• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.26-32
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• 2023

Hajj is a fundamental pillar of Islam that all Muslims must perform at least once in their lives. However, Umrah can be performed several times yearly, depending on people's abilities. Every year, Muslims from all over the world travel to Saudi Arabia to perform Hajj. Hajj and Umrah pilgrims face multiple issues due to the large volume of people at the same time and place during the event. Therefore, a system is needed to facilitate the people's smooth execution of Hajj and Umrah procedures. Multiple devices are already installed in Makkah, but it would be better to suggest the data architectures with the help of machine learning approaches. The proposed system analyzes the services provided to the pilgrims regarding gender, location, and foreign pilgrims. The proposed system addressed the research problem of analyzing the Hajj pilgrim dataset most effectively. In addition, Visualizations of the proposed method showed the system's performance using data architectures. Machine learning algorithms classify whether male pilgrims are more significant than female pilgrims. Several algorithms were proposed to classify the data, including logistic regression, Naive Bayes, K-nearest neighbors, decision trees, random forests, and XGBoost. The decision tree accuracy value was 62.83%, whereas K-nearest Neighbors had 62.86%; other classifiers have lower accuracy than these. The open-source dataset was analyzed using different data architectures to store the data, and then machine learning approaches were used to classify the dataset.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.525-543
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• 1998

This paper proposes a conceptual taxonomy of architectures far workflow management systems. The systematic classification work is based on a framework for workflow architectures. The framework, consisting of generic-level, conceptual-level and implementation-level architectures, provides common architectural principles for designing a workflow management system. We define the taxonomy by considering the possibilities for centralization or distribution of data, control, and execution. That is, we take into account three criteria. How are the major components of a workflow model and system, like activities, roles, actors, and workcases, concretized in workflow architecture？ Which of the components is represented as software modules of the workflow architecture？ And how are they configured and operating in the architecture？ The workflow components might be embodied, as active (processes or threads) modules or as passive (data) modules, in the software architecture of a workflow management system. One or combinations of the components might become software modules in the software architecture. Finally, they might be centralized or distributed. The distribution of the components should be broken into three: Vertically, Horizontally and Fully distributed. Through the combination of these aspects, we can conceptually generate about 64 software Architectures for a workflow management system. That is, it should be possible to comprehend and characterize all kinds of software architectures for workflow management systems including the current existing systems as well as future systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and "global perspective" to workflow architectural discussions. The vocabulary suggested here includes workflow levels and aspects, allowing very different architectures to be discussed, compared, and contrasted. Added clarity is obtained because similar architectures from different vendors that used different terminology and techniques can now be seen to be identical at the higher level. Much of the complexity can be removed by thinking of workflow systems. Therefore, it is used to categorize existing workflow architectures and suggest a plethora of new workflow architectures. Finally, the taxonomy can be used for sorting out gems and stones amongst the architectures possibly generated. Thus, it might be a guideline not only for characterizing the existing workflow management systems, but also for solving the long-term and short-term architectural research issues, such as dynamic changes in workflow, transactional workflow, dynamically evolving workflow, large-scale workflow, etc., that have been proposed in the literature.

• The Journal of Information Technology and Database
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• v.5 no.1
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• pp.97-108
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• 1998

This paper proposes a conceptual taxonomy of architectures for workflow management systems. The systematic classification work is based on a framework for workflow architectures. The framework, consisting of generic-level, conceptual-level and implementation-level architectures, provides common architectural principles for designing a workflow management system. We define the taxonomy by considering the possibilities for centralization or distribution of data, control, and execution. That is, we take into account three criteria. How are the major components of a workflow model and system, like activities, roles, actors, and workcases, concretized in workflow architecture. Which of the components is represented as software modules of the workflow architecture\ulcorner And how are they configured and operating in the architecture\ulcorner The workflow components might be embodied, as active (processes or threads) modules or as passive (data) modules, in the software architecture of a workflow management system. One or combinations of the components might become software modules in the software architecture. Finally, they might be centralized or distributed. The distribution of the components should be broken into three: Vertically, Horizontally and Fully distributed. Through the combination of these aspects, we can conceptually generate about 64 software Architectures for a workflow management system. That is, it should be possible to comprehend and characterize all kinds of software architectures for workflow management systems including the current existing systems as well as future systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and global perspective to workflow architectural discussions. The vocabulary suggested here includes workflow levels and aspects, allowing very different architectures to be discussed, compared, and contrasted. Added clarity is obtained because similar architectures from different vendors that used different terminology and techniques can now be seen to be identical at the higher level. Much of the complexity can be removed by thinking of workflow systems. Therefore, it is used to categorize existing workflow architectures and suggest a plethora of new workflow architectures. Finally, the taxonomy can be used for sorting out gems and stones amongst the architectures possibly generated. Thus, it might be a guideline not only for characterizing the existing workflow management systems, but also for solving the long-term and short-term architectural research issues, such as dynamic changes in workflow, transactional workflow, dynamically evolving workflow, large-scale workflow, etc., that have been proposed in the literature.

