Reviewerly/exHarmony huggingface dataset:
A Comparative Study on the Reform of Higher Education System and Its Enlightenment

From outside and inside there is ongoing pressures drive change in higher education institutions.Change in higher education is a reality that cannot be avoided, and in many cases, it is necessary.Currently, there are several trends in higher education domain that are influencing decisive changes in educational administration policies and the procedures of academic work.This article discusses the issue of change in social institutions, with a focus on the higher education sector.It provides a comprehensive picture of the change theory, through a definition and review of concepts and models, in order to understand the triggers of change, change objectives and the challenges that usually accrue within the implementation process.This article also presents a number of strategies and lessons that may help in the planning and implementation of the change process efficiently and flexibly, and in dealing with potential failures.
Modeling and Simulation of autonomous mobile robot system for collision avoidance in VR environment using Simscape-Multibody

Autonomous mobile robots have recently become a centre of attention in the robotics community due to their ease of design, modeling and implementation, making them very lucrative in logistics, monitoring, mapping and other purposes. Fundamentally, collision avoidance is a major aspect of an autonomous mobile robot which requires assistance from other aspects like sensor fusion, localization, path planning etc., to contribute to achieving proper functionality in an open environment, hence the inherently required integration makes it hard to many researchers, robotics and robot enthusiasts to incorporate multi-dimensional functionalities in their system. Sometimes traditional software for robotics makes it harder to acquire actual insight into their system due to a lack of cross-platform compatibility. Therefore, this research aims to demonstrate a way to integrate important aspects required for obstacle avoidance system for design and analysis using a compatible system which is SolidWorks and MatLab simscape multibody, which provides sufficient scope to properly and accurately simulate autonomous systems on a real-time basis that can be used with actual hardware to final implementation. The findings of the study demonstrate that it is very much feasible to use such a method for robotic and other complex mechanics applications, and further analysis of the sensor fusion algorithm reveals some shortcomings of the sensor fusing algorithm and data processing which can be avoided by introducing further sensor sequencing and implementing adaptive neuro fuzzy-based system.
Blockchain-assisted authentication and key agreement scheme for IoT based Healthcare System

Abstract Nowadays, the research work on integration of Blockchain in IoT based Healthcare System is highly focused in order to make the system decentralised, transparent and immutable. However, there are very few works that have integrated Blockchain for authentication and key establishment in IoT based Healthcare System. The patient’s medical data collected through IoT devices are vulnerable to attack by unauthorised user. Therefore, this paper consists of blockchain based authentication and key establishment scheme. Unlike the existing work, this paper uses Consortium Blockchain in order to remove public access and reduce third-party dependency. In addition, a secret key is established between Hospital Server and Smart Device for secure communication between them. A detailed Informal security analysis shows that the proposed protocol is secure and satisfy the predefined security goals. The Blockchain concept is implemented using Hyperledger Fabric platform. This provide multi-channel support where the transactions are executed privately by creating separate channel making the proposed system more confidential. Finally, the performance analysis and comparative study shows that the proposed protocol is computationally effective and have some additional features that makes it different from the existing work.
Graph Fusion Network for Multi-Oriented Object Detection

In object detection, non-maximum suppression (NMS) methods are extensively adopted to remove horizontal duplicates of detected dense boxes for generating final object instances. However, due to the degraded quality of dense detection boxes and not explicit exploration of the context information, existing NMS methods via simple intersection-over-union (IoU) metrics tend to underperform on multi-oriented and long-size objects detection. Distinguishing with general NMS methods via duplicate removal, we propose a novel graph fusion network, named GFNet, for multi-oriented object detection. Our GFNet is extensible and adaptively fuse dense detection boxes to detect more accurate and holistic multi-oriented object instances. Specifically, we first adopt a locality-aware clustering algorithm to group dense detection boxes into different clusters. We will construct an instance sub-graph for the detection boxes belonging to one cluster. Then, we propose a graph-based fusion network via Graph Convolutional Network (GCN) to learn to reason and fuse the detection boxes for generating final instance boxes. Extensive experiments both on public available multi-oriented text datasets (including MSRA-TD500, ICDAR2015, ICDAR2017-MLT) and multi-oriented object datasets (DOTA) verify the effectiveness and robustness of our method against general NMS methods in multi-oriented object detection.
METHODOLOGICAL MODEL OF PSYCHOLOGICAL COGNITION IN MODULAR-DEVELOPMENTAL EDUCATIONAL INTERACTION

