Reviewerly/exHarmony huggingface dataset:
Blockchain: Challenges and Opportunities for Management Research

Blockchain technology is widely hailed as a disruptive technology that will not only lead to the emergence of new business models, but also redefine what constitutes an organization and how it can effectively operate. Concurrently to the widespread adoption of blockchain and its technological maturity, a vibrant community of scholars studying blockchain and its implications for management is emerging. Therefore, we believe that the time is ripe to bring together leading scholars with different research foci and diverse methodological preferences to discuss, provide direction, as well as debate, how blockchain will affect management theory and practice. This panel symposium will serve as a forum to elaborate on how blockchain related research differs from past work, what are the associated challenges and opportunities, as well as identify areas that future blockchain research should focus upon. In a facilitated discussion, we will raise these issues, providing ample opportunities for participants to engage, raise questions, and learn from their peers to design and conduct top blockchain management research.
Leveraging New Technology for Creating a Better World? Towards a Typology of Blockchain Ventures

Blockchain technology, an institutional innovation, explored in depth in the information system literature, has been a growing research area over the past years. Even though it opens new opportunities for entrepreneurs, the entrepreneurship literature does not provide a theory or model of blockchain entrepreneurship. We know that blockchain drives the emergence of unprecedented types of ventures, with varying degrees of decentralization, both from the financing and governance perspectives. However, there is no consistency regarding the definitions and labels used to refer to blockchain ventures. This paper clarifies the definitions of blockchain-related ventures as well as presents a typology distinguishing four ideal types. It shows that entrepreneurs willing to leverage blockchain technology do not necessarily need to decentralize their governance or financing processes.
Advances in Big Data and Machine Learning in Cancer Detection in Women-Associated Cancers

Machine learning (ML) is a type of artificial intelligence (AI) that employs a range of statistical, deterministic and optimization methods to automatically learn and improve performance from fresh data and prior experiences without the need for explicitly coded instructions. When working with complex, massive, high-dimensional data, machine learning algorithms are usually capable of identifying crucial features and probable rules that are difficult to find using standard statistics. Nowadays, cancer diagnosis is acquiring exponentially more data from the past and projecting therapy strategies based on data analysis. Regrettably, previous approaches of applying machine learning algorithms were unable to meet the new problems of large data, particularly scalability. New big data technologies have recently evolved, lowering the cost of keeping vast amounts of data from breast cancer patients and enabling real-time information analysis by combining all stored and flowing data. This chapter attempts to showcase new breakthroughs in big data and machine learning techniques that are being used in the early detection of cancers that are largely linked with women all over the world.
Automated Syntactic Analysis for ELT

This chapter examines the affordances of automated syntactic analysis (ASA) for language teaching. Following an overview of the state-of-the-art natural language processing (NLP) technologies for ASA, the chapter systematically reviews three key research strands that demonstrate how such NLP capabilities can be implemented into language pedagogy with distinct pedagogical foci. In the first strand, ASA is used to identify, highlight, and create exercises on target syntactic features in pedagogical texts, with the goal to promote learners’ grammar acquisition. The pedagogical integration of ASA in this strand often draws on focus-on-form and input enhancement-based pedagogical activities. In the second strand, the role of ASA is to parse pedagogical texts and present them in modified formats in order to facilitate syntactic processing. This strand of research posits that syntactic enhancement affords learners greater access to syntactic relationships within a text, which, in turn, may promote the development of the learners’ reading skills and potentially other language skills, too. The third strand integrates ASA with rhetorical/functional analysis of texts to promote the development of learners’ ability to recognize genre-specific form-function mappings. The chapter concludes with a discussion of future directions of ASA-informed language pedagogy.
Answering Geosciences Research Questions at a Global Scale via a Hybrid Machine-Human Learning Approach: A Case Study of the Link between Climate and Volcanism

