatisfaction. However, customers that use conventional QMS needs to be within the facility to have access to the QMS information. With the integration of mobile application and cloud based QMS, customers are able to access QMS information anywhere. However, migrating to a new technology requires a study on the readiness of the system. Hence, the objective of this study is to understand the effect of implementing QMS by investigating the effect of time efficiency, cost efficiency, accessibility, reliability, variety, convenience towards customer satisfaction. 311 respondents were given survey questions with 100% response rate. The results were analysed using Statistical Package for the Social Sciences. For reliability analysis, the survey questions were proven to be valid, where factor analysis done supports the results to be effective for further analysis. Correlation and regression analysis done also show that there are influences between the independent variables and the dependent variable.&lt;/span&gt;
Determination of Net Radiation Balance using Satellite Imagery in Odeda Local Government Area, Ogun State, Nigeria

The energy received on the earth surface is responsible for driving activities on the earth and not all energy emitted by the sun reaches the earth surface; some are absorbed, reflected or scattered. There is need to determine the amount of energy that reaches the earth surface since not all the energy emitted from the sun reaches the earth. This energy is also responsible for making our general climate warm which ultimately brings us to the determination of Net radiation. This study applied remote sensing method to determine net radiation over Odeda Local Government Area. A Sentinel image from 2013 covering the study area was downloaded and computations were done using bands 5 and 7. These bands were used to compute the surface albedo, incoming short wave radiation, incoming long wave radiation and outgoing long wave radiation. The spectral signatures for each component from sentinel data were analysed, using the ArcGIS 10.6. The results showed the net radiation to be of moderate intensity with values ranging between 630.83 wm-2 and 684.68 wm-2 . The mean value over majority of the area was 651.20 wm-2 and the albedo of the area was low, with values ranging from 0.0028 to a value of 0.29 which is an indication of low reflectivity. This implied that more radiation was absorbed in the study area which impacted the soil temperature thereby influencing reduced soil moisture and a higher rate of evapotranspiration from plants within the study area.Keywords: thermal energy, atmospheric transmissivity, spatial analysis, surface albedo
Emotional speech feature selection using end-part segmented energy feature

The accuracy of human emotional detection is crucial in the industry to ensure effective conversations and messages delivery. The process involved in identifying emotions must be carried out properly and using a method that guarantees high level of emotional recognition. Energy feature is said to be a prosodic information encoder and there are still studies on energy use in speech prosody and it motivate us to run an experiment on energy features. We have conducted two sets of studies: 1) whether local or global features that contribute most to emotional recognition and 2) the effect of the end-part segment length towards emotion recognition accuracy using 2 types of segmentation approach. This paper discussed about Absolute Time Intervals at Relative Positions (ATIR) segmentation approach and global ATIR (GATIR) using end-part segmented global energy feature extracted from Berlin Emotional Speech Database (EMO-DB). We observed that global feature contribute more to the emotional recognition and global features that are derived from longer segments give higher recognition accuracy than global feature derived from short segments. The addition of utterance-based feature (GTI) to ATIR segmentation somewhat contributes to increase the accuracy by 5% up to 8% and conclude that GATIR outperformed ATIR segmentation approached in term of its higher recognition rate. The results of this study where almost all the sub-tests provide an increased result proving that global feature derived from longer segment lengths acquire more emotional information and enhance the system performance.
Which Types of Education are Important for Economic Growth?

The relationship between education and economic growth has been discussed on numerous occasions, and there is a consensus that education plays an important role toward economic growth. This paper empirically examines 55 countries’ panel data to determine which types of education are playing important roles for achieving economic growth. The results showed that the improvement of educational systems, finance skill, Internet usage, and English proficiency has a positive impact on economic growth. On the other hand, educational systems and Internet usage also shrink inequality in the economy. High quality education for students is important for attaining economic growth, and it would confer student’s chances and opportunities and promote sound economic growth.
Impact of Shakhty trial 1928 on the status of “bourgeois” engineering and technical intelligentsia in the USSR

