Reviewerly/exHarmony huggingface dataset:
Administrative, Infrastructural and Finance Related Factors Affecting Private Investment in East Gojjam Zone of Amhara Regional State, Ethiopia

The aim of this paper is to identify the main factors related to administrative, infrastructure and market related issues affecting private investment activities in East Gojjam zone with the intention of providing valuable information about the investment environment of the zone to potential investors.Descriptive type of research design has been used in this study by giving more emphasis on qualitative data analysis method.On the other hand, quantitative research analysis has been used to provide numerical measurement and analysis of the magnitude and extent of the problem and trend of private investment in the Zone.The study used both primary and secondary data.Pre-designed self-administered questionnaire has been used to collect primary data.In order to obtain primary data, a total of 310 questionnaires were distributed to investors found in East Gojjam zone and 305 of them were filled and returned to researchers.The outcome of this study revealed that, the major bottlenecks of investment in East Gojjam related to administrative and policy related factors include policy distortions and rent seeking, direct government involvement in some investment areas, corruption and dysfunction of the judiciary system, malpractices in granting licenses of investment activities, favoritism in tax revenue collection, arbitrary and inappropriate enforcement of business regulations, bureaucracy and policy implementation delay.Whereas, infrastructural factors affecting private investment include inadequate electric energy, poor water supply and transportation and communication problems.Shortage of foreign currency, fluctuations of exchange rates, access to credit in formal financial institutions, inadequate amount of loan, high interest rates, and bureaucracy of lending institutions to give loan are finance related factors affecting private investment in the study area.
Fin, Whale, Coin and Flatterer: Exploring Tangibles for Air Traffic Control

Air traffic control (ATC) is a safety-critical work domain that has a history of applying tangible elements in its workstations. In the past, development was mostly technology-driven, which resulted in usability challenges like handling multiple input and output devices. In this work, we followed a user-centred design approach with air traffic controllers (ATCOs). Starting from the users’ need for haptic feedback, we developed a novel tangible interaction concept for ATC. We iterated a set of tangibles – Fin, Whale, Coin, and Flatterer – based on formative evaluations with 24 ATCOs. From our qualitative results we extracted dimensions relevant to ATCOs‘ user experience including familiarity, efficiency and engagement. Our results can provide guidance and inspiration for the design of future ATC interfaces.
“Ana Malie” The Traditional Buginise Song Lyrics in Discourse Analysis

This study aimed to find out discourse analysis of traditional Buginese songs through elements used in the song.By analysing the lyrics of the song and focuses on the discourse widely used in the song.The study uses qualitative descriptive method.Some discourse devices that used are cohesion, coherence, intentionality, acceptability, informativeness, situationality, and intertextuality. In this song the cohesion of each part of the sentence does not appear, it is because the sentences depend on each other.The coherence in this song is clear enough because the meaning of each part of the sentences can be easily understood. The writer’s intentionality stated in a clear word that the writer used in each of the sentences.In acceptable devices the song is considered acceptable because the song uses phrases or words that are commonly used and known by the society. The informativeness we can gain fromthis song is the story about a mother who feels sorry about her son’s fate in this world, it is measured by constituting some sequence of utterances that contain information. In this song, situationality can be measured fromthe level of coherence and cohesiveness. Some cohesive markers in the song were not available.The sentences in the song are standalone but whether it is coherence or not, for the researcher its coherence. Intertextuality is the relation between texts that are inflicted by means of quotations and allusion The intention of the song writer was explicitly stated. The moral value that is immersed in the song gives a huge lesson of real life situations.
A semantic segmentation algorithm supported by image processing and neural network

The accurate segmentation of the lesion area is of great significance to the actual medical treatment. However, the segmentation results of the current segmentation network are not accurate enough to provide guidance for actual medical treatment. To solve this problem, a improved U-Net segmentation network is proposed. Firstly. The residual module and new attention mechanism are introduced to optimize the encoder, and 2&#x00D7;2 convolution is used instead of pooling operation, which can refine and extract features while retaining spatial feature information. Secondly, the attention mechanism is introduced before the upsampling jump connection, so that the network pays attention to the spatial information of the low-level feature map. The improved U-Net segmentation network was evaluated on the LiTS datasets. Compared with the traditional If-Net, the Dice coefficient and recall rate are increased by 5.6&#x0025; and 3.03 &#x0025; respectively in the liver segmentation task, the Dice coefficient and recall rate are increased by 7.51&#x0025; and 8.8&#x0025; respectively in the liver tumor segmentation task.
The Meaning of Narrative of the Recognition and Resolution of a Character’s Moral Dilemma in Children’s Literature

