Reviewerly/exHarmony huggingface dataset:
Flow Field and Neural Network Guided Steering Control for Rigid Autonomous Vehicles

This paper studies the steering control for low-speed manoeuvring of autonomous ground vehicles. A guidance method combining flow analogy and a neural network model is proposed to produce the proper angular velocity for the vehicle, which can be used as a reference for the control of the steering wheel. In a previous study, fluid flow itself has shown outstanding global search capabilities in guiding the vehicle through complicated environments. But the vehicle is not always able to follow the motion of the flow due to the difference of their nature. In this paper, the heat flow analogy is used instead of fluid flow, and a neural network model is added upon the flow layer in order to produce a steering reference more suitable for a rigid vehicle. Simulated results demonstrate that, except for the branching situations, the proposed method is able to guide the vehicle towards its desired destination.
Semi-automated Construction of Air Pollution Domain Ontology

Air pollution has become a substantial environmental issue in China, which has seriously affected human health. To clarify the relationship among air pollutants, pollution sources, influencing factors, evaluation indicators and harms, it is essential to build a domain ontology for air pollution. Domain ontologies have been gradually accepted as a method to indicate the relationship between terms. However, there is not a complete ontology in air pollution domain, and building domain ontologies manually is time-consuming and inconvenient. In this paper, a semi-automatic approach is presented to build an ontology in air pollution domain. This paper proposes a method of entity relationship joint extraction based on attention mechanism, which is combined with core concept mining method to extract knowledge, and then concepts, relationships, and relevant instances are organized in hierarchy. Finally, the ontology model is constructed semi-automatically and semantic inference is also carried out. The research shows that this knowledge extraction method can avoid the error accumulation caused by entity recognition and relationship extraction and deepen the inner connection between them, and a large amount of effective knowledge in the field of air pollution can be extracted. In addition, the ontology constructed based on this method can also visually analyze the relationship between various classes and concepts in the field of air pollution, deduce the pollutant propagation path, and provide practical experience for the semi-automatic ontology construction in other fields and data support for further research.
Retracted Article: Collaborative correlation space big data clustering algorithm for abnormal flow monitoring

Click to increase image sizeClick to decrease image sizeView retraction statement:RETRACTED ARTICLE: Statement of retraction: collaborative correlation space big data clustering algorithm for abnormal flow monitoring Additional informationNotes on contributorsTing FuTing Fu Master degree, Senior engineer, Graduated from Huaqiao University in 2008, State Grid Fujian Electric Power Company, Technology of Computer Application, artificial intelligence, e-mail address: 34158958@qq.com.Hong ChenHong Chen Master degree, Senior engineer, Graduated from Fujian Normal University in 2010, State Grid Fujian Electric Power Company, Data mining, artificial intelligence, e-mail address: xiaoqimin321@163.com.Fei WuFei Wu Master degree, Senior engineer, Graduated from Wuhan University of Hydraulic and Electrical Engineering in 2000, State Grid Fujian Electric Power Company, Power information construction, e-mail address: wufeiliting@163.com.YunDong SuYunDong Su Bachelor, Senior engineer, Graduated from Harbin Engineering University in 1996, State Grid Fujian Electric Power Company, Database, information security, e-mail address: 3202163740@qq.com.Li ZhuangLi Zhuang Master degree, Engineer, Graduated from the Open University of Hong Kong in 2010, Fujian Yirong Information Technology Co., Ltd, Power information construction, e-mail address: 3336932622@qq.com.
Proposal of Representation Techniques to Enhance Affective Impressions at Scene of Collision in 3DCG Video Games of Third-Person Point of View

When we play three-dimensional computer graphics (3DCG) video games of third-person point of view, we can usually control both an avatar and a camera. There are some enemy characters in the CG game world, and we often lose contact with an enemy after the avatar collides with it. In this paper, we propose a camera control system that the view point makes a half turn in a horizontal direction after the avatar collides with the enemy. The camera shows both of the avatar and the enemy from the backside of the avatar. In addition, we propose a representation technique that obstacles make translucent to avoid occlusion when the avatar collides with the enemy. As a result of subjective evaluation experiment, it was shown that the visual effects of the proposed techniques useful to enhance affective impressions. Therefore, we think that the proposed techniques contribute to qualities of action video games.
Excel-Online Digital Tools for Training and Assessing Chemistry Knowledge of Foreign Students of Pre-university Department

