Reviewerly/exHarmony huggingface dataset:
THE ROLE OF KNOWLEDGE MANAGEMENT IN IMPROVING THE PERFORMANCE OF MEDIA INSTITUTIONS: A CASE STUDY OF ABU DHABI TV

The purpose of this quantitative study is to recognize the relationships between Knowledge management and its processes such as creativity, innovation, and media content and process development. A questionnaire was distributed to all the employees (N.55) working in Abu Dhabi TV. The findings of the study showed that the employees of Abu Dhabi TV are aware of knowledge management and its components at a high level ranging between 6.84%, 6.79% and the simple regression analysis showed that there is a relationship between KM, creativity, innovation, media content and process development.
Content-Based Near-Duplicate Video Detection Using Density-Based Clustering: OR-DBSCAN

With advanced technologies employed in multimedia and web sectors, video data on the Internet is multiplying. As a result, the number of near-duplicate videos (NDVs) found on video uploading platforms is increasing. These NDVs often violate copyrights or clutter web search results, and hence, accurate procedures that detect NDVs are a necessity. In this paper, we propose a novel content-based near-duplicate video detection system. We consider that, given a query video and a database of videos, the goal is to find the similarity percentage of the query video with the original video from the database of videos. Following points summarize the key features of this paper: (1) Content of the video is defined by its visual features and not the metadata. (2) A novel adaptation of the density-based spatial clustering of applications with noise (DBSCAN) algorithm is implemented to perform clustering. (3) For search space optimization and in order to make the approach economical in time, object detection using You Only Look Once version3 (YOLO v3) is employed.
Effectiveness enhancement of non-contact vacuum pumps working process

Abstract Three options of rotor profiles of Roots vacuum pump are considered: elliptic, circular, and involute. Rotor profiles are drawn in the same housing and are analyzed from point of view of backward leakage minimization through inter-rotor channel and geometric pumping speed increase. It is shown that coefficient of working volume use is only 3% higher for involute profile. Averaged over one revolution conductance of rotor mechanism channels is minimal for elliptic rotor profile. For inter-rotor channel it is 14% less than for involute profile. The presented approach makes it possible to choose the optimal rotor profile of Roots pump for particular purpose.
Pattern Exploration as Keyword Search

Frequent pattern mining is one of the central tasks in data mining with broad applications in diverse domains. The mining process typically returns an overwhelmingly large number of patterns, making pattern evaluation and exploration extremely difficult. In this project, we adapt and extend information retrieval techniques to implement pattern retrieval, where we introduce Peak, an IR-based system that features a user-friendly keyword search interface allowing users to effectively explore itemset and sequential patterns based on their interest.
Discrete Linear Geometry on Non-square Grid

We define the algebraic discrete geometry to hexagonal grid system on a plane. Since a hexagon is an element for tiling on a plane, hexagons are suitable as elements of discrete objects. For the description of linear objects in a discrete space, algebraic discrete geometry provides a unified treatment employing double Diophantus equations. Furthermore, we develop an algorithm for the polygonalisation of discrete objects on the hexagonal grid system.
Possible lightweight modification of hashing algorithms GOST R 34.11-94 and GOST R 34.11-2012

Abstract The paper discusses the development of a lightweight modification of the hashing algorithms GOST R 34.11-2012 and GOST R 34.11-94. The quality of optimization of the obtained algorithms and their safety are considered.
End-to-End Recurrent Cross-Modality Attention for Video Dialogue

Visual dialogue systems need to understand dynamic visual scenes and comprehend semantics in order to converse with users. Constructing video dialogue systems is more challenging than traditional image dialogue systems because the large feature space of videos makes it difficult to capture semantic information. Furthermore, the dialogue system also needs to precisely answer users' question based on comprehensive understanding of the videos and the previous dialogue. In order to improve the performance of video dialogue system, we proposed an end-to-end recurrent cross-modality attention (ReCMA) model to answer a series of questions about a video from both visual and textual modality. The answer representation of the question is updated based on both visual representation and textual representation in each step of the reasoning process to have a better understanding of both modalities' information. We evaluate our method on the challenging DSTC7 video scene-aware dialog dataset and the proposed ReCMA achieves a relative 20.8% improvement over the baseline on CIDEr.
High Beam Detection Method Based on Deep Learning

