• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.1-14
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• 2024

While text-to-image models have made remarkable progress in image synthesis, certain models, particularly generative diffusion models, have exhibited a noticeable bias to- wards generating images related to the culture of some developing countries. This paper introduces an empirical investigation aimed at mitigating the bias of image generative model. We achieve this by incorporating symbols representing Saudi culture into a stable diffusion model using the Dreambooth technique. CLIP score metric is used to assess the outcomes in this study. This paper also explores the impact of varying parameters for instance the quantity of training images and the learning rate. The findings reveal a substantial reduction in bias-related concerns and propose an innovative metric for evaluating cultural relevance.

• IE interfaces
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• v.16 no.spc
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• pp.21-27
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• 2003

Objective of this paper is to develop the user mobility model(UMM) which is used for the performance analysis of location update and paging algorithm and at the same time, consider the user mobility pattern(UMP) in zone-based cellular networks. User mobility pattern shows correlation in space and time. UMM should consider these correlations of UMP. K-dimensional Markov chain is presented as a UMM considering them where the states of Markov chain are defined as the current location area(LA) and the consecutive LAs visited in the path. Also, a new two dimensional Markov chain composed of current LA and time interval is presented. Simulation results show that the appropriate size of K in the former UMM is two and the latter UMM reflects the characteristic of UMP well and so is a good model for the analytic method to solve the performance of location update and paging algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.199-208
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• 2022

The world health organization classified the emerging coronavirus (known as Covid-19) as a pandemic after confirming the extent of spread and scale. As a matter of fact, outbreaks of similar scale or even worse have been witnessed throughout history. Thus, the development of prevention strategies exists to protect against such calamaties. One of the widely proven measures that controls the spread of any contagious diseases is social distancing. As a result, this paper will demonstrate the concept of an application "Be Aware" on enabling the implementation of this preventive measure. In particular "Be aware" evaluates the extent of congestion in public places using current time data. The proposed project will use Global Positioning System (GPS), and Application Programming Interface (API), to ensure information accuracy, and the API use Crowdsourcing to collect Real-Time Data (RTD) from the selected places. One line

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.23-30
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• 2022

Glaucoma is a chronic neuropathy that affects the optic nerve which can lead to blindness. The detection and prediction of glaucoma become possible using deep neural networks. However, the detection performance relies on the availability of a large number of data. Therefore, we propose different frameworks, including a hybrid of a generative adversarial network and a convolutional neural network to automate and increase the performance of glaucoma detection. The proposed frameworks are evaluated using five public glaucoma datasets. The framework which uses a Deconvolutional Generative Adversarial Network (DCGAN) and a DenseNet pre-trained model achieves 99.6%, 99.08%, 99.4%, 98.69%, and 92.95% of classification accuracy on RIMONE, Drishti-GS, ACRIMA, ORIGA-light, and HRF datasets respectively. Based on the experimental results and evaluation, the proposed framework closely competes with the state-of-the-art methods using the five public glaucoma datasets without requiring any manually preprocessing step.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.319-323
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• 2022

Handwritten text recognition is one of the active research areas nowadays. The progress in this field differs in every language. For example, the progress in Arabic handwritten text recognition is still insignificant and needs more attentions and efforts. One of the most important fields in this is Arabic handwritten manuscript text recognition which focuses in extracting text from historical manuscripts. For eons, ancients used manuscripts to write everything. Nowadays, there are millions of manuscripts all around the world. There are two main challenges in dealing with these manuscripts. The first one is that they are at the risk of damage since they are written in primitive materials, the second challenge is due to the difference in writing styles, hence most people are unable to read these manuscripts easily. Therefore, we discuss in this study different papers that are related to this important research field.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.132-138
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• 2022

Due to the impacts of the current pandemic COVID-19 and the continuation of studying online. There is an urgent need for an effective and efficient education platform to help with the continuity of studying online. Therefore, the question bank system (QB) is introduced. The QB system is designed as a website to create a single platform used by faculty members in universities to generate questions and store them in a bank of questions. In addition to allowing them to add two types of questions, to help the lecturer create exams and present the results of the students to them. For the implementation, two languages were combined which are PHP and Python to generate questions by using Artificial Intelligence (AI). These questions are stored in a single database, and then these questions could be viewed and included in exams smoothly and without complexity. This paper aims to help the faculty members to reduce time and efforts by using the Question Bank System by using AI and Natural Language Processing (NLP) to extract and generate questions from given text. In addition to the tools used to create this function such as NLTK and TextBlob.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.84-92
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• 2021

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.214-224
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• 2023

Fraudulence, cheating, and deception can occur in the commercial real estate (CRE) industry, besides the difficulty in searching for and transferring properties while ensuring the operation is processed through an authoritative source in a trusted manner. Nowadays, real estate transactions use neutral third parties to sell land. Indeed, properties can be sold by the owners or third parties multiple times or without a proper deed. Moreover, third parties request a large amount of money to mediate between the seller and buyer. Methods: We propose a new framework that uses a private blockchain network and predefined BPMN instances to enable the fast and easy recording of deeds and their proprietary transfer management controlled by the government. The blockchain allows for multiple verifications of transactions by permitted parties called peers. It promotes transparency, privacy, trust, and commercial competition. Results: We demonstrated the easy adoption of blockchain for land registration and transfer. The paper presents a prototype of the implemented product that follows the proposed framework. Conclusion: The use of Blockchain-based solutions to resolve the current land registration and transfer issues is promising and will contribute to smart cities and digital governance.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.52-54
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• 2002

정보화 기술의 급속한 발전과 인터넷을 통한 세계적인 전자상거래 시장확대 및 B2B 비중의 증가 등 경제 패러다임이 변화하고 있다. 이러한 급변하는 시장환경과 B2B 거래 활성화에 따라 기업 간 비즈니스 프로세스 및 거래 문서의 표준화가 대두되었고, 이를 위해 XML을 이용한 인터넷 기반 글로벌 전자상거래 실현을 위한 지원 기술로서, ebXML이 국제 표준으로 등장하였다. 본 논문에서는 비즈니스 프로세스 모델링을 위한 UMM 모델링 방법론과 비즈니스 프로세스의 표준화를 위해 ebXML에서 제시하고 있는 워크시트를 이용하여 신발산업의 비즈니스 프로세스 표준화를 위한 모델링을 제안하였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1093-1099
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• 2003

본 논문에서는 기존의 화주/차주간 물류중개의 문제점들을 극복할 수 있는 보다 효율적인 인터넷 기반 물류중개 개념을 제안한다. 이러한 개념을 구체화하여 하나의 실제적인 비즈니스 모델을 정의하고 이를 토대로 필요한 정보시스템을 개발하기 위해서는 모델링 방법론을 활용한 비즈니스 프로세스 분석이 필수적이다. 본 연구에서는 최근 정자상거래 분야의 표준 모델링 방법으로 급부상하고 있는 UMM(UN/CEFACT Modeling Methodology)을 활용하여 화주/차주간 물류중개에 대한 비즈니스 프로세스 분석을 수행한다. UMM을 활용하여 이와 같은 분석을 수행해본 결과, UMM이 참여자간 협업이 중요시되는 전자상거래 분야의 비즈니스 및 정보시스템 모델링을 위한 효율적인 분석 도구로써 이용될 수 있음을 알 수 있었다.