• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2148-2167
• /
• 2021

The proliferation of the Internet of Things (IoT) technologies and applications, especially the rapid rise in the use of mobile devices, from individuals to organizations, has led to the fundamental role of secure wireless networks in all aspects of services that presented with many opportunities and challenges. To ensure the CIA (confidentiality, integrity and accessibility) security model of the networks security and high efficiency of performance results in various resource-constrained applications and environments of the IoT platform, DDO-(data-driven operation) based constructions have been introduced as a primitive design that meet the demand of high speed encryption systems. Among of them, the TMN-family ciphers which were proposed by Tuan P.M., Do Thi B., etc., in 2016, are entirely suitable approaches for various communication applications of wireless mobile networks (WMNs) and advanced wireless sensor networks (WSNs) with high flexibility, applicability and mobility shown in two different algorithm selections, TMN64 and TMN128. The two ciphers provide strong security against known cryptanalysis, such as linear attacks and differential attacks. In this study, we demonstrate new probability results on the security of the two TMN construction versions - TMN64 and TMN128, by proposing efficient related-key recovery attacks. The high probability characteristics (DCs) are constructed under the related-key differential properties on a full number of function rounds of TMN64 and TMN128, as 10-rounds and 12-rounds, respectively. Hence, the amplified boomerang attacks can be applied to break these two ciphers with appropriate complexity of data and time consumptions. The work is expected to be extended and improved with the latest BCT technique for better cryptanalytic results in further research.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.338-344
• /
• 2021

The recently continuous enhancement and development in the biomedical side for the betterment of human life. The Wireless Body Area Networks is a significant tool for the current researcher to design and transfer data with greater data rates among the sensors and sensor nodes for biomedical applications. The core area for research in WBANs is power efficiency, battery-driven devices for health and medical, the Charging limitation is a major and serious problem for the WBANs.this research work is proposed to find out the optimal solution for battery-friendly technology. In this research we have addressed the solution to increasing the battery lifetime with variable data transmission rates from medical equipment as Wireless Endoscopy Capsules, this device will analyze a patient's inner body gastrointestinal tract by capturing images and visualization at the workstation. The second major issue is that the Wireless Endoscopy Capsule based systems are currently not used for clinical applications due to their low data rate as well as low resolution and limited battery lifetime, in case of these devices are more enhanced in these cases it will be the best solution for the medical applications. The main objective of this research is to power optimization by reducing the power consumption of the battery in the Wireless Endoscopy Capsule to make it battery-friendly. To overcome the problem we have proposed the algorithm for "Battery Friendly Algorithm" and we have compared the different frame rates of buffer sizes for Transmissions. The proposed Battery Friendly Algorithm is to send the images on average frame rate instead of transmitting the images on maximum or minimum frame rates. The proposed algorithm extends the battery lifetime in comparison with the previous baseline proposed algorithm as well as increased the battery lifetime of the capsule.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1469-1476
• /
• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.4
• /
• pp.171-176
• /
• 2021

Die-to-wafer (D2W) hybrid bonding in the multilayer semiconductor manufacturing process is one of wafer direct bonding, and various studies are being conducted around the world. A noteworthy point in the current die-to-wafer process is that a lot of voids occur on the bonding surface of the die during bonding. In this study, as a suggested method for removing voids generated during the D2W hybrid bonding process, a flexible mechanism for implementing convex for die bonding to be applied to the bond head is proposed. In addition, modeling of flexible mechanisms, analysis/design/control/evaluation of static/dynamics properties are performed. The proposed system was controlled by capacitive sensor (lion precision, CPL 290), piezo actuator (P-888,91), and dSpace. This flexure mechanism implemented a working range of 200 ㎛, resolution(3σ) of 7.276nm, Inposition(3σ) of 3.503nm, settling time(2%) of 500.133ms by applying a reverse bridge type mechanism and leaf spring guide, and at the same time realized a maximum step difference of 6 ㎛ between die edge and center. The results of this study are applied to the D2W hybrid bonding process and are expected to bring about an effect of increasing semiconductor yield through void removal. In addition, it is expected that it can be utilized as a system that meets the convex variable amount required for each device by adjusting the elongation amount of the piezo actuator coupled to the flexible mechanism in a precise unit.

• The Journal of Korea Robotics Society
• /
• v.17 no.2
• /
• pp.142-151
• /
• 2022

With the advent of the 4th industrial revolution, autonomous driving technology is being commercialized in various industries. However, research on autonomous driving so far has focused on platforms with wheel-type platform. Research on a tracked platform is at a relatively inadequate step. Since the tracked platform has a different driving and steering method from the wheel-type platform, the existing research cannot be applied as it is. Therefore, a path-tracking algorithm suitable for a tracked platform is required. In this paper, we studied a path-tracking algorithm for a tracked platform based on a GPS sensor. The existing Pure Pursuit algorithm was applied in consideration of the characteristics of the tracked platform. And to compensate for "Cutting Corner", which is a disadvantage of the existing Pure Pursuit algorithm, an algorithm that changes the LAD according to the curvature of the path was developed. In the existing pure pursuit algorithm that used a tracked platform to drive a path including a right-angle turn, the RMS path error in the straight section was 0.1034 m and the RMS error in the turning section was measured to be 0.2787 m. On the other hand, in the variable LAD algorithm, the RMS path error in the straight section was 0.0987 m, and the RMS path error in the turning section was measured to be 0.1396 m. In the turning section, the RMS path error was reduced by 48.8971%. The validity of the algorithm was verified by measuring the path error by tracking the path using a tracked robot platform.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.11
• /
• pp.107-114
• /
• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• Journal of Advanced Technology Convergence
• /
• v.1 no.1
• /
• pp.1-6
• /
• 2022

