Reviewerly/exHarmony huggingface dataset:
Gaussian Network Model of Global Seismicity

The plate tectonics needs the direct stress continuity between the far-distant subduction zones within the travel time of the elastic wave through the rigid plate. Therefore, the plate boundary zones in the globally connected western and eastern Pacific regions possibly form some kinds of mechanical network system in which the global correlated seismicity of the subduction zones is coherent with each other. The dynamics of this type of globally connected seismicity network should be controlled by the rotation-invariant potential energy with connectivity matrix (Kirchhoff matrix).
Explaining Machine Learning Predictions: A Case Study

The growing trends and demands for Artificial Intelligence in various domains due to their excellent performance and generalization ability are known to all. These decisions affect the population in general as they usually deal with sensitive tasks in various fields such as healthcare, education, transportation, etc. Hence, understanding these learned representations would add more descriptive knowledge to better interpret the decisions with the ground truth. The European General Data Protection Regulation reserves the right to receive an explanation against a model producing an automated decision. Understanding the decisions would validate the model behavior, ensure trust, and deal with the risk associated with the model. Upon analyzing the relevant features, we can decide whether the model predictions could be trusted or not in the future. We can further try to reduce the misclassification rate by rectifying the features (of the misclassified instances) if needed. In this way, we can peek into the black-box and gain insight into a model’s prediction, thus understanding the learned representations. In pursuit of this objective, a common approach would be to devise an explanatory model that would explain the predictions made by a model and further analyze those predictions with the ground truth information. We initiated a case study on a diabetes risk prediction dataset by understanding local predictions made by five different Machine Learning models and trying to provide explanations for the misclassified instances.
Fault-tolerant Hybrid Quantum Software Systems

We are currently experiencing the Noise Intermediate-Scale Quantum (NISQ) era where quantum algorithms are forced to be small in terms of qubits and gates used. This limitation makes it infeasible to apply quantum error correction. Consequently, running quantum algorithms on NISQ devices leads to gate and measurement errors and thus unreliable calculations. In this work, we approach this problem at the software architecture level. More precisely, we instantiate well-known and established architectural patterns for fault-tolerant systems in the context of quantum computing. Our preliminary results indicate that this approach is very promising as the patterns are applicable to the context of quantum programming and allow to gain more reliable results.
Embedded solar tracking system using arduino

&#x0D; &#x0D; &#x0D; This paper describes a systematic approach to building an intelligent solar Tracking system (ISTS), for improving the performance of solar panels. The ISTS is a hybrid hardware / software prototype, which automatically provides best alignment of solar panel with the sun, to get maximum output (electricity). This method is increasing power collection efficiency by developing a device that tracts the sun to keep the panel at a right angle to its rays.The Embedded solar tracking instrumentation system by using microcontroller. The system consists of Light Dependent Resistor (LDR) sensor, DC motor .Arduino UNO microcontroller is the main component for controlling the system. The solar system will track the location of the sun to ensure the solar panel is always perpendicular with the sun therefore optimizing power output. The operation of the system on sunny and bad weather condition has been presented in this paper. The solar tracking prototype has been stated for future works.&#x0D; &#x0D; &#x0D;
Horizontal axis wind turbine

&#x0D; &#x0D; &#x0D; This paper describes a systematic approach to building an intelligent solar Tracking system (ISTS), for improving the performance of solar panels. The ISTS is a hybrid hardware / software prototype, which automatically provides best alignment of solar panel with the sun, to get maximum output (electricity). This method is increasing power collection efficiency by developing a device that tracts the sun to keep the panel at a right angle to its rays.The Embedded solar tracking instrumentation system by using microcontroller. The system consists of Light Dependent Resistor (LDR) sensor, DC motor .Arduino UNO microcontroller is the main component for controlling the system. The solar system will track the location of the sun to ensure the solar panel is always perpendicular with the sun therefore optimizing power output. The operation of the system on sunny and bad weather condition has been presented in this paper. The solar tracking prototype has been stated for future works.&#x0D; &#x0D; &#x0D;
Hybrid Artificial Neural Networks for Electricity Consumption Prediction

We present a comparative study of electricity consumption predictions using the SARIMAX method (Seasonal Auto Regressive Moving Average eXogenous variables), the HyFis2 model (Hybrid Neural Fuzzy Inference System) and the LSTNetA model (Long and Short Time series Network Adapted), a hybrid neural network containing GRU (Gated Recurrent Unit), CNN (Convolutional Neural Network) and dense layers, specially adapted for this case study. The comparative experimental study developed showed a superior result for the LSTNetA model with consumption predictions much closer to the real consumption. The LSTNetA model in the case study had a rmse (root mean squared error) of 198.44, the HyFis2 model 602.71 and the SARIMAX method 604.58.
Multi-label Convolution Neural Network for Personalized News Recommendation based on Social Media Mining

