Reviewerly/exHarmony huggingface dataset:
Ambient Assisted Living – A Bibliometric Analysis

Introduction: Ambient Assisted Living technologies provide assistance and support to people with some disabilities, such as the elderly and in cases of dementia. They offer greater control and reduction of predicted economic costs as life expectancy and the incidence of dementias tend to increase. The AAL is a growing area of research and there is a need to assess the existent publications, research trends, and characteristics in this field, providing an overview of the development of AAL systems-related research. Therefore, the aim of this study is to analyze and understand the research trends and characteristics in the AAL field by means of a bibliometric analysis. Methods: We performed a document search in Scopus with a query designed to reflect the AAL field of study, from inception up to the end of 2018. Subsequently we made several analyses to discover publication trends and patterns in this research area. Results: There are a total of 14645 authors in the AAL field, which corresponds to a mean of 1.84 authors per document. The most productive country was Spain with 895 documents, followed by United Kingdom and Germany with 723 and 718 respectively. Conclusion: This paper provides an overall picture of the state of the research regarding the field of ambient assisted living, identifies the most active authors and highlight relations between areas of research. It shades light on possible collaborations with research groups and across countries.
ANALISIS PENERIMAAN PENGGUNA APLIKASI SIAKAD DESKTOP UNIVERSITAS BRAWIJAYA MENGGUNAKAN UTAUT

Education services from tertiary institutions have applied a lot of the Academic Information System (SIAKAD). In the research on heuristic evaluation in the Academic Information System of Brawijaya University, there were several problems related to users, including problems in the ease of users to interact or use applications, SIAKAD Desktop which did not provide information to the user about the condition of a process within a certain time period or time. On the other hand, universities must guarantee the best service. Therefore, it is necessary to evaluate the acceptance of SIAKAD Desktop users to find out what factors can affect the use of Desktop SIAKAD. UTAUT as a theoretical model will be used to explore the acceptance and use of the technological environment, especially for SIAKAD users in the academic section of the Faculty of Computer Science, Universitas Brawijaya. The data that has been collected will then be analyzed using the Partial Least Square Sequence Equation Modeling (PLS SEM) method. The results of the analysis show that only the conditions of the facilities significantly influence the behavior of using SIAKAD Desktop. The UTAUT model can only explain 44.8% of the factor variants using SIAKAD Desktop which is included in the moderate category. Therefore, it is necessary to develop a research model construct construct so that the prediction of the variance accuracy of the research model increases. In addition, it is expected that further research can cover a wider population target so that data is more reliable.
Dimitri Komatitsch (1970–2019)

Dimitri Komatitsch had a profound impact on computational seismology and embodied the notion of open-source, collaborative research.
Image Recovery with Data Missing in the Presence of Salt-and-Pepper Noise

In this paper, an image recovery problem under the case of salt-and-pepper noise and data missing that degrade image quality is addressed if they are not effectively handled, where the salt-and-pepper noise as the impulsive noise is remodeled as a sparse signal due to its impulsiveness and the data missing pattern, denoted by a sparse vector, contains only zeros and ones to formulate the data missing. In particular, the salt-and-pepper noise and data missing are reformatted by their sparsity, respectively. The wavelet and framelet domains are explored to sparsely represent the image in order to accurately reconstruct the clean image. From the reformulations conducted and to recover the image, under one optimization framework, a joint estimation is developed to perform the image recovery, the salt-and-pepper noise suppression, and the missing patter estimation. To solve the optimization problem, two efficient solvers are developed to obtain the joint estimation solution, and they are based on the alternating direction method of multipliers (ADMM) and accelerated proximal gradient (APG). Finally, numerical studies verify that the joint estimation algorithm outperforms the state-of-the-art approaches in terms of both objective and subjective evaluation standards.
Features Of Professional Self-Determination Of Modern Schoolchildren In The Kabardino-Balkarian Republic

The article investigates the features of professional self-determination of graduates of secondary schools in the Kabardino-Balkarian Republic (KBR), Russian Federation. The relevance of the study is due primarily to the need for students of early professional choice in the current situation, when psychological readiness to make a conscious and responsible choice is still insufficient. The requirements of the federal state educational standards (FSES) of secondary education of the Russian Federation provide for requirements for personal learning outcomes, the characteristics of the graduate school - he must be prepared to make a conscious choice of profession, to understand the value of professional activities for the individual and society. The results of an empirical study of the influence of self-esteem of professional inclinations and abilities on the choice of a future profession by graduates of general education schools of the KBR are given. There are four types of professional choice: taking into account abilities and aptitudes; taking into account only the abilities; taking into account only inclinations; excluding the abilities and aptitudes. The differences between girls and boys are revealed. Comparing the results of the urban and rural students showed a higher percentage of rural students who choose a profession without regard to aptitudes and abilities (150).The recommendations on the organization of vocational guidance work with adolescents and high school students, aimed at the formation of psychological readiness are presented. The use of methods aimed at the formation of professional identity in the process of teaching students will help to activate.
Compact Dominant Synergistic Excitation Pattern Learning for Illumination-Insensitive Image Representation With Boosting

