Reviewerly/exHarmony huggingface dataset:
Comparison of Deep-Learning Training Techniques for Person’s Social Convention Estimation Model

The difference in person's social convention, like culture, nationality, age, or gender, makes the consumer decision-making style different and unique. Various businesses use this information to analyze and assist them in making the activities or the advertisement media consistent with the target customer. This research focuses on the estimation method that uses machine learning techniques to identify individuals' social conventions, such as gender and age. Here, five training techniques are compared. The results show significant results that can be used in age and gender estimation. This information can be used in the application to estimate the target customer decision-making style.
Intelligent Framework for Sentiment Analysis of Movie Reviews - A Comprehensive Survey

Abstract—Sentimental research, also known as Opinion mining, is concerned with evaluating attitudes and classify opinions based on reviews or comments. SA has emerged as a leading research area of Natural Language Processing (NLP). The role of Sentiment Analysis (SA) is to categorize people's views as positive or negative based on a specific statement or evaluation. Review and opinions play a significant part in determining the degree of happiness of consumers with a specific organization. Since human perceptions help to improve product quality, and the popularity or loss of a movie is determined by its ratings, there is an increased demand and need for building a good sentiment analysis model that classifies movie reviews.The research article offers a study of emerging methods for categorizing sentimental analysis in general, as well as a summary of the key research problems posed in recent domain like sarcasm detection. We discovered that machine learning-based methods, such as supervised learning, unsupervised learning techniques, and Lexicon-based techniques, are the most commonly utilized. Research on different data sources has been supported using various algorithms such as Naive Bayes, SVM, and Ensemble classifier.
A COMPARATIVE STUDY OF USING CLASSWIDE PEER TUTORING TECHNIQUE AND ‎STUDENT TEAM ‎ ACHIEVEMENT DEVISION TECHNIQUE IN ‎ TEACHING READING COMPREHENSION AT STATE SENIOR HIGH SCHOOL ‎ ‎1 TUALANG‎

The purpose of this study was to explore which strategy that required a teacher for a better learning process in improving students’ reading comprehension in the eleventh grade at state senior high school Tualang. It was done based on experimental design which focused on the quantitative research group. A group were taken as experimental groups and a group as the comparison group. The sample consisted of 60 students that were taken from the eleventh grade at state senir high school Tualang which were comprised of 30 students from XI-4class for this experimental group 1 (Classwide Peer Tutoring Technique), 30 students from XI-5 class for this experimental group 2 (Student Team Achievement Technique).Observation sheets and reading comprehension tests were used in the study. There are 40 items of multiple choice questions used for the pre-test and post-test. To analyze the data, independent sample t-test were calculated by using SPSS 20 with a significant probability of Ho was accepted if P&lt;0.05 or there was no significant effect after giving the treatments, Ha was accepted if P&gt;0.05 or there was no significant effect after giving the treatments. Classwide Peer Tutoring Technique got the effect size or eta-squared as follows: Eta-squared = 0.84x 100% = 84%. Student Team Achievement Technique got the effect size or eta-squared as follows: Eta-squared = 0.91 x 100% = 91%. The highest effect was from Student Team Achievement Technique, but the two classes did not differ significantly. Therefore, the two strategies could improve the students’ reading comprehension.
Intelligent TRIPLE DES with N Round Based on Genetic Algorithm

This work presents an approach for the applying Triple DES (TRIPLE DES) based on using genetic algorithm by adding intelligent feature for TRIPLE DES with N round for genetic algorithm. Encapsulated cipher file with special program which send an acknowledgment to a sender to know who decipher or broken to crash it , Thus it is considered as the initial step to improve privacy. The outcome for proposed system gives a good indication that it is a promising system compared with other type of cipher system.
Inter-operability and Orchestration in Heterogeneous Cloud/Edge Resources: The ACCORDION Vision.

