Along with the increase in renewable energy, research on energy harvesting combined with piezoelectric energy is being conducted. However, it is difficult to predict the power generation of combined harvesting because there is no data on the power generation by a single piezoelectric material. Before predicting the corresponding power generation and efficiency, it is necessary to quantify the power generation by a single piezoelectric material alone. In this study, the generated power is measured based on three parameters (size of the piezoelectric ceramic, depth of compression, and speed of compression) that contribute to the deformation of a single PZT (Lead zirconate titanate)-based piezoelectric element. The generated power was analyzed by comparing with the corresponding parameters. The analysis results are as follows: (i) considering the difference between the size of the piezoelectric ceramic and the generated power, 20 mm was the most efficient piezoelectric ceramic size, (ii) considering the case of piezoelectric ceramics sized 14 mm, the generated power continued to increase with the increase in the compression depth of the piezoelectric ceramic, and (iii) For piezoelectric ceramics of all diameters, the longer the depth of deformation, the shorter the frequency, and depending on the depth of deformation, there is a specific frequency at which the charging power is maximum. Based on the findings of this study, PZT-based elements can be applied to cases that receive indirect force, including vibration energy and wave energy. In addition, the power generation of a PZT-based element can be predicted, and efficient conditions can be set for maximum power generation.

Nowadays, 3 Dimensional (3D) Printing is an effective and fast way to fabricate prototypes. It can fabricate desired shape by layering multiple thin layers using various types of plastics. Making objects with 3D printing are faster and less expensive than the existed ways like machining, molding and etc. But 3D printed objects are not considered as high robustness because of making method of Fused Deposition Modeling (FDM) such as 3D printing. Following experiments are planned to compare the strength of 3D printed objects. In this research, Nylon 645 and blue, green, brown, blue colored Polylactic Acid (PLA) filaments are used to fabricate tensile and compression test specimens. First, specimens are tested to investigate a relationship between filament colors, extrude temperature and strength. Second, tensile test is conducted to investigate a relationship between the rate of infill and strength using PLA and Nylon 645 specimens. Third, compression test is conducted to investigate a relationship between the rate of infill and strength using PLA and Nylon 645 specimens. This research shows that extrude temperature does not affect strength and each colored PLA filaments have their own strengths. Brown colored PLA is strongest of the PLA filament in this experiment. Rate of infill affects strength significantly. As infill rate become higher, Ultimate Tensile Strength (UTS), Ultimate Compressive Strength (UCS), and Young’s modulus also become higher. The results of this research will help designing objects which be made with 3D print to be loaded.

The study proposed a smart farm system using renewable energy to tackle global food shortages and declining agricultural populations. Unlike traditional smart farms relying on soil cultivation, this system employs hydroponics for better environmental management and faster crop growth. It integrates a wind generator, solar generator, and battery for energy, and uses controllers for temperature, water level, humidity, and photosynthesis in a plastic tank. The temperature controller activates a heating coil to maintain water temperature, while the water-level controller manages nutrient levels and the humidity controller prevents moisture buildup. A lighting device supports photosynthesis in darkness, with sensor data accessible via short-range communication. Lettuce cultivation experiments showed consistent temperature, accurate water level control (160 mm), effective humidity reduction, and timely LED operation. Energy experiments produced an average of 1060 Wh/day, with daily power consumption at 400 Wh, allowing 2.5 days of operation without extra power. Hydroponic cultivation improved temperature management and energy efficiency. A 40-day test with two lettuce groups-one with the system and one without-showed significantly higher growth rates for the system-applied group. The study confirms the effectiveness of renewable energy in operating a smart farm and provides insights for handling complex situations, including emergencies.

Parkinson’s disease (PD) is a common neurodegenerative disease, one of the symptoms of which is a gait disorder, which decreases gait speed and cadence. Recently, augmented feedback training has been considered to achieve effective physical rehabilitation. Therefore, we have devised a numerical modeling process and algorithm for gait detection and classification (GDC) that actively utilizes augmented feedback training. The numerical model converted each joint angle into a magnitude of acceleration (MoA) and a Z-axis angular velocity (ZAV) parameter. Subsequently, we confirmed the validity of both the GDC numerical modeling and algorithm. As a result, a higher gait detection and classification rate (GDCR) could be observed at a higher gait speed and lower acceleration threshold (AT) and gyroscopic threshold (GT). However, the pattern of the GDCR was ambiguous if the patient was affected by a gait disorder compared to a normal user. To utilize the relationships between the GDCR, AT, GT, and gait speed, we controlled the GDCR by using AT and GT as inputs, which we found to be a reasonable methodology. Moreover, the GDC algorithm could distinguish between normal people and people who suffered from gait disorders. Consequently, the GDC method could be used for rehabilitation and gait evaluation.

Background. Postural instability has been identified as a fall risk factor with a significant impact on the quality of life of patients with Parkinson’s disease (PD). The aim of this study was to compare the center of pressure (COP) between faller and nonfaller patients with PD during static standing. Methods. Thirty-two faller patients and 32 nonfaller patients with PD participated in this study. All patients performed the static balance test on a force plate. COP data were recorded during quiet standing. Mean distance, sway area, mean velocity, mean frequency, and peak power were derived from the COP data. Statistical analysis was performed using independent t-tests to compare faller and nonfaller patients. Results. Fallers presented a greater average distance, wider sway area, faster average speed, and greater peak power than nonfallers ( < 0.05). In contrast, no significant group differences were observed in peak frequency and mean frequency ( > 0.05). Conclusions. Although falls occur during dynamic activities, our study demonstrated that even a safe and simple static postural balance test could significantly differentiate between faller and nonfaller patients. Thus, these results suggest that quantitatively assessed static postural sway variables would be useful for distinguishing prospective fallers among PD patients.