Reviewerly/exHarmony huggingface dataset:
Dear Cloud, I Think We Have Trust Issues: Cloud Computing Contracts and Trust

Abstract Cloud computing is the dominant paradigm in modern computing, used by billions of Internet users worldwide. It is a market dominated by a small number of hyperscale cloud service providers. The overwhelming majority of cloud customers agree to standard form click-wrap contracts, with no opportunity to negotiate specific terms and conditions. Few cloud customers read the contracts that they agree to. It is clear that contracts in cloud computing are primarily an instrument of control benefiting one side, the cloud service provider. This chapter provides an introduction to the relationship between psychological trust, contracts and contract law. It also offers an overview of the key contract law issues that arise in cloud computing and introduces some emerging paradigms in cloud computing and contracts.
Usability Evaluation of Lecturer Information Systems Using Sirius Framework and Moscow Technique

An example of application technology in university is developing an information system so that it can support performance and facilitate the information flow. Institute of Technology and Business (ITB) STIKOM Bali is a technology-based university that has an information system, one of which is the Lecturer Information System (SID) considering the role of Lecturers as the main actors in the world of university. SID was developed to facilitate and streamline the work of lecturers. The implementation of SID should be usefull to institutions so that the resources spent on building this system are not wasted. However, until now there has never been an evaluation of the usability of SID, causing the relevant stakeholders not to know the usefulness of the system and not knowing the improvements that need to be made to the SID system. Based on these problems, an evaluation of the SID ITB STIKOM Bali usability was carried out using the Sirius framework and the Moscow technique. The results of the research are the global usability value for SID based on ten aspects of the Sirius framework usability and recommendations for improving the SID STIKOM Bali system based on the Moscow Technique ranking. This research is expected to be a reference material for stakeholders in determining policies related to improving the SID system at ITB STIKOM Bali. The research method used in this research is literature study and observation, SID system analysis, distribustion and processing questionnaire data, data analysis and drawing conclusions
Accelerating BERT Inference for Sequence Labeling via Early-Exit

Both performance and efficiency are crucial factors for sequence labeling tasks in many real-world scenarios. Although the pre-trained models (PTMs) have significantly improved the performance of various sequence labeling tasks, their computational cost is expensive. To alleviate this problem, we extend the recent successful early-exit mechanism to accelerate the inference of PTMs for sequence labeling tasks. However, existing early-exit mechanisms are specifically designed for sequence-level tasks, rather than sequence labeling. In this paper, we first propose a simple extension of sentence-level early-exit for sequence labeling tasks. To further reduce the computational cost, we also propose a token-level early-exit mechanism that allows partial tokens to exit early at different layers. Considering the local dependency inherent in sequence labeling, we employed a window-based criterion to decide for a token whether or not to exit. The token-level early-exit brings the gap between training and inference, so we introduce an extra self-sampling fine-tuning stage to alleviate it. The extensive experiments on three popular sequence labeling tasks show that our approach can save up to 66%-75% inference cost with minimal performance degradation. Compared with competitive compressed models such as DistilBERT, our approach can achieve better performance under the same speed-up ratios of 2X, 3X, and 4X.
A Modulus Factorization Algorithm for Self-Orthogonal and Self-Dual Quasi-Cyclic Codes via Polynomial Matrices

A construction method of self-orthogonal and self-dual quasi-cyclic codes is shown which relies on factorization of modulus polynomials for cyclicity in this study. The smaller-size generator polynomial matrices are used instead of the generator matrices as linear codes. An algorithm based on Chinese remainder theorem finds the generator polynomial matrix on the original modulus from the ones constructed on each factor. This method enables us to efficiently construct and search these codes when factoring modulus polynomials into reciprocal polynomials.
Pretrained Language Models for Text Generation: A Survey

Text generation has become one of the most important yet challenging tasks in natural language processing (NLP). The resurgence of deep learning has greatly advanced this field by neural generation models, especially the paradigm of pretrained language models (PLMs). In this paper, we present an overview of the major advances achieved in the topic of PLMs for text generation. As the preliminaries, we present the general task definition and briefly describe the mainstream architectures of PLMs for text generation. As the core content, we discuss how to adapt existing PLMs to model different input data and satisfy special properties in the generated text. We further summarize several important fine-tuning strategies for text generation. Finally, we present several future directions and conclude this paper. Our survey aims to provide text generation researchers a synthesis and pointer to related research.
Private Release of Text Embedding Vectors

