Reviewerly/exHarmony huggingface dataset:
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction

There is growing interest in large-scale machine learning and optimization over decentralized networks, e.g. in the context of multi-agent learning and federated learning. Due to the imminent need to alleviate the communication burden, the investigation of communication-efficient distributed optimization algorithms - particularly for empirical risk minimization - has flourished in recent years. A large fraction of these algorithms have been developed for the master/slave setting, relying on a central parameter server that can communicate with all agents. This paper focuses on distributed optimization over networks, or decentralized optimization, where each agent is only allowed to aggregate information from its neighbors. By properly adjusting the global gradient estimate via local averaging in conjunction with proper correction, we develop a communication-efficient approximate Newton-type method Network-DANE, which generalizes DANE to the decentralized scenarios. Our key ideas can be applied in a systematic manner to obtain decentralized versions of other master/slave distributed algorithms. A notable development is Network-SVRG/SARAH, which employs variance reduction to further accelerate local computation. We establish linear convergence of Network-DANE and Network-SVRG for strongly convex losses, and Network-SARAH for quadratic losses, which shed light on the impacts of data homogeneity, network connectivity, and local averaging upon the rate of convergence. We further extend Network-DANE to composite optimization by allowing a nonsmooth penalty term. Numerical evidence is provided to demonstrate the appealing performance of our algorithms over competitive baselines, in terms of both communication and computation efficiency. Our work suggests that performing a certain amount of local communications and computations per iteration can substantially improve the overall efficiency.
Image Denoising Algorithms and DWT: A Concept

A extremely good mission in the field of image processing these days, is image denoising. Although, there have been proposed diverse techniques and algorithms for the identical, however, maximum of them have no longer attained the desirable results. The performance does not fit with the assumed one. The wavelet principle is enormously the latest idea on this field. The fundamental purpose of this study (paper) is to study various algorithms and discrete wavelet remodel, and knowledge the idea of denoising thoroughly.
Other options for your h-card as well ...

Other options for your h-card as well without using display: none (which I do sometime in a pinch). Check out this page: https://indieweb.org/authorship#How_to_publish I like
LibGuides: Marketing Research And Planning For Your Business: THE PRODUCT

A guide introducing you to the basics of marketing and recommending which databases to use for effective research results.
A SURVEY ON RECENT TRENDS IN CONTENT BASED IMAGE RETRIEVAL SYSTEM

Content-Based Image Retrieval (CBIR) is a technique that uses image display features such as color, composition, shape, texture, etc. to search for the desired image of the user from the big image database in the form of a query image. These peculiar features of the images are taken, and a similarity check is implemented as the images. The issue of retrieving content-based image is based on peculiar query generation. Related images meet their information needs, either by leveraging a sketch as an automatic search or by submitting image-like features. The similarity between the extracted features can be measured using different mechanisms. Improves process optimization by using appropriate feedback as a post-recovery step. The on-demand image is always encouraging to explore the growing volume and develop video-efficient CBIR algorithms. Various functions and models of image retrieval have been sought in the last twenty years. In this study, the CBIR aims to present a detailed study of the area, the recent development of image representation, the key parts of image portrayal and image portrayal models from low-level feature extraction to ongoing semantic deep learning draws near. Significant ideas of the research reports dependent on CBIR and image portrayal were examined in detail, and future research will keep on empowering further research right now.
Deep Reinforcement Learning for Dialogue Systems with Dynamic User Goals

Dialogue systems have recently become a widely used system across the world. Some of the functionality offered includes application user interfacing, social conversation, data interaction, and task completion. Most recently, dialogue systems have been developed to autonomously and intelligently interact with users to complete complex tasks in diverse operational spaces. This kind of dialogue system can interact with users to complete tasks such as making a phone call, ordering items online, searching the internet for a question, and more. These systems are typically created by training a machine learning model with example conversational data. One of the existing problems with training these systems is that they require large amounts of realistic user data, which can be challenging to collect and label in large quantities. Our research focuses on modifications to user simulators that change their mind mid-episode with the goal of training more robust dialogue agents. We do this by taking an existing dialogue system, modifying its user simulator, and observing quantitative and qualitative effects against a set of goals. With these results we demonstrate benefits, drawbacks, and tangential effects of using various rules and algorithms while recreating goal changing behavior.
“Spinning In”: the merger of Canadiana.org with the Canadian Research Knowledge Network / Réseau Canadien de deocumentation pour la recherceh.

