Reviewerly/exHarmony huggingface dataset:
Performance Improvement of Ovarian Cancer Classification Model Using Multiple Biomarkers and Menopause Information

The tumor biomarker test used for the early diagnosis of ovarian cancer is a relatively simple test using blood.In previous studies, an optimal combination of 2 or 3 biomarkers from 16 cancer biomarkers showing a specific response to ovarian cancer was designed to obtain an ovarian cancer classification model.Menopause is an important information for diagnosing ovarian cancer.In this study, we applied the menopausal status to the classification model and confirmed the performance results.The classification model has better performance when including menopausal clinical information.
Research on Multithreaded Download and Local File Operation of HTML5 Browser

Traditional browsers are inefficient in single-threaded download and rely too heavily on target servers. In order to improve download speed and stability, multithreaded download tools are urgently needed. However, current multithreaded download tools, such as Thunder and Free Download Manager, cannot meet the convenience and versatility of browser download process. Aiming at the above problems, this paper proposes a method that use Web Workers to implement multithreaded download of browser-side. Multiple sub-threads are created by the main thread of the browser, and these sub-threads request file data from the server at the same time, thereby improving file download efficiency and download speed. This article demonstrates the feasibility of this technique and verifies the integrity of the downloaded file using the File System API provided by HTML5.
Domain Adaptive Neural Sentence Compression by Tree Cutting

Sentence compression has traditionally been tackled as syntactic tree pruning, where rules and statistical features are defined for pruning less relevant words. Recent years have witnessed the rise of neural models without leveraging syntax trees, learning sentence representations automatically and pruning words from such representations. We investigate syntax tree based noise pruning methods for neural sentence compression. Our method identifies the most informative regions in a syntactic dependency tree by self attention over context nodes and maximum density subtree extraction. Empirical results show that the model outperforms the state-of-the-art methods in terms of both accuracy and F1-measure. The model also yields a comparable accuracy in readability and informativeness as assessed by human evaluators.
Engineering Projects ”Savanturiers de l’Ingénierie”

The "Savanturiers -School of Research" initiative is a French nationwide educational program that aims to introduce investigative approaches into schools through the creation of science projects.During the course of several Savanturiers projects, primary school pupils struggled with program design, among other difficulties, and we felt the need for methodical, technical and human support.In a computer science degree, the capstone project offers students the possibility of a "learning by doing" approach to software development, from the requirements to the product qualification.To overcome the difficulties mentioned, we have mobilized Bachelor of Computer Science students by giving them the classes involved in the Savanturiers projects as "clients" for their capstone projects.This has reduced the technical scope of the capstone projects but has increased their social utility.Although some Bachelor students did not take advantage of this situation, it was a positive endeavor as attested by the student feedback.
Chinese Medical Question Answer Matching with Stack-CNN.

Question and answer matching in Chinese medical science is a challenging problem, which requires an effective text semantic representation. In recent years, deep learning has achieved brilliant achievements in natural language processing field, which is utilized to capture various semantic features. In this paper, we propose a neural network, i.e., stack-CNN, to address question answer matching, which stacks multiple convolutional neural networks to capture the high-level semantic information from the low-level n-gram features. Substantial experiments on a real-world dataset show that our proposed model significantly outperforms a variety of strong baselines.
Real Time Analysis of Crowd Behaviour for Automatic and Accurate Surveillance

Surveillance in this modern era is a necessity.Creating an alert in case of emergencies and disturbances is of very much importance.As the number of simultaneous camera feeds increase, burden on human supervisor also increases.The proposed system is a way to aid human supervisor in the surveillance job.Creating alerts in real time will help responding quickly to crucial situations.With this in mind, we propose the following things: (1) Generation of ViF (Violent Flow Descriptors) as high-level features in real time.(2) Using generated ViF's of a Video Dataset for training a neural net and testing its accuracy.(3) Developing a system that can detect the signs of disturbance among the crowd in real time and can learn from the decisions it makes.
Complementary Knowledge Compilation Using the Hyper Extension Rule

We introduce the concept of Complementary formula (COMF), which is a new and non-equivalent way for Knowledge compilation (KC). Based on the Hyper extension rule (HER) which is an expansion of Extension rule (ER), we design a compilation algorithm which can formula compile each Conjunctive normal form (CNF) formula to complementary Fully complementary connected diagram (c-FCCD), named as C2C (CNF formula to cFCCD). Theoretically, c-FCCD is a kind of complementary formulae of the input formulae and can support all queries and partial transformations in KC map. Experimentally, C2C is competitive with the EPCCL compilers KCER, C2E, UKCHER, DKCHER and IKCHER.
PERANCANGAN DAN PENERAPAN COMPUTER BASED TEST (CBT) PADA SMK MUHAMMADIYAH KRAGILAN