Ensuring strong theoretical privacy guarantees on text data is a challenging problem which is usually attained at the expense of utility.However, to improve the practicality of privacy preserving text analyses, it is essential to design algorithms that better optimize this tradeoff.To address this challenge, we propose a release mechanism that takes any (text) embedding vector as input and releases a corresponding private vector.The mechanism satisfies an extension of differential privacy to metric spaces.Our idea based on first randomly projecting the vectors to a lower-dimensional space and then adding noise in this projected space generates private vectors that achieve strong theoretical guarantees on its utility.We support our theoretical proofs with empirical experiments on multiple word embedding models and NLP datasets, achieving in some cases more than 10% gains over the existing state-of-the-art privatization techniques.
Important Considerations of Data Collection and Curation for Reliable Benchmarking of End-User Eye-Tracking Systems

In this article we discuss how to build a reliable system to estimate the quality of a VR eye-tracker from an accuracy and robustness point of view. We list up and discuss problems that occur at the data collection, data curation and data processing stages. We address this article to academic eye-tracking researchers and commercial eye-tracker developers with the purpose of raising the problem of standardization of eye-tracking benchmarks, and to make a step towards repeatability of benchmarking results. The main scope of this article is consumer-focused eye-tracking VR headsets, however some parts also apply to AR and remote eye-trackers, and to research environments. As an example, we demonstrate how to use the proposed methodology to build, benchmark and estimate the accuracy of the FOVE0 eye-tracking headset.
The relationship between computer game addiction and obesity in third and fourth grade elementary school students

Various reasons leading to a child's being less active, decreased sports events and increased immobile activities can lead to a positive energy balance in children with similar nutrition.Activities with less physical demand such as watching TV, playing video games, and using the computer are closely Aims: Childhood obesity has been defined as a very serious public health issue.It was aimed to investigate the relationship between computer game addiction and obesity in 3 rd and 4 th grade elementary school students. Methods:In this cross-sectional study, two separate questionnaires including demographic characteristics, physical activity, nutrition and computer game habits were applied to students and their parents.The students were also asked to fill the Computer Game Addiction Scale.Results: This study included 491 children and parents.Above the half (51.5%) were female and 69% were at normal weight.The body mass index (BMI) percentile values of children in the 8-9-year-old group were higher than those in the 10-11-year-old group (t=3.044;p=0.002).When children's computer game addiction was evaluated, it was found that while 86.9% of them were at low level of addiction, 12.7% were at moderate level of addiction.Having an overweight brother/sister, high paternal BMI, increase in time spent on screen, and low maternal education status increased BMI percentile values in children (p<0.05).As long as the time of playing computer game increased, it was observed that BMI percentile values also increased significantly (p=0.033). Conclusions:This study shows that the level of computer game addiction and the time spent on screen are factors that increase obesity.In addition, the high level of frequency of snack in children is supportive of this result.If the ways to fight obesity are to promote physical activity and to move away from sedentary life style in children, it is clear that measures should be taken regarding the time that they spend in front of the screen.
Exponential forgetting of smoothing distributions for pairwise Markov models

We consider a bivariate Markov chain Z={Zk}k≥1={(Xk,Yk)}k≥1 taking values on product space Z=X×Y, where X is possibly uncountable space and Y={1,…,|Y|} is a finite state-space. The purpose of the paper is to find sufficient conditions that guarantee the exponential convergence of smoothing, filtering and predictive probabilities: supn≥t‖P(Yt:∞∈⋅|Xl:n)−P(Yt:∞∈⋅|Xs:n)‖TV≤Ksαt,a.s. Here t≥s≥l≥1, Ks is σ(Xs:∞)-measurable finite random variable and α∈(0,1) is fixed. In the second part of the paper, we establish two-sided versions of the above-mentioned convergence. We show that the desired convergences hold under fairly general conditions. A special case of above-mentioned very general model is popular hidden Markov model (HMM). We prove that in HMM-case, our assumptions are more general than all similar mixing-type of conditions encountered in practice, yet relatively easy to verify.
An Ontology for Composite Cloud Services Description

In last few years, cloud services are described and analyzed as independent atomic services without taking into account their relationships with other services existing in cloud environment. This later is a complex ecosystem of multiple services, delivered by different cloud providers in different formats using their own vocabulary. These heterogenous services are involved as service components in the creation of a value-added cloud composite applications. The composition of these services is challenging and can decrease portability and interoperability of cloud offerings. In this paper, we propose a model for a complete definition and description of cloud services, considering them as composite services. Five service description aspects are considered in this work; the business, technical, operational, structural and semantic aspects. Therefore, we propose to use an ontology representation, extended from the Linked USDL language, which enables an effective description and a rich specification of the domain knowledge of composite cloud services. In addition, we show how the proposed description could be used in a concrete example and how semantic rules are implemented to infer additive knowledge in order to select relevant cloud services for composition.
Secured Medical Image Hashing Based on Frequency Domain with Chaotic Map

