• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.787-799
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• 2023

As IoT devices are widely used at home, IoT automation system that is integrate IoT devices for users' demand are gaining populrity. There is automation rule in IoT automation system that is collecting event and command action. But attacker delay the packet and make time that real state is inconsistent with state recongnized by the system. During the time, the system does not work correctly by predefined automation rule. There is proposed some detection method for delay attack, they have limitations for application to IoT systems that are sensitive to traffic volume and battery consumption. This paper proposes a practical packet delay attack detection technique that can be applied to IoT systems. The proposal scheme in this paper can recognize that, for example, when a sensor transmits an message, an broadcast packet notifying the transmission of a message is sent to the Server recognized that event has occurred. For evaluation purposes, an IoT system implemented using Raspberry Pi was configured, and it was demonstrated that the system can detect packet delay attacks within an average of 2.2 sec. The experimental results showed a power consumption Overhead of an average of 2.5 mA per second and a traffic Overhead of 15%. We demonstrate that our method can detect delay attack efficiently compared to preciously proposed method.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.2
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• pp.24-34
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• 2023

Objective : This study sought to investigate the effects of a sensory integration intervention focusing on vestibular and proprioceptive on the spatial relations and visual-motor coordination of children with developmental disorders. Methods : Three children with developmental disabilities aged 5 to 6 years were the subjects of this study, and the ABA' design, which is one of the single subject research designs. A total of 18 sessions were conducted over a six-week period-that is, three 30-minute sessions per week. During the three baseline sessions, the children's spatial relations and visual-motor coordination were evaluated prior to the intervention. During the 12 sessions conducted in the intervention period, a vestibular and proprioception sensory integration intervention was performed, while in the final three sessions, the children's spatial relations and visual-motor coordination were again evaluated (without any further intervention Children were measured and evaluated every session after intervention using a computer cognitive rehabilitation program (CoTras-C). Moreover, the Kaufman Assessment Battery for Children and the Korean-Development Test of Visual Perception-2 were used as evaluation tools to verify the effectiveness of the intervention. Results : There were significant differences in the spatial relations and visual-motor coordination scores of the children with developmental disorders before and after the vestibular and proprioceptive sensory integration intervention. More specifically, after the intervention, all three children showed statistically significant improvements. Conclusion : The applied vestibular and proprioceptive sensory integration therapy had a significant impact on the spatial relations and visual-motor coordination of the three children with developmental disorders.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.41-52
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• 2023

The purpose of this study was to determine the effects of resilience on information processing. Thirty-nine male high school students were randomly selected and assigned to one of the three experimental groups: (1) high group (n = 13), (2) middle group (n = 13) and low group (n = 13) according to their resilience scale (KRQ-53) scores. The tasks were simple reaction time, choice reaction time-1, and choice reaction time -2. Electroencephalogram (EEG) was measured at Fp1, Fp2, F3, F4, Fz, Cz and Pz. A 3 × 8 × 4 (groups × areas × times) ANOVA with repeated measures on the last factor was calculated to determine resilience effects on EEG. P300 was analyzed using a 3 × 3 × 8 (groups × tasks × areas) ANOVA. The results showed that the theta waves of the middle group were higher than those of the high and low groups. Second, as a result of analyzing alpha waves, the high group demonstrated higher alpha waves than the middle and low groups. Third, the mid-beta waves of the middle and low groups were higher than those of the high group. Lastly, the result of this study showed that the P300 amplitude of the middle group was higher than that of the high and low groups. These results indicated that the middle group processed cognitive information more efficiently than the other two groups. The findings of this study demonstrated that cognitive information processing ability varies depending on the degree of resilience.

• The Journal of the Acoustical Society of Korea
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• v.26 no.1
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• pp.25-31
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• 2007

This paper describes an attempt to prevent the external acoustic noise from being misrecognized as the speech recognition target. For this, in the speech activity detection process for the speech recognition, it confirmed besides the acoustic energy to the lip movement image signal of a speaker. First of all, the successive images are obtained through the image camera for PC. The lip movement whether or not is discriminated. And the lip movement image signal data is stored in the shared memory and shares with the recognition process. In the meantime, in the speech activity detection Process which is the preprocess phase of the speech recognition. by conforming data stored in the shared memory the acoustic energy whether or not by the speech of a speaker is verified. The speech recognition processor and the image processor were connected and was experimented successfully. Then, it confirmed to be normal progression to the output of the speech recognition result if faced the image camera and spoke. On the other hand. it confirmed not to output of the speech recognition result if did not face the image camera and spoke. That is, if the lip movement image is not identified although the acoustic energy is inputted. it regards as the acoustic noise.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.159-165
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• 2007

In this paper, we propose a new pre-selection of candidate units that is suitable for the unit selection based Japanese TTS system. General pre-selection method performed by calculating a context-dependent cost within IP (Intonation Phrase). Different from other languages, however. Japanese has an accent represented as the height of a relative pitch, and several words form a single accentual phrase. Also. the prosody in Japanese changes in accentual phrase units. By reflecting such prosodic change in pre-selection. the qualify of synthesized speech can be improved. Furthermore, by calculating a context-dependent cost within accentual phrase, synthesis speed can be improved than calculating within intonation phrase. The proposed method defines AP. analyzes AP in context and performs pre-selection using accentual phrase matching which calculates CCL (connected context length) of the Phoneme's candidates that should be synthesized in each accentual phrase. The baseline system used in the proposed method is VoiceText, which is a synthesizer of Voiceware. Evaluations were made on perceptual error (intonation error, concatenation mismatch error) and synthesis time. Experimental result showed that the proposed method improved the qualify of synthesized speech. as well as shortened the synthesis time.

