Reviewerly/exHarmony huggingface dataset:
Learning Polytopes with Fixed Facet Directions

We consider the task of reconstructing polytopes with fixed facet directions from finitely many support function evaluations. We show that for a fixed simplicial normal fan, the least-squares estimate is given by a convex quadratic program. We study the geometry of the solution set and give a combinatorial characterization for the uniqueness of the reconstruction in this case. We provide an algorithm that, under mild assumptions, converges to the unknown input shape as the number of noisy support function evaluations increases. We also discuss limitations of our results if the restriction on the normal fan is removed.
SMILE: A Cost-Effective System for Serving Massive Pretrained Language Models in The Cloud

Deep learning models, particularly pre-trained language models (PLMs), have become increasingly important for a variety of applications that require text/language processing. However, these models are resource-intensive and often require costly hardware such as dedicated GPU servers. In response to this issue, we present SMILE, a novel prototype system for efficient deployment and management of such models in the cloud. Our goal is to build a cloud platform from which tenants can easily derive their own custom models, and rent PLM processors to run inference services on these models at reduced costs. To facilitate this, we present a co-design of cost-effective storage and computation scheme for managing massive customized PLMs with constrained hardware resources via effective resource sharing and multiplexing. Our system consists of four core components: vPLM creator, vPLM storage appliance, vPLM trainer, and vPLM processor, which allow tenants to easily create, store, train, and use their customized PLM in the cloud without the need for dedicated hardware or maintenance. In particular, vPLM processors are virtualized from a physical machine, and are designed to have a multi-tenant nature, enabling efficient utilization of resources by precomputing the intermediate representation of PLMs and using adapters to provide customization instead of training the entire model. This allows tenants to host their PLMs in the cloud at minor costs. In our demonstration, we show that over 10,000 models can be hosted on one single machine without compromising the inference speed and accuracy. Overall, our system provides a convenient and cost-effective solution for tenants to host and manage PLMs in the cloud for their customized tasks.
An Exploration of The Relationship Between Mindfulness and Stress Levels of Taekwondo Athletes by Different Variables

This study aimed to explore the relationship between mindfulness and stress levels in taekwondo athletes in light of different variables.To this end, 532 taekwondo athletes (246 female and 286 male) were selected through convenience sampling.Data for the assessment of mindfulness were collected through the Mindfulness Inventory for Sport, developed by Thienot et al. ( 2014) and adapted to Turkish by Tingaz (2020).The Depression Anxiety Stress Scales, developed by Lovibond and Lovibond (1995), and adapted to Turkish by Akın and Çetin (2007), were used to assess stress.Descriptive statistics (i.e., percentages and frequencies) were used to display the distribution of the participants' background information, and skewness-kurtosis values were checked for data normality.Due to the data's non-normality, Mann-Whitney U and Kruskal-Wallis tests were utilized along with descriptive statistics.Findings indicated significant differences in the mindfulness levels of the participants by age, athletic background, category, and previous injuries.In addition, participants' stress levels differed significantly by age, athletic background, and category.Limitations of the study were discussed, and recommendations for future studies were made accordingly.
An Open-Source 2D Digital Image Correlation Software: Case Study on the Hyperelastic Behaviour of Silicone-Based Material

Digital Image Correlation (DIC) is an optical-numerical method used to compute displacement and strain fields of target surfaces. This method has been widely implemented in the study of structures and to perform inspections, at several observation scales. Several software have been already proposed to carry out DIC measurements. In this study, a new integrated open-source DIC software is presented, so-called iCorrVision-2D. This DIC software includes a build-in grabber and post-processing modules that are not usually available on other open-source or commercial DIC software. The accuracy of this software is verified using an experimental dataset of silicone-based specimens subjected to uniaxial tensile test. The isotropic hyperelastic behaviour of the silicone-based specimens was investigated using the Neo-Hookean, Mooney-Rivlin, Lopez-Pamies, Ogden and Yeoh models. Results indicate that this software can be efficiently used to reconstruct the displacement and strain maps, yielding consistent mechanical properties for the hyperelastic material. This case study is important to illustrate the reliability of DIC on measuring deformations that have been used to extract relevant mechanical properties. This software can then be used consistently for other engineering applications.
Uncoded Video Data Stream Denoising in a Binary Symmetric Channel

