Reviewerly/exHarmony huggingface dataset:
Bionic Vision Descriptor for Image Retrieval

Human visual system gets remarkable performance by processing low-level features. In the last decade, many descriptors have been proposed for feature extraction. However, fewer of them get satisfying performance with low-level features. Compared to high-level ones, low-level features make use of natural underlying elements like texture and they are extracted directly, which makes low-level features more efficient in image retrieval domains. In this paper, a new descriptor named Bionic Vision Descriptor (BVD), which is based on the principle of human visual system, is proposed. The descriptor fuses uniform low-level features extracted from color, texture and gradient elements. Moreover, matrix calculation and feature selection are utilized to accelerate the calculation of BVD. Experimental results show that our method outperforms other state-of-the-art traditional descriptors with less runtime and fewer initial dimensions on benchmark datasets.
Dependability Evaluation of Middleware Technology for Large-scale Distributed Caching

Distributed caching systems (e.g., Memcached) are widely used by service providers to satisfy accesses by millions of concurrent clients. Given their large-scale, modern distributed systems rely on a middleware layer to manage caching nodes, to make applications easier to develop, and to apply load balancing and replication strategies. In this work, we performed a dependability evaluation of three popular middleware platforms, namely Twemproxy by Twitter, Mcrouter by Facebook, and Dynomite by Netflix, to assess availability and performance under faults, including failures of Memcached nodes and congestion due to unbalanced workloads and network link bandwidth bottlenecks. We point out the different availability and performance trade-offs achieved by the three platforms, and scenarios in which few faulty components cause cascading failures of the whole distributed system.
Development of rough terrain mobile robot by self-position estimation used single marker and outer Product

In the present study, a mobile robot control strategy of rough terrain capable of position and direction estimation by a single marker was proposed, and the effect was performed. To realize wheel/caterpillar mobile robot movement on the rough terrain such as house farm, two major problems (1) the precise position estimation and (2) the direction estimation are important before the development of the control theory. Generally, the position/direction have been estimated by the wheel rotation (odometry) and gyro or acceleration sensor's output integration, but there are many problems such as many impacts from the ground and the wheel slipping on the rough ground to the precise estimation. The aim of this study is to develop a method (algorithm) to estimate the mobile robot direction using a single marker placed at the top of the robot by changing the front movement and the target direction movement periodically. The reason using a single marker is that it is difficult to process to find and analyze positions of the many markers attached on the robot in the camera image from a long distance, and the positions of many markers have been unstable by the tilting of the robot, agricultural product's shadow, getting dirty of the body and so on. Our proposed method would be effective in the difficult situation to find or analyze the marker position of the robot surfaces by the reason of camera position and the environment, and it could realize wheels/caterpillar type mobile robot movement on the muddy situation.
Library Research Guides: GIMMS Guide to the United States Congress: Finding Congressional Publications

What kinds of documents does the U.S. Congress produce and how can I access them at Indiana University? Find out here! Where to locate Congressional Publications at the library and on the Internet.
Inferring Highly-dense Representations for Clustering Broadcast Media Content

We propose to employ a low-resolution representation for accurately categorizing spoken documents.Our proposed approach guarantees document clusters using a highly dense representation.Performed experiments, using a dataset from a German TV channel, demonstrate that using low-resolution concepts for representing the broadcast media content allows obtaining a relative improvement of 70.4% in terms of the Silhouette coefficient compared to deep neural architectures.
IDENTIFIKASI KOMPETENSI DAN PERFORMANSI DALAM KARANGAN BERBAHASA JEPANG

The knowledge and skills acquired or studied are a competency possessed by a learner. Competence refers to a person's basic knowledge of a system, event, or fact, which is an unobservable ability to do and display something. While performance is a concrete manifestation and can be observed or realized on a competency. This research was conducted to determine how much performance shown by Japanese language students in Japanese Literature Study Program Untag Surabaya in the sixth semester in using Japanese sentence pattern learning material in an essay. Students of Japanese Literature Study Program Untag Surabaya in the sixth semester took the Sakubun II course (Writing Level II / Intermediate). The choice of words and sentence patterns in the essays produced were compared with the number of Japanese sentence patterns they had learned. The research method used is an observation method with a qualitative descriptive approach. The results of the study stated that 1) the sentences produced in the essay used a sentence pattern that was lower than the number of sentence patterns that had been studied; 2) found sentence patterns that were not taught through required textbooks, it was alleged that students used sentence patterns they learned from other textbooks, internet, anime, mangoes, and from other sources; 3) students use sentence patterns that are adjusted to the level of writing in the Sakubun II course.
The mediating role of employee productivity for determining relationship between human resources management factors and cleaner production (case study: Shahid Bahonar Copper Industries Company)