This article explores the background and process that led to the merger of the Canadian Research Knowledge Network / Réseau Canadien de deocumentation pour la recherceh and Canadiana.org in 2018. Seizing a moment of opportunity in a rapidly shifting digital research landscape, the two organizations “spun in” to each other in order to leverage their complementary mandates and overlapping memberships. The new merged organization is now better positioned to meet the challenges of collaborative work in research and Canadian heritage content acquisition and access.
The Development of Performance Management Indicators and Model for ‘Eup·Myeon·Dong Lifelong Learning Center’ : The Case of Seoul Metropolitan Government’s ‘Community Learning Center Project’

「평생교육법」에 명시된 읍·면·동 평생학습센터는 근거리 평생학습 기회 보장과 마을공동체 형성의 거점 역할을 할 수 있다는 점에서 매우 중요하다. 이 연구는 서울시 ‘한걸음에 닿는 동네배움터 사업’을 사례로 읍·면·동 평생학습센터의 정책적 가치와 철학을 반영한 성과관리체제를 개발하는 데 목적이 있다. 이를 위해 관련 정책 분석, 현장 방문 조사, 서울시 동네배움터 사업관계자 및 성과관리 전문가 초점집단인터뷰 및 설문조사를 진행하였다. 연구 결과로 읍·면·동 평생학습센터 운영에 관여하는 자치구, 현장 운영자, 학습자 별로 성과를 관리할 수 있는 성과지표를 제안하였다. 자치구는 ‘기반구축’, ‘학습공간’, ‘학습활동’, ‘협력과 확장’을 중점 영역으로 12개의 세부 지표를, 운영자는 ‘기획·개발’, ‘운영·지원’, ‘학습·실천’, ‘평가·반영’을 중점영역으로 10개의 세부 지표를, 학습자는 ‘자기성장’, ‘관계의 질’, ‘공동체 활동’을 중점영역으로 12개의 세부 지표를 제안하였다. 이를 바탕으로 <공동체디자인 플레이어(CD-PLAYER, 민주주의, 현실관여, 되살리기를 목표로 한 장소 기반 평생학습과 행동)>라는 가치기반 윱·면·동 평생학습센터 성과모형과 ①성과 달성형, ②자치구 성과 달성형, ③운영자 성과 달성형, ④ 학습자 성과 달성형, ⑤성과 미흡형, ⑥자치구 성과 미흡형, ⑦운영자 성과 미흡형, ⑧학습자 성과 미흡형이라는 유형을 제안하였다.It is important that the ‘Eup·Myeon·Dong Lifelong Learning Center’, as specified in the Lifelong Education Act, can serve as a base for securing near-distance lifelong learning opportunities and forming local communities. The purpose of this study is to develop a performance management system that reflects the policy values and philosophy of the Eup·Myeon·Dong Lifelong Learning Center, using a case of the “Community Learning Center” project from Seoul Metropolitan Government. The following study involves policy analysis, field research, survey and focus group interviews with officials and experts. Based on the results of the study, three indexes for a district (Gu), an operator, and a learner of the community learning center are proposed. There are a total of 12 sub-indicators for the district (Gu), 10 sub-indicators for the operator, and 12 sub-indicators for the learner. The core indicators for the district (Gu), operator, and learner are as follows: foundation building, learning space, learning activity, and cooperation-expansion; planning-development, operation-support, learning-practice, and evaluation-reflection; self-growth, quality of relationships, and community activities. Based on the performance management indicators for each subject, a performance management model of CD-PLAYER (Community Design: Place-based Lifelong Learning & Action for demoracY, Engagement, and Revitalization) and eight different types of evaluation scores (① Performance achievement, ② Autonomous district’s performance achievement, ③ Operator’s performance achievement, ④ Learner’s performance achievement, ⑤ Poor performance, ⑥ Autonomous district’s poor performance, ⑦ Operator’s poor performance, ⑧ Learner’s poor performance) are suggested.
A Study on the Internalization of Sensor Technology by Comparison of IT Leading Countries

