An object replication algorithm for real-time distributed databases

A real-time distributed database system (RTDDBS) must maintain the consistency constraints of objects and must also guarantee the time constraints imposed by each request arriving at the system. Such a time constraint of a request is usually defined as a deadline period, which means that the request must be serviced on or before its time constraint. Servicing these requests may incur I/O costs, control-message transferring costs or data-message transferring costs. As a result, in our work, we first present a mathematical model that considers all these costs. Using this cost model, our objective is to service all the requests on or before their respective deadline periods and minimize the total servicing cost. To this end, from theoretical standpoint, we design a dynamic object replication algorithm, referred to as Real-time distributed dynamic Window Mechanism (RDDWM), that adapts to the random patterns of read-write requests. Using competitive analysis, from practical perspective, we study the performance of RDDWM algorithm under two different extreme conditions, i.e., when the deadline period of each request is sufficiently long and when the deadline period of each request is very short. Several illustrative examples are provided for the ease of understanding. Recommended by: Ashfaq Khokhar     

Topical delivery of paclitaxel for treatment of skin cancer

Context: Skin cancer represents the most growing types of cancer in human and ultraviolet radiation can be cited as one of the prime factor for its occurrence. Current therapy of skin cancer suffers from numerous side effects; for effective therapy, topical application of formulation of paclitaxel (PTX) can be considered as a novel approach.

Objective: The present study is an attempt to prepare formulation of solid lipid nanoparticles (SLN) of PTX for the effective treatment of various form of skin carcinoma.

Methods: The SLN were prepared by high-speed homogenization and ultrasonication method. The prepared SLN were characterized. The optimized PTX SLN were loaded in carbopol gel. The prepared gels were evaluated for its gelling properties and finally studied for in vivo anti-cancer efficacy and histopathological study.

Results: The particle size distribution was found to be in the range of 78.82–587.8?nm. The product yield (%) was found between 60% and 66% and showed a highest entrapment efficiency of 68.3%. The in vitro release of the drug from SLN dispersion was found to be biphasic with the initial burst effect, followed by slow release. SLN-loaded gel were subjected to permeability study and the results show steady-state flux (J_ss), permeability coefficient (K_p), and enhancement ratio were significantly increased in SLN-loaded gel formulation as compared with PTX-loaded gel. The histopathological study clearly reveals the efficacy of the SLN-F3 3G in the treatment of skin cancer.

Conclusion: The experimental formulations show controlled release of PTX and thus expected to show reduce dose-related side effects.     

On the design of communication-aware fault-tolerant scheduling algorithms for precedence constrained tasks in grid computing systems with dedicated communication devices

Fault-tolerant scheduling is an imperative step for large-scale computational Grid systems, as often geographically distributed nodes co-operate to execute a task. By and large, primary-backup approach is a common methodology used for fault tolerance wherein each task has a primary and a backup on two different processors. In this paper, we address the problem of how to schedule DAGs in Grids with communication delays so that service failures can be avoided in the presence of processors faults. The challenge is, that as tasks in a DAG have dependence on each other, a task must be scheduled to make sure that it will succeed when any of its predecessors fails due to a processor failure. We first propose a communication model and determine when communications between a backup and backups of its successors are necessary. Then we determine when a backup can start and its eligible processors so as to guarantee that every DAG can complete upon any processor failure. We develop two algorithms to schedule backups, which minimize response time and replication cost, respectively. We also develop a suboptimal algorithm which targets minimizing replication cost while not affecting response time. We conduct extensive simulation experiments to quantify the performance of the proposed algorithms.     

Access Time Minimization for Distributed Multimedia Applications

The problem of minimizing the access time of a requested multimedia (MM) document on a network based environment is addressed. A generalized version of this problem is formulated and retrieval strategies that minimize the access time of the user-requested MM document from a pool of MM servers are proposed. To this end, we design single-installment and multi-installment MM document retrieval strategies, through which the minimization of access time can be carried out. The main idea is to utilize more than one MM server in downloading the requested document. Each server assumes the responsibility of uploading a predetermined portion of the entire document in a particular order. Single- and multi-installment strategies differ in the number of disjoint document pieces each server sends to the client. We first introduce a directed flow graph (DFG) model to represent the retrieval process and generate a set of recursive equations using this DFG. Then, we derive closed-form solutions for the portions of the MM document downloaded from the various servers and the corresponding access time. We present rigorous analysis for these two strategies and show their performance under MPEG-I and MPEG-II video streams playback rates. Their behavior under different network bandwidths is also examined, revealing in-depth information about their expected performance. We also show that in the case of a multi-installment strategy, the access time can be completely controlled by fine tuning the number of installments. Since the number of installments is software tunable, the adaptive nature of the strategies to different channel bandwidths is also demonstrated. Important trade-off studies with respect to the number of servers involved in the retrieval process and the number of installments are presented. In the case of a heterogeneous network employing a single-installment strategy, we prove that the access time is independent of the server sequence used. Illustrative examples are provided for ease of understanding.     