The results of developing and testing digital elements of a distant computer system for assessment of chemistry knowledge to control the training level of foreign students of the pre-university department are provided. The Excel-online table kit is designed to support the training of foreign citizens for selection testing and continuous and midterm assessment tests. It is supposed to rely on BYOD technology, provide online access to tests and simulators via students’ mobile devices. The system is focused primarily on assessing knowledge of the subject. The wordings of the questions do not require fluent Russian language and do not contain complicated speech patterns. Answers also consist of the simplest phrases. The technology of using Excel-online tables as an environment for the development and performance of simulators and tests is described. Students are offered the opportunity to pass training on model sets of two-type test questions. The effectiveness of digital technology of automated transformation of the Russian version of the table test into any other language is shown. The described approach with regard to the level of students’ knowledge of the Russian language, multi-lingual test and the opportunity of preliminary training can lift language, technological and other barriers and assess exactly the knowledge of chemistry, but not the Russian language or information technology. The publication has been prepared under the support of the “People’s Friendship University of Russia Program No. 5-100”.
Cyclic quantum walks: photonic realization and decoherence analysis

Quantum walks serve as novel tools for performing efficient quantum computation and simulation. In a recent experimental demonstration [1] we have realized photonic quantum walks for simulating cyclic quantum systems, such as hexagonal lattices or aromatic molecules like benzene. In that experiment we explored the wave function dynamics and the probability distribution of a quantum particle located on a six-site system (with periodic boundary conditions), alongside with simpler demonstration of three- and four-site systems, under various initial conditions. Localization and revival of the wave function were demonstrated. After revisiting that experiment we will theoretically analyze the case of noisy quantum walks by implementing the bit-phase flip channel. This will allow us to draw conclusions regarding the performance of our photonic quantum simulation in noisy environments. Finally, we will briefly outline some future directions.
Text Summarization with Different Encoders for Pointer Generator Network

The ever-growing increase of documents has compelled the need of text summarization. In the past, deep learning models have shown state-of-the-art results for text summarization. In this paper, a comparison is conducted between different encoders for pointer generator network. The two different encoders used for comparison are bi-directional GRU encoder and bi-directional LSTM encoder. The decoder used with both the encoders is unidirectional LSTM decoder. The results are evaluated using ROUGE value. The experiments show that the bi-directional LSTM gives better result in comparison to GRU encoder.
An Efficient Learning Algorithm for Regular Pattern Languages Using One Positive Example and a Linear Number of Membership Queries

A regular pattern is a string consisting of constant symbols and distinct variable symbols. The language of a regular pattern is the set of all constant strings obtained by replacing all variable symbols in the regular pattern with non-empty strings. The present paper deals with the learning problem of languages of regular patterns within Angluin's query learning model, which is an established mathematical model of learning via queries in computational learning theory. The class of languages of regular patterns was known to be identifiable from one positive example using a polynomial number of membership queries, in the query learning model. In present paper, we show that the class of languages of regular patterns is identifiable from one positive example using a linear number of membership queries, with respect to the length of the positive example.
Publisher Correction: Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Font Comparison System Based on Multiple Similarity Metrics

Digital fonts are widely used in various fields such as documents, webpages, movie subtitles, etc., thus, how to select the best font for the content is an important issue. For the same font, the similarity calculated using different metrics is different. In this paper, we propose a font comparison system that considers different similarities by sorting the similarity of each font. For measuring similarity, we use MSE, PSNR, SSIM, and HaarPSI for image quality assessment, as well as Euclidean distance and cosine similarity in t-SNE to reduce the number of dimensions. We evaluate how the correlation to the font order of each comparison method changes depending on the resolution of the image, the character type, and the comparison method.
Wavelet-based baseline correction optimization algorithm for SF6 spectral signal

Abstract SF6 gas is widely used in various power equipment. In this paper, a baseline correction algorithm based on spectral detection method based on optimal wavelet basis is proposed. The algorithm selects the optimal wavelet base, removes the strong spectrum information by threshold method, eliminates the influence of continuum fitting, and performs the least squares fitting on the residual signal to obtain the continuum, and removes the continuum from the original spectrum to obtain the required Line spectrum. The accuracy of the quantitative analysis of the line spectrum intensity after processing is greatly improved, and the baseline is effectively estimated and corrected, and the fitting accuracy is higher than the traditional iterative wavelet baseline correction algorithm.
Thoughts on Basketball Teaching Reform in Colleges and Universities Under the Background of “Internet +”

With the development of Internet technology in China, the application of “Internet +” on basketball teaching in colleges and universities has become wider and wider. Under this background, this work first analyzed the influence of Internet on basketball teaching reform in colleges and universities, and then discussed the present situation on basketball teaching in colleges and universities, thus finding out the countermeasures on basketball teaching reform in colleges and universities and improving the quality of basketball teaching.
Visual Animations Content Feature Analysis Based on Image Information Extraction

