Reviewerly/exHarmony huggingface dataset:
Edge Detection Through Dynamic Programming in Ultrasound Gray Scale Digital Images

Ultrasound medical pictures area unit are widely utilized since ultrasound might be a non-obtrusive and non-ionizing nosology system. Edge detection technique is generally utilized for any segmentation or extra estimations of components within the image. Edges speak to high frequency segments of an image. Initially we will convert ultrasound images into digital images through images processing technique. Then we propose dynamic programming procedure for locally discovering edges in gray level of ultrasound digital images. The DP algorithms method the for ultrasound images to urge the minimum accumulative value matrix to tracing a world best edge. Dynamic programming methodology and a threshold inclination administrator procedure are being utilized for edge discovery on each initial and noisy form of this gray level digital ultrasound image.
NURSING STUDENTS NEED OF LEARNING MEDIA FOR LEARNING ENGLISH

English language is frequently taught in Indonesian vocational college such as in Nursing Department. It is such a challenge for the students and the lecturer as well due to the tight schedule. The students need more exposures in English language, but the English course so far is only taught conventionally in the classroom once in a week for 2 semesters. The students need to fulfill certain competence in English in effective ways, one of the competence is English speaking skill. Learning speaking needs more effective methods. The methods could be in the form of the media used in teaching learning process. Besides, English speaking skill was so urgent for the students both in academic affair and professionalism. This study, therefore, observes the students’ need of learning media for learning English speaking. This was a qualitative research by conducting a syllabus investigation, interview, and questionnaire to collect the qualitative research data. The quantitative data was also conducted through delivering questionnaires to add the meaning of the qualitative data. This study revealed the kinds of learning media that the students need in learning English speaking skills that would also help them easily get the English courses exposures. The appropriate learning media for learning English speaking was a mobile learning media which has portability and high connectivity. It was a kind digital learning media that can be accessed at anytime and anywhere, installed in their smartphones which consisted of some speaking activities and their supporting activities.
Success History-Based Position Adaptation in Fuzzy-Controlled Ensemble of Biology-Inspired Algorithms

In this study, a new modification of the meta-heuristic approach called Co-Operation of Biology-Related Algorithms (COBRA) is proposed. Originally the COBRA approach was based on a fuzzy logic controller and used for solving real-parameter optimization problems. The basic idea consists of a cooperative work of six well-known biology-inspired algorithms, referred to as components. However, it was established that the search efficiency of COBRA depends on its ability to keep the exploitation and exploration balance when solving optimization problems. The new modification of the COBRA approach is based on other method for generating potential solutions. This method keeps a historical memory of successful positions found by individuals to lead them in different directions and therefore to improve the exploitation and exploration capabilities. The proposed technique was applied to the COBRA components and to its basic steps. The newly proposed meta-heuristic as well as other modifications of the COBRA approach and components were evaluated on three sets of various benchmark problems. The experimental results obtained by all algorithms with the same computational effort are presented and compared. It was concluded that the proposed modification outperformed other algorithms used in comparison. Therefore, its usefulness and workability were demonstrated.
Machine Learning Techniques to Analyze Operator’s Behavior

With more effective management teams, airlines are becoming more stable, more productive, and more punctual. The problems plaguing the aviation industry, however, have not gone away, and instead they have become more complicated. Schedule recovery is the process of recovery operating disturbances. The operator can either solve the problem manually, use a solution created by the recovery solver, or use a combination of both. The recovery solver from Jeppesen is a software tool that produces a set of solutions to resolve these operational disruptions. This research has been carried out at Jeppesen, a Boeing company. To analyze the Jeppesen airline system and recovery solver extensively and to identify various machine learning algorithms that can be used to answer the following questions: Will, the operator, use the recovery solver? and If the operator uses the recovery solver, which solution will she prefer? In this paper, we thoroughly study and understand the historical labeled data of alerts from a Mexico-based airline company created during disruptions. We have labeled the data points into two categories: manual solution and recovery solver solution. The experimental results obtained from this project have shown that that neural network models do not significantly improve predictive performance compared to the boosting models.
Meta-moderation for crowdsourced disaster management and urban participatory applications

This paper presents the Enterprise Meta-moderation of Innovation (EMI) system, which was designed, developed, and deployed to drive innovation in MTR Corporation, Hong Kong.Although EMI was designed specifically for use in an organisation, the system can potentially be extended to serve other useful functions in society.Hence, an important aspect of this paper involves identifying and discussing key considerations that need to be addressed in order for such a system to be used in crowdsourced disaster management and other urban participatory applications.The study highlights the role of agent-based modelling in better addressing some of the socio-technical challenges identified.
A Study on the Career Development of an Artist: The Case of KAWS

