Reviewerly/exHarmony huggingface dataset:
Implementation of Digital Literacy toward Pandemic Situation

This paper aims to describe the level of students’ digital literacy in their study since pandemic situation. It is very important to know because it gives the answer of education’s challenging faced covid-19 situation for the students’ safe and comfortable. This research is survey research to describe the implementation of digital literacy through level of digital literacy as challenging pandemic situation. Data collection techniques using the instrument in the form of a questionnaire. The four concept was constructed referred to Bawden (2008) such as basic literacy skills (reading and writing), background information knowledge (intellectual level), skills in the field of ICT, and attitudes and perspectives. This needs to be known to identify how far digital literacy was important for the students in their studying since Covid- 19 situation. This research involved 20 respondents who always use digital literacy in their study. The data was collected from the distribution of digital literacy questionnaire instruments for the students, then the data was describing through percentage to know how the students’ level of digital legacy when there are teaching learning process. The findings indicate that respondents have a high level of digital literacy. In the aspect of basic digital literacy skills, all respondents were able to connect to the platform to take part in online learning, and were able to use worksheet technology to write assignment articles according to the provisions. In the aspect of background information knowledge, almost all respondents were able to find learning supplements in the form of reference articles and find their relevance based on the abstracts of the articles. In the main aspects of digital literacy, most respondents are able to cite the relevant sections to compile assignment articles, and are able to compare the contents of several reference articles. On the aspects of attitudes and perspectives of information users, all respondents are able to write citations and compile a bibliography for reference articles referred to.
The development trends and features of online news websites in Bangladesh

This article refers to the brief history of the development of online media in Bangladesh starting from the beginnings of the Internet to the contemporary stage.&#x0D; Since 2006 Bangladeshi news organizations have been reshaping their strategy towards being a digital-only news outlet. News organizations are now using different features of mobile devices and social media to tell stories and engage with their target audiences. Today both the digital-only news outlets and mainstream media use QR codes, messengers, social media platforms, which enable them to reach a wider area of audiences. By using yet inexpensive digital tools journalists can easily create and distribute content for digital-only platforms.&#x0D; We consider digital-only platforms as new media, social media, and convergence media platforms. Social media platforms have provided the opportunity for traditional journalists to share news quickly, get feedback from the audience, and have two-way communication with the reader.&#x0D; Previous studies have looked at the genres of online journalism from a western perspective. Little has been done on the topic from the context of Bangladesh.&#x0D; In this article, we analyze the basic features of online news media that exist in contemporary Bangladesh and provide an account of the development trends. We outline the new genres, techniques, and use as a sample two most famous online news platforms: The Daily Star and bdnews24. A series of semi-structured interviews were conducted with 5 different professionals from Journalism and mass media. This study is based on both primary and secondary sources of qualitative data to understand the new genres of online news media, challenges, and opportunities to work in the ever-changing media landscape.
An Analysis of Artificial Intelligence Clinical Decision-Making and Patient-Centric Framework

The smart decision-making support framework is typically referred to as artificial intelligence (AI). The clinical decision framework can transform the process of decision-making using various technologies. These technologies incorporate framework engineering and information technology. The vital centered ontology-centered automatic reasoning which is incorporated in machine learning methodologies has been established in the present patient databases. The approach evaluated in this paper is in the support of the interoperability between various health information systems (HIS). This has been evaluated in sampling implementations that link up to three separate databases: drug prescriptions guidelines, drug-to-drug interaction and patient information which are databases used to showcase the efficiency of an algorithm used to provide effective healthcare decisions. Generally, the possibility of artificial intelligence was evaluated in the process of supporting tasks that are essential for medical experts including the aspect of coping up with noisy and missing patient information and enhancing the utility of various healthcare datasets.
Maintainability Prediction in Eclipse Mylyn Software Program Code Using Mamdani's Fuzzy Inference System Approach

Software quality can be assessed using certain measures and methods, as well as using software testing. ISO is used as one of the benchmarks of software quality that has been created by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). Software testing can use metrics to increase productivity, this software is very useful in simplifying the testing process by focusing the programmer on the code quality part of the program. The ability of software to be modified includes correction, improvement or adaptation to changes in the environment, requirements, and functional specifications. Metrics can be used to measure the quality level of a model's program code based on indicators from Chidamber Kemerer (CK) by performing Maintainability Predictions which are tested on the metrics bug prediction found in the eclipse mylyn application which consists of four properties, namely WMC, DIT, NOC, and , RFCs. To be able to help carry out the process of calculating software quality based on CK Metrics on mylyn eclips data using the Mamdani fuzzy inference system, it can prove the classification into Low, Medium, High forms. In this case, the defuzzification method is confirmed using the COA (centre of area) method to determine the final value obtained from the membership function formed from the composition process of all outputs.
Combined Gray Level Transformation Technique for Low Light Color Image Enhancement

