Reviewerly/exHarmony huggingface dataset:
SIP-UNet: Sequential Inputs Parallel UNet Architecture for segmentation of Brain Tissues from Magnetic Resonance Images

Our work introduces a novel architecture for extracting information from neighboring slices in the image segmentation. The Proposed architecture consists of parallel UNets for each slice/image. These UNets are fused using Residual Network for late fusion. We passed features from central slice only in the residual network so that the features from the image to be segmented will not be lost. We performed segmentation using this architecture on the brain Magnetic Resonance Images (MRI). The processed data is obtained from the Open Access Series of Imaging Studies (OASIS) dataset. Data of each subject is in 3D. We extracted 2D slices/images from each subject and train/test for each view (axial, coronal, sagittal). As the 3D data has neighboring slices, that are similar to each other, we hypothesize and considered before and after slices as neighboring slice for segmentation of central slice.
Weather Condition Monitoring System as A Floods Prevention in Malang using Android Application

On January 2021 rain often splashing Malang City with intensity high and deep period a long time, so some areas experience flood. BMKG is an Indonesian official institution in charge to give information forecast weather good through online media nor offline. However, they do not give specific information about real-time location weather. This study aims to make it easy for user in accept information on bulk rain, water level, wind speed and temperature as effort to prevent flood. This study proposed prototype using bulk sensor rain, water level, wind speed and temperature as well as using ESP32 as microcontroller with monitoring via android. This tool could put in general place or in a vulnerable flood area. Results show that sending data from ESP32 microcontroller to firebase database is successful sent through "AVRO POLINEMA" Wi-Fi connection. QoS performance between ESP32 to Firebase shows throughput = 7.076368 Kb / s (poor), packet loss = 0.5% (very good), delay = 250,582 s (good), jitter = 0.0299139 ms (good) and between Application to Firebase got results throughput = 32.24112 (medium), packet loss = 0.4% (very good), delay = 118.009 ms (very good), jitter = 0.0903578947 ms (good).
Intelligent computer aided diagnosis system to enhance mass lesions in digitized mammogram images

&lt;span&gt;The paper presents an intelligent system to enhance mass lesions in digitized mammogram images. This system can assist radiologists in detecting mass lesions in mammogram images as an early diagnosis of breast cancer. In this paper, the early detection of mass lesion is visually detected by enhancing mass lesions in mammogram images using hybrid neuro-fuzzy technique. Fuzzified engine is proposed as a first step to convert all pixels in mammogram image to a fuzzy value using three linguistic labels. After that, artificial neural networks are used instead of the inference engine to accurately detect the mass lesions in the mammogram images in a short time. Finally, five linguistic labels are used as a defuzzifier engine to restore the mammogram image. Processed mammogram images are extensively evaluated using two different types of mammogram resources, mammographic image analysis society (MIAS) and University of South Florida (USF) databases. The results show that the proposed intelligent computer aided diagnosis system can successfully enhance the mass lesions in mammogram images with minimum number of false positive regions.&lt;/span&gt;
Images2Poem in different contexts with Dual‐CharRNN

Image to caption has attracted extensive research attention recently. However, image to poetry, especially Chinese classical poetry, is much more challenging. Previous works mainly focus on generating coherent poetry without taking the contexts of poetry into account. In this paper, we propose an Images2Poem with the Dual-CharRNN model which exploits images to generate Chinese classical poems in different contexts. Specifically, we first extract a few keywords representing elements from the given image based on multi-label image classification. Then, these keywords are expanded to related ones with the planning-based model. Finally, we employ Dual-CharRNN to generate Chinese classical poetry in different contexts. A comprehensive evaluation of human judgements demonstrates that our model achieves promising performance and is effective in enhancing poetry's semantic consistency, readability, and aesthetics. We present an Images2Poem with the Dual-CharRNN model exploiting images to generate Chinese classical poems in different contexts, which effectively improves the semantic consistency, readability and aesthetics of the generated poetry.
A cost-effective water heating solution for the people of Chhattisgarh, India

In this paper, we offer a cost-effective water heating solution for the rural people of Chhattisgarh, India. A single glazed floating cover has been designed from locally available materials in the current effort to boost the effectiveness of open heating water outside in the sun. The cover's upper face is made of transparent polythene, while the lower face is made of black polythene. The floating cover must be kept over the water-filled thermocol insulated bucket/tub. The solar radiation transmits through glazing is absorbed by black polythene. The water in contact gets heated. The heated water can be utilized later in the day. A mathematical model of the proposed heater has been developed and validated by an experiment. The overall heat loss coefficient has been experimentally determined. A simple techno-economic analysis has been performed. The cost of heating water is Rs0.71/kWh (US$0.01/kWh) for the climate of Raipur, Chhattisgarh, India (21° 9′ 53.9748″ N and 81° 46′ 31.1052″ E). The proposed method's cost of heating water is about 85.8% less than the cost of water heating by electricity. The water temperature available in winters is between 29°C to 38°C, and the maximum degree of heating of water is about 17.1°C.
COVID-19 Pandemic