Illumination-insensitive image representation is a great challenge in the computer vision field. Illumination variations considerably obstruct the effectiveness of image feature extraction. In this paper, we present a novel and generalized learning framework for illumination-insensitive image representation, which can learn the discriminative features through maximizing the inter-difference and minimizing intra-difference of the images with boosting. Particularly, we enhance the discriminative capacity of illumination-insensitive image representation in three aspects. First, we learn a subset of different synergistic Weber excitation patterns (SWEP) to generate the dominant SWEP (DSWEP) and DSWEP codebook for exploring optimal illumination-insensitive patterns. Second, a compact DSWEP (C-DSWEP) is learned with a boosted set of weight to generate C-DSWEP codebook. Discriminative learning is aimed at robustness and compactness. Third, the discriminative histogram learning model is established for encoding CDSEP to further improve the discriminative ability and reduce redundancy. The extensive experiments on CMUPIE, FERET, Yale B, Yale B ext., LFW, and PhoTex databases have highlighted the superiority and the robustness of our method compared with some other state-of-the-art methods.
Automating Data Science (Dagstuhl Seminar 18401).

Data science is concerned with the extraction of knowledge and insight, and ultimately societal or economic value, from data. It complements traditional statistics in that its object is data as it presents itself in the wild (often complex and heterogeneous, noisy, loosely structured, biased, etc.), rather than well-structured data sampled in carefully designed studies. It also has a strong computer science focus, and is related to popular areas such as big data, machine learning, data mining and knowledge discovery. Data science is becoming increasingly important with the abundance of big data, while the number of skilled data scientists is lagging. This has raised the question as to whether it is possible to automate data science in several contexts. First, from an artificial intelligence perspective, it is interesting to investigate whether (data) science (or portions of it) can be automated, as it is an activity currently requiring high levels of human expertise. Second, the field of machine learning has a long-standing interest in applying machine learning at the meta-level, in order to obtain better machine learning algorithms, yielding recent successes in automated parameter tuning, algorithm configuration and algorithm selection. Third, there is an interest in automating not only the model building process itself (cf. the Automated Statistician) but also in automating the preprocessing steps (data wrangling). This Dagstuhl seminar brought together researchers from all areas concerned with data science in order to study whether, to what extent, and how data science can be automated.
PERBANDINGAN ALGORITMA CART DAN K-NEAREST NEIGHBOR UNTUK PREDIKSI LUAS LAHAN PANEN TANAMAN PADI DI KABUPATEN KARAWANG

Karawang regency is known as one of the nation rice granaries because the are many areas of rice fields, especially rice. But the transfer of function from agricultural land into industrial or recidential area can change the geographical structure of Karawang regency previously filled with agricultural land into industrial and property areas. Data mining is a technique of extracting an information from large data. One of them regression techniques. In predicting something a dataset of a numeric data type usually uses a regression technique. In this study used regression techniques to predict the area of harvested land in Karawang regency by using tools WEKA 3.8.2. The resulting comparison is seen from correlation coefficient, mean absolute error, and root mean squared error. In comparison algorithm used the same scenario is cross validation 10 folds. The result of the experiment using the same scenario shows that both algorithm can be used to predict the area of harvest area in Karawang regency. The result of evalution with same scenario shows that CART algorithm has better performance than KNN algorithm with correlation coefficient 0,9646, MAE 498,6229, and RMSE 834,0204
AN ANALYSIS OF STUDENTS WRITING SKILL IN PARAGRAPH WRITING

Paragraph writing can be very simple and complicated in the same time, because writing takes time and needs skills. Dealing with that statement a descriptive research is conducted in Muhammadiyah University of Tangerang. The objective of this research is to analyze students’ skill in their paragraph writing. After analyzing the data quantitatively and qualitatively, it is found that the students’ skill in their paragraph writing is 15,13Key words: Writing, Paragraph writing
Automated Testing of Motion-based Events in Mobile Applications