The study concerns a systematic methodological substantiation of a fundamentally new psychological solution to the scientific problem of the step-by-step deployment of modular-developmental educational interaction in the space of modern higher education institutions. It was stated that a higher school has a multi-parameter structure, multi-level organization and functionally optimizes personal growth and professional development of participants in the educational process. The strategic direction of a successful solution to this problem was the expansion of the object-subject format of scientific research. On the one hand, the understanding of the educational process is a psychologically based system of goals, tasks, forms, content, technologies, methods and tools of professionally organized education, on the other hand, the determination of psychological characteristics in a modular manner means a developmental interaction of participants in the educational process of higher education as a sequence of four periods of its innovative psycho-content support. Methodologically, it is argued that modular-developmental interaction in the conditions of higher education activates the sequence of four types of exchange (informational-knowledge, normative-volitional, cyclical-meaningful, spiritual-meaningful) and their corresponding styles of developmental interaction (inhibitory, facilitative, moderating, spontaneous) of training participants as carriers of subjective reality in the ontological hypostases of the subject, personality, individuality, universe, forms of their mental activity (behavior, activity, learning, self-creation), psychological mechanisms of deployment of polydialogic interaction (activation, intensification, actualization, self-actualization), which are grounded in the epistemic framework of principles modular-developmental interaction (mentality, modularity, development, spirituality) and the psychological content of periods of a complete educational cycle and stages of the act of psychological cognition (informational-cognitive – situation, normative-regulatory – motivation, value-reflective – action, spiritual-creative – after-action). Thus, the modular development system is based on an innovative scientific paradigm, which comes from a deep (purely psychological) and most progressive awareness of the process of socialization as a vita-cultural phenomenon. The subject of scientific knowledge here is the whole world of the psychocultural experience of mankind, in which numerous national traditions are related to the universal stereotypes, the essential characteristics of the spiritual life of society are diversified by abstract and logical forms of native culture, and scientific rationalism (laws, axioms, etc.) is organically combined with vitacultural taxa, aesthetic images and multivariate material meanings.
Incertidumbre Lógica: Pluralismo Lógico y Consecuencia Lógica

It is traditionally thought that logic leaves no room for uncertainty. The validity of arguments and whether a statement is a logical truth or not are typically not issues that invite reasons for doubt. In this paper, I argue that, despite its widespread acceptance, this view is difficult to maintain. I offer two main reasons for this conclusion: (a) In light of the plurality of logics, there are significant disagreements about the validity of arguments. (b) It is similarly difficult to reconcile the view that logic is certain with considerations to the effect that logical consequence, arguably the central concept of logic, cannot be analyzed. The very nature of logical consequence is, thus, open for doubt. After giving some illustrations in support of (a), I discuss a dilemma for the adequacy of any conceptual analysis of logical consequence, in support of (b), and respond to some possible objections. In the end, logic is what it is independently of any certainty. I close with some reflections as to why this is not a bad outcome.
Supervenience, Entailment, and Vague Objects

Not long ago came into common use, the relation of supervenience is rapidly gaining in popularity. At the same time, its logical nature, in particular its possible correlations with such fundamental logical relation as entailment, remains unresolved and needs clarification. In this paper, I compare these two relations and outline a new approach to formal explication of supervenience. In so doing, I employ as main sources two conceptions: of intensional semantics, and impossible object descriptions as its core part, introduced in section 3, and of relevant consequence relation, briefly described in section 4, where I also delineate a new entailment interpretation of supevenience. Thus, quite naturally we arrive at contradictory and incomplete descriptions of objects, and that way, uncertainty comes into play. Equally, it allows to propose a tentative definition of supervenience without referring to the terminology of the possible worlds semantics.
Search Term Identification Methods for Computational Health Communication: Word Embedding and Network Approach for Health Content on YouTube

