• Imaging Science in Dentistry
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• v.52 no.2
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• pp.187-195
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• 2022

Purpose: This study developed a convolutional neural network (CNN) model to diagnose maxillary sinusitis on panoramic radiographs(PRs) and cone-beam computed tomographic (CBCT) images and evaluated its performance. Materials and Methods: A CNN model, which is an artificial intelligence method, was utilized. The model was trained and tested by applying 5-fold cross-validation to a dataset of 148 healthy and 148 inflamed sinus images. The CNN model was implemented using the PyTorch library of the Python programming language. A receiver operating characteristic curve was plotted, and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for both imaging techniques were calculated to evaluate the model. Results: The average accuracy, sensitivity, and specificity of the model in diagnosing sinusitis from PRs were 75.7%, 75.7%, and 75.7%, respectively. The accuracy, sensitivity, and specificity of the deep-learning system in diagnosing sinusitis from CBCT images were 99.7%, 100%, and 99.3%, respectively. Conclusion: The diagnostic performance of the CNN for maxillary sinusitis from PRs was moderately high, whereas it was clearly higher with CBCT images. Three-dimensional images are accepted as the "gold standard" for diagnosis; therefore, this was not an unexpected result. Based on these results, deep-learning systems could be used as an effective guide in assisting with diagnoses, especially for less experienced practitioners.

• Archives of Plastic Surgery
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• v.50 no.5
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• pp.468-477
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• 2023

Background This article describes the development of the Myanmar Articulation, Resonation, Nasal Emission, and Nasal Turbulence test for children with cleft lip and palate (CLP), and evaluation of its validity and reliability. Methods It was created by three Thai researchers and a Burmese research assistant based on Burmese phonology. The content validity was evaluated by six Burmese language experts. All test items were divided into three groups: high-pressure oral consonants, low-pressure oral consonants, and nasal consonants. Results All items (58-word and 32-phrase/sentence) gave an excellent level of the expert agreement (item-level content validity indexes = 1.00). The target items were illustrated as color pictures. Each picture was clearly drawn and easy to identify. As a pilot study of face validity, all pictures were administered to 10 typical-developing children. The actual testing was assessed by 10 CLP children, and the developed test was analyzed through consultation of the Burmese teachers and interpreters from a speech camp. Testing scores for a total including three groups of target items were shown acceptable for internal consistency reliability (ranged from 0.4 to 0.88). Conclusion The constructed test is valid in terms of its content.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.758-761
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• 2004

This paper proposes a design and implementation of multiplierless digital PID (Proportional-Integral-Derivative) controller using FPGA (Field Programmable Gate Array) for controlling the speed of DC motor in digital system. The multiplierless PID structure is based on Distributed Arithmetic (DA). The DA is an efficient way to compute an inner product using partial products, each can be obtained by using look-up table. The PID controller is designed using MATLAB program to generate a set of coefficients associated with a desired controller characteristics. The controller coefficients are then included in VHDL (Very high speed integrated circuit Hardware Description Language) that implements the PID controller onto FPGA. MATLAB program is used to activate the PID controller, calculate and plot the time response of the control system. In addition, the hardware implementation uses VHDL and synthesis using FLEX10K Altera FPGA as target technology and use MAX+plusII program for overall development. Results in design are shown the speed performance and used area of FPGA. Finally, the experimental results can be shown when compared with the simulation results from MATLAB.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.273-280
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• 2019

Many studies have shown that job performance and leadership are important in our society. In addition, to improve the quality of work or to improve the work efficiency is still a lot of challenges for each leader. In Vietnam, there are few specific studies on the impact of leadership styles on employee engagement such as: transformational leadership styles, business leadership styles and leadership styles. In the field of higher education, the fewer studies on these issues. A study is conducted to test the impact of leadership styles on the engagement of cadres, lecturers and staff at public universities in Vietnam. Using adjustment techniques, inspecting the scales and theoretical models representing the relationship among the influential factors. The research is based on a sample of 309 cadres, lecturers and staff currently working in universities in Vietnam and used Structural Equation Modeling (SEM) to test the relationships among the variables. The study results show that the scales of the variables: transformational leadership, transactional leadership, laissez faire leadership, job satisfaction and organizational engagement attain the validity and reliability in the research. The study results also show transformational leadership, transactional leadership and laissez faire leadership are directly and indirectly affected by job satisfaction and organizational commitment.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.245-256
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• 2022

