• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.211-218
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• 2021

A recent spread of personal mobility devices such as electric kickboards has brought about a rapid increase in accident cases. Such vehicles are susceptible to falling accidents due to their low dynamic stability and lack of outer protection chassis. This paper presents the development of an automatic emergency braking system and a safe starting system as driving assistance devices for electric kickboards. The braking system employed artificial intelligence to detect nearby threaening objects. The starting system was developed to disable powder to the motor until when the driver's boarding is confirmed. This study is meaningful in that it proposes the convergence technology of advanced driver assistance systems specialized for personal mobility devices.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.679-686
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• 2022

In this paper, we implemented an algae removal device that recognizes and removes algae existing in water using Raspberry Pi camera and DO (Dissolved Oxygen) sensor. The Raspberry Pi board recognizes the color of green algae by converting the RGB values obtained from the camera into HSV. Through this, the location of the algae is identified and when the amount of dissolved oxygen's decrease at the location is more than the reference value using the DO sensor, the algae removal device is driven to spray the algae removal solution. Raspberry Pi's camera uses OpenCV, and the motor movement is controlled according to the output value of the DO sensor and the result of the camera's green algae recognition. Algae recognition and spraying of algae removal solution were implemented through Arduino and Raspberry Pi, and the feasibility of the proposed portable algae removal device was verified through experiments.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.157-162
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• 2022

Cerebral palsy is one of the most serious forms of disorders of the psychophysical development of children, which manifests itself in disturbances of motor functions, which are often combined with speech disorders, other complications of the formation of higher mental functions, and often with a decrease in intelligence. The article will discuss the speech disorder in children with cerebral palsy. Emphasis is placed on some important aspects, which should bear in mind, investigating the problem of specifics of speech development of children with cerebral palsy. In particular at the heart of speech disorders in the cerebral palsy is not only damage to certain structures of the brain, but also the later formation or underdevelopment of those parts of the cerebral cortex, which are of major importance in linguistic and mental activity. This is an ontogenetically young region of the cerebral cortex, which is most rapidly developing after birth (premotor, frontal, temmono-temporal). It is important to take into account, that children with cerebral palsy have disturbances of phonemic perception. Often, children do not distinguish between hearing sounds, cannot repeat component rows, allocate sounds in words. At dysarthria, there are violations of pronunciation of vowel and consonant sounds, tempo of speech, modulation of voice, breathing, phonation, as well as asynchronous breathing, alignment and articulation. As a result, we identified the main features and specifics of the speech development of children with cerebral palsy and described the conditions necessary for the full development of language. Language disturbances in children's cerebral palsy depend on the localization and severity of brain damage. Great importance in the mechanism of speech disorders has a pathology that limits the ability of movement and knowledge of the world.

• Journal of IKEEE
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• v.27 no.4
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• pp.518-523
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• 2023

The diagnosis of Inter Turn Short Circuits (ITSC) in induction motors is critical due to the escalating severity of faults resulting from even minor disruptions in the stator windings. However, diagnosing ITSC presents significant challenges due to similarities in noise and losses shared with 3-phase induction motors. Although artificial intelligence techniques have been explored for efficient diagnosis, practical applications heavily rely on model-based methods, necessitating further research to enhance diagnostic performance. This study proposed a diagnostic method applied the Clarke Transformation approach, focusing solely on current components while disregarding changes in rotating flux. Experimental results conducted over a 30-minute period, encompassing both normal and ITSC conditions, demonstrate the effectiveness of the proposed approach, with FAR(False Accept Rates) of 0.2% for normal-to-ITSC FRR(False Rejection Rates) and 0.26% for ITSC-to-normal FRR. These findings underscore the efficacy of the proposed approach.

