Reviewerly/exHarmony huggingface dataset:
A Bunch of Broken Schemes: A Simple yet Powerful Linear Approach to Analyzing Security of Attribute-Based Encryption.

Verifying security of advanced cryptographic primitives such as attribute-based encryption (ABE) is often difficult. In this work, we show how to break eleven schemes: two single-authority and nine multi-authority (MA) ABE schemes. Notably, we break DAC-MACS, a highly-cited multi-authority scheme, published at TIFS. This suggests that, indeed, verifying security of complex schemes is complicated, and may require simpler tools. The multi-authority attacks also illustrate that mistakes are made in transforming single-authority schemes into multi-authority ones. To simplify verifying security, we systematize our methods to a linear approach to analyzing generic security of ABE. Our approach is not only useful in analyzing existing schemes, but can also be applied during the design and reviewing of new schemes. As such, it can prevent the employment of insecure (MA-)ABE schemes in the future.
Reliability Maximization in Uncertain Graphs (Extended Abstract)

Network reliability measures the probability that a target node is reachable from a source node in an uncertain graph, i.e., a graph where every edge is associated with a probability of existence. In this paper, we investigate the novel and fundamental problem of adding a small number of edges in the uncertain network for maximizing the reliability between a given pair of nodes. We study the NP-hardness and the approximation hardness of our problem, and design effective, scalable solutions. Furthermore, we consider extended versions of our problem (e.g., multiple source and target nodes can be provided as input) to support and demonstrate a wider family of queries and applications, including sensor network reliability maximization and social influence maximization.
A Modified Type-2 Neuro-fuzzy SVM based inverter fed IM drive

In indirect vector control, the conventional speed and current controllers operate satisfactorily when the operating point is constant. But the operating point is always dynamic; the reference voltages obtained in a closed-loop system feeding to the inverter contains more harmonics. Due to this, the pulses which are going to produce are uneven and in turn, understudy creates the inverter output voltages produced with more harmonics. In order to produce a better output voltage from the inverter, this paper presents the neuro-fuzzy type-2 (NFT2) space vector modulation technique. Performance comparison of the inverter is done with conventional space vector modulation (SVM) and neuro-fuzzy type-1 (NFT1) system using MATLAB simulation and experimental validation. The performance parameters of the induction motor based on current, torque, and speed with neuro-fuzzy type-2 space vector modulation is compared with conventional and type-1 neuro-fuzzy SVM. The % THD of inverter output voltages are also compared. The experimental validation of a DSpace-1104 is used to analyse the performance of the induction motor which is obtained by the simulation. The experimental validations are carried out considering 2HP induction motor in the lab.
Learned transform compression with optimized entropy encoding

We consider the problem of learned transform compression where we learn both, the transform as well as the probability distribution over the discrete codes. We utilize a soft relaxation of the quantization operation to allow for back-propagation of gradients and employ vector (rather than scalar) quantization of the latent codes. Furthermore, we apply similar relaxation in the code probability assignments enabling direct optimization of the code entropy. To the best of our knowledge, this approach is completely novel. We conduct a set of proof-of concept experiments confirming the potency of our approaches.
Application of laser ranging technology in tunnel visualization

Laser ranging technology is a widely used non-contact active measurement method, which could quickly and accurately obtain distance data. The research propose of this paper is to use python to process the data of Yanqing wall-mounted highway which scanned by laser ranging technology, and visualizing point cloud data. The results demonstrated that the system can quickly and accurately describe the shape of the tunnel in a non-contact manner, thereby reducing the limitations of traditional geological survey methods, which could satisfy the data source and the basis for judging the shape of the tunnel. Further works such as filtering and surface reconstruction could be finished according to the needs of the project ,which meet more project needs.
Adversarial Training for Deep Learning-based Intrusion Detection Systems

Nowadays, Deep Neural Networks (DNNs) report state-of-the-art results in many machine learning areas, including intrusion detection. Nevertheless, recent studies in computer vision have shown that DNNs can be vulnerable to adversarial attacks that are capable of deceiving them into misclassification by injecting specially crafted data. In security-critical areas, such attacks can cause serious damage; therefore, in this paper, we examine the effect of adversarial attacks on deep learning-based intrusion detection. In addition, we investigate the effectiveness of adversarial training as a defense against such attacks. Experimental results show that with sufficient distortion, adversarial examples are able to mislead the detector and that the use of adversarial training can improve the robustness of intrusion detection.
Symposium: Dynamic Decisions, Conflict Resolution, and Real-Time Diagnosis in Complex Domains

