Reviewerly/exHarmony huggingface dataset:
The Effect of Storytelling Picture Book on Reading Readiness of Group B Kindergarten Children in Padang

The purpose of this study to determine the effect of storytelling picturebook activity on the group B children's reading readiness kindergarten in the city of Padang in 2018.The method used an experimental method using a pretest-posttest control group design.Data were analyzed using T test to calculate the two averages.The population of this research is all kindergarten children Group B located in the District of West Padang, Padang city.The sample in this study 18 children in group B TK Negeri II as an experimental group and 18 children in group B TK Aisyiyah 24 JondulRawang as a control group.The results of this study indicate that there are significant differences in reading readiness of children in group B were given treatment by using storytelling picture book by Wordbook, while reading readiness in children given the treatment group B using pictorial word card is not a significant difference.
OIDPR: Optimized Insulin Dosage based on Privacy-Preserving Reinforcement Learning

The precise dosage of insulin plays an important role in the treatment of diabetes. To offer accurate dosage, some AI-based auxiliary dosing systems have been proposed. Unfortunately, these schemes demand real-time health data, which is highly relevant to the health situation of the diabetics. The traditional personalized drug delivery frameworks for accurate dosing of insulin always collect and transmit medical data in plaintext, which may cause the disclosure of user privacy. Therefore, to optimize insulin dosage and protect privacy simultaneously, we propose a framework for an optimized insulin dosage via privacy-preserving reinforcement learning for diabetics (OIDPR). In OIDPR, both the additive secret sharing and edge computing are deployed to complete data encryption and improve efficiency. The user’s medical data is divided into secret shares uniformly at random, then compute separately at the edge servers. During the computation task of Q-learning, data is stored in the format of ciphertext and processed using the proposed additive secret sharing protocol. Finally, comprehensive theoretical analyses and experiment results demonstrate the security and efficiency of our framework.
A Study of Corporate CSR Effects on Corporate Crisis Management

Purpose: In modern corporate management, the establishment of a crisis management system that minimizes damage through measures used to respond to corporate crises is no longer an option. The importance of corporate reputation and brand asset management in modern enterprise management cannot be overemphasized and negative events that might arise from a number of different causes can cause brand crises. Research design, data and methodology: More than half of the questionnaire respondents were female (252 or 53%). More than a fourth of the respondents were aged 20 (122 or 26%) and the number of married participants was 196 (41%). Of the participants, 32% (153) had graduated from college. Only 18% (87) were employees and the monthly household income was 121. In this study, we conducted factor analysis in order to extract the variables that may enhance the explanation capability of each variable. For the method of factor extraction, an Eigen value of at least 1 was used as was factor loading. An analysis was performed using the Cronbach's alpha coefficient to verify the reliability of the measurement scale. Results: First, the analysis of the impact of the social responsibility activities on brand image revealed that the social, economic, philanthropic, ethical, and environmental responsibility activities significantly affected brand image, but legal responsibility activities were not statistically significant. Second, the analysis of the impact of brand image on loyalty showed that brand image had a significant impact on loyalty. Third, the analysis of the impact of social responsibility activities on loyalty showed that they had a significant impact on loyalty. Conclusions: The pro-social enterprise image is not only a brand asset that can be shared, but also a heavy proposition followed by a corresponding social responsibility, it will have to practice transparent corporate management based on clear principles through the establishment of various systems and the implementation of a strict code of conduct within the enterprise.
The Students' Writing Difficulties in Writing an Essay Based on Cognitive Process

The main problem of this research was “what are the students” writing difficulties in writing an essay at fourth semester of Grade E? and what factors do influence the students’ writing difficulties in writing an essay based on the cognitive process at fourth semester of grade E? The objective was aimed to identify the students’ writing difficulties in writing an essay at fourth semester of Grade E and to identify the factors do influence the students’ writing difficulties in writing an essay based on the cognitive process at the fourth semester of Grade E.The subject was the students at fourth semester grade E in 2016/2017 academic year which consists of twenty two students. This research used Qualitative Research method. The data is gathered from observation, document (students’ essay) and interview.The findings showed that there are two types of students writing difficulties in writing an essay, they are pre writing and pre-drafting.The result of result that there are nine students who difficult in pre writing and there are twelve students difficult in pre writing drafting.  Pre writing difficulties like difficult in getting the topic and pre-drafting difficulties like difficult in getting topic and organizing the essay.. Key words: Writing difficulties, Writing essay, cognitive process
Fashion Android Application using Augmented Reality

