• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.205-211
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• 2022

Performing the rituals of Hajj and Umrah is an obligation of Allah Almighty to all Muslims from all over the world. Millions of Muslims visit the holy mosques in Makkah every year to perform Hajj and Umrah. One of the most important pillars in Performing Hajj/Umrah is Tawaf and Sa'ay. Tawaf finished by seven rounds around the holy house (Al-Kabaa) and Sa'ay is also seven runs between As-Safa and Al-Marwa. Counting/knowing the number of runs during Tawaf/Sa'ay is one of the difficulties that many pilgrims face. The pilgrim's confusing for counting (Tawaf/Sa'ay) rounds finished at a specific time leads pilgrims to stay more time in Mataff bowl or Masa'a run causing stampedes and more crowded as well as losing the desired time for prayers to get closer to Almighty Allah in this holy place. These issues can be solved using effective crowd management systems for Tawaf/Sa'ay pillars, which is the topic of this research paper. While smart devices and their applications are gaining popularity in helping pilgrims for performing Hajj/Umrah activities efficiently, little has been dedicated for solving these issues. We present an autonomous Mobile-based framework for guiding pilgrims during Tawaf/Sa'ay pillars with the aid of GPS for points tracking and rounds counting. This framework is specially designed to prevent and manage stampedes during Tawaf/Sa'ay pillars, by helping pilgrims automatically counting the rounds during Tawaf/Sa'ay with supported Supplications (in written/audio form with different languages) from the Quran and Sunna'a.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.309-318
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• 2010

Simulation-based acquisition(SBA) is a new acquisition paradigm to deliver combat systems cheaper, faster, and better. ROK MND adopts the vision of SBA and is pushing ahead with dramatic reform. However, ROK MND does not develop the SBA architecture framework which facilitates the reuse of tools and techniques and data software code and algorithms among participants of collaborative environments. In this paper, we propose a conceptual Model of architecture framework for SBA. To do so, we analyse acquisition process of MND and propose the to-be operational view that describes fundamental concept for how Government, Industry, and Academia can collaborate and share information more effectively throughout the acquisition process. Furthermore, we identify the tools and techniques that supports the operational nodes, and propose technical view and all view, too. technical view compose of set of standards that can ensure interoperability among tools, techniques and data, and all view provide an overarching description of the architecture.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.139-146
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• 2009

Recently, software industry regarding national defense increases system development of distributed simulation system of M&S based to overcome limit of resource and expense. It is one of key technologies for offering of mutual validation among objects and reuse of objects which are discussed for developing these systems. RTI, implementation of HLA interface specification as software providing these technologies uses Federation Object Model for exchanging information with joined federates in the federation and each federate has a characteristic that is supposed to have identical FOM in the federation. This paper presents a characteristic of Base Object Model, SISO standardization for improving reuse and interoperability of Federation Object Model applied simulation network manager based HLA/RTI and suggests method of designing the structure of simulation network manager through the modularity of Federation Object Model.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.211-217
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• 2023

Recently, many studies have introduced artificial intelligence systems in the surgical process to reduce the incidence and mortality of complications in patients. Bleeding is a major cause of operative mortality and complications. However, there have been few studies conducted on detecting bleeding in surgical videos. To advance the development of deep learning models for detecting intraoperative hemorrhage, three models have been trained and compared; such as, YOLOv5, RetinaNet50, and RetinaNet101. We collected 1,016 bleeding images extracted from five surgical videos. The ground truths were labeled based on agreement from two specialists. To train and evaluate models, we divided the datasets into training data, validation data, and test data. For training, 812 images (80%) were selected from the dataset. Another 102 images (10%) were used for evaluation and the remaining 102 images (10%) were used as the evaluation data. The three main metrics used to evaluate performance are precision, recall, and false positive per image (FPPI). Based on the evaluation metrics, RetinaNet101 achieved the best detection results out of the three models (Precision rate of 0.99±0.01, Recall rate of 0.93±0.02, and FPPI of 0.01±0.01). The information on the bleeding detected in surgical videos can be quickly transmitted to the operating room, improving patient outcomes.

