Reviewerly/exHarmony huggingface dataset:
Perancangan Sistem Informasi Helpdesk Menggunakan Website Design Methode Dalam Mendukung Tata Kelola Teknologi Informasi

Information Technology is important in increasing efficiency and efficiency in achieving company goals. Is a regionally owned company that in carrying out the functions and duties of clean water services for customer needs is never separated from the company's services to customers. Thus the helpdesk application is designed as a Single Point of Contact to focus on customer service issues. The purpose of this research is to analyze and manage the helpdesk application with a display design using the website design method. Built with PHP and MySql database, the application aims at implementing ITIL, which is useful for managing and assisting any problems (reporting) and service requests (requirements) to be sent to the unit that manages the handling schedule based on priority weights.
An Artificial System for Prognosis Cancer Cells through Blood Cells Images using Image Processing

In present scenario, imaging in act an important role throughout the integrated medical process from indicative and find out about diseases through studies. Considering most of the imaging techniques have gone directly digital, with unceasingly increasing perseverance, these medical image processing has to confront many upcoming challenges from broad data measures. In our paper we describe the process of analysing cancer cell and how image processing is helpful and immensely important in medical science. The paper analyse and discover bacteria under blood cells through its rate of growth of bacteria in blood with the help of object recognition technique of image processing by getting the image through microscope. This work presents an precise way of static image processing technique of object recognition for detection and prognosis of cancer cell. This method used for diagnosis of abnormal growth of cells in any body part using blood cell image. This procedure include artificial expert system techniques, such as machine learning, artificial neural network, and fuzzy logic with medical imaging techniques. We subsist blood images as input for our expert system to analyse and detect the classification of growth of abnormal cell through static image processing technique. This paper presents another technique of image processing as pattern recognition for analysis and classification of cancer cells using microscopic blood cells images..The proposed method achieved sensitivity of 80%. specificity of 91.04% and accuracy of 96.4%.
The Second Class of Applied Undergraduate Mathematics and the Practice of College Students' Innovative Ability Cultivation

With the goal of cultivating the innovative ability of college students, this paper constructs the second classroom activity model of "three combinations and three progressions", and continuously enriches the content of activities to maximize the students' innovative ability.At the same time, the evaluation system of college students' innovation ability based on the second classroom activity of mathematics is constructed.The fuzzy comprehensive evaluation based on the analytic hierarchy process is used to comprehensively evaluate students' innovation ability.It is concluded that the second classroom activity of mathematics has a positive effect on the cultivation of college students' innovative ability.
An Insight on Social Media Stream Mining

Data stream mining is one of the realms gaining upper hand over traditional data mining methods. Transfinite volumes of data termed as Data Streams are often generated by Internet traffic, Communication networks, On-line bank or ATM transactions etc. The streams are dynamic and ever-shifting and need to be analysed online as they are obtained. Social media is one of the notable sources of such data streams. While social media streaming has received a lot of attention over the past decade, the ever-expanding streams of data presents huge challenges for learning and maintaining control. Dealing with billions of user’s data measured in pet bytes is a demanding task in itself. It is indeed a challenge to mine such dynamic data from social networks in an uninterrupted and competent way. This paper is purposed to introduce social data streams and the mining techniques involved in processing them. We analyse the most recent trends in social media data stream mining to translate to the detailed study of the matter. We also review innovative implementations of social media stream mining that are currently prevalent.
Pembuatan Aplikasi Panggilan Darurat Berbasis Android Menggunakan Location Based Services

In everyday life we often encounter emergency situations such as accidents, drowning victims, fires, crimes and so on. Certain community may have had socialization or learned how to handle or first aid the emergencies, but not all societies know how to do first aid for emergencies.This research is aimed at building an Android-based emergency call application system for Bengkulu Region so that people can dial important phone numbers and public services when there is a crime or accident. The benefits of this application is as a medium to facilitate users of mobile devices based on Android in making emergency public service calls. From the problems that occur then, the problem of this research is How to Create Android-Based Emergency Call Applications For Bengkulu Region Using Location Based Services. The purpose of this research is to Design and Build Android-Based Emergency Call Applications for Bengkulu Region Using LBS Technology and create easily and quickly Emergency safe Calling System. The place of research is conducted on public service in Bengkulu city and is independently created. Data collection is done by using interview, observation and literature study method. The results showed that Applications that are created can help people to face emergencies so they do not get constrained when looking for agencies contact information that provide assistance services in times of emergency.Keywords : Applications, Emergency Calls, LBS
The Impact of Distortions on the Image Recognition with Histograms of Oriented Gradients