In spite of the fact that we are in 21st century with loads of advancement in the field of innovation and improved periods of utilizing applications inside the scope of our fingertips, the desire towards a novel and better innovation for a life of simplicity ne'er comes to stop.One such new innovation is expanded reality.This is an application where clients can shop online in the most astute manner by taking a stab at various embellishments like caps, shades, pieces of jewellery and so forth simply utilizing our versatile camera to.This application gives an easy to understand frontal picture of face with no/light cosmetics and short/bound hair.The Beauty specialist's framework won't just propose the client appropriate cosmetics and hairdo, it even shows the manufactured impacts.
Optimised analysis of community medical APP user experience under cognitive load theory

Based on community medical APP as the carrier, this paper studies the emotional and experiential process of community doctors using mobile community medical APP under different cognitive loads, and puts forward the improvement of product optimization. Firstly, based on the cognitive load theory, objective user data is obtained through cognitive load control experiments on target users. Second, ask the target user to fill in the Positive and Negative Affect Scale and System Usability Scale to obtain subjective user data. Finally, analyze the user’s subjective and objective data. Based on the analysis of experimental results and user observation, the improvement strategy is proposed to reduce the barriers to community doctors learning and using community medical apps.
KONSTRUK ASESMEN LITERASI FUNGSIONAL UNTUK SISWA SEKOLAH MENENGAH PERTAMA

Literasi fungsional menyiratkan bahwa literasi dapat digunakan untuk meningkatkan kapasitas masyarakat, meraih tujuan, dan meningkatkan kemampuan diri. Penelitian validatif ini bertujuan untuk mengidentifikasi konstruk asesmen literasi fungsional untuk siswa SMP dan mengalisis butir soalnya dengan Model Rasch. Data penelitian ini dikumpulkan melalui observasi, wawancara, FGD, dan tes. Sebanyak 5 orang guru dan 246 siswa dari 5 SMP di DIY, serta 3 pakar dilibatkan dalam proses pengumpulan data. Hasil penelitian berupa konstruk literasi fungsional dari National Assessment for Adult Literacy (NAAL) dimodifikasi dalam 15 jenis literasi, yaitu literasi prosa, digital, dokumen, numerik, lingkungan, kesehatan, pariwisata, transportasi, keselamatan jalan, kesantunan berbahasa, mitigasi bencana, finansial, budaya, visual, dan sosial. Hasil analisis 60 butir soal dengan Model Rasch berbantuan program QUEST menunjukkan probability level 0,50 dengan indeks reliabilitas 0,98. Mean INFIT MNSQ sebesar 1.00 dengan SD 0,04 yang fit dengan Model Rasch. Butir soal yang layak berada pada rentang threshold (± 2) adalah 51 buah (85%), sedangkan yang di luar rentang tersebut 9 butir (15%). Siswa dengan skor ≥75 sebesar 38,2%, sedang yang belum memenuhi standar sebanyak 61,8%. Indikator esensial dan batang soal menjadi bagian penting untuk melihat kemampuan literasi fungsional siswa. Kata kunci: literasi fungsional, asesmen, analisis butir soal, Model Rasch THE CONSTRUCTS OF FUNCTIONAL LITERACY ASSESSMENT FOR JUNIOR HIGH SCHOOL STUDENTS AbstractFunctional literacy implies that literacy can be used for improving society capacities, obtaining goals, and increasing self-capabilities. The present study is aimed at identifying the constructs of the functional literacy assessment of junior high school students and analysing the item responses by using the Rasch Model. The data were collected through observation, interview, FGD and testing. Five teachers, 246 students from five junior high schools in Yogyakarta Province, and 3 experts were involved in the research processes. Results show that the constructs of the functional literacy from the National Assessment for Adult Literacy (NAAL) concepts have been modified into 15 types of literacy: prose, digital, document, numerical, environmental, health, tourism, transportation, road safety, language civility, disaster mitigation, financial, cultural, visual, and social). The results of the item analysis (60 items) using the Rasch Model with the QUEST program produce a probability value of 0.50 with a reliability index of 0.98. The INFIT MNSQ mean of 1.00 with an SD of 0.4 fits with the Rasch model. Items are eligible for an appropriate threshold range (± 2) of 51 grains or 85% while items outside the range of ± 2 is 9 (15%). Students with a score of ≥ 75 are 94 in number (38.2%). Meanwhile, students who have not fulfilled the standard amount to 61.8%. Essential indicators and item stems have an important role in reflecting the students’ functional literacy competences. Keywords: functional literacy, assessment, item response, Rasch model
AN OPEN SAND-BOX FLOW MODEL IN THE ACTION-ADVENTURE RPG: THE AEGIS