In this paper, a method for denoising an uncoded video stream in a binary symmetric channel is considered. When a bit of information is damaged, noise similar to impulse noise occurs with a certain probability. This work considers a model for transmitting visual data through a binary symmetric channel, where the noise characteristic corresponds to impulse noise distributed over the image with random values. Both random variables are distributed uniformly, both in brightness and in spatial location. In the proposed method, the distorted pixel is detected by comparing pixels inside the filter mask. Pixels are compared by their brightness value, and the remoteness of pixels within the detector area is also taken into account. The distance between pixels is calculated using the Euclidean metric. The local area of the filter takes into account pixels from the previous and next frames. Video frame recovery is performed using adaptive median filtering. A comparison was made with known methods. Based on the mean square error (MSE) and structural similarity index (SSIM) characteristics, it was shown that the proposed method copes with the task of denoising visual data better than the known methods.
Efficient Maintenance of Hospital Records by Entrusted Proof of Work Algorithm in Block Chain Technology

This century resulted in a surge of changes and revolution in technology by and large in the networking domain. As a result, metadata became an integral part of the service exchange cycle in service domains such as networking integration, management, and maintenance, and information security. The recent pandemic posed threats to many service sectors, namely health care (a reported increase in data breach and identity theft of 37%), proving the importance of data privacy and immutability. The metadata obtained entail the interoperability of data records. Thus, blockchain-based innovations emancipate data breaches, data mutability, and interoperability crashes of sensitive data. In this chapter, we will encounter case studies of health care breaches, a review of the existing literature, and work flow of the existing applications. Work that proposes consistency in interoperability and immutability, along with consensus protocols for decentralization also gains from blockchain environs. The flow determines the patient or stakeholder’s sensitive specifics can be classified and viewed with the authentication or authenticated personnel in sine qua non. The work provides preferable health care management and is unquestionably superior to the Environmental Health Safety (EHS) service.
MediVizor: Visual Mediation Analysis of Nominal Variables

Mediation analysis is crucial for diagnosing indirect causal relations in many scientific fields. However, mediation analysis of nominal variables requires examining and comparing multiple total effects and their corresponding direct/indirect causal effects derived from mediation models. This process is tedious and challenging to achieve with classical analysis tools such as Excel tables. In this study, we worked closely with experts from two scientific domains to design MediVizor, a visualization system that enables experts to conduct visual mediation analysis of nominal variables. The visualization design allows users to browse and compare multiple total effects together with the direct/indirect effects that compose them. The design also allows users to examine to what extent the positive and negative direct/indirect effects contribute to and reduce the total effects, respectively. We conducted two case studies separately with the experts from the two domains, sports and communication science,and a user study with common users to evaluate the system and design.The positive feedback from experts and common users demonstrates the effectiveness and generalizability of the system.
Review of optimization methods for supervised deep learning

Abstract： Deep learning technique has been developing intensively in big data era.However， its capability is still chal• lenged for the design of network structure and parameter setting.Therefore， it is essential to improve the performance of the model and optimize the complexity of the model.Machine learning can be segmented into five categories in terms of learn• ing methods： 1) supervised learning， 2) unsupervised learning， 3) semi-supervised learning， 4) deep learning， and 5) reinforcement learning.These machine learning techniques are required to be incorporated in.To improve its fitting and 中图法分类号： TP391
AN ANALYSIS OF USING MINIMAL PAIRS IN PRONOUNCING CONSONANTS AND VOWELS

This research aimed to describe pronunciation error and correct pronunciation in English consonants and vowels by the participants on Phonology subject. The data were from the fourth semester students of English education study program. Furthermore, all of the students that participated there were 12 students. This research applied a descriptive study with qualitative approach. The data of this research was collected by test and documentation. To conduct the test, the researcher chose minimal pair words which are focused on thirteen English consonant sounds: /ð/, /t/, /d/, /s/, /z/, /f/, /v/, /k/, /g/, /ʔ/, /tʃ/, /dʒ/, and /h/. Then, nine vowel sounds, there were : /iː/, /ɪ/, /e/, /o/, /ɔː/, /eɪ/, /ɑː/, /әʊ/, and /æ/. Additionally, the documents consisted of students’ voice such as audio recorded. The research finding were analyzed how many of them who made error in pronouncing the minimal pairs words. There were 3 steps in analyzing data, such as data reduction, data display, and conclusion/verification. For the result of this research, it shows that the dominant pronunciation errors made by the fourth students semester was in English consonant sounds /s/ and /z/. The students who made pronunciation error was 91,7%. Whereas, the dominant errors pronunciation of minimal pair words by the participants in vowel sounds were /æ/ and /eɪ/. The students made pronunciation error was 91,7%.Keywords : Pronunciation, minimal pairs.
Peran kepala sekolah dalam pengelolaan perpustakaan untuk mendukung pembelajaran di masa pandemi COVID-19

