Task migration in three-dimensional meshes

As a result of the emerging use of mesh-based multicomputers (and recently mesh-based multiprocessor systems-on-chip), issues related to processor management have attracted much attention. In a mesh-based multiprocessor, after repeated submesh allocations and de-allocations, the system network may be fragmented, i.e. there might be unallocated nodes in the network. As a result, in a system with contiguous processor allocation, no new tasks can start running due to the lack of enough free adjacent processors to form a suitable submesh. Although there might be enough free processors available, they remain idle until the allocator can find a set of adjacent free nodes forming a submesh to be used for the new task. This can lead to low system performance. Task migration was introduced as a solution to this problem through migration of tasks running on some submeshes to other free areas in order to reduce fragmentation by chaining the newly freed areas and disengaging nodes to form larger submeshes. In this paper, we propose a novel structured and formulated way to code task migration, which is helpful for congestion detection in different steps of task migration algorithms. Moreover, considering the fact that the 3D mesh-based multicomputers are now very popular, a new task migration algorithm in 3D meshes is proposed. We also address the special case of the 2D migration in a 3D mesh multicomputer.     

An efficient optimal algorithm for the quantity discount problem in material requirement planning

An optimal algorithm based on branch-and-bound approach is presented in this paper to determine lot sizes for a single item in material requirement planning environments with deterministic time-phased demand and constant ordering cost with zero lead time, where all-units discounts are available from vendors and backlog is not permitted. On the basis of the proven properties of optimal order policy, a tree-search procedure is presented to construct the sequence of optimal orders. Some useful fathom rules have been proven, which make the algorithm very efficient. To compare the performance of this algorithm with the other existing optimal algorithms, an experimental design with various environments has been developed. Experimental results show that the performance of our optimal algorithm is much better than the performance of other existing optimal algorithms. Considering computational time as the performance measure, this algorithm is considered the best among the existing optimal algorithms for real problems with large dimensions (i.e. large number of periods and discount levels).     

Stability domains of the delay and PID coefficients for general time-delay systems

Time delays are encountered in many physical systems, and they usually threaten the stability and performance of closed-loop systems. The problem of determining all stabilising proportional-integral-derivative (PID) controllers for systems with perturbed delays is less investigated in the literature. In this study, the Rekasius substitution is employed to transform the system parameters to a new space. Then, the singular frequency (SF) method is revised for the Rekasius transformed system. A novel technique is presented to compute the ranges of time delay for which stable PID controller exists. This stability range cannot be readily computed from the previous methods. Finally, it is shown that similar to the original SF method, finite numbers of singular frequencies are sufficient to compute the stable regions in the space of time delay and controller coefficients.     

Profiling drivers based on driver dependent vehicle driving features

This work addresses the problem of profiling drivers based on their driving features. A purpose-built hardware integrated with a software tool is used to record data from multiple drivers. The recorded data is then profiled using clustering techniques. k-means has been used for clustering and the results are counterchecked with Fuzzy c-means (FCM) and Model Based Clustering (MBC). Based on the results of clustering, a classifier, i.e., an Artificial Neural Network (ANN) is trained to classify a driver during driving in one of the four discovered clusters (profiles). The performance of ANN is compared with that of a Support Vector Machine (SVM). Comparison of the clustering techniques shows that different subsets of the recorded dataset with a diverse combination of attributes provide approximately the same number of profiles, i.e., four. Analysis of features shows that average speed, maximum speed, number of times brakes were applied, and number of times horn was used provide the information regarding drivers’ driving behavior, which is useful for clustering. Both one versus one (SVM) and one versus rest (SVM) method for classification have been applied. Average accuracy and average mean square error achieved in the case of ANN was 84.2 % and 0.05 respectively. Whereas the average performance for SVM was 47 %, the maximum performance was 86 % using RBF kernel. The proposed system can be used in modern vehicles for early warning system, based on drivers’ driving features, to avoid accidents.     

Structural,optical and electrical properties of Cu<Subscript>2</Subscript>Zn<Subscript>1−x</Subscript>Cd<Subscript>x</Subscript>SnS<Subscript>4</Subscript> quinternary alloys nanostructures deposited on porous silicon

The Cu₂Zn_1?xCd_xSnS₄ quinternary alloy nanostructures with different Cd contents were grown using spin coating technique on porous silicon (63.93 %) substrate. The structural properties of Cu₂Zn_1?xCd_xSnS₄/PS were investigated by X-ray diffraction and field emission-scanning electron microscope (FE-SEM). The optical properties studied through photoluminescence technique, indicated that the band gap is shifted as Cd content increases from 1.84 eV at x = 0 to 1.76 eV at x = 1. The electrical characterization of the Ag/n-PS/Cu₂Zn_1?xCd_xSnS₄/Ag diode through current to voltage (I–V) characterization shows the highest photo-response of (value if any) at Cu₂Zn_0.4Cd_0.6SnS₄ composition.     