Since 2015, the government has been making efforts to distribute Korean smart farms. However, the supply is limited to large-scale facility vegetable farms due to the limitations of technology and current cultivation research data. In addition, the efficiency and reliability compared to the introduction cost are low due to the simple application of IT technology that does not consider the crop growth and cultivation environment. Therefore, in this paper, data analysis services was performed based on public and external data. To this end, a data-based target smart farm system was designed that is suitable for the situation of farms growing in facilities. To this end, a farm risk information notification service was developed. In addition, light environment maps were provided for proper fertilization. Finally, a disease prediction model for each cultivation crop was designed using temperature and humidity information of facility farms. Through this, it was possible to implement a smart farm data service by linking and utilizing existing smart farm sensor data. In addition, economic efficiency and data reliability can be secured for data utilization.

• Design & Manufacturing
• /
• v.16 no.4
• /
• pp.1-6
• /
• 2022

Fine blanking is a press processing technology that can process most of the product thickness into a smooth surface with a single stroke. In this fine blanking process, shear is an essential step. The punches and dies used in the shear are subjected to impacts of tens to hundreds of gravitational accelerations, depending on the type and thickness of the material. Therefore, among the components of the fine blanking mold (dies), punches and dies are the parts with the shortest lifespan. In the actual production site, various types of tool damage occur such as wear of the tool as well as sudden punch breakage. In this study, machine learning algorithms were used to predict these problems in advance. The dataset used in this paper consisted of the signal of the vibration sensor installed in the tool and the measured burr size (tool wear). Various features were extracted so that artificial intelligence can learn effectively from signals. It was trained with 5 features with excellent distinguishing performance, and the SVM algorithm performance was the best among 33 learning models. As a result of the research, the vibration signal at the time of imminent tool replacement was matched with an accuracy of more than 85%. It is expected that the results of this research will solve problems such as tool damage due to accidental punch breakage at the production site, and increase in maintenance costs due to prediction errors in punch exchange cycles due to wear.

• Design & Manufacturing
• /
• v.17 no.1
• /
• pp.56-63
• /
• 2023

In this study, the vibration signal of the mold was measured and analyzed to monitor the process information and characteristics during the press molding process. A necklace-type picture frame mold was used for press molding, and the vibration signal was measured by GY-61 acceleration sensor module attached to the surface of the upper (movable) mold base. The change of the vibration signal of the mold according to press speed was analyzed. As a result, the vibration signal had a large change at five sections: "Holder contact", "Punch contact and start of pressing", "End of pressing", "Mold open", and "Demolding". The time difference between "Punch contact and start of pressing" and "End of pressing" means the pressing time which is the actual time the material is molded under pressing pressure. The time intervals for each section, represented by the time interval between "Holder contact" and "Punch contact and start of pressing", can be used to compare and evaluate the press speed applied to the process. By comparing the vibration signals at 60 rpm and 90 rpm, the amplitude at the section of "Punch contact and start of pressing" increased as the press speed increased. This result means that as the press speed increases, more force and pressure is applied to the material. Also, the peak values of the other sections were found to increase as the press speed increased. It was found that the pressing time, the time interval between "Punch contact and start of pressing" and "End of pressing", decreases as the pressing speed increases. Similarly, press speed factor, the time interval between "Holder contact", and "Punch contact and start of pressing", is found to be shorter. Therefore, based on the result of this study, the pressing time, press speed, pressing(punching) pressure of each cycle can be monitored by measuring the vibration signal of the mold. Also, it was confirmed that the level and trend of process information and characterization can be evaluated as the change of the mold vibration during press molding.

• Journal of the Korean Geosynthetics Society
• /
• v.22 no.3
• /
• pp.27-35
• /
• 2023

Ensuring the stability of visible structures during excavation works are extremely crucial. While the stability of the ground is analyzed through numerical calculations the during design phase, the conditions during construction often differ. Therefore, it is imperative to analyze the stability of the wall through measurements. The cost of measurements on the construction site is set at a very low unit price, which increases the risk of accidents involving retaining walls. In this study, we argue for the importance of automated or wireless system measurements of retaining walls, by estimating construction duration and accident costs through the analysis of hypothetical accident cases, and comparing these with measurement costs. In case of a major destruction during excavation work, the accident handling cost could be less than 5% of the total measurement budget. Therefore, increasing the measurement budget to prevent accidents in advance can be economically beneficial.