While most existing image recognition benchmarks consist of relatively high quality data, in the practical applications images can be affected by various types of distortions. In this paper we experimentally evaluate the extent to which image distortions affect classification based on HOG feature descriptors. In an experimental study based on several benchmark datasets and classification algorithms we evaluate the impact of Gaussian, quantization and salt-and-pepper noise. We examine both known and random types of distortion, and evaluate the possibility of applying distortions on training data and using denoising to mitigate the negative impact of distortions. Although presence of distortions significantly impede classification with the HOG features, in the paper we show how this negative effect can be greatly mitigated in practical realizations. Experimental results underpin our findings.
Web Scraping and Winnowing Algorithms for Plagiarism Detection of Final Project Titles

Plagiarism in research can occur due to accident or intentional. Plagiarism is an act that violates copyright and includes actions that harm others. In submitting the title of the research, for example, for the final assignment research, not a few students who repeatedly submitted titles were rejected and considered doing plagiarism because the title proposed had already existed before. Then we need a system that can detect the similarity between the titles to be submitted and the existing titles so that it is expected to reduce the occurrence of plagiarism. This study uses a winnowing algorithm to find the percentage similarity between titles. The Google Scholar will be used to obtain data on research titles that have been previously available as comparison titles. Web scraping with CURL (Client URLs) and simple HTML DOM parser is used to retrieve title data from Google Scholar. The results of the study with the application of a Winnowing algorithm to find the percentage similarity to data from Google Scholar were able to present a percentage of similarities in percent with the category of mild, moderate or severe plagiarism, while also helping early detection as prevention of plagiarism.
Diving Frequency Increase the Risk Barotrauma in Traditional Fisherman-Divers

Barotrauma is a problem caused by differences between air pressures inside the body and in the environment. This condition causes damage to many organs and body tissues. Many factors influence the occurrence of barotrauma. However, the two factors that are not obviously influencing the incidence of barotrauma are the diving frequency and the diving resting time. This study aimed to identify the effect of diving frequency and resting time on barotrauma. This study used an observational analytic design through a case-control approach of 174 respondents. The results show p-value=0.000 and OR=5.48 that indicate an effect of diving frequency on barotrauma. The diving resting time does not influence barotrauma with p-value=0.621. The diving frequency is a factor that affects the incidence of barotrauma.
Transitivity properties of ternary fuzzy relations

Recently, we have introduced six types of composition of crisp ternary relations.These compositions are close in spirit to the definition of the composition of binary relations.In this note, we extend these notions to the fuzzy setting.Based on these types of composition, we introduce several types of transitivity of a ternary fuzzy relation and investigate their properties.
Correction to: From receptive profiles to a metric model of V1

The authors would like to note an omission, in the published paper, of the Matlab code initially included as Electronic Supplementary Material. Therefore, we hereby re-submit the code in question.
Research &amp; Implementation of Multitasking Lego Robots

In this paper, according to the FLL competition task, a multitasking Lego Robot is developed by using the LEGO MINDSTORMS EV3 platform provided by LEGO Company which can connect water pipes, water flowers, extinguish fires and remove water pipes and so on, involving the mechanical structure, the sensor, the controller, the actuator and other devices. The mechanical structure design includes the chassis design, body design and the stability analysis of robot. The design of controller includes task optimization and control software design, and can be realized by two methods. One is EV3 graphic programming, the way of programming is multi-order structure, and the parallel structure is used to realize the linkage of different motors. Another is ROBOTC programming, using C language programming to minimize the need for computer hardware to run software. The test results reach the expected goal.
Bibliographical activity in the networked information environment

