Reviewerly/exHarmony huggingface dataset:
PEMBUATAN APLIKASI MULTIMEDIA INTERAKTIF PEMBELAJARAN BAHASA JEPANG LEVEL DASAR

In this increasingly advanced era, mastering a foreign language can provide many advantages, one of them is Japanese language. By looking at these advantages, such as expanding opportunities in the working world, getting scholarships and knowing the culture of the country concerned, then the Japanese language course appears. However Japanese characters which consists of three characters make students difficult to memorize because these characters are too many. In addition, a boring learning method that used by teacher can make students lazy to learn. Therefore, an application that can help the community to understand the Japanese language with role playing learning method is created. In this application, the lesson divided into six stages and delivered briefly. Overall, the user will interact a lot with a female character. This character will guide the user from beginning to the end to tell the user some basic sentence patterns and Japanese characters of hiragana and katakana. Evaluation in this application is given by answering some questions and accompanied by match and pair letter and picture cards mini games. From the test results, it can be concluded that this multimedia application can help beginners to learn Japanese with an interesting appearance and help users in memorizing Japanese characters and without spending any cost.
A No-Reference Blur Metric based on Second-Order Gradients of Image

Estimation of blurriness value in image is an important issue in image processing applications such as image deblurring. In this paper, a no-reference blur metric with low computational cost is proposed, which is based on the difference between the second order gradients of a sharp image and the one associated with its blurred version. The experiments, in this paper, performed on four databases, including CSIQ, TID2008, IVC, and LIVE. The experimental results indicate the capability of the proposed blur metric in measuring image blurriness, also the low computational cost, comparing with other existing approaches.
Low Cost Gunshot Detection using Deep Learning on the Raspberry Pi

Many cities using gunshot detection technology depend on expensive systems that ultimately rely on humans differentiating between gunshots and non-gunshots, such as ShotSpotter. Thus, a scalable gunshot detection system that is low in cost and high in accuracy would be advantageous for a variety of cities across the globe, in that it would favorably promote the delegation of tasks typically worked by humans to machines. A repository of audio data was created from sound clips collected from online audio databases as well as from clips recorded using a USB microphone in residential areas and at a gun range. One-dimensional as well as two-dimensional convolutional neural networks were then trained on this sound data, and spectrograms created from this sound data, to recognize gunshots. These models were deployed to a Raspberry Pi 3 Model B+ with a short message service modem and a USB microphone attached, using a software pipeline to continuously analyze discrete two-second chunks of audio and alert a set of phone numbers if a gunshot is detected in that chunk. Testing found that a majority-rules ensemble of our one-dimensional and two-dimensional models fared best, with an accuracy above 99% on validation data as well as when distinguishing gunshots from fireworks. Besides increasing the safety standards for a city’s residents, the findings generated by this research project expand the current state of knowledge regarding sound-based applications of convolutional neural networks.
Improving Search Relevance Feedback through Human Centered Design

Artificial intelligence (AI) is expected to play a transformational role in health and wellbeing. Search (i.e. information retrieval) technologies already play a significant role in healthcare research and practice. Relevance feedback in Search is vital for system evaluation and improvements. However, in small user scale contexts, the exploitation of user behaviors may not infer valid relevance judgments. Therefore, engaging users to provide such feedback explicitly is essential for improving search performance (i.e. effectiveness). However, previous research has found that users are generally reluctant to provide explicit feedback in digital environments, and the willingness decreases overtime in some experiments. In collaboration with myTomorrows, an Amsterdam-based pharma-tech company, this Master thesis aims to find answers to the challenge mentioned above through a specific context of myTomororws AI-powered treatment Search which has the urgent need for engaging healthcare professionals (HCPs) in providing relevance feedback on search results (e.g. Clinical Trials and Expanded Access Programs) for system evaluation and improvements. Through Human Centered Design methods such as interviews, observations, and speed dates, the project yielded a future myTomorrows Search design enhanced with three relevance feedback collection concepts. As research materials, the concepts were tested and evaluated by nine HCPs from three countries (the Netherlands, China, and Brazil). The user study results indicate that embedding utility, as the motivator, in relevance feedback collection appeals to HCPs more than using motivators such as altruism or enjoyment. Moreover, the best point of user engagement is identified as the moment between users finishing the examination of information and starting the next ones. Additionally, this study generalized the project process and user study insights into a four-stage guide for designing explicit feedback collection in text-base Search. Although it remains unvalidated, this guide has the potential to apply to other small user scale contexts, guiding or inspiring user researchers and designers to design explicit user feedback collection in Search.
When Does Unsupervised Machine Translation Work

