• Journal of the Microelectronics and Packaging Society
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• v.12 no.3 s.36
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• pp.187-196
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• 2005

MEMS devices such as a vibratory gyroscope often suffer from a lower yield rate due to fabrication errors and the external stress. In the decoupled vibratory gyroscope, the main factor that determines the yield rate is the frequency difference between the sensing and driving modes. The gyroscope, fabricated with SOI (Silicon-On-Insulator) wafer and packaged using the anodic bonding, has a large wafer bowing caused by thermal expansion mismatch as well as non-uniform surfaces of the structures caused by the notching effect. These effects result in large distribution in the frequency difference, and thereby a lower yield rate. To improve the yield rate we propose a packaged SiOG (Silicon On Glass) technology. It uses a silicon wafer and two glass wafers to minimize the wafer bowing and a metallic membrane to avoid the notching. In the packaged SiOG gyroscope, the notching effect is eliminated and the warpage of the wafer is greatly reduced. Consequently the frequency difference is more uniformly distributed and its variation is greatly improved. Therefore we can achieve a more robust vibratory MEMS gyroscope with a higher yield rate.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.41-47
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• 2009

Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The power consumption imbalance among sensor nodes may cause a network partition and failures where the transmission from some sensors to the sink node could be blocked. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications and can drastically affect the network's communication energy dissipation. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Our improved cluster head selection method ensures that energy is consumed evenly among the nodes in the network, thereby increasing the network lifetime. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 10.36% and 24.05% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively and also prolongs the network lifetime.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.167-183
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• 2023

In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.8
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• pp.759-769
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• 2013

Electronic equipment has been applied to virtually every area associated with commercial, industrial, and military applications. Specifically, electronics have been incorporated into avionics components installed in aircraft. This equipment is exposed to dynamic loads such as vibration, shock, and acceleration. Especially, avionics components installed in a helicopter are subjected to simultaneous sine and random base excitations. These are denoted as sine on random vibrations according to MIL-STD-810F, Method 514.5. In the past, isolators have been applied to avionics components to reduce vibration and shock. However, an isolator applied to an avionics component installed in a helicopter can amplify the vibration magnitude, and damage the chassis, circuit card assembly, and the isolator itself via resonance at low-frequency sinusoidal vibrations. The objective of this study is to investigate the dynamic characteristics of an avionics component installed in a helicopter and the structural dynamic modification of its tray plate without an isolator using both a finite element analysis and experiments. The structure is optimized by dynamic loads that are selected by comparing the vibration, shock, and acceleration loads using vibration and shock response spectra. A finite element model(FEM) was constructed using a simplified geometry and valid element types that reflect the dynamic characteristics. The FEM was verified by an experimental modal analysis. Design parameters were extracted and selected to modify the structural dynamics using topology optimization, and design of experiments(DOE). A prototype of a modified model was constructed and its feasibility was evaluated using an FEM and a performance test.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.3
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• pp.33-38
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• 2021

Recently, rollable and foldable displays are attracting great attention in the flexible display market due to their excellent form factor. To predict and prevent the mechanical failure of the display panels, it is essential to accurately understand the mechanical properties of brittle SiN_x thin films, which have been used as an insulating film in flexible displays. In this study, tensile properties of the ~130 nm- and ~320 nm-thick SiN_x thin films were successfully measured by coating a ~190 nm-thick organic nano-support-layer (PMMA, PS, P3HT) on the fragile SiN_x thin films and stretching the films as a bilayer state. Young's modulus values of the ~130 nm and ~320 nm SiN_x thin films fabricated through the controlled chamber pressure and deposition power (A: 1250 mTorr, 450 W/B: 1000 mTorr, 600 W/C: 750 mTorr, 700 W) were calculated as A: 76.6±3.5, B: 85.8±4.6, C: 117.4±6.5 GPa and A: 100.1±12.9, B: 117.9±9.7, C: 159.6 GPa, respectively. As a result, Young's modulus of ~320 nm SiN_x thin films fabricated through the same deposition condition increased compared to the ~130 nm SiN_x thin films. The tensile testing method using the organic nano-support-layer was effective in the precise measurement of the mechanical properties of the brittle thin films. The method developed in this study can contribute to the robust design of the rollable and foldable displays by enabling quantitative measurement of mechanical properties of fragile thin films for flexible displays.