The purpose of this research is to find the effect of factors related to the human resources management on cleaner. The research results after being ensured of the sample normality by using of the route analysis indicated that although the human resources management does not have direct and significant effect on cleaner production; but, there is a significant and direct relation between the humane indexes influencing on employee productivity and cleaner production and there is also a direct and significant effect between human resources management and employee productivity in Shahid Bahonar Copper Industry Company in Kerman. Also, the human resources management with mediation of humane indexes influencing.
Differences between DockerizedContainers and Virtual Machines : A performance analysis for hosting web-applications in a virtualized environment

This is a bachelor thesis regarding the performance differences for hosting a web-application in a virtualized environment. We compare virtual machines against containers and observe their resource ...
Modern trends in typhlobibliography in the Republic of Sakha (Yakutia)

New vectors in typhlobibliographical activities of Republican Library for the Blind are examined: the Typhlopole full-text database and the retrospective national bibliography «Publications for the blind and visually impaired in the Republic of Sakha (Yakutia) in 1971–2021».
SIRI: Spatial Relation Induced Network For Spatial Description Resolution

Spatial Description Resolution, as a language-guided localization task, is proposed for target location in a panoramic street view, given corresponding language descriptions. Explicitly characterizing an object-level relationship while distilling spatial relationships are currently absent but crucial to this task. Mimicking humans, who sequentially traverse spatial relationship words and objects with a first-person view to locate their target, we propose a novel spatial relationship induced (SIRI) network. Specifically, visual features are firstly correlated at an implicit object-level in a projected latent space; then they are distilled by each spatial relationship word, resulting in each differently activated feature representing each spatial relationship. Further, we introduce global position priors to fix the absence of positional information, which may result in global positional reasoning ambiguities. Both the linguistic and visual features are concatenated to finalize the target localization. Experimental results on the Touchdown show that our method is around 24\% better than the state-of-the-art method in terms of accuracy, measured by an 80-pixel radius. Our method also generalizes well on our proposed extended dataset collected using the same settings as Touchdown.
Penerapan Data Mining Pada Data Pelanggaran Lalu Lintas Menggunakan Metode K-Means Clustering (Studi Kasus : Pengadilan Negeri Dumai)

Dumai District Court is a place to receive, examine, decide and settle case disputes at the First Level by the applicable laws and regulations. The increase in traffic violations in the city of Dumai is due to the lack of awareness of road users towards the traffic rules, which makes a lot of ticket data received by the Dumai District Court. The algorithm used for the application of data mining is a k-means clustering method that will group some data into clusters, so that data that has the same characteristics are grouped into the same cluster and data which have different characteristics are grouped in different clusters. and is useful for getting information that is useful for policy users in the decision-making process. Samples of data taken from the table of traffic violations in 2017 were 8986 violations. This test uses the RapidMiner 5 application where the variables used to conduct the test are the type of violation and the month. So that it will produce violation data with the most types of violations, few and less.
Recognition of Gurmukhi Signboard Image Classes Based on Static and Dynamic Feature Sets

The efficient feature extraction technique plays a pivotal role in the text recognition systems. A stable and an effective feature set can help to achieve benchmarked accuracy in text recognition systems. In the present study, we aim to recognize the Gurmukhi signboard image classes using the dynamic, static and hybrid feature sets. The static features consist of the zoning and diagonal features, while dynamic features are based on the recovery of drawing order technique. The hybrid feature set comprises both static and dynamic features. An in-house dataset of the Gurmukhi characters has been developed from 820 real-time Gurmukhi signboard images as no benchmarked Gurmukhi signboard dataset is available publicly. 43 distinct classes are obtained for Gurmukhi middle zone characters having 9,544 strokes. The stroke recognition has been performed using the Support Vector Machine and Conv1D deep learning method. Best overall recognition accuracy using a hybrid feature set have been achieved using the Support Vector Machine and Conv1D deep learning method as 91.37% and 93.39% respectively. The primary objective of the proposed study is to present a comparison of the static, dynamic and hybrid features based recognition scheme for various image classes obtained from the Gurmukhi signboard images. This work can be extended for other Indic scripts as it is suitable for real-life applications.
Estimation of Design Shear Strength of Concrete Using Genetic Programming

