Reviewerly/exHarmony huggingface dataset:
Assessment of Students’ Performance in Construction Management Program for Online Learning amid COVID-19

The COVID-19 pandemic has created a large disruption to higher education institutions across the globe. Owing to lockdown, movement restriction, as well as health and safety concerns of students and educators, all institutions of higher learning, were instructed to migrate their teaching and learning mode from offline to online during the pandemic period. This overnight shift of teaching and learning pedagogy has inevitably created various challenges for students. This research aims to study the impacts of the COVID-19 pandemic on the performance of construction management students. The study applied qualitative semistructured interviews and involved 4 construction management students (research respondents) from a private college in Kuching Sarawak, Malaysia. The purposive sampling method was adopted for selecting targeted respondents who must have undergone both teaching and learning experience before and during the COVID-19 pandemic, as well as from different geographical divisions in Sarawak, Malaysia to study on the impacts of change. Findings from this study showed that the performance of construction management students in online learning during the COVID-19 pandemic was affected, particularly in the context of numeracy skills and entrepreneurship skills. In addition, the study found out that poor infrastructure facility is a potential threat to online learning satisfaction and the perceived students’ performance.
Anomaly Detection Using Unsupervised Machine Learning Algorithms

In recent times, Machines malfunction due to the anomalies present in the sensors that lead to a lot of losses. The malfunction of one machine can lead to a lot of problems overall in the system or can harm an individual if they are close to the machine. Anomaly detection is important because it helps us prevent the deterioration of the machines beforehand. It also helps to maintain security. Machine Learning helps us predict the future and with the help of it, we can predict the anomalies. Any machine anomaly depends on the sensors present in the machines. This research aims to predict if there is an anomaly, given the setting and sensor details of a machine.
Distance Education and Pursuit of the Common at the Time of COVID-19

The radical changes in social systems and people's ways of living that have arisen with the coronavirus disease of 2019 (COVID-19), and the difficulties and critical situations that people are now confronting, has made them realize that the private question, "What does it mean to live a happy life?" is simultaneously part of the public agenda.The crisis in hospitals, the bankrupt businesses, the enforced reconstruction of educational systems and methods-all encourage a shift of thinking over the division of the private and the public in democracy, making us realize that individuals in their various domestic things are involved in the creation of public knowledge and that they are already in a shared space.The line between the private and the public is blurred, and the very meaning of "the public" should be reconsidered, as should "the private."The crisis itself impels us towards a holistic view of human being, and this orients us towards a renewed way of creating the common.Against this background, this essay focuses on the digital commons, which we believe is a potentially fruitful concept for reconsidering the idea of the common at the time of COVID-19.It is a public site of shared space, resources and knowledge, enabled by border-crossing digital space and time.The term "digital commons" has come into use in such empirical areas as sustainability studies, computer technology, and economics, and it has emerged also in library practice. 1 The combination of the digital and the commons has created new possibilities as well as challenges in our times.As the digitalization of university education indicates, shared digital space, resources and knowledge are expected to have the potential to enable a pooling of knowledge beyond differences in position, in which new
Enhancing User Experience through Interaction Design - Rethinking the municipal agora of Chania through AR narratives

This paper examines the relationship between designing interactive experiences based on new technologies and the process of architectural narration.It highlights the idea of rethinking a building with historical, architectural and functional value, as an experience and a journey.Referring to the historic building of the Municipal Market of Chania, Greece and using the conceptual idea of designing through narratives, it delineates the process of integrating new technologies into the process of designing a spatial and temporal experience.Exploiting Augmented Reality, we design an application implementing a digital layer with architectural and historical content, that is integrated into reality, improving the on-site visit, providing enhanced understanding of the building and introducing experiential visitor-building interaction.The application is available through mobile devices and the proposed system is evaluated by a group of users showing the positive effects of the use of interactive technologies in redesigning the experience of a space.
Alternative digital currencies in international monetary law: Global stablecoins