Common methods for extracting content in health communication research typically involve using a set of well-established queries, often names of medical procedures or diseases, that are often technical or rarely used in the public discussion of health topics. Although these methods produce high recall (ie, retrieve highly relevant content), they tend to overlook health messages that feature colloquial language and layperson vocabularies on social media. Given how such messages could contain misinformation or obscure content that circumvents official medical concepts, correctly identifying (and analyzing) them is crucial to the study of user-generated health content on social media platforms.Health communication scholars would benefit from a retrieval process that goes beyond the use of standard terminologies as search queries. Motivated by this, this study aims to put forward a search term identification method to improve the retrieval of user-generated health content on social media. We focused on cancer screening tests as a subject and YouTube as a platform case study.We retrieved YouTube videos using cancer screening procedures (colonoscopy, fecal occult blood test, mammogram, and pap test) as seed queries. We then trained word embedding models using text features from these videos to identify the nearest neighbor terms that are semantically similar to cancer screening tests in colloquial language. Retrieving more YouTube videos from the top neighbor terms, we coded a sample of 150 random videos from each term for relevance. We then used text mining to examine the new content retrieved from these videos and network analysis to inspect the relations between the newly retrieved videos and videos from the seed queries.The top terms with semantic similarities to cancer screening tests were identified via word embedding models. Text mining analysis showed that the 5 nearest neighbor terms retrieved content that was novel and contextually diverse, beyond the content retrieved from cancer screening concepts alone. Results from network analysis showed that the newly retrieved videos had at least one total degree of connection (sum of indegree and outdegree) with seed videos according to YouTube relatedness measures.We demonstrated a retrieval technique to improve recall and minimize precision loss, which can be extended to various health topics on YouTube, a popular video-sharing social media platform. We discussed how health communication scholars can apply the technique to inspect the performance of the retrieval strategy before investing human coding resources and outlined suggestions on how such a technique can be extended to other health contexts.
Matched entanglement witness criteria for continuous variables

We use quantum entanglement witnesses derived from Gaussian operators to study the separable criteria of continuous variable states. We transform the validity of a Gaussian witness to a Bosonic Gaussian channel problem. It follows that the maximal means of two-mode and some four-mode Gaussian operators over product pure states are achieved by vacuum (or coherent states and squeezed states) according to the properties of Bosonic Gaussian channels. Then we have necessary and sufficient criteria of separability not only for Gaussian quantum states, but also for non-Gaussian states prepared by photon adding to or/and subtracting from Gaussian states. The criterion can be further explicitly expressed with covariance matrix of the Gaussian state or covariance matrix of Gaussian kernel of the non-Gaussian state. This opens a way for precise detection of non-Gaussian entanglement.
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation

Recent work on mini-batch consistency (MBC) for set functions has brought attention to the need for sequentially processing and aggregating chunks of a partitioned set while guaranteeing the same output for all partitions. However, existing constraints on MBC architectures lead to models with limited expressive power. Additionally, prior work has not addressed how to deal with large sets during training when the full set gradient is required. To address these issues, we propose a Universally MBC (UMBC) class of set functions which can be used in conjunction with arbitrary non-MBC components while still satisfying MBC, enabling a wider range of function classes to be used in MBC settings. Furthermore, we propose an efficient MBC training algorithm which gives an unbiased approximation of the full set gradient and has a constant memory overhead for any set size for both train- and test-time. We conduct extensive experiments including image completion, text classification, unsupervised clustering, and cancer detection on high-resolution images to verify the efficiency and efficacy of our scalable set encoding framework. Our code is available at github.com/jeffwillette/umbc
Multimedia Generative Script Learning for Task Planning

Goal-oriented generative script learning aims to generate subsequent steps to reach a particular goal, which is an essential task to assist robots or humans in performing stereotypical activities. An important aspect of this process is the ability to capture historical states visually, which provides detailed information that is not covered by text and will guide subsequent steps. Therefore, we propose a new task, Multimedia Generative Script Learning, to generate subsequent steps by tracking historical states in both text and vision modalities, as well as presenting the first benchmark containing 5,652 tasks and 79,089 multimedia steps. This task is challenging in three aspects: the multimedia challenge of capturing the visual states in images, the induction challenge of performing unseen tasks, and the diversity challenge of covering different information in individual steps. We propose to encode visual state changes through a selective multimedia encoder to address the multimedia challenge, transfer knowledge from previously observed tasks using a retrieval-augmented decoder to overcome the induction challenge, and further present distinct information at each step by optimizing a diversity-oriented contrastive learning objective. We define metrics to evaluate both generation and inductive quality. Experiment results demonstrate that our approach significantly outperforms strong baselines.
Low hanging fruit and the Boasian trilogy in digital lexicography of morphologically rich languages