Despite the reported success of unsupervised machine translation (MT), the field has yet to examine the conditions under which the methods succeed and fail. We conduct an extensive empirical evaluation using dissimilar language pairs, dissimilar domains, and diverse datasets. We find that performance rapidly deteriorates when source and target corpora are from different domains, and that stochasticity during embedding training can dramatically affect downstream results. We additionally find that unsupervised MT performance declines when source and target languages use different scripts, and observe very poor performance on authentic low-resource language pairs. We advocate for extensive empirical evaluation of unsupervised MT systems to highlight failure points and encourage continued research on the most promising paradigms. We release our preprocessed dataset to encourage evaluations that stress-test systems under multiple data conditions.
Simplifying Random Forests using Diversity

In this paper, we propose a diversity measure for random forests simplification using both SFS andSBE paths. This is performed in two stages: 1) we use first an overproduce method which generates a largenumber of trees; 2) We use SFS and SBE paths combined with diversity measurement to reduce the initialensemble of trees. The proposed method is applied to UCI Repository data sets. A comparative study of the twotypes of paths with a performance-based pruning method is given. The results are encouraging and allowobtaining ensembles of reduced sizes exceeding, in some cases, the performances of the initial forest and themethod used for comparison.
A VISUAL SERVOING APPROACH FOR ROBOTIC FRUIT HARVESTING IN THE PRESENCE OF PARAMETRIC UNCERTAINTIES

In this paper, we address the robust visual servoing problem for a fixed target using an eyein-hand camera configuration, when the camera calibration parameters are uncertain. The proposed solutioncombines the image-based visual servoing (IBVS) and the position-based visual servoing (PBVS) approaches totake advantage of both strengths to perform successful robotic fruit harvesting tasks. An image-based detection and recognition method, based on SURF and RANSAC algorithms, is used to extract the image feature of  the fruit for the vision-based control algorithm. A kinematic control design, with robustness properties, is employed to cope with the uncertainties in the calibration parameters of the camera-robot system. To deal with possible singular configurations of the robot arm, that may arise during the task execution, we employ the Damped Least-Squares (DLS) inverse method. Experimental results, obtained with a Mitsubishi robot arm RV-2AJ carrying out strawberry harvesting tasks, are included to illustrate the performance and feasibility of the proposed methodology.
UAV Path Planning Optimization based on GNSS Quality and Mission Requirements

One of the most crucial factors for the overall success of an Unmanned Aerial Vehicle (UAV) mission is navigation performance, which is severely affected in Global Navigation Satellite Systems (GNSS) challenging environments. A solution to this problem could come through path planning optimization. This paper investigates the impact that GNSS quality information included in the UAV path planning process would have on the overall UAV mission success rate (MSR) when flying through an urban canyon. Number of visible satellites and Horizontal Dilution of Precision (HDOP) in addition to mission-specific requirements are given as input to the Particle Swarm Optimization (PSO) algorithm to calculate the optimal path for two cases. One includes the GNSS observables, and the other does not. Optimal paths for three different altitudes are obtained. All paths are simulated by a GNSS signal simulator, including a comprehensive multipath model. GNSS data are collected by a hardware receiver for analysis of the UAV positioning error and GNSS availability. Mission failures cases are defined accordingly, and the overall mission success rate (MSR) of each scenario is assessed. By analyzing the findings, it is concluded that in 83% of cases, the path planning process that included GNSS information was able to increase the MSR. Also, the increase in MSR was bigger when flying at low altitude.
Estimation of the contamination levels of heavy metals in selected soil samples from Irri, Delta State-Nigeria

Soil samples obtained from different locations in Idheze-Irri was analyzed for the presence of heavy metals; lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu) and Cadmium (Cd). The estimated mean concentrations of the studied metals were below the global world average respectively while Cd was undetected in the samples. Pollution (contamination) Index (PI) values obtained for Pb, Ni, Cu and Cd are within the category of PI ≤ 1. Enrichment Factor (EF) values indicate that the samples are moderately enriched with Pb and Cu, minimally enriched with Ni and extremely enriched with Cd. Geo-accumulation Index (Igeo) shows that the samples are unpolluted with Pb, Ni, Cu, Cd and Cr. Ecological Risk Index (ERI) values are within the category of ERI ≤ 50 which implies that their quantity in the soil is minimal and hence poses low risk to the environment. All the results and analysis show that the samples are unpolluted with heavy metals (Pb, Ni, Cu, Cd and Cr) and thus the study area is considered safe for habitation and other human activities.Keywords: Heavy metals, Concentration, Oil spillage, Pollution, Soil samples.
DIGITAL TECHNOLOGIES IN THE DAILY LIFE OF THE ALFA GENERATION

