Reviewerly/exHarmony huggingface dataset:
Parallel optimization of O (1) rectangular kernel max/min filters algorithm

The max/min filters are the most basic operator in gray-scale morphology. van Herk proposed an efficient O(1) rectangular kernel max/min filters algorithm which is independent of the size of filter window. This paper mainly studies the parallel optimization of van Herk’s max/min filters algorithm by using the single-instruction, multiple data (SIMD) technology and OpenMP parallel optimization technology for multi-core processors. First, the Intel Sreaming SIMD Extensions 2 (SSE2) is used to perform data-level parallel optimization for van Herk’s max/min filters algorithm in column direction, and a method based on histogram statistics is proposed to accelerate the calculation in row direction, the parallel speed-up ratio can reach 2. Then, the OpenMP parallel optimization technology is used to further perform thread-level parallel optimization for the SSE2 optimized version. The total speedup ratio under 4 cores and 4 threads CPU is about 7. Finally, compared with the rectangular kernel gray morphological operators in the powerful machine vision software MVTec HALCON17.12, the optimized algorithm in this paper has a great advantage in large window filtering size.
Initial Coin Offerings (ICOs)

Recently, Initial Coin Offerings (ICOs) have developed substantial influence as a funding mechanism while being largely neglected by research. In parallel, microblogs were identified as a source of organizational legitimacy and underpricing in Initial Public Offerings. In this paper, we investigate the influence of different types of social media, specifically microblogs and discussion forums, on organizational legitimacy in the realm of ICOs. As legitimacy cannot be measured directly, we follow renowned scholars and use underpricing as the dependent variable and an established proxy for legitimacy. We analyze data of 95 ICOs and provide first results indicating that discussion forum activity confers organizational legitimacy. Additionally, we show that the influence of strategic twitter management by the legitimacy-accruing organization is mediated by the activity of independent users on discussion forums. Furthermore, we introduce the phenomenon ICO as a funding mechanism fundamentally based on information technology and motivate further research on this topic.
KOHESI DAN KOHERENSI PADA KARANGAN DESKRIPSI SISWA KELAS VII SMP N 15 YOGYAKARTA

Cohesion is a semantic concept that displays the relationship of meaning between text elements. The relationship occurs because the meaning of one element of the text depends on other elements. Without the cohesion of the discourse, the text is not considered communicative and every element in it is interconnected. Coherence in sentences or paragraphs is the relationship between elements contained in a text. This research is descriptive qualitative research. This study uses a description of eighth-grade students of SMP N 15 Yogyakarta. The subjects of this study are the sentences in the writing of students' essays description. The object of this study is a marker of cohesion and coherence relationships used by students, including types, and how variations in their use. The design of this research is descriptive qualitative. Data collection techniques are done by reading and note-taking techniques. The method of analysis uses descriptive qualitative analysis methods. The instrument used in this study was a human instrument. The results of this study indicate that the total number of errors found was 10 errors consisting of six cohesion errors and four coherence errors. Keywords : cohesion, coherence, description essays
Arts Council funding boosts live jazz and blues at Sandwell libraries

Live jazz and blues will be heard at Sandwell's libraries throughout 2020 following a successful bid for funding to Arts Council England.
Research on Knowledge Context Management Model Based on Ubiquitous Learning and Its Application

In a ubiquitous learning environment, learners can use smart devices anytime, anywhere, and obtain the required knowledge points for learning in a massive knowledge base.However, the huge amount of knowledge resources in different scenarios and situations restricts the learners' learning and reduces the learning efficiency.This project focuses on the concentration of knowledge resources in different scenarios and the promotion of problems, and conducts basic scientific research on the knowledge management model that integrates knowledge context.Specifically, it includes the modeling of knowledge resource concentration and knowledge resource push, the construction and implementation of a Knowledge Context Management Model (KCMM) of integrated knowledge context, and the practical application of the model.It is hoped that the effective concentration of knowledge resources in the ubiquitous learning environment, the intelligent push of knowledge required based on different knowledge scenarios, and the accurate acquisition of knowledge content by learners will improve learning efficiency.It provides a theoretical basis for scene-based knowledge representation and knowledge management, and plays a dual inspiration at the theoretical and practical levels for guiding teaching resources and the construction of smart campuses.
THE USE OF MIND MAP TO IMPROVE STUDENTS WRITING DESCRIPTIVE TEXT