Shakhty trial of 1928 again raised the question of party and state's attitude towards "bourgeois" intelligentsia.Accusation of "wrecking" made against a group of engineers and technicians in brought to the forefront of Soviet propaganda demand for political identification of intelligentsia with prevailing ideology and regime.At the same time, suspicions about the presence of "counter-revolutionaries" not yet identified in the economy opened the gateways for attacks on engineering and technical personnel "from below", primarily from proletariat.The calls to establish control "from below" over the activities of specialists led to destabilization of the previously existing labor subordination, sharply weakening the authority of engineering and technical workers.In addition, the control placed specialists under abnormal conditions: engineering and technical workers often did not dare to take responsibility for making production decisions, for fear of being accused of "wrecking".As a result of the Shakhty affair, the economy was positioned as an arena for the struggle between "revolutionary" and "counter-revolutionary" forces, and any professional activity began to be regarded as political."Wrecking" in the Donbass turned out to be a good example for the authorities that education, special professional knowledge and skills could be used as a weapon of "counter-revolutionary struggle".Logic of this struggle dictated that belonging to one side or another in this battle was determined, inter alia, by social origin and pre-revolutionary status.This not only accelerated etraining of "red" specialists, but also led to increased hostility to corporate culture of "old" technical intelligentsia.
Penerapan Jaringan Saraf Tiruan untuk Mengukur Korelasi Beban Kerja Dosen Terhadap Peningkatan Jumlah Publikasi

One important point in carrying out the functions of the Tridharma of Higher Education by lecturers is to carry out research and publish the results of their thoughts and analyzes. The demands of publication by the academic community of Higher Education have a considerable impact on the awareness of the lecturers of the importance of conducting studies, research and writing scientific works. The development of scientific work in Indonesia has been relatively better, especially since the enactment of government regulations, which required S1, S2 and S3 students to write articles in scientific journals as one of the prerequisites for graduation. Lecturers certainly have greater demands to actively write in scientific journals both at accredited national level and reputable international journals. So the authors conducted this study aimed at analyzing the correlation of the level of lecturer workload to the increase in the number of publications. STIKOM Tunas Bangsa does not yet have a system to analyze the level of lecturer workload with an increase in the number of studies. For this reason, it is necessary to apply the Backpropagation algorithm. ANN combined with the Backpropagation algorithm can measure the level of correlation. The variables used are structural positions, number of even and odd semester credits, number of services. The target used is the amount of research. So the pattern of correlation between the two variables is formed. The output of the lecturer workload is reduced by the target which is the number of publications. So the results obtained are correlations between lecturers' workloads to the increase in the number of publications.
111 Medisense technology for breast cancer

<h3>Introduction</h3> It is not uncommon for a patient coming to the NHS to present with investigations and treatments done in EU countries and outside the EU for various medical and surgical conditions. Many times, reports are written in languages other than English and therefore does not to contribute to medical consultations. Another issue with the patients is that they feel helpless and frustrated when they can’t understand what the reports mean for them. To resolve these problems, we developed a technology called Medisense is a medical report image capture, data extraction, validation and interpretation technology. By using this technology, doctors and patients can take a snap of the picture of any report and get an instant translation, interpretation and review of the report. <h3>Study design</h3> In the current study, we carried out 97 cases of breast cancer histopathology reports of various patients. The test was carried out using a specified protocol in a test environment. <h3>Results</h3> The study results show that in all the 97 cases, the image capture was successful. However, the data extraction was successful only in 93 cases. In 90 cases, the data interpretation was correct. In the 4 instances where image capture was not successful, the poor printing quality of the report(n=1), folds and creases in the report(n=1), and technical error(n=2) was responsible. <h3><b>Conclusion</b>s</h3> Medisense will be a helpful tool in medical consultations when a patient arrives with a report in a non-native language. This would also help patients interview and interpretation of their medical reports. Further studies and improvements are required to optimise this technology further.
Exploration of Incentive Mechanism on Informatization Management of the University