Quantum dot light emitting devices for photomedical applications

While OLEDs have struggled to find a niche lighting application that can fully take advantage of their unique form factors as thin, flexible, lightweight and uniformly large‐area luminaire, photomedical researchers have been in search of low‐cost, effective illumination devices with such form factors that could facilitate widespread clinical applications of photodynamic therapy (PDT) or photobiomodulation (PBM). Although existing OLEDs with either fluorescent or phosphorescent emitters cannot achieve the required high power density at the right wavelength windows for photomedicine, the recently developed ultrabright and efficient deep red quantum dot light emitting devices (QLEDs) can nicely fit into this niche. Here, we report for the first time the in‐vitro study to demonstrate that this QLED‐based photomedical approach could increase cell metabolism over control systems for PBM and kill cancerous cells efficiently for PDT. The perspective of developing wavelength‐specific, flexible QLEDs for two critical photomedical fields (wound repair and cancer treatment) will be presented with their potential impacts summarized. The work promises to generate flexible QLED‐based light sources that could enable the widespread use and clinical acceptance of photomedical strategies including PDT and PBM.     

Extracting 3D information on bone remodeling in the proximity of titanium implants in SRμCT image volumes

Bone-implant integration is measured in several ways. Traditionally and routinely, 2D histological sections of samples, containing bone and the biomaterial, are stained and analyzed using a light microscope. Such histological section provides detailed cellular information about the bone regeneration in the proximity of the implant. However, this information reflects the integration in only a very small fraction, a 10 μm thick slice, of the sample. In this study, we show that feature values quantified on 2D sections are highly dependent on the orientation and the placement of the section, suggesting that a 3D analysis of the whole sample is of importance for a more complete judgment of the bone structure in the proximity of the implant. We propose features describing the 3D data by extending the features traditionally used for 2D-analysis. We present a method for extracting these features from 3D image data and we measure them on five 3D SRμCT image volumes.We also simulate cuts through the image volume positioned at all possible section positions. These simulations show that the measurement variations due to the orientation of the section around the center line of the implant are about 30%.     

Agent-based multimedia presentation and adaptation service

In this paper, we aim to provide adaptive multimedia services especially video ones to end-users in an efficient and secure manner. Users moving outside the office should be able to maintain an office-like environment at their current locations. First, the agents within our proposed architecture negotiate the different communication and interaction factors autonomously and dynamically. Moreover, we needed to develop a user agent in addition to service and system agents that could negotiate the requirements and capabilities at run time to furnish best possible service results. Thus we designed and integrated a video indexing and key framing service within our overall agent-based architecture. We integrated this video indexing and content-based analysis service to adapt the video content according to run time conditions. We designed a video XML schema to validate the media content out of this multimedia service according to specific requirements and features, as we will describe later.

Adsorptive performance of penta-bismuth hepta-oxide nitrate, Bi?O?NO?, for removal of methyl orange dye

The adsorption of methyl orange dye from aqueous solution onto penta-bismuth hepta-oxide nitrate, Bi(5)O(7)NO(3), synthesized by precipitation method, was studied in a batch adsorption system. The effects of operation parameters such as adsorbent dose, initial dye concentration, pH and temperature were investigated. The adsorption equilibrium and mechanism of adsorption was evaluated by Langmuir and Freundlich isotherm and different kinetic models, respectively. The results indicate that adsorption is highly dependent on all operation parameters. At optimum conditions, the adsorption capacity was found to be 18.9 mg/g. The adsorption data fits well with the Langmuir isotherm model indicating monolayer coverage of adsorbate molecules on the surface of Bi(5)O(7)NO(3). The kinetic studies show that the adsorption process is a second-order kinetic reaction. Although intra-particle diffusion limits the rate of adsorption, the multi-linearity plot of intra-particle model shows the importance of both film and intra-particle diffusion as the rate-limiting steps of the dye removal. Thermodynamic parameters show that the adsorption process is endothermic, spontaneous and favourable at high temperature.