scholarly journals Research on LRU Hierarchy based on Optimal Granularity Level

2021 ◽  
Vol 1748 ◽  
pp. 022018
Author(s):  
Yang Fei ◽  
Shuo Dong ◽  
Li-Zhong Shi
Keyword(s):  
Granularity Level

scholarly journals The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review

2021 ◽  
Vol 113 (7-8) ◽  
pp. 2395-2412
Author(s):  
Baudouin Dafflon ◽  
Nejib Moalla ◽  
Yacine Ouzrout
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Review Literature ◽  
Comprehensive Understanding ◽  
Physical Systems ◽  
Fine Grained ◽  
Key Technologies ◽  
Granularity Level ◽  
Human Component

AbstractThis work aims to review literature related to the latest cyber-physical systems (CPS) for manufacturing in the revolutionary Industry 4.0 for a comprehensive understanding of the challenges, approaches, and used techniques in this domain. Different published studies on CPS for manufacturing in Industry 4.0 paradigms through 2010 to 2019 were searched and summarized. We, then, analyzed the studies at a different granularity level inspecting the title, abstract, and full text to include in the prospective study list. Out of 626 primarily extracted relevant articles, we scrutinized 78 articles as the prospective studies on CPS for manufacturing in Industry 4.0. First, we analyzed the articles’ context to identify the major components along with their associated fine-grained constituents of Industry 4.0. Then, we reviewed different studies through a number of synthesized matrices to narrate the challenges, approaches, and used techniques as the key-enablers of the CPS for manufacturing in Industry 4.0. Although the key technologies of Industry 4.0 are the CPS, Internet of Things (IoT), and Internet of Services (IoS), the human component (HC), cyber component (CC), physical component (PC), and their HC-CC, CC-PC, and HC-PC interfaces need to be standardized to achieve the success of Industry 4.0.

Method Using Command Abstraction Library for Iterative Testing Security of Web Applications

2018 ◽  
pp. 192-215
Author(s):  
Seiji Munetoh ◽  
Nobukazu Yoshioka
Keyword(s):  
Web Application ◽  
Agile Development ◽  
Application Framework ◽  
Security Testing ◽  
Application Development ◽  
Security Assurance ◽  
Security Issues ◽  
Application Logic ◽  
Granularity Level ◽  
Scripting Language

A framework based on a scripting language is commonly used in Web application development, and high development efficiency is often achieved by applying several Agile development techniques. However, the adaptation of security assurance techniques to support Agile development is still underway, particularly from the developer's perspective. The authors have addressed this problem by developing an iterative security testing method that splits the security test target application into two parts on the basis of the code lifecycle, application logic (“active development code”) and framework (“used code”). For the former, detailed security testing is conducted using static analysis since it contains code that is changed during the iterative development process. For the latter, an abstraction library at the command granularity level is created and maintained. The library identifies the behavior of an application from the security assurance standpoint. This separation reduces the amount of code to be statically inspected and provides a mechanism for sharing security issues among application developers using the same Web application framework. Evaluation demonstrated that this method can detect various types of Web application vulnerabilities.

A Granular Framework for Recognition of Arabic Handwriting

2009 ◽  
Vol 13 (5) ◽  
pp. 512-519
Author(s):  
Mokhtar Beldjehem ◽  
Keyword(s):  
Topological Structure ◽  
Morphological Analysis ◽  
Handwriting Recognition ◽  
Logical Structure ◽  
Reading Process ◽  
Levels Of Abstraction ◽  
Arabic Word ◽  
Granularity Level ◽  
Points Of View ◽  
Effective Use

We propose a novel cognitively motivated unifying framework for Arabic handwriting recognition that takes into account the nature of the human reading process of Arabic handwriting. This Modular Granular Architecture tackles the problem by observing Arabic handwriting from both perceptual and linguistic points of view and hence analyzes the underlying input signal from different granularity levels. It is based on three levels of abstraction: a low granularity level that uses perceptual features called global visual indices, a medium granularity level that is the conventional recognition stage and a high granularity level that consists on morphological analysis dedicated to segmentation/recognition. The original idea is the effective use of Arabic word's morphology in the recognition not only in post-processing. This architecture carries well around the Arabic word's morphology, as typically in Arabic, the Arabic word's morphology is by excellence the logical structure (even semantic) of a given Arabic word, whereas the visual data constitute the physical geometric (topological) structure of a given word. We need to integrate both of them for an effective cooperative recognition of Arabic Handwriting. This framework subsumes the lexicon-driven approaches; in that it can recognize a word that does not exist within the lexicon.

scholarly journals OpenKG Chain: A Blockchain Infrastructure for Open Knowledge Graphs

