Efficient schemes for similarity-aware refinement of aggregation queries

Interactive data exploration platforms in Web, business and scientific domains are becoming increasingly popular. Typically, users without prior knowledge of data interact with these platforms in an exploratory manner hoping they might retrieve the results they are looking for. One way to explore large-volume data is by posing aggregate queries which group values of multiple rows by an aggregate operator to form a single value: an aggregated value. Though, when a query fails, i.e., returns undesired aggregated value, users will have to undertake a frustrating trial-and-error process to refine their queries, until a desired result is attained. This data exploration process, however, is growing rather difficult as the underlying data is typically of large-volume and high-dimensionality. While heuristic-based techniques are fairly successful in generating refined queries that meet specified requirements on the aggregated values, they are rather oblivious to the (dis)similarity between the input query and its corresponding refined version. Meanwhile, enforcing a similarity-aware query refinement is rather a non-trivial challenge, as it requires a careful examination of the query space while maintaining a low processing cost. To address this challenge, we propose an innovative scheme for efficient Similarity-Aware Refinement of Aggregation Queries called (EAGER) which aims to balance the tradeoff between satisfying the aggregate and similarity constraints imposed on the refined query to maximize its overall benefit to the user. To achieve that goal, EAGER implements efficient strategies to minimize the costs incurred in exploring the available search space by utilizing similarity-based and monotonic-based pruning techniques to bound the search space and quickly find a refined query that meets users’ expectations. Our extensive experiments show the scalability exhibited by EAGER under various workload settings, and the significant benefits it provides.     

A semantic based Web page classification strategy using multi-layered domain ontology

World Wide Web is a continuously growing giant, and within the next few years, Web contents will surely increase tremendously. Hence, there is a great requirement to have algorithms that could accurately classify Web pages. Automatic Web page classification is significantly different from traditional text classification because of the presence of additional information, provided by the HTML structure. Recently, several techniques have been arisen from combinations of artificial intelligence and statistical approaches. However, it is not a simple matter to find an optimal classification technique for Web pages. This paper introduces a novel strategy for vertical Web page classification, which is called Classification using Multi-layered Domain Ontology (CMDO). It employs several Web mining techniques, and depends mainly on proposed multi-layered domain ontology. In order to promote the classification accuracy, CMDO implies a distiller to reject pages related to other domains. CMDO also employs a novel classification technique, which is called Graph Based Classification (GBC). The proposed GBC has pioneering features that other techniques do not have, such as outlier rejection and pruning. Experimental results have shown that CMDO outperforms recent techniques as it introduces better precision, recall, and classification accuracy.     

Emulation of complex open quantum systems using superconducting qubits

With quantum computers being out of reach for now, quantum simulators are alternative devices for efficient and accurate simulation of problems that are challenging to tackle using conventional computers. Quantum simulators are classified into analog and digital, with the possibility of constructing “hybrid” simulators by combining both techniques. Here we focus on analog quantum simulators of open quantum systems and address the limit that they can beat classical computers. In particular, as an example, we discuss simulation of the chlorosome light-harvesting antenna from green sulfur bacteria with over 250 phonon modes coupled to each electronic state. Furthermore, we propose physical setups that can be used to reproduce the quantum dynamics of a standard and multiple-mode Holstein model. The proposed scheme is based on currently available technology of superconducting circuits consist of flux qubits and quantum oscillators.     

Bifurcation control in a delayed two-neuron fractional network

The issue of bifurcation control for a delayed fractional network involving two neurons is concerned. Delay-dependent stability conditions and the bifurcation point are established by discussing the associated characteristic equation of the proposed network. Then, a delayed feedback controller is firstly designed to stabilize the Hopf bifurcation, and desirable dynamics is achieved. It is indicated that the designed controller is extremely effective which can postpone the onset of bifurcation by carefully selecting the feedback gain. Finally, simulation results are given to verify the efficiency of the theoretical results.     

An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows

Binary image representation is essential format for document analysis. In general, different available binarization techniques are implemented for different types of binarization problems. The majority of binarization techniques are complex and are compounded from filters and existing operations. However, the few simple thresholding methods available cannot be applied to many binarization problems. In this paper, we propose a local binarization method based on a simple, novel thresholding method with dynamic and flexible windows. The proposed method is tested on selected samples called the DIBCO 2009 benchmark dataset using specialized evaluation techniques for binarization processes. To evaluate the performance of our proposed method, we compared it with the Niblack, Sauvola and NICK methods. The results of the experiments show that the proposed method adapts well to all types of binarization challenges, can deal with higher numbers of binarization problems and boosts the overall performance of the binarization.     

SimClus: an effective algorithm for clustering with a lower bound on similarity

Clustering algorithms generally accept a parameter k from the user, which determines the number of clusters sought. However, in many application domains, like document categorization, social network clustering, and frequent pattern summarization, the proper value of k is difficult to guess. An alternative clustering formulation that does not require k is to impose a lower bound on the similarity between an object and its corresponding cluster representative. Such a formulation chooses exactly one representative for every cluster and minimizes the representative count. It has many additional benefits. For instance, it supports overlapping clusters in a natural way. Moreover, for every cluster, it selects a representative object, which can be effectively used in summarization or semi-supervised classification task. In this work, we propose an algorithm, SimClus, for clustering with lower bound on similarity. It achieves a O(log n) approximation bound on the number of clusters, whereas for the best previous algorithm the bound can be as poor as O(n). Experiments on real and synthetic data sets show that our algorithm produces more than 40% fewer representative objects, yet offers the same or better clustering quality. We also propose a dynamic variant of the algorithm, which can be effectively used in an on-line setting.     

