Fault tolerant control for RP* architecture of Scalable Distributed Data Structures

Scalable Distributed Data Structures consist of two components dynamically spread across amulticomputer: records belonging to a file and a mechanism controlling record placement in thefile space. Record (data) faults may lead to invalid computations at most, while record placementfaults may bring whole file to crash. In this paper, extended SDDS RP* (Range Partitioning)architecture tolerant to the latter faults is presented and evaluated

Fault-tolerant control for Scalable Distributed Data Structures

calable Distributed Data Structures (SDDS) can be applied for multicomputers. Multicomputers were developed as a response to market demand for scalable and dependable but not expensive systems. SDDS consists of two components dynamically spread across a multicomputer: records belonging to a file and a mechanism controlling record placement in the file. Methods of making records of the file more or less fault-tolerant have already been given. Methods of making the mechanism controlling record placement in the file fault-tolerant have not been studied, yet, although it seems that this is more important for the system dependability than record fault tolerance. Faults in control may lead an application to crash, while record data faults may cause invalid computations at most. In the paper a fault-tolerant control for SDDS is given. It is based on an application of Job Comparison Technique along with TMR. Time overhead due to redundancy introduced is estimated, too

An Application of Expectation-Maximization for Model Verification

A description which summarizes entire and usually big set of data is called its model. The problem investigated in the paper consists in verification of models of data coming from a simulation experiment of selecting candidates for operators of mobile robot (more strictly building reliable predictive model of the data). The models are validated using train-and-test method and verified with the help of the EM (expectation-maximization) algorithm which was originally designed for solving clustering problems with missing data. Actually, the selecting is a clustering problem because the candidates are assigned to ‘chosen’, ‘accepted’ or ‘rejected’ subgroups. For such a case the missing data is the category (the subgroup) for which a candidate should be assigned on the basis of his activity measured during the simulation experiment. The paper explains the procedure of model verification. It also shows experimental results and draws conclusions

SDDSfL vs. local disk - a comparative study for Linux

Efficient data management and distribution in a multicomputer is a subject of much research. Distributed file systems are the most common solution of this problem, however, recent works are focused on more general data distribution protocols. Scalable, Distributed Data Structures (SDDS) are another promising approach to this issue. In this paper we discuss the efficiency of an implementation of SDDS in various applications. The results of experiments are presented

An implementation of articial advisor for dynamic classication of objects

The paper presents an original method of dynamic classication of objects from a new domain which lacks an expert knowledge. The method relies on analysis of attributes of objects being classied and their general quality Q, which is a combination of particular object's attributes. The method uses a test of normality as a basis for computing the reliability factor of the classication (rfc), which indicates whether the classication and the model of quality Q are reliable. There is no need to collect data about all objects before the classication starts and possibly the best objects ale selected dynamically (on-the-y) while data concerning consecutive objects are gathered. The method is implemented as a software tool called Articial Classication Adviser (ACA). Moreover, the paper presents a case study, where the best candidates for reghting mobile robot operators are selected

Cytotoxicity induced by cypermethrin in Human Neuroblastoma Cell Line SH-SY5Y

The purpose of this study was to evaluate the cytotoxic potential of Cypermethrin (CM) on cultured human Neuroblastoma SH-SY5Y cells. SH-SY5Y cells were treated with CM at 0–200µM for 24, 48, and 72 h, in vitro . It was found that CM induced the cell death of Neuroblastoma cells in a dose- and time-dependent manner, as shown by LDH assays. Next, some aspects of the process of cell death triggered by CM in the human SH-SY5Y cell line were investigated. It was revealed that the pan-caspase inhibitor Q-VD-OPh, sensitizes SH-SY5Y cells to necroptosis caused by CM. Furthermore, signal transduction inhibitors PD98059, SL-327, SB202190, SP600125 failed to attenuate the effect of the pesticide. Finally, it was shown that inhibition of TNF-a by Pomalidomide (PLD) caused statistically significant reduction in CM-induced cytotoxicity. Overall, the data obtained suggest that CM induces neurotoxicity in SH-SY5Y cells by necroptosis

Enriching WPCs and NFPCs with Carbon Nanotubes and Graphene.

Carbon nanotubes (CNTs) and graphene, with their unique mechanical, electrical, thermal, optical, and wettability properties, are very effective fillers for many types of composites. Recently, a number of studies have shown that CNTs and graphene may be integrated into wood-plastic composites (WPCs) and natural-fibre-reinforced polymer composites (NFPCs) to improve the existing performance of the WPCs/NFPCs as well as enabling their use in completely new areas of engineering. The following review analyses the results of the studies presented to date, from which it can be seen that that inclusion of CNTs/graphene may indeed improve the mechanical properties of the WPCs/NFPCs, while increasing their thermal conductivity, making them electroconductive, more photostable, less sensitive to water absorption, less flammable, and more thermally stable. This study indicates that the composition and methods of manufacturing of hybrid WPCs/NFPCs vary significantly between the samples, with a consequent impact on the level of improvement of specific properties. This review also shows that the incorporation of CNTs/graphene may enable new applications of WPCs/NFPCs, such as solar thermal energy storage devices, electromagnetic shielding, antistatic packaging, sensors, and heaters. Finally, this paper recognises key challenges in the study area, and proposes future work