Reviewerly/exHarmony huggingface dataset:
Towards Ubiquitous Serverless Computing: Fast Large-Scale Machine Learning and Optimal Pricing for the Cloud

Author(s): Gupta, Vipul | Advisor(s): Ramchandran, Kannan; Courtade, Thomas | Abstract: Serverless computing platforms represent the fastest-growing segment of cloud services and are predicted to dominate the future of cloud computing. However, the real-world applications of serverless systems are somewhat constrained due to several inherent bottlenecks such as their stateless nature, frequent occurrence of stragglers, naive resource allocation and pricing of computing resources, etc. The broader aim of this dissertation is to propose techniques to mitigate such bottlenecks and make the use of serverless computing ubiquitous. In particular, we focus on four applications that relate to large-scale serverless computing and describe them as follows.Total time for end-to-end distributed computation in such systems suffers due to a subset of slower workers, also referred to as stragglers. First, we propose straggler mitigation schemes for large-scale numerical linear algebra on serverless systems. Serverless systems allow users to massively scale the number of workers, but the total computation time is further exacerbated by high-communication latencies and the stateless nature of Function-as-a-Service (FaaS) platforms. Second, we further propose algorithms for large-scale convex optimization that are amenable to serverless systems. Recently, serverless computing --- due to its elasticity, scale, and ease of management --- has garnered significant traction from the industry and academia as a platform to train deep neural networks. Third, we further propose algorithms for massive scale non-convex optimization for training deep neural networks that take advantage of the scale of the serverless platform while mitigating communication costs. Finally, any ubiquitous platform is not viable until it serves the needs of the masses. In game-theoretic terms, a commercial platform should provide the required quality of services to customers while maximizing their utility (or satisfaction). Fourth, we propose principled yet practical schemes for allocating and pricing resources in serverless platforms.
Reasoning About Agents That May Know Other Agents’ Strategies

We study the semantics of knowledge in strategic reasoning. Most existing works either implicitly assume that agents do not know one another’s strategies, or that all strategies are known to all; and some works present inconsistent mixes of both features. We put forward a novel semantics for Strategy Logic with Knowledge that cleanly models whose strategies each agent knows. We study how adopting this semantics impacts agents’ knowledge and strategic ability, as well as the complexity of the model-checking problem.
STUDENT RELATIONSHIP MANAGEMENT SYSTEM OF THE NEW NORMAL BASED ON CLOUD COMPUTING

Aim: The purposes of this research were 1) to design the student relationship management system of the new normal based on cloud computing, 2) to develop the student relationship management system of the new normal based on cloud computing, and 3) to assess the student relationship management system of the new normal based on cloud computing.Methods: The research instrument used was the model of assessment system. The sample group of subjects were the students of King Mongkut’s University of Technology North Bangkok and nine experts evaluated the system quality were selected through the purposive random sampling method from three different fields: student relationship management, cloud processing, and informative technology. The data was analyzed by simple statistics: means and standard deviations.Results: The research found that 1) the participants of the student relationship management system of the new normal based on cloud computing were divided into three groups: students, teachers and office staff, 2) the student relationship management system of the new normal based on cloud computing consisted of four development phases, i.e., planning, analysis, design and implementation, and seven modules, i.e., calendar management module, online and face to face management module, assessment management module, representation management module, activity management module, collaborate management module and knowledge management module and 3) the overall efficiency of the student relationship management system of the new normal based on cloud computing was at a high level (xEÂ�? = 4.60), and the standard deviation (S.D.) was of 0.62.Conclusion: This could be concluded that the performance of the student relationship management system of the new normal based on cloud computing was efficient.Practical implications: Due to the pandemic of Covid-19, social distance is required and it is necessary to use this relationship management system to solve problems of the conventional teaching and learning and enhance educational efficiency. In addition to the face-to-face online classroom teaching, there are also tools to support the students’ learning activities and group assignments, e.g., media devices, videos and other teaching and learning materials and also to facilitating the students and the teachers through the calendar system. The system could be implemented to overcome educational problems especially the situation of the covid pandemic.
Multi-view Keyframe Extraction Techniques: A Comparative Analysis for Closed Room Scenario

The enormous library of videos is developing by the day in modern era. Analyzing such vast amounts of data is often a time-consuming procedure. Access to user-friendly information is an important part of making effective use of video content. This contributes to the development of the field of study known as video summarization. This paper introduces various methods of extracting keyframes from a large video and by embedding the keyframes in a temporal graph, a summarized video would be generated.
FDI, ECONOMIC FREEDOM AND ECONOMIC GROWTH OF NIGERIA