Prediction of user’s multi label interests and recommending the users interest based popular news articles through mining the social media are difficult task in Hybrid News Recommendation System (HYPNRS). To overcome this issue, this study proposes a deep learning approach - Multi-label Convolution Neural Network for predicting users' diversified interest in 15 labels using the binary relevance method. Based on labels of user’s interest, the most popular news articles are determined and their labels were clustered by mining social media feeds Facebook and Twitter along with current trends. The reliability of retrieved popular news articles also verified for recommendation. Eventually, the latest news articles catered from news feeds integrated along popular news articles and current trends together provide a recommendation list with respect to user interest. Experimental results show the proposed method diversified users interest labels prediction performance improved 5.87%, 12.09%, and 18.49% with the following state of art Support Vector Machine (SVM), Decision Tree and Naïve Bayes. The recommendation performance concerning users’ interest achieved 90%, 93.3%, 90% with social media feeds Facebook, Twitter and News Feeds accordingly.
Federate learning on Web browsing data with statically and machine learning technique

Purpose Federation analytics approaches are a present area of study that has already progressed beyond the analysis of metrics and counts. It is possible to acquire aggregated information about on-device data by training machine learning models using federated learning techniques without any of the raw data ever having to leave the devices in the issue. Web browser forensics research has been focused on individual Web browsers or architectural analysis of specific log files rather than on broad topics. This paper aims to propose major tools used for Web browser analysis. Design/methodology/approach Each kind of Web browser has its own unique set of features. This allows the user to choose their preferred browsers or to check out many browsers at once. If a forensic examiner has access to just one Web browser's log files, he/she makes it difficult to determine which sites a person has visited. The agent must thus be capable of analyzing all currently available Web browsers on a single workstation and doing an integrated study of various Web browsers. Findings Federated learning has emerged as a training paradigm in such settings. Web browser forensics research in general has focused on certain browsers or the computational modeling of specific log files. Internet users engage in a wide range of activities using an internet browser, such as searching for information and sending e-mails. Originality/value It is also essential that the investigator have access to user activity when conducting an inquiry. This data, which may be used to assess information retrieval activities, is very critical. In this paper, the authors purposed a major tool used for Web browser analysis. This study's proposed algorithm is capable of protecting data privacy effectively in real-world experiments.
User Experience

Safety is a central goal for automotive design, which legitimises the focus on the cognitive processes involved in driving and the failures that may occur. However, drivers are not just information processing organisms; instead, they also experience emotions while driving. This insight is captured by the notion of user experience and creating positive user experiences has become a major goal for automotive design, adjacent to safety. In this chapter, we discuss the notion of user experience and summarise user experience theory. Finally, we look at recent trends that go beyond the user experience.
Mobile-based aural oral skill lessons: The effects on EFL teacher trainees’ oral performance

EFL teacher-educators and teachers are seen as ignorant of teaching aural skills for referring to resource shortages is a common mechanism for their scapegoating. It hinders students’ opportunity to boost oral proficiency in the abundance of their smartphones in the classrooms to learn aural and oral skills. Hence, Moodle 3.0, a learning application, was used to create and deliver aural comprehension lessons by customizing audiovisual texts on social media to practice oral skills. A one-group-only quasi-experimental, Interrupted Time Series Design was employed to investigate the effect of mobile-based aural comprehension lessons on the general and specific oral skills’ performances of the preservice teacher trainees at Arba Minch Teacher Education College in Ethiopia. A total of 25 trainees of the 3-year diploma program were taken comprehensively as samples. To analyze data quantitatively, in addition to descriptive methods, Kruskal-Wallis, and Wilcoxson’s Signed Rank Tests were run to inferentially determine the significance of differences in the effects across the oral sub-skills and on the trainees’ general oral performance, respectively. Thus, the results disclosed that mobile-based aural oral skill lessons had positive significance in the trainees’ general oral performance without significant differences in the effects in performance across the oral sub-skills. Finally, the researchers recommended others to investigate and minimize first language interference and pronunciation problems of EFL learners. The EFL teacher trainees’ learning styles should also be further studied to understand the effect of mobile-based aural-oral skill lessons on their EFL learning/studying habits after the exposure to mobile-based lessons.
From Script to Screen: What Role for Intellectual Property in IP Movie

