Reviewerly/exHarmony huggingface dataset:
THE CONCEPT AMERICAN DREAM: COMPARATIVE ANALYSIS

The concept AMERICAN DREAM is a mental unit, a compound set of ideas marked by national and cultural specificity. The meaning of this concept for each individual changes depending on the interpretations of the ethical and moral values of the representative of the linguaculture, the context it is used in and historical period when it is mentioned. The concept AMERICAN DREAM can have both positive and negative aspects of understanding at the same time. Complex coloring and features of the subtext may vary completely in different contexts. AMERICAN DREAM is considered to be as something unattainable. This concept is interpreted the example of an ideal life in which all luxuries are present, such as a house, family, children and pets. The concept AMERICAN DREAM is quite popular at all times. So it is often used in all cultures. Features of exact interpretation of ideal type of life differ according to the overview of the culture. If we speak about Ukrainian young respondents, they imagine AMERICAN DREAM as the way of cool life. But here we can also trace the variability of moral values and achievements of each person that will definitely influence on the thoughts about idealism. Taking into account the fact of the presence of various opportunities to built your dreams in the way you want, it is possible to notice certain common aspects in different questions in terms of discussion the meaning of importance of AMERICAN DREAM. This can be reflected and tracked with the help of definitions taken from various explanatory dictionaries, as well as in the minds of citizens themselves, that can be analyzed in the form of an anonymous questionnaire of respondents. The need to research the concept AMERICAN DREAM is that this phenomenon satisfies the most important human needs and is desired by many people of different nationalities.
TAQS: An Arabic Question Similarity System Using Transfer Learning of BERT With BiLSTM

With the rapid increase of Arabic content on the web comes an increased need for short and accurate answers to queries. Machine question answering has appeared as an important emerging field for progress in natural language processing techniques. Machine learning performance surpasses that of humans in some areas, such as natural language processing and text analysis, especially with large amounts of data. There are two main contributions of this research. First, we propose the Tawasul Arabic question similarity (TAQS) system with four Arabic semantic question similarity models using deep learning techniques. Second, we curated and used an Arabic customer service question-similarity dataset with a 44,404 entries of question–answer pairs, called “Tawasul.” For TAQS, first, we use transfer learning to extract the contextualized bidirectional encoder representations from transformers (BERT) embedding with bidirectional long short-term memory (BiLSTM) in two different ways. Specifically, we propose two architectures: the BERT contextual representation with BiLSTM (BERT-BiLSTM) and the hybrid transfer BERT contextual representation with BiLSTM (HT-BERT-BiLSTM). The hybrid transfer representation combines two transfer learning techniques. Second, we fine-tuned two versions of bidirectional encoder representations from transformers for Arabic language (AraBERT). The results show that the HT-BERT-BiLSTM with the features of Layer 12 reaches an accuracy of 94.45%, where the fine-tuning of AraBERTv2 and AraBERTv0.2 achieve 93.10% and 93.90% accuracy, respectively, for the Tawasul dataset. Our proposed TAQS model surpassed the performance of the state-of-the-art BiLSTM with SkipGram by a gain of 43.19% in accuracy.
Efficient Parallel Implementations of PIPO Block Cipher on CPU and GPU

Data encryption is essential for securely managing clients’ data in servers in data-centric ICT environment. Clients must encrypt the data before transmitting it to severs or other clients. Encrypting a large volumne of data requires a lot of time. Therefore, in order for servers and clients to not only secure but also smoothly communicate each other, the optimization of data encryption is necessary on both the server-side and the client-side. Especially, the server environment is responsible for managing/processing lots of data from clients. In this paper, we present two kinds of highly optimized PIPO cipher software in CPU and GPU environment, respectively. PIPO was proposed in ICISC’19 as a lightweight block cipher. For optimization, we take full advantage of two parallel processing technologies: AVX-related instructions in CPU and NVIDIA CUDA platform in GPU. Regarding the optimization in CPU environment, we process several plaintext blocks such as 32 and 64 blocks with the proper use of AVX2 and AVX-512 instruction sets and the proposed arithmetic techniques, respectively. Regarding the optimization on GPU environment, we propose a data alignment/data combining methods, and PTX inline assembly utilization method considering the characteristics of GPU architecture. In Intel Core i9-11900K (3.50GHz) architecture, our PIPO software utilizing AVX-2 has a performance improvement on 839.64% (resp. 985.46% [AVX-512]) compared to the existing reference code (Regarding AVX-512, this is the first PIPO software using AVX-512 instructions as far as we know). Finally, in RTX 2080Ti, our PIPO GPO software shows throughput of up to 1110.08 Gbps.
Sign Language Recognition of Selected Filipino Phrases Using LSTM Neural Network

