Reviewerly/exHarmony huggingface dataset:
Modern Art Interactive Design Based on Artificial Intelligence Technology

To improve the effect of modern art design, this study presents a camera pose estimation algorithm based on the least feature points of quaternion. Moreover, this study detects and matches the feature points of the camera image and establishes a system of formulas through the rigid constraints of the feature points, thereby constructing an eigenvalue problem to solve the camera pose. In addition, this study combines artificial intelligence technology to construct the modern art interactive design system and structure the system function structure. Finally, this study analyzes the logical structure and spatial structure of the system and uses the design to analyze the performance of the modern art interaction design model proposed in this study. Through experimental research, it can be known that the modern art interactive design system based on artificial intelligence technology proposed in this study can basically meet the artistic design needs of the new media era.
Generation of Gradient-Preserving Images allowing HOG Feature Extraction

In this paper, we propose a method for generating visually protected images, referred to as gradient-preserving images. The protected images allow us to directly extract Histogram-of-Oriented-Gradients (HOG) features for privacy-preserving machine learning. In an experiment, HOG features extracted from gradient-preserving images are applied to a face recognition algorithm to demonstrate the effectiveness of the proposed method.
Implementation of Web Application for Disease Prediction Using AI

The Internet is the largest source of information created by humanity. It contains a variety of materials available in various formats such as text, audio, video and much more. In all web scraping is one way. It is a set of strategies here in which we get information from the website instead of copying the data manually. Many Web-based data extraction methods are designed to solve specific problems and work on ad-hoc domains. Various tools and technologies have been developed to facilitate Web Scraping. Unfortunately, the appropriateness and ethics of using these Web Scraping tools are often overlooked. There are hundreds of web scraping software available today, most of them designed for Java, Python and Ruby. There is also open source software and commercial software. Web-based software such as YahooPipes, Google Web Scrapers and Firefox extensions for Outwit are the best tools for beginners in web cutting. Web extraction is basically used to cut this manual extraction and editing process and provide an easy and better way to collect data from a web page and convert it into the desired format and save it to a local or archive directory. In this paper, among others the kind of scrub, we focus on those techniques that extract the content of a Web page. In particular, we use scrubbing techniques for a variety of diseases with their own symptoms and precautions.
Perception on the Adoption of WhatsApp for Learning amongst University Students’

This paper “perception on the adoption of WhatsApp for learning amongst two hundred level curriculum and instruction I students of Sokoto State University, Nigeria” was guided by three objectives, three research questions. The researcher used descriptive survey research design in the study. The researcher used qualitative method with the use of individual interview for data collection. Random sampling technique was employed to select the sample. The entire sample that was chosen is 10. The instruments used for data collection was data-blank. Coding system was applied to gather and interpreted data. The results indicated that majority of students used WhatsApp for learning, poster that WhatsApp is very easy to operate for learning and also shows that the attitude of students towards the use of WhatsApp for learning is positive. The research manifested that WhatsApp may be accepted as instructional tool in teaching and learning. Keywords: WhatsApp; Learning; Social media; E-learning.
Colorimetrical performance estimation of a reference hyperspectral microscope for color tissue slide assessment

A hyperspectral imaging microscope system (HIMS) was recently designed for color truth establishment of histological tissue slides used for whole slide imaging (WSI) systems color performances assessment. Here, we present the estimation procedure of the colorimetrical performance of the HIMS by measuring the transmittance spectra of spatially uniform neutral density and color filters and deriving the color coordinates in the CIELAB color space. The transmittance and CIELAB results are compared to reference transmittance spectra and subsequent CIELAB coordinates provided by measurement of the same region of interest with a spectroradiometer. To measure the same region of interest, the spectroradiometer is equipped with a fiber probe whose tip is set in one of the eyepiece tubes of the microscope. The CIE 1976 color difference, &#x394;E*ab, is the metric used for goodness estimation.
Predicting Student Performance using Data Mining Techniques in Libyan High Schools

Student performance in schools have been always the key factor for the teacher ability to teach and what brings good reputation to the school. Recently schools in Libya are facing an issue trying to figure out why students perform poorly in certain subjects and how can they know how they will perform next in the future in coming semesters in perspective subject. There are several methods proposed to predict the studentâ€™s performance, using data mining. This paper proposes using Math and English as key factors to predict the performance of the students. results and findings of the presented method in terms of predicting studentsâ€™ performance based on their grades in Math and English. The results are divided in to three main sections clustering analysis using k-mean algorithm, classification analysis was done using two rounds first using Gain Ratio Evaluations to find out the top attributes that used by J84 algorithm in second round of classification, and rule association analysis using A priori algorithm. Rule association analysis is applied for the clusters generate by clustering analysis to generate the rules associated with each cluster. For each section, a list of inputs is presented with the scale used for the values followed by the results of the algorithm and explanation for the finding.
GAIN-QoS: A Novel QoS Prediction Model for Edge Computing

