Reviewerly/exHarmony huggingface dataset:
Convolutional neural network based medical images integrity verification

With the development of multimedia and communication technologies in domains like telemedicine, it's critical to determine whether an medical image has been modified by some processing. Previous works mainly pay attention to the medical image modification based on global image processing methods. In this paper, we focus on local and global image processing detection, and propose a convolutional neural network (CNN) based method for this task. The input of the CNN is the characteristic function image (CFI) which is proposed in this paper and is extracted from the reorganized block-based discrete cosine transform coefficients. MURA dataset and 7 image processing methods are used to evaluate the proposed method and experimental results demonstrate the effectiveness of the proposed method.
Towards Trustable Internet of Things Certification

This chapter will outline the most recent evolution in the domain of IoT security and data protection labelling and certification. It provides an overview of several international research projects, including Create-IoT, Privacy Flag and ANASTACIA.
게이미피케이션 요소를 적용한 ‘사이언스 레벨 업’ 과학 수업이 과학긍정경험에 미치는 효과

The aim of this study was to find out how the science class program with applied elements of gamification, have effects on students’ change of positive experiences about science (PES hereafter). The participants of this study were 96 fifth graders of M elementary school located in Incheon. They were divided into the experimental group of 47 students and the comparative group of 49 students. For this study, The science textbook contents were reorganized into the integrated science, and instructions were carried out 16 times in total. The experimental group was provided the educational program with reorganized subject content and applied elements of gamification. The comparison group was provided the traditional educational program based on the textbook. The measurement of PES was conducted in five domains: science academic emotion, science-related self-concept, science learning motivation, science-related attitude, and science-related career aspiration. According to the result of the post-test of the PES, the experimental group significantly improved in PES than the comparative group. This seems possible because the attributes of the game itself are immersive and can induce learning motives. In addition, since the game itself is usually played in a certain rule with the members of the group, a game with the meaning of winning raises internal motivation for science learning, and it will have lasting impacts on hopes and aspirations for science-related career pathways.
SCALING-UP OF MEDIA EDUCATION PRACTICES IN MULTICULTURAL SCHOOLS. SOME RECOMMENDATIONS

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 2158-2164ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.0601Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
Can AI Outperform Doctors at Detecting Cervical Cancer

A new computer algorithm was able to accurately analyze digital images of cervical screenings and identify precancerous changes that required further medical follow-up.
Sistem Penggajian Online Untuk Guru dan Karyawan di Yayasan Pendidikan Al Irsyad Surakarta

Payroll system is now developing, namely the application of information technology. Yayasan Al Irsyad Surakarta has implemented an online payroll system, but in the payroll system there are still shortcomings, such as mistakes and lack of some desired features, for example there are some features that cannot be used or often occur errors such as sending email reports to banks and edit benefits data. Other features that do not yet exist are deleting job data, locking personal data, sorting the report names of each unit based on the alphabet and other features. This application was built using sublime text 3, PHP programming, Navicat, MySQL and xampp v3.2.2. This payroll system is made by the method of System Development Life Cycle (SDLC) with a waterfall model where this method has 5 stages, namely: needs analysis, planning, coding, testing and implementation. This system has also been tested using black box testing from 24 points tested, all of which are good and based on testing questionnaires with 35 respondents including treasurers of LPP, principals, teachers and employees with a 72,4% yield. So the respondents agreed that this system was feasible and capable of helping the performance of employees at the Yayasan AlIrsyad Surakarta.
Prototype Development Of Information System Customer Relationship Management Web-Based Aesthetic Beauty Clinics

Every company will definitely develop innovations that are always the latest in order to provide comfort in service to customers. Good service quality must be managed professionally, especially in managing information related to the customer. One of the means to accommodate customer data management is to develop a Customer Relationship Management (CRM) information system on Kartika Aesthetic that operates in the field of beauty clinics. As in general, customers who will take care must come directly to Kartika Aesthetic for registration. Not only that, notification of the customer's routine check schedule is also done when the customer finishes doing maintenance. Therefore, many customers forget the check date again because there is no notification or reminder about it. Notifications regarding discounts or treatment promo prices are also notified using social media Instagram and Facebook, if the customer does not have an account, then the customer does not get information about the ongoing promo or discount. With the existence of this CRM information system, it is expected to be able to help the acquisition of information needed by customers to be easy and fast in accordance with the expectations and needs of customers and to bridge the communication between Kartika Aesthetic and customers. The purpose of this research is to develop a prototype CRM information system, to test and evaluate the CRM information system that has been designed. The programming languages used in this system are Java and MySQL databases. The method for developing this information system uses the Relational Unified Process method with UML tools (use case diagrams, activity diagrams, class diagrams and Sequence diagrams). This CRM information system is designed with attention to user needs. In addition to making it easy for customers to register directly through the Prototype information system, this CRM information system enables customers to obtain information about maintenance schedules, new types of treatments and other promos easily and in accordance with and the need sof the customers. Keywords: CRM, Prototype, UML
A Precise Performance Analysis of Support Vector Regression

