Falls are common among older people. Age-related changes in toe strength and force steadiness may increase fall risk. This study aimed to evaluate the performance of a fall risk prediction model using toe strength and force steadiness data as input variables. Participants were four healthy adults (25.5±1.7 yrs). To indirectly reproduce physical conditions of older adults, an experiment was conducted by adding conditions for weight and fatigue increase. The maximal strength (MVIC) was measured for 5 s using a custom toe dynamometer. For force steadiness, toe flexion was measured for 10 s according to the target line, which was 40% of the MVIC. A one-leg-standing test was performed for 10 s with eyes-opened using a force plate. Deep learning experiments were performed with seven conditions using long short-term memory (LSTM) algorithms. Results of the deep learning model were randomly mixed and expressed through a confusion matrix. Results showed potential of the model"s fall risk prediction with force steadiness data as input variables. However, experiments were conducted on young adults. Additional experiments should be conducted on older adults to evaluate the predictive model.

A clean room is used for adjusting the concentration of suspended particles using an air-conditioner. It has a fan-filter unit combining a centrifugal fan and a high-efficiency particulate air filter that purifies the outside air and directly affects its cleanliness. Defects in these systems are typically detected using special sensors for each fault, which can be costly. Therefore, this paper proposes a system for diagnosing defects in the fan-filter unit using a single differential sensor and deep learning. The fan-filter unit is part of the air-conditioning system, and it is usually defective in bearings, filters, and motors. These faults include ball wear, internal bearing contamination, filter contamination, and motor speed changes. Each defect was artificially induced in experiments, and the differential pressure data of each defect was learned using a long short-term memory (LSTM) deep learning algorithm. The results of deep learning experiments generated by randomly mixing data five times were presented using a confusion matrix, and the results showed an accuracy of 87.2±2.60%. Therefore, the possibility of diagnosing defects in the fan-filter unit using a single sensor was confirmed.

This paper presents a construction method regarding a tubular nano-mesh for which the anodic oxidation of aluminum (Al) wire is used. The first step of tubular-nano-mesh production is Al-wire anodization. A new anodizing device was made for the wire-based uniform anodization for this study, and a high-purity (99.999%) Al wire with a 2 mm diameter was used. Also, an electrolytic solution was used as a 0.07 M oxalic acid, while the electrolytic-solution temperature was maintained at -3℃. While the applied voltage and the process time were varied, the AAO (Anodic Aluminum Oxide) characteristics of the Al wire were observed. When 60 V was applied to the wire, alumina cracks were not evident, whereas the application of 100 V produced alumina cracks; this is because the growth rate of the nano-pore voltage affected the alumina shape. For the subsequent construction of the tubular alumina structure, an Al-etchant (HCl + H2O + CuCl2 + 2H2O) etched-Al portion of the anodized wire was employed. The final step is a pore-widening process that is implemented through the hole channel. The anodized wire was dipped in the alumina etchant, and the pore-wall removal was checked over time.

In this paper, the embedding type novel liquid metal strain gauge was developed for measuring the deformation of wind turbine blades. In general, the conventional methods for the SHM have many disadvantages such as frequency distortion in FBG sensors, the low gauge factor and mechanical failures in strain gauges and extremely sophisticated filtering in AE sensors. However, the liquid metal filled in a pre-confined micro channel shows dramatic characteristics such as high sensitivity, flexibility and robustnes! s to environment. To adopt such a high feasibility of the liquid metal in flexible sensor applications, the EGaIn was introduced to make flexible liquid metal strain gauges for the SHM. A micro channeled flexible film fabricated by the several MEMS processes and the PDMS replication was filled with EGaIn and wire-connected. Lots of experiments were conducted to investigate the performance of the developed strain gauges and verify the feasibility to the actual wind turbine blades health monitoring.

In this paper, a three-dimensional computational fluid dynamic model of a proton exchange membrane fuel cell(PEMFC) with serpentine flow channel is presented. A steady state, single phase and isothermal numerical model has been established to investigate the influence of the GDL (Gas Diffusion Layer) parameters. The GDL is made of a porous material such as carbon cloth, carbon paper or metal wire mesh. For the simplicity, the GDL is modeled as a block of material having numerous pathways through which gaseous reactants and liquid water can pass. The porosity, permeability and thickness of the GDL, which are employed in the model parameters significantly affect the PEMFC performance at the high current region.