Introduction. This research is to examine perspectives of teachers, students and librarians toward leadership roles regarding information technology development in school libraries in supporting learning in the era of the COVID-19 pandemic.&#x0D; Data Collection Methods. This study used a quantitative descriptive approach with 100 respondents. The sampling technique used the probability sampling with simple random sampling method. &#x0D; Results and Discussion. The role of school leaders in developing library governance has not yet been significant so that libraries could not contribute effectively to the learning process. During the pandemic, the role of IT is needed by teachers and students, particularly for the library users to finish their assignment from home. Users also need to have the library updates regarding books. Many teachers and students do not understand how to use of information technology in the library including how to access or search information (online).&#x0D; Conclusion. School leaders play an active role in improving the quality of the library as a source of learning to create benefits for the school community. The discussion on the abnormal situation leadership among school leaders.
Block-chain based Secure Data Access over Internet of Health Application Things (IHoT)

The medical sector actively changes and implements innovative features in response to technical development and revolutions.Many of the most crucial elements in IoT-connected health services are safeguarding critical patient records from prospective attackers.As a result, BlockChain (BC) is gaining traction in the business sector owing to its large implementations.As a result, BC can efficiently handle everyday life activities as a distributed and decentralized technology.Compared to other industries, the medical sector is one of the most prominent areas where the BC network might be valuable.It generates a wide range of possibilities and probabilities in existing medical institutions.So, throughout this study, we address BC technology's widespread application and influence in modern medical systems, focusing on the critical requirements for such systems, such as trustworthiness, security, and safety.Furthermore, we built the shared ledger for blockchain-based healthcare providers for patient information, contractual between several other parties.The study's findings demonstrate the usefulness of BC technology in IoHT for keeping patient health data.The BDSA-IoHT eliminates 2.01 seconds of service delay and 1.9 seconds of processing time, enhancing efficiency by nearly 30%.
Smart Wheelchair with Advanced Assistance and Governing System for Disabled

This smart wheelchair model can be used by quadriplegic people to move comfortably. Sufferers with paraplegic or leg impairment face issue in achieving locations. A few people try and use a walker in many instances, the patient may also loose balance and fall and injure themselves. To avoid this state of affairs, our model can be used. This version is powered through a raspberry pi; it is geared up with LCD and RF module and atmega controller, Servo motor, a DC motor and a wheelchair. The user just need to touch the displayed options for movement. The transmitter and receiver circuit communicate using RF communication. This version additionally has an emergency characteristic; the person ought to press the alert button in case of emergency. The patient can then circulate the usage of button instructions. The patient can use the forward and backward buttons to move forward or backward, and can press the stop button to stop at a certain point and to make the chair stand, the patient needs to click on stand up button. so that the person sitting on the wheelchair can stand allowing to pick any items without any help.
The Adaptation of Concept Drift: A Fit Prediction Algorithm Based on Local Optimum

With the rapid development of Internet industry, the learning methods based on data stream have attracted more and more attention owing to their great application value in many industries such as banking, insurance, and telecom industry. In the process of learning from stream data, one of the most significant challenges is how to adapt to the so-called concept drift which means that the data stream distribution changes over time in unpredictable ways. To deal with the problem, some methods have been put forward. However, most of them pay more attention to the whole entity of a given model and overlook the impact of local data on the model. In this article, we propose a novel ensemble algorithm to overcome the problem of ignoring local samples in previous methods, namely, the fit prediction algorithm based on local optimum (FPLO) which uses the information of local data to fit (predict) a concept drift. Furthermore, an adaptive method based on the so-called concept changing rate is proposed to choose those classifiers of suitable sizes to overcome the problem of selecting too much or too little historical drift information in previous methods and to make the prediction more accurate. The experimental results on nine synthetic stream datasets and eight real-world stream datasets which all have the concept drift problem show that our FPLO is able to tackle the problem more effectively in comparison to other state-of-the-art methods.
Keterampilan literasi informasi pustakawan Universitas Negeri Malang dalam implementasi layanan berbasis inklusi sosial

Introduction. Inclusion-based libraries aim to improve information literacy, quality of life, and community welfare, as well as become a place for lifelong learning. The librarians need to have sufficient information literacy skills in implementing social inclusion-based services.&#x0D; Data Collection Methods. Qualitative case study approach was used. The data was collected by interviews, observations, and documentation from librarians at the Malang State University Library.&#x0D; Data Analysis. We analyzed our data by using data reduction, data presentation, and conclusion.&#x0D; Results and Discussion. Information literacy skills of librarians were examined by several indicators such as identify, scope, plan, gather, evaluate, manage, and present. Those indicators have not been applied, particularly to the implementation of social inclusion-based services. Five indicators of information literacy skills can be applied properly including identification of needs information, determining the scope of information needs, planning information retrieval strategies, gathering information sources, as well as evaluating. In this study, skills in managing and presenting information have not been implemented properly.&#x0D; Conclusion. The information literacy skills of librarians in social inclusion-based services have not been maximized due to absence of competency development, lack of librarians, and absence of collections and facilities that support all information needs based on the user.
Pengaruh Pembelajaran Daring dan Locus Of Control Internal Terhadap Motivasi Belajar Mahasiswa Pada Program Studi Pendidikan Ekonomi FKIP Universitas Palangka Raya