Our study aims to analyze the change in coverage of health issues awareness, printed on the front page of Indian E-Papers (The Hindustan Times and The Times of India) for the pre-and- peri coronavirus period. The collected news articles are examined by performing the Latent Dirichlet Allocation algorithm. The sentiment analysis is performed to analyze the change in the emotions aroused from news articles. The outcome regarding the pre-coronavirus period reveals that the focus of the e-papers was mostly on politics, crime, and economy whereas, in the peri-coronavirus period, the e-papers are focusing more (i.e. 40 % topics) on publishing the news related to disseminating the awareness about the Coronavirus disease. The priority of news topics includes the active number of cases, medical facilities, COVID-19 testing. The outcome regarding sentiment analysis reveals that negative sentiments are prominent in the peri-coronavirus period due to fear of the outbreak of the virus.
A Study on the Current Status of Basic Liberal Arts Consulting for Junior Colleges

The purpose of this study is to summarize the achievements and limitations of basic general education consulting for junior colleges over the past 4 years, and to suggest improvement plans. The basic consulting for general education at junior colleges, which started in 2018, brought up the conversation topic regarding general education at junior colleges. Also, as general education was included as one of the the basic competency diagnostic evaluation items of junior colleges to be implemented in 2021, junior colleges began to accept general education as a practical task rather than as a superficial object. From 2018 to 2021, 41 junior colleges out of a total of 133 junior colleges participated in the basic general education consulting program, and the participation rate was 30.8%. 11 junior colleges particpated in 2018, 14 in 2019, 14 in 2020, and 7 in 2021. The junior colleges satisfaction with the consulting conducted to date has been quite high, as the students had the opportunity to actually check and improve the status of basic general education through the consulting program. In this study, for the development of basic general education consulting for junior colleges in the future, three things are proposed: First, the expansion of participation among junior colleges, second, quality improvement of the pre-diagnosis report, and third, the implementation of the consent form.
Factorial research and the recognition problem solution using the example of obstructive sleep apnea syndrome

Abstract The article is devoted to the problem of identifying factors directly or indirectly influencing the presence of obstructive sleep apnea syndrome in patients (OSAS) and solving the problem of pattern recognition in the factor space using the example OSAS. A factorial study was carried out for each group of indicators characterizing the condition of patients with OSAS, optimal factor structures were formed and the interpretation of the identified latent-integrative factors was carried out. It was implemented Bayes’ formula for calculating probabilities by OSAS groups in factor space. It is proposed formula for the transition from initial data to factors for finding the n-dimensional distribution density which is necessary for solving problems of recognition and based on the Bayesian criterion. There are given the proof of the transition formula and computational algorithms for the recognition problem.
Comparative analysis of interface sketch design tools in the context of User Experience

The design stage plays a significant role in software development. Making skeleton models helps to understand the specification and requirements of the product. Design tools, as well as any other tools, should focus on User Experience. The aim of the publication is to compare tools for sketching interfaces taking into account User Experience. The main criterion for the evaluation of the tools was a test consisting in measuring the time and distance of a computer mouse during the execution of a given application sketch in 8 selected tools. Then, the respondents assessed the possibilities and experiences resulting from working in a given tool. This was supplemented by the assessment of the technical criteria. Ultimately, the best and the worst tools were selected according to the research subgroups. The level of education has been proven to influence the evaluation of interface sketch design tools.
Fuzzy Logic and Deep Learning Integration in Likert Type Data

Deep learning networks have many modern applications and demonstrate a high-performance level.As the applications of deep learning networks to real-world problems continues to spread, the reason why they are effective remains unknown.However, it is possible to make some judgments by examining the behaviour of the network in experiments.The main aim of this study is to analyse the performance of deep learning techniques in the form of a 5-point Likert-type scale by converting the artificial data sets into a fuzzy form using triangular or trapezium fuzzy numbers.To test the performance of the proposed model, which is the integration of deep learning and fuzzy logic techniques, the satisfaction estimation problem was chosen.Data sets consisting of fuzzy numbers which reach at least three or four times more parameters than normal data sets.Thus, it decreases the possibility of falling into the local optimum trap in optimization studies with big data.In the analysis conducted with deep learning, in accordance with the fuzzification examples in the literature, the defuzzification was carried out with separate results for peak, maximum, and minimum values.In contrast to the literature, the performances of the deep learning model were investigated by suggesting that fuzzy numbers produce a single result series.
development of interdisciplinarity and transdisciplinarity in modern Russian science and higher education