A common challenge in science is the human capability to evaluate the real impact of an observation and a data set.This is a complex task due to having only partial information and/or to the complexity of the problem, requiring different fields to be combined.In order to overcome these important limitations, we need to be able to review all the available data and interpretations.This would allow us to evaluate the global distribution of a specific process or phenomenon of interest.The increasing number of scientific publications prevents scientists from being able to keep up with all the available literature especially when scientific papers cross disciplines.These challenges prevent us from evaluating the global impact of a certain process and are particularly relevant today given the impact of our scientific assessment on one of the most pressing issues of our time, which is climate change and its impact on society.We present here an application of artificial intelligence to geosciences: We conduct a systematic analysis of geoscience literature through a hybrid machine-human approach.Such applications are more common in other fields such as biomedicine and are in their infancy in the geosciences because of various difficulties the machines encounter in parsing geologic literature.We describe here some of these limitations and how we overcame them.We then use the following case study as an example to test our approach: We ask whether climate is influenced by volcanism in the geologic past.Our case study results show, as expected, that most analyzed literature in this experiment conclude that volcanism influences climate change in deep time, but there is no complete consensus on this question.Similarly, any question of potential global significance, such as the impact of human activities on climate change, can be posed as an interrogating technique for our vast and fast-growing literature in the field of geosciences.Such an approach has the potential to be applied to a variety of complex problems, hence addressing some of the major limitations with cross-disciplinary research.
Moon Jae-in Government Teacher Policy Evaluation Based on CIPP Model

본 논문에서는 문재인 정부의 교원정책 평가를 통해 향후 새 정부에서 추진해야 할 교원정책에 대한 시사점을 제시하는 것을 목적으로 한다. 이를 위해서 문재인 정부의 교원 정책에 대하여 CIPP 모형에 근거하여 평가를 수행하였다. 먼저 상황평가 결과 대부분의 교원 정책들은 적합성에서 문제가 없는 것으로 평가된다. 그러나 학생 1인당 교원 수 감축은 학령인구의 급격한 감소 상황을 반영하지 못한 것으로 평가된다. 그리고 비정규직의 정규직화 역시 한국의 교사임용경쟁 상황을 고려하지 못한 현실적합성이 낮은 정책으로 평가된다. 투입의 경우, 내국세 증가로 인한 지방교육재정교부금의 증가로 비교과교사 채용, 유아교원 처우 개선 방안 등 재정투자가 필요한 정책들의 현실가능성이 높아진 것으로 평가된다. 과정평가 결과 문재인 정부는 숙의와 공청회, 그리고 외부인사로 대부분 구성된 위원회 등을 통해서 합리적 절차를 거쳐서 관련 개선방안을 마련하고 추진한 것으로 평가된다. 마지막으로 산출결과의 경우 유아교사처우 개선과 비교과교사 법정정원 충원율 증가, 개방헝 공모제의 점진적 증가 등의 성과가 있는 것으로 평가될 수 있다. CIPP 모형에 근거한 문재인 정부의 교원정책 평가결과 향후 새 정부에서는 교원양성체제 개편 추진, 유아교원자격체제 개편, 비교과교사 법정정원 충원율의 점진적 확대와 교원 처우 개선 및 행정업무 경감을 위한 교원정책이 적극적으로 추진될 필요가 있을 것으로 보인다. The Moon Jae-in government's teacher policy was evaluated based on CIPP model. As a result of context evaluation, it is evaluated that the reduction in the number of teachers per student did not reflect the changed situation of the sharp decline in the school-age population. In addition, the conversion of non-regular workers to full-time positions is also evaluated as a policy with low practical relevance. In the case of input, it is evaluated that the practicality of policies that require financial investment. As a result of the process evaluation, it is evaluated that the Moon Jae-in government prepared and promoted related improvement measures through rational procedures through deliberation, public hearings, and a committee composed mostly of stake-holders. Lastly, in the case of the policy output, it can be evaluated that there are achievements such as improvement of the treatment of early childhood teachers, an increase in the legal quota for non-teaching teachers, and a gradual increase in the open recruitment system. Thus, the new government needs to actively pursue policies to promote the reform of the teacher training system, the reform of the early childhood teacher qualification system, the gradual expansion of the statutory quota for professionals (i.e. school psychologists), and reduction of administrative works of teachers.
The Regulation Anti-Unfair Competition Law on Either-or Choice Behavior of Online Platforms in E-Commerce

