Effectiveness of NAQ-tree in handling reverse nearest-neighbor queries in high-dimensional metric space

Reverse nearest-neighbor (RNN) query processing is important for many applications such as decision-support systems, profile-based marketing and molecular biology; consequently, RNN query processing has attracted considerable attention in the research community in recent years. Most existing approaches for RNN query processing either rely on nearest-neighbor pre-computation or work for specific data space (e.g., the Euclidean space). The only method for RNN query processing in metric space is based on the M-tree. In this paper, we propose an approach for RNN query processing in high-dimensional metric space using distance-based index structure (in particular, NAQ-tree that outperforms the other distance-based index structures as we have already verified in a previous study). In high-dimensional space, the properties of distance-based index structure provide strong pruning rules than the M-tree. In addition, unlike the previous work, our approach integrates the filtering and verification steps and uses the information obtained in the verification stage to further improve the filtering rate. Our approach delivers results incrementally and hence well serves real-time applications. The reported experimental results demonstrate the applicability and effectiveness of the proposed NAQ-tree-based RNN approach.     

Interactive 3D visualization for wireless sensor networks

Wireless sensor networks open up a new realm of ubiquitous computing applications based on distributed large-scale data collection by embedded sensor nodes that are wirelessly connected and seamlessly integrated within the environment. 3D visualization of sensory data is a challenging issue, however, due to the large number of sensors used in typical deployments, continuous data streams, and constantly varying network topology. This paper describes a practical approach for interactive 3D visualization of wireless sensor network data. A regular 3D grid is reconstructed using scattered sensor data points and used to generate view-dependent 2D slices that are consequently rendered with commodity graphics hardware leading to smooth visualization over space and time. Furthermore, the use of efficient space partitioning data structures and the independent processing of sensor data points facilitates interactive rendering for large number of sensors while accommodating constantly changing network topology. The practical value of the proposed method is demonstrated and results obtained for visualizing time-varying temperature distributions in an urban area are presented.     

Out-of-core detection of periodicity from sequence databases

In this paper, we address the scalability problem of periodicity detection for time series and sequence databases. We present time and space efficient periodicity detection method that efficiently uses external memory (disk) when the series cannot be processed inside the available main memory. Our approach uses suffix tree to facilitate periodicity detection. We consider two cases, namely in-core and out of core. First, we optimize storage requirements of the suffix tree to be able to fit larger suffix trees in-core. This guarantees the ability to mine larger sequences when everything can be kept in-core, which is what the current periodicity detection approaches are able to mine. Second, when the data structures go out of core, we extend the suffix tree construction part to use external memory. We are able to achieve this while maintaining linear time complexity. As a result, when we go out of core, we can mine databases that require considerably larger space to keep the data structures compared to the available main memory. For the out-of-core periodicity detection part, the proposed method allows the required data structures to be kept on external memory partially when a memory overflow situation occurs. Various pruning strategies are also proposed to allow the proposed approach to process large sequences within reasonable amount of time. Additionally, we introduced the notion of “emulated tree traversal” for fast suffix tree traversal. Due to all these special considerations, we are able to mine much larger sequences compared to other existing periodicity detection algorithms. To demonstrate the applicability, power, and effectiveness of the proposed framework, we present results of periodicity detection up to 500 MB of time sequence data, which (to the best of our knowledge) is the largest reported sequence mined for periodicity detection ever.     

Optimisation of X-ray examinations in Lithuania: start of implementation in mammography

Optimisation of medical X-ray examinations is very important for the enhancement of the reliability of the examination and for the reduction of the radiation dose to patients. Results of investigations of doses to patients during mammography using thermoluminescence dosemeters at different hospitals are presented together with a brief overview of the situation for mammography in Lithuania. It is shown that the entrance surface air kerma varies in a broad range and differed from hospital to hospital. Nevertheless the calculated values of average glandular dose (AGD) for a 'standard' breast being relatively high were comparable with those (3.2 mGy per exposure at net optical density 1.4) currently accepted by international authorities. Differences in AGD values evaluated at different hospitals demonstrate the existing potential for optimisation of the mammography screening procedures. The results of this investigation will be included in a database for patient doses in Lithuania and used for establishing a national reference dose level for mammography. Currently, reference levels recommended by international authorities are used in Lithuania.     

In-situ modification of natural fabrics by Cu-BTC MOF for effective release of insect repellent (<Emphasis Type="Italic">N,N</Emphasis>-diethyl-3-methylbenzamide)

Insect repellent fabrics are now of interest to secure human beings from the harmful effects of insects, but control the release of insect repellent from such fabrics is much important. The present study showed a good strategy to release effectively of N,N-diethyl-3-methylbenzamide (DEET) as insect repellent, from natural fabrics. Copper-benzene-1,3,5-tricarboxylic acid (Cu-BTC) as metal organic framework (MOF) material was in-situ incorporated into the matrix of natural fabrics including Cotton, Linen and Silk. DEET was then loaded onto the modified fabrics and the release of DEET from fabrics was studied. The successfulness of Cu-BTC incorporation was confirmed by scanning electron microscope, energy dispersive X-ray, X-ray diffraction and attenuated total reflectance—fourier transform infrared spectroscopy. The measured contents of Cu and Cu-BTC in fabrics were ranged in 35.9–38.9 and 115.4–130.3 mg/g fabrics, respectively. After loading the DEET into fabrics, the measured content of DEET was followed the order of Silk?<?Linen?<?Cotton and the modified fabrics exhibited much higher DEET by percent of 65–110%. Due to MOF modification, the released amount of DEET from fabrics was considerably increased by value of 205–220 mg/g and the release time became as long as 24–36 h. The release rate was fitted well to zero order model as the rate is independent of the reactant concentration. The so-obtained product can be applicable as disposable insect repellent materials for controllable and effective release of DEET for such a long residence time exceeded 9 days.     