Studies of cognition beyond laboratory walls have flourished in recent years. These developments have been enabled by both methodological and theoretical advances that have facilitated investigations of “cognition in the wild”. These endeavors promise to profoundly impact the discipline of cognitive science. This symposium presents research pertaining to the development of decision-making expertise in complex and diverse environments.
A beginner’s guide to the Fourth Industrial Revolution in Africa: By Abel Matheba and Debates

What is a revolution?A revolution is change that happens over a length of time. This type of change is driven by human beings. It starts as an idea inthe minds of a few, and then spreads out into the minds of more people so that it gains momentum to force a change in the world. A political revolution is often forced through protests or policies, where the majority of the affected people drive thischange in their desired direction. An industrial revolution is a change in economic power, where the main driver of the economy is changed from a certain technological sector to another.
Online Game-Based Approach in Teaching English: Cases of Teaching during Pandemic Covid-19 at Universitas Darwan Ali Sampit

Teaching during pandemic now changes the concept of teaching learning from the conventional way to virtual based teaching. Teachers might use online media in conducting the lesson, for instance zoom, google meet, online game, and so forth. The aim of the study was to know the students’ ability in English by using this online game called Quizizz (web-based, Quizizz.com ) as a well-featured platform yet interactive for freshmen in English I class at Universitas Darwan Ali Sampit in academic year 2020/2021. The design of the study was experimental research design in quantitative method. The population of this research was the freshmen of Business Management class taking English I subject. Two classes were taken as the sample, they were: FB 1 A as the control class and FB 1 B as the experimental class. To collect the main data, pre-test and post-test were used. The data from those tests were analyzed by using SPSS for Windows version 16.0. To find out the validity and the reliability of the instrument, the data from the English I quiz result were collected and analyzed. The result of research showed that the t-test gave t-value of 2.999 which was higher than t table 2.009, with sig. (2-tiled) showing that .004 was lower than .05. It could be concluded that H 0 was rejected and H 1 was accepted; which means teaching English using online game Quizizz could improve the students’ ability in English.
Factors and challenges that influence higher education students' acceptance of Elearning system after Coronavirus pandemic

As the coronavirus pandemic continues to spread, and the world is now in a state of emergency, universities around the world are reacting with different and alternative ways of learning such as e-learning systems applications to slow the spread of this disease. However, the successful implementation of e-learning in higher education will be based on users' acceptance of this technology and on understanding the main challenges that face the current e-learning systems. Thus, the purpose of this paper is to study the factors that influence university students' intentions to accept e-learning after coronavirus pandemic where the e-learning became an obligatory system and to investigate the critical challenges of it. Based on the unified theory of acceptance and use of technology (UTAUT) this study proposes a model to identify the factors that influence the acceptance of web-based learning platform, Moodle in Faculty of Economics and Political Sciences, after coronavirus pandemic. Partial Least Square-Structural Equation Modelling (PLS-SEM) was used to analyze the data collected from 346 students' participants. The results indicated that behavioral intention and facilitating conditions have direct impacts on use behavior while performance expectancy, effort expectancy, social influence, price value, facilitating conditions and motivation to use were all significant factors that affect behavioral intention to use e-learning. In addition, the results indicated that there are many main challenges that obstruct the usage of e-learning system not related only to the technological challenges, but also culture challenges which must be taken under consideration. Overall, the respondents expressed unfavorable opinion concerning e-learning acceptance during the lockdown situation and its impacts on students' academic performance, they accept using the technology but as a complementary part in the education process, not as the alternative of the face to face educational process. It is believed that the findings will be useful for understanding challenges better and to help the universities policy makers, designers and developers to make superior decisions based on them as soon as possible. © 2021 Little Lion Scientific. All rights reserved.
Education and the Pursuit of Wisdom: The Aims of Education Revisited

Educational TheoryVolume 70, Issue 6 p. 797-806 BOOK REVIEW Education and the Pursuit of Wisdom: The Aims of Education Revisited Bruce Novak, Bruce Novak The Foundation for Ethics and MeaningSearch for more papers by this author Bruce Novak, Bruce Novak The Foundation for Ethics and MeaningSearch for more papers by this author First published: 21 June 2021 https://doi.org/10.1111/edth.12454Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume70, Issue6Special Issue: Symposium: Democracy in Crisis and Education: Educating for Citizenship in the Age of PopulismDecember 2020Pages 797-806 RelatedInformation
The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks

We study the effects of mild over-parameterization on the optimization landscape of a simple ReLU neural network of the form $\mathbf{x}\mapsto\sum_{i=1}^k\max\{0,\mathbf{w}_i^{\top}\mathbf{x}\}$, in a well-studied teacher-student setting where the target values are generated by the same architecture, and when directly optimizing over the population squared loss with respect to Gaussian inputs. We prove that while the objective is strongly convex around the global minima when the teacher and student networks possess the same number of neurons, it is not even \emph{locally convex} after any amount of over-parameterization. Moreover, related desirable properties (e.g., one-point strong convexity and the Polyak-{\L}ojasiewicz condition) also do not hold even locally. On the other hand, we establish that the objective remains one-point strongly convex in \emph{most} directions (suitably defined), and show an optimization guarantee under this property. For the non-global minima, we prove that adding even just a single neuron will turn a non-global minimum into a saddle point. This holds under some technical conditions which we validate empirically. These results provide a possible explanation for why recovering a global minimum becomes significantly easier when we over-parameterize, even if the amount of over-parameterization is very moderate.
Layanan Kajian Pra Riset Berbasis Literature Review dan Bibliometrik Di Pusat Data dan Dokumentasi Ilmiah LIPI Tupan

(Objectives) A literature review and biliometric based pre-research service review was conducted at the Center for Scientific Data and Documentation of the Indonesian Institute of Sciences . (Method) Reviews of literature review and bibliometric services were carried out by tracing methods from various sources of information both from within and outside the country, namely for domestic information sources used were ISJD.pddi.lipi.go.id, https://garuda.ristekbrin.go.id/, and https://moraref.kemenag.go.id/. Meanwhile, foreign databases consist of Scopus and Web of Science. The search results of manuscripts that are in accordance with bibliometric-based pre-research services and literature reviews are analyzed descriptively as a result and discussion . (Findings) The results of the study show that literature review services can help analyze certain topics as a consideration in conducting research. Literature reviews can also encourage objective thinking, and a systematic approach to the research to be carried out. Meanwhile, the bibliometric service helps researchers evaluate research results by looking at the bibliometric map. With the bibliometric visualization map, it can be seen that research topics are rarely conducted which are the basis for researchers to conduct further research .
Improved Fuzzy Based Non-Local Mean Filter to Denoise Rician Noise

Nowadays MRI has become an important tool to diagnose medical conditions but there is a growing need for a denoise image produced. Rician noise is one of the major challenges in MRI.  So the nonlocal means (NLM) filter has gained popularity to denoise medical images as it gives excellent results. In the present work, an Improved Fuzzy-based Non-Local Mean Filter is proposed for denoise Rician noise. In the proposed method the first step is to find the non-local similar pixel in the image using fuzzy function. Then these similar pixels are used to generate noise-free pixels. The above approach is tested with real data and the results are compared with existing Fuzzy techniques by using root mean square error, structural similarity index measure, and peak signal-noise ratio (PSNR) methods. This technique gives better result than the existing Fuzzy Non-Local Mean technique with both high and low-density Rician noise in the image
Team Diversity and Project Performance: Role of Trust and Absorptive Capacity in it Industry

Team diversity has emerged as an essential concept in the field of project management. In a diverse climate, team members have different thinking capacities, knowledge, perspectives, and strategies that help to create new ideas. But sometimes, this diversity causes conflicts among the team members, ultimately creating tension, resentment, and loathing behavior at the workplace. Therefore, the current study attempts to understand the relationship between team diversity (knowledge, value) and project performance through trust and absorptive capacity. Data were collected from team members involved in IT (Information Technology) projects. Findings reveal that team diversity enhances project performance through trust and absorptive capacity. But the relationship is partially mediated in the case of value diversity and fully mediated with knowledge diversity. This study contributes to the IT sector, where dynamic team members utilize their innovative capabilities and problem-solving skills for achieving project success
Towards securing cloud data in the multi-cloud scenario

Cloud computing has emerged to be the accepted computing model which provides services on-demand. The most used service layer is infrastructure as a Service (IaaS) to outsource data to the cloud. With this service, organizations and individuals can avail of cloud services in pay as you use fashion instead of investing money for such infrastructure. Cloud provides many such benefits to its users. However, as the cloud servers are remote and assumed to be untrusted, users are worried about data security. Initially, a single cloud was used to store data. With the advancements in technologies and for reliability reasons, the concept of multi-cloud has emerged. The security and reliability issues with a single cloud can be overcome with multi-cloud systems. The rationale behind this is that a single cloud might have malicious insiders. When two or more clouds collaborate and provide services to end-users, it is expected to have more reliability and possible reduction in malicious insiders. This paper focuses on studying the potential security of data that is stored in multi-cloud. We built an algorithm and prototype application that demonstrates the concept of securing data in a multi-cloud environment. The empirical results revealed that the proposed system could ensure the data outsourced to cloud computing where a multi-cloud scenario prevails.
Scania A.H Boekema V8 Sound V11.0 [1.36.X]

