Reviewerly/exHarmony huggingface dataset:
Inter-space Machine Learning in Smart Environments

Today, our built environment is not only producing large amounts of data, but –driven by the Internet of Things (IoT) paradigm– it is also starting to talk back and communicate with its inhabitants and the surrounding systems and processes. In order to unleash the power of IoT enabled environments, they need to be trained and configured for space-specific properties and semantics. This paper investigates the potential of communication and transfer learning between smart environments for a seamless and automatic transfer of personalized services and machine learning models. To this end, we explore different knowledge types in context of smart built environments and propose a collaborative framework based on Knowledge Graph principles and IoT paradigm for supporting transfer learning between spaces.
A Near-Real-Time Answer Discovery for Open-Domain With Unanswerable Questions From the Web

With the proliferation of question and answering (Q&A) services, studies on building a knowledge base (KB) using various information extraction (IE) methodologies from unstructured data on the Web have received significant attention. Existing IE approaches, including machine reading comprehension (MRC), can find the correct answer to a question if the correct answer exists in the document. However, most are prone to extracting incorrect answers rather than producing no answers when the correct answer does not exist in the given documents. This problem is likely to cause serious real-world problems when we apply such technologies to practical services such as AI speakers. We propose a novel open-domain IE system to alleviate the weaknesses of previous approaches. The proposed system integrates an elaborated document selection, sentence selection, and knowledge extraction ensemble method to obtain high specificity while maintaining a realistically achievable level of precision. Based on this framework, we extract answers on Korean open-domain user queries from unstructured documents collected from multiple Web sources. For evaluating our system, we build a benchmark dataset with the SKTelecom AI Speaker log. The baseline models KYLIN infobox generator and BiDAF were used to evaluate the performance of the proposed approach. The experimental results demonstrate that the proposed method outperforms the baseline models and is practically applicable to real-world services.
Learning Lines with Ordinal Constraints

We study the problem of finding a mapping f from a set of points into the real line, under ordinal triple constraints. An ordinal constraint for a triple of points (u,v,w) asserts that |f(u)-f(v)| < |f(u)-f(w)|. We present an approximation algorithm for the dense case of this problem. Given an instance that admits a solution that satisfies (1-e)-fraction of all constraints, our algorithm computes a solution that satisfies (1-O(e^{1/8}))-fraction of all constraints, in time O(n⁷) + (1/e)^{O(1/e^{1/8})} n.
Virus Shutdown: Time for Digital Government to Prove Itself

Government IT staff and industry researchers weigh in on how digital services are meeting their moment, with office buildings closed, Web traffic spiking and applications for relief programs becomi...
On the relationship between the centroid and the footprint of uncertainty of Interval Type-2 fuzzy numbers

This paper presents experimental results about the relationship between the Footprint Of Uncertainty (FOU) and the centroid of Interval Type-2 Fuzzy Numbers (IT2FN) which are a subclass of Type-2 fuzzy numbers. Four types of IT2FNs are analyzed: singleton-core triangular, interval-core triangular, singleton-core Gaussian and interval-core Gaussian IT2FNs. A quadratic relationship was detected, characterized, and their results are presented and discussed using numerical experiments.
Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission

The mission of the Directorate General for Translation (DGT) is to provide high-quality translation to help the European Commission communicate with EU citizens. To this end DGT employs almost 2000 translators from all EU official languages. But while the demand for translation has been continuously growing, following a global trend, the number of translators has decreased. To cope with the demand, DGT extensively uses a CAT environment encompassing translation memories, terminology databases and recently also machine translation. This paper examines the benefits and risks of using neural machine translation to augment the productivity of in‒house DGT translators for the English‒Polish language pair. Based on the analysis of a sample of NMT‒translated texts and on the observations of the working practices of Polish translators it is concluded that the possible productivity gain is still modest, while the risks to quality are quite substantial.
A multi-strategy approach for the merging of multiple taxonomies

Taxonomy merging is an important work to provide a uniform schema for several heterogeneous taxonomies. Previous studies primarily focus on merging two taxonomies in a specific domain, while the merging of multiple taxonomies has been neglected. This article proposes a taxonomy merging approach to automatically merge multiple source taxonomies into a target taxonomy in an asymmetric manner. The approach adopts a strategy of breaking up the whole into parts to decrease the complexity of merging multiple taxonomies and employs a block-based method to reduce the scale of measuring semantic relations between concept pairs. In addition, for the problem of multiple inheritance, a method of topical coverage is proposed. Experiments conducted on synthetic and real-world scenarios indicate that the proposed merging approach is feasible and effective to merge multiple taxonomies. In particular, the proposed approach works well in the aspects of limiting the semantic redundancy and establishing high-quality hierarchical relations between concepts.
Inovasi Perpustakaan Melalui Pemanfaatan Teknologi Augmented Reality Dan Virtual Reality di Era Generasi Z

