• ETRI Journal
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• v.44 no.4
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• pp.613-623
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• 2022

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.295-311
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• 2023

Cloud computing has evolved significantly, intending to provide users with fast, dependable, and low-cost services. With its development, malicious users have become increasingly capable of attacking both its internal and external security. To ensure the security of cloud services, encryption, authorization, firewalls, and intrusion detection systems have been employed. However, these single monitoring agents, are complex, time-consuming, and they do not detect ransomware and zero-day vulnerabilities on their own. An innovative Record and Replay-based hybrid Honeynet (R2NET) system has been developed to address this issue. Combining honeynet with Record and Replay (RR) technology, the system allows fine-grained analysis by delaying time-consuming analysis to the replay step. In addition, a machine learning algorithm is utilized to cluster the logs of attackers and store them in a database. So, the accessing time for analyzing the attack may be reduced which in turn increases the efficiency of the proposed framework. The R2NET framework is compared with existing methods such as EEHH net, HoneyDoc, Honeynet system, and AHDS. The proposed system achieves 7.60%, 9.78%%, 18.47%, and 31.52% more accuracy than EEHH net, HoneyDoc, Honeynet system, and AHDS methods.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• Archives of Plastic Surgery
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• v.51 no.2
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• pp.196-201
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• 2024

Nevus lipomatosus superficialis (NLS) is a hamartoma of adipose tissue, rarely reported in the past 100 years. We treated one case, and we conducted a systematic review of the literature. A 41-year-old man presented with a cutaneous multinodular lesion in the posterior region near the right auricle. The lesion was excised and examined histopathologically. To review the literature, we searched PubMed with the keyword "NLS." The search was limited to articles written in English and whose full text was available. We analyzed the following data: year of report, nation of corresponding author, sex of patient, age at onset, duration of disease, location of lesion, type of lesion, associated symptoms, pathological findings, and treatment. Of 158 relevant articles in PubMed, 112 fulfilled our inclusion criteria; these referred to a total of 149 cases (cases with insufficient clinical information were excluded). In rare cases, the diagnosis of NLS was confirmed when the lesion coexisted with sebaceous trichofolliculoma and Demodex infestation. Clinical awareness for NLS has increased recently. NLS is an indolent and asymptomatic benign neoplasm that may exhibit malignant behavior in terms of huge lesion size and specific anatomical location. Early detection and curative treatment should be promoted.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.147-155
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• 2024

Purpose: The purpose of this study is to analyze the danger signs of buildings and present a plan to install a building monitoring system to develop measurement technology for small private buildings in the blind spot of disaster safety. Method: The cause of building risk behavior, components of monitoring measuring equipment, location of measuring equipment installation, management plan, etc. are presented. Result: Measuring instruments essentially include acceleration sensors, tilt sensors, gyro sensors, GPS, etc. The measuring instrument should take into account the height and cross-sectional area of the pillar. Conclusion: The results of this study can strengthen disaster safety capabilities in preparation for disasters arising from building collapses that may occur in small private buildings.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.1-6
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• 2024

Recently, artificial neural networks have been playing a crucial role and advancing across various fields. Artificial neural networks are typically categorized into feedforward neural networks and recurrent neural networks. However, feedforward neural networks are primarily used for processing static spatial patterns such as image recognition and object detection. They are not suitable for handling temporal signals. Recurrent neural networks, on the other hand, face the challenges of complex training procedures and requiring significant computational power. In this paper, we propose memristors suitable for an advanced form of recurrent neural networks called reservoir computing systems, utilizing a mask processor. Using the characteristic equations of Ti/TiOx/TaOy/Pt, Pt/TiOx/Pt, and Ag/ZnO-NW/Pt memristors, we generated current-voltage curves to verify their memristive behavior through the confirmation of hysteresis. Subsequently, we trained and inferred reservoir computing systems using these memristors with the NIST TI-46 database. Among these systems, the accuracy of the reservoir computing system based on Ti/TiOx/TaOy/Pt memristors reached 99%, confirming the Ti/TiOx/TaOy/Pt memristor structure's suitability for inferring speech recognition tasks.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.2
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• pp.267-274
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• 2017