The paper introduced an Open World, Action- Adventure, Role Playing Game called The Aegis. The game proposed in this paper is an action-adventure fantasy RPG game called The Aegis. This game is made in 3D with Open world element. This game inspired from many places such as Titanfall and from movies as well such as king Ghidorah is from Godzilla. This is a 3D RPG and is to be a big-scale game. This includes a fun gameplay and a continues story being told. In this paper, the concepts and designs used, the systems implied, the story, walkthrough, background and future enhancements will be elaborated.
On Cyclic and Negacyclic Codes of Length 8p&lt;sup&gt;s&lt;/sup&gt; Over Fp&lt;sup&gt;m&lt;/sup&gt; + uFp&lt;sup&gt;m&lt;/sup&gt;

In this paper, we establish the algebraic structure of all cyclic and negacyclic codes of length 8&lt;em&gt;p&lt;/em&gt;&lt;sup&gt;s&lt;/sup&gt; over the chain ring Fp&lt;sup&gt;m&lt;/sup&gt; + uFp&lt;sup&gt;m&lt;/sup&gt; in terms of their generator polynomials, where u&lt;sup&gt;2&lt;/sup&gt; = 0 and s is a positive integer and p is an odd prime. We also find out the number of codewords in each of these cyclic codes. Besides this, we determine duals of cyclic codes and list self-dual cyclic and negacyclic codes of length 8&lt;em&gt;p&lt;/em&gt;&lt;sup&gt;s&lt;/sup&gt; over Fp&lt;sup&gt;m&lt;/sup&gt; + uFp&lt;sup&gt;m&lt;/sup&gt;. Also, we determine μ and -constacyclic codes of length 8&lt;em&gt;p&lt;/em&gt;&lt;sup&gt;s&lt;/sup&gt; over Fp&lt;sup&gt;m&lt;/sup&gt; + uFp&lt;sup&gt;m&lt;/sup&gt;.
DENSITY-BASED SMART TRAFFIC LIGHT TIME PREDICTOR

The traffic congestion problem in urban areas increasing every day, there is an urgent need to introduce modern equipment and technologies to improve the traffic control system in almost all countries. Existing methods such as human control or timer are proving to be less efficient to improve this crisis. Some existing traffic control systems have been proposed by measuring vehicle density in real-time with modern ordinal image processing techniques. These traffic flow control systems offer noteworthy improvements in vehicle management, time of response, reliability, automation of traffic systems, and all over efficiency above the existing systems. To overcome the disadvantages of the existing system, we need an efficient system for effective traffic flow light control through image processing with machine learning. This system will recognize the images of vehicles instead of using sensors integrated into a pathway to capture the images of vehicles. These images will be analysed and processed using edge detection algorithms to detect vehicles with OpenCV, rendering to traffic circumstances, then timer setting for traffic controlling light will be managed. The experimental results revealed that our system outperforms when compared with the existing system.
African Economic Development: Evidence, Theory, Policy by Christopher Cramer, John Sender, and Arkebe Oqubay, Oxford, Oxford University Press, 2020, xiv + 319 pp.

