• Journal of Korea Game Society
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• v.20 no.6
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• pp.13-22
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• 2020

RIO is a new network API for Windows that is designed to have high I/O performance through low overhead and latency. Using RIO, MMO game servers may have much performance benefits. In addition, HTM has better productivity and performance compared to existing synchronization methods, so adopting it may produce better performance, also. In this paper, we improved server performance by implementing a new MMO game server architecture optimized with RIO and HTM. The performance of the server was verified through a benchmark program, and the number of concurrent users increased by 19%.

• Atmosphere
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• v.31 no.1
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• pp.73-83
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• 2021

Numerical weather prediction (NWP) models play an essential role in predicting weather factors, but using them is challenging due to various factors. To overcome the difficulties of NWP models, deep learning models have been deployed in weather forecasting by several recent studies. This study adapts long short-term memory (LSTM), which demonstrates remarkable performance in time-series prediction. The combination of LSTM model input of meteorological features and activation functions have a significant impact on the performance therefore, the results from 5 combinations of input features and 4 activation functions are analyzed in 9 Automated Surface Observing System (ASOS) stations corresponding to cities/islands/mountains. The optimized LSTM model produces better performance within eight forecast hours than Local Data Assimilation and Prediction System (LDAPS) operated by Korean meteorological administration. Therefore, this study illustrates that this LSTM model can be usefully applied to very short-term weather forecasting, and further studies about CNN-LSTM model with 2-D spatial convolution neural network (CNN) coupled in LSTM are required for improvement.

• Journal of Korean Clinical Health Science
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• v.10 no.2
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• pp.1600-1606
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• 2022

Objective: This study was to compares and analyzes programs applied to improve cognitive function in patients with mild cognitive impairment and early dementia in the community to find out their effectiveness. Methods: In this study, 12 papers were finalized by searching for "elderly", "cognitive", "community", and "program" using the database of the Research Information System (RISS), National Assembly Library, and Korean Studies Information (KISS). Results: Programs for cognitive function were in the order of cognitive stimulation program, arts and crafts, and exercise program. In the program, rather than applying the cognitive stimulation program alone, the program was operated by combining leisure or exercise, music, art, and handicraft. The time was shown to be 30 minutes. The most frequently used evaluation tool was MMSE, followed by GDS and BBS. By cognitive domain, cognitive stimulation program and memory, satisfaction in psychology, and balance ability in exercise were evaluated the most. In the cognitive area, various cognitive stimulation areas were included, and in the exercise area, basic exercise, muscle strength exercise, joint exercise, and balance exercise were applied. Conclusion: Therefore, developing a program to improve cognitive function for mild cognitive impairment, it will be possible to prepare guidelines to establish and development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.394-395
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• 2022

Exergames are playing an important role in healthcare/rehabilitation. It has also been used to improve motivation among patients with reduced cognition. The purpose of this pilot study was to evaluate the feasibility of using augmented reality (AR) with game-based cognitive-motor training programs for executive function, restricted and repetitive behaviors (RRBs) in children with autism spectrum disorder. Sixteen children aged 6 -16 years were randomly allocated to the experimental group and control group. Outcome measures were performed before and after the intervention and included executive function, restricted and repetitive behavior. A satisfactory survey was conducted post-intervention. A statistically significant improvement was observed in working memory and cognitive flexibility in the experimental group (P<0.05). However, despite no statistical improvements in cognitive inhibition and four subscales of RRBs, promising changes were observed in all the subscales of the executive function and the behavioral outcomes. Parents appreciated the program and children enjoyed the interaction with the AR game-based training. The findings of this preliminary feasibility study showed that AR using Kinect v2 motion with a cognitive-motor game content can be used for children with autism. However, there is a need for conducting a large-scale study to evaluate his effectiveness on executive function and restricted and repetitive behaviors.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.49-56
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• 2023