The aim of the study is to improve the students’ skill in learning English especially writing descriptive text. This research belongs to experimental research. Based on the observations, the problems found in teaching writing were ineffective strategy and instruction, language structure, vocabulary and lack of motivation. The data were obtained by interviewing the tenth grade students of SMK Yusuf Abdussatar Kediri Lombok Barat, holding the discussion with the English teacher, and doing observations in the English teaching and learning process. The instruments of the study were pre-test and post-test, observation guidelines, and interview guidelines. Qualitative and quantitative methods were used to collect the data. The data were analyzed from the field notes, interview transcript and the result of the pre-test and post-test. The result of the study showed that the students’ writing descriptive text in English teaching and learning process improved through mind maps. The result of the research showed that the mean score of post-test was higher than that of the mean score of the pre-test. The mean score of pre-test was (62.78) and the mean score of post-test was (75. 89). Thus, there was an increasing point of 13. 11. Keywords : mind-map, writing, descriptive text.
PENDAMPINGAN LITERASI SAINS DALAM PEMBELAJARAN DI SDN JELAMBAR BARU 01 PAGI [SCIENCE LITERACY ASSISTANCE IN LEARNING AT SDN JELAMBAR BARU 01 PAGI]

Literacy is not just the ability to read and write but adds knowledge, skills, and abilities that can make a person have ability to think critically, solve problems in various contexts, communicate effectively, develop potential and actively participate in social life. Community Partnership Program Activities in 2019 will be held at SDN Jelambar Baru 01 Pagi West Jakarta. This activity is carried out based on realizing a generation that can have broad insights into literacy activities that will guide them to be able to think critically. For this reason, teachers are trained to stimulate their students with problems and examples that are contextual with the subject matter so that teachers are able to explore their students' knowledge in teaching and learning activities so that partner schools can achieve performance targets both in aspects of learning, so mentoring Science Literacy to teachers in increasing the ability and understanding of their students. The method used is (active participatory methods in mentoring both in the socialization, discussion, and equalization of perceptions between the PKM team and teachers in partner schools. The results of this PKM from observation and evaluation there is a significant increase in literacy mastery for illustrated teachers from the lesson plans that they arrange to be implemented in learning.
Exploiting Consensus Clustering for Light Curve Data Analysis

Consensus clustering has been one of the major fields in data science, with increasing numbers of theoretical development and publications over the past twenty years. Recently, a new method for ensemble generation has been introduced with a good use of noise to create diversity via data perturbation. Based on good results with several benchmark data sets, its application to domain-specific problem such as astronomy seems to be an appropriate step ahead. Henceforth, this paper presents an empirical study of the noise-induced consensus clustering with a real data collection, obtained from published LSST light curve catalogue. Note that light curve profiles can be categorized into groups of known astronomical objects with common characteristics and behavior over time. As such, it is important to recognize new or unforeseen objects detected in a sky survey as one of those types, leading to appropriate data collection and further analysis. In particular, two different feature extraction techniques are used to derive features from raw time series records. With these, the performance of simple clustering of k-means and noise-induced ensemble counterpart are compared, using the set of four common clustering validity indices. The experimental results are highlighted with respect to factors of imbalanced data, quality of extracted features and number of clusters. These may help to improve the application of a single or ensemble clustering to light curve data in the future.
RIGS16-248-0412: V-logging and citizenship: the Malaysian experience

This research examined the relationship between vlogging and citizenship in Malaysia. Despite strict legal restrictions, Malaysians have taken their political discourses online and are challenging the contested freedom of speech and expression. Vlogging, in particular, enabled everyday Malaysians to become interactive social activists and political actors. By capturing this complex dynamics, this research provided a contextualized analysis of the many factors that build the vlogging-citizenship connection in Malaysia. Among others, it discussed the role of the Malaysian socio-political and media system in shaping the vlogging experience as well as the features of the vlogging technology that are changing the established Malaysian cultural and political traditions.
Tree-structured Bayesian compressive sensing based image watermarking

Watermarking is of vital importance for copyright protection and content authentication of images. With the development of compressive sensing, it has been successfully applied for watermarking with improved performance. Since an image can exhibit tree structure in wavelet domain, a new watermarking embedding and extraction method is proposed based on tree-structured Bayesian compressive sensing. The Markov Chain Monte Carlo (MCMC) method and the variational Bayesian (VB) analysis can be used for inference, respectively. Attacks to the watermarking, such as Gaussian noise, salt and pepper noise, Gaussian filtering, and JPEG compression, are given to evaluate the watermarking robustness with comparison to other reported reconstruction algorithms such as basis pursuit, orthogonal matching pursuit, Bayesian compressive sensing using relevance vector machine (RVM), and Bayesian compressive sensing with VB. Simulation results and comparisons show remarkable advantages of the tree-structured Bayesian compressive sensing for watermarking embedding and extraction.
Wall deadlock evasion motion of tracked vehicles for narrow space navigation

