Reviewerly/exHarmony huggingface dataset:
A Literature Review of Cuckoo Search Algorithm

Optimization techniques play key role in real world problems.In many situations where decisions are taken based on random search they are used.But choosing optimal Optimization algorithm is a major challenge to the user.This paper presents a review on Cuckoo Search Algorithm which can replace many traditionally used techniques.Cuckoo search uses Levi flight strategy based on Egg laying Radius in deriving the solution specific to problem.CS optimization algorithm increases the efficiency, accuracy, and convergence rate.Different categories of the cuckoo search and several applications of the cuckoo search are reviewed.
Functional Encryption for Pattern Matching with a Hidden String

We propose a new functional encryption for pattern matching scheme with a hidden string. In functional encryption for pattern matching (FEPM), access to a message is controlled by its description and a private key that is used to evaluate the description for decryption. In particular, the description with which the ciphertext is associated is an arbitrary string w and the ciphertext can only be decrypted if its description matches the predicate of a private key which is also a string. Therefore, it provides fine-grained access control through pattern matching alone. Unlike related schemes in the literature, our scheme hides the description that the ciphertext is associated with. In many practical scenarios, the description of the ciphertext cannot be public information as an attacker may abuse the message description to identify the data owner or classify the target ciphertext before decrypting it. Moreover, some data owners may not agree to reveal any ciphertext information since it simply gives greater advantage to the adversary. In this paper, we introduce the first FEPM scheme with a hidden string, such that the adversary cannot get any information about the ciphertext from its description. The security of our scheme is formally analyzed. The proposed scheme provides both confidentiality and anonymity while maintaining its expressiveness. We prove these security properties under the interactive general Diffie–Hellman assumption (i-GDH) and a static assumption introduced in this paper.
Development of professional culture in the activities of future teachers and psychologists

The formation of professional culture of an individual is one of the most important conditions for changing the system of training qualified educational psychologists. This article aims at studying the main prerequisites for effective building of professional culture of young specialists in the field of educational psychology.The research collected data from previous researches and analyzed them using content analysis. The analysis show that future specialists’ positive motivation to work is one of the key aspects that contribute to successful development of his/her competence and professional culture. The higher educational institution is an important factor for the formation of a new value system and should use its educational potential to form the proper attitude of future educational psychologists to the future professional activity.&#x0D; &#x0D; Keywords: competence practical psychology; professional activity; student’s preparedness; teacher-psychologist; professional development.
Comparison of Program Representations on Vulnerability Detection with Graph Neural Networks

As software vulnerabilities have surged, efforts to discover them have increased. The syntactic and semantic information of a program is required to detect vulnerabilities. Each information can be represented as a graph, such as Abstract Syntax Tree and Program Dependency Graph. In this paper, the program representations were extracted using various static analysis tools, including Clang Static Analyzer, Joern, and SVF, and compared using Graph Neural Networks to select the appropriate representations for vulnerability detection in C/C++. From the comparison, PDG shows the best performance among the multiple representations. This result indicates a suitable program representation and a tool for vulnerability detection that can be utilized in research utilizing graph neural networks.
OADA: An Online Data Augmentation Method for Raw Histopathology Images

Deep learning-based automatic medical diagnosis is intensively studied in recent years. Abundant clinical raw records can be utilized, but we demonstrate that mixed and unknown magnification scales and staining conditions of raw histopathology images greatly hinder many successful deep models in this task. To address this problem, this paper proposes an Online Adaptive Data Augmentation method (OADA). In each training epoch, OADA adaptively selects base images and determines the personalized augmentation size of each image based on the current training status. The chosen images are augmented to update the training set. Extensive experiments show that OADA-empowered deep models obtain significant improvement compared to their bare versions, and OADA outperforms a suite of data augmentation baselines and state-of-the-art competitors.
EFFECTIVENESS OF DISTANCE LEARNING DURING COVID-19 PANDEMIC FROM EDUCATIONAL PROCESS PARTICIPANTS’ VIEWPOINT