Many codes provide empirical formulation for design shear strength of concrete which greatly vary from code to code. Moreover, many investigations into the shear problem that have been carried out have led to numerous empirical or semi-empirical formulae. These formulae usually agree quite well with the corresponding test result but not applicable for general use. The researchers have made use of experimental data set or analytical data set obtained from nonlinear finite element analysis. The equations are derived using nonlinear regression technique in which the form of the equation is required to be initially assumed. The present study investigates the application genetic programming (GP) in predicting the design shear strength of concrete. It is concluded that the values obtained by the equations derived from GP models estimate the design shear strength of concrete fairly close to the actual values.
A Combinatorial Perspective on Transfer Learning

Human intelligence is characterized not only by the capacity to learn complex skills, but the ability to rapidly adapt and acquire new skills within an ever-changing environment. In this work we study how the learning of modular solutions can allow for effective generalization to both unseen and potentially differently distributed data. Our main postulate is that the combination of task segmentation, modular learning and memory-based ensembling can give rise to generalization on an exponentially growing number of unseen tasks. We provide a concrete instantiation of this idea using a combination of: (1) the Forget-Me-Not Process, for task segmentation and memory based ensembling; and (2) Gated Linear Networks, which in contrast to contemporary deep learning techniques use a modular and local learning mechanism. We demonstrate that this system exhibits a number of desirable continual learning properties: robustness to catastrophic forgetting, no negative transfer and increasing levels of positive transfer as more tasks are seen. We show competitive performance against both offline and online methods on standard continual learning benchmarks.
Design and Implementation of Secure Video Communication Over Ip Using PYNQ-Z1 Board

Now a day’s security cameras are everywhere and are an important part of the surveillance system. Specifically, in sensitive areas cameras are essentials. So now security is a big concern for the surveillance system itself. Through covert eavesdropping Communication of surveillance systems can be tapped with various techniques this is often called bugging. A Bug is a device that is placed in an area, which then intercepts communications and transmits or conducts them out of that area to a listening post. Most of the organizations didn’t pay much attention to this vulnerability. So, in this paper solution is presented for securing communication by using pynq-z1 FPGA board.
Organizational culture and small and medium-sized enterprises performance: An empirical investigation in the Jakarta context

This study investigated the postulated relationship between organizational culture and SME’s performance. The necessity of the assessment of this relationship is driven on the basis of the past literature. For the present inquiry, the survey method was employed with a total number of 265 questionnaires. The population was drawn using stratified random sampling technique. The Smart-PLS 3.0 was used for data analysis due to its increasing popularity in presenting authentic calculations. The reporting of the results was based on Smart-PLS standards followed by a two-step approach: first, the assessment of reliability and validity was conducted using measurement model, and secondly, assessment of hypothesized relationship was done using structural model. This study underlined that organizational culture had significant relationship with SME’s performance
Modern digital technologies in teaching philological disciplines

The purpose of writing an academic paper is to analyze a variety of digital technologies, the use of which is appropriate in the process of teaching philological disciplines and the determination of the basic factors that have a decisive influence on the quality of the modern educational process. The research methods: comparison, system-structural research, statistical-analytical method, tabular, graphical, analytical modeling, as well as methods of abstraction, analysis and generalization. As a result of the generalization of modern educational trends in various European countries, it has been determined that today’s society is characterized by a high level of bilingualism and plurilingualism. The conducted study has proved that increasing level of digitalization of education is ensured through the application of effective regulatory measures by intergovernmental and national governments, as well as standardization, formalization, high quality educational services and integration of new digital technologies in teaching process.
SURVEY ON CONSENSUS ALGORITHMS IN BLOCKCHAIN FOR SECURE DATA SHARING

Blockchain technology is one of the latest innovations that provides a secured decentralized, distributed database of records of all transaction and digital events. In recent years, blockchain technology is being applied in many powerful applications such as financial services, smart contracts, healthcare, supply chain management, e-voting etc. As blockchain ensures high security, it is being trusted and accepted by many business organizations. Consensus algorithms are the primary component of blockchain technology that maintains integrity and security in blockchain. This paper reviews consensus algorithms in blockchain technology that were applied in the recent research works for providing data sharing security. The importance of consensus algorithms in blockchain, their advantages and disadvantages are discussed in this paper.
A Study of QoE-Aware Adaptation Mechanism for DASH Video Streaming based on Objective Visual Quality Assessment

