Ming-Hui Jin

Personal paging area design based on mobile's moving behaviors

We propose a new location tracking strategy called behavior-based strategy (BBS) based on each mobiles moving behavior. With the help of data mining technologies the moving behavior of each mobile could be mined from long-term collection of the mobiles 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.

Homogeneous Features Utilization to Address the Device Heterogeneity Problem in Fingerprint Localization

Building context-aware services in pervasive computing environments have enabled the wide development of wireless local area network-based indoor positioning systems. In fingerprint localization, radio frequency (RF) signal strengths from access points (APs) are annotated with location labels to build the map of RF fingerprints. However, the newly received signal strength (RSS) variation due to device heterogeneity, which may cause RSS pattern mismatch, could jeopardize positioning accuracy. Solutions based on extra manual calibrations of RSSs for new, individual devices could address the problem. However, they are laborious and unpractical for real-world deployment. In this paper, an indoor positioning algorithm that utilizes two homogeneous features of different devices is proposed to solve the problem of device heterogeneity in fingerprint localization. The features of RSS order and linear dependency between RSSs measured by different devices are extensively investigated. The experimental results show that the proposed positioning algorithm solves the device heterogeneity problem without requiring extra manual calibration for diverse devices.

The Repetitive Sequence Database and Mining Putative Regulatory Elements in Gene Promoter Regions

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.

A hierarchical routing protocol for large scale ad hoc network

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.

Intelligent radio map management for future WLAN indoor location fingerprinting

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.

Agile Urban Parking Recommendation Service for Intelligent Vehicular Guiding System

Nowadays, Intelligent Transportation Systems (ITS) technologies are exploring a wide range of services such as freeway management, crash prevention & safety, driver assistance, and infotainment of drivers and/or passengers. In this paper, an agile urban parking recommendation service for vehicular intelligent guiding system is designed to facilitate city citizens with fully efficient, real-time and precise parking lot guiding suggestions for the sustainability of the future green city. The system offers drivers a friendly parking lot recommendation sequence and saves drivers time circling around by the accurate prediction of the successful parking probability in each parking lot. The proposed cost model constructs an optimal recommendation sequence considering successful parking probability and time to reach the parking lot. Through the collection and analysis of realistic records from parking lots in Taipei city, a prediction algorithm is developed to estimate the successful parking probability by using current available space counts. Extensive experiments are conducted to demonstrate the effectiveness of the prediction algorithm.

An evolutionary approach to fixed channel assignment problems with limited bandwidth constraint

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.

A Novel RSS-Based Indoor Positioning Algorithm Using Mobility Prediction

Severe received signal strength (RSS) fluctuation is one of the crucial problems in an indoor positioning system using fingerprint-based algorithms. Even at a fixed location, the RSSs received by a mobile device at different time have large discrepancy. Adopting these fluctuated signals for positioning may lead to inaccurate results. To mitigate this problem, in this paper, any of the existing fingerprint-based indoor positioning algorithms can be integrated into our positioning system to estimate the location of mobile device. Then, a mobility prediction algorithm using the model of Brownian motion is presented for further calculating the rationality of the estimated location and correcting the inaccurate results. To be realistic, some experiments in a real WLAN environment with a multitude of people moving in a testing area demonstrate the noticeably better accuracy of this approach. The solution can ensure low and stable positioning error. Besides, the region where training records are out of date can also be found out.

Location query based on moving behavior

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.

Innovative Wireless Dedicated Network for e-Bus

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.