Integrity, Medical image SLT
Analysis of the Role of Information Systems Technology in Lecture Learning during the Corona Virus Pandemic

Abstract— At this time the spread of the Corona Covid-19 Virus was sweeping the world, Indonesia was also affected, especially in the world of education where the teaching and learning process was usually carried out face-to-face in the classroom. So as a result of this pendemi the teaching and learning process must be done online. The role of information systems technology is very meaningful in lecture learning. This study aims to analyze a model of campus learning conditions and the role of information system technology in college learning amid the COVID-19 corona virus pandemic at STMIK Sinar Nusantara Surakarta. The research method is to make observations and literature studies to obtain data and information used in research. The results of this study indicate the use of information technology has a very important role in the implementation of online distance learning in the midst of the corona covid 19 virus pandemic, among online online media such as: google classroom, whatsapp, zoom. Of the online learning media, it is proven that Google Classroom: 55.9% is widely used as media for sharing materials and assignments, while video conferences lectures are the most users of Google Meet as much as: 70.6%. The results of the analysi s of the online learning value are: 44.1%. Based on this data, it shows that the role of information system technology plays an important role and helps in the teaching and learning process amid the Covid-19 corona virus pandemic.
NEED FOR VALUE EDUCATION AS AN INTEGRAL PART OF SUSTAINABLE EDUCATION

For a peaceful world and society, it is essential for cultures to be developed and transformed through common values, and value education is one of the main ways to do that since core values are formed from an early age. But when society is going through a radical transformation process as it is in the case of Latvia, it is difficult to avoid anomie when different and conflicting ideas, memories and norms exist in society.The aim of the research is to explore and analyse the tendencies of the main values in the society of Latvia across different age groups, to see how the situation has developed and what are the main values that need to be stressed through value education in the ongoing educational reform process. To reach the aim of the research, a literature review as well as the analysis of the European Social Survey (2008 and 2018) data was conducted.The research results show some shift in values of the society in Latvia mainly due to priorities of younger generation in the period from 2008 to 2018: universal values have replaced self-direction values as the third most common value in the society of Latvia. In the case of younger generations value perception is indefinite. Partly this is due to the lack of focus on values in our education system since the restoration of independence. There is a need to strengthen the motivational values connected with conformity, self-direction, stimulation and universalism (tolerance) through value education. It is desirable to highlight the values of achievement such as creativity and desire to succeed, as they are essential for the knowledge society and stimulate motivation for entrepreneurship.
Survey on Blockchain Based Accounting and Finance Algorithms Using Bibliometric Approach

The aim of this study is to evaluate the impact of blockchain especially on accounting and finance functions, the strategic role of CFOs, and to the restructuring process of accounting and finance functions in the future. In this respect, a business model is recommended that finance, accounting, and audit professionals can benefit from. It is aimed to contribute to the literature by providing blockchain adaptation and implementation strategy via providing information about accounting, finance, and auditing algorithm samples for revolutionizing these functions. To the best of our knowledge, this will be a pioneering work that makes a survey by examining blockchain algorithm samples in the field of accounting, auditing, and finance by using Bibliometric Network Analysis. In this analysis, six major clusters are estimated for defining the impacts of blockchain in the literature based on “Co-citation” aspects for the period 2005–2021 considering the SSCI indexed articles. In addition, the ranking of the top three contributing countries is found to be China, USA, and the UK respectively. This indicates the power of these countries to shape the future of accounting, finance, and auditing standards by means of producing blockchain algorithms and determining innovation policies of these professions in the future.
THE DEVELOPMENT OF CONSTANT MOTIVATION OF FUTURE PRIMARY SCHOOL TEACHERS IN CONDITIONS OF BLENDED LEARNING