This study aims to determine the benefits of Augmented Reality and Virtual Reality technology applied to libraries in the Z generation era. The research method used study of literature by collecting several reference as sources that are relevant to the study material and and interviews with several generation Z informants. The results of the study found that the implementation of Augmented Reality technology can be used to create and read the Interactive Opac Brochure with AR; Utilization of Library Collection Display; Utilization for Searching Library Collections in Shelves through AR; Utilization for Interactive Learning Media for Users. While the implementation of Virtual Reality technology can be used for tours or library tours; Library Services; Information Literacy and Online Catalog.
The Position of Modern Biotechnology in Proving the Violation of the Living Right as a Right to Determine the Destiny

The role of different sciences in the development of each other is quite clear and undeniable. Today, the application of scientific and laboratory facilities for discovering the truth and collecting evidence has increasingly extended and almost dominated the old methods. Hence, the era of probative evidence has been introduced as the age of scientific and legal evidence convergence. Meanwhile, applying the evidence provided through biotechnological methods has become commonplace among judges for achieving the certainty and getting persuaded. On the other hand, the right to life is on the top of the list of fundamental rights inherited to the human beings which accurse the action of physically removing any person or a group of persons for any specific and non-specific reason. Self-determination is another basic human right which knows people possessing the fundamental right to determine their own destiny by birth. In a legal biological system, scientific experiments providing physical, chemical, and mechanical evidence from laboratory and biological examinations will be taken as the basis of criminal evidence, known as forensic biotechnology. In the present paper, the role of forensic biotechnology in establishing the above-mentioned human rights is summarized.
Q-Scrum: A Framework for Quality in Safety-Critical Development

This paper describes an adapted Scrum framework applied to a successful academic experience, using Interdisciplinary Problem Based Learning (IPBL) to conceptualize, model, and develop safety-critical prototypes. It presents an adapted version of the Scrum agile method used to develop a safety-critical project, achieving compliance with software standards. It also reports the development of some academic projects using IPBL and involving students from four different courses yearly offered by the Aeronautics Institute of Technology. At the end of each year, a prototype was developed and presented by the students.
Deriving A Novel Health Index Using A Large-Scale Population Based Electronic Health Record With Deep Networks

Health indexes are useful tools for monitoring the health condition of a population and can be used to guide healthcare policy of governments. However, most health indexes are constructed by using statistical methods to summarize recent adverse events (e.g., mortality). Information from these tools may reflect merely the impact of prior health policy holistically and can hardly indicate the most recent dynamics and its impact on future health conditions. As the advancements in medications and medical techniques rapidly evolve, there is a need of new health indexes that can reflect the most recent predictive health condition of a population and can easily be summarized with respect of any sub-population of interest. In this work, we develop a novel health index by using deep learning technique on a large-scale and longitudinal population based electronic health record (EHR). Three deep neural network (DNN) models were trained to predict 4-year event rates of mortality, hospitalization and cancer occurrence at an individual-level. Platt calibration approach was used to transform DNN output scores into estimated event risks. A novel health index is then constructed by weighted scoring these calibrated event risks. This individual-level health index not only provide a better predictive power but can also be flexibly summarized for different regions or sub-populations of interest - hence providing objective insights to develop precise personal or national policy beyond conventional health index.
Motion trajectory planning for a multi-link manipulator in an unknown environment based on ant colony optimization

А.Н. Горитов, К
A bibliometric overview of the International Symposium on Symbolic and Numeric Algorithms for Scientific Computing between 2005 and 2018

Current research offers a bibliometric overview of the International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, from 2005 to 2018, from different perspectives, in order to highlight the generated impact, the dimensions and strength of international collaborations, as well as a statistical study of conference papers, typical structure of collaboration groups, evolution of research trends, and others. Associated findings are presented either as raw data, or processed via VOSViewer.
Maternal health information in Nigeria: The myth and the beliefs

The influence of cultural beliefs on maternal health information and the sources of these information on maternal health in Nigeria was studied. Multi-stage sampling was used to select 1,706 participants from the six geo - political zones. Information was retrieved using questionnaire while variables formulated in the study were tested using chi square statistical tool. Awareness of maternal health information among the participants is high though were various beliefs at the detriment of maternal health in participants was noted, for instance, 67.0% of the participants believe people should have as many children as possible, 42.0% opined infertile couple should wait for God‘s time while 81.5% believe that child spacing is ungodly. The source of maternal health information was hospital (22.3%), radio (18.6%), internet (13.2%), friends (12.4%), television (12.2%), school (10.8%) and family (10.5%). Dissemination of adequate information on maternal health in local and pidgin languages is strongly recommended.Keyword: Maternal Health, Maternal Mortality, Cultural Beliefs, Nigeria.
An optimized encryption algorithm and F function with dynamic substitution for creating S-box and P-box entries for blowfish algorithm

