Reviewerly/exHarmony huggingface dataset:
Preference elicitation with argument-based machine learning

We have developed a novel method for determining people's preferences based on their explanations of visual data. To this end, we have extended the existing framework for argument-based machine learning (ABML), which includes argument-based rule learning and an interactive knowledge refinement loop, with a recommendation engine and a pipeline based on convolutional neural networks to obtain interpretable data from images. We have developed an interactive application inspired by ABML to determine users' dating preferences. To enable a user to argue and explain his preferences based on image data, we introduced a novel approach where the user explains his preferences by drawing rectangles to select a part of the image he likes or dislikes. The ABML knowledge refinement loop allows the user to focus on the most critical parts of the current knowledge base and helps the user to adequately explain selected relevant examples - in our case, images.We have shown experimentally that the new approach to preference elicitationallows successful preference elicitation when it comes to dating. All usersfound the final selection of images useful, and the selection of images that theuser is likely to prefer gradually improved during the interaction. Theidentified preferences of each user of the application are presented as arule-based model that helps to quickly find images according to the user'staste. We have shown that this rule model is easy to interpret. All participantsfound that most of the rules in the final model matched their preferences.The beauty of our approach to preference elicitation is that, at least in principle, we can address any domain that can be represented by images, where people can explain which parts of the image they like or dislike, provided that it is possible to obtain meaningful attributes from images.
Recognition and Tracking of Moving Objects Under Video Surveillance Using Matlab

&lt;p&gt;Now-a-days its becoming very important to know about any information in a digital way in order to avoid crimes and mischief activites. Conventional methods that are used now do have limited advantages we have to check for every minute information in thorough way. By using this method, we need not put effort of many hours over monitors, instead it gives the complete information about what, how and when that happened over there. This method shows how to perform automatic detection and motion-based tracking of moving objects in a video from stationary camera. Detection of motion-based tracking are important components of many computer vision applications including activity recognition, traffic monitoring and automotive safety The problem of motion based object tracking can be divided into two parts:&lt;/p&gt; &lt;p&gt;[1]Detecting moving objects in each frame.&lt;/p&gt; &lt;p&gt;[2]Associating the detections corresponding to the same object over time.&lt;/p&gt; &lt;p&gt;For instance in a video surveillance system that aims to identify people based on their motion information, it is essential to accurately detect the moving objects and then use a robust algorithm to track them. In terms of accuracy and efficiency, the proposed method is shown to be highly accurate in determning the number of moving objects and also fast in tracking them in the scene.&lt;/p&gt;
The Impact Of Smartphone Technology On Employees Work Performance In Private Sector

The purpose of this study is to examine the impact of smartphone technology onemployees work performance in private sector’ in Kota Kinabalu, Sabah. Data weregathered from 6 employees from organization in Kota Kinabalu area. Qualitativeresearch methodology is used in this research and the data were collected using Semistructured interview as the instrument. The data were analysed using content analysiswhich was condensation, code, category, inference and summarize. The findings haveshown that distraction was the main impact of smartphone technology that makeemployees work performance decrease in private sector in Kota Kianabalu, Sabah.Besides, findings from this study also indicated that the most affecting ways to copewith this issue was employees need to stay focus and know their priority in theorganization. The study contributes to the existing pool of knowledge to theemployees in private sector in Malaysia. It has enhanced both the organization andhuman resource practitioners’ knowledge and understanding on how smartphonetechnology can impact work performance in private sector in Kota Kinabalu, Sabah.On the other hand, the result of this study could help the organization to implementand improve the usage of smartphone technology among employees for workperformance and quality to ensure the organizations can achieve their goals
LibGuides: Induction: Induction Videos

This guide is to introduce you to the Library and the services and facilities on offer to our students. Links to the induction videos for Lincoln and Newark campuses
Big Data Technology and Its Application in Future Library Practice

The digital revolution brings the mass production of all types of data, both structured and unstructured. One of thesolutions in terms of processing any type of information – text, audio, or video – lies in the development of big datatechnology. It is characterized by a large volume and variety of data that can be processed in a short period of time.The use value of the obtained results is reflected in the truthfulness and value of information that provides insightinto the datasphere of the future. This technology is applicable in all spheres of the development, from the social,natural, and technical sciences, through administration, health, education, to the economy.There are many challenges that the application of big data technology poses to librarianship. Depending on thesupport of the founders and governing bodies, innovations are introduced into institutions faster or slower. One ofthe challenges can certainly be the library budget, i.e. the available funds for new investments. From the personnelpoint of view, the challenge may be the introduction of business changes and additional obligations of employees, aswell as the organization of training in big data management. Besides, librarians should keep abreast of technologicalinnovations, trends in research and data processing, as well as legal regulations. Like any innovation, this one canalso encounter certain obstacles. They can be overcome by educating the governing body and employees, in orderto point out the benefits of this concept. Only when professional staff have fully mastered big data management willthey be able to advocate and use it.The aim of this paper is to bring big data technology closer to the professional and scientific public in Serbia andpoint out its possible applications, advantages, and challenges for library and information practices.
Towards Neural-Symbolic AI for Media Understanding