With recent increases in the number of network-connected devices, the number of edge computing services that provide similar functions has increased. Therefore, it is important to recommend an optimal edge computing service, based on quality-of-service (QoS). However, in the real world, there is a cold-start problem in QoS data: highly sparse invocation. Therefore, it is difficult to recommend a suitable service to the user. Deep learning techniques were applied to address this problem, or context information was used to extract deep features between users and services. However, edge computing environment has not been considered in previous studies. Our goal is to predict the QoS values in real edge computing environments with improved accuracy. To this end, we propose a GAIN-QoS technique. It clusters services based on their location information, calculates the distance between services and users in each cluster, and brings the QoS values of users within a certain distance. We apply a Generative Adversarial Imputation Nets (GAIN) model and perform QoS prediction based on this reconstructed user service invocation matrix. When the density is low, GAIN-QoS shows superior performance to other techniques. In addition, the distance between the service and user slightly affects performance. Thus, compared to other methods, the proposed method can significantly improve the accuracy of QoS prediction for edge computing, which suffers from cold-start problem.
Image Processing Technology in Remote Monitoring and Intelligent Medical System

In order to study the application of image processing technology in remote monitoring and intelligent medical systems, the principle and implementation method of a remote intelligent image monitoring system based on virtual local area network is proposed; this method analyzes the key technologies to be considered in the remote realization of image monitoring, adopts advanced digital image compression coding and decoding technology and digital image transmission technology, and applies intelligent image processing and recognition technology to display, adjust, and track images; it overcomes the defects that the general monitoring system requires excessive intervention by monitoring personnel and low intelligence. After verification, the experimental results show that the proposed model can accurately and efficiently segment nonoverlapping cervical cell images, and compared with other existing models, this model has both higher segmentation accuracy and faster calculation speed. The application of multicast is still only in the laboratory or small local area network; with the further development of network technology, its application prospects will be very broad.
E-Mail Spam Filtering

Abstract: E-mail is that the most typical method of communication because of its ability to get, the rapid modification of messages and low cost of distribution. E-mail is one among the foremost secure medium for online communication and transferring data or messages through the net. An overgrowing increase in popularity, the quantity of unsolicited data has also increased rapidly. Spam causes traffic issues and bottlenecks that limit the quantity of memory and bandwidth, power and computing speed. To filtering data, different approaches exist which automatically detect and take away these untenable messages. There are several numbers of email spam filtering technique like Knowledge-based technique, Clustering techniques, Learning-based technique, Heuristic processes so on. For data filtering, various approaches exist that automatically detect and suppress these indefensible messages. This paper illustrates a survey of various existing email spam filtering system regarding Machine Learning Technique (MLT) like Naive Bayes, SVM, K-Nearest Neighbor, Bayes Additive Regression, KNN Tree, and rules. Henceforth here we give the classification, evaluation and comparison of some email spam filtering system and summarize the scenario regarding accuracy rate of various existing approaches. Keywords: e-mail spam, unsolicited bulk email, spam filtering methods.
Quantum Support Vector Regression for Disability Insurance

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The modeling of logistic disability inception probabilities is formulated as a support vector regression problem. Using a quantum feature map, the data are mapped to quantum states belonging to a quantum feature space, where the associated kernel is determined by the inner product between the quantum states. This quantum kernel can be efficiently estimated on a quantum computer. We conduct experiments on the IBM Yorktown quantum computer, fitting the model to disability inception data from a Swedish insurance company.
Personality Development: Reset In The Context Of Digital Reality

The paper analyzes personality development in the context of digital reality.It is emphasized that personal spiritual domain is being transformed; among threats to spiritual security there are several factors: globalization trends in culture, religious ecumenism, transnational confessions previously absent from the Russian society, bringing changes to personal identity.New features of communicative interactions are noted between elder and younger generations, manifesting in psychological communication barriers due to opposing attitudes to virtual reality and worldview.An important role of teachers is stated for every level of education, as they serve as tutors and navigators in the vast sea of information.A significant role of religion is identified in formation of the cultural component of personal communicative behavior in the context of influence from digital technologies.Formative and developmental features are analyzed for communicative behavioral models of non-standard situations, together with changes in personal consciousness that reset personal spiritual world and raising great concerns due to threats to spiritual security.It is emphasized that there is a need to develop along with the fast-changing world, taking into account both negative and positive influences of digital technologies onto intellectual, spiritual, emotional, volitional and behavioral domains of a person.A conclusion has been drawn that immersion into digital environment facilitates loss of personal individuality, changes in behavioral style following certain algorithms, estrangement of mental world, loss of freedom of choice.
The body as the border: A new era