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.51-73
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• 1998

This paper is to evaluate the application potentials of data mining in the areas of Supply Chain Management (SCM) and to suggest the architectures of Decision Support Systems (DSS) that support data mining activities. We first briefly introduce data mining and review the recent literatures on SCM and then evaluate data mining applications to SCM in three aspects: marketing, operations management and information systems. By analyzing the cases about pricing models in distribution channels, demand forecasting and quality control, it is shown that artificial intelligence techniques such as artificial neural networks, case-based reasoning and expert systems, combined with traditional analysis models, effectively mine the useful knowledge from the large volume of SCM data. Agent-based information system is addressed as an important architecture that enables the pursuit of global optimization of SCM through communication and information sharing among supply chain constituents without loss of their characteristics and independence. We expect that the suggested architectures of intelligent DSS provide the basis in developing information systems for SCM to improve the quality of organizational decisions.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.881-888
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• 2009

This research introduces the architecture of managing products based software. There are many of the architectures for managing products using software instead of manpower. In case of MVC and existing architectures, The architectures transfer redundant data so the architectures cause a problem that unnecessary data moved. This research presents VMDC(View, Model, Dispatcher, Controller) architecture to solve the problem. Dispatcher of VMDC grasps necessary data and reconstructs objects to efficient transferring data. This research shows usecase that designed VMDC(View, Model, Dispatcher, Controller) and demonstrate efficiency of VMDC(View, Model, Dispatcher, Controller) together. after demonstration this research present with next research.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.985-994
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• 1995

In this paper, we propose two hot standby architectures which not only provide high system availability but also lose little data on fault occurrence. In order to evaluate the performance of the proposed hot standby architectures, the warm standby architecture. In order to evaluate the performance of the propose d hot standby architectures, the warm standby architecture which is made from the hot standby architecture by eliminating its synchronization unit is considered. After system unavailability for each architecture is computed by using the corresponding Markov state diagram, the results are compared and evaluated. As the results, in most cases, hot standby architectures have higher availability than warm standby architecture. Also, hot standby architecture with external synchronization unit always maintains a little higher availability than hot standby architecture with internal synchronization unit. Active set time and personnel recovery rate for each architecture have little effect on system availability. However, in the case that data recovery time is too long, system availabilities of hot standby architectures and warm standby architecture degrade rapidly. In this case, the performance degradation of hot standby architectures is severe, and system availabilities of hot standby architectures eventually become lower than system availability of warm standby architecture.

• Journal of architectural history
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• v.14 no.3 s.43
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• pp.23-37
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• 2005

The purpose of this study is to clarify the characteristics of the ancient architectures of the Yuan Dynasty(元代). The result is expected to efficient for a basic data to research history of the Koryo(高麗) architectures. This study was focused on the architecture of the Yuan dynasty in Hancheng city, because the buildings of the Yuan Dynasty were remained in Hancheng city(韓城) of Shanxi province(陝西) in the largest numbers through all China territory. And the study was especially analyzed in the angle of the system of wooden structures among various architectural points. It was looked into, in large, views of form of whole structure and, in detail, joining method of detail parts. As a result of the study, the characteristics of architectures of the Yuan Dynasty in Hancheng city were summarized as follow a reduction of the unit size, a shifting of columns, a removal of columns and a simplicity of ornaments. These are different with architecture of other empire periods. Also, these are the characteristics of the Korean tradition at architectures. This study of the Yuan's architectures of Hancheng is expected to be the basis of the advanced study about the relationship between Koryo(高麗) architectures and Yuan(元) architectures.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.39-48
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• 2021

In this paper, a GAN-based data augmentation method is proposed for topology optimization. In machine learning techniques, a total amount of dataset determines the accuracy and robustness of the trained neural network architectures, especially, supervised learning networks. Because the insufficient data tends to lead to overfitting or underfitting of the architectures, a data augmentation method is need to increase the amount of data for reducing overfitting when training a machine learning model. In this study, the Ganerative Adversarial Network (GAN) is used to augment the topology optimization dataset. The produced dataset has been compared with the original dataset.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.2 no.3
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• pp.48-60
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• 2003

With the rapid successful deployment of WLANs worldwide in numerous hotspots for high data rate, wireless access for data services has created the need to integrate the Cellular Networks with WLAN Networks. The integrated wireless environment will provide the end user a much better service experience along with a single subscription and a single bill. In this paper we focus on inter-working approaches, which combine WLANs and Cellular Networks into an integrated wireless environment capable of ubiquitous access to data services and very high data rates in hotspots areas. We first list the key requirements which are currently being standardized within the 30PP for integration with WLANs networks. We discuss two inter-working architectures namely loosely coupled and tightly coupled This paper will detail the loosely coupled inter-working approach while briefly discussing the tightly coupled inter-working. Finally, we will conclude that the loosely coupled approach is evolutionary and less intrusive than the tightly coupled approach.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.3
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• pp.163-174
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• 2023

Though box compression strength (BCS) is commonly used as a performance criterion for shipping containers, estimating BCS remains a challenge. In this study, artificial neural networks (ANN) are implemented as a new tool, with a focus on building up ANN architectures for BCS estimation. An Artificial Neural Network (ANN) model can be constructed by adjusting four modeling factors: hidden neuron numbers, epochs, number of modeling cycles, and number of data points. The four factors interact with each other to influence model accuracy and can be optimized by minimizing model's Mean Squared Error (MSE). Using both data from the literature and "synthetic" data based on the McKee equation, we find that model estimation accuracy remains limited due to the uncertainty in both the input parameters and the ANN process itself. The population size to build an ANN model has been identified based on different data sets. This study provides a methodology guide for future research exploring the applicability of ANN to address problems and answer questions in the corrugated industry.