This research aimed at investigating the effect of online learning and Locus of Control Internal to Students learning Motivation in Economic Education Study Program, the Teaching and Education Faculty, Palangka Raya University. The research method used was expos facto in which the source of data were the students of 2019 and 2020 entrance year. The research result showed that the Online learning gave the partial contribution more to the Students lerning motivation as 71,40%, meanwhile Locus of Control internal contributed 17,81%. The analysis of simultaneous testing was done later on and gained the score of Fvalue &gt; Ftable (31,388 &gt; 3,12) with the significance level 0,000 (r &lt; 0,05). The conclusion of this research was 31,388% of Economic Education Study Program students’ learnng motivation affected by Online learning and Locus of Control internal and the rest was affected by other external factors.
Crafting the MPEG metrics for objective and perceptual quality assessment of volumetric videos

Efficient objective and perceptual metrics are valuable tools to evaluate the visual impact of compression artifacts on the visual quality of volumetric videos (VVs). In this paper, we present some of the MPEG group efforts to create, benchmark and calibrate objective quality assessment metrics for volumetric videos represented as textured meshes. We created a challenging dataset of 176 volumetric videos impaired with various distortions and conducted a subjective experiment to gather human opinions (more than 5896 subjective scores were collected). We adapted two state-of-the-art model-based metrics for point cloud evaluation to our context of textured mesh evaluation by selecting efficient sampling methods. We also present a new image-based metric for the evaluation of such VVs whose purpose is to reduce the cumbersome computation times inherent to the point-based metrics due to their use of multiple kd-tree searches. Each metric presented above is calibrated (i.e., selection of best values for parameters such as the number of views or grid sampling density) and evaluated on our new ground-truth subjective dataset. For each metric, the optimal selection and combination of features is determined by logistic regression through cross-validation. This performance analysis, combined with MPEG experts’ requirements, lead to the validation of two selected metrics and recommendations on the features of most importance through learned feature weights.
Investigating the impact of fast count rates on timing jitter in SNSPDs

High count rates (10’s to 100’s to 1000’s of MHz) and very precise timing (10’s of ps FWHM jitter or less) are two of the features which make superconducting nanowire single-photon detectors a revolutionary experimental and engineering tool. Both of these performance metrics also depend on the device bias current level. The maximum count rate is determined by how soon after detection the bias current recharges to the level required for maximum efficiency, while the timing jitter decreases with increased bias current even beyond level which yields maximum efficiency. For a device with a strong detection efficiency plateau, the bias current recharge can push the device into the regime of maximum efficiency at a fractional level of the current required to achieve the desired jitter. Here, we present an experimental analysis of this effect. These results should enable users to consider the trade-off between count rate and timing jitter for various experiments.
The Design of Educational Guide System Based on Children's Psychology

The guide system is an educational model.In today's society, children's mental health problems are becoming more and more serious.People begin to realize the importance of scientific and effective guidance and guidance for children.This paper mainly analyzes the relevant theoretical knowledge about children's psychological education at home and abroad.From the perspective of psychology, this paper discusses the beneficial effects and significance of combining it with the current reality of this country, and then puts forward its own unique opinions and attempts to improve it in the process of practice in view of the shortcomings of the current domestic research on this kind of subject.After that, the framework diagram of the education guide system was designed and the performance of the system was tested.The test results showed that the education guide system based on children's psychology ran very quickly and its operation efficiency was more than 80%, which met the needs of users and could better promote the healthy development of children's body and mind and comprehensively improve the national quality level.
A Comparative Study of Reading Text Difficulty of CET-6 and IELTS Based on Coh-Metrix

This study aims to compare the text complexity of reading texts from CET-6 and IELTS using Coh-Metrix, SPSS, and Range.The study found that IELTS reading texts are generally more complicated than those of CET-6 in terms of readability, and there are inherent differences between the two sets of texts.Compared with IELTS reading texts, those of CET-6 exhibit higher narrativity, and higher connectivity, while lower word concreteness, and lower referential cohesion.This reflects the nature of the complexity of a text, namely, referential cohesion can help readers better understand the articles with difficult topics; Moreover, there is no positive relationship between word concreteness and lexical resources.