Methods based on Machine Learning have become state-of-the-art in various segments of computing, especially in the fields of computer vision, speech recognition, and natural language processing. Such methods, however, generally work best when applied to specific tasks in specific domains where large training datasets are available. This paper presents an overview of the state-of-the-art in the area of Deep Learning for Multimedia Content Analysis (image, audio, and video), and describe recent works that propose The integration of deep learning with symbolic AI reasoning. We draw a picture of the future by discussing envisaged use cases that address media understanding gaps which can be solved by the integration of machine learning and symbolic AI, the so-called Neuro-Symbolic integration.
Knowledge Distillation for End-to-EndPerson Search

We introduce knowledge distillation for end-to-end person search. End-to-End methods are the current state-of-the-art for person search that solve both detection and re-identification jointly. These approaches for joint optimization show their largest drop in performance due to a sub-optimal detector. We propose two distinct approaches for extra supervision of end-to-end person search methods in a teacher-student setting. The first is adopted from state-of-the-art knowledge distillation in object detection. We employ this to supervise the detector of our person search model at various levels using a specialized detector. The second approach is new, simple and yet considerably more effective. This distills knowledge from a teacher re-identification technique via a pre-computed look-up table of ID features. It relaxes the learning of identification features and allows the student to focus on the detection task. This procedure not only helps fixing the sub-optimal detector training in the joint optimization and simultaneously improving the person search, but also closes the performance gap between the teacher and the student for model compression in this case. Overall, we demonstrate significant improvements for two recent state-of-the-art methods using our proposed knowledge distillation approach on two benchmark datasets. Moreover, on the model compression task our approach brings the performance of smaller models on par with the larger models.
Arabic Tweets Sentiment Analysis using Hybrid Approaches

The unrestrained-access to social media makes people share their daily life; a Twitter platform allows its users to openly express and share their emotions about several issues in a predefined length.Thus, it becomes one of the most dominant networks in Arabic countries.Therefore, the Sentiment Analysis of Arabic tweets is a practical task of analyzing common sentiments and feelings.However, the existing resources regularly focus on the English language due to the shortage of Arabic Sentiment resources.In this paper, a new sentence-based sentiment analysis system had developed for Arabic tweets.Initially, the main sentiment classification approaches had applied for the sentence-level to obtain the most suitable one.As a result, the steps towards the construction of a new dataset had evaluated.The experiments show that the supervised approach is the most accurate one, especially with the absence of the Arabic dialects' (informal) lexicons.Experiments comparisons achieve satisfactory results with high accuracy (78.08%) by supervised approach, Unsupervised gives acceptable accuracy (75%), and Fmeasure (74.1%) using a Hybrid classifier.
Border Detection of Malaria Infected Cells in Microscopic Images for Diagnosis: A Computer Vision Approach

A computer vision approach is presented for border detection of malaria infected cells in microscopic blood images for accurate diagnosis. First, the microscopic 24-bits RGB color blood image converted in to 8-bits gray scale image for a single channel procesing. The poroposed two-stage thresholdingmethod used for segmentation of malaria infected cells. Regarding border irregularities, the chosen descriptor is the perimeter factor and 4-connected neighbourhood. The experimental results on benchmark dataset that comprises around 300 images show that the proposed method successfully detects borders of malaria infected cells with no prior knowledge of the contents of the image without parameter tuning. The proposed one compared with other existing methods and results are discussed.
Technology of cybernetic models’ creating for the synthesis and refinement of autonomous underwater vehicle motion control system controllers

The technology of cybernetic models’ creating for the synthesis and refinement of algorithms for controlling the autonomous underwater vehicle’s (AUV’s) motion is considered. The paper gives a description of the following sequence of actions performed at each stage of the cybernetic model development: dynamic model type and parameters identification, controller type selection, construction and analysis of the considered control loop block diagram, determination of the controller’s optimal parameters. The synthesis of heading, pitch and depth stabilization regulators for streamlined shape AUV during propulsion engines controlling is performed. The results of numerical modeling and research of the various factors influence on the quality of control are presented.
Identifying cyber hate: overview of online hate speech policies &finding possible measures to counter hate speech on internet

