An Indexing Method for Answering Queries on Moving Objects

We consider the problem of indexing a set of objects moving in d-dimensional spaces along linear trajectories. A simple external-memory indexing scheme is proposed to efficiently answer general range queries. The following are examples of the queries that can be answered by the proposed method: report all moving objects that will (i) pass between two given points within a specified time interval; (ii) become within a given distance from some or all of a given set of other moving objects. Our scheme is based on mapping the objects to a dual space, where queries about moving objects are transformed into polyhedral queries concerning their speeds and initial locations. We then present a simple method for answering such polyhedral queries, based on partitioning the space into disjoint regions and using a B+-tree to index the points in each region. By appropriately selecting the boundaries of each region, we guarantee an average search time that matches a known lower bound for the problem. Specifically, for a fixed d, if the coordinates of a given set of N points are statistically independent, the proposed technique answers polyhedral queries, on the average, in O((N/B)^1−1/d⋅(log _B N)^1/d+K/B) I/O's using O(N/B) space, where B is the block size, and K is the number of reported points. Our approach is novel in that, while it provides a theoretical upper bound on the average query time, it avoids the use of complicated data structures, making it an effective candidate for practical applications. The proposed index is also dynamic in the sense that it allows object insertion and deletion in an amortized update cost of log _B(N) I/O's. Experimental results are presented to show the superiority of the proposed index over other methods based on R-trees. recommend Ahmed Elmagarmid     

Data mining-based materialized view and index selection in data warehouses

Materialized views and indexes are physical structures for accelerating data access that are casually used in data warehouses. However, these data structures generate some maintenance overhead. They also share the same storage space. Most existing studies about materialized view and index selection consider these structures separately. In this paper, we adopt the opposite stance and couple materialized view and index selection to take view–index interactions into account and achieve efficient storage space sharing. Candidate materialized views and indexes are selected through a data mining process. We also exploit cost models that evaluate the respective benefit of indexing and view materialization, and help select a relevant configuration of indexes and materialized views among the candidates. Experimental results show that our strategy performs better than an independent selection of materialized views and indexes.     

A new model for the hazardous waste location-routing problem

Hazardous waste management involves the collection, transportation, treatment and disposal of hazardous wastes. In this paper a new multiobjective location-routing model is proposed. Our model also includes some constraints, which were observed in the literature but were not incorporated into previous models. The aim of the proposed model is to answer the following questions: where to open treatment centers and with which technologies, where to open disposal centers, how to route different types of hazardous waste to which of the compatible treatment technologies, and how to route waste residues to disposal centers. The model has the objective of minimizing the total cost and the transportation risk. A large-scale implementation of the model in the Central Anatolian region of Turkey is presented.     

Dynamic storage and access load balancing for answering range queries in peer-to-peer networks

Recently, many applications have used Peer-to-Peer (P2P) systems to overcome the current problems with client/server systems such as non-scalability, high bandwidth requirement and single point of failure. In this paper, we propose an efficient scheme to support efficient range query processing over structured P2P systems, while balancing both the storage load and access load. The paper proposes a rotating token scheme to balance the storage load by placing joining nodes in appropriate locations in the identifier space to share loads with already overloaded nodes. Then, to support range queries, we utilize an order-preserving mapping function to map keys to nodes in order preserving way and without hashing. This may result in an access load imbalance due to non-uniform distribution of keys in the identifier space. Thus, we propose an adaptive replication scheme to relieve overloaded nodes by shedding some load on other nodes to balance the access load. We derive a formula for estimating the overhead of the proposed adaptive replication scheme. In this study, we carry simulation experiments with synthetic data to measure the performance of the proposed schemes. Our simulation experiments show significant gains in both storage load balancing and access load balancing.     

