Reviewerly/exHarmony huggingface dataset:
Anytime Case-Based Reasoning in Large-Scale Temporal Case Bases

This work has been funded in part by the project PlayS and, by the project ´ Innobrain - New Technologies for the Innovation in Cognitive Stimulation and Rehabilitation, COMRDI-15-1-0017 (RIS3CAT comunitats); and the project SGR, 2017-SGR-172 from Generalitat de Catalunya; and FEDER funds.
EOSC-SYNERGY EU Milestone: M6.2 First release of the customized training platform including self-deployable tutorials capabilities, and HaaS platform

EOSC-SYNERGY receives funding from the European Union’s Horizon 2020 research and innova on programme under grant agreement No. 857647.
The Placeholder View of Assumptions and the Curry–Howard Correspondence (Extended Abstract)

Proofs from assumptions are amongst the most fundamental reasoning techniques. Yet the precise nature of assumptions is still an open topic. One of the most prominent conceptions is the placeholder view of assumptions generally associated with natural deduction for intuitionistic propositional logic. It views assumptions essentially as holes in proofs (either to be filled with closed proofs of the corresponding propositions via substitution or withdrawn as a side effect of some rule), thus in effect making them an auxiliary notion subservient to proper propositions. The Curry-Howard correspondence is typically viewed as a formal counterpart of this conception. In this talk, based on my paper of the same name (Synthese, 198(11), 10109–10125, 2021), I will argue against this position and show that even though the Curry-Howard correspondence typically accommodates the placeholder view of assumptions, it is rather a matter of choice, not a necessity, and that another more assumption-friendly view can be adopted.
Supervised and Unsupervised Learning Theory for Signal Processing

A decent approach for refining in the true machine learning method is to appraise the data, to state the goal, to assess accessible algorithms, and to know fruitful applications. Evaluation of the data is required to know if the data is labeled or unlabeled and is the master idea is in need to support extra labeling. Evaluating the data helps to determine the supervised, unsupervised, or semi-supervised learning method to be used. Defining the goal helps to know if the problem recurs back or to know whether the algorithm predicts the new problem. By reviewing the existing algorithm, it helps in finding out the dimensionality, features, attributes, and characteristics. Study in the machine learning concept is a grouping of invasive well-known essential questions and emerging new programs for modeling the necessities of new machine learning applications. Improved thoughtful in what way supplementary data, such as unlabeled information, suggestions from an operator, or ex-sophisticated responsibilities, can supreme be used by an ML algorithm to develop its competence to train new things. ML model has focused on problems of cultivating a task (say, recognizing the difference) from labeled instances. Access to large quantities of unlabeled data potentially provides useful information, e.g., other hints from the user besides just labels, such as highlighting relevant portions of the information or previously learned information and to transfer the same experience to the present job. These are all matters for which a compact theory needs to be developed.
Indistinguishability Obfuscation of Null Quantum Circuits and Applications

We study the notion of indistinguishability obfuscation for null quantum circuits (quantum null-iO). We present a construction assuming: - The quantum hardness of learning with errors (LWE). - Post-quantum indistinguishability obfuscation for classical circuits. - A notion of ''dual-mode'' classical verification of quantum computation (CVQC). We give evidence that our notion of dual-mode CVQC exists by proposing a scheme that is secure assuming LWE in the quantum random oracle model (QROM). Then we show how quantum null-iO enables a series of new cryptographic primitives that, prior to our work, were unknown to exist even making heuristic assumptions. Among others, we obtain the first witness encryption scheme for QMA, the first publicly verifiable non-interactive zero-knowledge (NIZK) scheme for QMA, and the first attribute-based encryption (ABE) scheme for BQP.
Documenting Information Processes and Practices: Paradata, Provenance Metadata, <scp>Life‐Cycles</scp> and Pipelines

Abstract Processes and practices—and in general, informational doings and their diverse constellations—are pertinent elements of the information landscape. This panel presents research on documentation and description of processes and practices in the information field addressing: 1) how different conceptualisations of processes and practices influence how they emerge as describable entities; 2) what different approaches to document and describe processes and practices exist and have been proposed in information science and technology research; 3) what aspects of processes and practices different documentation approaches capture, make visible and invisible; and 4) what novel insights from the current state‐of‐the‐art research can be drawn to support practitioners in different areas of the information field, including knowledge organisation, information management, information literacy instruction, and development of information systems and services.
Analysis Of Breast Cancer Data Using Machine Learning Techniques