Automated test case generation is one of the main challenges in testing mobile applications. This challenge becomes more complicated when the application being tested supports motion-based events. In this paper, we propose a novel, hidden Markov model (HMM)-based approach to automatically generate movement-based gestures in mobile applications. A HMM classifier is used to generate movements, which mimic a user's behaviour in interacting with the application's User Interface (UI).We evaluate the proposed technique on three different case studies; the evaluation indicates that the technique not only generates realistic test cases, but also achieves better code coverage when compared to randomly generated test cases
Translation domain segmentation model based on improved cosine similarity for crowd motion segmentation

With the continuous growth of the global population, large-scale public gatherings have become more common, and crowd management at these gatherings has become an urgent problem for public safety management. Crowd motion analysis and early warning based on crowd motion segmentation in video surveillance systems has become an important research topic in computer vision. A translation domain segmentation (TDS) model based on improved cosine similarity (ICS) is proposed to segment moving crowds with different crowding levels and complex motion modes. The method reconstructs the objective function of the basic TDS model by ICS to simultaneously measure the difference between both magnitude and direction of two vectors; thus, undersegmentation due to the magnitude difference can be avoided. By switching between “localization” and “globalization” modes of the objective function, the algorithm can be applied to segment crowds with different densities and motion states. Moreover, by simultaneously introducing local motion magnitude and local frame difference magnitude thresholds, nonforeground regions can be excluded from the initial regions during region evolution. Experimental results show that the proposed method achieves superior performance and higher accuracy compared to existing flow field-based methods when applied to complex scenes containing moving crowds.
PENGOLAHAN CITRA DIGITAL PERBANDINGAN METODE HISTOGRAM EQUALIZATION DAN SPESIFICATION PADA CITRA ABU-ABU

A digital image processing software has been successfully constructed. The software can increase image contrast using the histogram equalization method. The results given by the equalizaton histogram method can improve image quality, so that the information in the image is more clearly seen. But not all digital images have a visual display that satisfies the human eye. Dissatisfaction can arise due to noise, the lighting quality in digital images that are too dark or too bright. So that a method is needed to improve the quality of the digital image. To improve image quality in terms of color contrast, we can give treatment to the histogram. The treatment referred to in this article is an equalization histogram on grayscale images. Image histogram is said to be good if it is able to involve all possible levels or levels at the gray level. Of course the goal is to be able to display details on the image so that it is easy to observe. The process of segmenting and repairing digital images is done using MATLAB.
Co-Saliency Detection via Local Prediction and Global Refinement

This paper presents a novel model in the field of image co-saliency detection. Previous works simply design low level handcrafted features or extract deep features based on image patches for co-saliency calculation, which neglect the entire object perception properties. Besides, they also neglect the problem of visual similar region's mismatching when designing co-saliency calculation model. To solve these problems, we propose a novel strategy by considering both local prediction and global refinement (LPGR). In the local prediction stage, we train a deep convolutional saliency detection network in an end-to-end manner which only use the fully convolutional layers for saliency map prediction to capture the entire object perception properties and reduce feature redundancy. In the global refinement stage, we construct a unified co-saliency refinement model by integrating global appearance similarity into a co-saliency diffusion function, realizing the propagation and optimization of local saliency values in the context of entire image group. To overcome the adverse effects of visual similar regions' mismatching, we innovatively incorporates the inter-images saliency spread constraint (ISC) term into our co-saliency calculation function. Experimental results on public datasets demonstrate consistent performance gains of the proposed model over the state-of-the-art methods.
Keefektifan Penggunaan Media Gambar Berseri dalam Keterampilan Menulis Kalimat Sederhana Bahasa Jerman Siswa

The purpose of this study was to obtain data related the effectiveness of serial image media in increasing students' simple German sentence writing skills. The design of this study is true Experimental Design (Pretest-Postest Control Group Design). Samples are selected randomly. Data were analyzed using t-test. The results of the analysis show that t-count 5.52 &gt; t table 2.005 at a significant level of 0.05. The results showed that serial image media were effective in increasing students' simple German sentence writing skills.
Corpus for Angry Birds Level Generation

Levels testify as an important game element for Procedural Content Generation. Recently, machine learning techniques have been used for the automatic content generation of games. However, there is a need for a corpus for training purposes. Considering this, we provide a corpus for the famous angry birds game. Our corpus contains 200 levels in total, with 100 levels from the original Angry Birds game and 100 from the Baseline level generator. These levels are encoded using a tile-based approach and are freely available for applying machine learning techniques. Further to this, our next step would be to mimic the style of these levels in the forthcoming angry birds level generation competition.
National Society for Histotechnology and Digital Pathology Association Online Self-Paced Digital Pathology Certificate of Completion Program

