HaRim Jung

Digital tomosynthesis of the chest: Utility for detection of lung metastasis in patients with colorectal cancer

AIM To evaluate the performance of digital tomosynthesis (DT) of the chest for detection of lung nodules in patients with colorectal cancer (CRC). MATERIALS AND METHODS The institutional review board approved this study, and all patients provided informed consent. A commercial caesium iodide/amorphous silicon (CsI/a-Si) flat-panel detector system was used to verify the performance of the DT and chest radiography (XR) methods. DT was performed in 142 patients with CRC. All 142 patients underwent chest computed tomography (CT) within a week of DT. As a reference standard, two radiologists reviewed the chest CT in consensus and recorded the presence of pulmonary nodules. Another two radiologists independently observed the DT images and recorded the presence of pulmonary nodules. The status of all lung nodules was assessed either histologically or by follow-up over a period of 1 year. The nodules were classified into metastasis, benign, and uncertain. Statistical analysis of the results was performed. RESULTS Two hundred and thirty-seven nodules from 142 patients were found at CT. These included 71 proven metastases and 126 benign nodules; 40 nodules were uncertain. Observers detected 83% of all lung nodules and 93% of proven metastases using DT. Among 237 nodules, 147 nodules were larger than 4mm in diameter on the CT images. Observers detected 87% of lung nodules that were larger than 4mm. CONCLUSION Despite a reasonably low radiation dose, DT is a sensitive method, and is comparable to chest CT for the detection of lung nodules, particularly metastatic lung nodules in patients with CRC.

Processing generalized k-nearest neighbor queries on a wireless broadcast stream

In this paper, we investigate the problem of processing generalized k-nearest neighbor (GkNN) queries, which involve both spatial and non-spatial specifications for data objects, in a wireless broadcasting system. We present a method for processing GkNN queries on the broadcast stream. In particular, we propose a novel R-tree variant index structure, called the bit-vector R-tree (bR-tree), which stores additional bit-vector information to describe non-spatial attribute values of the data objects. In addition, each node in the bR-tree stores only one pointer to its children, which makes the bR-tree compact. We generate the broadcast stream by multiplexing the bR-tree and the data objects in the broadcasting channel. The corresponding search algorithm for the broadcast stream is also described. Through a series of comprehensive simulation experiments, we prove the efficiency of the proposed method with regard to energy consumption, latency, and memory requirement, which are the major performance concerns in a wireless broadcasting system. Furthermore, we test the practicality of the proposed method in a real prototype system.

QR-tree: An efficient and scalable method for evaluation of continuous range queries

Abstract In this paper, we explore the problem of the scalable evaluation of continuous range queries (CRQs) over moving objects, each of which continually retrieves the moving objects that are currently within a given query region of interest. Most existing methods assume that moving objects continually communicate with the server to report their current locations and the server continuously updates the results of queries. However, such an assumption degrades the system performance, because the communication cost is huge and the server workload is increased when the number of moving objects and queries is enormous. In this paper, we propose a novel query indexing structure, referred to as the Query Region tree (QR-tree), which allows the server to cooperate with moving objects efficiently by leveraging the available computational resources of the moving objects to improve the overall system performance. In addition, we present another version of the QR-tree, called the Bit-vector Query Region tree (BQR-tree), for the evaluation of CRQs that specify additional non-spatial selections. The BQR-tree stores a summary of the non-spatial information specified by CRQs in the form of bit-vectors. Through a series of comprehensive simulations, we verify the efficiency of the QR-tree and the BQR-tree in terms of the communication cost and server workload.

Cache Strategies for Semantic Prefetching Data

In this paper, we propose a Semantic Prefetching (SP) scheme as a new dissemination method for semantic information, using a dynamic caching strategy that considers a preference of user in Semantic Prefetching Area (SPA). Our contribution is that a proposed mechanism maintains query results in the cache before a user requests a query. In SP, an efficient algorithm for searching a prefetching description Fd is introduced with definitions, and we propose a new query processing algorithm with a Preference Priority Replacement (PPR) strategy to manage cache. Through an extensive performance analysis, we show that SP is superior to existing caching mechanisms for location-based services.