The educational system of Ukraine, like those of most countries in the world, was not ready for the long-term changes caused by the COVID-19 pandemic. The survey of participants of the educational process revealed that 25% of secondary school students did not start the educational process at all for various reasons, which indicates the need to rethink and restructure the educational process based on new organizational and methodological approaches. The article presents the results of a study of the data of the survey “Challenges of distance learning” conducted by the Institute of Gifted Child of the National Academy of Pedagogical Sciences of Ukraine from 25.05.2020 to 10.08.2020 on determining the opinion of participants of the educational process in conditions of the COVID-19 pandemic. The purpose of the study was to determine the features of distance learning and identify the disadvantages and advantages of distance education for individual participants (parents, students, educators). The research used statistical methods: summarizing and grouping data and visualization methods for their presentation, the method of testing hypotheses using the chi-square criterion, as well as analysis of variance. Respondents evaluated the effectiveness of forms and means of distance learning for different age groups of secondary school students, in particular, the importance for the educational institution of a unified learning platform, resources, partnership, individual choice of forms and methods of distance learning by the teacher, reasonable workload, weekly planning. Educators evaluate the existing measures to improve the effectiveness of distance learning higher than students and parents. In general, parents' assessment of the effectiveness of remote forms and means is the lowest. The study identified gender characteristics of views on the quality of distance learning. In addition, the survey participants, based on their experience, outlined a vision for the future of the educational system.
Creating Effective Virtual Reality Learning Experiences: Lessons Learned

VR is an effective tool that can be used to augment skill-based learning by fully immersing the user in the virtual environment with a hands-on experience. However, there are certain aspects to consider when using VR for training.
Certifying derivation of state machines from coroutines

One of the biggest implementation challenges in security-critical network protocols is nested state machines. In practice today, state machines are either implemented manually at a low level, risking bugs easily missed in audits; or are written using higher-level abstractions like threads, depending on runtime systems that may sacrifice performance or compatibility with the ABIs of important platforms (e.g., resource-constrained IoT systems). We present a compiler-based technique allowing the best of both worlds, coding protocols in a natural high-level form, using freer monads to represent nested coroutines , which are then compiled automatically to lower-level code with explicit state. In fact, our compiler is implemented as a tactic in the Coq proof assistant, structuring compilation as search for an equivalence proof for source and target programs. As such, it is straightforwardly (and soundly) extensible with new hints, for instance regarding new data structures that may be used for efficient lookup of coroutines. As a case study, we implemented a core of TLS sufficient for use with popular Web browsers, and our experiments show that the extracted Haskell code achieves reasonable performance.
The Effectiveness of a Virtual Reality Marketing Video on the People Desire to Buy a Product

Virtual Reality technology can provide new experiences and different points of view of activities, events, or products for the users. In line with advances from VR technology, YouTube initiates to support the spread of VR videos by creating a VR feature on their platform. A hundred videos about a dangerous activity, Horror activity, and Marketing video of software or a movie product are found on the YouTube platform. Meanwhile, it is still not yet known how the effectiveness of an advertisement using VR video via the YouTube platform on the people desires to buy a product, especially in Indonesia, which then became the purpose of this study. In carrying out this study, a quantitative study was used by creating a digital questionnaire and distributed it with Google Forms. Then the data obtained will be processed by the respondent demographics and the 4 types of analysis, such as the Validity analysis, the Reliability analysis, the Ranking of VR applications on product promotions, and the Correlation analysis. Afterward, the study found that the B1 and B2 variables refer to Advertising, making it easy for us to understand the product has the most correlation coefficient. Moreover, 80% of the respondents stated that they like the VR advertisement product. It means that people are interested in trying and feel something new in the way VR technology is given to them. Ultimately, the respondents agree that VR advertising has informed them well about the product.
The OpenQKD Testbed in Berlin

The Berlin OpenQKD Testbed demonstrates the integration of QKD technology into a field installed network infrastructure using a PQC secured key management system and hybrid key exchange protocols to secure communication applications.
Student engagement through personal pronouns in secondary school and university

Personal pronouns are a linguistic device that is used to engage students at various educational levels. Personal pronouns are multifunctional and their functions range from inclusion to exclusion and include establishing rapport with students. In this chapter we compare the use of personal pronouns at university and secondary school levels. Our previous study (Yeo & Ting 2014) showed the frequent use of you in lecture introductions (2170 instances in the 37373-word corpus) to acknowledge the presence of students. The arts lecturers were more inclusive than the science lecturers reflected in the less frequent use of exclusive-we and we for one as well as the frequent use of you-generalized. We have also compiled and analyzed a 43511-word corpus from 15 English lessons in three Malaysian secondary schools. This corpus yielded 2019 instances of personal pronoun use. The results showed that you was the most frequently used personal pronoun followed by we and I. You-audience was used more than you-generalized and the main function was to give instructions to students. The teachers appeared to be more directive than the lecturers in the previous study who sometimes used the inclusive-we for you and I and we for I to lessen the social distance with students indicating that the discourse functions of personal pronouns vary with the educational context. The findings suggest that educators can be alerted to the versatility of personal pronouns for example for engaging students in the lesson and for asserting authority in the subject matter.
Mathematical modeling of drive transitive process with linear change in control input