Being the fastest growing and highly accessible medium, todayinternet is becoming a powerful source to disseminate any sort ofcontent by individuals. World Wide Web (www) is crowded with avariety of content in the form of information, posts, comments, andmessages etc. which are readily available to internet users. The cyberworld is the hot spot to spread any particular ideology, belief,propaganda, violence or hatred against any individual or group insociety for any significant or insignificant reason that also includesspreading or becoming victim of cyber hate.This research aims to study online hate speech policies and thepreventive measures that can be taken to counter cyber hate.Researcher has evaluated top five search engines and their hatespeech policy to report any type of abusive or hateful content to beremoved that may target any specific group, bullying ordehumanizing individuals, spreading political violence and defamingsacred or revered figures on internet.
DEVELOPING ENGLISH READING MATERIAL BASED ON PROBLEM BASED LEARNING FOR GRADE XII STUDENTS OF LIGHT VEHICLE TECHNIQUE AT SMK SWASTA DWIWARNA MEDAN

This study aims to develop English reading materials needed by students of Vocational School and develop English reading materials for students of Light Vehicle Technique based on Problem Based Learning. The research was conducted by Research and Development (R and D) design through six phases; gathering information and data, analyzing data, designing new materials, validating by experts, revising and final product. It was conducted in SMK Swasta Dwiwarna Medan, especially grade XII. The data were gathered by administering interview and distributing questionnaire results prove that the students need English reading materials which contain English lecturer and the second from English teacher. It means that the developing reading materials categorized as suitable or appropriate for grade XII of Light Vehicle Technique. Key Words: Research and development (R and D), reading materials, Light Vehicle Technique
Modelling of Intelligent Cooling of a Building in MATLAB/Simulink Environment

This study analyses thermal behaviour of a house through simulation in MATLAB/Simulink environment considering the effect of outdoor environment over the same. For a given house geometry (including dimension, number of windows, thermal properties of materials used, etc.), cooler characteristics (temperature, flow rate etc.), and Setpoint, this model predicts the cost-effectiveness in view of energy efficiency. The model is developed for a room located in a hot climate zone, where in general the outside temperature is high and the room temperature needed to be set at a lower value for occupant comfort.
Analysis, optimization and modelling of electrical energies produced by the photovoltaic panels and systems

The works realized in this article concern the simulation in Pspice and the experimentation operation of the photovoltaic (PV) panels and systems. We have analyzed the optimal operation of PV panels as a function of the weather conditions (solar irradiation, temperatures…), and design of a PV system provided with MPPT command ensuring instantaneously the optimal operation of photovoltaic panels. The various results obtained show that the optimal electrical properties (voltage, current and power) of photovoltaic panels depend on the solar irradiation and the panels association (parallels or series). Also, the photovoltaic system optimizes the operation of PV panels independently the load nature: number of batteries,...
Context-Aware Convolutional Neural Network for Single Image Super-Resolution

Super-resolution is an algorithm for reconstructing high-resolution image from low-resolution image. It is one of the more active research topics in the field of computer vision. In recent years, convolutional neural network has made much progress in single image super-resolution. However, the super-resolution algorithms based on convolution network is still difficult to accurately reconstruct the image. In order to improve the reconstruction performance, it is essential to consider the channel information and spatial information of convolution network. We propose a model based on convolutional neural network and attention mechanism, which utilize channel attention modules and spatial attention modules to enhance the flow of information. The convolution network which combines the channel and spatial context information can enhance the network performance. Our model has better ability to utilize context features to more effectively reconstruct the image. Experimental results on several widely used datasets show that our model achieves better reconstruction performance than other model.
PERFORMANCE BREAKDOWN OF REACT NATIVE FRAMEWORK COMPARE TO NATIVE APPLICATIONS

Creating a mobile application often requires the developers to create one for Android and one for iOS, the two leading operating systems for mobile devices. The two applications may have the same layout and logic but several components of the user interface (UI) will differ and the applications themselves need to be developed in two different languages. This process is gruesome since it is time consuming to create two applications and it requires two different sets of knowledge. There have been attempts to create techniques, services or frameworks in order to solve this problem but these hybrids have not been able to provide a native feeling of the resulting applications. This study evaluate the React Native framework which helps developers to build cross platform application on a single code base with native feeling.
ARTISTIC AND CREATIVE ACTIVITY AS A MEANS OF EDUCATING THE PROFESSIONAL CULTURE OF FUTURE TEACHERS OF MUSIC

