Reviewerly/exHarmony huggingface dataset:
High-Level Design Stories in Architecture-Centric Agile Development

Capturing and communicating the architecture decisions of a project is very important in architecture knowledge management, so that those decisions can deliver value to the system stakeholders and also support the system implementation. In agile development contexts, there is often a balancing act between documenting the design decisions in detail and keeping the documentation efforts to a level tolerable for the project. To this end, we present the notion of High-level Design stories (or HLDs), as small, modular artifacts that record the main design decisions and their context, but also include information about architecture assumptions, quality-attribute analysis, and pending issues for the system. HLDs are intended to be created and refined during the different phases of an architecture-centric development process, and assist in the validation of the decisions (and pending issues) in that process. This way, a global (although detailed) architecture design can be obtained from the combination of the HLDs. In this work, we discuss the pros and cons of using HLDs for design decisions based on experiences from an industrial software project.
Quality, reliability, data (III), and the impact of the GDPR …

The General Data Protection Regulation (EU) 2016/679 (“GDPR”) is a regulation in EU law on data protection and privacy for all individuals within the European Union (EU) and the European Economic Area (EEA). It also addresses the export of personal data outside the EU and EEA areas. […] Controllers of personal data must put in place appropriate technical and organisational measures to implement the data protection principles. Business processes that handle personal data must be designed and built with consideration of the principles and provide safeguards to protect data (for example, using pseudonymization or full anonymization where appropriate), and use the highest-possible privacy settings by default, so that the data is not available publicly without explicit, informed consent, and cannot be used to identify a subject without additional information stored separately. No personal data may be processed unless it is done under a lawful basis specified by the regulation, or unless the data controller or processor has received an unambiguous and individualized affirmation of consent from the data subject. The data subject has the right to revoke this consent at any time. On first sight, this new law severely complicates the use of “open data.” While in my previous editorial on this subject I strongly advocated that in papers in this journal authors should give, wherever possible, contextual information that would enable future researchers to further develop prior work this new law does not make this easier. The law has rules on the collection, organization, structuring, storage, alteration, consultation, use, communication, combination, restriction, erasure, or destruction of personal data. And, if I look to the papers in our journal, as soon as there is an operator/user involved, data easily becomes personal. This risk of this is that authors restrict their datasets to the bare minimum. Already now we see papers that predict or optimize quality and reliability by presenting only a table of numbers (or re-using an earlier published version) without giving any contextual information. Although conceptually often interesting these papers have little added value for engineers and practitioners since especially the contextual information is often relevant for actual implementation in real engineering systems. In order to meet these conflicting demands, I see, also in my own organization, the emergence of a new profession: data stewards. My guess is that these data stewards will fulfill an increasingly important role in the future of quality and reliability engineering. It is, of course, of utmost importance that personal information is treated very carefully. It is also of utmost importance that papers are published including contextual data in order to be of value for those who wish to apply it or use it as a basis for future research. In my own organization, we are still busy finding out the exact role for these data stewards but already now they are already of great help finding the required middle-ground.
Special Moments in Ukrainian and Foreign Students Perception of a Lecturer’s Personality

Background and Aim of Study:In process of introduction of new requirements and standards of teaching, significant transformations of lecturer and student's interaction take place.A system of role expectation as to lecturer's main qualities changes.The aim of the study: to research and justify of theoretical basements of diagnostics of results of forming professional competencies of pedagogues in universities. Materials and Methods:For analyzing special features of language training lecturer's perception that are important for students of our university we conducted a survey: "A lecturer in foreign students' eyes".Students of faculty of construction and faculty of architecture of Kharkiv National University of Civil Engineering and Architecture took part in it.This survey been held in several stages.On stage one foreign students of elder grades had to finish the sentence: "Modern university lecturer should be …" by using their own thoughts.After processing the results of our survey, we made a list of lecturer's features that are important for students.Students of younger grades had to rank the features from the list we got.Our research has been held for 10 years.We have been using methods of covert surveillance and partial distributive analysis of researched material. Results:For Ukrainian and foreign students image of their lecturer consists of many subjective factors of perception and includes several groups of qualities: personal qualities, that characterize lecturer as a person; professional qualities, that characterize lecturer's professional level; and social qualities, that characterize lecturer's communicative skills and his ability to "stay in touch" with students.Conclusions: Effectiveness and optimization of Ukrainian and foreign students' teaching process depends both on lecturer's pedagogical masterpiece and on his character.
Recognition in Unseen Domains: Domain Generalization via Universal Non-volume Preserving Models.