Computer architecture serves as a link between application requirements and underlying technology capabilities such as technical, mathematical, medical, and business applications' computational and storage demands are constantly increasing. Machine learning these days grown and used in many fields and it performed better than traditional computing in applications that need to be implemented by using mathematical algorithms. A mathematical algorithm requires more extensive and quicker calculations, higher computer architecture specification, and takes longer execution time. Therefore, there is a need to improve the use of computer hardware such as CPU, memory, etc. optimization has a main role to reduce the execution time and improve the utilization of computer recourses. And for the importance of execution time in implementing machine learning supervised module linear regression, in this paper we focus on optimizing machine learning algorithms, for this purpose we write a (Diabetes prediction program) and applying on it a Practical Swarm Optimization (PSO) to reduce the execution time and improve the utilization of computer resources. Finally, a massive improvement in execution time were observed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3398-3415
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• 2023

Internet-of-Things (IoT) is an emerging technology that interconnects millions of small devices to enable communication between the devices. It is heavily deployed across small scale to large scale industries because of its wide range of applications. These devices are very capable of transferring data over the internet including critical data in few applications. Such data is exposed to various security threats and thereby raises privacy-related concerns. Even devices can be compromised by the attacker. Modern cryptographic algorithms running on traditional machines provide authentication, confidentiality, integrity, and non-repudiation in an easy manner. IoT devices have numerous constraints related to memory, storage, processors, operating systems and power. Researchers have proposed several hardware and software implementations for addressing security attacks in lightweight encryption mechanism. Several works have made on lightweight block ciphers for improving the confidentiality by means of providing security level against cryptanalysis techniques. With the advances in the cipher breaking techniques, it is important to increase the security level to much higher. This paper, focuses on securing the critical data that is being transmitted over the internet by PRESENT using key-based dynamic S-Box. Security analysis of the proposed algorithm against other lightweight block cipher shows a significant improvement against linear and differential attacks, biclique attack and avalanche effect. A novel key-based dynamic S-Box approach for PRESENT strongly withstands cryptanalytic attacks in the IoT Network.

• Journal of Life Science
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• v.34 no.7
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• pp.509-519
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• 2024

A previous study showed that krill oil improved recognition and memory through anti-oxidative effects in an amyloid β model, but the authors noted that further investigations are necessary of alterations to neurotransmitters' states and of serum lipid profile improvements related to serum lipid peroxidation. Accordingly, in this study, ICR mice were pre-treated intraperitoneally with scopolamine prior to induced neurotransmission impairment, and the effects of krill oil provision on their capabilities of cognition were tested by performing a passive avoidance test (PAT), water maze test (WMT), and novel object recognition test. Then, parameters including the acetylcholine (ACh) concentration, acetylcholinesterase activity (AChE), lipid peroxidation, serum lipid levels, and nerve cell proliferation were investigated. The results showed that krill oil improved the mice's abilities in recognition and memory as the times taken to complete the PAT and WMT were reduced compared to the mice in a comparison scopolamine-treated group. Krill oil produced an increased concentration of Ach, and this was accompanied by a decrease in AChE. As shown in a scopolamine-treated SH-SY5Y cell line, krill oil reduced the activity of AChE. Moreover, the suppression of lipid peroxidation-reflected in the finding that malondialdehyde was decreased with krill oil provision-is speculated to affect the recorded serum triglyceride and cholesterol decreases and LDL cholesterol increase. The intake of krill oil was also found to produce an improvement in brain-derived neurotrophic factor expression by stimulating the activation of cyclic AMP response element binding protein in the brain tissue. Overall, the current results imply that the provision of krill oil raises the cognition and memory by elevating neurotransmitters and by improving the serum lipid profile and nerve cell proliferation, which occur as lipid peroxidation is suppressed in the brain tissue.

• The Korean Journal of Food And Nutrition
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• v.29 no.3
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• pp.382-391
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• 2016

