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共 1492 条记录，以下是231-240 订阅

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Factorial analysis in the internal control's dimensions on lithographic companies 17

Factorial Analysis in the internal control's dimensions on l...

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17th international conference on Future Networks and Communications / 19th international conference on Mobile systems and Pervasive Computing / 12th international conference on Sustainable Energy Information Technology, FNC/MobiSPC/SEIT 2022

作者： Velandia-Pacheco, Gabriel Escobar-Castillo, Adalberto Navarro-Manotas, Evaristo Otalora-Beltrán, Jorge Archibold-Barrios, Wendell Franklin-Navarro, Stefanell Ramos-Barrios, Liliana García-Rodríguez, José Universidad de la Costa CUC Barranquilla08003 Colombia Universidad del Atlántico Barranquilla08003 Colombia Universidad Juárez Autónoma de Tabasco 86040 Mexico

Previous studies have highlighted the influence of control mechanisms on organizational performance, since it reduces uncertainty in decision making. However, there is no evidence of literature demonstrating how managers apply internal control strategies to create dynamic tensions that contribute to superior performance. therefore, the objective of the article is to analyze the dimensions of internal control in the lithographic companies of Barranquilla. A positivist, explanatory and non-experimental research was developed. As an instrument for collecting information, a Likert-type ordinal scale questionnaire was produced for 150 managers of the companies under study. On the other hand, a confirmatory factor analysis was applied as a statistical technique. the results show that risk assessment (0.968), control environment (0.959) and information and communication (0.957) are the dimensions of internal control that present the greatest loads within the factorial model, which allows us to deduce that, in the companies studied the development of strategies to reduce the risks inherent in their business activities becomes more relevant;thus guaranteeing the achievement of corporate objectives by reducing information asymmetry and incorporating tools that make communication more effective. © 2022 the Authors. Published by Elsevier B.V. this is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the conference Program Chairs.

关键词： Risk assessment

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Development of A BIM-based Automated Fall Hazzard Identification as Prevention-through-Design(PTD) Tool for Structural Designers

Development of A BIM-based Automated Fall Hazzard Identifica...

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IEEE Global conference on Consumer Electronics (GCCE)

作者： Rimmon Labadan Sho Takahashi Kriengsak Panuwatwanich Toru Hagiwara Faculty of Engineering Hokkaido University Japan and Sirindhorn International Institute of Technology Thammasat University Thailand Faculty of Engineering Hokkaido University Hokkaido Japan Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand

Fall-from-heights have historically been the major cause of fatalities in the construction sector, accounting for around one-third of all fatalities in the construction industry. this type of risk can be prevented or mitigated during the design phase through an innovative safety management approach called Prevention through Design (PTD). However, past research suggests that the lack of PTD tools is one of the reasons for the slow adoption of PTD among designers. thus, the current study aimed to develop a BIM-based automated fall hazard identification as a designer’s tool for PTD. A BIM-based PTD framework for structural designing has been developed and evaluated through a case study. Results have reinforced the viability of BIM software as a tool for PTD analysis in structural designing.

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Principal Component analysis Visualization and State Discovery with Soil Data

Principal Component Analysis Visualization and State Discove...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Miki Sirola Markku Koskinen Tatu Polvinen Mari Pihlatie University of Helsinki Helsinki Finland

Data exploration helps to gain understanding of the dataset and the system itself. there are methodologies to handle large number of sensors as well. In this paper operational states are defined to interpret physical behaviour in a soil ecosystem. Dimensionality reduction is achieved with Principal Component analysis (PCA) method giving another view to the soil dataset from spring term. K-means algorithm groups data densities by clustering the data. this grouping is the basis for defining operational states in the system. Soil data as a part of an ecosystem involves specific features. In the applied approach dynamic visualization including animations constitute an important exploration view. All experiments are realized in Jupyter programming environment with Python 3 programming language. Related literature about data visualization is reviewed. Combining methods and tools with this data as a result soil ecosystem features are recognized.