Managing the illegal use of high beams can reduce the occurrence of night traffic accidents. However, at present, there is no efficient detection method for high beam of night, and relevant traffic regulations cannot be effectively implemented. In order to solve this problem, an algorithm to detect the high beam at night was proposed in this paper. Based on YOLOv3, this algorithm optimizes the network structure of Darknet53, retains the information integrity of the object, accelerates its operation speed, uses standard residual components and dilated convolution to enhance the feature expression ability of the network, and uses K-means++ algorithm to optimize the prior bounding boxes clustering. The experimental results show that the mean average precision (mAP) of the algorithm designed in this paper is 98.88%, which is 50% higher than the efficiency of YOLOv3. The algorithm satisfies the practical requirement and could detect the violation effectively.
Research on Prediction of “Four Difficult Students” Based on Contextual Awareness in the Era of Big Data

Aiming at the problem that the predictive effect of the “four difficult students” is difficult to achieve the expected results, a context-aware framework of the “four difficult students” inclined student prediction is proposed. This framework introduces the contextual factors in the environment of students, and further explores the relationship between the students, their situations, and the characteristics of the “four difficult students At the same time, the framework improves the ability of dimensionality reduction and prediction generalization in feature selection. The experimental results show that the context-aware “four difficult students” tendency student prediction framework can be effectively applied to “four difficult students” tendency prediction, so as to provide powerful early warning and timely intervention for the management work of college students.
Association Rules Extraction from Date’s Product Dataset Using the Apriori Algorithm

When working with large data collections to obtain, in a short time, the most relevant information they contain, it is possible to perform pattern extraction by means of Data Mining. Among the most used patterns are Association Rules, which measure the co-occurrence of items in large collections of transactions. After many trials, one type of transaction has been found that can be treated more efficiently than the one that has been used up to now. In this study, a new method was applied to this type of transactions, which allowed to obtain in the first tests much faster execution times and more information than the one obtained with the classic Association Rules Mining Algorithms. This will allow to improve the response times of a web recommendation system to provide answers to the users in real time.
Research on Mixed Teaching of Big Data Technology and Application Specialty Based on Internet

In recent years, with the continuous development of science and technology students' individualized learning and obtain better teaching results, the author draws big data with the interactive teaching platform and analyses the learning behaviour of learners to summarize the general laws. "Online Offline" mixed teaching environment, differentiated mixed teaching method, mixed teaching method,it mixedevaluation focusing on process evaluation, effective integration of interactive teaching platform and teaching resources the aspect discussed restructures the mixed teaching mode.
Y robot extension module for educational and marketing purposes

At the Faculty of Management Science and Informatics, of University of Žilina an initiative was created to support the increase of interest in the study of hardware oriented programmees, such as the Computer Engineering programmee which we offer. This paper focuses at further explanation of one of the additional modules of the open-source platform Yrobot. Yrobot is a modular education robotic platform which is dedicated to support the teaching of robotics and other hardware subjects in high schools and universities. The extension module based on Bluetooth technology enables wireless work and control of Yrobot, which can be used and extended at the robotics lessons in teaching.
Strategic Planning for Polytechnic Information Systems with an Enterprise Architecture Planning Approach

Abstract Higher education institutions in implementing information systems need strategic planning, especially for Polytechnics in Indonesia. It is intended that the application of the information system is in accordance with the vision, mission and objectives of the Polytechnic. The Polytechnic information system strategic planning uses the Enterprise Architecture Planning method. The Enterprise Architecture Planning method provides an overview of data architecture, application architecture and technology architecture from the application of information systems so that the Polytechnic is not wrong in implementing information systems. The result of this research is the form or formulation of information system strategic plan which is suitable for higher education especially for Polytechnic. The information system strategic plan consists of a data architecture, there are 41 entities, while for data and application architectures there are 8 application candidates. In addition, the results of the information system strategic plan in the technology architecture section to support the Polytechnic business processes are also built.
Personalized Menu: a New Contextual Collaborative Recommender System

The varied number of suggested meals put people who spend most of their time outside to a confusing situation. In addition, the proposed items (meals) are standard for all people, meaning that they receive the same menu, although they differ in many attributes such as age, weight, health status, eating habits and tastes. A recommendation based on nutritional value can help people to prevent or control certain diseases such as diabetes, hypertension and obesity. However, learning about people's food preferences and making recommendations that simultaneously appeal to their health expectations, which can be very difficult, is really a very difficult task. Many existing recommendation systems do not take into account the context in which the user is placed and often suffer from the cold start system problem. Through this work, we propose a new collaborative and contextual recommendation system that allows the target user to be directed towards healthy menu of tasty meals. For this, the proposed approach was named Healthy and Tasty (H&T). H&T is a recommendation system based on a multilayer architecture, where the highest layer is based on the pre-filtering algorithm, which eliminates the cold start system problem, and is based mainly on the thresholds of the compatible nutritional elements with the user profile, thus ensuring the healthy factor in the recommendations. The middle layer based on collaborative filtering algorithm works in particular to ensure the taste factor, while the deepest layer is the pertinent layer based on the post-filtering algorithm, where the recommendation will be much more adapted to the environment of the user. The proposed approach has been realized via an Android application where the experimental results are promoters.
Light Field Stitching Based on Mesh Deformation