이 연구는 아동문학에서 인물이 인식하는 도덕적 딜레마와 이를 해소하는 과정에서의 서사적 의미를 분석하였다. 도덕적 딜레마는 특정 선택에 대해 ‘왜’ 그랬는지의 과정을 중시하며 독자로 하여금 아동 인물이 무엇을 느끼고 생각했을지 상상하게 한다. 분석을 위해 세 작품을 선정하였고 아동문학에서 인물이 인식하고 해소하는 도덕적 딜레마를 추적하여 그것의 서사적 의미를 밝혔다. 먼저 아동 인물은 도덕적 문제를 유발하는 딜레마 상황에 대한 무지함으로 잘못된 상황임을 인지하지 못하는 경우로 인해 서사가 진행된다. 또는 가정에서의 결핍이 그들로 하여금 올바르지 못한 선택을 하게 하고, 치밀하지 못하여 곧 타인에게 탄로나게 된다. 그럼에도 아동문학에서는 난처한 상황을 아동이 헤쳐 나가는 서사를 구성하는 경향이 있다. 옳지 못한 선택을 했을 때 그들은 양심의 가책을 느끼며 잘못을 뉘우친다. 이때 성인이나 또래의 역할이 결정적이다. 또는 스스로 뉘우치고 성찰하는 아동 인물의 모습도 확인할 수 있었다. 이와 더불어 아동이 아닌 성인 인물도 스스로의 잘못을 뉘우치는 서사 장면을 제시하여 아동과 성인이 함께 변화하는 양상을 보이기도 한다. 아동문학 속 도덕적 딜레마와 관련된 서사적 의미를 감상하며 독자는 아동 인물이 어떻게 상황을 해소하는지에 관해 관찰하고 상상하며 그 과정을 생생하게 감상할 수 있다. 후속 논의를 통해 도덕적 딜레마의 해소 과정이 독자에게 주는 미적 가치에 관해서도 심층적으로 논의할 것이다. This study analyzed the moral dilemma perceived by the character in children’s literature and the meaning of narrative in the process of solving it. The moral dilemma values the process of ‘why’ for a specific choice and makes the reader imagine, what the child’s character felt and thought. Three works were selected for analysis, and a moral dilemma recognized and resolved by the individual in children’s literature was tracked to reveal its meaning of narrative. First of all, the narrative proceeds due to the case where the child character is unaware of the wrong situation due to ignorance of the dilemma that causes moral problems. Or, deficiency at home causes them to make the wrong choice, and they are not meticulous, so they are soon discovered by others. Nevertheless, in children’s literature, there is a tendency to construct narratives in which children go through difficult situations and When they make the wrong choice, they feel guilty and repent of their mistakes. At this time, the role of adults and peers is crucial. Or, it was possible to confirm the appearance of a child character who regretted and reflected on himself. In addition, adult characters, not children, also present narrative scenes that repent of their faults and show a changing pattern of children and adults together. While appreciating the meaning of narrative related to the moral dilemma in children’s literature, readers can observe, imagine, and vividly appreciate the process of how the child character solves the situation. Through follow-up discussions, we will also discuss in-depth the aesthetic value of the process of resolving moral dilemmas to readers.
Pelatihan Aplikasi Game Edukasi Kahoot Untuk Meningkatkan Motivasi Belajar Siswa Di Era Pandemi Covid 19

Community Service Activities carried out at the Integrated Islamic Elementary School (SDIT) Insan Rabbani in the Bekasi area, aimed at providing training in the learning method of the Kahoot educational game method which can be used as an alternative online learning media by taking advantage of opportunities to play games that can support the improvement of educational services. to teachers and students so that they can motivate teaching and learning activities and can support educational services at SDIT Insan Rabbani to be more fun and be able to evaluate the results of learning activities through giving assignments or quizzes and displaying answers to grades for each student and ranking the best three in each assignments or quizzes given so that with the Kahoot application learning objectives are achieved for each subject, especially during the current covid 19 pandemic. In this training, the method used is the online training method using the zoom application by providing exposure related to the Kahoot application and direct practice on the Kahoot application. So that it is hoped that through this training, it is hoped that the ability to achieve an even understanding and mastery of the teacher council supports learning using the Kahoot application as an alternative learning method to create a more interesting, fun and effective learning process.&#x0D; Keywords: educational game, kahoot application, online, zoom application
EXPLORING ENGLISH TEACHERS’ STRATEGIES IN COPING WITH STUDENTS’ MISBEHAVIOR IN LEARNING ENGLISH: A CASE STUDY AT A PRIVATE VOCATIONAL HIGH SCHOOL IN PEKANBARU