본 연구는 미술가 경력형성에 영향을 주는 주체 및 기관을 이해하는 것에 그 목적이 있다. 이에, 본고는 선행 연구를 바탕으로 예술학교, 갤러리, 비평가 및 미디어, 컬렉터 등 작가의 경력에 영향을 미치는 매개자의 역할을 이론적으로 검토하였다. 본 연구는 현대 미술가 카우스(KAWS)를 본질적 사례로 선정하고, 질적 사례연구를 수행하였다. 본 논문은 카우스의 경력 궤적(trajectory)과 연관된 다양한 출처의 이차자료를 수집하고, 이를 이론적 배경 안에서 분석하였다. 분석 결과, 사회학적 시각을 내포한 선행연구의 연장선에서 예술계를 구성하는 갤러리, 비평가 및 미디어, 컬렉터가 카우스 경력발전에 중요한 영향을 끼침을 명료화하였다. 한편, 본 연구는 선행연구에서 경시된 작가에 대한 대중의 관심을 미술가 경력형성의 측면에서 이해하는 것에 의의가 있다.This paper aims to understand the agents which have an impact upon artists career development. By critically exploring previous research, this article conceptualizes the roles of intermediaries such as art schools, galleries, critics, and collectors in influencing the careers for artists. The qualitative case study is conducted by selecting KAWS as an intrinsic case. This study collects secondary data about the career trajectory of KAWS by various sources, which are analyzed according to the conceptual framework. The outcome of this research clarifies previous research from a sociological point of view in which highlights the significant importance of the art world’s gallery, critics, media and collectors in developing the artist s career. In this paper, more importantly, the public attention to artists is construed as one of the agents influencing the career development of artists.
LibGuides: COVID-19: Faculty

This guide is to assist students and faculty with their research and instructional needs for library resources during the transition of online learning due to COVID-19.
Design of Software Trusted Tool based on Semantic Analysis

At present, the research on software trustworthiness mainly focuses on two parts: behavioral trustworthiness and trusted computing.The research status of trusted computing is in the stage of active immune of trusted 3.0.Behavioral trustworthiness mainly focuses on the detection and monitoring of software behavior trajectory.Abnormal behaviors are found through scene and hierarchical monitoring program call sequence, Restrict sensitive and dangerous software behavior.
Dynamic Load Balancing Algorithm for Heterogeneous Hadoop Cluster

Hadoop is a MapReduce open source implementation [1]. In homogeneous environment MapReduce can complete the parallel computing without major obstacles. load imbalance in the cluster is caused by heterogeneous nodes. We propose a dynamic load balancing model for heterogeneous clusters in this paper. In this a monitoring module is used to collect the real time information of each node. Load balancing is achieved by allocating the data dynamically based on computing capability and current load of a node. The results indicate the proposed algorithm reduced the execution time and balancing the load in the nodes of a cluster is achieved.
Design and Aural Analysis of Signal Processing Using Time Delay

This paper presents the design in PureData of some audio signals processes in real time like delay, echo, reverb, chorus, flanger e phaser. It also applies techniques of Aural Analysis, which intends to solve problems of intrinsic sound perception. We analyze the technical characteristics of each process and the psychoacoustic effects produced by them in human perception and audio applications. The approach for these processes is based mostly on Roads (1996), Berardino and Puckette (2006). We look for a better understanding of how some sound processes based on delay lines, such as simple delay, reverb and echo, affect the frequency spectrum of the processed sound during the time flow. Besides that, we identified other processes that also affect the spectrum, such as chorus, flanger e phaser, which nevertheless many times are not classified as resulting from time processes but as general effects. A deeper comprehension of the consequences of sound processes based on delay lines favors not only the awareness for the identification of the involved phenomena but also the technical choice of which process to use. This knowledge also helps the decision-making in professional audio applications such as the choice and positioning of microphones for audio recording in different acoustic spaces. This skill also benefits sound edition and mixing, besides music composition that employs sound effects in pre-processed or real time.
Effective migration resource reallocation based on cloud computing

A dynamic technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multi objective scheduling, and distributed and parallel scheduling.
PENGARUH PENGGUNAAN MODEL THINK PAIR AND SHARE TERHADAP HASIL BELAJAR MATEMATIKA BAGI SISWA KELAS V DI SD NEGERI GROJOGAN

