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The importance of location prediction is rapidly increasing with the current trend of database applications in mobile computing environment. However, current personal communication services network could only provide currently maintained location information of non-idle mobile terminals. Pertinent researches predict the future location based on tangent velocity approaches, which require mobile terminals to spend lots of precious electronic power to sense and then measure a sequence of positions for predicting the future tangent velocity, and the prediction is effective only within a short range of time. In this study, we propose an approach to predict future locations of mobile terminals based on the moving behaviors mined from their long-term moving history. Location prediction based on moving behavior requires no power consumption for position measurement, and the prediction results are effective for a long time without requiring the queried clients to be non-idle. With the help of moving behavior, we propose several location prediction operators for location query. Finally, we demonstrate the accuracy of the location query operators through simulation statistics. The experimental results show that the predictions are accurate enough for regular moving mobile terminals.

Granulocyte colony-stimulating factor (G-CSF) is required for proliferation, differentiation, and survival of cells. It is also a biomarker of human oocyte developmental competence for embryo implantation. In humans, the G-CSF concentration peaks during the ovulatory phase of the ovarian cycle. In this study, the expressions of G-CSF and its receptor were analyzed by polymerase chain reaction in granulosa cells (GCs), CL, cumulus cells (CCs), and oocytes. Cumulus-oocyte complexes were aspirated from antral follicles of 1 to 3 mm (small follicles) and 4 to 6 mm (medium follicles). Cumulus-oocyte complexes from two kinds of follicles were matured in protein-free maturation medium supplemented with various concentrations of G-CSF (0, 10, and 100 ng/mL). By real-time polymerase chain reaction, the expressions of G-CSF and its receptor were detected in GCs, CL, CCs, and oocytes. Interestingly, the G-CSF transcript levels were significantly lower in oocytes than in the other cell types, whereas the G-CSF receptor transcript levels in oocytes were similar to those in GCs. After 44 hours of IVM, no differences in the rate of nuclear maturation were detected; however, the intracellular reactive oxygen species levels in oocytes from both groups of follicles matured with 10 ng/mL of human recombinant G-CSF (hrG-CSF) groups were significantly lower (P < 0.05). After parthenogenetic activation, the cleavage rates were significantly (P < 0.05) higher in 100 ng/mL hrG-CSF-treated small (63.3%) follicles than in 0, 10 ng/mL hrG-CSF-treated small (38.6% and 49.0%, respectively) follicles and 0 ng/mL hrG-CSF-treated medium (52.1%) follicles, and the cleavage rates were significantly (P < 0.05) higher in 10 ng/mL hrG-CSF-treated medium (76.3%) follicles than in all other groups. The blastocyst formation rates were significantly (P < 0.05) higher in 100 ng/mL hrG-CSF-treated small (31.2%) follicles than in 0 and 10 ng/mL hrG-CSF small (10.4% and 15.6%, respectively) follicles, and the 10 ng/mL hrG-CSF medium (45.7%) follicle was significantly (P < 0.05) higher than in all other groups. The total cell number in blastocysts from the 10 ng/mL hrG-CSF medium (106.5) follicles was significantly (P < 0.05) increased compared to 0, 10, 100 ng/mL hrG-CSF small (55.0, 73.7 and 59.5, respectively) follicles and 0, 100 ng/mL hrG-CSF-treated medium (82.5 and 93.5, respectively) follicles. After IVF, the blastocysts stage was significantly (P < 0.05) increased in 10 ng/mL hrG-CSF-treated medium (36.4%) follicles. Fertilization efficiency was significantly high in 100 ng/mL of small (29.1%) and 10 ng/mL of medium (44.0%) follicles. We also examined the Bcl2 and ERK2 transcript levels and found that they were significantly higher in the small and medium follicle treatment groups. In conclusion, these results indicate that hrG-CSF improve the viability of porcine embryos.