To assess the prospects for the development of inter- and transdisciplinarity, we studied science and technology indicators for research in the Russian Federation, conducted by the Higher School of Economics (2017). We also analyzed the content of 150 scientific articles written by academic researchers and university teachers (2017–2020), in addition to reflecting on 30 years of experience at the Russian School of Transdisciplinarity (1990–2020). Our findings revealed two streams of institutional changes in interdisciplinary and transdisciplinary interactions, including insights from specific historical conditions in Russia. The first stream is evident in academic institutes and universities, where interdisciplinarity expands traditional academic outlooks through cognitive tools in two disciplines. The second stream is evident in autonomous non-profit organizations, where transdisciplinarity expands the academic disciplinary worldview by generalizing disciplinary knowledge. After describing historical conditions in modern Russia, this chapter refines definitions of interdisciplinary and transdisciplinary interactions. We then describe the development of interdisciplinarity and transdisciplinarity in academic institutions and universities. The chapter concludes with a section describing the prospects for developing transdisciplinarity in the non-state science sector of modern Russia.
THE ACTIVITIES AND DEVELOPMENT OF THE TOKYO GENERAL CONSTRUCTION WORKERS UNION CONCERNING HOUSING

This paper shows the development of the activities of the Tokyo General Construction Workers Union from 1947 to 1965 as a genealogy of the architectural movement in Japan after WWII. This union is an industrial labor union established by construction workers such as craftsmen in 1947. The postwar architectural movement was led by architects and focused exclusively on housing as a social issue. Therefore, we understood their activities concerning housing from the perspective of its relationship with architects and discussed its subsequent development.
A Study of Kindergarten's Self-Learning Tools to Read Jawi using Mobile Application

Jawi is a script based on the writing of the Al-Quran and derived from Arab-alphabet characters. When reading and writing religious books, stories, and so on, Jawi script is essential. However, in order to understand Jawi, students must first learn how to read Jawi, which should begin in kindergarten. They must be able to identify characters in Jawi. As a result, this paper addresses a research gap for existing work on learning Jawi script that is available in the market for commercial and scientific uses of mobile applications. We present our findings through a review and analysis of several studies. The features' and utility's strengths and shortcomings are also offered to provide a better knowledge of the gaps and weaknesses of each tool.
Introduction to the special section on intelligent systems and pattern recognition (SS:ISPR20)

The primary example of instance-based learning is the k-nearest neighbor rule (kNN), praised for its simplicity and the capacity to adapt to new unseen data and toss away old data. The main disadvantages often mentioned are the classification complexity, which is O(n), and the estimation of the parameter k, the number of nearest neighbors to be used. The use of indexes at classification time lifts the former disadvantage, while there is no conclusive method for the latter.This paper presents a parameter-free instance-based learning algorithm using the Half-Space Proximal (HSP) graph. The HSP neighbors simultaneously possess proximity and variety concerning the center node. To classify a given query, we compute its HSP neighbors and apply a simple majority rule over them. In our experiments, the resulting classifier bettered KNN for any k in a battery of datasets. This improvement sticks even when applying weighted majority rules to both kNN and HSP classifiers.Surprisingly, when using a probabilistic index to approximate the HSP graph and consequently speeding-up the classification task, our method could improve its accuracy in stark contrast with the kNN classifier, which worsens with a probabilistic index.
Information system of remote sensing data analysis

Abstract The information system is designed to solve the problems of analyzing remote sensing data and making decisions using non-parametric pattern recognition algorithms, the synthesis of which is based on kernel estimates of probability density. Initial information is compiled by training samples on the states of the investigated natural objects and their corresponding spectral data, which are presented in Microsoft Excel files. The application of the software provides the following functions: primary processing of remote sensing data to evaluate the main quantitative characteristics of the laws of distribution of random variables; testing of the hypothesis on distributions of multivariate random variables based on non-parametric pattern recognition algorithms; estimating the state of natural objects by spectral data; mapping of territories by state of natural objects based on spectral data of earth surface elements and their corresponding spatial coordinates. Results of the presented functional tasks are saved in the form of reports in graphic files and spreadsheets of Microsoft Excel. Software tools can be used in the study of various nature objects from remote sensing data.
What’s new in the use of punctuation: Analysis of questions and answers in the Language Counseling Service

