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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Pandey, Ravindra Rongali, Aruna Sri Gopinath, S. Anute, Nilesh Nama, Forda Pund, Sachin Hult International Business School United States University of the Cumberlands Doctoral Information Technology Information Technology Emphasis Information Technology United States Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India ASM's Institute of Business Management and Research Pune India University of Lampung Doctoral Program of Environtmental Science Department of Informatics Bandar Lampung Indonesia Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350357769

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets. © 2023 IEEE.

关键词： approximately gaining knowledge mastering performance regression

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High embedding reversible data hiding scheme for JPEG

High embedding reversible data hiding scheme for JPEG

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6th International Conference on Intelligent information Hiding and Multimedia Signal Processing, IIHMSP 2010

作者： Kuo, Wen-Chung Kuo, Shao-Hung Wuu, Lih-Chyau Depart. of Computer Science and Information Engineering National Formusa University Yunlin 632 Taiwan Graduate School of Engineering Science Technology Doctoral Program National YunLin University of Science and Technology Yunlin 640 Taiwan

ISBN: (纸本)9780769542225

Both Data hiding and data compression are very important technologies in the field of image processing. It seems that there is no relationship between data hiding and data compression because most of the data hiding mechanisms focus on information security and the data compression mechanisms emphasize the compression ratio. In fact, they are closely related. Until now, there are many literatures to discuss the secret data how to be embedded into the media image. Unfortunately, the stego-image's size will be increased when the media image is hidden a lot of secret data. In order to overcome this disadvantage, a reversible data hiding scheme based on EMD data hiding and JPEG compression technology will be proposed in this paper. According to the experimental results, we can prove that our proposed scheme still keeps high embedding capacity, security and good compression ratio. © 2010 IEEE.

关键词： Steganography

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Purchasing Intention of Tour Package Brands in Access to Digital technology and User Generated Content on Bali Travel Tour 1

Purchasing Intention of Tour Package Brands in Access to Dig...

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1st IEEE International Symposium on Consumer technology, ISCT 2024

作者： Raka Novandra Asta, Ngr. Putu Suryani, Erma Hari Ginardi, Raden Venantius Interdisciplinary School of Management Technology Institut Teknologi Sepuluh Nopember Surabaya Surabaya Indonesia Politeknik NegeriBali Doctoral Program in Technology Management Bali Indonesia Institut Teknologi Sepuluh Nopember Surabaya Department of Information Systems Surabaya Indonesia

ISBN: (纸本)9798350365191

Digital technology is currently a vital medium to influence consumers with diverse behaviours and a high level of sensitivity when purchasing goods and services. The purpose of this study is to analyse the impact of exposure to digital technology and user-generated content on the brand purchase intention of travel packages in the Bali tourism sector. As digital technology changes the way we communicate or convey information to attract consumers, one of the methods used to attract consumers is user-generated content (UGC) to create a more intimate engagement between products, services, and consumers. A total of 200 tourists who bought tour packages were used as respondents using accidental sampling. The results of the study explain that digital technology and user integration center have a significant influence on brand purchase intention, and brand exposure and brand familiarity have a considerable positive influence on brand purchase intention. A different influence is found: brand knowledge and attitude have a negative impact on brand purchase intention. The results of this study can enrich knowledge about the currently developing topic of e-marketing aimed at academics. From a practical perspective, this research can provide marketers with insight into the effectiveness of content as an advertising platform in the travel and tourism industry. © 2024 IEEE.

关键词： Leisure industry

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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Modifying the Revised NIOSH Lifting Equation using Anthropometric Variables to Calculate Horizontal and Vertical Multipliers 4

Modifying the Revised NIOSH Lifting Equation using Anthropom...