In this paper, we study the hard and soft support vector regression techniques applied to a set of $n$ linear measurements of the form $y_i=\boldsymbol{\beta}_\star^{T}{\bf x}_i +n_i$ where $\boldsymbol{\beta}_\star$ is an unknown vector, $\left\{{\bf x}_i\right\}_{i=1}^n$ are the feature vectors and $\left\{{n}_i\right\}_{i=1}^n$ model the noise. Particularly, under some plausible assumptions on the statistical distribution of the data, we characterize the feasibility condition for the hard support vector regression in the regime of high dimensions and, when feasible, derive an asymptotic approximation for its risk. Similarly, we study the test risk for the soft support vector regression as a function of its parameters. Our results are then used to optimally tune the parameters intervening in the design of hard and soft support vector regression algorithms. Based on our analysis, we illustrate that adding more samples may be harmful to the test performance of support vector regression, while it is always beneficial when the parameters are optimally selected. Such a result reminds a similar phenomenon observed in modern learning architectures according to which optimally tuned architectures present a decreasing test performance curve with respect to the number of samples.
Comprehensive Information Security Awareness (CISA) in Security Incident Management (SIM): A Conceptualization

Information security incidents are a major concern for organizations today, and the prevention and mitigation of such incidents are essential for business survival and smooth functioning. Organizations implement a security incident management process to detect and mitigate security incidents. Despite an organization’s investment and efforts to prevent security incidents, its occurrences have increased over the years, signaling limitations in the existing process. We posit that the limitations may be due to the lack of a comprehensive awareness of threats by security professionals. To this effect, we define and conceptualize Comprehensive Information Security Awareness (CISA) as comprising of three elements, namely: security, system, and situational awareness. We leverage the knowledge, skills, and abilities-based approach in NIST-SP-800-16 and security awareness concepts from the literature for conceptualizing CISA. We discuss the effects of CISA on threat management tasks in the context of security incident management.
An Approach Towards Usability Parameter for Graphical Based Authentication System

Authentication systems are the protective barrier of any software. The authentication system can be classified as Token based, Biometric based and Knowledge based. This research study is based on knowledge based authentication system. As an initial step the existing knowledge based authentication system has been studied for its highlights, comparative facts, advantages and disadvantages. For acceptance of any secure system the usability aspect is the first step in the authentication process. The various usability evaluation parameters of the existing systems and an approach towards developing a modified usable authentication system have been briefly discussed. Future scope of other dimensions viz. randomness and security and a deep study have been highlighted as the concluding remark of this research work.
Achieving Data Truthfulness and Privacy Preservation in Data Markets over Cloud Computing

As data plays an important role in any organization where data DE duplication is a data encoding approach which is used for deleting present duplicate copies of replicated data, as well as it is preferably used for storage purpose in cloud to conserve space and bandwidth. To preserve privacy laws with some allowing de-duplication, the heterogeneous encoding method has been proposed to secure communications before privatization. It is the first comprehensive effort to address the issue of permitted data de-duplication in addition to enhancing data security. In contrast to conventional de-duplication methods, the replicate check approach often discusses both the data and the users' differential rights. In a hybrid cloud architecture, we do demonstrate a number of new de-duplication structures that allow for duplicate check. Our scheme is secure in respect of the definitions identified in the proposed security model, thus according securing data. We provide a prototype of our proposed accepted duplicate check scheme as a proof of concept and perform experiments with it. As compared to conventional operations, we display that our proposed allowed replicate check schemes suffers reduced overlap.
THE ROLE OF CREATIVITY IN TEACHING A TECHNOLOGICAL SUBJECT

The article is devoted to the study of the problem of creativity in teaching technology subjects. The author pays special attention to the issue of preparing students in the modern educational system for social and social life through technological subjects. Considered the main features of creativity, the value of using creativity in teaching, pedagogical and psychological characteristics of creativity. The peculiar features of the psychological development of students with creative thinking.
Social learning dynamics influence performance and career-related attitudes in career-oriented educational virtual environments