• Knowledge Management Research
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• v.24 no.4
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• pp.87-102
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• 2023

Awe is recognized as an emotion linked to enhancing openness to new experiences and broadening one's cognitive perspective through the acquisition of new knowledge. This research aimed to investigate awe's impact on consumer behavior in advertising, using a 2 (emotion: awe/control) × 2 (product type: innovative/non-innovative) experimental design with 118 undergraduate students in Seoul, Korea. Findings revealed that awe-inducing advertising significantly increases product preference and positive technology readiness, particularly for innovative products compared to non-innovative ones or when awe is not elicited. The analysis of moderated mediation showed that positive technology readiness plays a mediating role in the relationship between awe induction and product preference. Notably, in the case of innovative products, awe-inducing advertising heightens positive technology readiness, subsequently increasing consumer preference for these products. These results reinforce existing literature on awe's positive effects, demonstrating its role in augmenting consumers' favorable attitudes toward innovative products. The study offers valuable insights for marketing strategies of companies promoting innovative products or services, highlighting the effectiveness of awe-inducing emotional appeals in shaping consumer attitudes towards innovation.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.

• Knowledge Management Research
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• v.25 no.2
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• pp.49-68
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• 2024

Increasing concerns regarding personal data privacy have complicated the acquisition of customer data through online marketing. This study investigates factors influencing customers' willingness to disclose information via a generative AI-based chatbot. Drawing on privacy calculus theory and regulatory focus theory, we explore how customer regulatory focus and familiarity with the generative AI-based chatbot shape disclosure intentions. Our study, involving 473 participants, reveals that low familiarity with the chatbot leads individuals with a prevention focus to perceive higher privacy risks and lower perceived usefulness compared to those with a promotion focus. However, with high familiarity, these differences diminish. Moreover, individuals with a promotion focus show a greater inclination to disclose information when familiarity with the generative AI-based chatbot is low, whereas this regulatory focus does not significantly impact disclosure intentions when familiarity is high. Perceived privacy risks mediate these relationships, underscoring the importance of understanding familiarity with the generative AI-based chatbot in facilitating personal information disclosure.

• Information Systems Review
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• v.25 no.2
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• pp.205-227
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• 2023

Recently, Virtual Human(VH) has begun to appear in various media, not only on social media, but also in advertisements, music sources, and dramas. Virtual human has become a primary marketing tool for companies, but there also exist concerns when the companies do not disclose the identities of virtual humans. Accordingly, it is necessary to examine users' responses toward content that features virtual humans. This study aimed to examine how the exposure of virtual humans in the content affects users' perceptions. Therefore, the study defined the concept of 'VH Disclosure(VHD)', referring to the exposure of the virtual human's identity, and explored the impact of VH disclosure on attitude toward the ad (Hedonism, Utilitarianism, and Interestingness) and source credibility (Trustworthiness and Expertise). The study conducted an experimental survey with 302 respondents. Regardless of when the ad featured a VH or a human, the results showed that there was no significant difference between users' attitudes and source credibility. The results revealed that it was more effective to disclose the VH in social media feeds than directly reveal the VH's identity in the content. Therefore, this study utilizes a new concept of 'VH Disclosure(VHD)' to enhance the understanding of VH and contributes to establishing marketing strategies optimized for consumers in the creation of virtual human-related content.

• Journal of Platform Technology
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• v.12 no.2
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• pp.34-44
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• 2024

This paper proposes a dynamic clock supply control algorithm and a system load power stabilization algorithm that minimizes the power consumption of the sensing system, which accounts for the largest percentage of power consumption in mobile devices, to extend the usage time of the rechargeable battery mounted on the mobile device. The dynamic clock supply control algorithm can reduce the power consumed by the sensing system by configuring a circuit to cut off the power of the sensing system and by recognizing the state of low sensor change and adjusting the measurement cycle. The system load power stabilization algorithm is an algorithm that controls the power of the surrounding module according to the power consumption state, and when it requires a lot of power, it controls the clock supply to stabilize the operation. The experimental results confirmed that applying only the dynamic clock supply control algorithm reduces the power consumed by the sensing system by 17%, and applying only the system load power stabilization algorithm reduces power consumption by 9.3%, enabling it to operate stably in situations that require a lot of power such as image processing. When both algorithms were applied, the power consumption of the battery was reduced by 67% compared to before applying the algorithm. Through this, the reliability of the proposed method was confirmed.