• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.120-130
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• 2021

The spinal cord or CSF surgery is a very complex process. It requires continuous pre and post-surgery evaluation to have a better ability to diagnose the disease. To detect automatically the suspected areas of tumors and symptoms of CSF leakage during the development of the tumor inside of the brain. We propose a new method based on using computer software that generates statistical results through data gathered during surgeries and operations. We performed statistical computation and data collection through the Google Source for the UK National Cancer Database. The purpose of this study is to address the above problems related to the accuracy of missing hybrid KNN values and finding the distance of tumor in terms of brain cancer or CSF images. This research aims to create a framework that can classify the damaged area of cancer or tumors using high-dimensional image segmentation and Laplace transformation method. A high-dimensional image segmentation method is implemented by software modelling techniques with measures the width, percentage, and size of cells within the brain, as well as enhance the efficiency of the hybrid KNN algorithm and Laplace transformation make it deal the non-zero values in terms of missing values form with the using of Frobenius Matrix for deal the space into non-zero values. Our proposed algorithm takes the longest values of KNN (K = 1-100), which is successfully demonstrated in a 4-dimensional modulation method that monitors the lighting field that can be used in the field of light emission. Conclusion: This approach dramatically improves the efficiency of hybrid KNN method and the detection of tumor region using 4-D segmentation method. The simulation results verified the performance of the proposed method is improved by 92% sensitivity of 60% specificity and 70.50% accuracy respectively.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.328-342
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• 2022

The Internet of Things (IoT) is a technology that offers lucrative services in various industries to facilitate human communities. Important information on people and their surroundings has been gathered to ensure the availability of these services. This data is vulnerable to cybersecurity since it is sent over the internet and kept in third-party databases. Implementation of data encryption is an integral approach for IoT device designers to protect IoT data. For a variety of reasons, IoT device designers have been unable to discover appropriate encryption to use. The static support provided by research and concerned organizations to assist designers in picking appropriate encryption costs a significant amount of time and effort. IoTES is a web app that uses machine language to address a lack of support from researchers and organizations, as ML has been shown to improve data-driven human decision-making. IoTES still has some weaknesses, which are highlighted in this research. To improve the support, these shortcomings must be addressed. This study proposes the "IoTES with Security" model by adding support for the security level provided by the encryption algorithm to the traditional IoTES model. We evaluated our technique for encryption algorithms with available security levels and compared the accuracy of our model with traditional IoTES. Our model improves IoTES by helping users make security-oriented decisions while choosing the appropriate algorithm for their IoT data.

• Wind and Structures
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• v.35 no.1
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• pp.21-34
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• 2022

Gust factor is an important parameter for the conversion between peak gust wind and mean wind speed used for the structural design and wind-related hazard mitigation. The gust factor of typhoon wind is observed to show a significant dispersion and some differences with large-scale weather systems, e.g., monsoons and extratropical cyclones. In this study, insitu measurement data captured by 13 meteorological towers during a strong typhoon Morakot are collected to investigate the statistical characteristics, height and wind speed dependency of the gust factor. Onshore off-sea and off-land winds are comparatively studied, respectively to characterize the underlying terrain effects on the gust factor. The theoretical method of peak factor based on Gaussian assumption is then introduced to compare the gust factor profiles observed in this study and given in some building codes and standards. The results show that the probability distributions of gust factor for both off-sea winds and off-land winds can be well described using the generalized extreme value (GEV) distribution model. Compared with the off-land winds, the off-sea gust factors are relatively smaller, and the probability distribution is more leptokurtic with longer tails. With the increase of height, especially for off-sea winds, the probability distributions of gust factor are more peaked and right-tailed. The scatters of gust factor decrease with the mean wind speed and height. AS/NZ's suggestions are nearly parallel with the measured gust factor profiles below 80m, while the fitting curve of off-sea data below 120m is more similar to AIJ, ASCE and EU.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.179-187
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• 2023