This paper investigates Foreign Direct Investment, Economic Freedom and Economic Growth of Nigeria between 1995 and 2018. Specifically, the data on: Foreign Direct Investment (FDI) inflows, Economic Freedom (Aggregate index) and the data on real gross domestic product (RGDP) were used during the analysis. Time-series data were tested for stationarity using the Augmented Dickey-Fuller Unit Root test method. Vector Autoregressive (VAR) estimation method was adopted to examine the effect of FDI, Economic Freedom on Economic growth. The interactive effect of FDI and Economic Freedom on Economic growth was determined using regression analysis while Granger Causality test method was adopted for determining the causality relationship among the variables. The result of the Vector Autoregressive (VAR) suggests that both FDI and Economic freedom do not have a significant effect on economic growth in Nigeria. The result of regression analysis shows that the joint coefficient of both FDI and EF is negative and not significant. The result of Granger Causality revealed that there is a uni-directional relationship between RGDP and FDI and between EF and FDI respectively. The research recommends that the federal government of Nigeria should adopt appropriate foreign trade strategies to enhance the impact of FDI on economic growth in Nigeria.
History Re-Experienced: Implementing Mixed Reality Systems into Historic House Museums

As immersive technologies have become ubiquitous today, traditional museums are finding success augmenting existing exhibits to increase visitors’ satisfaction. However, due to the immutable nature of house museums, and their tendency to place visitors in direct contact with historical artifacts, museum managers are seeking original approaches to cultural preservation. Implementing mixed reality systems into historic house museums is one such approach. The goal of this study is to develop and test a conceptual matrix that guides how designers use the affordances of mixed reality systems to create experiences that align with the range of historical narratives found in house museums. Experiences that can contribute to improving visitors’ satisfaction, self-interpretation, and understanding of the homeowner’s life and the community within which they lived. Building on human-centered design methods, the researcher developed and tested a prototype of an augmented reality (AR) mobile application centered on the Pope House Museum in Raleigh, North Carolina. The outcome of the research suggests house museum visitors should have agency in deciding the lens through which they experience the variety of historical narratives present in the home.
Android-based Mobile Multimedia Application Development Training

&lt;p align="center"&gt;Covid-19 demands the use of technology as an online learning media tool. The technology that becomes a low-cost developer is the Android Technology operating system. The main target of this community service activity is the 3rd &amp;amp; 5th semester Computer System Study Program students at the Faculty of Science and Technology at the Panca Budi Development University in using Android technology, where learning about Android has been carried out but not maximized in building a Mobile Application. The method used is to provide training and demonstrations in making Multimedia Applications using Android Studio with online media support in the form of Zoom, YouTube, and Google Drive links. The results of the feedback response to material questions submitted by the resource person were 67% very good, participant responses to the material presented were 41% good, the relationship between material and participant needs was 59% very good, the relationship between material and applications that could be absorbed by participants was 54% very good, the linkage of the material with needs is 42% good, the presentation technique of the presenter is 56% very good, the time spent by the presenter is 44% giving a good response, the clarity of the material is 59% clear, the interest of the participants is 47% good, and overall satisfaction level of 51% gave a satisfied response to the training activities.&lt;/p&gt;
Design And Analysis Of An Efficientbit Based Object Detection

Video understanding can be viewed with useful contextual information in static cameras beyond a few seconds. Subjects may conduct similarly over a number of days and background objects remain static. The frequency of sampling is low, often less than a frame per second, and occasionally irregular because of the power and storage limitation of the motion trigger. If they are to be effective in this setting, models must be robust to irregular sampling rates. Users have developed a new range of EfficientDet Object detectors based on these optimizations and better backbones to improve efficiency over many resources compared to state-of-the-art. CentreNet is the highest speed-precision disruption in MS COCO at 28,1% CA for 142 FPS, 37,4% AP for 52 FPS and 45,1% AP for multi-scale tests with 1.4 FPS. We use the same approach to estimate the 3D border box in the KITTI benchmark and human position in the COCO keyboard dataset. With sophisticated multi-stage methods, our method works competitively and runs in real-time.
국내 지진관측기록의 P파를 이용한 지진현장경보기술 적용