RF MEMS continuous reversible variable inductor based on a microfluidic network

In this work, RF MEMS continuous reversible variable inductor has been fabricated by using microelectronic technology and lamination process. We review, evaluate and compare this variable inductor with other work. The proposed inductor is a dual circular coil and has an inductance of few nH. The fundamental idea is to place a liquid droplet between the metal turns of a coil in order to modify the capacitive/resistive coupling between metal tracks and hence to change the stored magnetic energy. The SU-8 resin was used to realize the microfluidic channels and Au as metallic tracks. To prove the reversibility of the inductor, two cases were studied: filling and emptying of channels. The tuning range of the inductance is approximately 107 % at 1.6 GHz, making these devices very suitable as building blocks in many RF applications.     

Analysis of the human immune response to vaccinia by use of a novel protein microarray suggests that antibodies recognize less than 10% of the total viral proteome

Control of smallpox by mass vaccination was one of the most effective public health measures ever employed for eradicating a devastating infectious disease. However, new methods are needed for monitoring smallpox immunity within current vulnerable populations, and for the development of replacement vaccines for use by immunocompromized or low-responding individuals. As a measure for achieving this goal, we developed a protein microarray of the vaccinia virus proteome by using high-throughput baculovirus expression and purification of individual elements. The array was validated with therapeutic-grade, human hyperimmune sera, and these data were compared to results obtained from individuals vaccinated against smallpox using Dryvax. A high level of reproducibility with a very low background were apparent in repetitive assays that confirmed previously reported antigens and identified new proteins that may be important for neutralizing viral infection. Our results suggest that proteins recognized by antibodies from all vaccinees constituted <10% of the total vaccinia proteome.     

An analysis of BioHashing and its variants

As a result of the growing demand for accurate and reliable personal authentication, biometric recognition, a substitute for or complement to existing authentication technologies, has attracted considerable attention. It has recently been reported that, along with its variants, BioHashing, a new technique that combines biometric features and a tokenized (pseudo-) random number (TRN), has achieved perfect accuracy, having zero equal error rates (EER) for faces, fingerprints and palmprints. There are, however, anomalies in this approach. These are identified in this paper, in which we systematically analyze the details of the approach and conclude that the claim of having achieved a zero EER is based upon an impractical hidden assumption. We simulate the claimants’ experiments and find that it is not possible to achieve their reported performance without the hidden assumption and that, indeed, the results are worse than when using the biometric alone.     

Argon plasma treatment of glass surfaces

The effect of argon plasma treatment of glass surfaces is studied by FTIR and SEM. The argon plasma on cleaned glass surfaces resulted in increased surface area due to microetching and surface rearrangement of the silicate network as indicated by the observed changes in the Si-O stretching infrared absorption. The result was a relative increase in surface hydrophilicity which could be optimized by the plasma reaction conditions. The etching action of the argon plasma on the substrate surfaces facilitated the removal of the micrometre thick sizing from the commercial fibres accompanied by little loss in tensile strength. Plasma was also used to graft selected monomers to the surface of glass fibres for enhancement of bond compatibility in a composite system. This grafting treatment was followed by an argon etching step. The argon plasma action on the coated surfaces improved the wettability further and increased the sur face area. Changes in surface chemistry that accompanied the argon etching treatment were very subtle in the case of the plasma polymer of allylamine, but proved significant in the case of the plasma polymer of hexamethyldisiloxane. On the latter surfaces, rearrangement of the siloxane (Si-O-Si) bonds to silylmethylene (Si-(CH₂) _n -Si) groups is suggested.     

Supplier selection with an integrated methodology in unknown environment

This paper proposes an integrated methodology and its solution for supplier selection problem. A two-stage stochastic programming model and fuzzy TOPSIS methods are consolidated in this methodology. After pre-research phase, in the second part of the methodology, fuzzy TOPSIS is used for ranking potential suppliers considering qualitative data under fuzzy environment. In the third part of the methodology a group of ranked potential suppliers are included in a two-stage stochastic programming model for evaluation. In the two-stage stochastic programming model demand is assumed as uncertain and different scenarios are generated for this parameter. With this methodology, supplier evaluation procedure can be done in unknown environment. Our methodology is interested with a problem in multi-product, multi-period and multi-sourcing environment.