Visual animation is a popular media on the web. It consists of many media elements such as text, graphics, images and sound. Based on the structure of flash animation files, this paper analyzes the content features of visual animation and builds a platform for extracting content features. Creating an index library for image features of flash animation is part of the research. The model is the development of content-based animation retrieval system. The media objects are extract the dynamic features of the moving objects, such as the motion trajectories and movement patterns of the media objects in the animation. Based on the extraction of media objects, dynamic features and interaction feature, high-level semantic features such as interaction degree, animation tempo and animation category can also be automatically extracted in the future. As a result, the creation of animation can be deduced to some extent based on these high-level semantic features.
Sensory design and smart textiles

This chapter describes a wearable biofeedback intervention that delivers a localized “scent bubble” diffused in response to a sudden change of mood. The research is informed by the author’s lived experience of bipolar affective disorder. It builds on earlier arts and humanities projects leading to transformative wearable technology that releases the appropriate “bio-synchronized” fragrance in response to different emotional triggers. eScent is an emotionally responsive, data-driven, liquid-dispense platform for connected clothing and jewelry, offering “personalized scent” as a self-delivery intervention for mental distress. Using machine learning and data to personalize treatment and care, the idea is that well-being fragrances (or other liquids) can be delivered once an artificial intelligence system has detected an increase in stress or change in environment. Wearable applications could lead to metered-dosed therapeutic scent dispersal to complement talking therapies, mindfulness meditation, or prodromal interventions for mood disorders, or as an internasal microdosing delivery system for psychedelic medicine. Closure of the loop of wearable scent delivery systems requires a transdisciplinary, creative, and collaborative approach, crossing many disciplines in neuroscience, olfaction, fragrances, psychological-related sciences, computer science, biotechnology, liquid engineering, fashion, and industrial and sensory design principles.
Michigan State University BEST

MSU presents our “Lessons Learned’ in the conception, formulation, execution and sustainment of the MSU BEST program. People with diverse expertise helped make this program real. Our trainees, fondly known as BESTies, made this program come to life. We share some of the things we did well, things we learned could have been done better, and the value of working as a team with a common goal.
A Lifelong Sentiment Classification Framework Based on a Close Domain Lifelong Topic Modeling Method

In lifelong machine learning, the determination of the hypotheses related to the current task is very meaningful thanks to the reduction of the space to look for the knowledge patterns supporting for solving the current task. However, there are few studies for this problem. In this paper, we propose the definitions for measuring the “close domains to the current domain”, and a lifelong sentiment classification method based on using the close domains for topic modeling the current domain. Experimental results on sentiment datasets of product reviews from Amazon.com show the promising performance of system and the effectiveness of our approach.
Evaluasi Sistem Drainase Menggunakan Storm Water Management Model (SWMM) dalam Mencegah Genangan Air di Kota Tarakan

Tarakan City experiences problems with standing water during the rainy season, especially in the west Tarakan sub-district which is the center of Tarakan. This puddle not only submerged settlements and offices but also shops and access roads that caused considerable economic losses. An evaluation was carried out by using the Storm Water Management Model (SWMM). SWMM is a rainfall-runoff simulation model used for simulating the quantity and quality of surface runoff from urban areas. Based on the evaluation using SWMM software, the drainage system in Tarakan, especially in Jalan Mulwarman has several inundated channels, namely channels 2, 3, 4, 5, 6, 7, 11, 12, 13, 14. This is influenced by the dimensions of the drainage channel that cannot accommodate existing water runoff and sediment thickness that covers the drainage channels so that the capacity is reduced, if it rains it will cause puddles at several points in Tarakan City. In order to deal with these puddles, it is necessary to change the dimensions of the channel and routinely dredge sediments that cover the drainage channels.
Incorporating Embedded Systems Security Awareness into a Computer Science Course via Minimal Interventions

In this poster, we describe our research on the use of small units of content, termed minimal interventions, to create awareness of embedded systems security concepts in an undergraduate course, Introduction to Operating Systems and Networking. This work focuses on the incorporation of simple activities such as short readings, and the evaluation of their potential as teaching tools. To study the effectiveness of this minimal intervention approach, we collected student performance data over six (6) semesters and across multiple modalities of the course, with a total of 1,168 study participants. Students were asked to complete a short survey before and after completing the activities, to assess prior knowledge of the subject and measure knowledge gains that resulted from participation in the activity.
The Relationship Between Psychological Stress and Self-efficacy Among the Educational Supervisors in Karak