Punching tools like an electrodes are made by milling or etching or EDM. These methods had time consuming, low efficiency and air pollution. So, we have developed a shearing device which counter punching method for burr less cutting of micro wire. Using the straightened SUS304 wire with 200 ㎛ diameter, we confirmed the tendency of the shear plane for punch tools. It was impossible to completely remove the burr in the shearing process. In order to minimize the burr size and fine shear plane, we have accomplished the various experiment conditions such as the U-groove, the effect of the counter punch, shear angle and clearance. The results of the experiments show that indentation, slip plane and bent shape were related to the shear angle and clearance.

Hot embossing lithography(HEL) has the production advantage of comparatively few process step, simple operation, a relatively low cost for embossing tools(Si), and high replication accuracy for small features. In this paper, we considered the nano-molding characteristic according to molding parameters(temperature, pressure, times, etc) and induced a optimal molding condition using HEL. High precision nano-patter master with various shapes were designed and manufactured using the DRIE(Deep Reactive Ion Etching), LPCVD(Low Pressure Chemical Vapor Deposition) and thermal oxidation process, and we investigated the molding characteristic ofDVD and Blu-ray nickel stamp. We induced flow behaviors of polymer, rheology by shapes and sizes of the pattern through various molding experiments. Finally, with achieving nano-structure molding with high aspect ratio, we will secure a basic technology about the molding of large-area nano-pattern media.

The Hot Embossing Lithography(HEL) as a method for the fabrication of the nanostructure with polymer is becoming increasingly important because of its simple process, low cost, high replication fidelity and relatively high throughput. In this paper, we carried out experimental studies and numerical simulations in order to understand the viscous flow of the polymer (PMMA) film during the hot embossing process. To grasp the characteristics of the micro patterning rheology by process parameters (embossing temperature, pressure and time), we have carried out various experiments by using the nickel-coated master fabricated by the deep RIB process and the plasma sputtering. During the hot embossing process, we have observed the characteristics of the viscoelastic behavior of polymer. Also, the viscous flow during the hot embossing process has been simulated by the continuum based FDM(Finite Difference Method) analysis considering the micro effect, such as a surface tension and a contact angle.

The shearing process for the sheet metal is normally used in the precision elements such as a lead frame of IC chips. In these precision elements, the burr formation brings a bad effect on the system assembly and demands the additional deburring process. In this paper, we developed the small size precision punching system to investigate burr formation mechanism and to present kinematically punch-die aligning methodology between the rectangular shaped punch and die. The punch is driven by an air cylinder and the sheet metal is moving on the X-Y table system which is driven by two stepping motors. The whole system is controlled by microprocessor and is communicated with each other by RS232C serial communication protocol. Punching results are measured manually using the SEM photographs and are compared aligning result with miss aligning one.

Optical fibers are indispensable for optical communication systems that transmit large volumes of data at high speed. But the aligning technology under the sub-micron accuracy is required for the precise axis adjustment and connection. For the purpose of precise alignment of the optical arrays, in this research, we have developed the 12-axis(with 8 automated axis and 4 manual axis) automatic optical fiber alignment system including the image processing-based searching system, the automatic loading system using the robot and the suction tool and the automatic UV bonding system. In order to obtain the sub-micron alignment accuracy, two 4-axis PC-based motion controllers and the two 50㎚ resolution 6-aixs micro-stage actuated by micro stepping motors are adopted.
The fiber aligning procedure consists of two steps. Firstly, the optical wave guide and an input optical array are aligned by the 6-axis input micro-stage with the IR camera. The image processing technique is introduced to reduce primary manual aligning time and result in achieving the 50% decrease of aligning time. Secondly, the IR camera is replaced by the output micro-stage and a wave guide and two optical arrays are aligned simultaneously before the laser power intensity delivered to the optical powermeter reached the threshold value. When the aligning procedure is finished, the wave guide and arrays are UV bonded. The automatic loading/unloading system is also introduced and the entire wave guide handing time is reduced significantly compared to the former commercial aligning system.

This paper presents the fabrication and evaluation of mechanical behavior for a peristaltic micropump by flow simulation. The valve-less micropump using the diffuser/nozzle is consists of the lower plate, the middle plate, the upper plate and the tube that connects inlet and outlet of the pump. The lower plate includes the channel and the chamber, and the plain middle plate are made of glass and actuated by the piezoelectric translator. Channels and a chamber on the lower plate are fabricated on high processability silicon wafer by the DRIE(Deep Reactive Ion Etching) process. The upper plate does the roll of a pump cover and has inlet/outlet/electric holes. Three plates are laminated by the aligner and bonded by the anodic bonding process. Flow simulation is performed using error-reduced finite volume method (FVM). As results of the flow simulation and experiments, the single chamber pump has severe flow problems, such as a backflow and large fluctuation of a flow rate. It is proved that the double-chamber micropump proposed in this paper can reduce the drawback of the single-chamber one.