The use of Filipino Sign Language (FSL) has contributed to the improvement of communication of deaf people; however, the majority of the population in the Philippines does not understand FSL. The study explored computer vision in obtaining the images and deep learning techniques in building the automated FSL recognition model to bridge the communication gap between the deaf community and the hearing majority. The model has been trained using LSTM neural network using the features extracted using MediaPipe Holistic from video files of Filipino phrases performed by three (3) FSL signers. The SLR system developed could recognize (15) continuous Filipino words. The model evaluation has shown an impressive result wherein the average accuracy achieved on the test set is 94%. In the experimentation conducted on 10 participants using the SLR system, the overall accuracy obtained on two trials is 72.38%, with an average prediction time of 0.3 s. Based on the analysis of the experiment results, the developed SLR system is robust, is time efficient, is signer independent, and can detect both manual and non-manual features of the gesture. More data will be collected for future directions to enable a conversational SLR system with more FSL vocabularies and sentences.
Weierstrass semigroups on the third function field in a tower attaining the Drinfeld-Vlăduţ bound

&lt;p style='text-indent:20px;'&gt;For applications in algebraic geometry codes, an explicit description of bases of the Riemann-Roch spaces over function fields is needed. We investigate the third function field &lt;inline-formula&gt;&lt;tex-math id="M1"&gt;\begin{document}$ F^{(3)} $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; in a tower of Artin-Schreier extensions described by Garcia and Stichtenoth reaching the Drinfeld-Vlăduţ bound. We construct new bases for the related Riemann-Roch spaces of &lt;inline-formula&gt;&lt;tex-math id="M2"&gt;\begin{document}$ F^{(3)} $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; and present some basic properties of divisors on a line. From the bases, we explicitly calculate the Weierstrass semigroups and pure gaps at several places on &lt;inline-formula&gt;&lt;tex-math id="M3"&gt;\begin{document}$ F^{(3)} $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;. All of these results can be viewed as a generalization of the previous work done by Voss and Høholdt (1997).&lt;/p&gt;
Pixel-Wise Fisheye Image Correction Method With Single-View Phase Target

Fisheye lens is widely employed in many practices due to its wide field-of-view (FOV) and portability. There are however serious image distortions followed up with the fisheye lens. To address the problem, this letter proposed a pixel-wise fisheye image correction method based on single-view phase target. Compared with traditional correction methods which rely on a specific fisheye model to calibrate the parameters of lens distortion, the proposed method can establish the pixel-to-pixel mapping between lens distortion and ideal undistortion without fisheye lens modeling, which is more flexible and efficient to use in practice. Given the correspondence above, the distorted image can be further mapped into the corrected image by means of interpolation. Experiments on different scenes demonstrate the feasibility and accuracy of the proposed method to correct fisheye images for lens distortion.
Positioning Cyber Security Risk Management Within a Consolidated Security Platform

The application of risk in cyber security plays an integral role as a basis of evidence for decision making as well as providing visibility over existing and potential security postures. To effectively leverage this utility, Risk Management must be integrated within a solution that unifies immediate, short-term, and longer-term functions that deliver cyber security capabilities for secure business services. Through structured language and entity models, integration of systems and processes enables automation that scale when unified holistically. Risk however is something that also integrates human motive with machine applications. It relates the management of source security data with traffic flow, asset criticality, asset owners, controls, as well as policy and predicted representations. The management of risk requires workflow design to manage decoupled governing practises and third-party involvement. What risk highlights is the importance of human-machine teaming, and it is the enhancement of that teamwork that is the focus of the case example, which elaborates on how layered architecture and interoperating mesh security solutions forms the basis of Red Piranha’s Consolidated Security Platform and holistic adoption of Cyber Security Risk Management (CSRM). The novel contribution of this paper is in outlining the adoption of CSRM within a Consolidated Security Platform (CSP). Moreover, the novel contribution here is in demonstrating how CSRM integrates multiple dimensions to leverage automation when unified in a way that can task both workflow and dataflow for its own end.
To what level have adults studied?

The attainment of upper secondary education has become a minimum requirement for navigating the modern economy and society. Young people today who leave school before completing upper secondary education not only face difficulties in the labour market, but also tend to have lower social connectedness than their higher-educated peers (OECD, 2019[1]). In most OECD and partner countries, the majority of younger adults (25-34 year-olds) have attained at least upper secondary education (). On average across OECD countries, 31% of older adults (55-64 year-olds) did not attain an upper secondary qualification, but this share falls to 15% among younger adults (25-34 year-olds). In all OECD member and partner countries except Estonia, Latvia and Lithuania, 25-34 year-olds are more likely to have completed at least an upper secondary education than 55-64 year-olds ().
Chinese Lexical Sememe Prediction Using CilinE Knowledge