• Korean Security Journal
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• no.10
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• pp.293-322
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• 2005

The culpability of a person, as determined by due process of law, for any of his actions that are defined as criminal. Determination of such responsibility is a legal function, not a psychiatric one, although a psychiatrist may be called upon to present evidence to the court in order to aid the judge or jury in reaching a decision as to responsibility. Determination of responsibility varies with the laws of the state in which the accused is being tried, but in general all states base their laws on three famous judicial decisions concerning criminal responsibility. 1. the M'Naghten(McNaughton) rule(a. to establish such a defense the accused, at the time the act was committed, must be shown to have been laboring under such defect of reason as not to know the nature and quality of the act he was doing, b. if he did know it, he did or know that what he was doing was wrong). 2. the irresistible impulse test. 3. the Durham decision. Under the Durham test, however, the psychiatrist may give any relevant testmony concerning the mental illness at issue. The psychological and behavioral appearance of a person, in clinical psychiatry this term is commonly used to refer to the results of the mental examination of a patient. The written report of the mental status usually contains specific references to the following areas: I. Attitude and General Behavior (1)General health and appearance. (2)General habits of dress. (3)Personal habits. (4)General mood. (5)Use of leisure time. (6)Degree of sociability. (7)Speech. II. Attitude and Behavior during interview (1)Co-operativeness. (2)Poise. (3)Facial expression. (4)Motor activity. (5)Mental activity. (6)Emotional reactions. (7)Trend of thought. III. Sensorium, mental grasp, and capacity (1)Orientation. (2)Memory and retention. (3)Estimate of intelligence. (4)Abstraction ability. (5)Tests of absurdity, interpretation of proverbs. (6)Judgment.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• The Journal of Pediatrics of Korean Medicine
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• v.15 no.1
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• pp.77-104
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• 2001

The effects of the oriental herbal medicine Saenghyetang(SHT, 生慧湯), which consists of Rehmanniae Radix (熟地黃 九蒸: was made by 9th steam) 40g, Corni Fructus(山茱黃) 16g, Polygalae Radix(遠志) 8g, Zizyphi Spinosae Semen(酸棗仁) 2g, Biotae Semen(柏子仁 去油: oil ingredient was removed) 20g, Poria Cocos(茯笭) 12g, Ginseng Radix(人蔘) 12g, Acori Graminei Rhizoma(石菖蒲) 2g, Sinapis Semen(白芥子) 8g, on learning ability and memory were investigated. Hot water extract(HWE) and ethanol extract(EE) from SHT were used for the studies. Learning ability and memory are related to modifications of synaptic strength among neurons that interactive. Enhanced synaptic coincidence detection leads to improved learning ability and memory. If the NMDA receptor, a synaptic coincidence detector, acts as a graded switch for memory formations, enhanced signal detection by NMDA receptors should enhance learning ability and memory. It was shown that NR2B was increased in the forebrains of oriental medicine-administrated mice, leading to enhanced activation of NMDA receptors and facilitating synaptic potentiation in response to stimulation at 10-100 Hz. These HWE-SHT treated mice exhibited that superior ability in learning and memory when performing various behavioral tasks, showing that NR2B is enhanced by HWE-SHT treatment and also is critical in gating the age-dependent threshold for plasticity and memory formation. NMDA receptor-dependent modifications, which were mediated in part by HWE administration, of synaptic efficacy, therefore, represent a mechanism for associative learning ability and memory. Results suggest that oriental medical enhancement of NR2B contributes to increase intelligence and memory in mammals On the other hand, to examine the effects of EE-SHT on the learning ability and memory in experimental mice, EE-SHT was tested on passive and active avoidance responses. The EE-SHT ameliorated the memory retrieval deficit induced by ethanol in mice, but not other memory impairments. EE-SHT(10, 20mg/100 g, p.o.) did not affect the passive avoidance responses of normal mice in the step through and step down tests, the conditioned and unconditioned avoidance responses of normal mice in the shuttle box, lever press performance tests and the ambulatory activity of normal mice in a normal condition. However, EE-SHT at 20 mg/kg significantly decrease the spontaneous motor activity during the shuttle box test, and also to extend the sleeping time induced by pentobarbital in mice. These results suggest that SHT has an ameliorating effect on memory retrieval impairments and a weak tranquilizing action.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.97-105
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• 2023

Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.