Driven by the growing number of the mobile subscribers, efficient channel resource management plays a key role for provisioning multimedia service in the next generation personal communication systems. To reuse limited channel resources, diminishing the coverage areas of cells seems to be the ultimate solution. Thus, however, causes more handover events. To provide seamless connection environment for mobile terminals and applications, this article presents a novel handover scheme called the intelligent channel reservation (ICR) scheme, which exploits the location prediction technologies to accurately reserve channel resources for handover connections. Considering the fact that each mobile terminal has its individual mobility characteristic, the ICR scheme utilizes a channel reserving notification procedure (CRNP) to collect adequate parameters for predicting the future location of individual mobile terminals. These parameters will be utilized by the handover prediction function to estimate the expected handover blocking rate and the expected number of idle channels. Based on the handover prediction estimations, a cost function for calculating the damages from blocking the handover connections and idling channel resources, and a corresponding algorithm for minimizing the cost function are proposed. In addition, a guard channel decision maker (GCDM) determines the appropriate number of guard channels. The experimental results show that the ICR scheme does reduce the handover-blocking rate while keeping the number of idle channels small.

Due to insufficient available bandwidth resources and the continuously growing demand for cellular communication services, the channel assignment problem has become increasingly important. To trace the optimal assignment, several heuristic strategies have been proposed. So far, most of them focus on the small-scale systems containing no more than 25 cells and they use an anachronistic cost model, which does not satisfy the requirements of most existing cellular operators, to measure the solution quality. Solving the small-scale channel assignment problems could not be applied into existing large scale cellular networks' practice. This article proposes a decomposition approach to solve the fixed channel assignment problem (FCAP) for large-scale cellular networks through partitioning the whole cellular network into several smaller sub-networks and then designing a sequential branch-and-bound algorithm that is made to solve the FCAP for them sequentially. The key issue of partition is to minimize the dependences of the sub-networks so that the proposed heuristics for solving smaller problems will suffer fewer constraints in searching for better assignments. The proposed algorithms perform well based on experimental results and they were applied to the Taiwan Cellular Cooperation (TCC) in ChungLi city to find better assignments for its network.

In recent years, several kinds of wireless network have been widely deployed. In this work, we focus on the e-bus-system for movements of buses. Passengers can get the bus information through the intelligent bus stop when they are waiting for the bus. In today’s environment of Taiwan, the transportation information is provided through some specific Mobile network operators. In this case, it costs a huge expenditure every month for the charge of data transmission. Therefore, we propose a new network system with Digital Mobile Radio (DMR) and Super Wi-Fi to replace the mobile network operator. Furthermore, when the catastrophe happened, the proposed system can also change to be used for the rescues. The implementation of the system architecture, the application of DMR and super WiFi in the proposed system, and the operation scenario are described in this paper.

EIMS is a stable and safe communication system. It integrates the communication of citizen patrols and police units. When unexpected emergency happens, the system can enhance the citizen patrols' communications capabilities, decrease the time in communication and response, and reduce the loss of life and property. There are five citizen patrols implemented EIMS in northern Taiwan. They have enhanced the capacity of community citizen patrols. And, there are more than 1,500 residents to enjoy the efficient of its system.

The fingerprint-based techniques are commonly used for indoor location estimation, in which a radio map is built by calibrating signal-strength values at several training locations in the offline phase. However, the signal-strength values change as the environment changes, and hence the radio map built may be out of date. Further, the recalibration of signal-strength values for each environment change is laborious and time consuming. Therefore, in this paper, an efficient radio map management method is proposed in response to the environment changes. We first demonstrate that different features of signal propagation are obtained in different regions of the indoor environment. According to the different features of signal propagation, the environment is divided into several regions and the signal-strength values collected at the training locations in different regions can be updated accurately and individually using proper propagation features. The experimental results show the usefulness of the proposed method and the accuracy of the localization can be improved.