• Knowledge Management Research
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• v.24 no.1
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• pp.127-145
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• 2023

This paper analyzed a patent trend for technological domain of hydrogen fuel cell, can improve future energy and pollution problems. Patent analysis is used in establishing a technological roadmap which it can discover the current technology capability and future technological development direction. However, the previous patent analysis is qualitative analysis and simple statistical analysis. The reason why it incorrectly analysis patent does not reflect the current technology environment. The current technology environment is development through recombination of technologies. In addition to, the speed of technological development is rapidly growing. So, qualitative analysis does not satisfy the analysis requirements of the times. This paper utilized KP(Knowledge Persistence)-based main path analysis and text mining methods to reflect the current technological environment. As a result, we found core patents, main technology development, and promising technologies for technological domain of the hydrogen fuel cell.

• Earthquakes and Structures
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• v.22 no.3
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• pp.245-261
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• 2022

Key questions to researchers interested in nonlinear analysis of skeletal structures are whether the distributed plasticity approach - albeit computationally demanding - is more reliable than the concentrated plasticity to adequately capture the extent and severity of the inelastic response, and whether force-based formulation is more efficient than displacement-based formulation without compromising accuracy. The present research focusing on performance-based seismic response of mid-span concrete bridges provides a pilot holistic investigation opting for some hands-on answers. OpenSees software is considered adopting different modeling techniques, viz. distributed plasticity (through either displacement-based or force-based elements) and concentrated plasticity via beam-with-hinges elements. The pros and cons of each are discussed based on nonlinear pushover analysis results, and fragility curves generated for various performance levels relying on incremental dynamic analyses under real earthquake records. Among prime conclusions, distributed plasticity modeling albeit inherently not relying on prior knowledge of plastic hinge length still somewhat depends on such information to ensure accurate results. For instance, displacement-based and force-based approaches secure optimal accuracy when dividing, for the former, the member into sub-elements, and satisfying, for the latter, a distance between any two consecutive integration points, close to the expected plastic hinge length. On the other hand, using beam-with-hinges elements is computationally more efficient relative to the distributed plasticity, yet with acceptable accuracy provided the user has prior reasonable estimate of the anticipated plastic hinge length. Furthermore, when intrusive performance levels (viz. life safety or collapse) are of concern, concentrated plasticity via beam-with-hinges ensures conservative predicted capacity of investigated bridge systems.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.519-529
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• 2022

Many consumers are opting for online booking over traditional booking systems. Customers can actively seek out information about hotels and lodging services, as well as book rooms, at any time and from any location. Customers also feel more supported when they interact with virtual assistants or professionals. Recognizing this issue, several hotels have focused on improving their websites by incorporating aspects that encourage customers to book directly through the hotel's website. The study's goal is to discover what factors impact people's decisions to book a hotel stay through the hotel's website. Therefore, hotel managers and owners can make decisions to improve the hotel website to attract residents to Can Tho City. The factors are website quality, affective commitment, social presence, and e-trust that affect customers' decision to book through the hotel website. The study uses quantitative methods to collect data from 180 residents living in Can Tho. Through data analysis on SPSS and Amos software, the research results show that three factors considered, namely website quality, affective commitment, and social presence, positively influence customers' booking decisions. This finding also suggests that e-trust is less critical to residents in Can Tho City, different from what the study had predicted.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.885-892
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• 2018

A series of revolutionary industrial changes took place from the 18th century of the First Industrial Revolution. The fourth industrial revolution is a new industrial revolution in which intelligence and information unite. Social, cultural, economic and educational systems are expected to emerge within the category of access and experience. In the course of intelligent mechanization, manpower and machinery need to be commandeered. Tools should be left to the machine and humans should look at essential issues. In the 4th Industrial Revolution, the paradigm of education should fundamentally change. Instead of routine technologies based on memorization, one should learn how to access and utilize. It needs to focus on areas of debate, cooperation, communication, sensibility, and artistry that robots and artificial intelligence can not afford. The fourth industrial revolution is the fusion of human beings and technology, the humanities and the technology.