Sememes are the smallest semantic units of human languages, the composition of which can represent the meaning of words. Sememes have been successfully applied to many downstream applications in natural language processing (NLP) field. Annotation of a word's sememes depends on language experts, which is both time-consuming and labor-consuming, limiting the large-scale application of sememe. Researchers have proposed some sememe prediction methods to automatically predict sememes for words. However, existing sememe prediction methods focus on information of the word itself, ignoring the expert-annotated knowledge bases which indicate the relations between words and should value in sememe predication. Therefore, we aim at incorporating the expert-annotated knowledge bases into sememe prediction process. To achieve that, we propose a CilinE-guided sememe prediction model which employs an existing word knowledge base CilinE to remodel the sememe prediction from relational perspective. Experiments on HowNet, a widely used Chinese sememe knowledge base, have shown that CilinE has an obvious positive effect on sememe prediction. Furthermore, our proposed method can be integrated into existing methods and significantly improves the prediction performance. We will release the data and code to the public.
All-or-nothing oblivious transfer based on the quantum one-way function

Oblivious transfer (OT) is one of the keystones of secure multi-party computation. It is generally believed that unconditionally secure OT is impossible. In this article, we propose a practical and secure quantum all-or-nothing oblivious transfer protocol based on the quantum one-way function. The protocol is built upon a quantum public-key encryption construction, and its security relies on the no-cloning theorem and no-communication theorem. Practical security is reflected in limitations on non-demolition measurements.
STUDENT DIFFICULTIES ON STRUCTURE AND WRITTEN EXPRESSION SECTION OF TOEFL IN HIGHER EDUCATION AT METRO CITY

Structure and Written Expression TOEFL is a major difficulty for students because of the lack of TOEFL understanding preparation, no specific TOEFL preparation book has been used, and the inaccurate use of strategies in understanding TOEFL. The purpose of this study was to analyze students' English language skills in the TOEFL Structure and Written Expression section material, to analyze the difficulties of the Structure and Written Expression material for students, and to describe the reasons for the difficulties faced by students in the Structure and Written Expression material. This research uses a descriptive method. The random sampling technique was carried out with a total sample size of 30 students in the English Language Study Program at Higher Education, namely the Islamic Institute of Islamic Studies Ma'arif Metro Lampung and IAIN Metro Lampung. Data collection techniques using tests, interviews, and observations. The test given in this study is the TOEFL Paper Based Test (PBT) published by the Educational Testing Service (ETS). The findings in this study have shown that students experience difficulties on the Structure and Written Expression of TOEFL because their ability in the test is at level C, "Enough". Second, among the eight indicators of the Structure and Written Expression material tested in the TOEFL, Inversion is the most difficult answer for students to answer because they have never studied this material and in-depth analysis is needed to answer the question. This shows that from the two TOEFL Structure tests the percentage of material difficulty is the highest among the other seven indicators.
Image caption generator using cnn and lstm

&#x0D; &#x0D; &#x0D; For this paper, we use CNN and LSTM to become aware of the caption of the image. Image caption generation is a system that comprehends natural language processing &amp; computer vision standards to recognize the connection of the image in English. In this research paper, we cautiously pursue a number of important concepts of photograph captioning and its familiar processes. We talk about Kera’s library, NumPy and Jupiter notebooks for the making of this paper. We also talk about Flickr dataset and CNN used for photo classification.&#x0D; &#x0D; &#x0D;
Modelling Of Solar Photovoltaic MPPT System by Using P &amp; O Algorithm

&#x0D; &#x0D; &#x0D; In this project Modelling of solar photovoltaic MPPT system by using P&amp;O algorithm is implemented. Solar cells convert sun light into electricity, but have the major drawbacks of high initial cost, low photo-conversion efficiency and intermittency. The current-voltage characteristics of the solar cells depend on solar insulation level and temperature, which lead to the variation of the Maximum Power Point (MPP).Here to improve photovoltaic (PV) system efficiency, and increase the lifetime of the battery, a microcontroller-based battery charge controller with maximum power point tracker (MPPT) is designed. Hence it gives effective outcome.&#x0D; &#x0D; &#x0D;
Communication in software development teams

Communication has been a widely studied factor because when performed ineffectively it leads to problems affecting the delivery of products and services to customers. In the context of software development, teams with communication problems are hampered in terms of time, cost and effort, progress of routine actions, and create team conflicts. This study investigates communication in software development teams through an extensive literature review. As a result, we obtained a set of factors classified into barriers and facilitators that affect communication in the software development process. This result is useful for developers and managers looking to improve communication as a strategy to streamline and improve the application development routine.
Current Status and Future Prospect of University Speaking Education During Non-Contact Era