Insufficient and poor lightning conditions affect the quality of videos and images captured by the camcorders. The low quality images decrease the performances of computer vision systems in smart traffic, video surveillance, and other imaging systems applications. In this paper, combined gray level transformation technique is proposed to enhance the less quality of illuminated images. This technique is composed of log transformation, power law transformation and adaptive histogram equalization process to improve the low light illumination image estimated using HIS color model. Finally, the enhanced illumination image is blended with original reflectance image to get enhanced color image. This paper shows that the proposed algorithm on various weakly illuminated images is enhanced better and has taken reduced computation time than previous image processing techniques.
Impact of Augmented Reality on Vocabulary Acquisition and Retention

The present study investigated the impact teaching academic vocabulary through an augmented reality (AR) approach had on acquisition and retention as compared to using a more traditional flash card based approach. 29 high school students ranging from 9th to 11th grade followed the pattern of a 10 word vocabulary pre-test, being taught those words through respective alternating AR and traditional vocabulary methods, and post-tested one week from the date of teaching. At the end of the testing and teaching process, the unit scores were compared to find if any differences occurred. Analysis revealed that there is a significant difference between the two teaching methods. Participants scored better in the AR unit as compared to the traditional unit. Furthermore, participants also reported greater satisfaction with the AR method because it held their attention, gave them something to focus on, and was overall more engaging. Comparatively, participants found the traditional method not engaging, however, they were comfortable with the traditional method because it is what they are comfortable with in the classroom. Given the curiosity of using AR in the classroom, more research could be conducted to find patterns in participant performance across all academic content areas as well as other uses for AR in the classroom.&amp;nbsp;
Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence

We develop new adaptive algorithms for variational inequalities with monotone operators, which capture many problems of interest, notably convex optimization and convex-concave saddle point problems. Our algorithms automatically adapt to unknown problem parameters such as the smoothness and the norm of the operator, and the variance of the stochastic evaluation oracle. We show that our algorithms are universal and simultaneously achieve the optimal convergence rates in the non-smooth, smooth, and stochastic settings. The convergence guarantees of our algorithms improve over existing adaptive methods and match the optimal non-adaptive algorithms. Additionally, prior works require that the optimization domain is bounded. In this work, we remove this restriction and give algorithms for unbounded domains that are adaptive and universal. Our general proof techniques can be used for many variants of the algorithm using one or two operator evaluations per iteration. The classical methods based on the ExtraGradient/MirrorProx algorithm require two operator evaluations per iteration, which is the dominant factor in the running time in many settings.
The Contemporary Grade of Marketing of Library Products and Services in M. Kumarasamy College of Engineering: An Investigative Study

Academic Libraries nowadays have to relate all its activities to public and its users very often and keep them updated with the changes and Updation in the Library. In order to attract the users and sustain in this modern ICT world, the user’s complete satisfaction is the ultimatum. We are in a digital world where one need not physically go to the Library or a computer to get information they want. Just a swipe on their smart phone and they have their required information in their finger tips. They just require a device to login and an internet or Wi-Fi connection. That’s it. This study is about the marketing of information products and services among users of M. Kumarasamy College of Engineering, Karur. From this research it is found that the marketing of services has been a great challenge with limited budget as well as the emerging ICT tools and technology day by day. The study shows the user behavior, their awareness level, usage, usefulness &amp; the marketing strategies used in the College Library for promoting their services. This paper also suggests that Librarians have to be proactive in marketing their information sources &amp; services with the help of current marketing strategies using ICT which is the need of the hour.
Calibrating trust toward an autonomous image classifier.

Successful adoption of autonomous systems requires appropriate trust from human users, with trust calibrated to reflect true system performance.Autonomous image classifiers are one such example and can be used in a variety of settings to independently identify the contents of image data.We investigated users' trust when collaborating with an autonomous image classifier system (AICS) that we created using the AlexNet model (Krizhevsky et al., Advances in neural information processing systems, 2012).Participants collaborated with the classifier during an image classification task in which the classifier provided labels that either correctly or incorrectly described the contents of images.This task was complicated by the quality of the images processed by the humanclassifier team: 50% of the trials featured images that were cropped and blurred, thereby partially obscuring their contents.Across 160 single-image trials, we examined trust toward the classifier, while we also looked at how participants complied with the classifier by accepting or rejecting the labels it provided.Furthermore, we investigated whether trust toward the classifier could be improved by increasing the transparency of the classifier's interface, by displaying system confidence information (SCI) in three different ways, which were compared to a control interface without confidence information.Results showed that trust toward the classifier was primarily based on system performance, yet this also was influenced by the quality of the images and individual differences among participants.While participants typically preferred classifier interfaces that presented confidence information, it did not appear to improve participants' trust toward the classifier.
Factors affecting the company's capitalization

