Recently, the border security systems attract attention as large-scale monitoring system in wireless sensor networks (WSNs). In the border security systems whose aim is the monitoring of illegal immigrants and the information management in long-period, it deploys a lot of sensor nodes that have the communication and sensing functions in the detection area. Hence, the border security systems are necessary to reduce the power consumption of the whole system in order to extend the system lifetime and accurately monitor the track of illegal immigrants. In this paper, we propose two effective barrier coverage construction methods by switch dynamically operation modes of sensor nodes to reduce the operating time of the sensing function that wastes a lot of power consumption. We carry out performance evaluations by computer simulations to show the effectiveness of two proposed methods and show that the proposed methods are suitable for the border security systems.

This paper presents a new technique for modeling High-Voltage lightly-doped-drain MOS (HV MOS) devices accurately with the BSIM3v3 SPICE model. Standard SPICE models do not model the voltage dependency of Rs and Rd in HV MOS devices; this causes large discrepancies between the simulated and measured I-V characteristics of HV MOS devices. We propose to assign physical meanings and values different from the original BSIM3v3 model to three of its parameters to represent the voltage dependency of Rs and Rd. With this method, we have succeeded in highly accurate parameter extraction, and the simulated I-V characteristics of HV MOS devices using the extracted parameters match the measured results well. The relationship between the proposed modeling technique and the physical mechanism of HV MOS devices is also discussed based on measurement and device simulation results. Since our method does not change any model equations of BSIM3v3, it can be applied to any SPICE simulator on which the BSIM3v3 model runs, so we can use SPICE simulation for accurate circuit design of complex circuits using HV MOS devices.

This paper presents a new technique for accurately modeling uni-directional High-Voltage lightly-doped- drain MOS (HV MOS) devices by extending the bi- directional HV MOS model and adopting a new parameter extraction method. We have already reported on a SPICE model for bi-directional HV MOS devices based on BSIM3v3. However, if we apply this bi- directional HV MOS model and its parameter extraction technique directly to uni-directional HV MOS devices, there are large discrepancies between the measured and simulated I-V characteristics of the uni- directional devices. This paper extends the bi- directional HV MOS model, and adopts a new parameter extraction technique. Using parameters extracted with the new method, the simulated I-V characteristics of the uni-directional n-channel HV MOS device match the measured results well. Since our method does not change any model equations of BSIM3v3, it can be applied to any SPICE simulator on which the BSIM3v3 model runs.

In the food, beverage and cosmetic industry and so on, odor sensing systems instead of human sensory test are demanded. We have developed odor sensing systems using QCM (quartz crystal microbalance) sensor array and pattern recognition method. Since the properties of the sensors depend on the gas sorption characteristics of the sensing films coated on them, the optimum films according to target odors should be selected. In this study, we tried to select sensing films appropriate for discrimination of slightly different apple flavors. The examples of typical apple flavors were prepared blending 9 compounds. The sensing films were extracted from various kinds of materials such as lipid, stationary phase material of GC (gas chromatography) and cellulose. The selection method under the condition of the small number of measurements was studied. We analyzed the data of steady-state sensor responses in terms of the Euclidean distance, and the films appropriate for apple flavor discrimination were successfully selected.