In education field, examinations have become one way to measure the level of student achievement at school. Examinations that are usually used in schools such as daily/weekly/monthly exams, midterm exams (UTS) and final semester examinations (UAS). By using the exam, both students and teachers can evaluate each other about their teaching and learning activities. The examination model used so far is a conventional method model using paper-based tests. Traditional methods still have many disadvantages so other methods are needed to create efficiency, effectiveness, security, accuracy, and fast testing system. Another model that has been applied in school student test activities is the Computer Based Test (CBT Method). This method is proven to improve efficiency and effectiveness in the exam. Unfortunately, this new approach is only applied to national examination activities and has not been evenly distributed throughout the school. To use it in all the exam processes such as daily/weekly/monthly exams, midterm exams (UTS) and final semester examinations (UAS), this research uses waterfall metod was conducted at the Muhammadiyah Kragilan. The goal to be achieved is the creation of alternative test methods that can be used by partner schools that are more efficient, more effective, safer, more accurate and faster than the old test method
Android Application to Convert Speech to Text and Text to Speech

21 st century is the age of smartphones [1] and other smart gadgets like tablets, portable media players, pocket computers, and smart watches.Most of these gadgets run android OS developed by Google and Open Handset Alliance (OHA) [2].Android OS supports many android applications, either developed by the company itself or by any third party called third party application (app).In this paper, we have presented one of the applications developed by us which can perform the task of converting speech to text and text to speech.The speech of the subject will be carefully and intelligently converted to text by formal approximations.Anything written or copied to the clipboard can be converted to speech.Our goal is to operate using English language.This can be later employed in the case of regional languages as well.
Visualization of Schrodinger Equations Polar Wave Functions for Non-Central Coulombic Rosen Morse Potential in ExcitationState nr = 2 and l = 1

Research has been conducted which shows the quantization visualization of hydrogen atom orbitals angular space in Rosen Morse potential system interference when the electrons are excited in the state of nr= 2 and l = 1 through the polar function analysis of the Schrödinger Potential of Non-Central Coloumbic Rosen Morse. The polar Schrödinger equation is solved using the Romanovski polynomial method to obtain the polar wave function. To show the accuracy of the analysis, the polar wave function spectrum i s visualized with Matlab-based computer programming.
A Novel Active Contour Model Using Oriented Smoothness and Infinite Laplacian for Medical Image Segmentation.

Active contour model (ACM) has been widely used in image segmentation. The original ACM has poor weak edge preservation ability and it is difficult to converge to the concave, especially long and thin indentation convergence. In order to address these defects, a series of models such as gradient vector flow (GVF) and general gradient vector flow (GGVF) were proposed. A new edge-preserving ACM using oriented smoothness, infinite Laplacian is proposed in this paper to further address these issues. Oriented smoothness and infinite Laplacian are adopted as the smoothness term in the energy function to promote the model’s weak edge preservation and concave convergence ability. Furthermore, we employ a component-based normalization to accelerate the concave convergence rate. The experimental results show that the proposed method achieves better performance than the other comparative methods.
Thoughts about Foreign Language Teaching Planning Reform in Military Academies

In the process of transition from general foreign language teaching to military foreign language teaching, the main challenge facing the foreign language teaching reform in military academies is how to define and test the new foreign language teaching objectives scientifically.The paper points out that it is the key to solve the dilemma of foreign language teaching in military academies to grasp the special requirements of the application of military foreign language ability and integrate it systematically into the whole process of talent training.This study can provide a reference for the reform of foreign language teaching in military academies and provide some enlightenment for the reform of foreign language teaching reform in local colleges and universities.
Detection of Sentiment Provoking Events in Social Media

Social media has become one of the main sources of news and events due to its ability to disseminate and propagate information very fast and to a large population.Social media platforms are widely accessible to the population making it difficult to extract relevant information from the huge amount of posted data.In our study, we propose an algorithm that automatically detects events using strong sentiment classification and appropriate clustering techniques.We focus our study on a specific type of events that triggers strong sentiment among the public.Results show that the suggested methodology is able to identify important events, such as a mass shooting and plane crash, using a generalized and simple approach.
INTERPRETATION OF VISUAL STIMULUS AS A STRATEGY FOR DEVELOPING THE CRITICAL AND CREATIVE THINKING

The paper is devoted to the issue of university preparation of future teachers of fine arts through the interpretation of visual stimuli as one of the strategies for developing their critical and creative thinking.The author examines the problem in relation to the objectives of the project supported by the Research and Development Agency under contract no.APVV-15-0368 in the context of current teaching practice requirements for developing critical thinking and creativity.
A Method of Film Clips Retrieval Using Image Queries Based on User Interests.