This paper introduces the ACCORDION framework, a novel framework for the management of the cloud-edge continuum, targeting the support of NextGen applications with strong QoE requirements. The framework addresses the need for an ever expanding and heterogeneous pool of edge resources in order to deliver the promise of ubiquitous computing to the NextGen application clients. This endeavor entails two main technical challenges. First, to assure interoperability when incorporating heterogeneous infrastructures in the pool. Second, the management of the largely dynamic pool of edge nodes. The optimization of the delivered QoE stands as the core driver to this work, therefore its monitoring and modelling comprises a core part of the conducted work. The paper discusses the main pillars that support the ACCORDION vision, and provide a description of the three planned use case that are planned to demonstrate ACCORDION capabilities.
A Systematic Literature Review on Phishing and Anti-Phishing Techniques

Phishing is the number one threat in the world of internet. Phishing attacks are from decades and with each passing year it is becoming a major problem for internet users as attackers are coming with unique and creative ideas to breach the security. In this paper, different types of phishing and anti-phishing techniques are presented. For this purpose, the Systematic Literature Review(SLR) approach is followed to critically define the proposed research questions. At first 80 articles were extracted from different repositories. These articles were then filtered out using Tollgate Approach to find out different types of phishing and anti-phishing techniques. Research study evaluated that spear phishing, Email Spoofing, Email Manipulation and phone phishing are the most commonly used phishing techniques. On the other hand, according to the SLR, machine learning approaches have the highest accuracy of preventing and detecting phishing attacks among all other anti-phishing approaches.
An Improvement Of Least Square - Twin Support Vector Machine

n binary classification problems, two classes of data seem tobe different from each other. It is expected to be more complicated dueto the number of data points of clusters in each class also be different.Traditional algorithms as Support Vector Machine (SVM), Twin Support Vector Machine (TSVM), or Least Square Twin Support VectorMachine (LSTSVM) cannot sufficiently exploit information about thenumber of data points in each cluster of the data. Which may be effectto the accuracy of classification problems. In this paper, we proposes anew Improved Least Square - Support Vector Machine (called ILS-SVM)for binary classification problems with a class-vs-clusters strategy. Experimental results show that the ILS-SVM training time is faster thanthat of TSVM, and the ILS-SVM accuracy is better than LSTSVM andTSVM in most cases.
Automatic Tool Generation for Diagnosing Blood Anemia

The development of new computer software techniques and erudition systems must emerge the creation of newsystems in several fields especially in the field of Bio-medical sciences, where new data frameworks have been madeto speak to innovative and initiating capacities to the degree application and uses are concerned. Sketch and carryingout of a computer-based erudition operation by appropriating a detailed line of attack are bestowed for enhancing theinterpretation of blood anaemia. This approach incorporates a lot of strategies and procedures to investigate bloodmisdirection images. Basically, a proficient strategy utilizing the picture handling procedure (picture upgrade,division, and highlight taking out) has been developed which can be utilized to examine blood spread picturesshouted with photomicroscope. Generally, blood spread imagery includes red blood cells, white blood cells, andplatelets. This system is used to classify the abnormal cells present in the blood sample. The framework checks thegeneral blood platelets and figures the level of various sorts of tallied anomalous cells like macrocyte, target cell,howel-jolley body, sickle cell, elliptocyte, tear, spherocyte, etc. The presence of a few strange sorts and the relatedrates show the kind of blood anaemia. The continuation of this strategy has a precision of 83%.
Percepção dos bibliotecários sobre a aplicabilidade das cinco leis de Ranganathan ao contexto da gestão da informação

It presents the results of the study whose general objective is to investigate the applicability of the five laws of Ranganathan and its influence on information management in libraries, in the city of Fortaleza. The research has an exploratory nature, and the data was collected through a questionnaire, in two methods of application: in locus, by the researcher and also sent electronically. Ten librarians, who work in public, university, specialized and school libraries participated in the empirical study. The results show that, in general, librarians have knowledge about the aforementioned laws and their applicability in information management, particularly the provision of informational products and services and the fulfillment of library objectives. Also, it became clear that, this understanding is more noticeable for those who have less time performing as professionals in market. In addition, most librarians point out that, the laws are intrinsic to the activities carried out within the libraries. We conclude that the laws, although elaborate and published in 1931, still reverberate in the performance of the librarians who participated in there search. This fact shows that understanding these laws can serve as a basis for optimizing services, contributing to innovation and promoting the quality of access to information, in the context the community where the libraries are inserted.
Linked Data for the Perplexed Librarian

Linked data has been an increasingly prevalent topic in the galleries, libraries, archives, and museums (GLAM) community in the past decade or so. Despite its increasing popularity and importance i...
Force-Directed Layout of Order Diagrams Using Dimensional Reduction

Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.
Colliding bodies algorithm with adaptive parameter adjustment strategy