2021 ◽  
pp. 1-18
Author(s):  
Huajun Chen ◽  
Ning Hu ◽  
Guilin Qi ◽  
Haofen Wang ◽  
Zhen Bi ◽  
...  
Keyword(s):  
Open Data ◽  
Knowledge Bases ◽  
Knowledge Graph ◽  
Cumulative Number ◽  
Trust Network ◽  
Fine Grained ◽  
Knowledge Based ◽  
Granularity Level ◽  
Knowledge Graphs ◽  
Structured Graphs

Abstract The early concept of knowledge graph originates from the idea of the Semantic Web, which aims at using structured graphs to model the knowledge of the world and record the relationships that exist between things. Currently publishing knowledge bases as open data on the Web has gained significant attention. In China, CIPS(Chinese Information Processing Society) launched the OpenKG in 2015 to foster the development of Chinese Open Knowledge Graphs. Unlike existing open knowledge-based programs, OpenKG chain is envisioned as a blockchain-based open knowledge infrastructure. This article introduces the first attempt at the implementation of sharing knowledge graphs on OpenKG chain, a blockchain-based trust network. We have completed the test of the underlying blockchain platform, as well as the on-chain test of OpenKG's dataset and toolset sharing as well as fine-grained knowledge crowdsourcing at the triple level. We have also proposed novel definitions: K-Point and OpenKG Token, which can be considered as a measurement of knowledge value and user value. 1033 knowledge contributors have been involved in two months of testing on the blockchain, and the cumulative number of on-chain recordings triggered by real knowledge consumers has reached 550,000 with an average daily peak value of more than 10,000. For the first time, We have tested and realized on-chain sharing of knowledge at entity/triple granularity level. At present, all operations on the datasets and toolset in OpenKG.CN, as well as the triplets in OpenBase, are recorded on the chain, and corresponding value will also be generated and assigned in a trusted mode. Via this effort, OpenKG chain looks to provide a more credible and traceable knowledge-sharing platform for the knowledge graph community.

scholarly journals Decomposing Semantic Inferences

2014 ◽  
Vol 9 ◽  
Author(s):  
Elena Cabrio ◽  
Bernardo Magnini
Keyword(s):  
Computational Linguistics ◽  
Research Community ◽  
Data Sets ◽  
Decomposition Approach ◽  
Semantic Inference ◽  
The Core ◽  
Granularity Level ◽  
Textual Entailment ◽  
Linguistic Dimension ◽  
Logical Representation

Beside formal approaches to semantic inference that rely on logical representation of meaning, the notion of Textual Entailment (TE) has been proposed as an applied framework to capture major semantic inference needs across applications in Computational Linguistics. Although several approaches have been tried and evaluation campaigns have shown improvements in TE, a renewed interest is rising in the research community towards a deeper and better understanding of the core phenomena involved in textual inference. Pursuing this direction, we are convinced that crucial progress will derive from a focus on decomposing the complexity of the TE task into basic phenomena and on their combination. In this paper, we carry out a deep analysis on TE data sets, investigating the relations among two relevant aspects of semantic inferences: the logical dimension, i.e. the capacity of the inference to prove the conclusion from its premises, and the linguistic dimension, i.e. the linguistic devices used to accomplish the goal of the inference. We propose a decomposition approach over TE pairs, where single linguistic phenomena are isolated in what we have called atomic inference pairs, and we show that at this granularity level the actual correlation between the linguistic and the logical dimensions of semantic inferences emerges and can be empirically observed.

Using ZigBee in Ambient Intelligence Learning Scenarios

2012 ◽  
Vol 4 (3) ◽  
pp. 33-45
Author(s):  
Óscar García ◽  
Ricardo S. Alonso ◽  
Dante I. Tapia ◽  
Juan M. Corchado
Keyword(s):  
Information And Communication Technologies ◽  
Ambient Intelligence ◽  
Communication Technologies ◽  
Traditional Teaching ◽  
Location Awareness ◽  
Traditional Teaching Methods ◽  
Granularity Level ◽  
Information And Communication ◽  
Learning Scenarios ◽  
To Receive

The inclusion of Information and Communication Technologies, especially mobile devices, in learning environments has allowed both the emergence of new ways of learning and the adaptation of traditional teaching methods. In this sense, Ambient Intelligence (AmI) paradigm represents a promising approach that can be successfully applied to education. Pervasive computing, context and location awareness are AmI features that can allow students to receive customized information in a transparent way. Fortunately, there are several technologies that can help to gather such information. In this regard, Real-Time Locating Systems (RTLS) is a key technology that can improve context-awareness in AmI-based systems. This paper presents the use of a novel RTLS based on ZigBee technology that provides users’ positions in order to enhance context information in learning applications. This way, this system allows customizing the content offered to the users without their explicit interaction, as well as the granularity level provided by the system.

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