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Rochmat, Moehamad Adi Madenda, Sarifuddin Handhika, Tri Ernastuti, Ernastuti Gunadarma University Department of Industrial Engineering Depok Indonesia Gunadarma University Doctoral Program in Information Technology Depok Indonesia Gunadarma University Centre for Computational Mathematics Studies Depok Indonesia Gunadarma University Faculty of Industrial Technology Depok Indonesia

ISBN: (纸本)9781665453950

The Revised NIOSH Lifting Equation is a work system assessment tool which often used in industrial world. The calculation result in the form of Recommended Weight Limit (RWL) and the Lifting Index (LI) become the basis for improving the work system carried out. RNLE is an application developed by NIOSH and uses American anthropometry as a constant in its calculations. Some researchers, especially in Asia, consider that the application is less suitable for Asia people who have anthropometric differences with Americans. The assessment carried out by the RNLE application is based on work activities carried out without considering the worker's body posture. In particular, the calculate of HM and VM in this application uses a constant related to anthropometry. RNLE uses the constants based on the average anthropometry of workers in calculation. The constant anthropometry used in the equation led to the results of the risk calculation that does not correspond to physical aspects of workers. It takes an equation that consider anthropometry workers to get the calculation of the value of the appropriate work risk. The study aims to propose equations that consider anthropometry factors to calculate the risk factor. The development of the equation with Python programming language allows further development in the field of information and communication technology. The results of the study shows that the average results of the RWL and LI calculation uses anthropometry data not equal to the RNLE, thus required new equation in order to resulting more objective risk value. © 2022 IEEE.

关键词： Anthropometry

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Accuracy Evaluation of A Diagnostic Test by Detecting Outliers and Influential Observations

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China Ocean Engineering 2008年第3期22卷 421-429页

作者： Hsien-Chueh Peter YANG Tsung-Hao CHEN Cheng-Wu CHEN Chen-Yuan CHEN Chun-Te LIU Department of Risk Management and Insurance National Knohsiung First University of Science and Technology Kaohsiung 811 China Department of Business Administration Shu-Te University Kaohsiung 82445 China Department of Logistics Management Shu-Te University Kaohsiung 82445 China Department of Management Information System Yung- Ta Institute of Technology and Commerce Pingtung 90941 China Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung 811 China

Logit regression analysis is widely applied in scientific studies and laboratory experiments, where skewed observations on a data set are often encountered. A number of problems with this method, for example, oudiers and influential observations, can cause overdispersion when a model is fitted. In this study a systematic statistical approach, including the plotting of several indices is used to diagnose the lack-of-fit of a logistic regression model. The outliers and influential observations on data from laboratory experiments are then detected. Specifically we take account of the interaction of an internal sohtary wave （ISW） with an obstacle, i.e., an underwater ridge, and also analyze the effects of the ridge height, the lower layer water depth, and the potential energy on the amplitude-based transmission rate of the ISW. As concluded, the goodness-of-fit of the revised logit regression model is better than that of the model without this approach.

关键词： diagnostic testing outliers influential observations internal solitary wave

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Integrating System Dynamics and Random Forest Algorithm for Sales Forecasting 1

Integrating System Dynamics and Random Forest Algorithm for ...

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1st IEEE International Symposium on Consumer technology, ISCT 2024

作者： Magdalena Rafu Mamulak, Natalia Suryani, Erma Dwi Trijoyo Purnomo, Jerry Institut Teknologi Sepuluh Nopember Interdisciplinary School of Management and Technology Doctoral Program in Technology Management Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Information Systems Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Statistics Surabaya Indonesia

ISBN: (纸本)9798350365191

This study proposes an approach to improve sales forecasting accuracy by integrating System Dynamics (SD) modeling with the Random Forest (RF) algorithm. The combination of these two methods offers a promising way to make sales predictions more reliable, especially in uncertain market conditions. Using SD principles within the RF algorithm helps us simulate expected sales growth, gain insights into market dynamics, and make our forecasting model more understandable to stakeholders. This study using synthetic sales data shows that the integrated approach is offered as an open idea and customizable, particularly in scenarios with dynamic growth patterns and feedback effects. © 2024 IEEE.

关键词： machine learning marketing random forest sales forecasting simulation system dynamics

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Automatic Identification and Reconstruction 3D Image of the Rhinosinusitis Mucus 12

Automatic Identification and Reconstruction 3D Image of the ...