The article considers the essence of the company's market value, clarifies the concept of enterprise capitalization. The author analyses Russian and foreign studies devoted to the identification of quantitative factors that affect the market value of companies. In the analysis of domestic research, the author pays special attention to the oil and gas and electric power industries of the economy. The analysis of foreign studies includes companies from Italy, Indonesia and Jordan. The paper analysed the structure and dynamics of the Russian stock market, the influence of revenue, net profit, the level of dividend payments, return on assets, the ratio of borrowed and own funds, as well as the return on sales by the amount of the market value of electric power companies whose shares are traded on the Russian stock market. The study identifies the main quantitative factors affecting the capitalization of companies. The author determines the directions of further research.
Applying ANN to the AI Utilization in Forecasting Planning Risks in Construction

Applying ANN to the AI Utilization in Forecasting Planning Risks in Construction Fawaz Habbal, Firas Habbal, Abdualla Alnuaimi, Anwar Alshimmari, Nawal Alhanaee and Ammar Safi Pages 1431-1437 (2020 Proceedings of the 37th ISARC, Kitakyushu, Japan, ISBN 978-952-94-3634-7) Abstract: A long-standing problem in the field of automated reasoning is designing systems that can describe a set of actions (or a plan) that can be expected to allow the system to reach the desired goal. Artificial Intelligence (AI) techniques provide the means to generate plans and to reason with as well as provide explanations from stored knowledge. However, these methods, which employ little domain knowledge and are originally used in AI for planning, proved inadequate for complex real-life problems such as project planning. As a result, more recent research adopts the knowledge engineering methodology as an efficient approach for developing planning systems. This paper highlights the limitations of existing project planning tools. It also illustrates the power of AI techniques in the construction planning domain through a summary and critique of previous and current research in AI planning. It then concludes with a suggested approach for development. From the study, it was found out that a proper application of the AI technology requires full support in form of a Data Bank, which, unfortunately, becomes one of the most significant hurdles in its adoption. To deal with this limitation, it is recommended to adopt the ANN. Keywords: Risks Planning; Construction Planning; Risks forecasting; Neural Network; Support Vector Machines DOI: https://doi.org/10.22260/ISARC2020/0198 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
BLOCKCHAIN AND INTERNAL CONTROL: THE COSO PERSPECTIVE: AN INTRODUCTION AND BRIEF REVIEW

As the title says this is an introduction and brief review of a long and rather complex study of issues related to internal controls over financial reporting (ICFR) and auditing the new distributed ledger technology known as Blockchain Ledgers. The report points out many of the control issues related to Blockchain Ledgers (BC), including potentially advantageous characteristics such as immutability and shared ledgers. It also addresses the new risks and needs for additional controls for which the search for solutions continues. Audit procedures have always followed technology advances, but they will never impede the innovation and related creative destruction that come with advancing business models. Much more work lies ahead, nevertheless, this COSO report is an excellent summary that will inform discussions about new control methods and methodologies. The COSO report has value for all readers including GRC professionals as well as C-suite and board members. However, the primary beneficiaries will be in tech support to the CFO and Chief Audit Executives, BC developers in company operations, and BC specialists in public accounting firms. This summary should inform all readers.
Blood Vessel Segmentation Based on the 3D Residual U-Net

In this paper, we propose blood vessel segmentation based on the 3D residual U-Net method. First, we integrate the residual block structure into the 3D U-Net. By exploring the influence of adding residual blocks at different positions in the 3D U-Net, we establish a novel and effective 3D residual U-Net. In addition, to address the challenges of pixel imbalance, vessel boundary segmentation, and small vessel segmentation, we develop a new weighted Dice loss function with a better effect than the weighted cross-entropy loss function. When training the model, we adopted a two-stage method from coarse-to-fine. In the fine stage, a local segmentation method of 3D sliding window is added. In the model testing phase, we used the 3D fixed-point method. Furthermore, we employ the 3D morphological closed operation to smooth the surfaces of vessels and volume analysis to remove noise blocks. To verify the accuracy and stability of our method, we compare our method with FCN, 3D DenseNet, and 3D U-Net. The experimental results indicate that our method has higher accuracy and better stability than the other studied methods and that the average Dice coefficients for hepatic veins and portal veins reach 71.7% and 76.5% in the coarse stage and 72.5% and 77.2% in the fine stage, respectively. In order to verify the robustness of the model, we conducted the same comparative experiment on the brain vessel datasets, and the average Dice coefficient reached 87.2%.
Correction to: An overview and evaluation of citation recommendation models