The outbreak of COVID-19 had affected almost every part of the world and caused disastrous results, the number of reported COVID-19 cases in past few months have reached to more than 29 million patients in the world globally. This pandemic has adversely affected all the activities of life, ranging from personal life to overall economic development. Due to the current situation, routinely turned to online resources, and people have relied on technology more than they have been before. Since cybercriminals are an opportunist and they utilized this entirely, by targeting the online services for all sectors of life. This fortnight online dependency of the community over the internet opened several easy doors for the cybercriminals. This causes exponential attacks over internet traffic during this epidemic situation. The current Covid-19 pandemic situation appeared at once, and no one was ready to prevail this. However, there is an urgent need to address the current problem in all means. . KSA is among one of the countries most affected by these CA and is a key victim for most cyber-crimes. Therefore, this paper will review the effects of COVID-19 on the cyber-world of KSA in various sectors. We will also shed light on the Saudi efforts to confront these attacks during COVID -19. As a contribution, we have provided a comprehensive framework for mitigating cybersecurity challenges.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.43-52
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• 2024

Medical imaginings assume a important part in the analysis of tumors and cerebrospinal fluid (CSF) leak. Magnetic resonance imaging (MRI) is an image segmentation technology, which shows an angular sectional perspective of the body which provides convenience to medical specialists to examine the patients. The images generated by MRI are detailed, which enable medical specialists to identify affected areas to help them diagnose disease. MRI imaging is usually a basic part of diagnostic and treatment. In this research, we propose new techniques using the 4D-MRI image segmentation process to detect the brain tumor in the skull. We identify the issues related to the quality of cerebrum disease images or CSF leakage (discover fluid inside the brain). The aim of this research is to construct a framework that can identify cancer-damaged areas to be isolated from non-tumor. We use 4D image light field segmentation, which is followed by MATLAB modeling techniques, and measure the size of brain-damaged cells deep inside CSF. Data is usually collected from the support vector machine (SVM) tool using MATLAB's included K-Nearest Neighbor (KNN) algorithm. We propose a 4D light field tool (LFT) modulation method that can be used for the light editing field application. Depending on the input of the user, an objective evaluation of each ray is evaluated using the KNN to maintain the 4D frequency (redundancy). These light fields' approaches can help increase the efficiency of device segmentation and light field composite pipeline editing, as they minimize boundary artefacts.

• Analytical Science and Technology
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• v.28 no.3
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• pp.246-254
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• 2015

From 2013 to 2014, volatile organic compounds (VOCs) were analyzed to determine biogenic volatile organic compounds (BVOCs) and anthropogenic volatile organic compounds (AVOCs) at eight sites in Mt. Mudeung and one site in downtown, by using a GC/Mass-ATD (automatic thermal desorber). The concentration of terpene noted as biogenic volatile organic compounds at Pungamjeong (PA), in a forest of Chamaecyparis obtusa, was 821 pptv, which was the highest among the eight sites. This value was followed by Wonhyogyegok (WH: 785 pptv), Norritzae (NZ, coniferous forest: 679 pptv), Dongjeokgol (DJ, mixed species forest: 513 pptv), Jangbuljae (JB, Abies koreana: 476 pptv), and Seinbongsamgerri (SS, pine trees: 464 pptv). 11~15 species of terpene was detected in the forest depending on the site. At PA in May, α-pinene showed the highest value, occupied 20% of terpene followed by coumarin, sabinene, phellandrene, myrcene, borneol, eucalyptol, β-pinene, cymene, δ-limonene, γ-terpinene, camphor, camphene, and mentol in the order. The mean concentrations of AVOCs were 0.74~2.52 ppbv in the forests and 3.14 ppbv in the downtown area. From May to July, the AVOCs ratios of the downtown to each forest were 1.9~4.0. Among 10 species of AVOCs, the sum of toluene and benzene was 2.34 ppbv and occupied 75%. In June, the ratios of toluene were 44.1% at DJ site and 53.1% at JW site (downtown). The BVOCs showed a positive correlation with the AVOCs at the forest sites (r = 0.328), which was statistically insignificant (p = 0.184).