The purpose of this experiment was designed to investigate the effects of medicinal herbs (MH) extracts on dementia induced by trimethyltin chloride (TMT) in rats. Six-week-old male Sprague-Dawley rats were randomly divided into five groups; normal group (group 1), control group (group 2), MH extracts group (250, 500 mg/kg) (group 3, group 4) and positive control group (tacrine group, group 5). In the control group to induce dementia, a 2.5 mg/kg of TMT intraperitoneal injection was used for 14 days (1 per day) in the rats. In the MH extracts group 250 mg/kg and 500 mg/kg of MH extracts were medicated in an oral inoculation for 20 days (1 per day). After 30 minutes, a 2.5 mg/kg of TMT intraperitoneal injection, which causes dementia, was used for 14 days (1 per day). In the positive control group (Tacrine group) 10 mg/kg of Tacrine, the dementia treatment, was medicated in an oral inoculation. After 30 mintues, 1 mg/kg of TMT intraperitoneal injection, which causes dementia, was used for 14 days (1 per day). The present author observed the passive avoidance performance test, and memory ability test (Y maze test), the values of MDA, acetlycholinesterase (AchE) activity in the brain and antioxidant enzyme in serum. MH extracts significantly improved memory of AD model rats in the Y-maze test, and also significantly improved memory of AD model rats in the passive avoidance test. MH extracts significantly reduced AChE activity, and significantly increased the SOD level, but not catalase and MDA. From the results above, MH extracts is thought to be effective in the improvement of antioxidant enzymes and memory ability.

• Journal of IKEEE
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• v.26 no.3
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• pp.408-415
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• 2022

In this paper, we propose a 3D point cloud reconstruction technique from 2D images using efficient feature map extraction network. The originality of the method proposed in this paper is as follows. First, we use a new feature map extraction network that is about 27% efficient than existing techniques in terms of memory. The proposed network does not reduce the size to the middle of the deep learning network, so important information required for 3D point cloud reconstruction is not lost. We solved the memory increase problem caused by the non-reduced image size by reducing the number of channels and by efficiently configuring the deep learning network to be shallow. Second, by preserving the high-resolution features of the 2D image, the accuracy can be further improved than that of the conventional technique. The feature map extracted from the non-reduced image contains more detailed information than the existing method, which can further improve the reconstruction accuracy of the 3D point cloud. Third, we use a divergence loss that does not require shooting information. The fact that not only the 2D image but also the shooting angle is required for learning, the dataset must contain detailed information and it is a disadvantage that makes it difficult to construct the dataset. In this paper, the accuracy of the reconstruction of the 3D point cloud can be increased by increasing the diversity of information through randomness without additional shooting information. In order to objectively evaluate the performance of the proposed method, using the ShapeNet dataset and using the same method as in the comparative papers, the CD value of the method proposed in this paper is 5.87, the EMD value is 5.81, and the FLOPs value is 2.9G. It was calculated. On the other hand, the lower the CD and EMD values, the better the accuracy of the reconstructed 3D point cloud approaches the original. In addition, the lower the number of FLOPs, the less memory is required for the deep learning network. Therefore, the CD, EMD, and FLOPs performance evaluation results of the proposed method showed about 27% improvement in memory and 6.3% in terms of accuracy compared to the methods in other papers, demonstrating objective performance.

• Korean Journal of Biological Psychiatry
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• v.1 no.1
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• pp.109-116
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• 1994

It is not known whether negative symptoms and cognitive functions are dissociable or improvements in symptoms are reflected in improvements in cognitive functions in chronic schizophrenic patients. We administered clozapine to evaluate its effect on cognitive functions in chronic schizophrenic patients and to show correlations between improvement in psychotic symptoms and in cognitive functions. Neuropsychological tests such as Wisconsin Card Sorting Test, Digit Span test and Judgment of Line Orientation Test were applied to 16 chronic schizophrenic patients at baseline and after 9 months of treatment with clozapine. Using BPRS we assessed psychopathology before initiation of clozapine and at 9 months. Clozapine improved both positive and negative symptoms in chronic schizophrenic patients significantly. After nine months of clozapine treatment, significant improvements occurred in attention, short-term memory and visual perception ability. And interestingly we noted the trend of improvement in executive functions even though they were not statistical significant. Any significant correlations between the clinical improvement and change in congnitive functions were not observed. Long-term treatment with clozapine improved parts of cognitive functions of chronic schizophrenics. The results of the study suggest that deficits in simple cognitive functions as well as psychotic symptoms are improved after 3 month period of short-term treatment, but executive functions requiring more sophisticated processing of information could be improved after more than 9 months of long-term treatment.