Reviewerly/exHarmony huggingface dataset:
Applying Cognitive Theories &amp; Methods to the Design of Computerised Medical Decision Support

This paper describes an approach to cognitive engineering which promotes a symbiosis between the theories and methodologies of cognitive psychology and the practices of human-computer interaction design. We ground the description of our approach in a particular design problem: the development of computerised decision support in medical intensive care. We review the psychological literature of medical reasoning and decision making, highlighting its potential to inform the design of medical computerised aids. We also discuss how addressing this design problem may in turn benefit cognitive theory. This is followed by a brief description of our proposed methodology.
Responding to a school SARS-CoV-2 outbreak: Insights and policy implications emerging from the pandemic.

The SARS-CoV-2 pandemic has affected also the school environment. Prolonged closures and the weakness of available data prevent a definitive answer to the question of school transmission. We report our experience of responding to COVID-19 cases in the school setting, presenting a case study of the management of an outbreak in a large school.The LHA/ASL Roma 1 has organized the School Units with a structure firmly rooted in the territory. At the local level, the District Unit mainly manages the relationship with schools, while the Hygiene and Public Health Service of the Prevention Department holds a coordinating and facilitating role. The HPHS carries out contact tracing activities facilitated by the schools, through the figure of the COVID-19 Contact Person, who is specifically trained to manage the preliminary stages of the reports.Following several reports of COVID-19 suspect cases from two schools and, after a complex phase of contact tracing, it was possible to identify the major transmission chains. Furthermore, we performed a population-based screening on the entire school. Beyond the known transmission chains, for which quarantine was already in place, only five additional cases emerged, all asymptomatic, out of 1,231 swabs tested with RT-PCR.Our experience confirms that an active interaction between the school and the School Unit made it possible to quickly control a potentially dangerous outbreak. The large-scale screening test demonstrated the substantial absence of collateral transmission chains. Effective contact tracing allowed to set forth a successful response. Our model of intervention can be used to support public health protocols regarding school outbreaks.
Words and Worlds: The Construction of Context for Definite Reference

Two eyetracking experiments were conducted to investigate how the domain of interpretation for referential expressions is constructed and coordinated during utterance processing. Of particular interest was how the uniqueness requirement for a definite noun phrase (e.g. ‘the book’) could be satisfied given a particular array of candidate referents. Experiment 1 demonstrated that the conceptual relation expressed by a preposition immediately limits attention to compatible referents and in turn facilitates definite reference to these objects. Experiment 2 showed that domains are further constrained by the judgment of which referents are compatible with an intended action, and that uniqueness can be established by such factors even when several objects compatible with the noun phrase are present in the perceptual field. The results demonstrate that domains of interpretation for referential expressions are constructed and updated dynamically as an utterance unfolds in time, taking both linguistic and nonlinguistic factors into account.
A Blockchain Enabled System for Security, Non-Repudiation and Integrity of Judiciary Proceedings

Judiciary systems and their proceedings are complex in nature but it is crucial to safeguard they are protected and not modified in any form without necessary authorization. Evidences pertaining to court cases are to be protected and made available and accessible to authorized people for faster closure of cases. The origin of this proposal is from the day to day experiences of judiciary systems and the lack of technology exploitation to promote efficiency and transparency in the system. Particularly Blockchain technology and data science platform with AI are used to ensure protection to judiciary proceedings and evidence documents associated with court cases. It ensures that the system is highly available, accessible to authorized people and all the transactions are immutable. From the literature and other real world sources, it is evident that there is need for improving speed and efficiency of judiciary system in different dimensions. This is the motivation and origin for this proposal.
Enhancing acoustical design using parametric optimization of surface geometries

Raytracing is commonly used to design surface geometries. To optimize this process, we propose combining a parametric design approach with an evolutionary solver. These optimization principles are widely implemented across engineering fields and could be exploited for acoustical design. Evolutionary optimization is an iterative tool to increase the “fitness”—or optimality—of a predefined target value, in this case reflecting and non-reflecting geometries given any acoustical design brief. The iterative nature of an evolutionary solver—which evaluates each generation in terms of its proximity to the target value—enables acousticians/designers to continually assess results at different stages of the optimization process. The proposed algorithms optimize parameters such as size, shape, number or orientation of surfaces by defining raytracing target values (e.g., number of rays reaching a receiver after n-reflections, density of rays in a diffuse field). We implement this approach using standard software: the Galapagos solver within the Grasshopper framework, a parametric design tool in the Rhino 3D environment. The limitless design options offered by the parametric approach are thus made available for acoustical optimization. This method can be used on all scales of geometrical acoustics, from alignment of absorber panels to geometries of enclosed spaces, such as concert halls.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review : Single Anonymous • Conference submission management system : The submission management was an on website uploading type one. Each abstract was uploaded on the conference website and the papers were sent directly via conference e-mail. • Number of submissions received : 65 • Number of submissions sent for review : 51 • Number of submissions accepted : 47 • Acceptance Rate (Submissions Accepted / Submissions Received × 100) : 72.3 • Average number of reviews per paper : 2 • Total number of reviewers involved : 48 • Contact person for queries: Name : Dorin Radu Email : dorin.radu@unitbv.ro Affiliation : Transilvania University of Brasov
User Specific Semantic Search for Encrypted Data