Dynamic Adaptive Streaming over HTTP (DASH) is a largely used video streaming technique. One key point is its adaptation mechanism which resides at the client's side. This allows various context-aware adaptation strategies in order to optimize the overall Quality of Experience (QoE) of the video streaming. In this paper, we present a study on an adaptation mechanism which uses an objective visual quality assessment, namely the Structural Similarity Index Measurement (SSIM) metric, as a key criterion for adaptation. More specifically, the SSIM helps to maximize the effective use of the available bandwidth, in the sense that we adopt a higher bitrate not only because it is allowed by network conditions, but also because it does bring a significant visual quality improvement (measured through SSIM metric). In this way, an upgrade in bandwidth consumption will be allowed only if there is a real contribution to visual quality. This study has been tested through a series of experimental results obtained with several strategies for the choice of the threshold value. Our tests are all based on real mobile-network traffic traces and real video sequences.
A NOVEL INTERPRETABLE WEB-BASED TOOL ON THE ASSOCIATIVE CLASSIFICATION METHODS: AN APPLICATION ON BREAST CANCER DATASET

Aim: The second-largest cause of cancer mortality for women is breast cancer. The main techniques for diagnosing breast cancer are mammography and tumor biopsy accompanied by histopathological studies. The mammograms are not detective of all subtypes of breast tumors, particularly those which arise and are more aggressive in young women or women with dense breast tissue. Circulating prognostic molecules and liquid biopsy approaches to detect breast cancer and the death risk are desperately essential. The purpose of this study is to develop a web-based tool for the use of the associative classification method that can classify breast cancer using the association rules method. Materials and Methods: In this study, an open-access dataset named “Breast Cancer Wisconsin (Diagnostic) Data Set” was used for the classification. To create this web-based application, the Shiny library is used, which allows the design of interactive web-based applications based on the R programming language. Classification based on association rules (CBAR) and regularized class association rules (RCAR) are utilized to classify breast cancer (malignant/benign) based on the generated rules. Results: Based on the classification results of breast cancer, accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score values obtained from the CBAR model are 0.954, 0.951, 0.939, 0.964, 0.939, 0.964, and 0.939 respectively. Conclusion: In the analysis of the open-access dataset, the proposed model has a distinctive feature in classifying breast cancer based on the performance metrics. The associative classification software developed based on CBAR produces successful predictions in the classification of breast cancer. The hypothesis established within the scope of the purpose of this study has been confirmed as the similar estimates are achieved with the results of other papers in the classification of breast cancer.
EUR ArTeC: Networking for Art, Science, Technology, and Humanities through Hydrology of Media

The Ecole universitaire de recherche (EUR) ArTeC is a consortium of fourteen French institutions including universities, art schools, museums, and archives. ArTeC (which stands for Arts, Technologies, numerique, mediations humaines et Cre-ation) was established in 2018 at the initiative of Paris 8, Nan-terre and Paris Lumiere with the intention to consolidate a long-term project inter-pollinating arts and sciences for education and research. While the multi-and interdisciplinary approaches are fundamental for us, we aim at focusing on art and creativity as the entry points to studies and practices that proliferate with the use of digital technologies. In this institutional presentation we will describe the main aspects of Ar-TeC and a brief overview of an ongoing project that reunites several international teams to reflect on environment-related issues.
Winning design for 2021 Road Safety calendar unveiled

The winner of South Lanarkshire Council’s annual Road Safety Calendar Competition has been announced.
The libraries: The transformation formula

Methods and approaches to transforming traditional libraries focused on the collections, to the new type of libraries to be focused on comprehensive facilitation of user intellectual and creative activities and, correspondingly, on advancement of the society being served, are discussed. The author argues that the key principle for the regenerated libraries would be users’ intensive participation in their content development, with the projects as the key method, number of users participating in intellectual and creative activities as the main criteria; and the libraries’ transforming into the community development center as the principal result of this transformation.
User Testing with Kids

User testing doesn’t necessarily come at the end of the development process. You can test an idea at the very beginning with low-fi prototypes, even paper prototypes. And you should test along the way any time you think it would be beneficial, for example, to test a specific functionality or interaction before moving forward with it. For sure though, it’s something you want to do before releasing to the market.
Improving recommendation by deep latent factor-based explanation

The Thirty-Fourth AAAI Conference on Artificial Intelligence: Interactive and Conversational Recommendation Systems (WICRS) Workshop, New York, United States of America, 7-12 February 2020