In general, stochastic partial differential equations and/or boundary conditions describing flow in phreatic aquifers are nonlinear. This paper uses second-order perturbation to approximate the response of a phreatic aquifer system subject to multiple random inputs. The approach is equivalent to assuming quadratic nonlinearities in the original nonlinear phreatic aquifer system. Using frequency domain representations, the resulting model is decomposed into linear and nonlinear (quadratic) frequency response functions (FRF). For Gaussian input, the response of a nonlinear phreatic aquifer system is non-Gaussian and is typically skewed. Thus the variance spectrum is insufficient to describe the response process. The bispectrum, defined as the Fourier transform of the third-order cumulant sequence, represents the distribution of skewness with frequency and further serves as a measure of the nonlinearity of the system. Given input processes of aquifer recharge and stream stage fluctuations, the linear and quadratic FRF are used to construct the spectrum and bispectrum of the response process. The role of nonlinearity in a stream-aquifer system is examined.

This paper presents a new behavior classification system that can analyze human behaviors from arbitrary views. Technically, if different viewing angle are used for observing a person, his appearances will change significantly. To freely recognize his behaviors, traditional methods tend to adopt 3-D data for behavior analysis. However, its inherent correspondence process will make it inappropriate for real time applications. To tackle this problem, a novel view alignment method is first proposed for mapping each action sequence to a fixed view. To achieve this mapping, two features extracted from spatial and temporal domains are used for representing each action sequence. For the spatial feature, the "centroid context" of each posture is defined and extracted through a triangulation technique. For the temporal feature, the "posture transition probability" is constructed for recording the probabilities of one posture type transferring to another one. After mapping, a novel matrix representation is proposed for describing each action more accurately. After that, the Viterbi algorithm is used for aligning two action sequences and then classifying them to different behavior types.

This study proposed a smart control algorithm to naturally adjust the thermal quality of the environment according to the interior and exterior environmental factors and the behavior of the inhabitants. To design an appropriate smart control algorithm for the smart buildings in the subtropical zones, this study conscientiously investigated the thermal effect of smart-skin facades of some office buildings in Taiwan to learn the correlation of the thermal parameters and the requirements of the inhabitants. To evaluate and further improve the proposed algorithm, an experimental building with two experimental zones was constructed. The experimental results show that the proposed algorithm significantly improves the thermal comfort and reduce power consumption through well coordinating the smart-skin equipment and air conditioners.

Nowadays, medical centers are working on setting a safe medicating environment by using information technology. This study tried to improve patients' safety environment, communications among medical workers and patients, medicating quality, and medical process efficiency through a wireless handheld RFID patient safety enhancement system for medical personnel. The proposed portable patient information integration system combines Radio Frequency Identification (RFID) technology, Wireless Network, Personal Digital Assistant (PDA) and Front-Monitoring System. Through the help of the proposed system, the medical workers can identify patients by non contact identification and get medical record immediately. Meanwhile the proposed system can record the history of the interaction between medical personnel and patients. It can also send alarm to the corresponding medical workers when reporting a high risk testing result and give medicine safety suggestion. The proposed system can improve the correctness and instantaneousness of patients' medical information and hence provide a safe environment for patients, and the Wan Fang Hospital is now verifying the performance of this system for improving the patients'safety.

This paper presents a smart home system prototype which employs an indoor positioning system called the Best Beacon Match (BBM) positioning method to intelligently trigger the appropriately services for the home members. To overcome the ninja problem in the BBM method, the signal filtering, adjustment and smooth procedures are proposed. We employ the Zigbee module to implement the prototypes of the components for the BBM positioning method, and the prototypes were pass the ZigBee Compliant Platform (ZCP) certification test. The proposed system prototype which intelligently controls the air condition and light system for smart home applications is also verifying in our demo room and in the smart house in National Taiwan University.

This paper formally presents the resident physician scheduling problem, which is one of the most important scheduling problems in hospital. The resident physician scheduling problem is characterized as satisfying the fair schedule constraint, the physician specification constraint and the safe schedule constraint simultaneously. To minimize the penalties from violating the constraints, this study adopts the evolutionary approach to propose a genetic algorithm for solving the problems. In addition the well-known genetic operators, this study proposed a new mutation operator called dynamic mutation for solving the resident physician scheduling problem. The experimental results show that the proposed algorithm performs well in searching optimal schedules.