During the COVID-19 pandemic, several studies focused on financial programs and SMEs' performance, but research on the relationship between non-financial programs, resilience, and SMEs' performance is still sparse. This study fills the gap by analyzing the role of local government in increasing SME resilience and performance by purchasing products (through civil servants) from SMEs and by facilitating online training to SMEs. This study also investigates the role of the local government in strengthening the relationship between resilience and SME performance. Data was collected using an online questionnaire distributed to SMEs in Malang Regency. As many as 410 questionnaires were received and eligible for statistical analysis using WarpPLS. The results show that resilience is positively and significantly related to the performance of SMEs. The local government programs have been proven to improve SME performance directly and indirectly through resilience. Local government programs are not proven to strengthen the relationship between resilience and the performance of SMEs, indicating that the role of government in developing countries such as Indonesia is more appropriate to be "rowing rather than steering" not "steering rather than rowing".

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.225-237
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• 2022

The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.925-928
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• 1993

In this paper the caracteristics of the fuzzy flip-flop which was proposed as a fuzzy sequential circuit is firstly mentioned. Secondly the circuit construction of typical fuzzy flip-flip circuits using VHDL (Very high speed integrated circuit Hardware Description Language) compiler and simulator is presented. Finally the possibility of the application of the fuzzy sequential circuit will be mentioned.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.109-113
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• 2007

Second language learners' variable degree of production difficulty according to the cluster type has previously been accounted for in terms of sonority distance between adjacent segments. As an alternative to this previous model, I propose a Phonetically Based Consonant Cluster Acquisition Model (PCCAM) in which consonant cluster markedness is defined based on the articulatory and perceptual factors associated with each consonant sequence. The validity of PCCAM has been tested through Korean speakers' production of English consonant clusters.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.124-131
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• 2000

In this study, the NEURAL NETWORK (hereinafter referred to as NN) was applied to control of the nonlinear factors for turning movement of the crawler vehicle and experiment was carried out using a small model of crawler vehicle in order to inspect an application of NN. Furthermore, CHAOS NEURAL NETWORK (hereinafter referred to as CNN) was also applied to this control so as to compare with conventional NN. CNN is especially effective for plane in many variables with local minimum which conventional NN is apt to fall into, and it is relatively useful to nonlinear factors. Experiment of turning on the slope of crawler vehicle was performed in order to estimate an adaptability of nonlinear problems by NN and CNN. The inclination angles of the road surface which the vehicles travel on, were respectively 4deg, 8deg, 12deg. These field conditions were selected by the object for changing nonlinear magnitude in turning phenomenon of vehicle. Learning of NN and CNN was carried out by referring to positioning data obtained from measurement at every 15deg in turning. After learning, the sampling data at every 15deg were interpolated based on the constructed learning system of NN and CNN. Learning and simulation programs of NN and CNN were made by C language ("Association of research for algorithm of calculating machine (1992)"). As a result, conventional NN and CNN were available for interpolation of sampling data. Moreover, when nonlinear intensity is not so large under the field condition of small slope, interpolation performance of CNN was a little not so better than NN. However, when nonlinear intensity is large under the field condition of large slope, interpolation performance of CNN was relatively better than NN.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2749-2752
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• 2012

Background: Breaking bad news to cancer patients is a delicate and challenging task for most doctors. Better understanding of patients' preferences in breaking bad news can guide doctors in performing this task. Objectives: This study aimed to describe the preferences of Malaysian cancer patients regarding the communication of bad news. Methodology: This was a cross-sectional study conducted in the Oncology clinic of a tertiary teaching hospital. Two hundred adult cancer patients were recruited via purposive quota sampling. They were required to complete the Malay language version of the Measure of Patients' Preferences (MPP-BM) with minimal researcher assistance. Their responses were analysed using descriptive statistics. Association between demographic characteristics and domain scores were tested using non-parametric statistical tests. Results: Nine items were rated by the patients as essential: "Doctor is honest about the severity of my condition", "Doctor describing my treatment options in detail", "Doctor telling me best treatment options", Doctor letting me know all of the different treatment options", "Doctor being up to date on research on my type of cancer", "Doctor telling me news directly", "Being given detailed info about results of medical tests", "Being told in person", and "Having doctor offer hope about my condition". All these items had median scores of 5/5 (IQR:4-5). The median scores for the three domains were: "Content and Facilitation" 74/85, "Emotional Support" 23/30 and "Structural and Informational Support" 31/40. Ethnicity was found to be significantly associated with scores for "Content and Facilitation" and "Emotional Support". Educational status was significantly associated with scores for "Structural and Informational Support". Conclusion: Malaysian cancer patients appreciate the ability of the doctor to provide adequate information using good communication skills during the process of breaking bad news. Provision of emotional support, structural support and informational support were also highly appreciated.