Educational virtual environments (EVEs) are defined by their immersiveness and fidelity to real-life scenarios. EVEs are associated with positive learning outcomes, but research has largely not explored the psychological processes underlying these outcomes. We present two studies that explore this phenomenon in welding skills training. Study 1 provides evidence that welding career exploration in EVEs is associated with positive career-related attitudes. Study 2 explored psychological mechanisms that may explain the attitudinal and performance outcomes of skills training in career-oriented EVEs through a social learning perspective. Since EVEs vary in their level of immersion and fidelity, this study compared groups training with VR to groups using a desktop simulation. Findings indicated strong social learning dynamics in both EVE contexts, but effects were stronger for the VR condition. Learners within groups converged on performance, and the performance of group members who functioned as behavioral models significantly predicted the performance of other group members. Performance at the individual level, in turn, predicted career self-efficacy but only for men. Overall, we observed that social dynamics were powerful among both EVE conditions and that these processes influenced learner performance and attitudinal outcomes. We conclude with recommendations for implementing career-oriented EVEs in skills training and implications for STEM workforce development.
Designing and Communicating Ontologies Visually

In this paper we discuss ways to support the Ontology Engineering process by providing a Visual Language forOWL 2 ontologies. We examine eight proposals for an ontology visual language stemming from Semantic Web research, including our own Visual Ontology Language that has evolved from our MOT semi-formal visual language. The MOT-OWL visual language implements the visual typing of ontology entities and links, and also the use of polysemy between these elements to increase the readability and manageability of the visual models. Then we compare this visual notation and other Visual Ontology Languages using principles from the Physics of Notation Theory. This comparison helps us identify improvements that are being implemented in our more recent visual language, G-OWL, based on a systematic meta-modeling effort.
Method to Encrypt Numbers in Binary System

This paper is an introduction to number cryptography. We use base-2 numerical systems and position properties to create a method which can convert numbers from binary to decimal and from decimal to binary in different ways depending of the integer used.
Bayesian Quadrature on Riemannian Data Manifolds

Riemannian manifolds provide a principled way to model nonlinear geometric structure inherent in data. A Riemannian metric on said manifolds determines geometry-aware shortest paths and provides the means to define statistical models accordingly. However, these operations are typically computationally demanding. To ease this computational burden, we advocate probabilistic numerical methods for Riemannian statistics. In particular, we focus on Bayesian quadrature (BQ) to numerically compute integrals over normal laws on Riemannian manifolds learned from data. In this task, each function evaluation relies on the solution of an expensive initial value problem. We show that by leveraging both prior knowledge and an active exploration scheme, BQ significantly reduces the number of required evaluations and thus outperforms Monte Carlo methods on a wide range of integration problems. As a concrete application, we highlight the merits of adopting Riemannian geometry with our proposed framework on a nonlinear dataset from molecular dynamics.
Multi-Objective Genetic Algorithm for Job Planning in Cloud Environment

In Cloud environments job planning decision need be organized in the small interval as there are a number of consumers conflicting for resources and spell. Optimization actions are required to create scheduling judgement and represent the goals of the planning procedure. Better resource utilization, higher the amount of effectively accomplished jobs and minimum wait time are the key constraints for optimization. The events are stated by means of the cost of objective purpose that measure the worth of supposed approach and associate this with dissimilar resolution. Here objective role is defined with the help of constraint and criteria. The suggested job planning methodology for Cloud computing implements Multi-Objective Genetic procedure and it is based on enhanced cost-based planning set of rules for building efficient allocation of resources to jobs. The proposed job planning set of rules minimizes resources budget and enhances the makespan. It gives better outcomes to scheduled tasks on the processor. The performance of suggested job planning methodology is evaluated by various control parameters and compared with another given algorithm. Finally, future work directions for job planning in Cloud environment have been identified.
KEMAMPUAN MENYIMPULKAN ISI BERITA PADA SISWA KELAS XI SEMESTER GENAP SMA AL AZHAR 3 BANDAR LAMPUNG TAHUN PELAJARAN 2018/2019