The Developing EconomiesVolume 58, Issue 3 p. 251-254 Book Review African Economic Development: Evidence, Theory, Policy by Christopher Cramer, John Sender, and Arkebe Oqubay, Oxford, Oxford University Press, 2020, xiv + 319 pp. Ben Fine, Corresponding Author Ben Fine bf@soas.ac.uk School of Oriental and African Studies (SOAS), London, UKSearch for more papers by this author Ben Fine, Corresponding Author Ben Fine bf@soas.ac.uk School of Oriental and African Studies (SOAS), London, UKSearch for more papers by this author First published: 22 July 2020 https://doi.org/10.1111/deve.12246Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume58, Issue3September 2020Pages 251-254 RelatedInformation
Retargeting PHM tools: from industrial to medical field

Prognostics and Health Management (PHM) approach, and theoretical models have had great success for industrial systems. Therefore, this accomplishment motivates us to think about potential extension of the PHM approach in such area as the medicine. The aim of this paper is to apply an adaptation of a PHM model from fault diagnosis of aircraft engine to diagnosis human heart disease. For that adaptation, an algorithm for retargeting extreme learning machine (ID-RELM) is applied. The complete process from data pre-processing to classification is developed. Numerical results using heart disease benchmark dataset showed that the combination of random forest and ID-RELM provides the highest classification accuracy and outperforms other algorithms in classifying this chronic disease status.
Tensor-Based Light Field Compressed Sensing and Epipolar Plane Images Reconstruction via Deep Learning

Light field (LF) can capture the spatial and angular information of the light in one single exposure. And the LF images are widely used in various fields, especially in immersive media. The rich imaging information in the LF poses great challenges for transmission. However, LF images are sparse and redundant to some extent, which makes LF compression possible. Besides, the compressed sensing (CS) theory shows that images can be recovered from a small number of measurements when they are sparse. In this paper, we propose a Tensor-based Compressed Sensing method to compress images and Epipolar Plane Images for reconstruction (TCSEPI). This method divides the viewpoints of LF images into several regions and stacks the images in each region into a 4D tensor, which conduct CS together and yields measurements with common characteristics. Subsequently, the epipolar plane images are used to reconstruct the LF images and restore the geometric consistency information. To achieve better reconstruction results, we design two cascaded convolutional neural networks to implement the measurement matrix optimization and LF images reconstruction sequentially. Experimental results show the superior performance of TCSEPI, which achieves at least 3dB gain in PSNR and outperforms state-of-the-art in the reconstruction quality.
Fitting User Research into Your Organization

More and more organizations require user researchers now. There is currently a high demand in the United Kingdom, in the United States, and in other parts of the globe. You can do a search for “user research” on Google or another search engine, and you will see some interesting results. Online recruitment agencies such as Reeds, Indeed, and even the Jobs section on LinkedIn have many offers.
Automated Analysis of Comments on Press Articles in Websites (Articles Literature as Case Study)

Due to the increasing electronic publishing sites for printed and certified newspapers, the reader faced the problem of reaching his goal by accessing these sites, which led to the neglect of a large section of important publications. The provision of an automated measure to verify the positive and negative articles based on the analysis of readers' comments on the articles is a necessity to see the important articles that are compatible with the corpus generated by us for inference. The project achieved the previous target and achieved a success rate. The Bag-of-Words Model (BoW) was used to obtain the repetition of the block of words to build the corpus. The proposed system is evaluated based on four metrics (Accuracy= 93%, Precision= 94%, Recall= 94% and F-measure= 94%). The effectiveness results obtain by this system was (Accuracy, Precision and Recall and F-measure).
Pemetaan Tingkat Rawan Bencana Banjir di Daerah Aliran Sungai Maros Provinsi Sulawesi Selatan