In order to effectively promote the information construction in this paper expounds the necessity of information construction, clearly constructs the principle of information incentive based on the present situation of information construction in SWPU (Southwest Petroleum University), and puts forward various effective measures to mobilize teachers and all units to actively participate in information construction. The reasonable and effective use of incentive measures not only promotes the better development of information construction, but also achieves the effect of strengthening university service, guaranteeing teaching and encouraging the cultivation of innovative talents.
A Survey on Data Replication and Resource Management in Distributed Systems

Data replication provides an efficient mechanism in dealing with data (or storage that hold these data) in large-scale distributed systems.Generally, data replication is one of the optimization strategies which have been implemented in the distributed systems including database communities where several copies of data are kept at two or more resource sites to achieve performance at high level, availability and reliability of the distributed systems.Consequently, it is realized that the resource selection process (as part of resource management) is tightly coupled with data replication strategies and resource management in distributed systems.Accordingly, this paper discusses of the existing data replication techniques in distributed systems, in particular distributed DBMS, Data Grids and Cloud computing environments.Further, a review of resource management in distributed systems is also provided, with specific focus on both Grids and Cloud computing.
REPRESENTATION OF ECOLOGICAL CONTENTS IN EDUCATION AND ASSESSMENT IN LOWER GRADES OF PRIMARY SCHOOL

The subject matter of this research is the representation of ecological contents in teaching in junior primary school and not only does it have practical application, but also theoretical. The ecological contents of teaching in junior primary school are directed towards the education of students and their development for the improvement of their immediate environment. In order to successfully approach the improvement in teaching lower grade students in primary school, regarding ecological contents, it is necessary first to examine and determine how many of our schools are represented. The aim and task of the research was to point out the importance of ecological contents and their representation in teaching in junior primary school. Accordingly, the paper presents a part of the research that shows what teachers think about the representation of ecological contents in the classroom. The research has shown that this is a very important topic.
Implementasi Data Mining dalam Mengelompokkan Rumah Tangga Kumuh di Perkotaan Berdasarkan Provinsi Menggunakan Algoritma K-Means

Slum is an area with a high population density levels in the city are generally inhabited by the poor and the unemployment rate is high, the slum also became a center of health problems because the conditions are not higenis. Slum slum household is is the home that do not have access to a source of drinking water, have no access to decent sanitation, have no access to floor area &gt; = 7.2 m2 Per capita, and do not have access to conditions the roof, floor, and walls. This study used data sourced from the Central Bureau of statistics the year 2015 – 2016. The method used is Datamining the K-Means Clustering, Clustering is a method used in datamining the how it works find and classify data that has a semblance and characteristics of data between one another with the data. Using this algorithm the data already obtained can be grouped into Clusters based on this data. This data can be entered to the local Government to recommend to the Government so that the Government can handle the Spreader area development assistance to areas of slum households.
A High Accuracy Nonlinear Dimensionality Reduction Optimization Method

In the analysis and processing of image recognition, extracting useful and valuable data from the original dataset has become a problem. Since the data to be processed often presents high dimensional and nonlinear feature, reasonable dimensionality reduction is an necessary method for improving the accuracy of data analysis. One of the dimensionality reduction methods Kernel Principal Component Analysis (KPCA) has certain advantages in dealing with nonlinear data, but it also has defects when facing the dataset in which data owe highly complex relationship. The other linear dimensional reduction method Linear Discriminant Analysis (LDA) has supervisory characteristics, which can reduce the dimensionality of dataset in which data owe highly complex relationship. However it can only handle linear data. So we propose a hybrid method which is the combination of the above two methods called KPCA-LDA. By it the new dataset obtained by the step of dimensionality reduction is beneficial to be processed in next step for classification. We combine KPCA-LDA with the Back Propagation Neural Network (BPNN) method to achieve the classification of handwritten numbers. The experimental results show that the classification accuracy of the proposed KPCA-LDA-BPNN model can reach 98.67%, which is about 3%-5% higher than the original method using K Nearest Neighbor (KNN) and Support Vector Machine (SVM).