This study aims to determine and describe the students' ability to conclude the contents of the news for class XI SMA Al Azhar 3 Bandar Lampung Years Of 2018/2019 . The problem discussed in this study is the ability to infer news content. Through the ability to conclude the news content is expected to improve the ability of high school students in the field of reading skills.The method used in this study is descriptive quantitative method, while the technique of data collection is the assignment technique, namely by assigning students to read and menyimpukan news content. The research population used as the sample of this study reached 30 people, the determination of the number of samples in this study was using random sampling. Analyzing data in this study is to use percentages.The results of this study are as follows: the ability to deduce the contents of the news for class XI students of SMA Al Azhar 3 Bandar Lampung 2018/2019 academic year obtained an average score of 69.99. Based on the assessment criteria used in this study, a score of 69.99 is included in the sufficient criteria. The level of ability to infer news content in aspects of writing down the headlines heard is in the sufficient category with an average score of 61.66. The level of ability to infer news content in aspects of writing news content that is heard is in the sufficient category with an average percentage of 66.66%. The level of ability to infer news content in the aspect of the ability to infer news content in one paragraph is in the good category with an average score of 83.33.
Spam Mail Classification Using SVM and Genetic Algorithm

Feature selection is a problem of global combinatorial optimization in machine learning in which subsets of relevant features are selected to realize robust learning models. The inclusion of irrelevant and redundant features in the dataset can result in poor predictions and high computational overhead. Thus, selecting relevant feature subsets can help reduce the computational cost of feature measurement, speed up learning process and improve model interpretability. SVM classifier has proven inefficient in its inability to produce accurate classification results in the face of large e-mail dataset while it also consumes a lot of computational resources. In this study, a Genetic Algorithm-Support Vector Machine (GA-SVM) feature selection technique is developed to optimize the SVM classification parameters, the prediction accuracy and computation time. Spam assassin dataset was used to validate the performance of the proposed system. The hybrid GA-SVM showed remarkable improvements over SVM in terms of classification accuracy and computation time.
Support Vector Machine Approach for Examining Arabic Content Reports and Classifying the Part of Speech Tagger

Text classification is the way toward arranging archives into a predefined set of classifications in light of their substance. Arabic is profoundly inflectional and derivational language, which makes content, mining a mind-complicated task. This paper aims to deploy the Support Vector Machines (SVM) for examining Arabic content reports and classifying the Part of speech tagger (POS). This paper reviewed many papers that implemented SVM in tagging words for the Arabic language. The results show that the researcher obtained high accuracy of 99.9% to 88.1%. The results evident that SVM is suitable to deploy the Part of Speech tagging. Also, the more preprocessing task is needed for preparing the text to be ready for the next process phase.
‘이/가’와 ‘은/는’의 사용 맥락 분석 및 교수학습 내용 연구 - 한국어 교재 대화문을 중심으로 -

This study analyzes uses of ‘i/ka’, ‘eun/neun’ in dialogues of Korean textbooks and suggests contents for explicit teaching-learning. In most Korean textbooks, ‘i/ka’ and ‘eun/neun’ have been taught implicitly by understanding and practicing dialogues. However this method is not efficient because there are many cases where the two grammatical items are not exclusively realized, and in that case the degree of appropriateness differs according to the context, or the meaning of the sentence varies greatly. Therefore, whenever a new usage of ‘i/ka’, ‘eun/neun’ is presented in the dialogue, it is necessary to compare and analyze the previous learning contents and explicitly teach the usage according to the context. As one of the goals of elementary grammar learning is to learn the basic sentence structure, this study analyzed the usage context of ‘i/ka’, ‘eun/neun’ in terms of predicates and sentence structure. As an outcome, the contents for explicit teaching-learning are presented.
Research on Searchable Symmetric Encryption

Cloud computing, as a new computing paradigm, offers dynamically scalable and seemly unbounded storage and computation resources in a pay-as-you-go manner. In order to enjoy superior data services and reduce the local maintenance cost, more and more resource-constrained users prefer to outsource their data to the cloud server. However, outsourcing data to the remote server suffers from data security concerns, because the server may try to learn the information of the outsourced data as much as possible for commercial purpose. The traditional encryption technique can protect the confidentiality of users’ data, however, it leads to the loss of search ability over the encrypted data. Fortunately, searchable encryption, as a promising solution, enables the server to perform keyword-based search over encrypted data. Recently, the design of searchable encryption scheme is becoming more and more diversified, aiming to improve the practicability of the scheme. This paper focuses on the current research for searchable encryption scheme in four aspects, including single keyword search, multi-modal search, forward/ backward secure search and verifiable search. This paper mainly introduces and analyzes the representative research results, summarizes the latest research progress and key technical difficulties, and finally prospects the future research direction.