In the field of cryptography, there has been a massive amount of enhancement in manipulating the plaintext which is unreadable, less prone to crackers and hackers, again manipulating this unreadable form to get back plaintext in some way. The Blowfish algorithm is a block cipher, has complex in structure in generating P-box and S-box entries using encryption algorithm. By simplifying the structure of encryption algorithm as well as F function with dynamic substitution, this can improve the performance by generating P-box and S-box entries of blowfish algorithm. In this paper, the proposed method simplifies the structure to produce P-box and S-box entries in order to reduce computational cost and demonstrates the performance of blowfish. The approach considers different security aspects namely EQ analysis, KS analysis, AV analysis, Entropy, Floating Frequency analysis and correlation of horizontally adjacent pixels in an encrypted image.
A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion

A novel self-organizing fuzzy proportional-integral-derivative (SOF-PID) control system is proposed in this paper. The proposed system consists of a pair of control and reference models, both of which are implemented by a first-order autonomous learning multiple model (ALMMo) neuro-fuzzy system. The SOF-PID controller self-organizes and self-updates the structures and meta-parameters of both the control and reference models during the control process "on the fly". This gives the SOF-PID control system the capability of quickly adapting to entirely new operating environments without a full re-training. Moreover, the SOF-PID control system is free from user- and problem-specific parameters and is entirely data-driven. Simulations and real-world experiments with mobile robots demonstrate the effectiveness and validity of the proposed SOF-PID control system.
The Construction of an Anti-drone System to Protect National Important Infrastructure

드론은 상대적으로 저렴한 비용, 구축 용이성 및 적절한 대응기술 부족으로 인해 이를 이용한 범죄가 점점 증가하면서 드론의 위협이 빠르게 증가하고 있다. 최근, 군사목표 공격에 사용되기도 하고, 국가 중요 인프라를 파괴하기도 한다. 이처럼 드론을 활용한 범죄와 테러가 발생하면서 국가 중요 시설에 침입하는 불법 드론을 탐지하고 추적해서 무력화하기 위한 신 기술과 동시에 안티드론 구축이 시급한 현안으로 대두되었다. 따라서, 대책으로는 첫째, 드론에 대비한 대공방어 및 중요시설 방호 차원의 안티드론 기술적용을 모색해야 한다. 둘째, 국가 중요 기반 시설에 대한 연구를 기반으로 시설 특징과 공격패턴에 맞춘 방어기술을 도입하는 것이 필요하다. 즉, 안티드론 시스템 구축 실증사업을 추진해야 한다. 셋째, 미래전은 드론에 의해 피해가 심각할 것이며, 이에 따라서 국방부 주도로 산ㆍ학ㆍ연과 협조하여 안티드론 기술 개발 로드맵을 수립해야 한다. 이러한 안티드론 시스템의 구축을 통해 드론으로부터 국가중요 기반시설을 완벽하게 보호할 수 있을 것이다.Crime and terrorism using drones have emerged as an urgent issue, along with new technologies to detect, track and neutralize illegal drones intruding into national important facilities. Therefore, as a countermeasure, first of all, anti-drone technical use should be sought for anti-drone defense against drones and protection of important facilities. Second, it is necessary to introduce defense technology tailored to facility characteristics and attack patterns based on research on national important infrastructure. In other words, the demonstration project for building anti-drone systems should be carried out. Third, the future war will be severely damaged by drones, so the Ministry of National Defense should establish a roadmap for the development of anti-drone technologies in cooperation with industry, academia and research institutes. By building these antidrone systems, we will be able to fully protect national critical infrastructure from drones.
Fuzzy Modeling Using LSTM Cells for Nonlinear Systems

The data driven black-box and gray-box models, like the neural networks and fuzzy systems, have some disadvantages, such as the high and uncertain dimensions and complex learning process. In this paper to affront these disadvantages, we use the Takagi-Sugeno fuzzy model and LSTM cells to propose a new fuzzy-network model. This novel model takes the advantages of the interpretability of the fuzzy system and the good approximation ability of the LSTM. We also propose a fast and stable learning algorithm for this model. Comparisons with others similar black-box and grey-box models are made, in order to observe the advantages of the proposal.
Pembelajaran Bahasa Inggris Berbasis Pendidikan Non-Formal di Kampung Inggris Kediri

