scholarly journals A Comparative Study of the Cross Entropy Approach with the State–of-the-art Simulation-based Traffic Assignment Algorithms

2012 ◽  
Vol 54 ◽  
pp. 749-757
Author(s):  
Tai-Yu Ma
Keyword(s):  
Comparative Study ◽  
Traffic Assignment ◽  
State Of The Art ◽  
The State ◽  
Cross Entropy ◽  
Simulation Based ◽  
The Cross

scholarly journals The State-of-the-Art Technology of Currency Identification

2017 ◽  
Vol 9 (3) ◽  
pp. 58-72 ◽  
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

The State-of-the-Art Technology of Currency Identification

2018 ◽  
pp. 252-269
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

scholarly journals Measurement and simulation of the background in the CMS muon detectors

2019 ◽  
Vol 214 ◽  
pp. 02020
Author(s):  
Cesare Calabria
Keyword(s):  
Gamma Irradiation ◽  
High Intensity ◽  
State Of The Art ◽  
The State ◽  
Cms Experiment ◽  
Simulation Based

The study of the different backgrounds which the muon detectors of the CMS experiment are exposed to, is fundamental to assess the system longevity and project its performance to the conditions expected for HL-LHC. In this respect, an accurate modelling of the backgrounds in simulation is of prime importance as many studies rely on simulation-based predictions while these future conditions have never been experienced in reality. This paper will present the state of the art of the work carried out to understand backgrounds observed with data collected during the LHC runs, as well as at the CERN high-intensity gamma irradiation facility. Furthermore, the effort made to improve the accuracy of FLUKA and GEANT4 based simulations of background will be thoroughly described.

scholarly journals The road towards industry 4.0: a comparative study of the state-of-the-art in the Italian manufacturing industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ting Zheng ◽  
Marco Ardolino ◽  
Andrea Bacchetti ◽  
Marco Perona
Keyword(s):  
Technology Adoption ◽  
Comparative Study ◽  
Industry 4.0 ◽  
State Of The Art ◽  
Geographical Area ◽  
The State ◽  
Manufacturing Companies ◽  
Content Type ◽  
Business Functions ◽  
Italian Manufacturing Firms

PurposeThis paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in technologies implemented and business functions involved, benefits perceived, and obstacles encountered in I4.0 implementation over a three-year period.Design/methodology/approachThe approach adopted in this research is descriptive, nesting longitudinal features. The paper presents a descriptive survey of 102 Italian manufacturing companies. The authors also evaluated non-response biases. The longitudinal approach was achieved by comparing the responses of the 40 sub-samples in common with a second similar survey launched three years prior, which aimed to identify patterns of evolution in the adoption of the I4.0 paradigm.FindingsSurvey findings demonstrate that Italian manufacturing companies still have limited awareness of I4.0 technologies, and the adoption of I4.0 technologies differs per technology. Company size and information system coverage level are the two factors that impact the company's technology adoption level. The comparative study shows that knowledge and adoption increase in a three-year interval with an unbalanced involvement of business functions regarding the I4.0 transformation. Indeed, companies are still seeking I4.0 solutions to reduce costs and lead times primarily, and the benefits perceived by companies are shown to be related to the number of I4.0 technologies in use. Finally, when companies put the I4.0 technologies into practice, competence is constantly considered the most significant barrier.Research limitations/implicationsThis paper aims at conducting a thorough investigation into the development of I4.0 adoption in manufacturing companies. The main limitation of this study concerns the limited number of subjects involved in the longitudinal study (40) and the focus on a limited geographical area (Italy). In addition, more I4.0 technologies could also be incorporated into the survey protocol to gain further insight into I4.0 development.Originality/valueThe authors provide one of the first attempts to assess the variations of I4.0 implementation concerning technology adoption, business function involvement, and the alteration of benefits and obstacles. Several studies presented in the literature highlight the lack of longitudinal studies investigating the development of the I4.0 paradigm in a specific manufacturing context: this paper is the attempt at filling this gap.

The Ultimate Horizontal Issue: The Environmental Policy Experiences of Alberta and Ontario, 1971–1993

1994 ◽  
Vol 27 (1) ◽  
pp. 129-152 ◽  
Author(s):  
Mark Winfield
Keyword(s):  
Environmental Policy ◽  
Comparative Study ◽  
Policy Making ◽  
Environmental Politics ◽  
The State ◽  
Policy Issues ◽  
Provincial Level ◽  
The Cross ◽  
Canadian Provinces

AbstractThis article summarizes the conclusions of a comparative study of the environmental policy experiences of two Canadian provinces, Alberta and Ontario, in the period 1971–1993. The examination led to the conclusion that there is a pattern of environmental politics and policy-making common to both provinces, although it emerges at a different pace. This divergence is a function of well-known societal differences between the two provinces. Furthermore, in the Ontario and Alberta experiences, the policy-making capacity of the state can be seen to be severely challenged by the cross-sectoral nature of environmental policy issues. A number of observations regarding the effects of federal-provincial relations and of American influences on environmental policy-making at the provincial level in Canada are also possible.