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analysis of Source Code Using UPPAAL 6

Analysis of Source Code Using UPPAAL

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19th international conference on tools and algorithms for the construction and analysis of systems (TACAS)

作者： Kulczynski, Mitja Legay, Axel Nowotka, Dirk Poulsen, Danny Bogsted Univ Kiel Kiel Germany Univ Louvain Louvain La Neuve Belgium Aalborg Univ Aalborg Denmark

In recent years there has been a considerable effort in optimising formal methods for application to code. this has been driven by tools such as CPACHECKER, DIVINE, and CBMC. At the same time tools such as UPPAAL have been massively expanding the realm of more traditional model checking technologies to include strategy synthesis algorithms - an aspect becoming more and more needed as software becomes increasingly parallel. Instead of reimplementing the advances made by UPPAAL in this area, we suggest in this paper to develop a bridge between the source code and the engine of UPPAAL. Our approach uses the widespread intermediate language LLVM and makes recent advances of the UPPAAL ecosystem readily available to analysis of source code.

关键词： Formal methods

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analysis and Forecast of Subway construction Cost Based on Bayesian Network

Analysis and Forecast of Subway Construction Cost Based on B...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Feng Guo Donghui Niu Guoling Zhang Na Hou Zhengbing Hu China Railway Seventh Bureau Group Electrical Engineering Co. Ltd Zhengzhou China National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine

In the process of subway construction, there is a complex nonlinear relationship among the engineering quantity, material cost, labor cost and total cost, which cannot be accurately calculated by manpower alone. therefore, the reasonable deployment of human, material, capital and other resources in the future requires a high-precision and highly reliable analysis and prediction model. Aiming at this problem, this paper proposes a Bayesian network model of subway construction project cost prediction based on principal component analysis and K2 algorithm on the basis of analyzing the financial data, contract data and the existing engineering quantity calculation data in the information data system. Firstly, the principal component analysis method is used to screen the influencing factors of subway mechanical and electrical engineering and extract the core data features. Based on the extracted features, a Bayesian network model was built according to the principle of K2 algorithm to dynamically analyze the engineering cost, and the actual subway engineering cost data was used to train, verify and predict the model. the experimental results show that the accuracy of the prediction model proposed in this paper is 87.5%, and the prediction results are completely within the controllable range, thus proving the effectiveness of the model and realizing the dynamic tracking of the construction cost of electromechanical engineering.

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Innovative analysis methods of energy performance of buildings

Innovative analysis methods of energy performance of buildin...

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9th international conference on New Energy and Future Energy systems (NEFES 2024)

作者： Dániel László Hegedűs Olivér Tóth Árpád Hajdu Kitti Ajtayné Károlyfi Tamás Horváth Dóra Szalai Department of Architecture and Building Construction Széchenyi István University H-9026 Győr Egyetem tér 1 Hungary Department of Structure and Geotechnical Engineering Széchenyi István University H-9026 Győr Egyetem tér 1 Hungary

ISBN: (数字)9781837241880

In the current era of architecture, sustainability and energy efficiency are becoming increasingly important, while at the same time, advanced technological tools and analytical methods are reshaping the design and construction of buildings. Architects must think responsibly and globally, as buildings account for a significant proportion of the world's energy use. As architects, we have a responsibility to create ecologically optimal facilities for the long term. With this in mind, we would like to present applications that trace the chronological milestones in the development of energy analysis. this paper provides a detailed overview of the different methods of energy analysis. the methods include software developed specifically for energy analysis, an analysis add-on built into modeling software, and among the more innovative technologies, we have also examined parametric design and methodologies based on artificial intelligence algorithms. We have tried to select these methodologies and software in a diversified way to get a more comprehensive picture of how they work. the main aim of this paper is to compare the conclusions drawn from case studies of our previous energy research and from the studies of these energy software, partly subjectively and partly with an objective perspective that tightens subjectivity. As such, a set of criteria we have defined will guide the structure of this analysis. In this article, we will try to highlight the advantages and disadvantages of each method, and we will also try to consider the importance of 3D model-based analysis.

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Implementing Project Management Principles Aligned with the Circular Economy

Implementing Project Management Principles Aligned with the ...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Sergey Bushuyev Natalia Bushuyeva Denis Bushuiev Victoria Bushuieva Kyiv National University of Construction and Architecture Kyiv Ukraine

the circular economy principles are examined in the context of developing integrated information technologies. A conceptual model for managing circular economy projects is presented, encompassing three management levels to ensure strategic sustainability. As an illustrative example, the business model of establishing an agrarian-industrial complex of energy-independent enterprises based on circular economy principles is explored. this model encompasses the comprehensive infrastructure of the agrarian-industrial complex, incorporating hybrid project management methodologies and an innovative development program. the application of process models, the waterfall life cycle, Agile models, and various project management methods are utilized. throughout the analysis of the business case, the architecture and interaction schemes of the program with the environment during its implementation are determined.