Now a days breast cancer in the world is one of the issuessince this disease occurs second place in the developed country.In medical field providing proper awareness, but the ratio of outreach the people understand the cancer awareness is less. The world health organizationreleased an article that  breast cancer is one of the challenging problems and  most of women affected by breast cancer sometimes one percentage of possibility for men also. The main aim of the study to analyze breast cancer data based on its characteristics and identify the effectiveness of clustering and classification instructions for analyzing breast cancer data. Breast cancer related images, different characteristics, including numerical data and attributes are used in this research work.Patients intake routine, age, lifestyles, occupation, details of diseases that cause problems are taken and then carry out for machine learning based classification and clustering  algorithms.And eventually clustering algorithms like k-Means and Expectation-Maximization (EM), and classification algorithms such as J48, Classification and Regression Trees (CART) and Support Vector Machine (SVM) are trained   as well as tested.The overall  performance of clustering and classifications are based on sensitivity, specificity, accuracy, error rate and process time.
USING SMARTPHONE VIDEO CAMERA TO CREATE DIGITAL STORIES FOR SPEAKING ACTIVITIES

The common problems faced by students in learning English speaking were anxiety, lack of confidence and lack of ideas. This research was conducted to determine the relevant factors and to present a solution by using a video camera smartphone application. To obtain data on this case, the experimental research was carried out in class and outside the classroom with a series of treatments and a questionnaire sheet was used as an instrument. Data were analyzed using the model proposed by Creswell (2012). The results of the study found that students had positive developments which were described bellows; the anxiety tends to decrease because they were given time before performing and they were prepared better, their self-confidence was increased and challenged by the method of using a smartphone video camera due to the application of new innovations in the speaking class. In addition, this smartphone application also affected students' learning styles to focus more on new things (cameras) and not be monotonous. The conclusion was to improve the speaking quality of students; lecturer needs to apply new methods, one of which was using a smartphone application. In addition to practicing self-confidence, students can master smartphone technology and create new energy in learning English.
Kompetensi Pustakawan IAIN Kudus dan UIN Walisongo Semarang dalam penulisan karya ilmiah

This research takes the theme of the problems of librarians in producing written works. The purpose of this research is to describe the competence of librarians in writing in the present era, and to reveal the problems faced by librarians in producing written works, seen from the supporting factors as well as from the librarian barrier factors in writing. Qualitative research is kind of the research used in this research, with a phenomenological approach. Interviews, observation and documentation as a data collection method. This study took informants from librarian elements who were then referred to as research subjects from IAIN Kudus and UIN Walisongo Semarang as research locus. The results of this study are that the writing competence of PTKIN librarians has penetrated the world of publications both in print and virtual, both the carrying capacity of writing competencies depends on cultural and structural support capacity and librarian obstacles in writing are plagiarism concerns, lack of reading activity, difficulty determining topics, laziness, lack of mastered references, and low credit numbers.
Multiple Detections Application for Indoor Tracking Using PIR Sensor and Kalman Filter

Recently, human tracking in multiple indoor environments is getting broadly in demand to enhance security surveillance. Traditional passive video surveillance shown that it has working ineffectively nowadays because the number of cameras has exceeded the ability of operators to monitor them. In this paper, we proposed methods of detecting human presence using Pyroelectric Infrared (PIR) Motion Sensor and tracking people in multiple indoor locations using Kalman filter-based estimation. The proposed method is implemented to analyze the movement of people within the prescribed area and the result will be presented in footprint mapping of the said area. This will further enhanced building security surveillance especially at the sensitive or restricted areas. Experiments for single target tracking in several areas are carried out to verify the application of the developed system. As the results, the maximum error for tracking trajectory reduced from 0.28m to 0.19m and average error for tracking trajectory also reduced from 0.10m to 0.07m after using Kalman filter estimation algorithm.
Σημεία στίξης στο Facebook: τελεία, κόμμα και άνω τελεία στον Τοίχο του Facebook μαθητών/μαθητριών Γυμνασίου

This study tries to map the punctuation landscape in a Greek-language digital environment, namely Facebook postings of adolescents. Employing a computer mediated communication analysis perspective, the question asked is: what is the status of period, comma and semicolon? The data show that the main use of the period is to indicate the finality of an utterance, whereas the comma retains its written discourse functions. As far as semicolon is concerned, it is non-existent in the data, partly because of the affordances of the medium, partly because its role is substituted by periods or commas. Punctuation use depends on user identity.
The challenges of integrating artificial intelligence applications and algorithms in the production of journalistic content