Objective: The objective of this study was to investigate the effect of 20-day litter weight on behavior and heart rate variability (HRV) of piglets under stress. Methods: Forty four original litters were categorized as high litter weight (HW) litters (n = 22) and low litter weight (LW) litters (n = 22) by 20-day litter weight. From each original HW litter, three males and three females were randomly selected after weaning and the 12 piglets from two original litters with similar age of days were regrouped into one new high litter weight (NHW) litter (11 NHW litters in total). The original LW litters were treated with a same program, so that there were 11 new low litter weight (NLW) litters as well. The latencies to first fighting, fighting frequencies and duration within three hours were recorded after regrouping and the lesions on body surface within 48 hours were scored. Besides, HR (heart rate, bpm, beats per minute) and activity count (ACT), time domain indexes and frequency domain indexes of the piglets were measured in an isolation trial to analyze the discrepancy in coping with stress between the original HW and LW litters. Results: The results exhibited that piglets from the HW litters launched fighting sooner and got statistically higher skin lesion score than those from the LW litters (p = 0.03 and 0.02, respectively). Regarding the HRV detection, compared with the HW litters, the LW litters exhibited a lower mean HR (p<0.05). In the isolation test, a highly significant higher ACT value was observed between the HW litters, compared to the LW litters (p<0.01). Significant differences were observed in standard deviation of R-R intervals, standard deviation of all normal to normal intervals, and most frequency-domain indicators: very low-frequency, low-frequency, and high frequency between the HW and LW litters as well. The difference in LF:HF was not significant (p = 0.779). Conclusion: This study suggests that compared with litters of low 20-day litter weights, litters with higher 20-day litter weight take more positive strategies to cope with stress and have stronger HRV regulation capacity; HW litters demonstrate better anti-stress and adaptation capacity in the case of regrouping and isolation.

• Journal of agricultural medicine and community health
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• v.34 no.1
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• pp.135-142
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• 2009

Objectives: This study was performed to investigate the changes in the prevalence and its related factors of the Clonorchis sinensis(C.S.) in the inhabitants at Goksung-Gun along Sum-Jin river after C.S. control intervention. Methods: The subjects were 416 among 699 in the 8 same villages selected by stratified cluster sampling in 1999. The formalin-esther sedimentaion technic was used for the C.S. egg detection and the questionnare for the related factors. The study was carried on from February, 2005 to March, 2005. Results: The prevalence of C.S. decreased significantly from 19.0% in 1999 to 11.3% in 2005. The signicicant factors in 1999 such as sex, age, area, raw fish eating habit and drink habit were not significant statistically. On the other hand factors such as the awareness of C.S. and the health behavior were changed significantly(p=0.034, p=0.021). Conclusions: These results suggest that C.S. prevalence became lower than previous study five years ago. But its control intervention should be extened to the general population regardless of sex, age, area, raw fish eating habits, drink habit and we need to make an effort to improve the awareness and the health behavior of C.S..

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.683-690
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• 2021

The ventilation system of the engine room of a ship is generally installed to supply the combustion air necessary for the internal combustion engine and to remove the heat source generated in the engine room, and it must satisfy the international standard (ISO 8861) for the design conditions and calculation standards for the ventilation of the ship engine room. The response delay of the ventilation system including the fire detector is affected by the airflow formed inside the area and the location of the fire detector. In this study, to improve the initial fire detection response speed of a fire detector installed on a fishing vessel and to maintain the sensitivity of the installed detector, the smoke behavior was simulated using the air flow field inside the engine room, the amount of combustion air in the internal combustion engine, and the internal pressure of the engine room as variables. Analysis of the simulation results showed that reducing the flow rate in the air flow field and increasing the vortex by reducing the internal pressure of the engine room and installing a smoke curtain would accelerate the rise of the ceiling of the smoke component and improve the smoke detector response speed and ventilation system.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.47-60
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• 2018

Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.