Abstract Colliding Bodies Optimization (CBO) is a new meta-heuristic algorithm that uses collisions between objects to move to a better position so that the solution tends to be an optimal solution. Aiming at the shortcomings of CBO algorithm's poor optimization accuracy and prone to evolutionary stagnation in the later stage of iterations, this paper proposes a new Colliding Bodies Optimization algorithm with adaptive adjustment strategy. Firstly, a set of initial solutions of colliding bodies are generated by the good-point set strategy to improve the stability of the algorithm solution. Secondly, we adjust the linear strategy of the control parameters to a nonlinear strategy and combine it with the fitness value to form an adaptive parameter adjustment strategy. Finally, in order to make the algorithm escape from the local optimal, a mutation operation is performed on the position of the object. In order to test the effectiveness of the proposed algorithm, experiments were conducted on 23 benchmark functions with it and the comparison algorithm. The experimental results show that the performance of the proposed algorithm is better than other experimental algorithms.
NOVEL S4 FILTER APPROACH FOR COPY-MOVE VIDEO FORGERY DETECTION

Video forgery detection is a challenging task nowadays due to fake forwarding through several social media apps. Especially copy-move type of attack is broadly in practice to tamper the original contents of the video or an image. In this paper, we have proposed a novel approach for the detection of copy-move attack in passive blind videos. We have inspected the forged video for detection of two scenarios, such as a single object is copied and pasted at a single time and a single object is copied and pasted multiple times within the same video. The algorithm proposed combines two novel techniques for object detection and copy-move detection respectively. Object detection and tracking are carried out based on a new contour-based approach and a copy-move attack is implemented by a novel S4 filter-based algorithm. These filters are- Slope (S1), Span (S2), and Size (S3) Similitude Index (S4). The proposed algorithm is tested and implemented for both standard and custom dataset for the detection of copied objects by tracing the exact frame number of the forged objects. With the combining effect of both techniques, the algorithm gives faster and accurate results than the state-of-art techniques.
On-board electronic telecommunication equipment with laser illumination in integrated search systems of underwater vehicles

The intensive development of autonomous underwater robotic complexes is very important for the development of the World Ocean. One of the main problems of using underwater robotic complexes is an increase searching efficiency of underwater devices based on the integration of the capabilities of onboard radio-electronic systems of obtaining information in various physical fields. Analyzing the physical basis of the search, including the consideration of the environment of its conduct, objects, as well as detection tools, it can be noted that the result of the search operations of the same objects in the same water areas for various underwater robotic complexes depends on what means of detection they are equipped. The presence of a certain set of the technical means will specify the development of the optimal sequence of actions of the search algorithm. The creation of such algorithms in relation to the task of increasing the search potential of underwater robotics will determine the direction of the research that ensures the formation of an optimal system of underwater search. Efficient use of search resources substantiates the conclusion that radio-electronic means of submersibles forming the system of underwater search, include the number of devices functionally interconnected for its effective conduct. The specified combination is aimed at the formation of the so-called integrated search system, which provides an exchange of information between different channels of searching devices about all objects detected. The article provides proposals for the creation of integrated search systems taking into account practical experiments and experience in designing underwater vehicles capable to implement the optimal system of underwater search using laser technologies.
A Glance at Dark-web - The Underground Market

According to Hindustan Times newspaper, the government replied to RTI (Right to Information) that around Rs. 615.39 crore was drawn off in more than 1.17 lakh registered cases of credit and debit card frauds in last decade. In separate incident in the parliament, the reply by the Indian finance minister quoted Rs. 129 crore was lost in 21,041 cases reported under Card/Internet in just last three months of the year 2019. In another astonishing revelation, the bulk database of debit cards and credit cards on Dark web has been surfaced, only 1% of card listed for sale were of Colombian banks and 98 % were of Indian bank (Group IB, 2019). Literature relating this research area focuses mainly on the organization and structure of the Dark web forums. Furthermore, studies on dark-web forums & market are usually based on literature review, expert interviews, or data from forums/market that have already been shut down. This paper provides an insight into active market places with an active trading of illicit products. The data collected was analyzed using mixed method approach. Lastly, the findings are discussed using information obtained after data analysis for dark-web Market growth and the presence of working reputation systems followed by researcher’s conclusion.
Research on Safety Protection Scheme of Distribution Network Automation

In order to meet the requirements of automatic security protection in smart grid, a security protection scheme for distribution automation based on security encryption chip is proposed. Without affecting the normal operation of the distribution terminal, the characteristics of distribution automation are added, such as wide distribution range and outdoor operation. The LKT4305-GM security chip is used, the security operating system is adopted, the function of sm1, sm2, sm3, sm4 state secret algorithm and the PKI system are realized. PKI power dispatching digital certificate uses digital certificate authentication technology, and based on the encryption technology of national commercial cipher algorithm, it realizes the two-way identity authentication between distribution station and distribution terminal.
Enhanced Text and Image Security Using Combination of DCT Steganography, XOR Embedding and Arnold Transform