»Der Korper als Grenze: Eine neue Ara«. COVID-19 has reminded us of the significance of borders. In 1989, with the fall of the Berlin Wall, many predicted that sealed gates would soon become relics of a bygone era. Today, we find a different reality. Instead of disappearing, borders are transforming. In this article, we build upon the shifting border logic to explore how responses to the global pandemic have accelerated processes of detachment of mobility control from a fixed territorial marker. From global travel bans to mandating pre-arrival proof of a negative test result taken within 48 or 72 hours prior to departure to requiring digital registration of a passenger’s travel history to enforcing strict post-arrival mandatory quarantine orders that arrest mobility, the shifting border paradigm has provided a template for policymakers to respond to a mounting global crisis. In addition to regulating movement across international borders and within countries, we trace the surprising return of subnational and inter-regional division lines in managing mobility, the erosion of the once taken for granted right to return to one’s home country, and the spatial and legal techniques used to block refugees from reaching terra firma during the pandemic. Next, we critically evaluate the authorization given under emergency regulations to deploy novel biometric and AI technologies, big data, and predictive algorithms to surveil moving bodies at real time and reprimand those deemed to have breached their quarantine or related governmental emergency measures. While drastic times call for drastic measures, techniques of movement control that “scan” and trace our bodies raise serious questions about justice, fairness, and the risk of discrimination, which may well remain with us even long after the pandemic is over. © 2021, GESIS - Leibniz Institute for the Social Sciences. All rights reserved.
THE INFLUENCE OF HEALTH EDUCATION WITH A THINK PAIR SHARE LEARNING MODEL ON THE KNOWLEDGE AND ATTITUDES OF SCHOOL-AGE CHILDREN IN VEGETABLE CONSUMPTION

The school-age group of children needs to get the fulfillment of the adequacy of its main nutrients with vegetable consumption. In fact, children still find it difficult to consume vegetables in adequate quantities. The think pair share method makes children will try to think, respond to each other and help in discussions. The aim of the study was to analyze the effect of the application of health education with a think pair share learning model on the knowledge and attitudes of school-age children in vegetable consumption.The study used pre-experimental research design (one-group pre-post testdesign). The population in this research is a grade IV student at SDI KHM Noer Surabaya. Sampling with total sampling technique. Respondents in this study numbered 40 respondents. The independent variable in the study was health education with a think pair sharelearningmodel. The dependent variables in the study are knowledge and attitude. Data collection using questionnaires. The data was analyzed using the Wilcoxon Sign Rank Test statistical test for knowledge and attitudes with significance α≤0.05.The results of the Wilcoxon Sign Rank Test show that health education with a think pair share learning model can affecta child's knowledge (p=0.000) and attitude (p=0.000).The results of this study concluded that health education with a think pair share learning model can increase children's knowledge and attitudes in vegetable consumption. Further research is expected to be conducted on the action of vegetable consumption in children with a multivariate statistical approach.
Lattice-Based Group Encryption with Full Dynamicity and Message Filtering Policy

Group encryption (GE) is a fundamental privacy-preserving primitive analog of group signatures, which allows users to decrypt specific ciphertexts while hiding themselves within a crowd. Since its first birth, numerous constructions have been proposed, among which the schemes separately constructed by Libert et al. (Asiacrypt 2016) over lattices and by Nguyen et al. (PKC 2021) over coding theory are post-quantum secure. Though the last scheme, at the first time, achieved the full dynamicity (allowing group users to join or leave the group in their ease) and message filtering policy, which greatly improved the state-of-affairs of GE systems, its practical applications are still limited due to the rather complicated design, inefficiency and the weaker security (secure in the random oracle model). In return, the Libert et al.’s scheme possesses a solid security (secure in the standard model), but it lacks the previous functions and still suffers from inefficiency because of extremely using lattice trapdoors. In this work, we re-formalize the model and security definitions of fully dynamic group encryption (FDGE) that are essentially equivalent to but more succinct than Nguyen et al.’s; Then, we provide a generic and efficient zero-knowledge proof method for proving that a binary vector is non-zero over lattices, on which a proof for the Prohibitive message filtering policy in the lattice setting is first achieved (yet in a simple manner); Finally, by combining appropriate cryptographic materials and our presented zero-knowledge proofs, we achieve the first lattice-based FDGE scheme in a simpler manner, which needs no any lattice trapdoor and is proved secure in the standard model (assuming interaction during the proof phase), outweighing the existing post-quantum secure GE systems in terms of functions, efficiency and security.
Implementation of Cognitive Theory in Developing Measurement Learning Multimedia for Deaf Students