The paper researches into dynamic parameters of transitive processes in electrical drive of technological equipment in acceleration mode given changes in control input under law of linearity.Analysis of two-mass dynamic model allows for solutions of differential equations describing three stages in the drive acceleration mode.Dynamic and static components of drive errors are discussed in relation to its velocity as being conditioned on the moment of load, the total moment of the drive inertia, stiffness ratio of static parameter and pre-defined programmed acceleration.
HPCGCN: A Predictive Framework on High Performance Computing Cluster Log Data Using Graph Convolutional Networks

This paper presents a novel use case of Graph Convolutional Network (GCN) learning representations for predictive data mining, specifically from user/task data in the domain of high-performance computing (HPC). It outlines an approach based on a coalesced data set: logs from the Slurm workload manager, joined with user experience survey data from computational cluster users. We introduce a new method of constructing a heterogeneous unweighted HPC graph consisting of multiple typed nodes after revealing the manifold relations between the nodes. The GCN structure used here supports two tasks: i) determining whether a job will complete or fail and ii) predicting memory and CPU requirements by training the GCN semi-supervised classification model and regression models on the generated graph. The graph is partitioned into partitions using graph clustering. We conducted classification and regression experiments using the proposed framework on our HPC log dataset and evaluated predictions by our trained models against baselines using test score, F1-score, precision, recall for classification, and R1 score for regression, showing that our framework achieves significant improvements.
Thoughts on the application of quantum-based artificial intelligence for military purposes

In today's information-based society, computer technology is developing rapidly, and thus the speed of operations is increasing exponentially. Fast and dynamic information processing has become one of the basic needs of countries and their organizations. Furthermore, higher levels of info-communication technologies can also be detected. In the field of computing, quantum computers are becoming more and more popular, and their current development process is particularly intense, which in turn has triggered a kind of competition between the countries interested in the subject. The estimated future usability of quantum computers for humans is currently being outlined. Regarding to the new computing capabilities, quantum informatics is closely related to artificial intelligence and military forces can gain unprecedented information superiority through the development.
Utilization of Landsat-8 OLI/TIRS Imagery for Geologic Mapping of El Sid and Fawakhir Ancient Gold Mines Area, Central Eastern Desert of Egypt

The base and precious metals and industrial minerals which are a focus of interest for mining companies, do not attract attention unless clear exploration targets are apparent from geological mapping or reconnaissance surveys.Therefore, the development of reconnaissance methods to assist in locating these lower value deposits is needed.This paper examines the use of modern Landsat 8 remote sensing imagery as rapid, low-cost aims to explore and revising the previous works in the ancient gold mines El Sid and Fawakhir in the Fawakhir area as a model to use in the Golden Triangular Project (Qena-Safaga-Quseir) and similar arid areas.Landsat 8 Operational Land Imager (OLI) data on visible (VIS), near-infrared (NIR) and Thermal Infrared (TIR) bands have been enhanced using image fusion with a high spatial resolution panchromatic band of the same data set.A data fusion technique is presented for geological mapping in arid environments, Hue, Saturation, and Value (HSV), Principal Component Analysis (PCA) is applied to the fused (HSV) image for mapping rocks of the Fawakhir area in the Central Eastern Desert (CED) of Egypt.A revised geological map of the study area is proposed based on the interpretation of Landsat 8 image results, previous works, spectrometry measurements and field confirmation.Also, establish a distribution map for the N-S and NNW image-lineament that previously mentioned by many authors as expected gold-bearing trends.It is concluded that the proposed methods have great potential for geological mapping in the arid regions and can be generalized in the Golden Triangular Project.
Vision based 3D Gesture Tracking using Augmented Reality and Virtual Reality for Improved Learning Applications

3D gesture recognition and tracking based augmented reality and virtual reality have become a big interest of research because of advanced technology in smartphones.By interacting with 3D objects in augmented reality and virtual reality, users get better understanding of the subject matter where there have been requirements of customized hardware support and overall experimental performance needs to be satisfactory.This research investigates currently various vision based 3D gestural architectures for augmented reality and virtual reality.The core goal of this research is to present analysis on methods, frameworks followed by experimental performance on recognition and tracking of hand gestures and interaction with virtual objects in smartphones.This research categorized experimental evaluation for existing methods in three categories, i.e. hardware requirement, documentation before actual experiment and datasets.These categories are expected to ensure robust validation for practical usage of 3D gesture tracking based on augmented reality and virtual reality.Hardware set up includes types of gloves, fingerprint and types of sensors.Documentation includes classroom setup manuals, questionaries, recordings for improvement and stress test application.Last part of experimental section includes usage of various datasets by existing research.The overall comprehensive illustration of various methods, frameworks and experimental aspects can significantly contribute to 3D gesture recognition and tracking based augmented reality and virtual reality.
Oblivious Online Contention Resolution Schemes