The purpose of descriptive research is to determine the trends in mathematics learning outcomes using Think Pair and Share learning models and Expository learning models. Comparatively to find out the effect of Think Pair and Share learning model and Expository learning model on the mathematics learning outcomes of class V students of SD Negeri Grojogan. The hypothesis proposed in this study is that there is a positive influence on the Think Pair and Share learning model on the results of mathematics learning in fifth grade students of SD Negeri Grojogan in the academic year 2017/2018. The type of research used is a quasi experiment. The population of the study was the fifth grade students of Grojogan State Elementary School totaling 45 students, while the sample of this study was students of class V B as the experimental class with the number of students 22 and class V A as the control class with the number of students 23. Data collection techniques used documentation and test techniques. The data analysis technique uses descriptive analysis and hypothesis testing using the t test which is preceded by the analysis prerequisite test, namely the balance test, variant homogeneity test and distribution normality test. Descriptive research results show that the tendency of mathematics learning outcomes using Think Pair and Share learning models is high with an average score of 19.73 and the tendency of mathematics learning outcomes using the Expository learning model is classified as moderate with an average score of 15.13. The results of the analysis obtained a value of tcount = 6.074 with a value of p = 0,000 &lt;0.01. Thus, there are very significant differences in mathematics learning outcomes of students who are taught using Think Pair and Share learning models and Expository learning models. By looking at the average learning outcomes using Think Pair and Share learning models 19.73 and those using the Expository learning model 15.13, the Think Pair and Share learning model has a more positive effect on improving mathematics learning outcomes than the Expository learning model. Based on the results of research, schools should add reading references about Think Pair and Share learning models that can be used as a reference in the implementation of learning.
PERANCANGAN SISTEM INFORMASI PEMBAYARAN SPP TERPADU MENGGUNAKAN MODEL PROTOTIPE

SPP payment has become a main administrative activity in every educational institution, including Islamic Boarding School. SPP payment made only using manual procedures experience many obstacles. Therefore, a computer-based information system is needed to overcome these obstacles. This study aims to develop an SPP Payment System using the prototype model. The objective of this study is an Information Systems that can be applied practically in Islamic Boarding School to overcome obstacles in manual processing so as to increase the effectiveness and efficiency of the administration of SPP payments.
Experiences of Using Linked Data and Ontologiesfor Operational Data Sharing in Systems-of-Systems

This paper addresses the problem of exchangingcomplex data between the constituent systems in a system-ofsystems. This is necessary to ensure that they have compatibleunderstandings of the world su ...
A Mathematical Assessment of the Isolation Tree Method for Data Anomaly Detection in Big Data.

We present the mathematical analysis of the Isolation Random Forest Method (IRF Method) for anomaly detection, introduced in {\sc F.~T. Liu, K.~M. Ting, Z.-H. Zhou:}, {\it Isolation-based anomaly detection}, TKDD 6 (2012) 3:1--3:39. We prove that the IRF space can be endowed with a probability induced by the Isolation Tree algorithm (iTree). In this setting, the convergence of the IRF method is proved, using the Law of Large Numbers. A couple of counterexamples are presented to show that the method is inconclusive and no certificate of quality can be given, when using it as a means to detect anomalies. Hence, a more robust version of the method is proposed whose mathematical foundation is fully justified. Finally, numerical experiments are presented to compare the performance of the classic method with the proposed one.
Inference of functional dependence in coupled chaotic systems using feed-forward neural network

We propose a new model-free method based on feed-forward artificial neuronal network for detecting functional connectivity in coupled systems. The developed method which does not require large computational costs and which is able to work with short data trials can be used for analysis and restoration of connectivity in experimental multichannel data of different nature. We test this approach on the chaotic Rössler system and demonstrate good agreement with the previous well-know results.
MENINGKATKAN KETERAMPILAN BERBICARA MELALUI METODE BERMAIN PERAN DI KELAS V SEKOLAH DASAR NEGERI KEAGUNGAN 05 PAGI JAKARTA BARAT

This study aims to improve speaking skills through the method of role playing on fifth  grade at Keagungan 05 Elementary School West Jakarta, with total subjects were 30 students. This research was conducted in March-April 2019 on second semester 2018/2019. In the first cycle students who obtained a value of ≥70 obtained a percentage of 63.3%, while in the second cycle reached 90%. These results indicate that the use of role playing methods in learning Bahasa can improve the speaking skills on fifth grade students at Keagungan 05 Elementary School,  West Jakarta. Based on the observation of the learning process by applying the role playing method in Bahasa subject, the percentage of teacher activity in the first cycle of the second meeting was 76.6%. For monitoring activity actions at the second meeting was 75%. In cycle II the monitoring of teacher activity measures gets the second meeting was 93.3% and for student activities at the second meeting was 91.6%. The implication of this research is the speaking skills on fifth grade students of Keagungan 05 Elementary School West Jakarta can be increased in learning Bahasa with role playing method.
M-Learning: características, ventajas y desventajas, uso