The 4th Industrial Revolution is a revolutionary change through intelligence, big fusion and personalization, and the importance of sensor technology that is the basis of core technology is emerging. This study empirically analyzes the derivation of national strategy for R&D of sensor technology, and draws out the effect of technology internalization effort through strategic R&D activities on technical performance and further on national economy. The research and development results are calculated for each type of technology internalization, and the results of the research and development are verified to establish a structure that contributes to the national economic performance. As a national technology internalization strategy, considering its own R&D investment and joint research and development, we examine the impact of each factor on patents and GDP, focusing on causality and ripple effects. For causality analysis, Grandeur causality analysis shows that R&D investment and joint research and development in all countries have mutual causal relationship with GDP. The implications are as follows. First, it is necessary to establish the policy of national economic development through the internalization of technology and knowledge. Second, it is necessary to establish policies according to the type of knowledge internalization. Third, it will be necessary to create an ecosystem environment based on a virtuous relationship between knowledge internalization and national technology and economic development.
Listening and speaking as powerful literacy practices

The aim of this paper is to establish the significance of listening and speaking as key and powerful components of effective literacy practices. The analysis is based on the Neo-Vygotskian theory, and on the methodology of communication content analysis, and speech monitoring strategies in educational contexts. The nature of oral discourse is analyzed from a functional, an ontogenetic, and a phylogenetic perspective, but also as a tool of symbolic power and knowledge. Τhe paper constitutes a theoretical meta-analysis of the subject. Listening and speaking as active literacy processes are discussed and two major models of oral communication are outlined, the dialogic and the transmission model. Finally, the paper presents research findings on effective literacy practices and formulates conclusions on the value of enhancing strategies that promote listening and speaking in literacy practices.
CYBER SECURITY AWARENESS AMONGUNIVERSITY STUDENTS: A CASE STUDY

This paper reports the preliminary outcomes of a quantitative survey intended to identifystudents' awareness and enthusiasm to learn cybersecurity in Nigerian Universities. The objective of the surveywas to see how students in this developing country are mindful of cyber-attacks and how they can mitigate theattacks and to find out if the cybersecurity awareness program is among the University program. Thepreliminary results indicated that the students claimed to have basic cybersecurity knowledge, but are not wellinformed of how to protect their data. It also seems that most Universities do not have an active cybersecurityawareness program to improve students' knowledge on how to protect themselves from any threats. Thesurveyed students also show interest in learning more about cybersecurity.
A Survey for Traditional, Cascaded Regression, and Deep Learning-Based Face Alignment

The task of face alignment is to automatically locate key facial feature points, such as eyes, nose tips and mouth corners. There are many methods to solve the face alignment problems. These methods are classified into three categories: traditional algorithms, cascade based on regression algorithm and deep learning-based algorithm. There are still some problems existing that processing of large pose and small pose, processing of different angles and facial occlusion. The experiment results of three categories of algorithms are summarized in this paper.
LibGuides: Policies: MERLIN & MOBIUS

General Policies of the University Libraries. Policies followed for MERLIN and MOBIUS loans
Patients with genetic disorders as risk group for COVID-19