A correction to this paper has been published: https://doi.org/10.1007/s11192-021-04065-z
A Study on Techno-typological of the Polyhedron: Focus on Loc. at Unjeong Paleolithic Site, Paju

여러면석기에 대한 연구사적인 측면으로 살펴보면 여러면석기에 대한 연구는 계측을 통한 수치화 연구나 최종형태적인 분류, 몸돌 의 분류체계에 도입한 분석 등이 이루어지고 있었다. 여러면석기(Polyhedron)는 구석기시대 사람들이 제작한 겉면이 대체로 여러 개의 면과 능선으로 되어 있으며 면이나 능선 위에 으스러지거나 얻어맞은 자국이 남아 있는 도구석기이다. 따라서, 여러 면에서 이루어진 제작과정에 대해 고민할 필요가 있으며, 여러면석기에 대해 보다 정확한 분석이 필요하다는 문제의식을 가지고 기존 연구뿐만 아니라 제작방법에 대한 분석을 추가하여 파주 운정1지구에서 출토된 여러면석기 가운데 가장 많이 출토된 36-5지점 여러면석기를 통해 기술형태적으로 연구하였다. 연구결과를 바탕으로 나아가 여러면석기에 대한 새로운 분류안(Ⅰ~Ⅳ식)도 제시하였고, 이를 파주 운정1지구 내 36-5지점 뿐 아니라 다른 지점에서 출토된 여러면석기에도 대입하기도 하였다. 이번 논문에서 제시한 분류안을 통해 향후 구석기유적에서 출토되는 여러면석기에도 적용 하여 제작의도 및 형태적인 특징 등 여러면석기에 대한 고찰에 적용할 수 있다는데 그 의의가 있다고 본다. 추후 여러면석기의 분류 결과와 다른 유적과의 문화층 연계, 여러면석기의 기능에 대한 연구 등을 보완하여 여러면석기에 대한 전체적인 성격에 대해 논의하고자 한다.Polyhedron is a stone artifact whose surface was made by the people of the Paleolithic age and is composed of many facets and ridges, with crushed or struck marks on them. Polyhedron has separated marks which are the same as those of the core during its creation process. In addition, polyhedron has been categorized into the range of the core due to the same characteristics shown in the core and the polyhedron. Therefore, the same characteristics identified in the core and the polyhedron have led only to researches on the research methods and the functional parts characterized by numerical values. this paper aims to examine the difference through the comparison of the polyhedron in order to techno-typologically classify the polyhedron based on the results. In this way, the polyhedrons have been classified with a new form(Ⅰ~Ⅳ) assigned, which provides more objective data on the polyhedron production process which is not easy to explore. It is also expected to be useful for the future researches on the classification of further identified polyhedrons.
A Simultaneous Multicomponent Measurement Method of Thermal Stress Based on DSSPI

Traditional thermal stress measurement methods usually assume that the stress is generated only in one direction and cannot measure multidimensional stress components in real time. To realize the real-time and full-field measurement of multiple components of thermal stress, we improved the digital speckle shearing pattern interferometry method and predigested the measurement structure. Additionally, we were able to simplify the measurement process and measure the out-of-plane as well as the in-plane components of the stress tensor at the same time without the symmetric dual-beam illumination or phase-shifting devices. In this article, we demonstrated the possibility of measuring three component gradients ∂ <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">u</b> / ∂ <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</b> , ∂ <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</b> / ∂ <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</b> , and ∂ <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</b> / ∂ <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</b> , and carried out experiments proving that this method allows for measuring the multicomponent thermal stress measurement of the object under the premise of certain mechanical structure.
Speech Signal Compression Deteriorates Acoustic Cues to Perceived Speaker Charisma

Previous research by the authors showed that signal compression codecs used in remote meetings and mobile communications have a substantial negative effect on perceived speaker charisma. Moreover, this effect size varied as a function of speaker gender. Following up from this previous study, we conducted a multiparametric acoustic analysis of a set of sentences elicited from male and female speakers in order to detail the effect of speech-signal compression on charisma-related acoustic-prosodic feature settings. Results show that all compression algorithms caused significant acoustic changes compared to the baseline condition. Almost all of them go in an unfavorable direction concerning speaker charisma. The six compression methods also performed differently well. While OPUS and MP3 caused the fewest negative effects, SPEEX and AMRNB resulted in the most negative effects; GSMFR took a middle position. Moreover, evidence is found for gender-specific effects in terms of both the number of negatively affected acoustic features and their type. The results are discussed with respect to their conceptual implications of perceived speaker charisma and the further development of codecs.