Reviewerly/exHarmony huggingface dataset:
Sweden’s structure and systems

This chapter reviews Sweden’s organisational structures and management systems for its development co-operation, and examines the extent to which these are fit for purpose and have appropriate capabilities to deliver on Sweden’s development objectives.Sweden has strengthened co-ordination between the Ministry for Foreign Affairs and its main implementing agency, Sida, enabling a more coherent and cohesive programme. Steps have also been taken to better align the Ministry and its other implementing agencies, but further work remains to be done, particularly with respect to strengthening the alignment of Swedfund’s investments to its development policy, including creating closer links between Swedfund and Sida’s activities.Sida is working hard to ensure a better balance between efficiency, quality control and risk management within its programming processes. A comprehensive toolbox for tackling corruption is in place and Sweden has given priority to addressing this issue. Sida is engaging in innovative partnerships and financial instruments.Sweden has enhanced its human resource planning and improved its staff capacity since the last review, but it needs to adopt a more long-term plan to ensure adequate staff capacity in light of a growing ODA budget and increasingly complex programme. Its decentralised workforce remains a major asset.
Heuristic Computational Matrix Method for Marathi Grammar Checker

Spelling, morphology, syntax and semantics are the important areas of Natural Language (NL) sentence analysis. Syntax checking of a sentence is broadly referred as a ‘grammar checking’, however it also involves morphological analysis hence technically it is a multidimensional problem. Syntax of a natural language defines permissible sentence structures and constraints on constituents such as their order and unification constraints. It is a purely theoretical aspect and considered as computationally trivial rule enforcement problem. Rule formulation needs expert labour work and is costly and time consuming affair. Modern data driven language engineering approach advocates use of minimal knowledge base (linguistic information) and relies on knowledge extraction from tagged data. It is difficult to find such tagged data for non-English natural languages like Marathi (Indian Language). Considering these facts for grammar checking problem, we have come up with intuitional heuristic method for Marathi grammar checking which uses basic syntactic cues and minimal lexical information. We have modeled this heuristic method scientifically using basic matrix comparison operation. Our approach relies on syntactic cues like word ending, verb ending. We have tested our method on handcrafted Marathi sentences catering different Marathi sentence structures (one hundred and fifty three). The performance is measured using precision and recall metrics. The system has yielded 83% precision and 93% recall on sample data. This approach can be exploited for well structured text documents typically in the closed domains like legal, official, educational etc.
Classification of Action Based Video using Heterogeneous Feature Extraction and SVM

Action recognition (AR) plays a fundamental role in computer vision and video analysis. We are witnessing an astronomical increase of video data on the web and it is difficult to recognize the action in video due to different view point of camera. For AR in video sequence, it depends upon appearance in frame and optical flow in frames of video. In video spatial and temporal components of video frames features play integral role for better classification of action in videos. In the proposed system, RGB frames and optical flow frames are used for AR with the help of Convolutional Neural Network (CNN) pre-trained model Alex-Net extract features from fc7 layer. Support vector machine (SVM) classifier is used for the classification of AR in videos. For classification purpose, HMDB51 dataset have been used which includes 51 Classes of human action. The dataset is divided into 51 action categories. Using SVM classifier, extracted features are used for classification and achieved best result 95.6% accuracy as compared to other techniques of the state-of- art.
Personality, (NEURO) Trust and LMX in Information Apportionment

Neuromanagement has evolved into a full-fledged enterprise of consilience; an attempt to not only test and bridge, but truly unify natural science and social science explanations of human behaviour (Wilson, 1998; Glimcher and Rustichini, 2004; Rangel, Camerer and Montague, 2008). This paper presents an empirical approach to neuro - based information sharing dynamics via personality, (neuro) trust and LMX. The Big Five Inventory matrix has been adopted to test the phenomenon. A neuro – based pathway has been projected. A symbiotic relational model has been arrived at.
Foundations