Indonesia is an archipelago with a tropical climate with very high rainfall. In the rainy season floods occur which cause losses, namely loss of life and property. This condition is a routine disaster that always threatens people's lives. Therefore, research needs to be done to identify flood-prone areas and flood-causing factors in the Maros River Basin. The method used to determine flood-prone areas is used by a combination of remote sensing, terrestrial, secondary data and interviews using the criteria of Sutikno et al (1995) with development. The variables used topography (flat and sloping), soil texture, drainage, inundation time and flood return period. The analysis shows that in the Maros watershed there are 3 classes that are prone to flooding namely not prone, prone and very prone. Most are vulnerable because more than 50 percent of the area is at a vulnerable and very vulnerable level. The class is very prone to spread from downstream to the middle of the watershed, covering the southern sub-districts of Maros Baru, Marusu, Turikale, southern Bantimurung, western Simbang, northern Mandai and northern Tanralili. The contributing factors are high rainfall, flat and sloping topography, fine soil texture in the downstream river, poor drainage due to poor waste management, land use dominated by ponds and paddy fields and high flood return periods.
Linear codes from vectorial Boolean power functions

In this paper, three classes of binary linear codes with few weights are proposed from vectorial Boolean power functions, and their weight distributions are completely determined by solving certain equations over finite fields. In particular, a class of simplex codes and a class of first-order Reed-Muller codes can be obtained from our construction by taking the identity map, whose dual codes are Hamming codes and extended Hamming codes, respectively.
PENGARUH POLA ASUH OTORITER TERHADAP KECENDERUNGAN CYBERBULLYING YANG DIMEDIASI OLEH KECERDASAN EMOSIONAL (EMOTIONAL INTELLIGENCE) PADA REMAJA DI KOTA BANDUNG.

This study aims to determine the effect of authoritarian foster pattern on cyberbullying tendencies mediated by emotional intelligence in teenagers in the city of Bandung. This research used a quantitive approach with regression analysis methods with variable mediation method. The sample in this study were 341 teenagers lived in Bandung. The sampling technique in this study used non-probability sampling. The authoritarian foster pattern is measured using instruments according to Riberio (2009) which is the result of the adaptation of Cahyanuari (2018), emotional intelligence is measured using instruments according to Goleman (2016) which is the result of the adaptation of Jonta (2018), and cyberbullying is measured using instruments from Willard (2017) which is a result adaptation of Agustin. The data analysis technique used in this study was a simple regression analysis to determine the influence of authoritarian foster patterns against cyberbullying tendencies mediated by emotional intelligence. The results of this study show that emotional intelligence cannot be mediated on an authoritarian foster pattern against cyberbullying tendencies.
Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework

Human-like chit-chat conversation requires agents to generate responses that are fluent, engaging and consistent.We propose Sketch-Fill-A-R, a framework that uses a personamemory to generate chit-chat responses in three phases.First, it generates dynamic sketch responses with open slots.Second, it generates candidate responses by filling slots with parts of its stored persona traits.Lastly, it ranks and selects the final response via a language model score.Sketch-Fill-A-R outperforms a state-of-the-art baseline both quantitatively (10-point lower perplexity) and qualitatively (preferred by 55% in head-to-head single-turn studies and 20% higher in consistency in multi-turn user studies) on the Persona-Chat dataset.Finally, we extensively analyze Sketch-Fill-A-R's responses and human feedback, and show it is more consistent and engaging by using more relevant responses and questions.
Exploratory Data Analysis dalam Konteks Klasifikasi Data Mining

Each type of data has various forms and behaviors. Therefore, the process of data analysis cannot be standardized through a certain procedure. EDA is a data analysis approach that can be used in interpreting the information contained in data. EDA is flexible in adjusting data behavior and can be used for data observation through various points of view. This data analysis strategy can be used to complement the results of data mining classification analysis used to recognize data patterns. In this article it will be explained that EDA can help in enriching the results of data analysis and assist in the pre-processing stages of data mining classification. Data mining classification is done using the Naive Bayes Classifier algorithm and Logistic Regression.