Alternative digital currencies were created to correct the shortcomings of the so-called first generation of cryptocurrencies. Their impact on the monetary order stability, systemic risk, and monetary policy strategy pursued by the Central Bank has been insufficiently examined, primarily because they are issued by large technology companies rather than the Central Bank as the custodian of monetary sovereignty. The treatment of cryptocurrencies in tort law is different from the monetary law standpoint. As such, the former is not considered in this paper because it is a private law relationship. On the other hand, monetary law refers to public law relations, including the regulatory powers of the Central Bank and the legal definition of alternative money by the provisions of the Central Bank law. As the supreme monetary institution, the Central Bank has a monopoly over the legal tender for designating and issuing money. In that sense, it would be useful to deal with the place and importance of alternative money in monetary law first, and then with other branches of private and public law. In legal terms, the acceptance and circulation of alternative money impose simultaneous (and highly demanding) consideration of the legal nature of cryptocurrency, where we can see the primacy of the social theory of money over state monetary nominalism. However, this primacy must be only temporary because the historical development of money (in all its forms) clearly shows that the emergence of any currency must sooner or later be regulated by adequate laws, for the sake of legal security and preservation of monetary stability. In a way, the accelerated technical-technological development has "caused" the existing status quo in the classical and (to some extent) the contemporary monetary law thought about how money is legally defined and who can take the role of money issuer, which has shaken the centuries-old awareness of the nature and functions of money in modern society. The circumstances that have influenced the reconsideration of already acquired habits include the emergence of reduced use of cash in circulation, the emergence of "sharing" technology that enabled the creation of cryptocurrencies, the announcement of leading technology and other multinational companies on issuing private cryptocurrencies, as well as the circumstances related to the global economic and financial crisis and the Covid-19 pandemic which point to certain advantages of alternative money.
The Effectiveness of Anticipation Guide and Visualization Strategies in Teaching Reading Comprehension to Students With High and Low Motivation

Teaching reading comprehension is not easy, the teacher must consider an appropriate strategy that can influence in the way of teaching-learning. The problem came from the Eight Grade students of SMPN 1 Kersana Brebes in the Academic year 2019/2020. The students lack motivation English subject because the teacher taught using conventional strategy which made them bored and could not achieve good score in English subject. The present study aims to explain how significant the studentsâ€™ achievement taught by using anticipation guide and visualization strategies in teaching reading comprehension to students with high and low motivation. This study was a quasi-experimental design with a 2x2 factorial design conducted in eighth grade students at SMPN 1 Kersana, Brebes as the research participants. There are two experimental group involved. The studentsâ€™ different level of motivation was taken as a factor that might influence the strategies. In collecting data, the writer used reading comprehension test to get studentsâ€™ scores and questionnaires. The data was analyzed using ANOVA to answer the main hypotheses. Based on the analysis of the significance score was 0.000 which was lower than 0.05. It can be concluded that there was significance difference on the studentsâ€™ achievement taught by anticipation guide and visualization for students with high and low motivation. This research is expected to give a contribution to give a contribution to English teaching learning such as giving appropriate strategy to teach reading comprehension.
The Effectiveness of Role-Play and Information-Gap in E â€“ Teaching Speaking Skill for High-Low Self-Confident Students

Teaching speaking is not easy. The teacher has to use an appropriate technique in teaching speaking. The research problem came from the Eighth Grade students of SMPN 1 Arjawinangun Cirebon. The students were passive in conversation when someone talked in English because the teacher taught using traditional method which made them bored and could not give feedback in English conversation. On the studentsâ€™ side, they get difficulties in learning speaking because they felt bored and passive during teaching and learning process. This research aims to explain how significant the studentsâ€™ achievement taught by using role play and information gap technique conducted with high and low self-confident of students in e-teaching speaking context. The research design was a quasi-experimental design with a 2x2 factorial design involving the eighth-grade students SMPN 1 Arjawinangun, Cirebon as the research participants. There were two experimental groups involved. The studentsâ€™ different self-confidence was taken as a factor that might influence the techniques. In collecting the data, the writer used speaking test to get studentsâ€™ scores and questionnaires made by Google Form and on-line system. The data was analyzed using ANOVA to answer the main hypotheses. Based on the analysis of the significance score was 0.178 which was higher than 0.05. It can be concluded that there was no significant difference on the studentsâ€™ achievement taught by role play and information-gap for students with high and low self-confidence. This research is expected to give a contribution to the research such as giving appropriate technique to teach speaking in e-learning.
Coalition Game-based Approach for Improving the QoE of DASH-based Streaming in Multi-servers Scheme