• Microbiology and Biotechnology Letters
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• v.37 no.2
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• pp.140-146
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• 2009

Cyclosporin, an immunosuppressant, is a representative group of biologically active secondary metabolites produced by the fungus Tolypocladium inflatum. The amount and ratio of cyclosporin derivatives in the culture broth are an important factors for the production of cyclosporin A and the purification in the industrial process. Therefore, we studied the effect of amino acids and complex organic nitrogen sources using Tolypocladium inflatum mutants on the productivity of cyclosporin A and the ratio of cyclosporin derivatives. Overproducing mutant YHC-004 having seven times higher productivity than mother strain's could be obtained through the artificial mutation by UV irradiation. The concentration and kind of organic nitrogens and amino acids shows the profound effect on the productivity of cyclosporin A and ratio of cyclosporin derivatives. As a result, it was possible to raise the productivity and the ratio of cyclosporin A up to 3,430 mg/L and 93% respectively, but on the other hand the other cyclosporin derivatives decreased less than 2% in the culture broth.

• Journal of Veterinary Clinics
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• v.21 no.2
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• pp.102-108
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• 2004

Orf virus (ORFV), a member of genus Parapoxvirus (family-Poxviridae), a causative agent of contagious ecthyma in sheep and goat leading to a condition commonly known as vesicular dermatitis. Recently, twelve goats from Iksan in Jeonbuk province were observed with clinical signs like necrotic vesicular lesions around the mucosa of mouth, nasal cavity, eye, ear, teats, abdomen and groin. Based on these clinical symptoms, contagious ecthyma infection was suspected. The skin scrapping was collected from lesions for isolation of DNA and subsequent PCR amplification of ORFV specific 235 bp region of B2L gene. All of the samples were found positive by PCR analysis. Sequencing and further phylogenetic analysis of the PCR product revealed 100% identity to Japan isolate of ORFV (Okinawa, GenBank accession number AB080769), and showed 99.6% of similarity to New Zealand strain (NZ-2, GenBank accession number U06671). It was concluded that ORFV strain detected in the present study is homologous to Japan isolate and New Zealand strain. The PCR test based on amplification of B2L gene is a highly useful tools for rapid and specific diagnosis of contagious ecthyma.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.201-208
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• 2020

This study examined the anti-obesity effect of krill oil (KO) by regulating adipokines in a high-fat diet (HFD)-induced obese mouse model. The mice were fed a 60 kcal% HFD for 16 weeks, and KO was then administered at an oral dose of 100, 200, and 500 mg/kg/day for four weeks before the end of the experiment. The administration of KO at concentrations of 200 and 500 mg/kg/day decreased body weight gain significantly compared with the HFD-fed control group. In addition, the HFD-fed control group showed the abnormal release of adipokines by an increase in leptin and decrease in adiponectin, compared to the normal diet-fed normal group. On the other hand, KO (500 mg/kg/day)-administered group attenuated the abnormal release of adipokines by the down-regulation of leptin and the up-regulation of adiponectin. Therefore, KO could be a promising therapeutic agent for obesity by the regulation of adipokines.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.399-410
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• 2008

This paper suggests a new retrieval method using weighted vector sum to resolve a problem of traditional location-based retrieval method, nearest neighbor (NN) query, and NN query using direction. The proposed method filters out data with the radius, and then the remained retrieval area is filtered by a direction information compounded of a user's moving direction, a pre-fixed interesting direction, and a pre-fixed retrieval angle. The moving direction is computed from a vector or a weighted vector sum of several vectors using a weight to adopt several cases. The retrieval angle can be set from traditional $360^{\circ}$ to any degree you want. The retrieval data for this method can be a still and moving image recorded shooting location, and also several type of media like text, web, picture offering to customer with location of company or resort. The suggested method guarantees more accurate retrieval than traditional location-based retrieval methods because that the method selects data within the radius and then removes data of useless areas like passed areas or an area of different direction. Moreover, this method is more flexible and includes the direction based NN.