The emergence of entertainment industry motivates the explosive growth of automatically film trailer. Manually finding desired clips from these large amounts of films is time-consuming and tedious, which makes finding the moments of user major or special preference becomes an urgent problem. Moreover, the user subjectivity over a film makes no fixed trailer meets all user interests. This paper addresses these problems by posing a query-related film clip extraction framework which optimizes selected frames to both semantically query-related and visually representative of the entire film. The experimental results show that our query-related film clip retrieval method is particularly useful for film editing, e.g. showing the abstraction of the entire film while playing focus on the parts that matches the user queries.
Awareness and Appreciation of Advertising Language

This research focuses on advertising language in advertisement slogans of various products written in English. The grand theory used is Stylistics, which is the study of the style of language or the study of the use of distinctive linguistic expressions and how they affect the target audience. To limit the discussion, this research more specifically covered the use of rhetorical figures and doublespeak in advertising language. These language features basically have the same functions, namely the aesthetic and persuasive functions, which aim to attract the audiences attention. This research, using an explanatory research method, was done to find out peoples awareness and appreciation of the outstanding use of advertising language by distributing questionnaires with Likert scale to the students and alumni of the English Department of a private university in Indonesia. Considering that in an advertisement there is also the visual aspect besides the textual aspect, the research was also done to find out whether or not there is a strong correlation between peoples awareness and appreciation of the visual and textual aspects.Keywords: advertising language, awareness, appreciation
Patterns Identification in the Consumption of Oracle Database Resources Using Weka Tool in Data Mining

This article focuses on the identification of periods of consumption of database resources helping the management of I.T. in decision-making.The purpose of this work is to mine data dictionary information from a given database, the Oracle Database System Manager, to obtain information to assist in analyzing the features of this database.For this, the KDD information extraction process was used in order to extract knowledge from the database by the identification of patterns.As a tool, we used Weka to develop this study, because it is open-source and has a range of algorithms that contains mining techniques, where it is possible to apply the last two steps of KDD.The applied methodology was a case study, making use of bibliographical techniques to collect information pertinent to the topic, in which all the 5 attributes related to the computational resources utilization of an Oracle DBMS were used.This data set consists of 5 attributes and 120 instances.Analyzing the statements generated by the rules it is possible to know which resource consumption is more or less used during a period of the day, proving to be useful in determining the resource consumption characteristics and thus assist in the decision to define a specific time to execute processes without affecting the overall performance of the database.
GEOMETRIC DEEP LEARNED FEATURE CLASSIFICATION BASED CAMERA CALIBRATION

This paper chiefly focuses on calibration of depth camera system, particularly on stereo camera.Owing to complexity of parameter estimation of camera, i.e., it is an inverse problem the calibration is still challenging problem in computer vision.As similar to the previous method of the calibration, checkerboard is used in this work.However, corner detection is carried out by employing the concept of neural network.Since the corner detection of the previous work depends on the exterior environment such as ambient light, quality of the checkerboard itself, etc., learning of the geometric characteristics of the corners are conducted.The pro-posed method detects a region of checkboard from the captured images (a pair of images), and the corners are detected.Detection accuracy is increased by calculating the weights of the deep neural network.The procedure of the detection is de-tailed in this paper.The quantitative evaluation of the method is shown by calculating the re-projection error.Comparison is performed with the most popular method, Zhang's calibration one.The experimental results not only validate the accuracy of the calibration, but also shows the efficiency of the calibration.
Efficient and Secure ECDSA Algorithm and its Applications: A Survey

Public-key cryptography algorithms, especially elliptic curve cryptography (ECC)and elliptic curve digital signature algorithm (ECDSA) have been attracting attention frommany researchers in different institutions because these algorithms provide security andhigh performance when being used in many areas such as electronic-healthcare, electronicbanking,electronic-commerce, electronic-vehicular, and electronic-governance. These algorithmsheighten security against various attacks and the same time improve performanceto obtain efficiencies (time, memory, reduced computation complexity, and energy saving)in an environment of constrained source and large systems. This paper presents detailedand a comprehensive survey of an update of the ECDSA algorithm in terms of performance,security, and applications.
Experiments About the Performance of Full Virtualization and Containers on ARM-v8 Platform