Emergency medicine is an important link in healthcare system. There is high complexity about the medical process across with different organizations because the care operation including multiple procedures and it's hard to pre-scheduling when there are many random emergencies happened in the chaotic environment. The bottleneck of emergency medicine system is hard to integrate the virtual data and physical object in emergency medical service (EMS) in real time with limited resource. The research describes an empirical experience about how Wan-Fang hospital in Taiwan implements RFID technology in EMS at the first stage, and how we integrate with the existent EMS architecture and legacy system. We develop an RFID EMS system, and evaluate the benefit from the implementation by quantity and quality methodology. The research can be referred to practice and academic in medical informatics related fields.

The attempts to develop a ubiquitous health care monitoring system arisen from the need of automatic real-time medical services for emergent diseases. Besides, the physiological statuses gathered and maintained by this system are very helpful for diagnosis and early warning. To improve the medical services and diagnosis accuracy, a Wireless Health Advanced Mobile Bio-diagnostic System (abbreviated as WHAM-BioS) is proposed. This study focuses on network/communication technology in the WHAM-BioS and proposes a novel clustered sensor network (CSN) architecture for long-term periodical telecare applications. In the proposed CSN architecture, most network functions are concentrated in a special purpose device called the human body gateway (HBG). The sensor nodes focus on detecting and reporting their detection results to their HBG. To reduce the design complexity and the implementation cost for the sensor nodes, the proposed architecture proposed several protocols to help each HBG to provide a contention free environment for their sensor nodes. The contention free environment significantly reduces the power consumption in data retransmission. Besides, to further reduce the power consumption of the sensor nodes, this study also proposes a power saving mechanism, which reduces the power consumption in idle listening. Based on the proposed network architecture and protocols, a prototype system is implemented

This paper introduces a novel scheduling problem called the active interval scheduling problem in hierarchical wireless sensor networks for long-term periodical monitoring applications. To improve the report sensitivity of the hierarchical wireless sensor networks, an efficient scheduling algorithm is desired. Therefore, in this paper, we propose a compact genetic algorithm (CGA) to optimize the solution quality for sensor network maintenance. The experimental result shows that the proposed CGA brings better solutions in acceptable calculation time.

This paper introduces a novel scheduling problem called the active interval scheduling problem in hierarchical wireless sensor networks for long-term periodical monitoring applications. To improve the report sensitivity of the hierarchical wireless sensor networks, an efficient scheduling algorithm is desired. In this paper, we propose a compact genetic algorithm (CGA) to optimize the solution quality for sensor network maintenance. The experimental result shows that the proposed CGA brings better solutions in acceptable calculation time.

A newly developed smart sensor node that can monitor the safety of temporary structures such as scaffolds at construction sites is detailed in this paper. The design methodology and its trade-offs, as well as its influence on the optimization of sensor networks, is examined. The potential impact on civil engineering construction sites, environmental and natural disaster pre-warning issues, etc., all of which are foundations of smart sensor nodes and corresponding smart sensor networks, is also presented. To minimize the power requirements in order to achieve a true wireless system both in terms of signal and power, a sensor node was designed by adopting an 8051-based micro-controller, an ISM band RF transceiver, and an auto-balanced strain gage signal conditioner. With the built-in RF transceiver, all measurement data can be transmitted to a local control center for data integrity, security, central monitoring, and full-scale analysis. As a battery is the only well-established power source and there is a strong desire to eliminate the need to install bulky power lines, this system designed includes a battery-powered core with optimal power efficiency. To further extend the service life of the built-in power source, a power control algorithm has been embedded in the microcontroller of each sensor node. The entire system has been verified by experimental tests on full-scale scaffold monitoring. The results show that this system provides a practical method to monitor the structure safety in real time and possesses the potential of reducing maintenance costs significantly. The design of the sensor node, central control station, and the integration of several kinds of wireless communication protocol, all of which are successfully integrated to demonstrate the capabilities of this newly developed system, are detailed. Potential impact to the network topology is briefly examined as well.