The implementation of cognitive theory in multimedia development for deaf students (students with visual channels only) would be re-examined for its effectiveness. This study aimed to develop mathematics-learning multimedia based on cognitive theory for deaf students on "measurement". This development study adopted the 4D (define, design, develop, disseminate) study design. This study focused on determining the media feasibility based on expert validation, practicality trials, and effectiveness in the first year. The subjects of this study were 4 experts (content expert, learning design expert, media expert, and linguist), 2 teachers, and 7 students. The media feasibility data were collected with validation sheets, questionnaires, and tests. Furthermore, the data were analyzed using descriptive statistics. Based on the results, the feasibility level based on material experts, media experts, learning design experts, and linguists were 93.3%, 96.7%, 90%, and 93.3%, so it could be said that the developed multimedia met validity criteria. Based totally on the consequences, the multimedia practicality test for teachers and students were 95% and 93% respectively so that it could be said that multimedia met the practical criteria and the average percentage of student material mastery was 80.1% with passing grade of 71.4% so it could be said that multimedia met the effective criteria. Since the multimedia met the valid, practical, and effective criteria, it could be said that multimedia is feasible for learning.
The Effects of Emergency Remote Teaching on Native English Instructors in a Korean University

The purpose of the study was to determine the attitudes of native-speaking English speakers at a Korean university on the impact on their teaching of moving to ERT due to the COVID-19 pandemic and if their attitudes changed between the first and second semesters of the 2020 academic year. All instructors were sent the survey in the spring and fall semesters. Eighty-eight instructors completed the survey in the spring and one hundred and six in the fall semester. The results showed that most participants in both semesters believed their students’ English ability and confidence had improved over the course. However, the participants believed student engagement, communication, collaboration, and sense of community suffered because of the necessity of ERT. In the fall semesters, the participants reported significantly higher communication with students, student engagement, student collaboration, sense of community and believed the students could express themselves in new ways more than in the spring semester. There are several reasons postulated for the relatively positive attitude of the instructors and the tentative success of the program. The first is the existing technological infrastructure in Korea and the technological proficiency of the students. A weekly professional development program mitigated the lesser technological proficiency of the teachers. In addition, the class sizes were small, making management easier. The standard curriculum was able to be used in ERT, preventing the chaos of creating an entirely new program in a very short time.
ISO 27001 INFORMATION SECURITY MANAGEMENT SYSTEM: EFFECT OF FIRM AUDITS IN EMERGING BLOCKCHAIN TECHNOLOGY

The emergence of Blockchain Technology is closely related to improving the ISO 27001 Information Security Management System for confidence in data and information security, preventing manipulation and various information risks that occur. This study examines the effect of the Audit Firm on companies that carry out ISO 27001 certification. This study uses 578 samples listed on the Indonesia Stock Exchange from 2013 – 2017. This study uses a quantitative method with OLS regression testing STATA 14. This study obtained the results that the Audit Firms have a significant influence at the 5% level on the company's decision to improve the Information Security Management System as proxied by ISO 27001. This research has an empirical contribution to developing theory, participating in developing research related to ISO 27001 certification, and assessing the existence of an Audit Firm on the improvement of the Security Management System. Corporate information in the era of blockchain technology .
PATTERNS OF ADAPTATION OF RIVER BANKS COMMUNITIES IN FACING FLOOD DISASTER IN SOUTH KALIMANTAN

South Kalimantan as an area that is blessed with a lot of river flows, this many river flows can be a blessing and can also be a disaster. As happened in January 2021, many districts in South Kalimantan were affected by floods. However, the people of South Kalimantan were able to deal with it and also minimal casualties, both in the form of property and life losses. The purpose of this study was to see the pattern of adaptation of the community in Tempakang Village and Halong Village in dealing with Floods. The results showed that the communication adaptation pattern of the riverbank community, in this case the village of Tampakang and the village of Halong, can be seen from the pattern of houses, namely houses on stilts. The adaptation process of the community in dealing with the flood disaster is closely related to the ability to predict the arrival of the rainy season which has an impact on flooding. Furthermore, the equipment and household furniture they have are generally made of light material so they are easy to move. In the village community of Tampakang, specifically accompanied by the ability to use boats and the ability to swim since childhood.