scholarly journals Cross Entropy of Neural Language Models at Infinity—A New Bound of the Entropy Rate

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 839 ◽  
Author(s):  
Shuntaro Takahashi ◽  
Kumiko Tanaka-Ishii
Keyword(s):  
Natural Language ◽  
State Of The Art ◽  
Training Data ◽  
Language Models ◽  
Cross Entropy ◽  
Entropy Rate ◽  
Natural Language Text ◽  
Power Law Decay ◽  
The Cross ◽  
Two Parameters

Neural language models have drawn a lot of attention for their strong ability to predict natural language text. In this paper, we estimate the entropy rate of natural language with state-of-the-art neural language models. To obtain the estimate, we consider the cross entropy, a measure of the prediction accuracy of neural language models, under the theoretically ideal conditions that they are trained with an infinitely large dataset and receive an infinitely long context for prediction. We empirically verify that the effects of the two parameters, the training data size and context length, on the cross entropy consistently obey a power-law decay with a positive constant for two different state-of-the-art neural language models with different language datasets. Based on the verification, we obtained 1.12 bits per character for English by extrapolating the two parameters to infinity. This result suggests that the upper bound of the entropy rate of natural language is potentially smaller than the previously reported values.

scholarly journals An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss

2019 ◽  
Vol 33 ◽  
pp. 7492-7500 ◽  
Author(s):  
Peixiang Zhong ◽  
Di Wang ◽  
Chunyan Miao
Keyword(s):  
Artificial Intelligence ◽  
Objective Function ◽  
State Of The Art ◽  
The State ◽  
Cross Entropy ◽  
Open Domain ◽  
Human Communication ◽  
Baseline Model ◽  
Implicit Information ◽  
Comparable Size

Affect conveys important implicit information in human communication. Having the capability to correctly express affect during human-machine conversations is one of the major milestones in artificial intelligence. In recent years, extensive research on open-domain neural conversational models has been conducted. However, embedding affect into such models is still under explored. In this paper, we propose an endto-end affect-rich open-domain neural conversational model that produces responses not only appropriate in syntax and semantics, but also with rich affect. Our model extends the Seq2Seq model and adopts VAD (Valence, Arousal and Dominance) affective notations to embed each word with affects. In addition, our model considers the effect of negators and intensifiers via a novel affective attention mechanism, which biases attention towards affect-rich words in input sentences. Lastly, we train our model with an affect-incorporated objective function to encourage the generation of affect-rich words in the output responses. Evaluations based on both perplexity and human evaluations show that our model outperforms the state-of-the-art baseline model of comparable size in producing natural and affect-rich responses.

scholarly journals The state of the art of agile kanban method: challenges and opportunities

2021 ◽  
Vol 12 (8) ◽  
pp. 2535-2550
Author(s):  
Hamzah Alaidaros ◽  
Mazni Omar ◽  
Rohaida Romli
Keyword(s):  
State Of The Art ◽  
The State ◽  
Extensive Review ◽  
Review Of The Literature ◽  
Research Teams ◽  
Future Studies ◽  
Current State ◽  
Challenges And Opportunities ◽  
The Cross

In the recent years, the Agile Kanban has emerged as an appropriate method used for managing projects in numerous fields and various settings. Despite getting an increased popularity in the software organizations, the Agile Kanban method still has different challenges that need to be addressed. Therefore, this study aims to concisely explore the current state of the art and latest researches on the Agile Kanban method through conducting an extensive review of the literature. The results of this study carry strong implications and confirm the important need for conducting researches on the Agile Kanban method. It also provides the key challenges and opportunities that can be investigated in future studies. The cross analysis of the results leads to a better understanding of the Agile Kanban method and aids the research teams to address the Kanban limitations and increase its adoption in the software organizations.

scholarly journals A Similarity Inference Metric for RGB-Infrared Cross-Modality Person Re-identification

2020 ◽  
Author(s):  
Mengxi Jia ◽  
Yunpeng Zhai ◽  
Shijian Lu ◽  
Siwei Ma ◽  
Jian Zhang
Keyword(s):  
Image Matching ◽  
Nearest Neighbor ◽  
State Of The Art ◽  
The State ◽  
Accuracy Improvement ◽  
Similarity Graph ◽  
The Cross

RGB-Infrared (IR) cross-modality person re-identification (re-ID), which aims to search an IR image in RGB gallery or vice versa, is a challenging task due to the large discrepancy between IR and RGB modalities. Existing methods address this challenge typically by aligning feature distributions or image styles across modalities, whereas the very useful similarities among gallery samples of the same modality (i.e. intra-modality sample similarities) are largely neglected. This paper presents a novel similarity inference metric (SIM) that exploits the intra-modality sample similarities to circumvent the cross-modality discrepancy targeting optimal cross-modality image matching. SIM works by successive similarity graph reasoning and mutual nearest-neighbor reasoning that mine cross-modality sample similarities by leveraging intra-modality sample similarities from two different perspectives. Extensive experiments over two cross-modality re-ID datasets (SYSU-MM01 and RegDB) show that SIM achieves significant accuracy improvement but with little extra training as compared with the state-of-the-art.

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