Most wireless sensor networks base their design on an ad hoc (multi-hop) network technology that focus on organizing and maintaining a network formed by a group of moving objects with a communication device in an area with no fixed base stations or access points. Although ad hoc network technologies are capable of constructing a sensor network, the design and implementation of sensor networks for monitoring stationary nodes such as construction sites and nature-disaster-prone areas can be furthered simplified to reduce power consumption and overhead. Based on the nature of immobile nodes, a hierarchical sensor network architecture and its associated communication protocols are proposed in this paper. In this proposed architecture, most elements in the sensor network are designed to be equipped with no functions for message forwarding or channel scheduling. The local control center uses a centralized communication protocol to communicate with each sensor node. The local control center can also use ad hoc network technology to relay the data between each of the sensors. This approach not only minimizes the complexity of the sensor nodes implemented but also significantly reduces the cost, size and power consumption of each sensor node. In addition, the benefit of using ad-hoc network technology is that the local controller retains its routing capabilities. Therefore, power efficiency and communication reliability can be both achieved and maximized by this type of hierarchical sensor network.

Attempts to develop a Wireless Health Advanced Mobile Bio-diagnostic System (abbreviated as WHAM-BioS) have arisen from the need to monitor the health status of patients under long-term care programs. The proposed WHAM-BioS as presented here was developed by integrating various technologies: nano/MEMS technology, biotechnology, network/communication technology, and information technology. The biochips proposed not only detect certain diseases but will also report any abnormal status readings on the patient to the medical personnel immediately through the network system. Since long-term home care is typically involved, the parameters monitored must be analyzed and traced continuously over a long period of time. To minimize the intrusion to the patients, a wireless sensor embedded within a wireless network is highly recommended. To facilitate the widest possible use of various biochips, a smart sensor node concept was implemented. More specifically, various technologies and components such as built-in micro power generators, energy storage devices, initialization processes, no-waste bio-detection methodologies, embedded controllers, wireless warning signal transmissions, and power/data management were merged and integrated to create this novel technology. The design methodologies and the implementation schemes are detailed. Potential expansions of this newly developed technology to other applications regimes will be presented as well.

This paper presents a novel 802.11-based positioning system called the maximal cluster centered positioning system (MCCPS) developed and demonstrated at National Central University. The MCCPS system locates mobile objects via collecting the sensed power strengths of the mobile objects to multiple wireless access points. To overcome the serious multipath fading problem in the indoor environment, several positions called reference points were selected and a database is introduced to maintenance the power signature of each reference point. The experimental results show that the location information provided by MCCPS assures high correctness of region classification and low distance error.

Due to the insufficiency of available bandwidth resources and the continuously growing demand for cellular communication services, the channel assignment problem becomes increasingly important. To trace the optimal assignment, several heuristic strategies have been proposed. So far, most of them focus on the small-scale systems containing no more than 25 cells and they use an anachronistic cost model that does not satisfy the requirements of most existing cellular operators to measure the solution quality. Solving the small-scale channel assignment problems could not be applied into existing large scale cellular networks' practice. This article proposes a decomposition approach to solve the fixed channel assignment problem (FCAP) for large-scale cellular networks through partitioning the whole cellular network into several smaller sub-networks and then a sequential branch-and-bound algorithm is designed to solve the FCAP for them sequentially. The key issue of partition is to minimize the dependences of the sub-networks so that the proposed heuristics for solving smaller problems will suffer fewer constraints in searching better assignments. The experimental results show that the proposed algorithms perform well and we applied our algorithms in finding better assignments for the cellular network of the Taiwan Cellular Cooperation in ChungLi city.