This study aimed to find out the level of awareness of experts about the possibility of integrating journalism into artificial intelligence algorithms, to find out whether there is a significant difference between experts and specialists in their awareness of the transformations that artificial intelligence algorithms may bring about, and to find out whether there is any significant difference between experts in their perception of professional practices. that can be performed by artificial intelligence algorithms. An open-ended questionnaire was used to collect data, which was distributed to a sample consisting of 178, to examine four hypotheses: that artificial intelligence algorithms in journalism are able to collect, analyse and formulate data in traditional journalistic templates and forms, that artificial intelligence algorithms will completely solve the tasks of a traditional journalist, that artificial intelligence algorithms in journalism will force changes in communication theories and structural construction of journalistic forms, Integrating AI algorithms into journalism shortens content production and marketing processes in no time. The study concluded with a set of results, the most important of which were: Artificial intelligence is still a new field for journalism, and within narrow limits, writing style is still the main component, and journalism needs human intervention when applying algorithms. Opinion differs about the changes that artificial intelligence applies to communication theories Infrastructure preparations will affect the acceleration of AI algorithms in journalism, sending and receiving.
Flexible Non-contact Capacitive Sensing for Hand Gesture Recognition

Hand gesture recognition has become a popular research topic of human machine interface (HMI), and effective wearable sensor is an important component in the loop of hand gesture recognition system. In this paper, we introduce a flexible non-contact capacitive wristband that can be used to detect both wrist and finger gestures. To demonstrate the effectiveness and performance of the designed prototype, nine wrist gestures and ten finger gestures were selected. Five subjects participated in the experiment. To validate the importance of considering spacial relationship among channels, especially when discriminating intricate finger gestures, CNN was implemented and compared with LDA. In the wrist gesture recognition task, LDA achieved the average accuracy of 98.38%, and CNN achieved the average accuracy of 99.81%. In the finger gesture recognition task, LDA achieved the average accuracy of 90.04%, and CNN achieved the average accuracy of 95.54%. This study suggested that the designed flexible non-contact capacitive wristband could be used as an alternative for hand gesture recognition, and considering spacial relationship among channels on different measuring location yields better recognition result.
Multi-target dataassociation and identification in binary sensor data

Thegrowing availability of consumer hardware has made various usecases of activity monitoring possible. The more complex theactivity or behavior that needs to be recognized, the more dataneeds to be collected. The sensors required to do so are oftenperceived as an invasion of privacy and therefore commonly rejectedin domestic settings. Conversely, low resolution sensors such asmotion sensors and magnetic contact switches provide little data toderive relevant information from, but are not perceived as invasiveand offer other benefits such as long battery life, being lowcostand easy to retrofit. We show that two residents of a two-bedroomapartment can be reliably tracked using basic ambient sensors only.We show that the tracking accuracy largely depends on the numberand positioning of the sensors and that tracking is particularlydifficult when two persons often cross paths or occupy the samespace. Combining ambient and body-worn sensors, such asacceleration data from a smartphone, by improving the motion modelof the tracking update function improves trackingaccuracy.%%%%Diesteigende Verfugbarkeit von gunstiger und verlasslicherVerbraucher-Sensorik ermoglicht eine Vielzahl von neuartigenAnwendungsfallen des Aktivitatsmonitoring. Je komplexer dieAktivitat bzw. das Verhalten ist, das vermessen werden soll, destomehr Daten mussen erhoben werden. Die Sensoren dafur werden haufigals Eingriff in die Privatsphare wahrgenommen und deshalb vonEndanwendern abgelehnt. Demgegenuber stehen niedrigauflosendeSensoren wie Bewegungsmelder und Kontaktsensoren, die zwar einzelnwenig Informationen liefern, aber als weniger invasiv angesehenwerden und zudem andere Vorteile wie einen einfachen Einbau mitsich bringen. Diese Arbeit zeigt, dass zwei Personen in einerWohnung mit Hilfe von einfachen ambienten Sensoren uber einenlangen Zeitraum nachverfolgt werden konnen. Die Genauigkeit desTracking-Algorithmus hangt stark von der Anzahl und Positionierungder Sensoren ab und die Tracking-Genauigkeit sinkt, wenn zwei odermehr Personen haufig den gleichen Raum einnehmen. Die Arbeit zeigtauch, dass die Kombination von ambienten und korpernahen Sensorendie Genauigkeit des Tracking-Algorithmusverbessert.
Positive psychological science: Improving everyday life, well‐being, work, education, and societies across the globe. DonaldsonSI, CsikszentmihalyiM &amp; NakamuraJ (EDS.) New York, NY: Routledge, 2020, 304 pages, $52.95 softcover.