This chapter introduces attitude reports in possible worlds semantics, with attention to the motivation of such an approach and its main challenges, and the major revisions and alternatives that such challenges have prompted. We begin with a brief introduction to possible worlds semantics. We then sketch Jaakko Hintikka’s highly influential possible worlds-based approach to attitude reports and outline the key predictions that it makes. We discuss the problem of logical omniscience that Hintikka’s approach faces, and outline two competing approaches for solving it. We then turn to the more basic problem of logical equivalence that any approach to attitude reports in possible worlds semantics faces; we discuss several solution strategies that go under the name ‘hyperintensionality’ in that they proffer ways of modeling propositions that achieve a finer grain than do possible worlds. A recurring question in this discussion is: Which of our intuitions about inference patterns in attitude reports reflect semantic reasoning, and which reflect pragmatic or extra-linguistic reasoning? Finally, we explore two competing hypotheses regarding the compositional semantics of attitude reports.
Cabot delivers ‘solid’ results in fiscal 2019 third quarter despite challenging conditions

For the third quarter of its 2019 fiscal year, Cabot Corp posted net income attributable to the company of US$32 million on net sales of $845 million. The sales total was only marginally lower than the $854 million achieved in the comparable period of fiscal 2018 but net income was substantially reduced from $88 million a year earlier.
Optimizing Deep Network for Image Classification with Hyper Parameter Tuning

The deep network model comprises of several processing layers and deep learning techniques help us in representing data with diverse levels of abstraction. Based on the practical importance and the efficiency of machine learning, optimization of deep models are carried out relating to the objective functions and its parameters for a particular problem. The present work focuses on an empirical analysis of the performance of stochastic optimization methods with regard to hyperparameters for the deep Convolution Neural Network (CNN) and to understand the rate of convergence of the optimization methods in high dimensional parameter spaces. Experimentation has been carried out in deep CNN model with different optimization methods viz. SGD, AdaGard, AdaDelta and Adam. The empirical results are evaluated using benchmark CIFAR10 and CIFAR100 datasets. The optimal values of the hyperparameters obtained demonstrates that the optimizer Adam shows the best results compared to other methods viz. SGD, AdaGard, and AdaDelta over the considered datasets. Further, it is noted that classification accuracy can be increased by choosing the best optimization techniques with hyperparameter tuning to get the optimal configuration of the deep CNN model.
Entropy Measurement to Extract the Signification of Abnormal Activity from Camera’s Frames and its Application for Fall Detection

Most of the indoor accidents are related with fall down. Many medical studies are point out that key factor for keeping patient’s life is fast response of monitoring system. In modern life, peoples are isolated with neighbor, especially in living quarters. Therefore many solutions are developed for falling down monitoring that base on wearable sensors. These methods require of an expensive sensors system with electric power supplier and telecommunication devices. In context of patients with disease and weak status, patients are trend to remove sensor system. This issue requires to find out another approach so that sensors system will not be needed. We study the fall detection by monitoring camera. For increase the accuracy, we proposed a simple and effective method to extract features of abnormal activities. By tracking the magnitude of entropy and its distribution, our fall detection model has a capability of differentiating falls from other activities
Pattern Recognition Referees 2017--2018

Script identification plays a significant role in analysing documents and videos. In this paper, we focus on the problem of script identification in scene text images and video scripts. Because of low image quality, complex background and similar layout of characters shared by some scripts like Greek, Latin, etc., text recognition in those cases become challenging. In this paper, we propose a novel method that involves extraction of local and global features using CNN-LSTM framework and weighting them dynamically for script identification. First, we convert the images into patches and feed them into a CNN-LSTM framework. Attention-based patch weights are calculated applying softmax layer after LSTM. Next, we do patch-wise multiplication of these weights with corresponding CNN to yield local features. Global features are also extracted from last cell state of LSTM. We employ a fusion technique which dynamically weights the local and global features for an individual patch. Experiments have been done in four public script identification datasets: SIW-13, CVSI2015, ICDAR-17 and MLe2e. The proposed framework achieves superior results in comparison to conventional methods.
Data Taking

We define “physics run” as data taking with the purpose of collecting a $$K_L \!\rightarrow \! \pi ^0 \nu \overline{\nu }$$ sample. We performed several kinds of data taking other than the physics run to calibrate detectors and to understand backgrounds.
Categories and Functions of Crypto-Tokens

We discuss emerging research on digital tokens and cryptocurrencies. Specifically, we (i) provide a comprehensive categorization of crypto-tokens as observed or designed in practice, (ii) discuss major issues concerning the economics of using tokens including platform finance, user adoption, stablecoins, crowdsourcing, and agency issues, with legal and regulatory implications, and finally, (iii ) suggest future directions of digital currency applications and tokenomics research.
iSAQB Curriculum