Light field is a potential technology which can help us get richer information from the world. However, light field is limited by the field of view (FOV). Stitching multiple light fields is a solution to raising FOV of light field. In this paper we present a method that can keep the angular consistency when stitching the light fields. We first use the traditional two-dimensionall (2D) image stitching method to stitch the central sub-aperture images (SAI). We can obtain the disparity maps of the light fields, and get the disparities on two directions. Then the disparity maps can help us get a group of control points to guide the mesh grids in the SAIs to deform and warp them to a new panorama. We evaluate the stitched light field by its epipolar plane image (EPI) and the ability of refocusing. The experimental results show that our method can stitch 4D light field effectively and keep the consistency of spatial and angular domain.
Experimental Research on Bearing Characteristics of the Asphalt Pavement Containing Buried Pipeline

The bearing characteristics of the asphalt pavement structure are greatly influenced by buried pipelines. Improper treatment of buried pipelines would cause early damage to pavement structure. By the digital speckle correlation method (DSCM), the experimental research on bearing characteristics of the asphalt pavement containing buried pipe was carried out. The mechanical characteristics of the asphalt pavement structure are studied under four different pipeline burial conditions. The vertical displacement and strain values of each layer of the asphalt pavement structure are obtained under four operating conditions. The results showed that (1) the digital speckle observation test method can accurately obtain the displacement and strain values of each layer of asphalt pavement structure containing buried pipeline, and the application effect is good. Compared with the traditional contact strain measurement method, this method is simple and accurate and can provide effective analysis data for experimental research. (2) There exists an interlayer effect of the asphalt pavement structure. The vertical displacement value and the strain value are discontinuities and can suddenly change between two adjacent layers. At the same time, the vertical strain and the shear strain concentration phenomenon appear at the bottom of each layer, especially at the bottom of the upper layer and the subbase layer of asphalt. (3) Affected by the buried pipelines, the vertical displacement value of the asphalt pavement structure reduces, and the tensile and shear strain values of asphalt pavement structure increase. The subbase layer of asphalt is most affected by the buried pipelines, which accelerated the destruction of the asphalt pavement structure.
Robust Calibration of a Multi-View Azure Kinect Scanner Based on Spatial Consistency

In this work, we introduce a new calibration method for a camera system comprising five Azure Kinect. The calibration method uses a ChArUco coded cube installed in the middle of the system. A new 3D optimization cost is proposed to overcome the IR camera noise and to enhance global 3D consistency of the captured model. The cost includes the repro-jection error and the point to plane distance. As a refinement stage, along with point to plane distance, a patch to plane distance is added in the cost to overcome the noise effect of the depth camera. The experimental results demonstrate that the proposed calibration method achieves a better reprojection error and more stable results in terms of standard deviation of the estimated pose compared to the state-of-the-art. In addition, the qualitative results show that the proposed method can produce a better registered point cloud compared to conventional calibration.
What Segments Are the Best in Representing Contours?

A pixel-by-pixel (iconic) computer representation of an image takes too much memory, demands lots of time to process, and is difficult to translate into terms that are understandable for human users. Therefore, several image compression methods have been proposed and efficiently used. The natural idea is to represent only the contours that separate different regions of the scene. At first these contours were mainly approximated by a sequence of straight-line segments. In this case, for smooth contours a few segments are sufficient to represent the contours; the more curved it is, the more segments we need and the less compression we get as a result. To handle curved edges, circle arcs are now used in addition to straight lines. Since the choice of segments essentially influences the quality of the compression, it is reasonable to analyze what types of segments are the best. In the present paper we formulate the problem of choosing the segment type as a mathematical optimization problem and solve it under different optimality criteria. As a result, we get a list of segment types that are optimal under these criteria. This list includes both the segments that were empirically proven to be efficient for some problems, and some new types of segments that may be worth trying.
The Design and Implementation of Arrow Game Projection Interactive System Based on Deep Learning