The present essay has the purpose of revealing the characteristics, strengths, weaknesses of m-Learning and several examples of its applicability in different environments, especially the educational one. Mobile Learning or mobile learning is a style that has been created thanks to the advances of smart devices. Learning based on them, have great benefits such as mobility or accessibility at any time and place, which breaks the barriers of time and space. The use of such data transceivers and their applications involves adapting digital materials so that they are better utilized.
Topic Tracking and Visualization Method using Independent Topic Analysis

In this paper propose a topic tracking and visualization method using Independent Topic Analysis.Independent Topic Analysis is a method for extracting mutually independent topics from the documents data by using the Independent Component Analysis.In recent years, as the amount of information increases, there is often a desire to analyse topic transitions in time-series documents and track topics.For example, it is possible to analyse the causes of trend and hoaxes by SNS and predict future changes.However, there is no topic tracking method in Independent Topic Analysis.There is also no way to visualize topic tracking.So, topics in each periodwas extracted, and topic transition was analysed based on the similarity of topics.And, a method for tracking these four topics was proposed.In addition, this paper developed an interface that visualizes time-series changes of the tracked topics and obtained effective results through user experiments.
Predicting Second Language Writing Proficiency in the Different Genres of Writing Using Computational Tools

This study explored if linguistic indices calculated by computational tools can predict L2 writing proficiency scored by human raters. Using the latest computational tools such as TAALES, TAACO, and TAASSC with learner corpus (YELC), the language data related to lexical sophistication, syntactic complexity, and cohesion were measured and analyzed. The findings of this study show that the L2 writing proficiency judged by human raters can be significantly predicted by linguistic features. Among the linguistic features, the indices of lexical sophistication, such as word frequency, psycholinguistic word information, and ngrams, have the strongest power in predicting the narrative and argumentative writing quality. Syntactically, the fine-grained indices concerning clausal and nominal complexity contributed to explaining writing proficiency. While general characteristics were similar across the two genres, the distinctive linguistic features of each genre were identified. These findings illuminate a variety of aspects of L2 learners’ writing development and allow us to draw pedagogical implications on teaching and assessing writing in the Korean EFL context.
Lexical Tools for Low-Resource Languages: A Livonian Case-Study

This article focuses on the empirical experience and conclusions, resulting from the creation of language research and acquisition tools for Livonian – one of the smallest languages in Europe. A cluster was created for Livonian containing three interconnected databases, each with distinct types of data – lexical, morphological, and a corpus. The lexical database contains the lemmas and their data, the morphological database stores morphological forms, while all textual material, including the dictionary examples, is in the corpus. When indexing the corpus, every word refers to a lemma in the lexical database and its morphological information (new lemmas are added prior to indexation), ensuring consistency of the language data, and from each database the full data set of the other databases can be accessed. The function of each cluster is to extract the maximum amount of information from limited data sources. While technologies designed for languages with a large number of speakers focus on using quantitative methods and automation to extract qualitative information from a large and constantly expanding amount of linguistic data, the main function of technologies designed for small languages is to extract the same type of information from a limited and largely static data set. This article also examines a string of problems faced when working with a small amount of resources (inadequate language data, insufficient personnel, lack of rules for automating processes, etc.) and methods for resolving these problems in the case of Livonian.
Remaining True to His Calling [Pathways]

Profiles IAS member Carson Bates. Growing up during a time when computers and electronics were at the forefront of developing technology, Bates, like many others of his generation, was fascinated by computers. He attended the Colorado School of Mines in Golden to pursue a degree in electrical engineering with the intention of specializing in electronic circuits and microprocessor design. This plan changed after he attended an IEEE Industrial Applications Society (IAS)- sponsored student Chapter luncheon held at the Colorado School of Mines.
Diffusion and impact of Marshall McLuhan's published work in the Web of Science

This study gauges the scientific impact of Marshall McLuhan’s works on academic research. To this end, an analysis was undertaken to study published research that cited his works in the Web of Science (WoS) from 1957 to 2017. A total of 6,591 documents were found that record 8,989 citations from a range of McLuhan’s, mainly scientific documents (journal articles and monographs). The temporary distribution of the documents, the citations received by the different types of documents, the subject matter of the papers and the other co-authors cited along with McLuhan were analyzed. Among the main results, it was found that compared to the Canadian researcher’s journal articles, his monographs received the most citations received, notably his work entitled “Understanding Media: The Extensions of Man”. In addition, it was discovered that the interdisciplinary nature of McLuhan’s thought has had repercussions in different fields, such as communication, education, sociology and computer science. Since the second half of the 20th century, McLuhan is a benchmark, together with outstanding sociologists, philosophers and communication theorists such as Theodor Adorno, Pierre Bourdieu and Zygmunt Bauman, among others.