Starting from around the mid-2010s, “Speaking” curriculum started to emerge. This change is highly due to the way university education requires communication in order to acquire and express knowledge. In addition, even after graduating university and working for a company, communication and speaking strategies are essential. In regards to this condition, the importance of speaking education in universities needs more consideration.&#x0D; Research on the existing speaking curriculum has been developed as follows. Most existing studies were conducted on middle school and high school students. Studies also including Korean speaking education for foreign students. However, the study of speaking subjects for a small number of Koreans consists of a special and fragmentary dimension. There are only a small limited amount of study on non-contact university speaking curriculum. The purpose of this study is to recognize the issue mentioned and to comprehensively grasp the current status of speaking education in consideration of the following purposes and to examine their own prospective direction.&#x0D; First, we examined the system and curriculum of university speaking courses in two forms and identified characteristics of the two mixed form. We created 17 different categories and studied the frequency from 11 university that adopted university speaking courses. Here, we also looked at the matters that should be applied more flexibly to the contents of the lecture in consideration of the situation during the pandemic. In addition, on the premise that there is a possibility of switching to a non-contact lecture at any time, we researched the method of non-contact response to university speaking courses.&#x0D; The existing speaking curriculum in university deals only in the speakers’ perspective. Accordingly, studies in the listeners’ perspective is also required. In particular, it is essential to further understand the role of recipients listening at an analytical level. Here, it was noted that counseling psychology approaches from a more analytical level according to individuals and groups, recipient situations, affiliation, and psychological environment.&#x0D; One of the characteristics of the existing speaking curriculum is the elements from a linguistic standpoint. According to this idea, the contents covered in the speaking subject were within the range of simple conversation and speech approached from a linguistic standpoint. Here, it is possible to organize into stories that exchange fragmentary conversations using narrative studies, and further organize them more closely in terms of discourse.
Volatility Spillover Between Bitcoin And Financial Stress Index

Purpose: This paper aims to test the volatility models for Bitcoin (BTC) and the financial stress index (FSI) and examine the volatility spillover among them. This aim was reached by obtaining weekly data from the 7th of January 2011 and the 24th of December 2021. Methodology: First, volatility modelling for the series is provided, and GARCH (1,1) for the BTC series and IGARC (1,2) for the FSI series are determined as the most appropriate volatility models. Then, residual volatility series are created for each variable over the IGARCH (1,2) and GARCH (1,1) models for the volatility spread between the series. The volatility spread between the series is examined with the diagonal VECH GARCH method. It is concluded that there is a positive volatility spillover effect from the FSI variable to the BTC variable. Then, impulse-response analysis is performed on the volatility residual series created for each variable. The empirical findings from impulse response analysis support a risk transfer between BTC and FSI series. Results and Findings: Changes in the BTC return series and FSI series are caused mainly by themselves, and the series are most affected by their shocks. By comparing the variance decomposition of the volatility series with the analysis results, it can be said that the changes in the volatility series are caused mainly by each other.
Analysis of research trends related to media literacy

Objectives This study analyzes the research literature related to media literacy to grasp the recent trend of research related to media literacy and to suggest the direction of media literacy education in the future.&#x0D; Methods As for the analysis data, primary data were collected by searching for keywords related to media literacy in the Korean academic journal Quote Index (KCI) and Academic Research Information Service (RISS), and secondary data were collected using the Netminer ‘Biblio Data Collector’ bibliographic information collection engine. A total of 521 papers were selected by reviewing the 1.2nd data. The analysis targets were classified by research period and method, and analysis was conducted by creating a reference frame with a matrix according to the research purpose and media literacy capabilities.&#x0D; Results First, research trends by period were steadily increasing from 2011 to 2020. Second, in the classification by research method, quantitative research was 34.7%, literature research was 31.3%, and qualitative research was 22.5%. Third, in the classification by research purpose, 201 studies on media literacy and competency were most actively conducted (38.6%) and in the classification by year of research purpose, studies on perception and competency (40.8%) and studies on education status (25.6%) were increasing in the second half. Fourth, in the detailed competency analysis of media literacy, 83 studies (32.0%) related to critical and discriminatory media evaluation capabilities were the most common, followed by 65 (25.1%) media expression capabilities and 61 (23.6%). Fifth, as a result of matrix analysis of research purpose and detailed competency, it was confirmed that research on media access and functional utilization and research on conceptual and theoretical considerations in enjoyment competency research were somewhat insufficient. In general studies excluding research on productive media expression capabilities, studies on program and model development and verification research, educational plans, and effectiveness analysis were found to be insufficient.&#x0D; Conclusions Based on the awareness of media literacy and the current status of education, it is necessary to conduct more active research on programs or models that balanced media literacy capabilities, and policy support from media education-related institutions and governments should be accompanied.