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12th International Conference on information and Communication technology, ICoICT 2024

作者： Eka Putra, Ondra Sumijan Tajuddin, Muhammad Universitas Putra Indonesia YPTK Padang Faculty of Computer Science Department of Informatics Technology Padang Indonesia Doctoral Program in Information Technology Universitas Putra Indonesia YPTK Padang Padang Indonesia Bumigora University Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350363432

Rhinosinusitis Mucus is mucus produced by mucus glands found in the nose in the paranasal sinus area which indicates inflammation. Segmentation of rhinosinusitis mucus is very difficult to do because of the many characteristics of different objects in the image of the paranasal Sinus CT-Scan in separating the mucus object with its background before the extraction process. The purpose of this study was to accurately identify and measure the mucus area of rhinosinusitis from CT-scan images of rhinosinusitis patients. The test data used in this study is secondary data from CT-Scan of paranasal sinus sagittal view in radiology RSUP M. Djamil Padang, Padang City, West Sumatra, Indonesia, using the Philips Ingenuity CT CT-Scan model type MRC880 numbered Tube series 163889. The segmentation process is carried out to obtain the optimal multi threshold value from each slice of the test image using the Improved Adaptive Multi Threshold (IAMT) segmentation method which produces a binary image to separate the mucus object with its background before the extraction process. Furthermore, the results of IAMT are applied to the identification and extraction model automatically to obtain the area of the rhinosinusitis mucus object. The extraction results were used for 2D to 3D image reconstruction in calculating the volume of rhinosinusitis mucus objects. The test results showed that the smallest area of rhinosinusitis mucus was 0.516 cm2 and the largest was 1.807 cm2, and the average volume was 0.95 cm3 with Accuracy is 96,5%. The identified areas and volumes indicate inflammation in the area of the paranasal sinuses and require treatment. Thus, this study can help doctors in making the right decision to take further medical action. © 2024 IEEE.

关键词： Computerized tomography

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An authenticated anonymous group key management with only one rekey message

An authenticated anonymous group key management with only on...

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5th IASTED European Conference on Internet and Multimedia Systems and Applications, EuroIMSA 2009

作者： Wuu, Lih-Chyau Hung, Chi-Hsiang Department of Computer Science and Information Engineering National Yunlin University of Science and Technology 123 University Road Touliu Yunlin Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology 123 University Road Touliu Yunlin Taiwan

ISBN: (纸本)9780889868021

In Internet, IP multicast has been used successfully to provide an efficient, best-effort delivery service for group communication applications. However, applications such as multiparty private conference, distribution of stock market information, pay per view and other subscriber services require secure multicast to protect integrity and confidentiality of the group traffic, and validate group member's authenticity. Providing secure multicast for group communication is problematic without a robust group key management. In this paper, we propose an anonymous group key management with ID-based Signature and secret sharing technologies to distribute a new group key securely to each participant of a group with only one rekey message whenever the group membership changes. The key management guarantees that a legal user, without revealing his/her real identity, can join a group after finishing the mutual authentication with the group initiator, and enforces the forward secrecy and backward secrecy.

关键词： Multicasting

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Optimation Cavacity Vehicle Routing Problem with K-Nearest Neighbor in Classification of Goods Ditribution Route 7

Optimation Cavacity Vehicle Routing Problem with K-Nearest N...

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7th IEEE International Conference of Computer Science and information technology, ICOSNIKOM 2023

作者： Novelan, Muhammad Syahputra Efendi, Syahril Sihombing, Poltak Mawengkang, Herman Universitas Sumatera Utara Doctoral Program of Computer Science Faculty of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Department of Computer Science Medan Indonesia Universitas Sumatera Utara Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia

ISBN: (纸本)9798350360752

Industrial and distribution service problems that belong to combinatorial optimization include vehicle routing with Vehicle Routing Problem. This research builds a framework and implements it in a multi-class optimization model to reduce overfitting and misclassification results caused by unbalanced multiclassification in the influence of the number of 'nodes' on vehicle routes with machine learning. The problem of imbalance in vehicle route classification has been a challenge in the classification process and attracted the attention of a number of researchers. The purpose of the model in general is to gain an understanding of the mechanism in the problem so as to classify the imbalanced vehicle route data based on JNE delivery routes. The solution method that will be used by applying k-nearest neighbor to determine the amount of carrying capacity of the goods will then determine the delivery location point with the vehicle routing problem. So that this model can be a model in determining vehicle routes based on the capacity limit of the number of shipments of goods. © 2023 IEEE.

关键词： Machine learning

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