Cloud computing is the one of the service oriented applications which is used for the various users according to the requirements. Searching is the most widely used in many applications for the retrieving of the various data or documents according to the user keyword search. Accessing of cloud data which is encrypted is most widely used with the help of many encryption and decryption algorithms. In this paper, the user specific semantic search for the various encrypted data (USSSED) is introduced to overcome the issues in the previous systems. Results show the performance of the proposed system in terms of security and searching data.
Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflow

Welcome to the 21st IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2021)! We hope that you enjoy the conference and that it will inspire you in your future research. Should you require a certificate of participation please contact Alexander Serebrenik, the general chair of SCAM, at a.serebrenik@tue.nl. For questions related to the Morressier virtual platform please contact support@morressier.com.
Assessing General Framework against Other HCI Frameworks

The chapter assesses the General Framework for HCI research for completeness against other frameworks for HCI. The General Framework comprises concepts of discipline, general as common, general problem, particular scope, general research, general knowledge and general practices. These concepts are assessed for completeness against 10 individual other frameworks, which are in turn assessed for completeness against the General Framework. Overall, the General Framework is considered to be complete, although this depends much on the coherence of individual concepts. This assessment, however, does not constitute a validation of the General Framework. It is nevertheless indicative of its comparability with other HCI frameworks with respect to its completeness. The frameworks are further considered as concerns their dissemination in the HCI research literature. Dissemination is understood to include the framework’s disseminators, as well as the dissemination’s content, media and means. The General Framework is then assessed for its accommodation of the factors that appear to influence the success of framework dissemination.
Bolashaq fızıka muǵalіmderіnіń ádіstemelіk quzіrettіlіgіn qalyptastyrýda oqý-ádіstemelіk tapsyrmalardy qoldaný [Use of Educational and Methodical Tasks in Formation of Methodical Competence of Future Teachers of Physics]

In this article the features of application of educational and methodical tasks at formation of methodical competence of future teachers of physics are considered. Researches of scientists on competences in various areas are analyzed. There are necessary conditions for the preparation of educational and methodical tasks. As an example, there are several tasks. Methodical activity of future teachers of physics is presented in the table. The features of open and closed tasks were considered, and examples were given. Бұл мақалада болашақ физика мұғалімдерінің әдістемелік құзіреттілігін қалыптастыруда оқу-әдістемелік тапсырмаларды қолдану ерекшеліктері қарастырылады. Түрлі салалар бойынша ғалымдардың құзіреттіліктер бойынша зерттеулері талданған. Оқу-әдістемелік тапсырмаларды дайындау үшін қажетті шарттар берілген. Мысал ретінде бірнеше тапсырма келтіріледі. Болашақ физика мұғалімдерінің әдістемелік қызметі кесте бойынша берілген. Ашық және жабық тапсырмалардың ерекшеліктері қарастырылып, мысалдар берліген.
Defending Humans in the Loop:Applying HCI for National Cybersecurity.

implementation of the goals outlined in Presidential Executive Order (EO) on Strengthening the Cybersecurity of Federal Networks and Critical Infrastructure (May 2017): To help owners and operators of critical infrastructure identify, protect, detect, respond, and recover cyber threats. ITCF helps organizations with the following features: provides an easy to use rapid assessment tool to perform an insider threat self-assessment; determines the current insider threat cybersecurity posture; defines investment based goals to achieve a target state; connects the cybersecurity posture with business processes, functions, and continuity; and finally, helps develop plans to answer critical organizational cybersecurity questions. In this paper, the webtool and its core capabilities are depicted by performing an extensive comparative assessment over two different high-profile insider threat incidents.
Framework for Hybrid Book Recommender System based on Opinion Mining