In this paper present the enhanced text and image security using the combination of hybrid enhanced model using the DCT Steganography, XOR embedding and Arnold transform techniques. In this first hide the text data into the secret image using the DCT Steganography technique and get the stego image. After getting the stego image embedded Stego image with cover image using the XOR embedding technique and get the embedded image. Now after getting the embedded image calculate the MSE and PSNR values. For better hiding low MSE and high PSNR value is required. In proposed work get the low MSE and high PSNR value then previous work done. After getting the MSE and PSNR value apply the Arnold transform on the embedded image and get the encrypted image that is totally differ than all the images. After getting the embedded image calculate the entropy of the proposed technique. Using proposed technique multiple layer of security provides to the text data and secret image and also provide the security of the cover image using the Arnold transform.
Creating a Multilingual Chatbot

Dialogflow supports many languages; it is possible to create multilingual chatbots. When you create a Dialogflow agent, you have to pick your default language, for example, English. Afterward, you can add other languages.
Research on Dynamic Monitoring of Third Language Teaching Quality Based on Big Data

The traditional teaching quality monitoring in colleges and universities has drawbacks such as long data collection time, difficulty in summarizing, feedback lag, one-sided evaluation, lack of systematization and integrity, especially the third language teaching has been hovering in the "gray zone" of monitoring due to its own characteristics. With the concept of "Internet plus" extending in the field of higher education, big data technology can be used to choose the appropriate teaching cloud platform, collect and analyze the data generated in the teaching process comprehensively. It can also be used to recommend personalized learning sources by capturing the click rate, retention time, stay location and learning mood of learners; to set up questionnaires for different evaluation objects, customize diversified indicators of teaching and learning evaluation; to form an efficient feedback and improvement mechanism among students, teachers, supervisors, secondary colleges and teaching management institutions, which can bring a new perspective for college third language teaching, and also provide a new path for teaching quality monitoring.
Sistem Pakar Deteksi Minat Untuk Pemilihan Jenjang Karir Menggunakan Metode Certainty Factor

Interests have an important role in the career path because interests will affect a person's performance, passion and abilities during their educational studies. The problem that occurs is that based on a survey conducted by the Indonesian Career Center Network, it was found that 87% of students in Indonesia felt that they were wrong in deciding which major they were taking. This problem is because the majors they take do not match their interests. This problem can be prevented by detecting interest early on so that career paths can be planned appropriately. This study aims to provide a solution to this problem by building an interest detection expert system to support career path selection. Certainty Factor methods are used in determining the output of the expert system to be built with the adaptation of the interest test tool, called RIASEC. Testing is done by comparing the system output results with expert consultation. The test results showed that the expert detection system was able to answer the interest with an accuracy of 93%. Based on the test results, the solution in interest detection expert system could be used as a reference assessment in planning career path choices
MENINGKATKAN KEAKTIFAN BELAJAR SISWA KELAS VI PADA MATA PELAJARAN IPS DENGAN MENGGUNAKAN MEDIA PETA DAN GLOBE DI SD NEGERI NAPUNGBIRI PANTE

The purpose of this study is to improve that the use of map and globe media can improve the learning activeness of Grade VI students at SD Negeri Napungbiri Pante in the academic year 2017/2018. Data collection techniques using the method of interviews, observation, field notes and documentation. Based on the results of the study showed an increase in the activeness and learning outcomes of students in social studies learning. This can be seen from the activity of students in each cycle, the initial conditions were 32.72%, increased by 53.63% in the first cycle of the first cycle, increased by 82.72% in the first cycle of the second round. Then in Cycle II also experienced an increase in the first round of 86.16%, in the second round it increased 92.45%. And learning outcomes in the initial conditions 29.41% experienced an increase of 47.05% in the first cycle of the first round and 70.58% in the first cycle of the second round. Then in the first cycle of the second cycle 82.35%, increased to 94.11% in the second cycle of the second round. Thus, from this study, it can be concluded that the use of map and globe media can increase the activeness and learning outcomes of students in social studies learning in the sixth grade students of SD Negeri Napungbiri in the 2017/2018 Academic Year.