ARM based devices become more common in mobile devices, servers and embedded systems recent years. With the growing of cloud computing, the demand for virtualization on ARM platform is growing year by year. Traditional full virtualization solutions, such as KVM, extend their supports on ARM platform. Meanwhile, light-weight virtualization solutions, such as docker, also become popular and technically mature these years. Different solutions of virtualization have their own advantages. In order to present the functional difference and to evaluate the performance difference between virtualization solutions, we make a thorough study of these virtualization methods, then design and implement a series of experiments with KVM and docker on an ARM-v8 development board. The result shows that light-weight virtualization achieves better efficiency and usability with sacrifice of isolation and safety to a certain extent. Our work introduces the details of comparison, which can be a guideline for users to choose their solutions of virtualization according to their demands.
The Use of PPP Model In Enhancing the Students’ Speaking Ability

Speaking is the ability to pronounce words in order to convey or stated intention, ideas, thoughsts, feeling and dificult to deal with students. There are some problems as causes of the students’ difficulties in speaking, such as they are afraid of making mistake, less convidence, seldom to communicate and cannot express their ideas. To solve the problems, the researcher suggests the use of PPP Model in learning process. Based on the previous explanation, the researcher formulates the objective of the research is to find out whether or not the speaking ability of the seventh grade students of SMP Negeri 9 Parepare can enhance through the Use of PPP Model In this research, the researcher applied quasi-experimental design, with two group namely experimental class and control class. The samples was chosen using cluster random sampling technique. The total numbers of sample were consisted of 55 students from two classes taken from the population of the seventh grade students of SMP Negeri 9 Parepare. The instrument used in this research was speaking test by record the students’ utterance. The data were analyzed by using t-test formula. The result of the data analyzed shows that the students’ speaking ability improved significantly. It was showed by the mean score of pre-test was 45.33 and the post-test was 72. 83. Besides, the mean score of the students in post-test (72.83) was higher than the Kriteria Ketuntasan Minimal (71) in SMP Negeri 9 Parepare and include good classification base on Dirjen Pendidikan Dasar dan Menegah (2005). In the same line, the result of t-test value was 2.102 and t-table value was 2.004 in post-test. It means that the t-test value (2.102) was higher than t-table value (2.004). Those indicate that H1 was accepted and H0 was rejected. It also shows there is a significant difference between the speaking ability of the students who were taught through the Use of PPP Model and the speaking ability of the students who were thought by Discovery Learning Model (Conventional Ways).
Correction to: ECML PKDD 2018 Workshops

In the originally published version of the book, the editor "Irena Koprinska" was erroneously omitted from the editors’ list. This has now been corrected.
CORRELATION RELATIONSHIPS BETWEEN PERCEPTION OF INTERPERSONAL INTELLIGENCE WITH AFFECTIVE STUDENTS IN CURRICULUM DEVELOPMENT IN ELEMENTARY TEACHER EDUCATION STUDY PROGRAM OF PAKUAN UNIVERSITY

This research is a correlational design and quantitative research model. The purpose of this study was to describe information about the correlation relationship between Interpersonal Intelligence Perception and Affective Students in Curriculum Development Courses in fifth Semester students of the Elementary Teacher Education Study Program (PGSD) of Pakuan University. Based on the results of research on questionnaire data recapitulation and documentation, it can be concluded that there is a positive and significant relationship between the perceptions of interpersonal intelligence with the affective variables of the fifth semester students of class A and B PGSD Study Program, which means the more interpersonal intelligence students have, the more also high affective, and vice versa the lower the interpersonal intelligence, the lower the affective. The relationship can be seen from the price coefficient of 0.921, which means that the relationship between variables is very strong. The coefficient of regression equation Ŷ = 23.67 + 0.68X, which means that each increase in one unit of interpersonal intelligence will increase the effectiveness of 0.68 units. The contribution of perceptions of interpersonal intelligence in increasing affective is 0.53 or 53% and the remaining 47% can be influenced by several other factors.
Path Planning for Unmanned Surface Vessels with Multisensor Fusion Design

To achieve a successful sea voyage, an effective path planning algorithm plays an important role in avoiding vessel collisions in an autonomous surface vessel design .This algorithm depends on real-time global images of explored environments.Currently, satellite images used for the path planning algorithm always have rough resolutions, which increase the risk of vessel collision.To solve this problem, an alternative solution of integrating the aerial images captured by the image sensor of a flying quadrotor and the global positioning system (GPS), electrical compass, and height sensor data is proposed to provide real-time images in the global coordinate instead of satellite images.Naturally, aerial images possess higher resolution pixels than the satellite images and allow real-time modifications of geographic information.Images captured by the image sensor installed on the quadrotor are essentially represented in local coordinates; hence, in this investigation, a coordinate transformation for converting the local coordinate of the aerial images into the global coordinate is developed and named the distanceresolution transformation.With the fusion of these sensors and designs, the global coordinate of the high-resolution image can be calculated directly, and the real-time path planning using this aerial image can be applied to plan a collision-free path to navigate the unmanned surface vessel in any unknown ocean environment.