In this paper, the authors construct a motion generation method to avoid wall deadlock problem. Wall deadlock is a phenomenon that the robot cannot leave from a wall once it collides on it because collision force inhibits the motion. The proposed method is constructed directory from a static model of the tracked vehicle colliding with a wall.
Didactic prototype of student modern training: aspect of educational robotic complex realization

The relevance of the study is due to the changed trends in University students' training, suggesting an effective solution to educational problems with the help of digital means, among which a special place takes the robotic complex.In this regard, the article for the first time, as an independent scientific direction, attempts to substantiate the theoretical and methodological approach to the use of educational robotic complex as a didactic prototype of modern student training.During the implementation of pedagogical modeling -the leading method of research, educational robotic complex is justified as a methodological basis for the didactic prototype of student training.Taking into account the new trends in the transformation of student training, the article reveals the phenomenology of the educational robotic complex.Based on its results the study establishes the pedagogical terms of the educational robotic complex's realization; substantiates algorithm of didactic designing of a prototype educational robotic systems and proves its effectiveness in educational process of the University.The article focuses materials on providing methodological assistance to University teachers and students in the development and use of educational robotic complex in the educational process of the University.It gives recommendations for teachers, methodologists, University managers and students.
Increasing Prediction Accuracy with the Backpropagation Algorithm (Case Study: Pematangsiantar City Rainfall)

The more advanced science and technology from various disciplines, currently rainfall can be predicted by carrying out various empirical approaches, one of which is by using Artificial Neural Networks (ANN). This study aims to apply ANN with backpropogation algorithm in predicting rainfall. The research data used is BPS data of the transfer city. The results of the study state that of the 6 models (4-5-1, 4-10-1, 4-25-1, 4-5-10-1, 4-5-25-1 and 4-5-50-1) architecture that was trained and tested using Matlab 6.1 application software, the results showed that the 4-5-25-1 architectural model was the best model for making predictions with 75% truth accuracy, Training MSE 0.001004582, Testing MSE 0.021882712 and Epoch 59,076 . It is expected that research can provide input to the government, especially BMKG Pematangsiantar city in predicting Rainfall based on computer science so as to improve the quality of services in the fields of Meteorology, Climatology, Air Quality and Geophysics in accordance with applicable laws and regulations.
Repairing Individual Trust in Organizational Setting: The Mediating and Moderating Role of Benevolence and Competence Based

Introduction:Trust is a social construct that is present in the day-to-day routine of humans negative events such as product failure, revelations of corrupt practices, and unfulfilled promises could distort trusting relationships, develop negative future expectations, and in due course lead to trust violations.To maintain or restore the resultant loss of trust, organizations must examine and understand how trust was violated in the first place since different means of damaged trust are likely to require different reparative responses.Objectives: This study investigates how individual trust is repaired in an organization using apology and justification as means of repairing competence -based and benevolence-based trust violations.Study Design: Using a medical practitioner working in a private medical foundation called Save the Child Foundation, this research adopts a quantitative survey methodology using self-administered questionnaires to collect data from 304 patients and workers from a fictitious medical hospital in Cameroon.Hypothesis testing was carried out using structural equation modeling and regression analyses.Results: Through a scenario questionnaire survey, the study provided support for all of the hypotheses.Hypotheses 1 and 3 focused on the strategies of repairing trust.The result shows that benevolence had a mediating effect on apology, justification and trust repair.With the help of benevolence, medical organizations can easily accept to re-engage with individuals' doctors (John Benson) after trust violation.This shows that apology and justification are a good combination factor that can be used for repairing individual trust in organizations.More also, this study shows that the verification of Hypotheses 2 and 4 confirmed that competence-based trust had an important moderating effect on the positive relationship between benevolence-based trust and trust repair.In this case, competence could be regarded as a determining factor of repairing trust that has been violated.
FACT and FAIR with big data allows objectivity in science: the view of crystallography