Dynamic Adaptive Streaming over HTTP (DASH) is becoming the de facto method for effective video traffic delivery at large scale.Its primer success factor returns to the full autonomy given to the streaming clients making them smarter and enabling decentralized logic of video quality decision at granular video chunks following a pull-based paradigm.However, the pure autonomy of the clients inherently results in an overall selfish environment where each client independently strives to improve its Quality of Experience (QoE).Consequently, the clients will hurt each other, including themselves, due to their limited scope of perception.This shortcoming could be addressed by employing a mechanism that has a global view, hence could efficiently manage the available resources.In this paper, we propose a game theoretical-based approach to address the issue of the client's selfishness in multi-server setup, without affecting its autonomy.Particularly, we employ the coalitional game framework to affect the clients to the best server, ultimately to maximize the overall average quality of the clients while preventing re-buffering.We validate our solution through extensive experiments and showcase the effectiveness of the proposed solution.
Laplace estimation for scalar linear systems

Uncertainties in many physical systems have impulsive properties poorly modeled by Gaussian distributions. Refocusing previous work, an estimator is derived for a scalar discrete-time linear system with additive Laplace measurement and process noises. The a priori and a posteriori conditional probability density functions (pdf) of the state given a measurement sequence are propagated recursively and in closed form, and the a posteriori conditional mean and variance are derived analytically from the conditional pdf. A simulation for an estimator is presented, demonstrating marked resilience to large, un-modeled spikes in the measurements.
Resource Possibilities of Cloud Technologies in Training the Preschool Education Specialists

The article presents cloud-based learning support systems used in the training of teachers of professional disciplines of preschool education. In particular, it describes on-line services and applications based on Google’s cloud technologies (G-mail, Google Calendar, Google Groups, Google Docs, Google Arts &amp; Culture, Google Sites, Google Video, Google Drive, Google Hangouts, Google Scholar, Google Classroom, Google Translate, YouTube, Google Presentations, Google Spreadsheets). The role and resource possibilities of cloud-oriented learning support systems in the formation of the future teacher of preschool disciplines, the development of his competencies to organize the educational process in a cloud-oriented educational environment are revealed.&#x0D; The authors, based on their own experience, propose to use cloud-based learning support systems to organize a single Internet space in higher education institutions, including educational online environment, educational planning, development, design, placement, storage and exchange of educational, scientific, informational -reference material, web-events of educational and scientific nature, corporate communication, individual and group work.
The Identification and Dissemination of Creative Elements of New Media Original Film and Television Works Based on Review Text Mining and Machine Learning

With the continuous growth of the film market and the consumption demand of audiences, the value of film content has become increasingly apparent. Extracting movie content elements is an important step in quantitative analysis of movie content. In this paper, based on text mining technology, deep data analysis of movie reviews is carried out using TF-IDF and machine learning to visualize high-frequency words, and sentiment analysis is performed on reviews to find out the hidden deep information behind the big data of movie reviews. Although the extracted keywords can draw the content and characteristics of the film for us, they cannot establish the correlation with the creative elements of the film and television works. Therefore, in this paper, the extracted keywords are clustered to find the central words of these words. First of all, in order to improve the representativeness of keywords, the Epoch data set and the Batchsize data set are used to conduct experimental analysis on the model in this paper. Through comparative experiments, it is concluded that when Batchsize = 32 and Epoch = 25, the model achieves the optimal classification effect. The analysis shows that when the training times are too small, the model is not fully learned, and when the training times are too many, the model will be overfitted, which will reduce the accuracy of the model, resulting in the opposite effect. The keywords extracted above can draw the content and characteristics of the movie for us.
Low‐latency selective encryption scheme for scalable extension of high‐efficiency video coding

Abstract This article presents a selective encryption (SE) chaotic video stream cipher for the scalable extended high‐efficiency video coding (SHVC) bitstream. The proposed SHVC SE uses a logistic map (LM) for enciphering the motion vector difference (MVD), discrete cosine transform (DCT) coefficients and delta quantization parameter (dQP) sign bits. The SHVC SE chaotic video stream cipher is proposed to secure the most sensitive bits of the SHVC while keeping the video format compliance feature. Also, this paper presents a performance analysis for the proposed SHVC SE and the AES in CFB operation mode. Experimental results illustrate the main feature of using the LM in the proposed SHVC SE, which is lower latency encoding time for the SHVC SE chaotic video stream cipher than using the AES in CFB operation mode. Security investigations are performed on the proposed SHVC SE for ensuring the robustness of the ciphered SHVC digital video against unauthorized attacks.
A 3D Face Modeling and Recognition Method Based on Binocular Stereo Vision and Depth-Sensing Detection