This article presents the results of two surveys among parents of primary school age children. Thes urveys are a part of undamental research, funded by the Bulgarian Science Fund – Digital Competencies and Media Education at Pre-school and Primary School Age (DN 05/8 14.12.2016) with coordinator Prof. Dr Rumyana Papancheva from the University „Prof. Dr Asen Zlatarov”, Bourgas. The author is the leader of the Working Group „Research of the connection between Reading and Digital literacy“as a part of the project. The accent in this article is on the results of parents’ surveys and a comparison between 2018 and new one – 2020 – there are analyzed parents’ attitudes towards a formation of digital literacy of their children.
African smart cities in 2030

Rejecting Western smart cities, which he feels are too top-down and remote from people’s real needs, Sename Koffi Agbodjinou is a champion of the neo-vernacular African city. This alternative vision of the smart city, inspired by traditional societies and the organic ways they work through peer-to-peer exchanges at the village level, proposes a city that is horizontal and distributed. A city designed for and by residents at the local level making free use of new technologies as they see fit. A real-life application of this urban utopia can be found in Lome where the HubCite project applies the principles of the neo-vernacular African city at the neighborhood level. HubCite exists to help people participate in how their city is designed and operated thanks to a network of technology innovation spaces, WoeLabs, that are dedicated to ultra-local urban projects. Each space serves a given area and supplies, on site, the resources that city-dwellers need to develop solutions that respond to their real needs, including waste collection, energy and 3D printing.
Support management of professional and educational trajectory of students under the conditions of social and cultural educational environment of the university

Recent dramatic transformations have led to the necessity of change Russian educational system, to reinterpretation of the idea of education in our country. It is necessary to pay more and more attention to the preparation of the university students for work in the rapidly changing conditions of social and professional activity. The transformations carried out in the political and socio-economic life of the society, affirm a new look at the personality of a graduate, require professionally trained, self-thinking people, which, in its turn, led to the transition to the new personality-oriented educational standards of the third generation. Federal state educational standards of higher professional education (hereinafter referred to as the FSES of HPE), which meet the need of the modern transition to personality-oriented educational standards, open up new opportunities for students and teachers, which take into account the individual characteristics and personal qualities of students, and ascertain the possibilities for preparing students as subjects of their own vocational education.
Optimasi Self-Organizing Map Menggunakan Particle Swarm Optimization untuk Mengelompokkan Desa/Kelurahan Tertinggal di Kabupaten Kutai Kartanegara Provinsi Kalimantan Timur

Self-Organizing Maps (SOM) is an efficient cluster analysis in handling high dimensional and large dataset. Particle Swarm Optimization (PSO) is an effective in nonlinear optimization problems and easy to implement. A clustering process occurs if all data can clustered into 1 cluster, however if one or two data did not join then the data have a deviant behavior called outliers or noise.  PSO is used to evolve the weights for SOM to improve the clustering result and to cluster some social aspect in society, for example is poverty. Development strategies are prioritized to regions with largest population lived in poverty. Kutai Kartanegara regency  (Kukar) are recorded as the biggest contributor on population lived in poverty at East Kalimantan in 2017. Development of underdeveloped villages is requires Village Potential data, which focus on visualizing the situation in the regions. This study aims to determine the number of clusters formed and to find the value of Davies Bouldin Index (DBI) from clustering underdeveloped villages in Kukar region using PODES 2018 data. This study uses 9 particle which are the final weight of the SOMs algorithm with different learning rate each particle. Based on the analysis, the optimal number of clusters is 2 clusters with DBI value of 0.7803, where cluster 1 consists of 82 underdeveloped villages and the cluster 2 consist of underdeveloped villages.
Repercusión académica de la COVID-19 en universitarios peruanos

Introduction: As a result of the coronavirus pandemic, many students are worried that they may lose their academic term. Objective: Validate a scale to measure the perception of possible academic impacts among Peruvian university students. Method: A validation process was conducted of a test measuring the perception of university students about possible academic impacts. The validation was based on a scientific bibliography search, development of a preliminary overview, validation of the test by 59 experts: epidemiologists, researchers and physicians, exploratory factor analysis, and statistical analysis. Results: In terms of relevance, item 7 was found to be more essential or important than the others (V = 1.00; CI 95 %: 0.73-0.96). Item 8 (M = 3.80; σ = 1.152) exhibits the highest mean, and item 6 the lowest (M = 3.03; SD = 1.342). AFE relevance is justified by the KMO index (0.85) and Bartlett's test (12577.0; gl = 28; p = < 0.001), both of which were found to be acceptable and significant. A Cronbach's α coefficient of 0.899 was obtained, with a confidence interval of 95%, SD 0.882-0.898, indicating a good consistency level. Conclusions: A single factor scale was validated which measures the perception of university students about the possible impacts of the coronavirus pandemic on their studies. It is necessary to evaluate each reality, and the tool may serve as a base scale for that purpose.
TÜRKİYE’DE MAYIS 2020 GÖZLENEN SICAK HAVA DALGASININ KLİMATOLOJİK VE SİNOPTİK DEĞERLENDİRMESİ