Purpose: This study aims to derive a predictive empirical equation for PGV prediction from P-wave using earthquake records in Korea and to verify the reliability of Onsite EEW. Method: The noise of P wave is removed from the observations of 627 seismic events in Korea to derive an empirical equation with PGV on the base rock, and reliability of Onsite alarms is verified from comparing PGV's predictions and observations through simulation using the empirical equation. Result: P-waves were extracted using the Filter Picker from earthquake observation records that eliminated noises, a linear regression with PGV was used to derive a predictive empirical equation for Onsite EEW. Through the on-site warning simulation we could get a success rate of 80% within the MMI±1 error range above MMI IV or higher. Conclusion: Through this study, the design feasibility and performance of Onsite EEWS using domestic earthquake records were verified. In order to increase validity, additional medium-sized seismic observations from abroad are required, the mis-detection of P waves is controlled, and the effect of seismic amplification on the surface is required.
포스트에디팅 결과물에 나타난 오류 고찰 - AI 학습용 한영 번역 말뭉치를 대상으로

With a keen interest in the quality of MT output, errors in raw MT output have received much attention in domestic translation studies. However, errors in post-edited output have rarely been discussed, although a considerable amount of errors in raw MT output remain uncorrected even after the post-editing task. Against this backdrop, this study aims to investigate errors in post-edited output with Korean-English parallel translation corpus for AI training, released in 2019 by the National Information Society Agency. For this purpose, 300 parallel sentences with errors were collected in economic news corpus and then classified by error type. Analysis results showed a wide array of errors ranging from accuracy to readability, indicating the need to examine errors in post-edited output and major factors affecting the post-editing process.
Tecnología de formación en la autoorganización de los estudiantes en la enseñanza de lenguas extranjeras

This paper examines the structure, criteria of self-organization, synergetic conditions and theoretical description of the authors’ technology in the process of teaching foreign languages at technical institute. To achieve this goal, a set of scientific methods: theoretical analysis of papers on the problem; diagnostic and statistical methods to process data and results of pedagogic observation of forming students’ self-organization competences were applied. The novelty of the authors’ flexible technology is based on personal-oriented education and synergetic methodology to meet modern education requirements to a person’s sustainable development in education environment. The results contribute to synergetic methodology of forming self-organization and didactic aspects of teaching foreign languages. Statistically verified data confirm appearance of students’ self-organization competency. The efficiency of authors’ technology is proved experimentally. Implications for conceptualization and measurement of self-organization are determined. In this context, the study has a theoretical foundation and practical application.
EVALUATION OF DIGITAL LITERACY STATUS OF PROSPECTIVE TURKISH TEACHERS IN TERMS OF VARIOUS VARIABLES

In this study, it is aimed to examine the digital literacy status of prospective Turkish teachers in terms of various variables.For this purpose, the digital literacy status of prospective Turkish teachers was analyzed according to the class levels, gender, technology usage levels, daily internet usage period and having a social media account variables. The scanning model was used in the research. “Digital Literacy Scale” which was developed by Ng (2012) and adapted by Hamutoglu, Gungoren, Uyanik, Erdogan (2017) was used as the data collection tool. The study groupy consisted of 257 prospective Turkish teachers studying at 5 different state universities. The data were collected in the fall semester of the 2018-2019 academic year. The data were analyzed by using SPSS for Windows 22.0 programme. While there was no significant difference in the class levels and gender variables, a significant difference was observed in the daily internet usage levels, technology usage levels and having a social media account variables. The results were discussed within literature review and suggestions were made about the study.
Pelatihan Kemahiran Berbahasa Indonesia Bidang Paragraf Bagi Guru Sekolah Dasar Negeri Se-Kabupaten Seluma

The purpose of this Community Service is to provide experienced knowledge and skills of Indonesian Language Proficiency in the Indonesian Language Paragraph Grammar for Public Elementary School teachers in Seluma Regency. The venue for the activities at the Arnanda hotel, Tais Seluma Market. Implementation time is on Thursday, March 21, 2019. The target of this activity is a change in attitudes, knowledge, and skills in writing paragraphs in Indonesian for public elementary school teachers in Seluma Regency, with a total of 50 participants. The activity method uses a training method through lectures, question and answer, and guided discussion in an intensive-participatory manner. The activity was carried out through the presentation of the paragraph grammar material from the resource persons followed by practice in writing the parts of the paragraph requirements in good Indonesian. The implementation of this training activity consists of three stages, namely (1) the planning stage, (2) the implementation stage, and (3) the evaluation and reporting phase with the achievement target, namely the preparation of reports on the results of community service activities in writing good Indonesian language paragraphs. The results of community service activities can be concluded that there has been a change in attitudes, knowledge, and skills of public elementary school teachers in Seluma Regency in writing paragraphs in Indonesian. This can be seen (1) the ability of participants to compile written products on good Indonesian paragraph grammar as a form of change in knowledge and skills which in the pretest and posttest activities of paragraph grammar increased from high to very high categories, and (2) related with a change in mindset that participants have shown enthusiasm, motivation, and enthusiasm in participating in training activities as evidences relevant to the results of answers to closed questions which generally state useful.
Research on the technology of optical motion capture system for robot inspection