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Composite Indicators Building Based on Concordant of Expert-Statistical Information Using Biased Ridge Kernel Regression

Composite Indicators Building Based on Concordant of Expert-...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Leonid Lyubchyk Galyna Grinberg Zoia Konokhova Klym Yamkovyi Computer Mathematics and Data Analysis Department National Technical University “Kharkiv Polytechnic Institute” Marketing Department National Technical University “Kharkiv Polytechnic Institute”

the problem of constructing a complex composite indicator based on expert scores and statistical information about particular indicators is considered. A procedure for estimating the parameters of a nonlinear model of a composite indicator based on the method of biased kernel ridge regression is proposed; at the same time, the problem of optimal concordant of expert and statistical information is solved by choosing the appropriate regularization functional. Using the method of Lagrange multipliers, expressions for estimating the parameters of a nonlinear model and a kernel-based model of a composite indicator are obtained. the results of a numerical experiment on the construction of a composite indicator model using real data are presented.

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A Web-Based Platform for Women Crime Data Visualization and analysis 12th

A Web-Based Platform for Women Crime Data Visualization and ...

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12th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA 2024

作者： Anvesh, Kachi Swapna, N. Prashanth, S.K. Farooqui, Maryam Fatima Habeeb, Novera Department of Information Technology Vardhaman College of Engineering Telangana Hyderabad501218 India Department of Computer Science and Engineering Vijay Rural Engineering College Telangana Nizamabad503003 India Department of Information Technology Vasavi College of Engineering Telangana Hyderabad500031 India Department of Computer Science and Engineering J.B. Institute of Engineering & Technology Telangana Hyderabad500075 India

ISBN: (纸本)9789819601387

A web-based platform created with Python, HTML, and CSS intended to offer useful crime data visualization for a particular city. Users of the platform can learn about crime patterns and trends through interactive visualizations because of the program’s usage of Python. An intuitive and user-friendly front-end interface was primarily created using HTML and CSS. through a web browser, users can access the platform and study crime data and engage with different visualizations. Python is used to create the crime Vs back end, which is essential for producing graphical representations based on crime data. Data collection, preprocessing, storage, and graphical representation are a few of the crucial elements involved in the development of crime rate Vs. crime statistics are gathered from trustworthy sources like law enforcement organizations and public records. Python is employed for transforming it into a suitable format for visualization. A database is used to store the processed data, making it easy to access it for graphical depiction. Gives users access to an appealing and interactive environment that was created using HTML and CSS. Users can personalize their views, filter data-based on crime types or time periods, and visualize crime incidents using a variety of graphical tools, including bar charts, pie charts, and heat maps. Users can use the visualizations to find patterns, hot spots, and trends in crime data, improving the understanding of crime processes. A Web site that targets high-crime states in India aims to inform women about crime rates and support law enforcement. It provides graphical statistics on trafficking, sexual assault, and other topics, allowing for educated safety measures and emphasizing the necessity of addressing underlying problems to create a safer atmosphere. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： HTML

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Using Active Learning Techniques for analysis of Photomicroscopy Images

Using Active Learning Techniques for Analysis of Photomicros...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Linda Blahova Jozef Kostolny Faculty of Management Science and Informatics University of Zilina Zilina Slovakia

Processing biomedical image data, specifically microscopic data from a blood sample, where it is necessary to identify and classify leukocytes, is a complex issue. Manual processing of such data is time-consuming and can be subjective and prone to human error. therefore, this work aims to analyze current processing techniques and available tools to simplify and automate this process. the paper includes an overview of the biomedical data used, and describes the analysis, the selection of the relevant data, a proposal for a solution using the general methods and overall automation of the process, an implementation of the solution, and an evaluation of its benefits in further research. Logistic regression was used to predict the leukocyte type, in combination with the active learning approach. the work results in a solution that simplifies and mainly speeds up the processing of microscopic data for leukocyte identification and classification by removing the human error and subjectivity. the proposed solution achieved classification accuracy of 92% in both training and testing dataset (Raabin-WBC) and 84% on vakidation dataset (BCCD), without any changes in the model parameters. this solution may find application in diagnosing various diseases such as blood cancers, infections, autoimmune diseases, or allergies.

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