Aiming at the low recognition rate of traditional editing software in IP movies, this paper proposes the application of editing software based on speech recognition technology in IP movies. On the premise of making clear the style of IP movie editing, the IP movie voice signal is preprocessed based on speech recognition technology, and then the IP movie voice signal is recognized to realize the application of editing software in IP movies. The experimental results show that after preprocessing based on speech recognition technology, the recognition rate of editing software in IP movies is significantly higher than that of the control group, which can solve the problem of low recognition rate of traditional editing software in IP movies.
Exploring the scope and utility of digital proximity tracing in the effective containment of COVID-19 infection: A narrative review

The ongoing coronavirus disease-2019 (COVID-19) pandemic can be acknowledged as one of the most significant public health emergencies the world has encountered in the last few decades. The purpose of the current review is to understand the significance of contact tracing and explore the pros and cons of digital contact tracing in ensuring better containment of the COVID-19 outbreaks. A widespread search of published articles pertaining to the topic was done in the PubMed search engine and a total of 46 articles matching the objectives of the present review were identified. However, four articles were discarded because of the non-availability of the free full text, and thus 42 research papers were finally included. Digital contact tracing bridges the gap wherein we aim to expedite the process of contact tracing to identify the potential contacts of the confirmed cases. These applications are designed in such a way that they send a notification on the smartphone of a person, once the user is exposed to one or more confirmed cases of COVID-19. To conclude, in the battle against the COVID-19 infection, the international welfare agencies and national policy makers have been looking forward to the employment of digital technologies to support the ongoing public health measures for contact tracing. The approach of digital contact/proximity tracing should be considered as a supplement to conventional manual tracing. The need of the hour is to take specific measures to improve the inherent design of these apps, their implementation and demonstration of their effectiveness, which in turn will play a part in enhancing their acceptance and usability among the general population.
A theoretical discussion on modeling the number of COVID-19 death cases using penalized spline negative binomial regression approach

The Covid-19 pandemic that has occurred since the end of 2019 has changed almost the entire order of the world community, including Indonesia, in terms of health, economic, social and cultural arrangements. Based on the initial study, it is known that the number of Covid-19 deaths in East Java in 2020 has a high variance in each district/city which will cause an over dispersion problem, to overcome this, regression can be used assuming the response variable has a negative binomial distribution. Therefore, in this study we determine theoretically a model estimate of the number of cases of Covid-19 deaths in East Java due to comorbidities using a nonparametric negative binomial regression (NNBR) model approach based on a penalized spline estimator which is applied to generalized additive model (GAM). In this study, we provided steps for a local scoring algorithm to estimate NNBR model based on penalized spline estimator. In the future, the theoretical results of this study can be applied to the real data namely the number of Covid-19 death cases affected by comorbidities such as percentage of diabetes mellitus patients, percentage of hypertension over 15 years old patients, and percentage of tuberculosis patients.
Emerging Technology of Blockchain for Energy Sector

Since the Bitcoin whitepaper was published in 2009, blockchain has been the technology of the decade. This revolutionary technology assures decentralization and immutability, which helps in fraud-prevention. In addition, it provides independence from central coordination entities which further ensures transparency and accountability. Like many other sectors, there are various uses of blockchain in the energy sector such as in energy trading, smart meter, and micro grid. The current landscape study is based on qualitative exploratory research methodology and focuses on the patenting activity for the use case of blockchain in the energy/power sector.
AI-Based Career Counselling with Chatbots

The days of connecting with a service solely through a keyboard have passed. Users are increasingly using voice assistants and chatbots to communicate with systems. A chatbot is a piece of computer software that converses with humans via messaging platforms by utilising artificial intelligence. Every time the chatbot receives user input, it remembers both the input and the response, allowing chatbots with limited baseline knowledge to grow based on the responses they receive. The chatbot’s precision improves as more responses are provided. In this paper, we will discuss an intelligent chatbot that could replace the traditional method of presenting questionnaires to users to collect data in order to accurately understand the user’s interests and recommend appropriate courses and colleges on the Website TheStudentSuccessapp.com by nSmiles. Based on the user’s previous inputs, this chatbot would intelligently select questions from its question bank, attempting to predict his/her interests and career possibilities with as few questions as possible. When the nSmiles psychometric engine finds an interest, the chatbot will deliver a short intermittent status report to the user, along with the option to examine the recommended list of courses and colleges, before moving on to explore other interests. Finally, a complete report with a list of courses and colleges recommended to the user based on all of his/her interests and choices would be presented. Several other features like email generation and graph visualisations are also included.
A Novel Framework for Malpractice Detection in Online Proctoring Environment

As a result of both pandemics and the advantage of a remote examination, job interviews have become popular and necessary. These systems are being used by the majority of companies and academic institutions for both recruitment and online exams. In this study, a new virtual assessment system uses deep learning to continuously monitor. Physical locations without the use of a live proctor, however, conducting exams in a safe environment are one of the main disadvantages of remote examination systems. In this work, there is a pipeline for an online interview and exam fraud analysis. Only a video of the candidate is required by the system, which is recorded during the exam. Face detection, recognition, object detection, and tracking algorithms are part of this work. The proposed work focus on techniques for identifying malpractices during online exam.
新聞史論、時事評析與新聞教育：卓南生的傳播研究與實踐