Selection criteria of induction machines for speed-sensorless drive applications

Induction motors, both three and single phase, are used extensively for adjustable-speed drives' applications. These machines are structurally very robust and are a primary source of motive power and speed control where DC machines cannot be used. For closed-loop control of these machines, sensorless speed estimation is usually preferred. Among the current estimation techniques available for speed-sensorless induction motor drives, speed measurement based on rotor-slot-related harmonic detection in machine line current happens to be a prominent one. While these harmonics can be strong in certain kinds of machines, some other machines may exhibit very weak rotor slot harmonics that can be obscured by noise. Skewing, slot shapes and types, structural unbalances, etc., also have a prominent effect on the detectability of these harmonics. This paper attempts to investigate this problem based on the interaction of pole pairs, number of rotor bars, and stator winding. Although the analysis and experimental results have been mainly provided for three-phase squirrel-cage induction motors, single-phase and slip-ring induction motors have also been addressed. Further, it has been shown that eccentricity-related fault detection could also be easily accommodated with this kind of speed detection technique at no or negligible extra cost when certain motors are selected.     

Iodine speciation studies on Bunsen reaction of S–I cycle using spectroscopic techniques

Bunsen reaction is an important step of sulfur–iodine cycle for hydrogen production from thermochemical splitting of water. Polyiodide species generated during the separation process need to be identified for complete understanding of the mechanism involved. Speciation of these polyiodide species formed during Bunsen reaction can lead to better understanding of kinetics of the process. HIx species formed have been analyzed using UV–visible and Raman spectroscopic techniques. Peak corresponding to HI₃ species have been ascertained and their conversion to higher HI₅, HI₇ …… species has been observed.     

Microwave Hydrothermally Synthesized Nanocrystalline Co-Zn Ferrites

Co-Zn ferrite nano-powder was synthesized using the Microwave- Hydrothermal (M-H) method. The powder was characterized using X-ray diffraction (XRD), Transmission Electron Microscopy (TEM), and Fourier Transform Infrared spectroscopy (FT-IR). The densification of nanoferrites was done using two methods: a) conventional and b) microwave sintering. Electrical and magnetic properties of the sintered samples were measured at room temperature. Electrical properties such as dielectric constant (?'), dissipation factor (D), initial permeability (μ_i) and quality factor (Q) were measured over a wide frequency range (10 kHz to 1 MHz). The Curie temperature has been determined from the permeability versus temperature plots. It was found that the enhanced electrical and magnetic properties were observed for microwave sintered samples.     

Calculus of fuzzy hierarchical censored production rules (FHCPRs)

The article addresses the problem of reasoning under time constraints with incomplete, vague, and uncertain information. It is based on the idea of Variable Precision Logic (VPL), introduced by Michalski and Winston, which deals with both the problem of reasoning with incomplete information subject to time constraints and the problem of reasoning efficiently with exceptions. It offers mechanisms for handling trade-offs between the precision of inferences and the computational efficiency of deriving them. As an extension of Censored Production Rules (CPRs) that exhibit variable precision in which certainty varies while specificity stays constant, a Hierarchical Censored Production Rules (HCPRs) system of Knowledge Representation proposed by Bharadwaj and Jain exhibits both variable certainty as well as variable specificity. Fuzzy Censored Production Rules (FCPRs) are obtained by augmenting ordinary fuzzy conditional statement: “if X is A then Y is B” (or A(x) ⇒ B(y) for short) with an exception condition and are written in the form: “if X is A then Y is B unless Z is C” (or A(x) ⇒ B(y) ∥ C(z)). Such rules are employed in situations in which the fuzzy conditional statement “if X is A then Y is B” holds frequently and the exception condition “Z is C” holds rarely. Thus, using a rule of this type we are free to ignore the exception condition, when the resources needed to establish its presence are tight or there simply is no information available as to whether it holds or does not hold. Thus if … then part of the FCPR expresses important information while the unless part acts only as a switch that changes the polarity of “Y is B” to “Y is not B” when the assertion “Z is C” holds. Our aim is to show how an ordinary fuzzy production rule on suitable modifications and augmentation with relevant information becomes a Fuzzy Hierarchical Censored Production Rules (FHCPRs), which in turn enables to resolve many of the problems associated with usual fuzzy production rules system. Examples are given to demonstrate the behavior of the proposed schemes. © 1996 John Wiley & Sons, Inc.     

On the design of high-performance algorithms for aligning multiple protein sequences on mesh-based multiprocessor architectures

In this paper, we address the problem of multiple sequence alignment (MSA) for handling very large number of proteins sequences on mesh-based multiprocessor architectures. As the problem has been conclusively shown to be computationally complex, we employ divisible load paradigm (also, referred to as divisible load theory, DLT) to handle such large number of sequences. We design an efficient computational engine that is capable of conducting MSAs by exploiting the underlying parallelism embedded in the computational steps of multiple sequence algorithms. Specifically, we consider the standard Smith–Waterman (SW) algorithm in our implementation, however, our approach is by no means restrictive to SW class of algorithms alone. The treatment used in this paper is generic to a class of similar dynamic programming problems. Our approach is recursive in the sense that the quality of solutions can be refined continuously till an acceptable level of quality is achieved. After first phase of computation, we design a heuristic scheme that renders the final solution for MSA. We conduct rigorous simulation experiments using several hundreds of homologous protein sequences derived from the Rattus Norvegicus and Mus Musculus databases of olfactory receptors. We quantify the performance based on speed-up metric. We compare our algorithms to serial or single machine processing approaches. We testify our findings by comparing with conventional equal load partitioning (ELP) strategy that is commonly used in the parallel processing literature. Based on our extensive simulation study, we observe that DLT paradigm offers an excellent speed-up characteristics and provides avenues for its use in several other biological sequence processing related problem. This study is a first time attempt in using the DLT paradigm to devise efficient strategies to handle large scale multiple protein sequence alignment problem on mesh-based multiprocessor systems.