With the prosperous development of the digital economy, major e-commerce platforms have increased their competitive advantage by implementing either-or choice behavior on operators within their platforms. Compared to the anti-monopoly law, which has strict application standards, the Anti-Unfair Competition Law covers a wider range of either-or choice behavior. However, the concept of neutrality of the article exclusive of Internet (the Article 12) neglects the infringement properties of unfair competition, and the enumeration of behaviors lacks typology. If the general articles are too flexible, it will lead to the offsite of application, and the main elements of judgment rely excessively on subjective measurement. In this regard, based on accurately grasping the infringement attributes of the conduct, the abstract features of the Internet article are clarified and supplemented, and the types are classified according to the standard of “directly affecting the free decision of consumers”. At the same time, the principle of “more or less” can be used to dynamically understand the application of Internet articles and traditional regulatory provisions in the regulation of unfair competition in the network environment. In addition, the principle helps to rationalize the relationship between the Internet underwriting articles and the general article, more objectively qualify the subjective discretionary scope of the general articles by whether the behavior has a legitimate interest and positive impact, and reduce the escape of the Internet article.
The Interactive Effect of Emotion and Voice on Voice Endorsement

How emotion in voice expressions affects voice endorsements is less understood. In this paper, we followed two lines of reasoning and incorporated the arguments of promotive and prohibitive voice to explain when and how emotional voice expressions facilitate voice endorsements. Specifically, based on the display rule of emotion perspective, we proposed that expressing positive emotion would lead to more voice endorsements through perceived voicers' emotion management ability, especially for prohibitive voice. However, based on the information processing perspective, we proposed that positive voice expression of promotive voice and negative expression of prohibitive voice would increase information processing fluency by eliciting perceived emotional expression authenticity, leading to higher voice endorsements. Results from two studies consistently supported the display rule of emotion perspective explanation. The practical implication, as well as future research direction, is discussed.
THE STUDENTS’ SELF-DIRECTED LEARNING IN ENGLISH LEARNING ON THE ELEVENTH-GRADE OF SMA NEGERI 1 TEMBILAHAN

The purpose of this research is to know the level of students' self-directed learning in English learning on eleventh-grade students of SMA Negeri 1 Tembilahan. This research was achieved by conducting a descriptive quantitative study. The total population of this research was 268 students. Sample of this research were 92 students of eleventh-grade students of SMAN 1 Tembilahan. The researcher used purposive sampling to take the sample. The researcher gave a questionnaire to collect data, consisting of 20 statements based on self-directed learning indicators. It was using the Likert Scale. The results revealed that students' self-directed learning in English learning relies on enough levels with 63,97%. It means that they have a problem being a self-directed learner in English learning. They need to improve themselves to become a self-directed learner. The role of the teacher is vital in order to guide them to be more independent. The teacher can provide the instructions needed to direct students' initiative in their learning process to be more independent.
Analisis Usabilty Antarmuka Halaman Kerja (Back Office) SLiMS Versi 8 Akasia Menggunakan Nielsen’s Attributes of Usability

The purpose of this study was to measure and analyze usability evaluation on the SLiMS Version 8 Akasia work page interface using the Nilsen's Attributes of Usability questionnaire method which consists of 5 indicators, namely Learnibility (easy to learn), Efficiency (efficient), Memorability (easy to remember), Error (failure), and Satisfaction (satisfaction). This type of research is descriptive with a quantitative approach. The limit of this study only discusses the usability level of the SLiMS 8 Akasia back office interface, not only on other interface pages in the SLiMS Version 8 Akasia application. The samples chosen were staff or librarians who were accustomed to using the SLiMS Version 8 Akasia application to support their daily work. The results of tabulation and analysis of respondent data stated their agreement on each indicator statement of Learnibility, Efficiency, Memorability, and Satisfaction. Meanwhile, respondents stated that the answer was neutral on the Error indicator
Versatile Automated Domain Mapping of 4D-STEM Data Utilizing ML Algorithms and Bayesian Statistics