The purposes of this study are to explore non-formal teaching methods and perceptions on the non-formal settings for learning the English language in base-camp, cafe and examination to interact with English native speakers in Prambanan Temple.  This study used a qualitative approach to assign a case study design. The study was conducted in Kampung Inggris Pare, Kediri, Indonesia in 5 weeks. A number of 30 respondents each of which 15 from AC course and 15 from CC course were selected.  Of the 30 respondents, 10 were good English competence, 10 fair and 10 low.  Data were analyzed using cultural thematic analysis, rate percentage, and frequency. Results show that non-formal education teaching methods are perceived by students as non-formal methods stressing in free classroom interactions and presentations.  Of three sites of learning, students with good competence in English accept all as comfortable learning sites.  In addition, maturity attitudes that include self-reliance, self-confidence, easy to adapt to the environment, and creativity are well performed by the students.  Likewise, students with fair English competence considered camp, cafe and the temple at lower degrees.  Maturity is also performed lower by the fair category students with the lowest degree at 60%.  The low competence students, however, can receive camp only as a comfortable place to learning.  All categories of maturity are performed in a low motion achieving 30% by the low competence students.
THE ROLE OF EDUCATION TECHNOLOGY IN THE DEVELOPMENT OF HUMAN RESOURCES AND EDUCATION TRANSFORMATION

The progress of globalizing technology has influenced all aspects of life both in the economic, political, cultural arts and even in the world of education. The development of science and technology is one of the productivity results of humans who have the knowledge gained from education. Where the development of science and technology has broad implications in human life, it is expected that these humans need to explore to take advantage of its benefits optimally and reduce the existing negative implications. Educational technology is only possible to be developed and put to good use when there are workers who handle it. They are skilled or experts in carrying out activities. The world of education, like it or not, must carry out a comprehensive innovation, means that all devices in the education system have a role and become a factor that is so influential in realizing reliable human resources and the success of the education system. Keyword: Education Technology, Education Transformation, Human Resources
A Coh-Metrix Analysis of the English Editorials of Korean, American, and British University Students

This study aims to identify differences between newspaper editorials of Korean, American, and British university students in order to shed light on more ‘native-like’ writing, and give pedagogical implications for L2 writing. The comparison between two native English groups could suggest which different results of linguistic aspects result from non-nativeness of Korean-English. The corpora consist of 209 English editorials of Korean, American, and British university students from student English newspapers, and then the editorials are analyzed. Coh-Metrix 3.0, which is a computational textual assessment tool, is used to measure the basic count of texts, lexical characteristics, syntactic complexity, discourse features, and readability level. As for the basic count, the sentence and paragraph length indices clearly show the remarkable difference between Korean- English and English-English editorials. Korean university students tend to write more sentences per paragraph. As for the lexical characteristics, the Korean EFL learners use the easiest words among the three groups. As for the syntactic complexity, the Korean students used significantly less complex syntactic patterns. As for the discourse features, the Korean students utilized connectives as cohesive devices the most. As for the readability level, the English editorials of the Korean students are less difficult than native English speakers.
3D MR image denoising using a modified adaptive high order singular value decomposition method

Magnetic resonance (MR) images are generally degraded by random noise governed by Rician distributions. In this study, we developed a modified adaptive high order singular value decomposition (HOSVD) method, taking consideration of the nonlocal self-similarity and weighted Schatten p-norm. We extracted 3D cubes from noise images and classified the similar cubes by the Euclidean distance between cubes to construction a fourth-order tensor. Each rank of unfolding matrices was adaptively determined by weighted Schatten p-norm regularization. The latent noise-free 3D MR images can be obtained by an adaptive HOSVD. Denoising experiments were tested on both synthetic and clinical 3D MR images, and the results showed the proposed method outperformed several existing methods for Rician noise removal in 3D MR images.
RAP3DF - One shoot 3D face dataset

Develop researches in the 3D biometrics field requires a large set of images, whether for training the algorithms or during the recognition test. Several datasets can be found in the literature. In an analysis of these datasets it was observed that a single dataset does not have the types of infrared images, visible and three-dimensional light, for the same sample. Given this context, the present work conceived this 3D facial dataset, with its respective visible light image and infrared spectrum, providing the entire image acquisition process from the Kinect One device. The work consists of 267 samples from 64 volunteers, where each volunteer has a frontal facial image and 3 images in arbitrary positions.
M-Learning in Developing Countries: Challenges, Remedies and Benefits in Instructional Activities

This paper attempted to discuss gains as well as weaknesses of m-learning usability in instructional activities in and outside classroom engagements. Hence, it examined its challenges, remedies and benefits in learning activities. Therefore, it is recommended that m-learning should be integrated into teaching and learning enterprise fully; teachers should be trained and retrained to develop maximum skills in Information and Communications Technology (ICT); and teachers should integrate and use m-learning in their classroom engagements.Keywords: M-learning, Technology, Information and Communications Technology, Challenges, Remedies