Multisensor based security robot system for intelligent building

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. The most importance role of the intelligent building is the security system. We develop a multi sensor-based intelligent security robot (ISR) that is widely employed in intelligent buildings. The intelligent security robot can detect abnormal and dangerous situations and notify users. The robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. The function of the ISR contains six parts. There is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. We develop a multi sensor-based sensor system in the ISR. We use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. There is an adaptive fusion method, a rule based method, and a statistical signal method. We demonstrate the remote supervisory system to control the ISR using a direct control mode and a behavior control mode. We think that the man–machine interface in a security robot system must have mobility and convenience. Therefore, we use a touch screen to display the system state, and design a general user interface (GUI) to service the user and visitors. The user can remotely control the appliance using a cell phone through a GSM modem, too. The appliance module can feedback reaction results to the user through a cell phone. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. In intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of the detection result to the user using a GSM modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.     

Data hiding in AMBTC images using quantization level modification and perturbation technique

Multimedia Tools and Applications - A novel data hiding method for Absolute Moment Block Truncation Coding (AMBTC) compressed image based on quantization level modification is proposed. Blocks of...     

Fabrication and characteristic detection of graphene nanoelectrodes

Graphene has the advantages of high electrical conductivity, high heat conductivity, and low noise, which makes it a potential option for integrated circuits interconnection and nanoelectrodes. In this paper, we present a novel fabrication method for graphene nanoeletrodes with nanogap. First, graphene grown by chemical vapor deposition (CVD) is assembled to a chip with microelectrodes. Second, an atomic force microscopy (AFM) based mechanical cutting method is developed to cut the graphene into nanoribbons and nanoeletrodes with nanogap. Then the electronic property of a single nanodot is characterized using the garphene nanoelectrodes, demonstrating the effectiveness of the graphene nanoelectrodes. The fabricated graphene nanoeletrode pairs can be used as probes to detect single molecule in micro-environment, and show an attractive prospect for future molecular electronics applications.     

SoHyFIS-Yager: A self-organizing Yager based Hybrid neural Fuzzy Inference System

The Hybrid neural Fuzzy Inference System (HyFIS) is a multilayer adaptive neural fuzzy system for building and optimizing fuzzy models using neural networks. In this paper, the fuzzy Yager inference scheme, which is able to emulate the human deductive reasoning logic, is integrated into the HyFIS model to provide it with a firm and intuitive logical reasoning and decision-making framework. In addition, a self-organizing gaussian Discrete Incremental Clustering (gDIC) technique is implemented in the network to automatically form fuzzy sets in the fuzzification phase. This clustering technique is no longer limited by the need to have prior knowledge about the number of clusters present in each input and output dimensions. The proposed self-organizing Yager based Hybrid neural Fuzzy Inference System (SoHyFIS-Yager) introduces the learning power of neural networks to fuzzy logic systems, while providing linguistic explanations of the fuzzy logic systems to the connectionist networks. Extensive simulations were conducted using the proposed model and its performance demonstrates its superiority as an effective neuro-fuzzy modeling technique.     

Analysis of the Optimum Configuration of Roadside Units and Onboard Units in Dedicated Short-Range Communication Systems

With the aid of a simple relation, which is analogous to the radar equation, the uplink signal strength received by the receiving module of a roadside unit (RSU) and emitted from the radiation module of an onboard unit (OBU) can be described. Setting the scale of this relation arbitrarily and determining the signal strength threshold from experimental measurements, and combined with the simulation of the radiation and the receiving pattern by cosineⁿ function, the relative signal strength emitted from the OBU and received by the RSU can be calculated successfully. From this computed relative signal strength and the threshold, the influence of the RSU and OBU mounting parameters, such as the mounting angles and mounting height, on the available communication region is analyzed. The effect of windshield fading is also considered. With the help of the analysis results, an optimum RSU and OBU mounting configuration can be easily obtained. This method can be used conveniently and successfully for very short wavelengths. This includes visible light, infrared, and even submillimeter-wave ranges. For millimeter-wave and microwave systems, this method can, in some cases, also provide a rudimentary estimation     

BiNem® manufacturing process for mass production

Abstract— As the need for high‐resolution ultra‐low‐power bistable displays grows, it is important to rapidly implement the mass‐production manufacturing of BiNem® LCDs. The cost‐effective approach for BiNem® manufacturing is based on using STN manufacturing process technologies since BiNem® and STN displays have a similar internal structure. The key differences between BiNem® and STN displays from a manufacturing point of view will be discussed. We show that industrial STN manufacturing equipment can be used to produce BiNem® LCDs at competitive costs. Reflective e‐book display modules with VGA resolution are produced in the pilot‐production series.     

Efficient mining of intertransaction association rules

Most of the previous studies on mining association rules are on mining intratransaction associations, i.e., the associations among items within the same transaction. We extend the scope to include multidimensional, intertransaction associations. In a database of stock price information, an example of such an association is "if (company) A's stock goes up on day one, B's stock will go down on day two but go up on day four:" whether we treat company or day as the unit of transaction, the items belong to different transactions. Moreover, such an intertransaction association can be extended to associate multiple properties in the same rule, so that multidimensional intertransaction associations can also be defined and discovered. Mining intertransaction associations pose more challenges on efficient processing than mining intratransaction associations because the number of potential association rules is extremely large. We introduce the notion of intertransaction association rule and develop an efficient algorithm, FITI (first intra then inter), for mining intertransaction associations, which adopts two major ideas: 1) an intertransaction frequent itemset contains only the frequent itemsets of its corresponding intratransaction counterpart; and 2) a special data structure is built among intratransaction frequent itemsets for efficient mining of intertransaction frequent itemsets.     

Advanced SPICE modeling of large power IGBT modules

An enhanced insulated gate bipolar transistor (IGBT) model based on the Kraus model with new derivations based on an extra parameter accounting for p-i-n injection was developed to allow simulation of both trench and DMOS IGBT structures. Temperature dependence was also implemented in the model. The model was validated against steady-state and transient measurements done on an 800-A 1.7-kV Dynex IGBT module at 25/spl deg/C and 125/spl deg/C. The Spice model has also shown excellent agreement with mixed mode MEDICI simulations. The Spice model also takes into account for the first time the parasitic thyristor effect allowing the dc and dynamic temperature-dependent latchup modeling of power modules as well as their temperature-dependent safe operating area.     

Heteroepitaxial growth of indium phosphide on silicon by MOCVD using adduct source

Abstract

The heteroepitaxial growth of InP on Si by low pressure metalor‐ganic chemical vapor deposition is reported. Trimethylindium‐trimethylphosphine adduct was used as In source in this study. From X‐ray and SEM examinations, good crystallinity InP epilayers with mirror‐like surfaces can be grown directly on (100) and (111) p‐type Si substrates. Carrier concentration profile shows that the carrier distribution in the InP epilayer is very uniform. The efficient photo‐luminescence compared with that of InP homoepitaxy shows the good quality of InP/Si epilayers.