The article considers the problems of implementation of distance and blended learning formats, the difficulties of increasing the constant motivation of students, ways to solve these problems and difficulties. The motives that motivate adult learners to study in the following conditions are determined: self-affirming, material, social, internal, insurance and leisure motives. It is emphasized that motivation is a source and a factor that motivates educational activities and increases the level of professional competence of future teachers. Difficulties in implementing the distance format are grouped into 4 groups: personal difficulties (initial low internal motivation of the applicant, the habit of strict control by the teacher, weak self-organization of students, lack of emotional and psychological contact with colleagues, low responsibility, lack of sense of belonging to groups of students), organizational problems (unclear organization of the course, problems with access to certain educational resources), professional (insufficient professional level in both computer skills and in the submission of material without adaptation to distance format), technical (unstable Internet access, lack of necessary hardware or software). Attention is paid to such strategically important components as attention, confidence, satisfaction. The article analyzes the means of influencing each component in the context of blended learning. The use of the materials described in the article will help to support and increase the motivation of learning in a blended and distance form, will help minimize the above risks, difficulties and problems. Specific examples of tools and instruments are given: during the implementation of the educational process in the context of blended learning is clearly defined feedback, creating a "success situation", formulating the goals of the whole course and individual modules, reflection of distance learning experience by filling out specially designed questionnaires and performing tasks of a reflexive nature. The toolkit can be expanded with additional features of already known platforms and tools – session halls and screen management on the ZOOM platform for online conferences, google forms for testing applicants on the selected topic with subsequent collection and analysis, applications and services Learningapps, Mentimeter, online boards AWWapp, etc.
The Relationship between Recreational Awareness and Satisfaction with Life: the Case of University Students

Adopting the suitable sampling method, the sampling group of the study was selected on a voluntary basis out of university students who study for various faculties and departments.The sample of the study consisted of a total of 764 university students including 490 women (64.1%) and 274 men (35.9%).The Recreational Awareness Scale and the Satisfaction With Life Scale (SWLS) were adopted to assess the awareness of subjects about attending events as a part of the study.The results indicated a significant difference in sub-dimension of pleasure & fun of Recreational Awareness Scale based on age while there was no significant difference in terms of the length of weekly free time.The difference between subjects in scores of satisfaction with life was significantly based on their wellbeing.It was evidenced that the relationship between recreational awareness and satisfaction with life was significant in a positive way.The limitations to the study and assessments over further studies were discussed in this regard.
NiaAML: AutoML framework based on stochastic population-based nature-inspired algorithms

The field of Automated Machine Learning (AutoML) has been developed to automate data preprocessing and search for optimal algorithms together with their hyperparameters in order to discover the best possible ML pipeline for an input dataset (Hutter et al., 2019).AutoML can be modeled as a continuous optimization problem with several potential optimization methods considered.Stochastic population-based nature-inspired algorithms (Engelbrecht, 2007;Yang, 2014) are a popular class of tools for dealing with such continuous optimization problems.These algorithms are inspired mainly by the biological behavior of various species living in nature (Fister Jr et al., 2013).Such algorithms are composed of a population of individuals that undergo different variation operations during the evolution process which results in new populations.The Python framework we have developed, NiaAML, incorporates these stochastic algorithms to search for the most suitable classification pipeline in a dataset (Fister Jr. et al., 2020).
Research on data storage model of household electrical appliances supply chain traceability system based on blockchain

In order to solve the problems of large amount of data storage and low query efficiency in home appliance supply chain traceability system, this paper studies a hyperledger fabric based dual storage block chain model of data on-chain and off-chain. When the total number of traceable data reaches 100000, the model is compared with the traditional model, and the results show that the query efficiency of the model is improved by at least 42.36%, which solves the problem of low efficiency of traditional data query, and can ensure the traceability reliability of supply chain data information of home appliance manufacturers.
Unambiguous determinism in captivity of illusory perceptions

This article attempt to clarify whether the accusations brought by modern physics and probabilistic thinking against unambiguous determinism are justified. Is it incompatible with the existence of various possibilities, coincidences, free will, and certain laws of microcosm? Does it really lead to absolute predetermination? Is the perception of universality and fundamentality of unambiguous causation really outdated? Can the dynamic laws &amp;nbsp;be limited in their manifestation? Can they be replaced with probabilistic laws? At the same time, the logic of research is founded on determination of the essence of all the phenomena that are supposedly incompatible with the unambiguous determinism. In the course of research, the author adheres to gradual implementation of the principle of materialistic monism. The conclusion is made that the classical representation of universality and fundamentality of unambiguous causality remains relevant and is fully compatible with the presence of various possibilities, coincidences, free will, and probability. The author reveals the nature of possibilities and coincidences, as well as indicated inseparability of these phenomena from the predictive activity of a human. The article also determines inextricable link between the dynamic laws and the materiality of &amp;nbsp;the cognizable world, which testifies to their unlimited fundamentality. The nature of probabilistic laws and their inseparability from dynamic laws is underlined. The author provides arguments that unambiguous causality does not lead to absolute predomination of events, emphasizes the importance of the worldview criterion of validity of scientific representations; and clarifies the definition of matter.