With the rapid development of projection technology, the implementation and study of projection interactive system with different scenarios has made great progress. Humans are no longer just satisfied with the traditional way of interacting with computers through peripheral devices, but are eager to obtain a more natural and friendly mode of interaction. Thus, an arrow game projection interactive system based on deep learning is designed and implemented in this paper. Firstly, an arrow game scene including varieties of vivid interfaces is developed by Unity3D in order to improve user experience. Secondly, a method of mapping the position of arrow in the captured image to the corresponding position of game scene is achieved. Thirdly, object recognition is realized by using the target detection algorithm based on YOLOv3. Finally, the experiment results demonstrate that the novel pattern of interactive system has good real-time performance and high robustness.
The Use of Genetic Algorithms for Cryptographic Keys Generation

On the base of Vernam’s cipher security conditions the encryption key must be greater than or equal to the open text we want to encrypt. On the other hand, this key must not be repeated in another encryption. Also, each change of the encryption key adds security to the encryption process. If a cipher is changed several times while encrypting a single open text, it becomes very difficult to decrypt the message. Therefore, our goal was to design a method to generate an encryption key for a Tree Parity Machine by Genetic Algorithm. This method is able to create the same encryption keys on both sides that enter the encryption process. These keys could be changed during encryption. One of the first tasks is to create an input population for the genetic algorithm from the synchronized Tree parity machine. In this paper, the modified genetic algorithm for cryptography system was implemented and demonstrated. Genetic Algorithm is used to produce new population of cryptographic keys. The paper starts explaining the basic theory of the Tree Parity Machine and the proposed method of cryptographic key generation by Genetic Algorithm is presented and then the results will be analyzed.
The Role of Multi-Criteria Decision-Making in a Sentry Agents Framework Utilizing Uncertainty of Information

Information has a dire role when it comes to decision-making, especially in complex multi-domain operational environments. While it can be assumed that obtaining more information is more beneficial, it can lead towards several challenges. For a decision maker, to collect and assess large quantities of information in order to make an informed decision can be a difficult task. The decision-making task becomes more problematic due to the imperfect nature of information expressed through the uncertainty of information (UoI) concept. This paper proposes implementing multi-criteria decision making (MCDM) within a dynamic multi-agent-based framework called Sentry Agents (SAGE), which allows for the simulation of various decision-making scenarios and diverse decision maker behaviors. We evaluate how MCDM can measure interdependence between criteria, and how that impacts the determination of an ideal course of action in a decision-making task.
Possibilities of using the electronic constructor "ZNATOK" at informatics lessons in primary school

The article discusses the possibilities of using the electronic constructor "ZNATOK" when studying the initial course of informatics. There are described four main directions of using the constructor: 1) when studying the concepts of "model" and "modeling"; 2) when studying the concept of "algorithm"; 3) when studying the device of a computer; 4) in the process of getting acquainted with the concept of "information processes". Possible stages of working with the constructor when considering these topics are presented: examples of exercises; methodological techniques that contribute to better memorization of educational material; planned learning outcomes for schoolchildren; possible areas of work in middle and high school. The material can be used not only by school teachers, but also by specialists of additional education system, as well as in higher education system in the preparation of bachelors in the areas of training 03.04.01 "Pedagogical education", 44.03.05 "Pedagogical education (with two training profiles) ", masters of the direction of training 44.04.01 "Pedagogical education", in the courses of advanced training of teachers.
AVOXI Integrates ZenDesk, HubSpot, FreshDesk and ServiceNow into its Cloud Communications Platform

News & Press Releases March 18th, 2021 .FixedLinks{ display: block; position: fixed; z-index: 99999; top: 50%; right: 0; ...
Recommended Methods for Using the 2020 NIST Principles for AI Explainability

In August 2020, the United States National Institute of Standards and Technology (NIST) published (NISTIR 8312) which promulgated for review four principles for Artificial Intelligence (AI) explainability to assist researchers and practitioners in the AI field. These four principles, defined in more detail in the NIST document, are Explanation, Meaningfulness, Explanation Accuracy, and Knowledge Limits. The principles were tied to five types of explainability: User Benefits, Societal Acceptance, Regulatory and Compliance, System Development, and Owner Benefits. The proposed approach is to engage knowledgeable researchers and practitioners to offer ideas congruent with the four principles and five types of explainability. In addition to more detailed frameworks and approaches within the bounds of NISTIR 8312, participants will examine the NIST propositions for completeness and sufficiency.