The human face is an important channel for human interaction and is the most expressive part of the human body with personalized and diverse characteristics. To improve the modeling speed as well as recognition speed and accuracy of 3D faces, this paper proposes a laser scanning binocular stereo vision imaging method based on binocular stereo vision and depth-sensing detection method. Existing matching methods have a weak anti-interference capability, cannot identify the spacing of objects quickly and efficiently, and have too large errors. Using the technique mentioned in this paper can remedy these shortcomings by mainly using the laser lines scanned onto the object as strong feature cues for left and right views for binocular vision matching and thus for depth measurement perception of the object. The experiments in this paper first explore the effect of parameter variation of the laser scanning binocular vision imaging system on the accuracy of object measurement depth values in an indoor environment; the experimental data are selected from 68 face feature points for modeling, cameras that photograph faces, stereo calibration of the cameras using calibration methods to obtain the parameters of the binocular vision imaging system, and after stereo correction of the left and right camera images, the laser line scan light is used as a pixel matching strong features for binocular camera matching, which can achieve fast recognition and high accuracy and then select the system parameters with the highest accuracy to perform 3D reconstruction experiments on actual target objects in the indoor environment to achieve faster recognition.
The integration of extended reality for student-developed games to support cross-curricular learning

While eXtended Reality (XR) ha s been shown to provide rich promise, its adoption within the educational context for student created games is still limited. Recent advances in XR technology, especially in mobile XR tools, have made XR more accessible. These advances have also enabled the development of student-created XR experiences that provide opportunities for integrating learning with technology skills development. Through the integration of critical digital skills across the curriculum, students can demonstrate a range of learning outcomes across many different learning areas. In this study, we explore how the affordances of XR can be leveraged to enable new learning opportunities, specifically in enabling students to design their own XR learning experiences. We also explore how the added context of XR games provides additional benefits to engage and motivate learners. In this article, we identify and explore twelve affordances framed in the notions of engagement , authenticity and contextualisation . These affordances have been identified in the literature to highlight the benefits of XR and were explored in terms of how the added context of student-created games leveraged these affordances. Drawing on a wider research project, we identify three scenarios that were adopted by three teachers (Mathematics, Science and Language teacher) to teach a range of subjects that drew on XR student-created games. From this analysis, we conclude with six proposed design principles that could be adopted by other teachers to help guide them in applying a similar approach in their teaching.
Compensation layer‐added federated learning receiver: Design and implementation

The federated learning‐based symbol detection technique has attracted much attention recently due to its application of processing data at the network edge (ie, mobile user equipment) in a distributed manner. In this regard, the federated receiver is presently being promoted as a replacement for and improvement on the conventional model‐based receiver. This paper proposes an average pooling with compensation layer and an average pooling with dense layers‐added federated receiver for symbol detection in a downlink fading channel. In average pooling with a compensation scheme, the average of the input data is extracted and then ripples of the data are minimized by multiplying the weight coefficient in the compensation layer. In average pooling with dense scheme, two pooling schemes, such as average pooling and max‐pooling, are incorporated into dense layers with various activation functions. Simulation results are provided to demonstrate that the proposed compensation layer‐added federated receiver outperforms the conventional federated receiver.
Domain Adaptation through Photorealistic Enhanced Images for Semantic Segmentation

In this paper, three types of domain adaptation which are defined as image-level domain adaptation, interdomain adaptation, and intradomain adaptation are efficiently combined to construct a high efficiency framework for semantic segmentation. The proposed domain adaptation platform can achieve a high reduction of time-consuming to generate exhausted supervised data in the real world using photorealistic images. The proposed framework achieved a mean Intersection-over-Union (mIoU) of 45.0%. Furthermore, by combining the proposed method with intradomain adaptation, the improvement of 1.2% mIoU is achieved compared to previous work.