Recommender system plays an important role in automatic filtering out the important and personalized information for the intended user from a large amount of available information on internet. Recommender systems for books provide personalized recommendations to the readers for reading and to the librarians for book acquisition process. The objective of this research paper is four folds. Firstly, it conducts an extensive literature review pertaining to book recommender systems, secondly it specifies the popular recommendation techniques being used in specific application area of books, thirdly the paper reflects on the methodology followed and evaluation techniques being used based on the techniques discussed. Lastly, the paper proposes a framework for a book recommender system using best-suited recommendation techniques.
Characterization of Search and Rescue Aircraft

Several different aircraft have been used in aviation search and rescue mission. The use of the aircraft in such mission has been mostly for common purpose of scouring the sea or land to identify and locate the victims. In addition, they are also utilized for rescue mission with some specialized equipment onboard. This study aims to identify the myriad of aircraft that have been used in the aviation search and rescue mission, and perform the simplistic analysis on their common and uncommon denominators. Based on the results, it has been established that these aircraft often have a small capacity and perimeter coverage, with low flight pace and rate of climb performance capabilities.
Application of Random Forest Prediction Technology in the Management of Public Opinion Events in Colleges and Universities

As an important window for the exchange and collision of various ideological trends, colleges and universities should strengthen the monitoring and management of network public opinion in the we media era, and timely grasp the ideological trends and behavior tendencies of college students, which is of great significance to avoid large-scale public crisis events, create a clear network space, and promote the construction of a harmonious campus. Therefore, the network public opinion management has undoubtedly become an important part of the ideological and political work. There are still some problems in the network public opinion management of colleges and universities in China, such as backward management mode, weak management consciousness and imperfect management mechanism. Only by keeping up with the pace of the times, paying close attention to the construction of management system, strengthening network ideological education, and constructing the prevention, monitoring and emergency response mechanism of network public opinion in Colleges and universities, can the management of network public opinion in Colleges and universities be in place one step, and promote the benign development of campus network environment. This paper analyzes the relevant literature through forest prediction technology, and then explores the public opinion of colleges and universities.
Training a Deep Learning Network with an Insignificantly Small Dataset

In the last few years, Deep Learning is one of the top research areas in academia as well as in industry. Every industry is now looking for a deep learning-based solution to the problems in hand. As a researcher, learning “Deep Learning” through practical experiments will be a very challenging task. Particularly, training a deep learning network with huge amount of training data will make it impractical to do this on a normal desktop computer or laptop. Even a small-scale application in computer vision using deep learning techniques will require several days of training the deep network model on a very higher end Graphical Processing Unit (GPU) clusters or Tensor Processing Unit (TPU) clusters that makes impractical to do that research on a conventional laptop. In this work, we address the possibilities of training a deep learning network with an insignificantly small dataset. Here we mean “significantly small dataset’ as a dataset with only few images (&lt;10) per class. Since we are going to design a prototype drone detection system which is a single class classification problem, we hereby try to train the deep learning network only with few drone images (2 images only). Our research question is: will it be possible to train a YOLO deep learning network model only with two images and achieve a descent detection accurate on a constrained test dataset of drones? This paper addresses that issue and our results prove that it is possible to train a deep learning network only with two images and achieve good performance under constrained application environments.
Large-scale Content-based Multimedia Analysis And Applications Using Bag-Of-Words Model

This dissertation focuses on the analysis of large-scale image and video data consortia with applications to multimedia indexing and retrieval. Bag-of-words (BoW) model is adopted and improved to suit the efficiency and effectiveness requirements in analyzing large-scale multimedia data. BoW method has been developed from the text retrieval domain and successfully applied in computer vision, such as image scene and object categorization. Specifically, we utilized the BoW model in the domain of image classification and retrieval, tackled challenges of large-scale multimedia applications of video analysis and mobile-based social activity recommendation using visual intents, respectively. Incorporating the BoW model with unsupervised classification, we propose a scalable and generic approach in video analysis. The method aims at systematically analyzing unlabeled video from its genre identification, frame classification, and event detection. Unlike conventional domain-knowledge dependent approaches, the BoW model is domain-knowledge independent. Moreover, the system is mainly unsupervised and requires minimum human input. Therefore, our method is capable of processing massive quantity of videos generically. In addition, for the evaluation, sports video has been used as the testing ground. Combining the BoW model with advanced retrieval algorithms, we propose a mobilebased visual search and social activity recommendation system. The merit of the BoW model in large-scale image retrieval is integrated with the flexible user interface provided by the mobile platform. Instead of text or voice input, the system takes visual images captured from the built-in camera and attempts to understand users’ intents through interactions. Subsequently, such intents are recognized through a retrieval mechanism using the BoW model. Finally, visual results are mapped onto contextually relevant information and entities (i.e. local business) for social task suggestions. Hence, the system offers users the ability to search information and make decisions on-the-go.
Jurisgenesis