Eco-friendly method to synthesize and characterize 2D nanostructured (1,2-bis(diphenyl-phosphino)ethyl) tungsten tetracarbonyl methyl red/copper oxide di-layer thin films

Three-layer thicknesses (\({T}_{1 }= 50\), \({T}_{2 }= 75\) and \({T}_{3 }= 100\) nm) of 1,2-bis(diphenylphosphino)ethyl tungsten tetracarbonyl methyl red (DPE-W-MR) were deposited onto the CuO thin film (50 nm) to produce DPE-W-MR/CuO di-layer thin films by sol–gel spin-coating technique. The composition and the chemical structure of the as-prepared thin films were characterized using various techniques including elemental analysis, Fourier transform infrared spectroscopy, \(^{1}\hbox {H}\)-NMR and X-ray diffraction (XRD). Scanning electron microscopy was used to investigate the size and shape of the CuO nanoparticles and the fabricated thin films. The films are crystalline as evidenced by the XRD pattern and DPE-W-MR has an orthorhombic crystal system. The crystallite size was calculated from an analysis of the line broadening features using the Scherrer formula; the average crystallite sizes of DPE-W-MR/CuO di-layer thin films are 52.92, 56.24 and 72.26 nm for \({T}_{1}\), \({T}_{2}\) and \({T}_{3}\), respectively. Thermogravimetric analysis and the thermal curve of DPE-W-MR complex were studied. Optical properties of DPE-W-MR/CuO di-layer thin films are discussed. The optical band gap energies of DPE-W-MR di-layer thin films/CuO decreased (2.25, 2.1 and 1.88 eV) as the film thickness increased (from \({T}_{1}\) to \({T}_{3})\). Based on the optical results and the quantum confinement effects, the DPE-W-MR/CuO di-layer thin films may be candidates as semiconductor materials for optoelectronic devices.     

Radiographic diagnosis of sacroiliitis--are sacroiliac views really better?

OBJECTIVE: To determine whether detailed oblique radiographs of the sacroiliac (SI) joints provide significant diagnostic advantage to a single AP projection of the pelvis in establishing the presence and severity of sacroiliitis. METHODS: Radiographs (both AP pelvis and detailed oblique projections) of 445 right SI joints and 442 left SI joints were obtained from patients with an established diagnosis of a seronegative spondyloarthropathy, and interpreted for severity. Data for the right and left SI joints were analyzed, comparing interpretations of severity based on AP pelvis projections with oblique views. RESULTS: Analysis of these data showed an agreement rate between AP views and SI views of 89.7% for the right SI joint radiographs and 86.4% for the left SI joint. There was no instance in which a patient with "unequivocal abnormalities"of the SI joints on the AP pelvis was read as having "normal" SI views. Similarly, there were no cases in which "normal" SI joints on AP pelvis films were read as having unequivocal abnormalities on SI views. CONCLUSION: In this group of patients with seronegative spondyloarthropathies, there was very close agreement between severity score of sacroiliitis from AP pelvis radiographs and SI joint views. We conclude that in most circumstances, the AP pelvis film will yield the diagnosis of sacroiliitis without the additional radiation exposure and expense related to specific SI joint radiographs.     

Replica selection strategies in data grid

Replication in Data Grids reduces access latency and bandwidth consumption. When different sites hold replicas of datasets, there is a significant benefit realized by selecting the best replica. By selecting the best replica, the access latency can be minimized. In this research, we propose two different replica selection techniques. To select the best replica from information gathered locally, a simple technique called the k-Nearest Neighbor (KNN) rule is exploited. The KNN rule selects the best replica for a file by considering previous file transfer logs indicating the history of the file and those nearby. We also propose a predictive technique to estimate the transfer time between sites. The predicted transfer time can be used as an estimate of transfer bandwidth of different sites that hold replica currently, and help in selecting the best replica among different sites. Simulation results demonstrate that the k-nearest algorithm shows a significant performance improvement over the traditional replica catalog based model. Besides, the neural network predictive technique estimates the transfer time among sites more accurately than the multi-regression model.     

Online mining of fuzzy multidimensional weighted association rules

This paper addresses the integration of fuzziness with On-Line Analytical Processing (OLAP) based association rules mining. It contributes to the ongoing research on multidimensional online association rules mining by proposing a general architecture that utilizes a fuzzy data cube for knowledge discovery. A data cube is mainly constructed to provide users with the flexibility to view data from different perspectives as some dimensions of the cube contain multiple levels of abstraction. The first step of the process described in this paper involves introducing fuzzy data cube as a remedy to the problem of handling quantitative values of dimensional attributes in a cube. This facilitates the online mining of fuzzy association rules at different levels within the constructed fuzzy data cube. Then, we investigate combining the concepts of weight and multiple-level to mine fuzzy weighted multi-cross-level association rules from the constructed fuzzy data cube. For this purpose, three different methods are introduced for single dimension, multidimensional and hybrid (integrates the other two methods) fuzzy weighted association rules mining. Each of the three methods utilizes a fuzzy data cube constructed to suite the particular method. To the best of our knowledge, this is the first effort in this direction. We compared the proposed approach to an existing approach that does not utilize fuzziness. Experimental results obtained for each of the three methods on a synthetic dataset and on the adult data of the United States census in year 2000 demonstrate the effectiveness and applicability of the proposed fuzzy OLAP based mining approach. OLAP is one of the most popular tools for on-line, fast and effective multidimensional data analysis. In the OLAP framework, data is mainly stored in data hypercubes (simply called cubes).