No AccessEffektive SoftwarearchitekturenAug 2020iSAQB CurriculumGernot StarkeGernot StarkeSearch for more papers by this authorhttps://doi.org/10.3139/9783446465893.014SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2020Pages: 415-427Print ISBN: 978-3-446-46376-9eISBN: 978-3-446-46589-3 Copyright & Permissions© 2020 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Spring Security Architecture and Design

In the previous chapter, you developed an initial application secured with Spring Security. You got an overview of the way this application worked and looked in detail at some of the Spring Security components that are put into action in common Spring Security–secured applications. In this chapter, we are going to extend those explanations and delve deeply into the framework.
Low-Cost Image and Video Processing Using High-Performance Middleware in Single-board Computers with Open Internet Standards

Image processing is becoming ubiquitous in many activities. This kind of systems use industry-standard libraries, such as OpenCV, and GPGPU techniques such as CUDA and OpenCL. Nowadays, these are being ported to many computing platforms, offering significant processing power even in devices with limited resources. However, the only model that is truly ubiquitous, is the web itself. Modern browsers feature quite complex internals and offer sophisticated development and profiling tools, in order to offer the best user experience. Introduction of HTML5 allows Realtime video and image manipulation, in browser space, without any plugin. In addition, Wasm (web assembly) Javascript execution engine provides fastest possible performance by means of highly customized compiler and runtime, in almost any browser, including embedded ones. This paper presents an image processing system, architected as a modular web application, using only Raspberry PIs with a compact but fast middleware server, that performs all image operations in browser space by means of web assemblies. All components, including database support, can run in a single board, providing image and video processing speeds that match, or surpass, their native compiled C counterparts on the same platform. This solution has a very low cost, that fits with emerging markets, making it ideal for LATAM scenarios.
Pedagogtyń kásіbı utqyrlyǵynyń qurylymy [Structure of the Professional Mobility of the Teacher]

In the article, the author aims to bring to readers a generalized structure of professional mobility of future teachers for the successful implementation of tasks defined in the course of professional training of professional training specialists from the author's point of view. During the implementation of this goal, the main components of professional mobility of future teachers of vocational training are defined and the main concepts are formulated. In the life of the person can be mobile, flexible to change and creative self-realization in the framework of the acquired profession. But only if he has certain personal and professional qualities. It is formulated that the structural elements of professional mobility are: the quality of the individual; human activity; the process of transformation of the individual and the environment; types of mobility (vertical and horizontal); characteristics (objective, subjective and characterological). Автор мақалада кәсіптік оқыту мамандарын кәсіби даярлау барысында анықталған міндеттерін табысты жүзеге асыру үшін, болашақ педагогтардың кәсіби ұтқырлығының жалпы құрылымын авторлық көзқарас тұрғысынан оқырмандарға жеткізуді мақсат етеді. Осы мақсатты жүзеге асыру барысында болашақ кәсіптік оқыту педагогтарының кәсіби ұтқырлығының негізгі құрылымын құраушылар анықталып, негізгі ұғымдар айқындалды. Адам өмірінде меңгерген мамандығы шеңберінде икемді түрде жаңғырып, шығармашылық тұрғыдан өзін-өзін жетілдіре алатындай ұтқыр бола алады. Бірақ ол үшін белгілі бір жеке және кәсіби қасиеттерге ие болуы керек. Кәсіби ұтқырлықтың құрылымдық элементтері: жеке тұлға сапасы; адамның іс-әрекеті; адамның өзін және қоршаған ортаны түрлендіру процесі; ұтқырлық түрлері (тік және көлденең); сипаттамалары (объективтік, субъективтік және мінезін зерттеу) екендігі тұжырымдалды.
Towards the design of an assurance framework for increasing security and privacy in connected vehicles

Intelligent transport systems (ITS) play a key role in our daily activities. ITS development over the last decades has been based on the rapid evolution of information and communication technologies (ICT), which include processing capabilities, availability of hardware and communication technologies. However, as the development of ITS services increases so does the users' awareness regarding the degree of trust that they demonstrate on adopting this kind of services. This has brought to light several security and privacy concerns that ITS analysts should consider when designing and implementing various IT related services. This paper identifies how risk analysis can interact with security and privacy requirements' engineering world, in order to provide a holistic approach for reasoning about security and privacy in such complex environments like ITS systems.
Chapter 4 Measuring barriers in adoption of blockchain in supply chain management system