Recognition across domains has recently become an active topic in theresearch community. However, it has been largely overlooked in the problem ofrecognition in new unseen domains. Under this condition, the delivered deepnetwork models are unable to be updated, adapted or fine-tuned. Therefore,recent deep learning techniques, such as: domain adaptation, featuretransferring, and fine-tuning, cannot be applied. This paper presents a novelapproach to the problem of domain generalization in the context of deeplearning. The proposed method is evaluated on different datasets in variousproblems, i.e. (i) digit recognition on MNIST, SVHN and MNIST-M, (ii) facerecognition on Extended Yale-B, CMU-PIE and CMU-MPIE, and (iii) pedestrianrecognition on RGB and Thermal image datasets. The experimental results showthat our proposed method consistently improves the performance accuracy. It canbe also easily incorporated with any other CNN frameworks within an end-to-enddeep network design for object detection and recognition problems to improvetheir performance.
Complex forest management system based on small size forest machines

The aim of this study is to clarify the possibilities for applying compact class logging machines in Latvian conditions.The equipment evaluated in the study is the Vimek harvester and forwarder.The possibility of using both machines in forest operations from ditch clearing to final felling has been evaluated in terms of productivity and economy.The productivity of the Vimek harvester can be characterized by polynomial equations.Statistical significantly higher productivity in pre-commercial thinning was observed in spring trials in forest areas with or without extracted undergrowth trees in comparison to areas with dense undergrowth vegetation.Statistically significant difference was observed in artificially and naturally regenerated stands -in naturally regenerated stands better figures were obtained during the extraction of small trees (D 13 < 17 cm), in artificially regenerated stands -in the extraction of bigger trees.The Vimek harvester was equipped with a specialized felling head with a circular saw and chain (Bracke C.12) in early tending and felling-bunching head with a chain feed roller (Keto-Forest Eco) in thinning.The productivity achieved in small ditch clearing was 187 m•h -1 , while clearing of larger ditches resulted in an average productivity of 107 m•h -1 , the productivity of early tending is 0.2 ha•h -1 .Harvesting productivity highly depends on the average tree diameter, but the average value is 9.0 m 3 •h -1 .The productivity in final felling in grey alder stands is 11.5 m 3 •h -1 .In all cases productivity is expressed as efficient work hours.The prime cost of log production (extraction and delivery) ranges from 22.9 EUR•m -3 , but the cost of ditch clearing and early tending can be estimated from the average hourly cost of 63 EUR•h -1 .
THE USE OF DISCOVERY LEARNING METHOD TO IMPROVE STUDENTS’ WRITING DESCRIPTIVE TEXT

The direction of the research is to prove whether the discovery learning method can improve the students competence in writing descriptive text or not. The subject is the tenth grade students of MA Nurul Hidayah Batujajar which consist of 16 students. The researcher conducted 2 cycles of classroom action research as the research method. Each cycle comprised pre-test, two meetings for treatment and post-test. In collecting data, the researcher used test and non-test. From the data taken, the result tends to be satisfied. During teaching learning process, the students tend to become active participants. The results of the research showed that the students are more confident in writing descriptive text and know what to write. Furthermore, there are some improvements in their test scores which are the mean score of post-test1 in cycle one (5. 65 ) is higher than the mean score of pretest (4. 03 ) and the mean score of post-test2 in cycle two ( 6. 7 2 ) is higher than the mean score of post-test1 in cycle one. From the results of the research, it can be summariz ed that using discovery learning method can improve the students’ writing descriptive text.
Contrastive Analysis: Difficulties Arabic Learners Face in Using English Language Tenses