In a mobile environment, a decision maker would usually like to query times, locations, and moving behaviors of certain mobile terminals. For example, a mobile transaction would like to know where is the next cell of its mobile clients and the probabilities that the mobile clients will move to the cells so that it could reserve appropriate channels for them. As a result, tracking the changing times and positions of mobile terminals capable of continuous movement is becoming increasingly necessary. However, current personal communication services (PCS) networks can only offer current maintained location information of non-idle mobile terminals. Pertinent researches predict location based on tangent velocity approaches. Location prediction based on tangent velocity is effective only within a short time interval. In this paper, we propose a model to model the moving behavior of each mobile terminal. From the moving behavior, we estimate and propose several location prediction functions for location query. The experimental results show that our proposed location prediction functions are accurate enough for regular moving mobile terminals.

We propose a new location tracking strategy called behavior-based strategy (BBS) based on each mobile's moving behavior. With the help of data mining technologies the moving behavior of each mobile could be mined from long-term collection of the mobile's moving logs. From the moving behavior of each mobile, we first estimate the time-varying probability of the mobile and then the optimal paging area of each time region is derived. To reduce unnecessary computation, we consider the location tracking and computational cost and then derive a cost model. A heuristics is proposed to minimize the cost model through finding the appropriate moving period checkpoints of each mobile. The experimental results show our strategy outperforms fixed paging area strategy currently used in the GSM system and time-based strategy for highly regular moving mobiles.

Due to the poverty of available bandwidth resources and increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. To trace optimal assignment, several algorithms have been proposed to minimize the amount of required channels. However, the total number of available frequencies are given and fixed in many situations. A new cost model is required for assigning channel in the cellular networks with limited bandwidth. We analyze the cost of each assignment in the view of damages from blocking calls and interfered by other frequencies. Furthermore, we formulate a new optimization problem for the fixed channel assignment problem by incorporating the limited bandwidth constraint into its cost model. To minimize the cost function, we adopt genetic approach to propose an evolutionary approach. Experimental results show that the cost function does reflect the quality of different assignments and also show that our algorithm does improve the solution quality significantly.

At least 43% of the human genome is occupied by repetitive elements. Moreover, around 51% of the rice genome is occupied by repetitive elements. The analysis of repetitive elements reveals that repetitive elements in our genome may have been very important in the evolutionary genomics. The first part of this study is to describe a database of repetitive elements - RSDB. The RSDB database contains repetitive elements, which are classified into the following categories: exact, tandem, and similar. The interfaces needed to query and show the results and statistical data, such as the relationship between repetitive elements and genes, cross-references of repetitive elements among different organisms, and so on, are provided. The second part of this study then attempts to mine the putative binding site for information on how combinations of the known regulatory sites and overrepresented repetitive elements in RSDB are distributed in the promoter regions of groups of functionally related genes. The overrepresented repetitive elements appearing in the associations are possible transcription factor binding sites. Our proposed approach is applied to Saccharomyces cerevisiae and the promoter regions of Yeast ORFs. The complete contents of RSDB and partial putative binding sites are available to the public at www.rsdb.csie.ncu.edu.tw. The readers may download partial query results.

In a location query process the most expensive procedure is maintaining the location information of mobiles. To reduce the expensive cost, we adopt the profile-based approach to design a behavior-based strategy (BBS) based on the moving behavior of each mobile generated by long-term collection of its moving history. We use a data mining technique to mine the moving behavior of each mobile and then estimate the probability that each mobile stays in each location at each time region given the last known location from its moving behavior. To reduce unnecessary computation, we consider the location tracking and computational cost and then derie a cost model. A greedy heuristic is proposed to minimize the cost modle through finding the appropriate checkpoints. The experimental results show our strategy outperforms fixed paging area strategy currently used in GSM or IS-54 system and time-based strategy for highly regular moving mobiles.

The hierarchical network structure significantly reduces the size and maintenance cost of routing table for huge networks. But in ad hoc networks, no fixed host leads to the challenge of the hierarchical structure, since the topology information needs to be updated dynamically due to membership changes caused by mobility. To construct the hierarchical structure of physical locations, we adopt a cluster infrastructure to partition the network into different groups for physical location maintenance. In order to construct the hierarchical structure of logical locations, all hosts are divided into several domains, each one of them has one corresponding domain location server to record all of the member physical locations (cluster locations). With the hierarchical structure, most necessary routing information can be ignored.