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Racial Identity Remains Embedded within Medical Imaging Data

HomeRadiology: Imaging CancerVol. 4, No. 4 PreviousNext Research HighlightsRacial Identity Remains Embedded within Medical Imaging DataPranay Singh, Ricky SavjaniPranay Singh, Ricky SavjaniPranay SinghRicky SavjaniPublished Online:Jul 22 2022https://doi.org/10.1148/rycan.229014MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In Highlighted ArticleGichoya JW, Banerjee I, Bhimireddy AR, et al. AI recognition of patient race in medical imaging: a modelling study. Lancet Digital Heal 2022;4(6):e406–e414. doi: https://doi.org/10.1016/s2589-7500(22)00063-2 Crossref, Medline, Google ScholarArticle HistoryPublished online: July 22 2022 FiguresReferencesRelatedDetailsRecommended Articles Management of Fractured Inferior Vena Cava Filters: Outcomes by Fragment LocationRadiology2017Volume: 284Issue: 3pp. 887-896Convolutional Neural Networks for Radiologic Images: A Radiologist’s GuideRadiology2019Volume: 290Issue: 3pp. 590-606Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADSRadiology2016Volume: 282Issue: 2pp. 348-355A Deep Learning Approach to Re-create Raw Full-Field Digital Mammograms for Breast Density and Texture AnalysisRadiology: Artificial Intelligence2021Volume: 3Issue: 4Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future PerspectivesRadiology2019Volume: 293Issue: 2pp. 246-259See More RSNA Education Exhibits A Primer on Machine Learning and Artificial Intelligence Applications in Breast ImagingDigital Posters2019Artificial Intelligence in Breast Imaging: Past, Present, and FutureDigital Posters2020Novel Image-Guided Micro-Invasive Percutaneous Treatments of Breast Lesions: Where Do We Stand?Digital Posters2019 RSNA Case Collection Poland SyndromeRSNA Case Collection2020Benign Breast LipomaRSNA Case Collection2021Breast FibromatosisRSNA Case Collection2022 Vol. 4, No. 4 Metrics Altmetric Score PDF download
A PEDAGOGICAL APPROACH FOR SOCIO-CULTURAL INCLUSION: A STUDY ON IMMIGRANT ENTREPRENEURS IN FINLAND

"According to the United Nations in 2019, the number of migrants worldwide reached 272 million and the wave of migration is expected to increase after the pandemic. As the number of immigrants increases, a strategy for their socio-cultural inclusion becomes essential. Finland is a Nordic country with a limited population that considered culturally, ethnically, and linguistically homogeneous, however, it is gradually changing as the number of immigrants increases. Promoting the integration of migrants and increasing their access to public services, labor market, private sector and opportunities in the host country is included in the strategies of the European Commission. Regarding the importance of entrepreneurship in the cultural inclusion of immigrants, this case study was conducted with an emphasis on the role of information technology in facilitating entrepreneurship for immigrants in Finland. Accordingly, a group interview was conducted to understand the challenges that migrants encounter in obtaining the information that they need. The results showed that immigrant entrepreneurs with different fields and backgrounds had difficulties finding some required information on Finnish websites. Some information or sources of information are known to locals while unknown or inaccessible to immigrants. In addition, participant of the study expected more variety and interaction in content on Finnish websites. This study proposes technological pedagogical content design (TPCD) as a systematic approach to design websites with more attention to multicultural users. TPCD assumes immigrants as learners who need to learn the new knowledge and skills in the host country. It utilizes pedagogical principles to define the needs of immigrants to clarify goals, create and organize content, and design web pages."
Design of the KAI Access System for Public Service Improvement in the Pandemic Era