The primary purpose of this research was to investigate the impact of different verb tenses in Arabic and English which caused errors by Arabic learners. The researcher provided a contrastive analysis of two different groups of tenses of English and Arabic: shared tenses and aspects as well as language specific tenses to determine if learners make errors based on different tense systems. The participants of this research were 35 freshmen students of Management Science at Yanbu University College (Female Campus). This research was a quantitative research and it used two grammar tests one examined the similar tenses and another examined the different tenses. The findings showed that shared tenses between English and Arabic received 91% correct answers while different tenses received only 27% correct answers. On the other hand, the wrong answers that shared similarities received 9% and differences received 73%. To sum up, the results showed that the differences in Arabic tenses were the main reason that affected learners' usage of English tenses.
End-to-End Resilience for HPC Applications

A plethora of resilience techniques have been investigated to protect application kernels. If, however, such techniques are combined and they interact across kernels, new vulnerability windows are created. This work contributes the idea of end-to-end resilience by protecting windows of vulnerability between kernels guarded by different resilience techniques. It introduces the live vulnerability factor (LVF), a new metric that quantifies any lack of end-to-end protection for a given data structure. The work further promotes end-to-end application protection across kernels via a pragma-based specification for diverse resilience schemes with minimal programming effort. This lifts the data protection burden from application programmers allowing them to focus solely on algorithms and performance while resilience is specified and subsequently embedded into the code through the compiler/library and supported by the runtime system. In experiments with case studies and benchmarks, end-to-end resilience has an overhead over kernel-specific resilience of less than $$3\%$$ on average and increases protection against bit flips by a factor of three to four.
Detecting and Tracking of Multiple Mice Using Part Proposal Networks

The study of mouse social behaviors has been increasingly undertaken in neuroscience research. However, automated quantification of mouse behaviors from the videos of interacting mice is still a challenging problem, where object tracking plays a key role in locating mice in their living spaces. Artificial markers are often applied for multiple mice tracking, which are intrusive and consequently interfere with the movements of mice in a dynamic environment. In this article, we propose a novel method to continuously track several mice and individual parts without requiring any specific tagging. First, we propose an efficient and robust deep-learning-based mouse part detection scheme to generate part candidates. Subsequently, we propose a novel Bayesian-inference integer linear programming (BILP) model that jointly assigns the part candidates to individual targets with necessary geometric constraints while establishing pair-wise association between the detected parts. There is no publicly available dataset in the research community that provides a quantitative test bed for part detection and tracking of multiple mice, and we here introduce a new challenging Multi-Mice PartsTrack dataset that is made of complex behaviors. Finally, we evaluate our proposed approach against several baselines on our new datasets, where the results show that our method outperforms the other state-of-the-art approaches in terms of accuracy. We also demonstrate the generalization ability of the proposed approach on tracking zebra and locust.
Punishing Artificial Intelligence: Legal Fiction or Science Fiction

Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI functionally commits a crime and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement for a guilty mind.Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show AI punishment cannot be categorically ruled out with quick theoretical arguments. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime.
Adaptive Reversible Data Hiding Scheme for Digital Images Based on Histogram Shifting

Existing histogram based reversible data hiding schemes use only absolute difference values between the neighboring pixels of a cover image. In these schemes, maxima and minima points at maximum distance are selected in all the blocks of the image which causes shifting of the large number of pixels to embed the secret data. This shifting produces more degradation in the visual quality of the marked image. In this work, the cover image is segmented into blocks, which are classified further into complex and smooth blocks using a threshold value. This threshold value is optimized using firefly algorithm. Simple difference values between the neighboring pixels of complex blocks have been utilized to embed the secret data bits. The closest maxima and minima points in the histogram of the difference blocks are selected so that number of shifted pixels get reduced, which further reduces the distortion in the marked image. Experimental results prove that the proposed scheme has better performance as compared to the existing schemes. The scheme shows minimum distortion and large embedding capacity. Novelty of work is the usage of negative difference values of complex blocks for secret data embedding with the minimal number of pixel shifting.
Deciphering Monetary Policy Board Minutes with Text Mining: The Case of South Korea

We quantify the Monetary Policy Board minutes of the Bank of Korea (BOK) by using text mining. We propose a novel approach that uses a field-specific Korean dictionary and contiguous sequences of words (n-grams) to capture the subtlety of central bank communications. Our text-based indicator helps explain the current and future BOK monetary policy decisions when considering an augmented Taylor rule, suggesting that it contains additional information beyond the currently available macroeconomic variables. In explaining the current and future monetary policy decisions, our indicator remarkably outperforms English-based textual classifications, a media-based measure of economic policy uncertainty, and a data-based measure of macroeconomic uncertainty. Our empirical results also emphasize the importance of using a field-specific dictionary and the original Korean text.
Children's Authentication