The present study aimed at exploring the relationship between psychological stress and self-efficacy among the educational supervisors in Karak, Jordan from their own perspective. To meet the study’s goals, a questionnaire was developed. It consists from thirty items. The validity and reliability of the study’s instrument were checked. The population consists from 120 educational supervisors in Karak, Jordan. The sample consists from all the members of the population. Those supervisors were selected purposively. Questionnaire forms were distributed to the sample members. 115 questionnaire forms only were retrieved. All of the retrieved forms are considered valid for statistical analysis. Thus, the response rate was 95.8%. The researchers used several statistical methods. For instance, arithmetic means, standard deviations and the values of Pearson correlation coefficient were calculated. In addition, the values of Cronbach Alpha coefficient were calculated and the multiple analysis of variance (MANOVA) was conducted by the researchers. It was found that the respondents’ psychological stress level is moderate. It was also found that the respondents’ self-efficacy level is moderate. It was found that there is a statistically significant relationship –at the statistical significance level of a ≤0.05- between psychological stress and self-efficacy among the educational supervisors in Karak, Jordan. In the light of the aforementioned results, the researchers suggested several recommendations. For instance, the researchers recommend developing strategies by the Jordanian Ministry of Education for reducing the psychological stress levels of educational supervisors at Karak. That should be done because psychological stress can negatively affect the educational supervisors’ work performance and capacity to do the required work tasks. Keywords : Psychological Stress, Self-efficacy, Educational Supervisors DOI: 10.7176/JEP/11-6-13 Publication date: February 29 th 2020
EVALUATION OF THE EFFECTIVENESS OF THE MENTORING PROGRAM USING THE MODEL OF D. KIRKPATRICK

This article considers the evaluation of the effectiveness of the mentoring program using the model of D. Kirkpatrick from the point of view of sociology, discusses the feasibility of using the model of D. Kirkpatrick, explained the author's position on this issue.
Effectiveness of computer-assisted and excursion strategies on senior secondary school students achievement in Biology towards sustainable development

This study examined the effectiveness of computer-assisted and excursion strategies on secondary school students' achievement in Biology towards sustainable development.The study adopted quazi experimental research design.The population consisted of all the biology students in public senior secondary schools in South West, Nigeria.The sample for the study consisted of 240 senior secondary year two (SS2) Biology students selected from six schools in the three states from South West Nigeria using multistage sampling technique.The subjects were divided into the two treatments and control groups, that is, Computer Assisted, Excursion and control groups.A forty item multiple choice test on Biology was administered to the students after exposing the experimental groups.The treatment is teaching.Three hypotheses were formulated and tested; the data generated were analyzed using t-test and Analysis of Covariance (ANCOVA).The result showed that the achievement of students in the two experimental groups were better than those in the control group.Students taught with excursion strategy achieved better than those taught with Computer Assisted strategy.Also, location has significant effect on achievement while gender has no significant effect on achievement in Biology.Based on the discoveries, it was recommended that Excursion strategies and Computer -Assisted should be employed in the teaching of Biology as innovative strategies.
INTENSIFICATION OF COGNITIVE ACTIVITY OF STUDENTS WHEN STUDYING TECHNICAL DISCIPLINES

The paper gives a justification for the use of case technology in relation to the study&#x0D; of general technical disciplines. The advantages of using this method on the example of studying belt&#x0D; drives are shown.
Technology at the Service of the Elderly

An increase in longevity almost always implies the manifestation of more health problems, especially chronic diseases. And here, the elderly’s well-being and quality of life may be compromised since their level of dependence on others for everyday activities tends to increase and accentuate. Technologies can play a fundamental role in supporting and helping both the elderly —through telepresence robots that reduce their social isolation— and the informal caregiver —by installing a network of sensors that allow programming alarms for changing position and taking medication, for example—. Therefore, technologies can and should be put at the service of the elderly not to replace the human factor, but as a complement thereto.
Hunting as an Educational Phenomenon and an Object of Teaching Non-Profile Disciplines at Agrarian Higher School

The article proposes a methodology for using translated sources of the antiquity period while teaching non-profile disciplines at higher professional education institutions. The author justifies the educational potential of Xenophon’s “Cynegeticus”, a treatise on hunting. Relevance of the principle of integrative synchronous learning in higher education is justified. The researcher accepts the adopted conception of integrated educational and pedagogical space and emphasizes the necessity to evoke students’ cognitive interest while teaching the “Culturology” discipline at agrarian higher school.