&lt;p&gt;學者卓南生以新聞史研究和國際時評知名，歷任新加坡《星洲日報》社論委員與《聯合早報》東京特派員；而從上世紀80年代末在日本東京大學新聞研究所任教開始，投身中、日新聞教育三十餘年，迄今仍然以北京大學新聞學研究會為平臺，與青年學子保持對話。代表性著作為1990年、1998年、2002年及2015年出版的《中國近代報業發展史（1815-1874）》，與2010年、2020年出版的《東亞新聞事業論》等。本文從他幼年時期目睹南洋政治的經歷出發，並在日本與亞洲社會的變遷背景下，勾勒出卓南生在史論治學、時評寫作和新聞教育方面的思想觀點；而從中國報業的新聞發生史開始，經過長時期對日本社會、華文報業的親身經驗，及在時事評析與新聞教育中，發展出清晰穩固的亞洲視角，與論從史出的歷史是非觀。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;Toh Lam Seng is a renowned scholar for his research on the history of journalism and a famous international affairs columnist. He worked as an editorial board member of Singapore&amp;rsquo;s Sin Chew Jit Poh and Lianhe Zaobao&amp;rsquo;s Tokyo correspondent. Starting from the late 1980s, when he began teaching at the Institute of Journalism and Communication Studies of the University of Tokyo late 1980s, Dr. Toh has been devoting himself in journalism education in China and Japan for more than 30 years. Currently, he still participates in the Institute of Journalism, Peking University and uses it as a platform to engage young scholars and students in dialogues. His representative works include The Beginnings of Modern Chinese Newspapers and their Development in the 19th Century (1815-1874) published in 1990, 1998, 2002, 2015, and East Asian Journalism published in 2010 and 2020. This study starts from Toh&amp;rsquo;s childhood experience, in which he witnessed the politics of Southeast Asia. Against the backdrop of social changes of Japan and other Asian societies, this study outlines Toh&amp;rsquo;s thoughts and views on historiography, column writing on international affairs, and journalism education. With his work on the history of the development of newspaper industry in China, his long years of personal experience of Japanese society and Chinese newspaper industry, and his career in international affairs column writing and Journalism education, he developed a clear and stable Asian perspective and an emphasis on historical evidence and critical analysis of history. &lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
串流運動：新冠疫情下臺灣運動紀錄片之發展脈絡與契機

&lt;p&gt;在疫情期間，講述籃球的《最後之舞》（The Last Dance）紀錄片掀起一股觀看風潮，本研究藉此契機，梳理臺灣運動紀錄片發展的歷史脈絡與社會條件，再則透過文本分析及深度訪談，發掘未來可能的發展方向及策略。研究發現，臺灣運動紀錄片拍攝項目雖以「棒球」居多，但整體上仍具備多樣性與獨特性；議題則多偏向於偏鄉青少年教育困境及運動輸贏「價值」，不若國外同類型影片的取材廣泛。而在臺灣訂閱式影音串流平臺間，因為強烈的商業考量，被播放的本土運動紀錄片重覆性極高，因此實難做為發展臺灣運動文化的常態播映管道，一如在主流院線播放；拍攝、行銷等關注者應當依據影片特性及目的，將規模較小且具專業特色的影音串流平臺，以及社群影片分享平臺納入推廣選項，以達到觸及更多網路觀眾之目的。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;The popularity of the basketball documentary The Last Dance during the pandemic was the inspiration for this study to examine the historical context and social conditions for the development of sports documentaries in Taiwan. This study explored the possible directions and strategies of future development for Taiwanese sports documentaries through textual analysis and in-depth interviews. The findings indicate that baseball was the most popular type of sports in Taiwan&amp;rsquo;s sports documentaries, although the overall types of sports presented in the films were diversified and unique. The issues presented in the documentaries centered mostly on the education for rural youth and the values of winnings and sportsmanship and were not as diversified as those in the foreign sports documentaries. Due to business concerns, the available Taiwanese sports documentaries on the Taiwanese subscription-based streaming platforms overlapped highly. For the purpose of developing sports culture in Taiwan, subscription-based streaming platforms and mainstream movie theaters should not be the primary venues for Taiwanese sports documentaries. Filmmakers and marketing professionals should consider the characteristics and objectives for each documentary film and include small-scale documentary streaming platforms and social media video platforms as options of screening venues in order to reach more online audience.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;