The field of digital pathology has rapidly expanded within the last few years with increasing adoption and growth in popularity. As digital pathology matures, it is apparent that we need well-trained individuals to manage our whole-slide imaging systems. This editorial introduces the joint National Society for Histotechnology and Digital Pathology Association online self-paced digital pathology certificate program which was launched in May 2018 that was established to meet this demand. An overview of how this program was developed, the content of the educational modules, and the way that this program is being offered is discussed.
Mechanisms and Conditions for Ecological Safety Provision in University Educational Environment

The relevance of the study is due to the fact that the increasing risks of global and local environmental crises put forward new demands to ensure national, economic, political, public ecological safety, including ecological safety of the educational space. The right to a favorable environment is one of the fundamental rights of citizens; therefore, ensuring ecological safety and comfort of the educational environment for the formation of a person focused on harmonious interaction with nature and protected from environmental threats becomes very important. The purpose of the study is aimed at the analysis of different approaches to the ecological safety of the University educational environment, the identification of mechanisms and conditions of the very process. The results of the study reveal that the system of ecological safety of the University educational environment is the combination of regulatory, training, educational, medical, recreational activities, aimed at harmonious interaction of man with the biosphere and the ecosphere. The ecological safety of the educational environment is determined by the compliance degree of the actual parameters of the environment ecological state with their optimal indicators for the preservation of the health of the educational process participants. The main elements of the mechanism to ensure environmental safety of the University educational environment are revealed: a comprehensive environmental assessment of the University and its surrounding area, environmental monitoring and effective management decisions in this area. The main conditions for the effectiveness to ensure environmental safety in the University educational environment are the use of the regulatory framework, the use of organizational and administrative impact and financial support, the unity of all participants’ activity in the educational process in this area. The Materials of the article are of theoretical and practical value for the development of educational and methodical complexes on ecology and environmental pedagogy, teachers’ training and retraining programs, as well as programs aimed at the formation of ecological safety of the University educational environment.
Foreign Direct Investments into Eastern Africa Region: The Governance Paradox

The role governance structures play in economic growth and development cannot be over emphasised. According to the World Bank, indicators that define governance include; Government effectiveness, control of corruption, political stability and absence of violence/terrorism, regulatory quality, rule of law, and voice and accountability. Regrettably, there has been limited attention to how governance indicators influence the flow of foreign direct investments. Therefore, this paper presents results from an extensive study on governance and foreign direct investments into 12 eastern Africa countries for the periods 2002 through 2016. By the use of generalized least squares on panel data, the study established that governance indicators do not have any significant relationship with the flow of foreign direct investments into the eastern Africa region, but when this relationship is controlled by availability of natural resources, exports, imports and labour force, the relationship turn significant. It is therefore, obligatory for countries to ensure a stable political environment which promotes security for both life and property. Additionally, institutions that promote public service delivery should be free from political patronage, align policy making and implementation to the development of the private sector and preventing corruption of all forms.
Block Chain a Peer-to-Peer Network: A Holistic Study from Research Firm to Corporate House

The blockchain, the technological innovation reinforcement the recognizable cryptocurrencies bitcoin, has progressively more the subject of academic and public question. In present circumstances it has become buzzword in a future too. Blockchain technology, first functional in the blueprint of Bitcoin in 2008, emerged from a movement of anarchists, computer scientists and crypto aficionado who aphorism the impending of the technology as a breakthrough in the long anticipated apprehension of an old “cypherpunk” dream of money that is free from the control of the state which also in a judicial language was considered as a legal tender and other third parties, such as commercial banks. The main aim of the research is to elucidate the concept of blockchain in a holistic manner vis-a-vis peer-to-peer network management by taking into consideration Internet of Thing (IoT), cryptocurrencies and bitcoin, positive etc. The study also highlights the impact of blockchain in a management perspectives. The paper also demonstrates how blockchain management with IoT will offer opportunities to the organizations and how it will impact their future competitiveness and market share and it exhibits various other issues relating to blockchain.
IMPLEMENTASI CLOUD BASED VIDEO CONFERENCE SYSTEM MENGGUNAKAN JITSI

Nowadays communication and information plays an important role. So that distance and time must be simplified so that decisions are made easily. Video conference is one. One result of the technological advancements that facilitate human is the Video conference. Video conference is an interactive communication device that can be used by second parties and can be used further through two-way audio and video delivery. Video conference technology must be in accordance with the International Telecommunication Union Standardization so that this communication is as desired, while H323 is the ITU standard for Video conference technology that includes audio, video and data related to networks that are not in accordance with Service Quality (QoS)