The coronavirus disease (COVID-19) pandemic has seriously affected the global population and has raised concerns about the effect of this new disease on individuals with genetic disorders, many of which have a systemic effect, including impairment of the respiratory system. A lack of published literature about the consequences of SARS-CoV-2 infection in genetic disorders is observed, in this sense, the present review analyses the current knowledge about COVID-19 and its impacts on patients with genetic disorders, also genetic variants as factors of susceptibility and possible risks and preventive measures to those patients, highlighting the role of the restriction to social contact in prevention.
The Correlation between Students’ Self-Confidence and Speaking Performance

The research aims to examine the correlation between students’ self-confidence and speaking performance in SMAN EX Palopo. The researcher implemented quantitative as the research design because the data in this research was correlation design. The sample of this research consist of students MIA 1, MIA 2, MIA 3. The researcher took five samples from each class. The researcher used the students score from spoken test to categorize as samples of this research. To collect the data, the researcher employed two kinds instrument, such as: Speaking Test and questioners. The result of correlation analysis shows that there is no correlation between students’ self-confidence and speaking performance in SMAN EX Palopo. It proofed from p-value (0.088) is higher than α (0.05). Therefore H0 is accepted and H1 is rejected.
LibGuides: LMU Library Staff Picks: Black Lives Matter

We know that our Lions are always on the hunt for great resources, so we have created a list of e-books and streaming films to keep you informed.
A unitary operator construction solution based on Pauli group for maximal dense coding with a class of symmetric states

Quantum dense coding plays an important role in quantum cryptography communication, and how to select a set of appropriate unitary operators to encode message is the primary work in the design of quantum communication protocols. Shukla et al. proposed a preliminary method for unitary operator construction based on Pauli group under multiplication, which is used for dense coding in quantum dialogue. However, this method lacks feasible steps or conditions, and cannot construct all the possible unitary operator sets. In this study, a feasible solution of constructing unitary operator sets for quantum maximal dense coding is proposed, which aims to use minimum qubits to maximally encode a class of t-qubit symmetric states. These states have an even number of superposition items, and there is at least one set of t/2 qubits whose superposition items are orthogonal to each other. Firstly, we propose the procedure and the corresponding algorithm for constructing 2^t-order multiplicative modified generalized Pauli subgroups (multiplicative MGP subgroups). Then, two conditions for t-qubit symmetric states are given to select appropriate unitary operator sets from the above subgroups. Finally, we take 3-qubit GHZ, 4-qubit W, 4-qubit cluster and 5-qubit cluster states as examples, and demonstrate how to find all unitary operator sets for maximal dense coding through our construction solution, which shows that our solution is feasible and convenient.
Wish #HigherEd would put the tech and ...

Wish #HigherEd would put the tech and jargon aside and just focus on good teaching. Everyone hated your lectures .errm discussions f2f. They are even
Digital Health Electronic Market Place DHEMP: A Blockchain Driven Digital Health E-Market Place for Medical Data Trading

Digital Health Electronic Market Place DHEMP: A Blockchain Driven Digital Health E-Market Place for Medical Data Trading
Enhanced Digital Image Encryption Using Sine Transformed Complex Chaotic Sequence

In order to increase the chaotic behaviour of the equation and to get better results than existing encryption methods, we have found a new chaotic equation, namely STLS. The chaotic map generated from STLS (as shown in Fig. 1) manifests convoluted behaviour in the entire range of parameters, and their output states scattered randomly and completely over the entire 2-D plane, which points out that they have an enhanced hyper-chaotic behaviour and shows highly random behaviour. For increasing the key space, our proposed encryption scheme uses effective scrambling and diffusion. Also, simulation results such as average entropy of encrypted image (7.9993) and NBCR (0.50005) show that our proposed algorithm is reliable and provides a high level of security.
Libraries: Creative Commons and Public Domain: Attribution or Citation?