Personnel PsychologyVolume 74, Issue 4 p. 867-868 BOOK REVIEW Positive psychological science: Improving everyday life, well-being, work, education, and societies across the globe. SI Donaldson, M Csikszentmihalyi & J Nakamura (EDS.) New York, NY: Routledge, 2020, 304 pages, $52.95 softcover. Eleni Lobene, Corresponding Author Eleni Lobene eleni.lobene@gmail.com Chief Human Resources Officer, District Growth, Washington, DC, USA Correspondence Eleni Lobene, Chief Human Resources Officer, District Growth, 1200 Potomac Ave. S.E., Washington, DC 20003. Email: eleni.lobene@gmail.comSearch for more papers by this author Eleni Lobene, Corresponding Author Eleni Lobene eleni.lobene@gmail.com Chief Human Resources Officer, District Growth, Washington, DC, USA Correspondence Eleni Lobene, Chief Human Resources Officer, District Growth, 1200 Potomac Ave. S.E., Washington, DC 20003. Email: eleni.lobene@gmail.comSearch for more papers by this author First published: 13 October 2021 https://doi.org/10.1111/peps.12487Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume74, Issue4Winter 2021Pages 867-868 RelatedInformation
AN INTERACTIVE PEDAGOGICAL ASSESSMENT TOOL USING MESSENGER CHATBOT IN LEARNING DELIVERY

This study was conducted to find out the efficacy of an interactive pedagogical assessment tool using chatbot in learning delivery. It significantly sought answer to the questions; What is the status of using chatbot as an assessment tool in learning delivery to students in terms of: objective, content, evaluation. What is the respondent’s level of acceptability in terms of: usability, quality factor, and ease of use? Is there a significant effect in the performance of the learners as respondents after using Messenger Chat bot as an interactive pedagogical assessment tool?The researcher coordinated with the TLE teachers of Pila Senior High School to select forty (40) students based from the students’ exposure to the use of messenger chatbot. The distribution of questionnaire and collection of data to the respondents were gathered using google form. This research employs quantitative and non-experimental design utilizing correlational technique. The researcher used descriptive research that aimed to know the effects of using messenger chatbot as an interactive pedagogical assessment tool in learning delivery.The data gathered has been codified into various traditional categories with appropriate hypothetical in null and working forms and subsequently tested by non- parametric treatment through P-value and F-value formula respectively to arrive substantial conclusion can be drawn in the resolution with the foregoing problem areas investigated. From the above step-by-step research cycle process, the basic questions propounded are resolved.......
Flexible Dispute Derivations with Forward and Backward Arguments for Assumption-Based Argumentation

Assumption-based argumentation (ABA) is one of the main general frameworks for structured argumentation. Dispute derivations for ABA allow for evaluating claims in a dialectical manner: i.e. on the basis of an exchange of arguments and counter-arguments for a claim between a proponent and an opponent of the claim. Current versions of dispute derivations are geared towards determining (credulous) acceptance of claims w.r.t. the admissibility-based semantics that ABA inherits from abstract argumentation. Relatedly, they make use of backwards or top down reasoning for constructing arguments. In this work we define flexible dispute derivations with forward as well as backward reasoning allowing us, in particular, to also have dispute derivations for finding admissible, complete, and stable assumption sets rather than only determine acceptability of claims. We give an argumentation-based definition of such dispute derivations and a more implementation friendly alternative representation in which disputes involve exchange of claims and rules rather than arguments. These can be seen as elaborations on, in particular, existing graph-based dispute derivations on two fronts: first, in also allowing for forward reasoning; second, in that all arguments put forward in the dispute are represented by a graph and not only the proponents.
Sectorized variable duty cycle f/1 diffractive transmission sphere for compensation of negative diffractive effects

Diffractive Transmission Sphere (DTS) can be successfully used for interferometric testing. Unfortunately, phenomena of annular rings occur on interferogram in a case of small period of diffractive patter. This effect reduces quality of measurements and became critical for apertures close to f/1. This work is devoted to computer simulation of such effects and development of technique for their partial compensation. It was proposed to do this compensation by modifying duty cycle. Computer simulation on the base of the rigorous coupled wave analysis was performed. Experimental DTS with was fabricated and tested.
LibGuides: Library Technologies: Library Technologies

The aim of this libguide is the help students with accessing the library technologies, such as the computers, printers, etc.
A Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments.

Deep Reinforcement Learning (DeepRL) methods have been widely used in robotics to learn about the environment and acquire behaviors autonomously. Deep Interactive Reinforcement Learning (DeepIRL) includes interactive feedback from an external trainer or expert giving advice to help learners choosing actions to speed up the learning process. However, current research has been limited to interactions that offer actionable advice to only the current state of the agent. Additionally, the information is discarded by the agent after a single use that causes a duplicate process at the same state for a revisit. In this paper, we present Broad-persistent Advising (BPA), a broad-persistent advising approach that retains and reuses the processed information. It not only helps trainers to give more general advice relevant to similar states instead of only the current state but also allows the agent to speed up the learning process. We test the proposed approach in two continuous robotic scenarios, namely, a cart pole balancing task and a simulated robot navigation task. The obtained results show that the performance of the agent using BPA improves while keeping the number of interactions required for the trainer in comparison to the DeepIRL approach.