Online lexicographical resources for the morphologically rich Indigenous languages in Canada use a wide range of strategies for conveying their language’s morphological system, i.e. how words are inflected and derived, which this paper illustrates in a survey of seventeen bilingual online resources. The strategies these resources employ boil down to two basic approaches to the underlying structure of the resource: 1) a lexical database, or 2) a computational model. Most resources we surveyed are constructed around lexical databases. These assume the word(form) as the basic unit, an assumption that makes it difficult to incorporate the language’s sub-word, morphological structure in full detail. However, one resource uses a computational morphological model to bring the language’s morphology into the core of the lexicon – this proved to be a “low-hanging fruit” in the application of language technology that had been accomplished within a reasonable time-frame, as has been advocated by Trond Trosterud. We discuss the value created and questions raised by this approach and argue that it successfully overcomes the traditional Boasian three-way partition of dictionary, grammar, and text, creating integrated language resources that meet the modern needs of low-resource endangered languages and their communities.
The Determinants of the Individual Absorptive Capacity in the Context of the SME: The Case of Tourism Small or Medium-sized Enterprises in the City of Agadir

Individual absorptive capacity is the individual's ability to innovate in his or her work. It is determined by the individual's ability to acquire, assimilate, transform and exploit information into knowledge and applicable skills. This work proposes to study the contribution of each of these dimensions to absorption capacity. From a sample of 37 tourism SMEs in the city of Agadir, and by controlling the different associations between the dimensions as well as the endogeneity of these dimensions concerning the absorptive capacity, our results show that the innovation of the individual in his work depends essentially on his ability to turn the information received into knowledge and to make it applicable knowledge. As both dimensions are essentially based on training and experience, this suggests the importance of specific professional training and experience in the company's innovation. Moreover, the exercise of an evolving job, characterized by non-repetitive tasks, reinforces the individual's knowledge and makes him more capable of innovating in his work.
Creating a corpus for Kven, a minority language in Norway

Language documentation, including the development and use of corpora, is frequently linked to revitalisation. This is also the case for the Kven language, a Finnic minoritised language, traditionally spoken in the two northernmost counties of Norway. Kven is a recognised minority language in Norway, protected by the European Charter for Regional or Minority Languages. This status led to increased efforts to document Kven, including the development of the Ruija Corpus, consisting of recordings of interviews in Kven. The corpus was an important tool for the standardisation of Kven. In this article we describe how the corpus was developed and account for search functions, including a discussion of the limitations of the corpus. We also discuss the role of corpora and other online tools for language revitalisation, with a particular focus on the standardisation of Kven and conclude by reflecting on how expertise also resides with the speakers of an endangered language and that they have a right to be involved in efforts of language documentation and revitalisation.
Språkdokumentasjon innen fennistikken og kvensk

The study of the Finnish language – called Fennistics – was focused on collecting Finnish dialect material from very early on. During the 19th century interest in studying dialects was governed by the idea that dialects could be used to develop modern written Finnish. However, gradually the study of dialects also became an area of study in its own right. Collecting material on Kven dialects belonged to the larger project of Fennistic materials collection from the very beginning. Therefore, many Kven dialect materials can be found in Finnish dialect archives. The documentation which resulted from dialect collections gathered via the field of Fennistics have been used in the process of revitalizing Kven. In this article, language documentation is defined to be an activity which also includes traditional dialectology. By contrast, documentary linguistics is a field of linguistics established in the 1990s which focuses on revitalizing endangered languages. The difference between language documentation in the Fennistic tradition and documentation of endangered languages in the field of documentary linguistics today is also discussed.
Cyclic feeding interactions between finite-state mal-rules

Intelligent Language Tutoring Systems typically attempt to automatically diagnose learner errors in order to provide individualized feedback. One common approach is the use of mal-rules to extend normative grammars by licensing specific types of learner errors. In finite-state morphologies, mal-rules can be implemented as two-level rules or replace rules. However, unlike the phonological rules of natural languages, mal-rules do not necessarily behave as a coherent system, especially with respect to feeding interactions. Using examples from learner errors attested in the RULEC corpus of Russian learner texts, we illustrate the problem of cyclic feeding interactions that can occur between mal-rules. We then describe a formal algorithm for identifying an optimal ordering for mal-rules to be applied to a transducer.