The third monograph in the series “Discussions on Orthography” (preceded by Pravopisna stikanja ['Junctures of Orthography'], 2012, and Pravopisna razpotja ['Orthography at a Cross-Roads'], 2015) provides an opportunity to present the codification process in more detail. The revision of the Slovenian normative guide is accompanied by thorough research and broad deliberations, in which linguists are assisted by experts from other fields. In this way, we hope to move closer to the ultimate ideal. However, the Commission on Orthography at the Slovenian Academy of Sciences and Arts and the Scientific Research Centre of the Slovenian Academy of Sciences and Arts is aware that perfection is difficult to achieve, partly because we respect the diversity of language practises and ideologies. In this respect, we resemble the princess in Andersen's fairy tale; despite many figurative orthographic mattresses and duvets, we wake up repeatedly bruised by orthographic peas. The 22 contributors to the monograph demonstrate precisely this sensitivity to various orthographic and orthography-related issues. Their 19 contributions are thematically grouped in sections titled “The Codification Process: Insights and Observations,” “Dictionaries as Companions to Normative Rules,” “Orthographic and Broader Views on Proper Names and Common Nouns in Slovenian,” “Borrowing in Slovenian: Between Principles and Solid Solutions,” and “Orthography in Cross-Section with Phonetic, Stress, Morphological, and Word Formation Issues.” The monograph Orthography and the Pea thus opens a new perspective on topics that are more or less closely related to the creation of the new orthographic guide.
Mapping and Analysis of Standard Indonesian Pronunciation Errors by Using the Bigram Method

Indonesian language is increasingly being ignored, even the mass media often find the use of non-standard language, so there is a uniformity in the use of words that often appear in scientific articles, especially those Indonesian. The uniformity of Indonesian pronunciation certainly confuses the general public, for example: television news viewers and radio listeners, to distinguish between standard and non-standard forms. The non-uniformity of Indonesian pronunciation often occurs in official situations such as official speeches or presentations. Based on this phenomenon, this study aims to conduct an analysis and mapping study of standard pronunciation errors that arise in several public services and develops application tools as automatically tool that can detect errors from the use of standard words obtained from voice recording results in the form of vowel errors, diphthongs and consonants by implementing the bigram method. This research was conducted by collecting voice recordings of conversations, speeches, public speaking and other recordings deemed necessary, then continued with standard pronunciation errors analysis and mapping of these errors using a tool that applied the Bigram technique. Based on statistical information obtained from the detection and correction process that has been carried out, it can be obtained a mapping of the error types in the use of Indonesian standard that often occur in public service environment. The results of the mapping and statistical information obtained are used as the basis for developing programs that aim to improve the quality of the use Indonesian standard in the form of FGDs, socialization and counseling. The study result indicate the standard of pronunciation errors that occur in various circles including presenters and lecturers, then the results of data analysis are described in the form of tables and diagrams so it is seen the percentage of errors that occur
Creativity in Science and Art

This article compares creative work in science and the arts based on the author’s own experience. In the field of science, the author works in the field of computer vision and is most interested in modelling 3D shapes from depth images. He started to collaborate with new-media artists almost three decades ago to produce interactive art installations that used also computer vision technology. Gradually, he developed also his own art installations. Ten years ago, he took up sculpting in wood and stone using the direct carving method. He has sought to enrich his sculptures in a virtual dimension by means of video projection. The scientist/artist describes how his experience in computer vision modelling 3D shapes has influenced his sculptures and compares how creativity is expressed in both fields. Although there is usually a wide gap between science and art, creative activity in both fields has surprisingly many common features.
Effect of Named Entity Recognition on English-Vietnamese Neural Machine Translation

Translators are becoming more and more popular and achieving reliable results since deep learning was born.English-Vietnamese machines translation (MT) still have limitations due to Vietnamese contain words with many different meanings, thus resulting in the lower accuracy of automatic MT systems.Our study applied Named Entity Recognition (NER) tool for Vietnamese sentences to determine the category of words in the English-Vietnamese parallel corpus with over 900K sentence pairs.Then, we performed experiments to assess the effect of NER on English-Vietnamese MT systems.The results showed that NER had a positive effect on MT with averagely 1.24 Bi-Lingual Evaluation Understudy (BLEU) scores and averagely 1.8 Translation Error Rate (TER) scores increased comparing to data without using NER.
The biomedical informatics short course at Woods Hole/Georgia: Training to support institutional change

The US National Library of Medicine's Biomedical Informatics Short Course ran from 1992 to 2017, most of that time at the Marine Biological Laboratory in Woods Hole, Massachusetts. Its intention was to provide physicians, medical librarians and others engaged in health care with a basic understanding of the major topics in informatics so that they could return to their home institutions as "change agents". Over the years, the course provided week-long, intense, morning-to-night experiences for some 1,350 students, consisting of lectures and hands-on project development, taught by many luminaries in the field, not the least of which was Donald A.B. Lindberg M.D., who spoke on topics ranging from bioinformatics to national policy.