Previous chapter Next chapter Full AccessProceedings Symposium on Simplicity in Algorithms (SOSA)Oblivious Online Contention Resolution SchemesHu Fu, Pinyan Lu, Zhihao Gavin Tang, Abner Turkieltaub, Hongxun Wu, Jinzhao Wu, and Qianfan ZhangHu Fu, Pinyan Lu, Zhihao Gavin Tang, Abner Turkieltaub, Hongxun Wu, Jinzhao Wu, and Qianfan Zhangpp.268 - 278Chapter DOI:https://doi.org/10.1137/1.9781611977066.20PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract Contention resolution schemes (CRSs) are powerful tools for obtaining “ex post feasible” solutions from candidates that are drawn from “ex ante feasible” distributions. Online contention resolution schemes (OCRSs), the online version, have found myriad applications in Bayesian and stochastic problems, such as prophet inequalities and stochastic probing. When the ex ante distribution is unknown, it was unknown whether good CRSs/OCRSs exist with no sample (in which case the scheme is oblivious) or few samples from the distribution. In this work, we give a simple -selectable oblivious single item OCRS by mixing two simple schemes evenly, and show, via a Ramsey theory argument, that it is optimal. On the negative side, we show that no CRS or OCRS with O(1) samples can be Ω(1)-balanced/selectable (i.e., preserve every active candidate with a constant probability) for graphic or transversal matroids. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-706-6 https://doi.org/10.1137/1.9781611977066Book Series Name:ProceedingsBook Code:SOSA22Book Pages:v + 320
Offline: The generation of ghosts

What happened to our ambition for a different, better world? One has to go back to World War 2 to find a time when our species faced a catastrophe on the scale of this COVID-19 pandemic. In the early 1940s, there were some observers of the mounting global chaos who recognised a need to create a new world order. In England, two writers stood out, and their far-reaching visions contrast sharply with the surprising lack of aspiration shown by my generation today.
Polarity Detection of Dialectal Arabic using Deep Learning Models

With the evolution of a new era of technology and social media networks, as well as an increase in Arabs sharing their point of view, it became necessary that this research be conducted.Sentiment analysis is concerned with identifying and extracting opinionated phrases from reviews or tweets.Specifically, to determine whether a given tweet is positive, negative, or neutral.Dialectical Arabic poses difficulties for sentiment analysis.In this paper, four deep learning models are presented, to be specific convolution neural networks (CNN), long short-term memory (LSTM), a hybrid of (CNN-LSTM), and Bidirectional LSTMs (BiLSTM), to determine the tweets polarities written in dialectal Arabic.The performance of the four models is validated on the used corpus with the use of word embedding and applying the (k-Fold Cross-Validation) method.The results show that CNN outperforms the others achieving an accuracy of 99.65%.
An Evaluation of the Psychological Factors influencing the Students’ Anxiety in Speaking English

Speaking is a productive skill that can be directly observed by considering several aspects. It can trigger the students’ anxiety as a psychological factor to communicate foreign language with others. This case has become a unique phenomenon to be analysed because anxiety has a relevance with foreign language abilities. This study aims to evaluate the psychological factor influencing the students’ anxiety in speaking English by using a qualitative approach. The data were collected by using observations, open-ended questionnaires, and interviews. There were 17 students in the ninth-grade of junior high school in Brebes Regency participating in this research. Three major phases of data analysis, namely data reduction, display, and conclusion drawing established to analyse the data. The researchers found three factors triggering the students’ anxiety in speaking English, namely communication apprehension, test-anxiety, and fear of negative evaluation which were influenced by the situation-specific anxiety. The situation could represent an uncomfortable experience emotionally and physically for some students to speak English in the class. The students felt anxious, frustrated, fearful, nervous, worried when they were unable to speak English. It made the students afraid of making mistakes and like to underestimate their abilities so that this prevents them from doing verbal activities. Therefore, this research discusses waysreduce the specific psychological factors that cause students’ anxiety in speaking English. This result can be used as guidance in managing learning conditions, learning materials, and learning strategies to deal with students’ anxiety in learning English. The teacher can use this research as a reference for analyzing the students’ anxiety symptoms during learning English in order to increase the students’ motivation and confidence in speaking performance.&#x0D;