With the widespread infusion of technology into society, children (ages 5-11) not only interact with technology but are also required to create and use credentials in order to authenticate and use various platforms. My primary goal with this research is to investigate children's understanding and practices in terms of creating and using credentials -- across the globe. I describe an initial study conducted via semi-structured interviews with children and an online survey with adults (parents and teachers), that help us to understand the adult's understanding of authentication and the role they play in children's credential creation and usage. Results shows that children have limited knowledge and understanding of credential creation and usage and that there is also a gap in adult's theoretical knowledge and practical implementations.
A Framework for Web Applications using an Agile and Collaborative Model Driven Development (AC-MDD)

This paper presents, as its main contribution, a Framework for Web Applications named Agile and Collaborative Model Driven Development (AC-MDD), seeking to reduce wastes on the modeling and documentation activities of web applications. The AC-MDD framework was elaborated based on related works that present Agile Model Driven Development processes (AMDD), but it deals with issues not yet considered by these researches. To adopt the AC-MDD framework, some visual elements from a novel Unified Modeling Language (UML) profile named Web-AML was designed, allowing to represent agile models of web applications. Besides that, in order to apply the proposed framework using these new models, a method was defined providing steps to transform agile models into web application source-codes. A case study was performed successfully in a real project that gives support to the population of a city located in the State of São Paulo (Brazil) to deal with the real flood problem they have been facing in recent years. This project was developed at the Federal Institute of Education, Science, and Technology of São Paulo to verify and validate the AC-MDD framework. Finally, a comparative analysis between the AC-MDD Framework and other AMDD processes was presented and highlighted the main aspects of the proposed framework.
Implementing NChooseK on IBM Q Quantum Computer Systems

This work contributes a generalized model for quantum computation called NChooseK. NChooseK is based on a single parametrized primitive suitable to express a variety of problems that cannot be solved efficiently using classical computers but may admit an efficient quantum solution. We implement a code generator that, given arbitrary parameters for N and K, generates code suitable for execution on IBM Q quantum hardware. We assess the performance of the code generator, limitations in the size of circuit depth and number of gates, and propose optimizations. We identify future work to improve efficiency and applicability of the NChooseK model.
PENGARUH GERAKAN LITERASI DALAM MENINGKATKAN MINAT BACA SISWA

In Indonesia, the interest in reading in all circles is still lacking, especially students and students who are usually involved in the world of education. Because people who are less aware of the benefits of literacy. In addition, there are quite a lot of obstacles that occur when reading. When the government makes a policy to build a culture of literacy through ways of getting students to read for 10-15 minutes before learning begins. This study intends to determine the influence and obstacles of the School Literacy Movement (GLS) program on reading hobbies among students at the Assyukur Bakti Health Vocational School. The subjects in this study were students of Assyukur Bakti Health Vocational School. The formulation of the problem in this study are: 1) What is meant by literacy? 2) What are the obstacles in literacy? 3) The approach used in this study is qualitative research. The data collection technique is done by questionnaire, observation, documentation, and interviews. The results of the study found that students' fondness for reading increased can be seen from the results of the questionnaire which showed the results that the students of reading were reading as gifts after the School Literacy Movement. Literacy culture can be improved, their reading activities can be observed, and their reading skills develop well by cultivating a culture of literacy in students.
User experience problems in immersive virtual environments

In recent years there has been a great boom in the use of immersive virtual environments applications, but research into interaction techniques for these technologies has not had the same growth. Therefore, it is necessary to study the user experience of the different forms of interaction that these technologies offer to users and give developers the information needed to use the techniques that best suit their applications and their users. This work is an exploratory study to detect the problems that the users find in this kind of applications. We aim to make an evaluation of a determined set of interaction techniques, both in virtual and augmented reality, attending to the problems produced in the users to know the strengths and weaknesses of each type of interaction technique. With this study, we will be able to make a guide for the developers, in order to give them clues about the best interaction technique for their applications.