During the COVID-19 pandemic one of the transportation modes that is the most vulnerable to crowds is trains. Currently, PT KAI as the train operator in Indonesia is leaning towards in optimizing its public services by making KAI Access. On the one hand KAI Access plays a very important role by facilitating online ticket ordering. However, in the pandemic situation the requirement for using trains has to be completed with vaccine certificate that is published by PeduliLindungi and not the part of KAI Access. This causes the passengers access two applications before allowed entering the station. So, in this paper, we proposed a design of the system that combines the two applications to ease passengers when using PT. KAI services. In our proposed system the passengers are only required to show the tickets that contains the complete identity of the passengers, their vaccination status, and also their contacts to enable the government to tracks them in order to prevent the spreading of COVID-19. Our proposed system is prospective to improve the quality of PT. KAI public services.
"EDUCATING FOR MODERN CLOUD TECHNOLOGIES IN A PLATFORM-AGNOSTIC FASHION "

"It is essential to provide computing students with hands-on exposure to modern techniques and technologies such as cloud computing. To this end we engaged with industry to co-design a curriculum for modern cloud computing to meet the industry needs for graduates. Vendors do provide access to cloud computing but their academic programs often leave much to be desired, with limited credits and features or a requirement to buy-in to their platform entirely. In the resource-constrained university sector simply buying vendor credits for students would be expensive but also wasteful as there is no capital investment. Having engaged with industrial partners to identify core theoretical skills and a subset of topics in which specific platform experience would be desirable we co-designed learning outcomes and assessments. To provide financially efficient platform-agnostic experience a private cloud was built using open-source tools which allowed a new large final year module. Having run this module for two full years and had excellent student feedback we reflect on the strengths and weaknesses of this approach and how industrial engagement cannot be a one-off, in a changing field it must be continuously performed to allow the curriculum to be refreshed and support emerging topics."
The walking stability control method of robots based on sensing quantitative fusion tracking

In order to solve the problem of poor stability and large steady-state error in the process of robot walking, a method of robot walking stability control based on sensor quantitative fusion tracking is proposed. In this paper, several sensors are used to collect the robot's attitude parameters and establish the robot's kinematics and dynamics model. The integral term of the tracking error is introduced and the steady-state error of the robot's walking is compensated by the backward sliding mode integral control. Under the external bounded interference, the conjugate gradient method is used to suppress the small interference and build the whole robot's walking system. The control law of the robot realises the stability control of the robot. The simulation results show that this method improves the tracking ability of robot motion parameters fusion and the accuracy of attitude parameters estimation, and improves the robustness of robot walking control.
Hand Gesture Recognition Using CBAM-RetinaNet

AbstractHand gesture recognition has become very popular with the advancements in computer vision, and efficient detection of hand gestures is certainly the talk of the hour. It finds numerous worthy real-world applications such as human computer interaction, sign language interpretation, immersive gaming experience, robotics control systems, etc. This paper presents an end-to-end system for the recognition of hand gestures, based on an efficient object detection architecture-RetinaNet. Convolutional Block Attention Module is used to improve performance. The method has been tested on Ouhands dataset and achieved better recognition accuracies and real-time application. Results show that our CBAM-RetinaNet model is robust and efficient in recognition of hand gestures in complex backgrounds and different illumination variations. KeywordsAttention mechanismBounding boxDeep learningHand gesture recognition
Design and Implementation of Reservation Management System - Case Study: Grand Ville Hotels

The management and booking of Rooms in hotels is a tedious and complicated task especially if it is done manually.Keeping track of large customers and all their details requires an inordinate space for file cabinets, not to mention the time the hotel administrator would spend going back and forth to file cabinets so as to look up each customer's information.This is why a good hotel reservation system is needed to make this task as easy as possible.This paper shows how the noted complicated human task can be solved by using a database Management System together with scripting and programming languages like Html and PHP respectively as the key tools in the development of a hotel reservation System.The system was developed using the object-oriented software development approach which includes the use of object-oriented analysis, object-oriented design and objectoriented programming.This was done so that the developed software can be maintainable, reliable and scalable.