Optical motion capture systems have been widely used in biomechanical, medical treatment, uav control and other fields. At present, the accuracy of optical motion system has been studied, but the relationship between the layout of optical camera in the detection area and the detection space boundary and the accuracy stability of the calibration system within the detection space has not been studied. In this paper, the optical motion capture system is composed of 8 Optitrack Prime 13 cameras arranged in a single ring with equal height and equal spacing. According to the size of the detection object, the pitch angle of the camera is adjusted through calculation, and the maximum detection volume is determined. The system is calibrated within the detection volume to upgrade the calibration accuracy. The quantization of the layout data of the optical motion capture system makes the system test data stable and reproducible, and the consistency of the test system parameters is realized.
LIABILITY OF ARTIFICIAL INTELLIGENCE IN INDIA

In the present century, the technological know-how has been changing and emerging rapidly. The replacement of various human activities by robots and computers is common and more pragmatic, given the complexities of the given age. As long as these robots and computers act as a mere tool of simplifying our lives, there is not much to ponder upon. However, when these computers and robots start thinking for us, this is when the matter becomes complex from various outlooks. When such machines are programmed to perform defined thought processes, they fall in the category of ‘Artificial Intelligence’. What differentiates ‘Artificial Intelligence’ from other machines is that the former is capable of imitating intelligent behavior as AI entities are the replication of human behavior and cognitive processes on a machine. It can be said safely that presently, AI entities are becoming more and more integral for disentangling various processes and simplifying human lives. However, since these machines have been taught to think and act for us and since they are carrying out large-scale operations for us, there is always a possibility that such an entity commits an act which makes it liable under any of the laws of the country. The moot point which arises here is of the liability of such an entity. Can an AI entity be made liable in such a situation? Can it be punished? By way of the present book chapter, the authors attempt to assess the fundamental impact which such a digitalization brings on the liability laws of our country. Apart from this, the authors will also study if there are any existing civil and criminal liability regimes in light of emerging use of “thinking” digital technologies in India. And if at all such liability regimes exist, then to ascertain if the same offer basic protection to victims who have suffered damage due to the operation of AI technology. The chapter will be concluded by highlighting the facets of liability issues in matters of digitalization and how a much more fair, equitable and appropriate response towards the interests of individuals who have suffered harm due to such can be adopted.
BROS: A Layout-Aware Pre-trained Language Model for Understanding Documents

Understanding documents from their visual snapshots is an emerging problem that requires both advanced computer vision and NLP methods. The recent advance in OCR enables the accurate recognition of text blocks, yet it is still challenging to extract key information from documents due to the diversity of their layouts. Although recent studies on pre-trained language models show the importance of incorporating layout information on this task, the conjugation of texts and their layouts still follows the style of BERT optimized for understanding the 1D text. This implies there is room for further improvement considering the 2D nature of text layouts. This paper introduces a pre-trained language model, BERT Relying On Spatiality (BROS), which effectively utilizes the information included in individual text blocks and their layouts. Specifically, BROS encodes spatial information by utilizing relative positions and learns spatial dependencies between OCR blocks with a novel area-masking strategy. These two novel approaches lead to an efficient encoding of spatial layout information highlighted by the robust performance of BROS under low-resource environments. We also introduce a general-purpose parser that can be combined with BROS to extract key information even when there is no order information between text blocks. BROS shows its superiority on four public benchmarks -- FUNSD, SROIE*, CORD, and SciTSR -- and its robustness in practical cases where order information of text blocks is not available. Further experiments with a varying number of training examples demonstrate the high training efficiency of our approach. Our code will be open to the public.
Inculcating The Habit Of Reading Newspapers Among College Students And Understand Its Influence On Content They Prefer

More specifically, for college students and textbooks, newspapers act as a fundamental source of information. Many students read newspapers in printed form or online copy as well. Every newspaper copy holds some useful information for every reader besides its age, gender, profession, and interest. So, for college students, it acts as a source of useful information to access updates from health, fitness, entertainment, sports, career and education, market, and business as well. Here, the main motive of the study is to teach the habit of reading newspapers among college students. Also, the aim was to understand the influence of reading newspapers on choosing the content by students. The entire study shows that students use newspapers to obtain the interesting information to widen their knowledge.