Can law keep up with runaway technology? In an era of runaway corporate surveillance, artificial intelligence, deep fakes, election hacking, social media disinformation, do-it-yourself biology, genetic modification, automation, and three-dimensional printed medical implants, law has seemed to take a back seat to rampant technological change. To listen to Silicon Valley barons, there is nothing any of us can do about it.CAN LAW KEEP UP? calls their bluff. The book provides a fresh look at law, at what it actually is, how it works, and how we can create the kind of laws that help humans survive and thrive in the face of technological change. It shows that law can keep up with technology because law is a kind of technology – social technology built by humans out of cooperative fictions like firms, nations, or money. To survive the challenges of the future, we need a new kind of law, and a new way of understanding how humans use language to cooperate, to build an ever-growing and ever-changing system of understandings about how we can secure the benefits of changing technology to all.
Optimization of the Size of Dstatcom System Based on Data – Driven Control Design

This paper elaborates on a Distributed Static Synchronous Compensator (DSTATCOM). It renders a setup of hardware which provides compensation of power along with the optimization of the size of DSTATCOM set up. This DSTATCOM hardware set up reduces the power loss through compensation of power, regulates the voltage profile and increases the power factor. The performance of the DSTATCOM for linear and nonlinear loads was simulated.
Optimal Feature Selection using Particle Swarm Optimization with Random Forest Classifier for Lymph Diseases Prediction

ML-based data classification approaches can be used as a decision making tool in various fields such as healthcare, disease prediction, etc. Presently, most of the data in medical domain comprise nature of high dimensionality Sometimes, FS (FS) methodologies is employed to improvise the classification results especially for high dimensionality issue by extracting the appropriate training instances to more number of determined features. This paper made an attempt to study the application of FS approaches on the classifier performance. For FS, genetic algorithm and particle swarm optimization (PSO) algorithm is used whereas random forest (RF) classifier is used for classification lymph diseases dataset. In the first stage, GA and PSO are used to reduce the feature subset and in the second stage, RF classifier is used. From the experimentation part, it is evident that the PSO based FS increases the classifier results compared to GA based FS. It is also studied that the FS process improvises the classifier results in a significant manner interms of diverse performance measures.
Preface

The 2019 International Conference on Artificial Intelligence Technologies and Applications (ICAITA 2019) was held in Qingdao, China, from 5 to 7 July 2019. The conference report reflects the current interests of international and Chinese research circles, such as artificial intelligence applications, artificial neural networks, natural computing, parallel processing, pattern recognition, programming languages and data mining. The 2019 International Conference on Artificial Intelligence Technology and Applications is a multidisciplinary conference that brings together students, young researchers, postdoctoral and experienced researchers working in different research fields to promote the gathering and sharing of interests and to achieve results so as to achieve better cooperation The Conference work was carried out in 3 sections: ● Artificial Neural Networks and Intelligent Application Technology ● Scientific Computing and Novel Computing Models ● Communications applications and Power Electronic Equipment Committee member List of Conference Chairs, Technical Program Committee, Conference Secretary are available in the pdf.
Pedagogical knowledge axiology: a palette of views and logical-epistemological code

Based on the analysis of epistemological works, the spectrum of components reflecting the value-loaded pedagogical knowledge is designated: a) knowledge embedded in the cultural environment; knowledge that has become a cultural phenomenon; b) knowledge enabling to solve practical problems relevant to the society; c) knowledge, recognized from the point of view of epistemological attributes, methods for its production, “protoform” and the degree of empirical, theoretical and contextual validity; d) pedagogical knowledge as a part of social reality or, otherwise, social determination of pedagogical knowledge. The third and the fourth components are discussed in detail. The project of “incorporating” pedagogy into the philosophical and epistemological glossary is presented: the categories of quantity and quality, of the part and the whole, identity and difference, form and content, essence and phenomenon, direct and indirect knowledge, pedagogical concept, judgment, inference analyzed in the light of an individual’s awareness of the way of its obtaining and degree of reliability. “Minto code” (complex cases of a causal analysis of the pedagogical field) is given a special attention. “Social determination of academic pedagogical cognition” is presented as a “lower layer” of the value-loaded knowledge.