This research aims to exploring English teachers’ strategies in coping with students’ misbehavior in learning English at a Private Vocational High School Pekanbaru. The study employed qualitative approach. The participants of this study involves two English teachers and 85 students of ten grade class. The data collecting technique used in this study were observation and interview. The result of this research discover six types of teachers’ strategies used by English teacher in coping with students’ misbehavior in the classroom. They were; (1) Verbal strategies, (2) Reprimand and punishment, (3) Non-verbal strategies, (4) Pre-empting misbehavior, (5) Dealing with confrontation, and (6) Pastoral care. Verbal strategies and reprimand and punishment used by English teacher quiet often in the classroom. However, verbal strategies is the most frequently strategies used by English teachers in coping with students’ misbehavior in English lessons at SMK TARUNA SATRIA Pekanbaru.
Hybrid approach redefinition with cluster-based instance selection in handling class imbalance problem

Class Imbalance problems often occur in the classification process, the existence of these problems is characterized by the tendency of a class to have instances that are much larger than other classes. This problem certainly causes a tendency towards low accuracy in minority classes with smaller number of instances and also causes important information on minority classes not to be obtained. Various methods have been applied to overcome the problem of the imbalance class. One of them is the Hybrid Approach Redefinition method which is one of the Hybrid Ensembles methods. The tendency to pay attention to the performance classifier, has led to an understanding of the importance of selecting an instance that will be used as a classifier. In the classic Hybrid Approach Redefinition method classifier selection is done randomly using the Random Under Sampling approach, and it is interesting to study how performance is obtained if the sampling process is based on Cluster-Based by selecting existing instances. The purpose of this study is to apply the Hybrid Approach Redefinition method with Cluster-Based Instance Selection (CBIS) approach so that it can obtain a better performance classifier. The results showed that Hybrid Approach Redefinition with cluster-based instance selection gave better results on the number of classifiers, data diversity, and performance classifiers compared to classic Hybrid Approach Redefinition.
<i>A Silvia</i>. Una nota ossianica

Adopting both a philological and comparative approach, this article is the first to propose Cesarotti’s translation of the Ossianic poems as a possible source for the opening of Leopardi’s poem A Silvia. The analysis is divided into two parts, the first of which surveys current trends in studies dedicated to the Ossian-Leopardi connection, including a reconstruction of the historical context and an analysis of Leopardi’s aesthetic and critical observations regarding the Ossianic poems. The second part focuses on the above-mentioned source of inspiration for Leopardi, demonstrating that the impact of Cesarotti’s translation outweighed (or was at least of equal bearing to) that of Petrarch.
An improve image security algorithm using hybrid cryptography approach

In the current communication trend, data transmission through different media is increasing day by day [1].The main data used in the communication are text, images and video.The wide use of data sending and receiving in terms of different pictures increases the demand of image data security.There are different dimensions in the image security research work.There is a lot of research work is going on including different dimensions and aspects [2-10].These aspects include cryptography and steganography techniques along with other mechanism for security breach detection also [11][12][13][14][15].Security mechanism in general handled by cryptography and steganography algorithms [16][17][18][19][20][21].
Combating illicit financial flows in Africa

Africa experienced strong GDP growth from 2000 to 2019, despite declines in commodity prices – including some severe drops in crude oil prices during this period. which particularly affected major oil-exporting countries such as Nigeria. The continent’s average growth rate in this period was around 5 percent but with considerable heterogeneity in growth patterns between countries. This came at a time when other global regions were experiencing a decline or stagnation in their economic activity.
Firebase Authentication Cloud Service for RESTful API Security on Employee Presence System

Authentication is essential in identifying users to access or use the system. One application of the Authentication process is the Presence System. The old Presence System at Amigo Company is prone to misuse and data manipulation, so it is necessary to develop a new Presence System based on Smartphones. Data communication between Back-end and Front-end architecture in Presence System using RESTful API. This study aims to implement security on the RESTful API by using JSON Web Token generated by Firebase Authentication Cloud Service. The results of the study indicate that the user cannot manipulate data or use the identity of another user because of Firebase Authentication security and the strict data verification process.
Application of Artificial Neural Networks Technology for Handwritten Arabic Letters Recognition

The mechanism that convert and detect the handwriting letters by using machine-encoded forms is called handwriting recognition. The interaction between machines and humans is very important so that the handwriting recognition must be found. The complexity of Arabic letters and the similarity of at least three letters is main challenge to recognize them .Thus, our main challenge is to propose a methodology, implementation and evaluation of Arabic letters recognition system by using Artificial Neural Network approach in order to achieve high accuracy with some techniques will be produced in this paper. In this paper, we apply recognition artificial neural network (ANN) for Arabic letters. We use the intensity values of pixels for input of the neural network. These results show that ANN with high number of training images have the highest performace.
AN ANALYSIS OF TEACHER’S STRATEGIES IN TEACHING ENGLISH