This paper examines the climatological and synoptic characteristics of the heatwave that affected Turkey in May 2020. For this purpose, the surface daily maximum temperatures (Tmax) and the heatwaves temporal change recorded in May in the 104-meteorological and climatological stations in Turkey and the heatwave and the upper atmospheric synoptic climatological/meteorological conditions for May 2020 are examined. Results show that May's highest temperature has shown an increasing trend from 1950 to 2000 and more evidently since the 1980s, especially in Eastern- and Southeastern Anatolia. The highest maximum air temperatures in May over the last 71 years were recorded in 2020, 2019, and 1990. Trend analysis shows that an increasing trend at 95 stations characterizes the number of heatwaves and this trend is statistically significant at 22 stations over Turkey from 1950 to 2018. The highest numbers of heatwaves experienced in May during the 1950-2018 period belong to 2019, 1994, and 2020. The frequency of heatwaves observed in May has also shown an increasing trend since the early 1990s, and this trend is statistically significant at 27 stations. The average duration of the heatwave days in May was 3 days before 1990; this figure also increased significantly to an average of 5.4 days after 2015. In the entire 71-year period, 2020 May was marked by record-breaking maximum temperatures in 32 stations over Turkey. From 15 to 21 May, daily maximum temperature values exceeded 40 °C at 11 stations. The study utilizes ground and upper-level synoptic charts, radiosonde observations, and prognostic maps in the synoptic analysis of the ground level and upper atmosphere. Continental tropical air mass (cT), which moved from over-North Africa under the effect of Azores high-pressure center, has expanded along the Eastern Mediterranean basin since 15 May 2020. The high-level, high-pressure centers and the stable conditions of the “ridge” region (atmospheric blockage) shown in 500 hPa charts have become more effective in most parts of Turkey and caused the breaking of maximum temperature records, especially in the Aegean and Mediterranean regions. When we consider the observed changes in daily maximum temperatures and the characteristics of the heatwaves accelerated during the last decades, we see an increasing likelihood of more frequent and longer heatwaves in Turkey in future decades.
Smart City As An Implementation of E-Government in Indonesia

This research is aimed at obtaining findings about public service through smart governance and smart mobility in Bandung city. Bandung city as one of the pilot-project cities in this program in Indonesia has initiated a number of efforts toward the concept of smart city. The main concept of smart city is sensing, understanding, and acting processes based on the use of information technology in the government (e-government). Besides, it was about to seek the city problems in real time, and then respond properly, so that those problems are immediately followed up. One of the efforts to realize smart governance and smart mobility is through the establishment of command room. This research employed qualitative approach. The informants were staffs of information commission officials in Bandung and Bandung citizensas the sample. The data collecting techniques were an in-depth interview, observation, and document analysis. The findings of this research indicated that the public service in Bandung city is experiencing improvement quantitatively and qualitatively after the implementation of smart governance and smart mobility in the smart city framework. All efforts in improving the public service are controlled in Bandung Command Center based on the ICT use. Recently, there have been about 150 applications of smart city system in Bandung that have been implemented through online mode. It covers the affairs on organizing ID card, checking the service license or permission, and monitoring the traffic jam and flood in which those can be done quickly and in real time. It is because of the direct relationship to Bandung Command Center. While, one of the constraints in implementing smart governance in Bandung city was there still lacks of adequate internet connection capacity in the implementation of online report system for the district heads. Regarding smart mobility, one of the constraints was the lack of availability on CCTV and security tools. Besides, the respondents complained on the lack of socialization about the implementation of online report system that has been implemented in Bandung government. The possible suggestions for the Bandung government are the concern to the needs of more mature planning toward the programs of smart governance and smart mobility, preparing the human resources, and providing supporting infrastructures.
Enhancing the Readership of Teacher Students With Digital Book Subscription Services

This article aims to illustrate a 7-month trial of digital book subscription services in teacher education. Student teachers of the University of Turku in Finland were encouraged to implement the service as part of their free time reading. The experiences of the digital subscription service were investigated using a questionnaire, and data were analyzed through a combination of qualitative analysis and quantitative analysis. The aim of the study was to consider the value of digital book subscription services in terms of reading for pleasure and to describe the readership of teacher students as well as their assessment of digital book subscription services as a pedagogical approach for supporting the reading of primary school students. The results indicated that digital book subscription services might enhance the readership of occasional readers and that audiobook services should be implemented more frequently in education since they seem to connect reading to other free time activities. More effort should be placed in supporting the readership of teacher students in teacher education. Currently, the attitude and amount of reading rely primarily on childhood experiences.