• Korean Journal of Clinical Laboratory Science
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• v.36 no.2
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• pp.193-198
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• 2004

PET/CT combines the functional information from a positron emission tomography (PET) exam with the anatomical information from a computed tomography (CT) exam into one single exam. A CT scan uses a combination of x-rays and computers to give the radiologist a non-invasive way to see inside your body. One advantage of CT is its ability to rapidly acquire two-dimensional pictures of your anatomy. Using a computer these 2-D images can be presented in 3-D for in-depth clinical evaluation. A PET scan detects changes in the cellular function - how your cells are utilizing nutrients like sugar and oxygen. Since these functional changes take place before physical changes occur, PET can provide information that enables your physician to make an early diagnosis. The PET exam pinpoints metabolic activity in cells and the CT exam provides an anatomical reference. When these two scans are fused together, your physician can view metabolic changes in the proper anatomical context of your body. PET/CT offers significant advantages including more accurate localization of functional abnormalities, and the distinction of pathological from normal physiological uptake, and improvements in monitoring treatment. A PET/CT scan allows physicians to measure the body's abnormal molecular cell activity to detect cancer (such as breast cancer, lung cancer, colorectal cancer, lymphoma, melanoma and other skin cancers), brain disorders (such as Alzheimer's disease, Parkinson's disease, and epilepsy), and heart disease (such as coronary artery disease).

• Journal of Ship and Ocean Technology
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• v.4 no.2
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• pp.38-57
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• 2000

This paper deals with reliability analysis of specially orthotropic plates subjected to transverse lateral pressure loads by using Monte Carlo simulation method. The plates are simply supported around their all edges and have a low short span to plate depth ratio with rectangular plate shapes. Various levels of reliability analyses of the plates are performed within the context of First-Ply-Failure(FPF) analysis such as ply-/laminate-level reliability analyse, failure tree analysis and sensitivity analysis of basic design variables to estimated plate reliabilities. In performing all these levels of reliability analyses, the followings are considered within the Monte Carlo simulation method: (1) input parameters to the strengths of the plates such as applied transverse lateral pressure loads, elastic moduli, geometric including plate thickness and ultimate strength values of the plates are treated as basic design variables following a normal probability distribution; (2) the mechanical responses of the plates are calculated by using simplified higher-order shear deformation theory which can predict the mechanical responses of thick laminated plates accurately; and (3) the limit state equations are derived from polynomial failure criteria for composite materials such as maximum stress, maximum strain, Tsai-Hill, Tsai-Wu and Hoffman.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.70-86
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• 2015

Short crested waves play an important role for planning and design of harbours. In this context a numerical simulation is carried out to evaluate wave tranquility inside a real harbour located in east coast of India. The annual offshore wave climate proximity to harbour site is established using Wave Model (WAM) hindcast wave data. The deep water waves are transformed to harbour front using a Near Shore spectral Wave model (NSW). A directional analysis is carried out to determine the probable incident wave directions towards the harbour. Most critical threshold wave height and wave period is chosen for normal operating conditions using exceedence probability analysis. Irregular random waves from various directions are generated confirming to Pierson Moskowitz spectrum at 20m water depth. Wave incident into inner harbor through harbor entrance is performed using Boussinesq Wave model (BW). Wave disturbance experienced inside the harbour and at various berths are analysed. The paper discusses the progresses took place in short wave modeling and it demonstrates application of wave climate for the evaluation of harbor tranquility using various types of wave models.

• Journal of Digital Convergence
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• v.2 no.1
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• pp.93-112
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• 2004

A license under UCITA(Uniform Computer Information Transactions Act) which represents the first comprehensive uniform computer information licensing law is not fundamentally rooted in intellectual property law such as patent or copyright law. A license under UCITA is simply a commercial contract, dependent wholly on the parties' ability to enter into a normal, commercial contract, just as a contract of sale or lease is simply and wholly a commercial contract. However, intellectual property rights may be licensed in a contract subject to UCITA. UCITA may not be used to vary or extend informational rights that are intellectual property rights, and expressly recognizes preemption by copyright, patent, or other federal intellectual property law in Section 105(b). Like the law of sales and leases, in general, the right to contract is constrained by principles of unconscionability, good faith and fair dealing, UCITA has an additional restraint, an express power for a court to deny enforcement of a provision in a licensing contract that violates fundamental public policy. This public policy defense is unique in UCITA. An essential purpose of this defense is to give courts some latitude in reconciling commercial licensing law with the principles of intellectual property law. Most intellectual property law is federal, and UCITA expressly recognizes the preemptive effect of that federal law. But the public policy defense gives courts an additional power to consider intellectual property principles purely within the context commercial law.