This research was conducted to analyze what strategies the teachers have used in teaching English and what factors influence these strategies. This was a descriptive qualitative research for the English teacher of SMAN 1 Segedong. Data collection was carried out using interviews with an English teacher at the school. Data were analyzed using Familiarization and Organizing, Coding and Reducing, Interpreting and Representing. Based on research findings, there were five teaching strategies used by the teacher and three factor influence it. These strategies were discussion strategies, demonstration strategies, using electronic media as learning media, using games and providing reinforcement in the end teaching and learning process. There were three factors that influenced the teacher strategy in English at SMAN 1 Segedong. The first was the student factor which includes the background of the student's majors such as Science and Social Studies, and the student's condition in following the learning process. The second was the factor came from the teacher. This factor concerned the ability of teachers to use technology in supporting teaching strategy. Lastly, the facility includes how the learning tools are limited.
Impact of Similarity Measure Functions on the Performance of Coherent Filtering Detection

Coherent motions depict the collective movements of individuals in crowd, which widely exist in physical and biological systems. In recent years, similarity-based clustering algorithms especially Coherent Filtering (CF) clustering approach has gained high popularity in the field of coherent motions detection. CF finds motion clusters of different scale, density, and shape, in the presence of large amount of noise and outliers. The similarity measure function is utilized as the initial base step for determining the relationships among crowd individuals and thus detecting coherent motion from noisy time series data. In this paper, we evaluated the impact of four different similarity measure functions upon CF clustering approach, namely, Chebyshev, Euclidean, Canberra and Cosine, and the results were compared subsequently. Quantitative evaluation and comparison are conducted on synthetic data in two dimensional space. Results reveal that the Euclidean similarity function emerges as the best measure for capturing coherent motions from crowd clutters, while Cosine similarity function performs the worst.
Research Data Management in China: Can Librarians Bring a Paradigm Shift?

Research data management (RDM) practices in China are underdeveloped despite the release of RDM policy on 2 nd April 2018 and research to unearth these challenges cannot be overemphasized.The objective of this study is to investigate the relationship among critical stakeholders in RDM specifically from librarians' perspective to speed up the RDM agenda for maximum benefit.This study used Structural Equation Modeling (SEM) to study the relationship among critical stakeholders in RDM.The findings revealed that the relationships among different stakeholders are significantly positive, and that institutions mediate the positive effect of Librarian on researchers' work.The effect of government on librarians is not significant.This later finding may be largely due to the poor attitudes of government towards the librarians, however, there could be a positive mediating effect rather than direct.This means that the librarians could bring a paradigm shift in RDM.Librarians should take a leadership role in RDM and should be involved in decision making.This could be the way forward to change the status quo in RDM.This study contributes to the discourse by helping to strengthen the existing relationship and also to understand the role of librarians in RDM.
Efficient Collaborative Energy Trading Between Smart Grids Using Blockchain and Smart Contracts

We consider a set of interconnected smart grids, where each grid supplies electricity to customers in its area. We develop a method of efficient collaborative energy trading, where the smart grids exchange electricity to meet the demands of their customers while minimizing the overall cost. Linear programming is used to determine the electricity transfers that minimize the overall cost. Machine learning is suggested to predict customer demands. A pricing model is also proposed. We also suggest how to detect and manage faulty behaviors, using an automatic mechanism of financial penalties and indemnities. The suggested energy trading method is enforced using a smart contract executed in blockchain. This ensures that electricity transfers, payments, penalties and indemnities comply with the rules and are recorded in blockchain in a secure, immutable, transparent and decentralized manner.
Sentiment Analysis in the Era of Web 2.0: Applications, Implementation Tools and Approaches for the Novice Researcher

Nowadays, people find it easier to express opinions via social media-formally known as Web 2.0. Sentiment analysis is an essential field under natural language processing in Computer Science that deals with analyzing people's opinions on the subject matter and discovering the polarity they contain. These opinions could be processed in collective form (as a document) or segments or units as sentences or phrases. Sentiment analysis can be applied in education, research optimization, politics, business, education, health, science and so on, thus forming massive data that requires efficient tools and techniques for analysis. Furthermore, the standard tools currently used for data collection, such as online surveys, interviews, and student evaluation of teachers, limit respondents in expressing opinions to the researcher's surveys and could not generate huge data as Web 2.0 becomes bigger. Sentiment analysis techniques are classified into three (3): Machine learning algorithms, lexicon and hybrid. This study explores sentiment analysis of Web 2.0 for novice researchers to promote collaboration and suggest the best tools for sentiment data analysis and result efficiency. Studies show that machine learning approaches result in large data sets on document-level sentiment classification. In some studies, hybrid techniques that combine machine learning and lexicon-based performance are better than lexicon. Python and R programming are commonly used tools for sentiment analysis implementation, but SentimentAnalyzer and SentiWordnet are recommended for the novice.&#x0D; Keywords: Sentiment Analysis; Web 2.0; Applications; Tools; Novice