GENOTOXICITY IN CHIRONOMUS KIIENSIS (CHIRONOMIDAE: DIPTERA) AFTER EXPOSURE TO POLLUTED SEDIMENTS FROM RIVERS OF NORTH PENINSULAR MALAYSIA: IMPLICATION FOR ECOTOXICOLOGICAL MONITORING

Rapid industrialization and urbanization has led to increasing input of chemical contaminants into the aquatic environment of Malaysia. Despite the threat civilization poses to the biota, there are still very few relevant studies on ecotoxicological testing of river ecosystems. To overcome this knowledge gap, we examined lethal and genotoxic effects of sediments from different rivers of the northern Malaysia against Chironomus kiiensis, a group well represented in the aquatic fauna of this region. We exposed the larvae to sediments from Selama River (SR), Permatang Rawa River (PRR) and Kilang Ubi River (KUR) at various durations (0, 6, 12, 24 and 48 h). The larval mortality was monitored, whereas DNA damage in survivors' cells was determined using the comet assay. Pollution level indexed by the amounts of heavy metals and other organic contaminants in the sediment showed progressive increases from SR to PRR to KUR. Highly polluted sediments (PRR to KUR) were detrimental to C. kiiensis larvae, most of which did not survive following exposure for long periods. DNA analyses revealed greater damages in nuclei derived from larvae maintained on polluted sediments, in particular, those from KUR. The effects on the genomic material of C. kiiensis larvae occurred in a time‐dependent manner, with damage level increasing as exposure time progressed. Our results highlight the genotoxic properties of polluted sediments. More importantly, this study showed that C. kiiensis larvae could respond to different levels of pollution with respect to exposure time. It is concluded that C. kiiensis larvae is a potential candidate for river ecotoxicological monitoring. Copyright © 2012 John Wiley & Sons, Ltd.     

Flexible and Autonomous Integrated System for Characterizing Metal Oxide Gas Sensor Response in Dynamic Environment

Characterization and calibration of gas sensor is a complex problem due to the dynamic behavior of gases and the limitations of current technology. This article reports a flexible, robust, and autonomous integrated system that is able to perform characterization on metal oxide-based gas sensors in dynamic environments. The system controls the concentration and flow of the relevant gases into the gas chamber and simultaneously measuring the sensor response. This feature allows the characterization of the sensor under continuous dynamic flow of gases similar to conditions on a robot or flow pipes. Several experiments have been performed on the system using hydrogen sulfide. The results provide information on the general characteristics of the sensor as well as its sensitivity. The noise levels were studied with different reference voltages. Overall, the results verify that the system is reliable and able to produce repeatable measurements.     

The future sustainability of water supply in Kuwait

Abstract

The main natural source of water available in Kuwait is the brackish groundwater located in the Kuwait Group and the Dammam aquifers, where the salinity ranges from 4300 to 10200 mg/l and from 2500 to 10000 mg/l, respectively. Limited fresh groundwater resources in Al‐Rawdhatain and Umm Al‐Aish fields, which have a salinity of 359 ‐1737 mg/l, are also available. Most of the groundwater in Kuwait is used for irrigation, domestic purposes, small‐scale industries and for blending with distilled water. Because rainfall is seasonal and less than annual evaporation, the recharge of the groundwater from rainfall is negligible. The objective of this paper is to assess the different water resources in Kuwait in order to make an integrated management plan and to focus on future sustainability. Generally, in the State of Kuwait, there is increasing pressure on the natural water resources because of the exploitation of the aquifers at a rate exceeding that of both the groundwater recharge and population growth (from 1.4 million in 1980 to 2.55 million in 2003). This has lead to the observed decline in groundwater level and to the deterioration of water quality. In the early 1950s, a plan was endorsed in Kuwait to establish seawater desalination plants. By 2005, six desalination plants have been established, with a total capacity of distillation units of 1434.72 ×103 m³/d (315.6 MIGD). However, the gross maximum consumption for the year 2003 reached a value of 1440.17 ×103 m³/d (316.8 MIGD), which is higher than the total capacity of the available distillation units. Given the limitation of conventional water and the shortages of non‐conventional water, along with the increasing population, Kuwait must consider the recycling of wastewater for irrigation, industrial or any other unrestricted non‐potable purpose.     

MODIFICATION OF GEOMETRY AND TECHNOLOGY OF CYLINDRICAL WORMS

The objective of this research is to develop a new method of grinding process that can efficiently make concave profile of the worm thread smooth. The grinding is carried out using a wheel with curvature profile in the axial plane in the form of an arc of logarithmic spiral. The proposed method will provide maximum line of contact between the tool and the worm with minimum stress concentration at any point. The generating equation of the grinding tool profile and its arrangement with respect to the worm during thread grinding were determined.