The article analyzes the psychological and pedagogical aspect of the phenomenon of "culture", "artistic and creative activity". It is emphasized that the professional culture of the individual is a model of a high level of mental development and should to be the norm of social life. Different approaches of scientists to the definition of professional culture are studied. The center of scientific research was the culturological paradigm in the training of future teachers of music. The problem of culturological approach of students of music-pedagogical universities is revealed, where the categorical apparatus of personality culture is analyzed. The peculiarities of the culturological approach of the students of pedagogical universities are characterized and the place and significance of the peculiarities of the culturological approach of the students of music-pedagogical universities in the educational process are substantiated. It is proved that artistic and creative activity is an effective means of educating professional culture of students of music and pedagogical universities and is a trajectory of culturological approach. The conclusions emphasize that to educate the future musician with a unique personality, as a professional, cultural carrier and subject of interpersonal relations, it is necessary to form a system of professional and cultural values that will ensure a high level of self- awareness and self-determination of future teachers and its focus on universal values, world and national spiritual culture. Therefore, the content of the subject area covers the paradigm of the phenomena of musical art, as a format of artistic values, humanistic morality and social consciousness; concepts and principles of practical improvement of musical and pedagogical activity, which contributes to raising the level of musical culture, general cultural and aesthetic levels of students; promoting the active participation of participants in artistic events in the cultural and social life of the educational institution.
Epipolar geometric association distance: A new cost function for passive sensor data association

The traditional way of passive sensor data association relies on the estimation of candidate target position, and hence suffers from severe performance degradation due to the estimation error and the so-called ghosts. The proposed new cost function is based on epipolar geometry theory that uses fundamental matrix to measure the correlation between sensor measurements directly without estimation of candidate target position. This approach has two superiorities: (1) it declines the accuracy loss caused by a large number of trigonometric operations, and (2) it greatly immunes to the impact of ghosts. A comparison with three traditional cost functions via numerical experiments demonstrates that the proposed cost function significantly improves the accuracy of data association, especially when the number of targets is more and the sensor distribution is closer.
On Convergence of Gradient Expected Sarsa(λ)

We study the convergence of Expected Sarsa(λ) with function approximation. We show that with off-line es- timate (multi-step bootstrapping) to ExpectedSarsa(λ) is unstable for off-policy learning. Furthermore, based on convex-concave saddle-point framework, we propose a con- vergent Gradient Expected Sarsa(λ) (GES(λ)) algorithm. The theoretical analysis shows that the proposed GES(λ) converges to the optimal solution at a linear convergence rate under true gradient setting. Furthermore, we develop a Lyapunov function technique to investigate how the step- size influences finite-time performance of GES(λ). Addition- ally, such a technique of Lyapunov function can be poten- tially generalized to other gradient temporal difference algo- rithms. Finally, our experiments verify the effectiveness of our GES(λ). For the details of proof, please refer to https: //arxiv.org/pdf/2012.07199.pdf.
MoDest: Multi-module Design Validation for Documents

Information extraction (IE) from Visually Rich Documents (VRDs) is a common need for businesses, where extracted information is used for various purposes such as verification, design validation, or compliance. Most of the research in IE from VRDs has focused on textual documents such as invoices and receipts, while extracting information from multi-modal VRDs remains a challenging task. This research presents a novel end-to-end design validation framework for multi-modal VRDs containing textual and visual components, for compliance against a pre-defined set of rules. The proposed Multi-mOdule DESign validaTion (referred to as MoDest) framework constitutes two steps: (i) information extraction using five modules for obtaining the textual and visual components, followed by (ii) validating the extracted components against a pre-defined set of design rules. Given an input multi-modal VRD image, the MoDest framework either accepts or rejects its design while providing an explanation for the decision. The proposed framework is tested for design validation for a particular type of VRDs: banking cards, under the real-world constraint of limited and highly imbalance training data with more than 99% of card designs belonging to one class (accepted). Experimental evaluation on real world images from our in-house dataset demonstrates the effectiveness of the proposed MoDest framework. Analysis drawn from the real-world deployment of the framework further strengthens its utility for design validation.
A social VR clinic for knee arthritis patients with haptics

Social virtual reality (VR) invites multiple users to interact in a shared immersive environment, which can be potentially useful for remote personalized healthcare. This demo presents a social VR clinic that allows patients to consult a nurse represented as a virtual avatar. It offers a walk-in virtual surgery room, enables patients to interact with animated virtual 3D artifacts, and train the patient to use an injection tool wearing a pair of mechanical VR gloves that provide haptic feedback (SenseGlove). The demo shows the potential of social VR as a new tool to help patients receive remote personalized medical care.