My “A.H. Boekema” variant of the V8 is here. I’ve remade it almost from scratch. It works for : The SCS R, Streamline, RJL (R and 4
Supporting Effort for IPD of Engineer-in-Training

I served as an executive member of Professional Development Committee, IPEJ from 2013 to 2017, and worked on the compilation of the “IPD GUIDE BOOK for EIT (Engineers-in-Training) (3rd edition)” which is a tool for initial professional development. The purpose of the 3rd edition are as follows.1) Reflecting the study results of Professional Engineer System Study Special Committee, MEXT (Ministry of Education, Culture, Sports, Science and Technology) Japan.2) Reflecting the contents of PC (professional competency) profiles of IEA (International Engineering Alliance) to adapt international engineer’s qualification of IPEA (International Professional Engineer Agreement) and APEC (Asia Pacific Economic Cooperation). 3) To describe plainly what is PC and how to acquire it. We classified Engineering Professional Competences into 16 items.I will explain the outline of “IPD GUIDEBOOK for EIT (3rd edition)” and public relations.
Connectionism: What’s structure got to do with it?

Most discussions of connectionism in cognitive science have focused on whether or not simple unstructured networks such as multilayer perceptrons suffice for cognition. Other types of connectionist models have received relatively less attention. The purpose of this symposium is to increase awareness of these other kinds of models, situating them in a context that allows a greater understanding of what kinds of models are good for what kinds of tasks. Our assumption is that in any given domain it is possible build some adequate model, but that the interesting question is how. The emphasis, then, will be on the strengths and weaknesses of competing connectionist architectures and how they can be usefully applied to models of cognition.
SCAN: A Spatial Context Attentive Network for Joint Multi-Agent Intent Prediction.

Safe navigation of autonomous agents in human centric environments requires the ability to understand and predict motion of neighboring pedestrians. However, predicting pedestrian intent is a complex problem. Pedestrian motion is governed by complex social navigation norms, is dependent on neighbors' trajectories, and is multimodal in nature. In this work, we propose SCAN, a Spatial Context Attentive Network that can jointly predict socially-acceptable multiple future trajectories for all pedestrians in a scene. SCAN encodes the influence of spatially close neighbors using a novel spatial attention mechanism in a manner that relies on fewer assumptions, is parameter efficient, and is more interpretable compared to state-of-the-art spatial attention approaches. Through experiments on several datasets we demonstrate that our approach can also quantitatively outperform state of the art trajectory prediction methods in terms of accuracy of predicted intent.
Online Book Store website

This paper represents a e-commerce website which provides facility to buy the books. This online bookstore provides Two Views as admin view, customer view and one back-end database to store the information. In Admin we can add products its category, subcategory as well as the conformation and cancellation of order of the product is given from the admin module. from website we can buy the various books or bunch of books that admin added through its admin module , we can search the books that we want but for all this we have to create our account through Sign-up page. For successful and safe delivery we have to fill right information in order page.
The overlap of aftershock coda waves and forecasting the first hour aftershocks

&amp;lt;p&amp;gt;We show that short term post-seismic incompleteness can be interpreted in terms of the overlap of aftershock coda waves. We use this information to develop a novel procedure which gives accurate occurrence probabilities of post-seismic strong ground shaking within 30 minutes after the mainshock. This novel approach uses, as only information, the ground velocity recorded at a single station without requiring that signals are transferred and elaborated by operational units. We will also discuss how this information can be implemented in the Epidemic-Type Aftershock Sequence model in order to reproduce statistical features in time and magnitude of recorded aftershocks.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Main references &amp;lt;/strong&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;de Arcangelis L., Godano C. &amp;amp; Lippiello E. (2018) &amp;lt;em&amp;gt;The Overlap of Aftershock Coda Waves and Short-Term Postseismic Forecasting. &amp;lt;/em&amp;gt;&amp;lt;strong&amp;gt;Journal of Geophysical Research: Solid Earth, &amp;lt;/strong&amp;gt;123: 5661-5674,doi:10.1029/2018JB015518&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Lippiello E., Petrillo G. , Godano G. , Tramelli A., Papadimitriou E. &amp;amp;, Karakostas V. (2019)&amp;lt;em&amp;gt; Forecasting of the first hour aftershocks by means of the perceived magnitude. &amp;lt;/em&amp;gt;&amp;lt;strong&amp;gt;Nature Communications&amp;lt;/strong&amp;gt; , 10, 2953, doi:10.1038/s41467-019-10763-3&amp;lt;/p&amp;gt;