The blockchain technology (BCT) or distributed ledgers is an emergent technology that allows the autonomous and immutable preservation of checked data by offering a revolutionary forum of a modern, decentralized and transparent exchange system for industries and companies. The inherited characteristics of BCT foster trust by clarity and traceability in every transaction involving records, products and financial capital. Through initial concerns, governments and major companies have recently investigated the implementation and improvement of this BCT in different fields of use, including supply chain (SC) networks. Slowly, the community of this sector realizes how profoundly blockchain (BC) could affect their industry. BC’s ability to guarantee accuracy, quality control and authenticity of data, coupled with smart contractual partnerships, represents a major reconsideration of SC and supply chain management (SCM). It provides more and more logistic items with sensors that produce data in the SC, for example, on the shipment status. This data must be processed in an external, open manner. Current practices for the types of obstacles to implementing BCTs are implemented in the fields of interorganizational, intraorganizational, technological and external barriers. Procurement costs, shipping costs, inventory costs and quality costs are the four primary reasons that increased the expenses in the conventional supply chains. In this research, we have identified the barriers against the use or development of sustainable SCM, by taking views of 500 working professionals of various global SC-oriented companies. The study’s outcome by using linear regression reviled economic obstacles, cross barriers, structure barriers and communication threats. Related barriers are BC barriers in general. Similarly, it can limit the use of BCT for SC. To improve these problems and to improve sustainability, the SC should also decrease resource use, reduce greenhouse gas emissions, check that the commodity is renewable in terms of greenhouse gas emissions, increase recycling, improve emissions sharing schemes (ETS) and improve governance using information management mechanism by understanding the barriers.
Design of an autonomic communication system

In modern communication systems, it is necessary to develop new approaches to optimise them. To achieve this objective, new paradigms are necessary. The present work proposes the conception of an autonomic communication system, which is based on a Bayesian network and on an ontology, to take reconfiguration decisions in the system. The ontology provides the knowledge about the performance factors and their relationships in the communication networks, to configure the structure of the Bayesian network. The Bayesian network is the stochastic reasoning mechanism used by the decision-making system. We present several tests on the NS2 simulator, and we observe an improvement in the system performance, for scenarios with high reconfiguration requirements.
Governance

Higher Education AbstractsVolume 55, Issue 4 p. 369-369 GOVERNANCE Governance First published: 22 November 2020 https://doi.org/10.1111/hea.24_12158Read 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 No abstract is available for this article. Volume55, Issue4October 2020Pages 369-369 RelatedInformation
Character Categories

Exploration 17 introduced and discussed characters. This Exploration continues that discussion with character classification (e.g., uppercase or lowercase, digit or letter), which, as you will see, turns out to be more complicated than you might have expected.
(Invited) Extracellular Matrix-Based Neural Interfaces

Neural interfaces to reveal neural activities at high temporal and spatial resolutions become critical for neuroscience research, emerging clinical applications and brain computer interfaces (BCI). However, the chronic performances of conventional neural interfaces degrade over time due to their incapability to address the biological, chemical and mechanical properties of neural tissues. Extracellular matrix (ECM) materials offers several intrinsic properties, such as high mechanical flexibility and biocompatibility, making them uniquely suitable for interfacing with neural tissues. In this talk, I will present our recent work on ECM-based neural interfaces, highlighting the microfabrication of ECM-based neural electrodes, the mechanical, electrochemical and biological characteristics of the ECM-based neural interfaces, and finally discuss several application examples.
Session details: Theme: Information systems: DM - Data mining track

ACM SAC Data Mining has a successful history of accepting quality papers and offering a stimulating platform for the exchange of ideas and disseminating cutting edge research to the community. The 2019 ACM SAC Data Mining Track is the nineteenth such event in the 34 years of ACM SAC tradition, co-chaired by Hasan Jamil and Rosa Meo.
Thrust Areas of Machine Learning and Its Current Scenario

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Features of the System of Formation of Compensatory Competence Among Agricultural Students as a Means of Filling in Professional Terminology

This article researches the main categories of compensatory (or strategic) competence which is defined as complementing the process of direct communication, reading professionally-oriented texts, identifying and eliminating the ability to communicate language and speech, rules for working with them, speaking in a foreign language and social experience. This also analyzes the ways of formatting compensatory competences to the students of agricultural directions by the means of professional terminology. Moreover, it also highlights components of compensatory competence, reproductive learning strategies for students using the innovative technologies.