A publication is an important narrative of the work done and interpretations made by researchers securing a scientific discovery.As The Royal Society neatly states though "Nullius in verba" ("Take nobody's word for it"), whereby the role of the underpinning data is paramount.Thereby the objectivity that preserving those data with the article gives is because readers can check each decision of the authors.But, how to achieve full data archiving?This is the raw data archiving challenge, in size and need for correct metadata.Processed diffraction data and final derived molecular coordinates archiving in crystallography has achieved an exemplary state of the art relative to most fields.One can credit IUCr with developing exemplary peer review procedures, of narrative, underpinning structure factors and coordinates data and validation report, through its checkcif development and submission system introduced for Acta Cryst.C and subsequently developed for its other chemistry journals.The crystallographic databases likewise have achieved amazing success and sustainability these last 50 years or so.The wider science data scene is celebrating the FAIR data accord, namely that data be Findable, Accessible, Interoperable and Reusable.Some social scientists also emphasise more than FAIR being needed, it should be "FACT", which is an acronym meaning Fair, Accurate, Confidential, and Transparent, this being the issue of ensuring reproducibility not just reusability.[Confidentiality of personal data not being relevant to our data obviously.]Acta Cryst.B, C, E and IUCrData are the closest I know to being both FACT and FAIR where, I repeat for due emphasis: the narrative, the automatic 'general' validation checks and the underpinning data are checked thoroughly by subject specialists (i.e. the specialist referees).IUCr Journals are also the best that I know of for encouraging and then expediting the citation of the doi for a raw diffraction data set in a publication; examples can be found in IUCrJ, Acta Cryst D and Acta Cryst F. The wish for a checkcif for raw diffraction data has been championed by the IUCr DDDWG (Diffraction Data Deposition Working Group) and its successor, the IUCr Committee on Data.
An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator

The traveling salesman problem (TSP) is a famous NP-hard problem in the area of combinatorial optimization. It is utilized to locate the shortest possible route that visits every city precisely once and comes back to the beginning point from a given set of cities and distance. This paper proposes an efficient and effective solution for solving such a query. A modified crossover method using Minimal Weight Variable, Order Selection Crossover operator, a modified mutation using local optimization and a modified selection method using KMST is proposed. The crossover operator (MWVOSX) chooses a particular order from multiple orders which have the minimum cost and takes the remaining from the other parent in backward and forward order. Then it creates two new offspring. Further, it selects the least weight new offspring from those two offspring. The efficiency of the proposed algorithm is compared to the classical genetic algorithm. Comparisons show that our proposed algorithm provides much efficient results than the existing classical genetic algorithm.
Some Aspects of Crime Scene Investigation

The crime scene investigation represents the procedural and criminalistic tactical activity whose object is the immediate perception of the place where the crime was committed; searching, discovering, revealing, fixing, picking up and examining traces and other means of evidence; specifying their position and status; determining the path taken by the offender (iter criminis), with the purpose of establishing the nature and the circumstances of the commission of the act, as well as the data necessary to identify the perpetrator. The crime scene investigation is the most important place for the criminal investigation, being, most of the times, the starting point of the forensic investigation. It is the richest in traces or data regarding the fact and its perpetrator, so how the entire investigation, search and collection of the traces or material evidence is carried out, as well as the determination of the results of the investigations, will depend on the discovery of the crime and the identification of the perpetrator.
Sliding window based weighted periodic pattern mining over time series data

Natural Sciences and Engineering Research Council of Canada (NSERC); University of Manitoba
Att förstärka sitt varumärke via influencer marketing : En studie om hur och varför företag använder sig av influencer marketing för att förstärka sitt varumärke

Influencer originally comes from the English word influence which means that you influence someone, for example in different purchases. Influencer marketing has over the years become a popular mark ...
Interpretation of musical composition: a methodical aspect

The article presents the issue regarding activation of artistic and interpretative activities of the students majoring in musical specialties at higher pedagogical educational institutions. The artistic-interpretative activity is considered as a factor of students’ creative development, growth and self-realization. The method of categorical analysis of the issue “interpretation” facilitated the establishment of a number of its values which were considered and implemented in the step-by-step experimental methods of training future music teachers in interpreting musical works. The course and results of the ascertaining stage of the pedagogical experiment have been presented. Based on the hermeneutical and artistic-mental approaches, the experimental methods of training students in interpreting musical works have been elaborated and presented. A wide range of methods of instrumental learning, performing exercises and independent artistic-interpretative tasks that determine the hierarchy of stages (initial-establishing, content-oriented and technological, analytical-final) of the presented methodology has been considered. The effectiveness of the text-centric paradigm of teaching in the practice of instrumental training of the future music teachers basing on a complex use of individual teaching methods alongside with dialogical methods of performing immersion, palliative and facilitation has been proved. The introduction of the lecture course “Fundamentals of Musical Interpretation”, the use of a complex of methods (analytical, practical, creative) and various artistic and interpretative tasks contributed to the increase of the respondents’ motivational orientation and activity as well as the increase of their interest in the artistic and interpretative activities. The results of the research and experimental work on the implementation of the methodology of training future music teachers in interpreting musical works testify to its expediency and effectiveness. Keywords: hermeneutical approach, interpretation, musical work, artistic and interpretive activity, teachers of Music.