Challenges of the digital information environment web 2.0 transform the ways of bibliographic activities. Among the features of digital information environment are unstructured and heterogeneous data that consist digital information sources; erasing differences between publish and unpublish information that complicates the universal bibliographic control and selection of the information sources for libraries' collections; also the role of the user in the semantic web is changing from passive use of information to active involving in information creation, development and management, or human information interaction. The main trends of bibliographic activities in the digital information environment are the development of bibliographic metadata formats in the context of the universal bibliographic control of the digital sources web 2.0; design of the information architecture web 2.0 and information systems using the bibliographic principles of document identification, description, classification and labeling for digital documents and data and taking into account the usability and human factors requirements; management of folksonomies and web-services for user's personal bibliographic activities; usage of cloud computing to develop digital libraries and bibliographic services; integration libraries online catalogs with the interfaces of internet search engines in discovery systems; using new infometrics like altmetrics for bibliographic researches.
DETERMINING LECTURAL EVALUATION IN FACULTY OF ENGINEERING MALIKUSSALEH UNIVERSITY USING K-NN

K-Nearest Neighbor is a method that can classify data based on the closest distance. In addition, K-NN is one of the supervised learning algorithms with learning processes based on the value of the target variable associated with the value of the predictor variable. In the K-NN algorithm, all data must have a label, so that when a new data is given, the data will be compared with the existing data, then the most similar data is taken by looking at the label of that data. Filling and processing many questionnaires to determining the results of lectural evaluation from the performance of lecturers certainly requires a lot of time and process. Therefore, it is necessary to apply the K-NN Manhattan Distance method. In this study, the testing data is taken from one of the training data and has a classification result that is "Very Good". After going through the K-NN Manhattan Distance method with k being the closest / smallest neighbor, then the following results are obtained: Distance 5.4, the classification result is "Very Good" and 74.03% of similarity value. Based on the results obtained, the result of the classification from K-NN Manhattan Distance method show similarities with the results of the pre-existing classification.
CBNU System for SIGMORPHON 2019 Shared Task 2: a Pipeline Model

In this paper we describe our system for morphological analysis and lemmatization in context, using a transformer-based sequence to sequence model and a biaffine attention based BiLSTM model.First, a lemma is produced for a given word, and then both the lemma and the given word are used for morphological analysis.We also make use of character level word encodings and trainable encodings to improve accuracy.Overall, our system ranked fifth in lemmatization and sixth in morphological accuracy among twelve systems, and demonstrated considerable improvements over the baseline in morphological analysis.
Robust and Secure Image Reverse Watermarking using Data Encryption Standard and RNS

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Social Mission of Students in the Educational Process: The Past and the Present

Abstract The article considers the interconnection between students’ social mission in the conditions of information society and improvement of higher educational process. The aim and tasks of the article are to examine the dynamics of students’ social mission, to study out the characteristic features of improving educational process in relation to contemporary tasks of training a competent professional, empiric verification of proposed scientific positions. To investigate the connection between students’ social mission and optimization of educational process a set of methods was used: theoretical – historical analysis to define students’ social mission; comparison, generalization of scientific facts to uncover contemporary interaction tendencies of students’ social role and the flow of educational process; synthesis for clarification of the “students’ social mission” concept; empiric – experimental research of students’ satisfaction with the educational process, survey through online questionnaire, mathematic processing and generalization of acquired data. Analysis of open-type responses regarding the proposed remarks and recommendations enabled the formation of action directions to improve the conditions of educational process, such as support and facilitation of students’ academic mobility, usage of new forms and means in educational process (distance learning, training, contemporary information technologies and others), correspondence of the contents of educative qualification study programs with contemporary demands of a job market and others. Results of this study will be useful for scholars of social pedagogy, teachers, methodologists and heads of higher educational institutions, social pedagogues, social workers, students, etc.
Segmenting User Sessions in Search Engine Query Logs Leveraging Word Embeddings

Segmenting user sessions in search engine query logs is important to perceive information needs and assess how they are satisfied, to enhance the quality of search engine rankings, and to better direct content to certain users. Most previous methods use human judgments to inform supervised learning algorithms, and/or use global thresholds on temporal proximity and on simple lexical similarity metrics. This paper proposes a novel unsupervised method that improves the current state-of-art, leveraging additional heuristics and similarity metrics derived from word embeddings. We specifically extend a previous approach based on combining temporal and lexical similarity measurements, integrating semantic similarity components that use pre-trained FastText embeddings. The paper reports on experiments with an AOL query dataset used in previous studies, containing a total of 10,235 queries, with 4,253 sessions, 2.4 queries per session, and 215 unique users. The results attest to the effectiveness of the proposed method, which outperforms a large set of baselines, also corresponding to unsupervised techniques.
Concept–based Analysis of Java Programming Errors among Low, Average and High Achieving Novice Programmers

Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However, most of the studies employed omnibus approaches, i.e. without consideration of different programing concepts and ability levels of the trainee programmers. Such concepts and ability specific errors identification and classifications are needed to advance appropriate intervention strategy. Methodology: A sequential exploratory mixed method design was adopted. The sample was an intact class of 124 Computer Science and Engineering undergraduate students grouped into three achievement levels based on first semester performance in a Java programming course. The submitted codes in the course of second semester exercises were analyzed for possible errors, categorized and grouped across achievement level. The resulting data were analyzed using descriptive statistics as well as Pearson product correlation coefficient. Qualitative analyses through interviews and focused group discussion (FGD) were also employed to identify reasons for the committed errors. Contribution:The study provides a useful concept-based and achievement level specific error log for the teaching of Java programming for beginners. Findings: The results identified 598 errors with Missing symbols (33%) and Invalid symbols (12%) constituting the highest and least committed errors respec-tively. Method and Classes concept houses the highest number of errors (36%) followed by Other Object Concepts (34%), Decision Making (29%), and Looping (10%). Similar error types were found across ability levels. A significant relationship was found between missing symbols and each of Invalid symbols and Inappropriate Naming. Errors made in Methods and Classes were also found to significantly predict that of Other Object concepts. Recommendations for Practitioners: To promote better classroom practice in the teaching of Java programming, findings for the study suggests instructions to students should be based on achievement level. In addition to this, learning Java programming should be done with an unintelligent editor. Recommendations for Researchers: Research could examine logic or semantic errors among novice programmers as the errors analyzed in this study focus mainly on syntactic ones. Impact on Society: The digital age is code-driven, thus error analysis in programming instruction will enhance programming ability, which will ultimately transform novice programmers into experts, particularly in developing countries where most of the software in use is imported. Future Research: Researchers could look beyond novice or beginner programmers as codes written by intermediate or even advanced programmers are still not often completely error free.
Correction to: Better beware: comparing metacognition for phishing and legitimate emails

The article “Better beware: comparing metacognition for phishing and legitimate emails”, written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 20 July 2019 without open access.
A Case Study on Wildfire Propagation Modelling Using Evolving Rule Based Fuzzy Cognitive Maps

Fuzzy Cognitive Maps (FCM) and other Dynamic Cognitive Maps (DCM) were originally developed as mechanisms to simulate the evolution of complex qualitative dynamic systems.In this paper we present a case study where we show that Evolving DCM (specifically Evolving Rule Based Fuzzy Cognitive Maps, Ev-RBFCM) can also be used as a valid qualitative option to model a complex physical dynamic system, the propagation of a wildfire.
Empirical Study of Segment Particle Swarm Optimization and Particle Swarm Optimization Algorithms

In this paper, the performance of segment particle swarm optimization (Se-PSO) algorithm was compared with that of original particle swarm optimization (PSO) algorithm.Four different benchmark functions of Sphere, Rosenbrock, Rastrigin, and Griewank with asymmetric initial range settings (upper and lower boundaries values) were selected as the test functions.The experimental results showed that, the Se-PSO algorithm achieved better results in terms of faster convergences in all the testing cases compared to the original PSO algorithm.However, the experimental results further showed the Se-PSO as a promising optimization algorithm method in some other different fields.
Web Crawler for Indexing Video e-Learning Resources: A YouTube Case Study

The main objective of the current paper is to develop and validate an algorithm focused on automatically indexing YouTube e-learning resources about a certain domain of interest.After identifying the keywords specific to the desired domain, a web crawler is developed for evaluating video resources (from the YouTube platform) in terms of relevance for that domain.Once the most relevant video resources are found, they are indexed with the usage of a NER engine applied on their transcripts.In this manner, semantic queries can be used further in order to find exactly the needed information inside these multimedia resources.The crawler will repeat the indexing process daily in order to maintain the repository of semantically indexed videos up to date.The final chapter presents the obtained results together with the validation of the model.