• Journal of Information Technology Applications and Management
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• v.28 no.4
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• pp.59-78
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• 2021

Mobile Grocery Shopping (MGS) has become the New Normal as the COVID-19 pandemic has changed the way consumers shop. Drawing on the framework of Customer Journey Map (CJM), this study explores consumers' MGS by identifying specific stages of Customer Journey and comparing consumers' satisfaction between PC-based online and mobile shopping experiences at each stage throughout the journey. This study collected 562 responses from subjects who have mobile and PC-based grocery shopping experiences at the major domestic e-Commerce platforms. Independent t-test analysis showed that differences in satisfaction between mobile and online shopping experiences exist in 5 main stages and 16 sub-stages of CJM. The results of service and technological innovation mentioned in the actual industry report were seen as empirical results leading to continued use of MGS as well as customer satisfaction. The findings of this study contribute to the research stream on Customer Journey by adopting the structure of CJM and analyzing specific stages of the journey in the context of MGS. Managerial implications for mobile-based business practitioners are also discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3842-3861
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• 2019

In cut throat competition, organizations all over the world try to utilize the immense opportunities the Internet has to offer in almost all of their operations. Today, Social networking sites (SNSs) provide utilities designed to help companies to recruit right personnel. Considering the implication of social media for recruitment at infancy stage in Pakistan and lack of studies related to it, this study aims to investigate the role of different SNSs qualities (Easily navigate, Secure process, Eminence Proficiency, Candidate's Attraction and Network Expedition) in effective E-recruitment (EER). Data were collected through structured questionnaire from employees and managers of major telecom companies of Pakistan. Finally, the result of 355 returned and valid questionnaire with 55% response rate show that the relationship between SNSs qualities and EER is significant. Moreover, results also prove that EER is better than the tradition recruitment and a SNSs comparison show that Facebook is more effective than LinkedIn for EER. The results of this study will help Pakistani companies to develop a successful e-HRM and EER strategy in the current scenario.

• Smart Media Journal
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• v.7 no.4
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• pp.24-29
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• 2018

Text analysis technique for natural language processing in deep learning represents words in vector form through word embedding. In this paper, we propose a method of constructing a document vector and classifying it into spam and normal text message, using word embedding and deep learning method. Automatic spacing applied in the preprocessing process ensures that words with similar context are adjacently represented in vector space. Additionally, the intentional word formation errors with non-alphabetic or extraordinary characters are designed to avoid being blocked by spam message filter. Two embedding algorithms, CBOW and skip grams, are used to produce the sentence vector and the performance and the accuracy of deep learning based spam filter model are measured by comparing to those of SVM Light.

• Journal of Veterinary Clinics
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• v.37 no.6
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• pp.297-300
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• 2020

Lameness is a variation of normal gait in an animal, and it means that one or more limbs cannot be used correctly to allow the animal to walk. In the usual context, the incidence of hindlimb lameness in dogs is most likely the result of trauma, joint diseases, and/or congenital diseases. Generally speaking, the factors influencing hindlimb lameness include the animal's specific breed, size, weight, and whether it engages in frequent or strenuous activities. Many studies have investigated the incidence of lameness of large breed dogs, as compared to small breed dogs. Considering that many domestic dogs are small breeds, the lameness of small breed dogs with a high population in Korea was evaluated. The major causes of hindlimb lameness were found to be joint, musculoskeletal, and neurological abnormalities and the most were identified as joint diseases. Among the joint diseases, it was noted that a patellar luxation was the most common, of which the grade 3 medial patellar luxation was the highest rated type of joint disease noted.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.316-321
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• 2022

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly, infecting millions of people worldwide. On March 11, 2020, the World Health Organization declared coronavirus disease (COVID-19) a pandemic owing to the worldwide spread of SARS-CoV-2, which created an unprecedented burden on the global healthcare system. In this context, there are increasing concerns regarding co-infections with other respiratory viruses, such as the influenza virus. In this study, clinical data of patients infected with SARS-CoV-2 and other respiratory viruses were compared with patients infected with SARS-CoV-2 alone. The hematology and blood biochemistry results of 178 patients infected with SARS-CoV-2 , who were tested on admission, were retrospectively reviewed. In patients with SARS-CoV-2 and adenovirus co-infection, C-reactive protein levels were elevated on admission, whereas lactate dehydrogenase (LDH), prothrombin time, international normalized ratio, activated partial thromboplastin clotting time, and bilirubin values were all within the normal range. Moreover, patients with SARS-CoV-2 and human bocavirus co-infection had low LDH and high bilirubin levels on admission. These findings reveal the clinical features of respiratory virus and SARS-CoV-2 co-infections and support the development of appropriate approaches for treating patients with SARS-CoV-2 and other respiratory virus co-infections.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.19-27
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• 2023

In recent times, an exponential increase in Internet traffic has been observed as a result of advancing development of the Internet of Things, mobile networks with sensors, and communication functions within various devices. Further, the COVID-19 pandemic has inevitably led to an explosion of social network traffic. Within this context, considerable attention has been drawn to research on network traffic analysis based on machine learning. In this paper, we design and develop a new machine learning framework for network traffic analysis whereby normal and abnormal traffic is distinguished from one another. To achieve this, we combine together well-known machine learning algorithms and network traffic analysis techniques. Using one of the most widely used datasets KDD CUP'99 in the Weka and Apache Spark environments, we compare and investigate results obtained from time series type analysis of various aspects including malicious codes, feature extraction, data formalization, network traffic measurement tool implementation. Experimental analysis showed that while both the logistic regression and the support vector machine algorithm were excellent for performance evaluation, among these, the logistic regression algorithm performs better. The quantitative analysis results of our proposed machine learning framework show that this approach is reliable and practical, and the performance of the proposed system and another paper is compared and analyzed. In addition, we determined that the framework developed in the Apache Spark environment exhibits a much faster processing speed in the Spark environment than in Weka as there are more datasets used to create and classify machine learning models.