This guide explains how to find free images, videos, and sound files for your class projects and how to give proper attribution to the creator.
LibGuides: Support for Online Teaching/Learning: Professional Development Opportunities

As you plan for a variety of scenarios in response to the global COVID-19 health crisis, CKLS wanted to share resources you can share with educators, students and parents to support distance learning.
LibGuides: Teaching & Learning: Engagements

Overview of services provided by the Teaching & Learning department with recommended resources and more.
Dynamic plasmonic color generation based on phase transition of vanadium dioxide (Conference Presentation)

Plasmonic color filtering and color printing have attracted considerable attention in recent years due to their supreme performance in display and imaging technologies. Although various color-related devices are designed, so far very few studies have touched the topic of dynamic color generation. In this article, dynamic color generation is demonstrated by integrating plasmonic nanostructures with vanadium dioxide based on its tunable optical properties through insulator–metal transition. Periodic arrays of silver nanodisks on a vanadium dioxide film are fabricated to realize different colors, relying on the excitation of localized and propagating surface plasmons, and Wood’s anomaly. By tuning spatial periodicity of the arrays and diameter of the silver nanodisks, various colors can be achieved across the entire visible spectrum. Further, using insulator–metal transition of vanadium dioxide, the colors can be actively tuned by varying temperature. The approach of dynamic color generation based on the phase transition of vanadium dioxide can easily realize diverse color patterns, which makes it beneficial for display and imaging technology.
Guides: Ask A Librarian: Have a question?

Meet your librarians and send us your questions! We're here to help you through your research projects.
Enhanced Support Vector Machine based on Metaheuristic Search for Multiclass Problems

Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities.Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications.However, the SVM has many parameters, which have significant influences on the performance of SVM in terms of its prediction accuracy that is very important measure specifically with critical applications such that used in Medical applications.This paper proposed an enhanced SVM, which employs a meta-heuristic method, called scatter search to determine the optimal or near optimal values of the SVM parameters and its kernel parameters in multi-classification problem.Scatter search has the potential to determine the appropriate values of parameters for machine learning algorithms due its flexibility and sophistication.Therefore, the proposed method integrates the advantages of scatter search method with SVM to specify the appropriate setting of SVM parameters.The experimental results on lung cancer datasets and other standard datasets prove that the scatter search is practical method for tuning SVM parameters and enhance its performance, where the achieved results are better and comparable to other related methods.
Lifted codes and lattices from codes over finite chain rings

In this paper we give the generalization of lifted codes over any finite chain ring. This has been done by using the construction of finite chain rings from p-adic fields. Further we propose a lattice construction from linear codes over finite chain rings using lifted codes.
The Effect of Utilizing Media Stand Power Steering Type Recirculating Ball on Interests and Learning Results on the Eye College System of Muhammadiyah Purworejo University

Abstract. This study aims to reveal: find out the appropriateness of media for recirculating ball type power steering system props at the University of Muhammadiyah Purworejo, find out the increase in learning outcomes and find out the increase in student learning interest in the steering system courses at the University of Muhammadiyah Purworejo.This type of research uses the Reseach and Development (R & D). Test data analysis using the normality test, homogeneity test, t-test test, small group trials, product use trials showed that the material in the form of stand learning media was appropriate to use. T-test results indicate that there is an increase in learning outcomes and an interest in learning. Keywords : Media, Interest in Learning, Learning Outcomes
Messages in games and player backgroundA player study about modeling and conveying emotional states through game rules and mechanics : A player study about modeling and conveying emotional states through game rules and mechanics

Games can be used to convey meaning and communicate messages. While there is ample research on games' expressive capacities, how players' backgrounds impact game interpretation has thus far been un ...
Discussion on deformation monitoring method of asphalt concrete core wall of high earth-rock dam

Abstract The deformation of asphalt concrete core wall of earth rock dam is an important monitoring item of safety management in the construction and operation period of the project. This paper summarizes the conventional monitoring methods and principles of the deformation of asphalt concrete core wall, analyzes the application scope and existing problems of the conventional monitoring methods, and introduces a new method and principle of the deformation monitoring of asphalt concrete core wall of high earth rock dam, which effectively solves the problems The problems of conventional monitoring methods are solved, and the three-dimensional deformation monitoring of asphalt concrete core wall is realized.