Towards real-time processing of monitoring continuous k-nearest neighbor queries

This paper addresses the problem of monitoring continuous k-nearest neighbor (k-NN) queries. In order to support highly dynamic environments, where objects and/or queries are frequently moving, monitoring continuous k-NN require real-time updated results when objects and/or queries change their locations. Thus, it is important to minimize time delay for maintaining up to date the results. In this paper, we present the monitoring method to shorten time delay for updating continuous k-NN queries based on the notion of result region and the minimum bounding rectangle enclosing all objects inside each cell, referred to as cMBR, in the main-memory grid index structure. Simulations are conducted to show the efficiency of the proposed method.

Evaluation of Content-Matched Range Monitoring Queries over Moving Objects in Mobile Computing Environments

A content-matched (CM) range monitoring query over moving objects continually retrieves the moving objects (i) whose non-spatial attribute values are matched to given non-spatial query values; and (ii) that are currently located within a given spatial query range. In this paper, we propose a new query indexing structure, called the group-aware query region tree (GQR-tree) for efficient evaluation of CM range monitoring queries. The primary role of the GQR-tree is to help the server leverage the computational capabilities of moving objects in order to improve the system performance in terms of the wireless communication cost and server workload. Through a series of comprehensive simulations, we verify the superiority of the GQR-tree method over the existing methods.

An Efficient Algorithm for Maximizing Range Sum Queries in a Road Network

Given a set of positive-weighted points and a query rectangle r (specified by a client) of given extents, the goal of a maximizing range sum (MaxRS) query is to find the optimal location of r such that the total weights of all the points covered by r are maximized. All existing methods for processing MaxRS queries assume the Euclidean distance metric. In many location-based applications, however, the motion of a client may be constrained by an underlying (spatial) road network; that is, the client cannot move freely in space. This paper addresses the problem of processing MaxRS queries in a road network. We propose the external-memory algorithm that is suited for a large road network database. In addition, in contrast to the existing methods, which retrieve only one optimal location, our proposed algorithm retrieves all the possible optimal locations. Through simulations, we evaluate the performance of the proposed algorithm.

A development of power consumption measurement system for Android smartphones

Smartphones are going to be more popular over the next five years and smartphone subscriptions will reach 6.1 billion in 2020. Moreover, mobile context-aware technologies and applications will be evolving more rapidly. However, smartphone users are always power-hungry. In order to solve such a problem, many researches for power measurement systems have been existed. But existing research have many limitations. In this paper, we propose to combine (i) the battery consumption information of users and (ii) log analyses, and develop a new power consumption measurement system, called the Log Analysis Consumption Report (LACR), which extends the open source of PowerTutor. The goal of our system is to measure the power consumed by WiFi, which is not supported by PowerTutor. The experiments performed on Galaxy S6 show that our system is much suitable for GalaxyS6 than existing methods.

Processing Continuous Range Queries with Non-spatial Selections

In this paper, we explore the problem of scalable evaluation of Continuous Range Queries (CRQs) with non-spatial selections, each of which continually retrieves the moving objects that (i) are currently within a specified spatial query region and (ii) satisfy specified non-spatial selections. We propose a new query indexing structure, called the Bit-vector Query Region tree (BQR-tree), which enables the server to cooperate with moving objects for evaluation of CRQs with non-spatial selections. Through simulations, we verify the efficiency of the BQR-tree.

Monitoring continuous k-nearest neighbor queries in the hybrid wireless network

In a mobile/pervasive computing environment, one of the most important goals of monitoring continuous spatial queries is to reduce communication cost for location-updates. Existing work uses many cellular wireless connections, which would easily become the performance bottleneck of the overall system. This paper introduces a novel continuous kNN query monitoring method to reduce communication cost in the hybrid wireless network, where the moving objects in the wireless broadcasting system construct the ad-hoc network. Simulation results prove the efficiency of the proposed method, which leverages the wireless broadcasting channel as well as the WiFi link to alleviate the burden on the cellular uplink communication cost.