A Stream X-Machine Tool for Modelling and Generating Test Cases for Chronic Diseases Based on State-Counting Approach

Programming and Computer Software - In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents)...     

Large-scale SRAM-based IP lookup architectures using compact trie search structures

SRAM-based pipelined architectures for high-speed IP lookup using Field Programmable Gate Arrays (FPGAs) has recently attracted a great deal of attention from researchers. Due to the limited amount of on-chip memory and the number of I/O pins of FPGAs, compact data structures providing high memory efficiency are in great demand.     

Viscoelastic and Processing Effects on the Fiber-Matrix Interphase Strength. Part I. The Effects of Loading Rate, Test Temperature, Fiber Sizing and Global Strain Level

The effects of loading rate, fiber sizing, test temperature and global strain level on the adhesion strength between carbon fibers and a thermosetting epoxy (Epon 815) are studied using the single fiber fragmentation test procedure. Analytical methodology describing the viscoelastic behavior observed is also presented. The possibility of rate-temperature-interphase thickness superposition for the interfacial strength function is illustrated based on the analytical models discussed. Experimental data are discussed using Weibull statistics and also presented in the form of percent relative frequency histograms for the fiber fragments in a collective fashion. The use of histograms allows for interpretation of the skewness in the data population.     

Fabrication of chitosan/polyvinyl alcohol/amine modified carbon nanotube composite films for rapid chromate removal

Composite adsorbent films with amine and hydroxyl functionalities were synthesized from chitosan (CS), polyvinyl alcohol (PVA), and amine-modified carbon nanotubes (a-MWCNT) by solvent casting method. Weight proportions of CS to PVA and weight percent of a-MWCNT were optimized to achieve highest chromate removal capacity. Structural characteristics of the composites were investigated using scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy, and thermal gravimetric analysis. Accordingly, incorporation of a-MWCNT to CS/PVA structure resulted in the generation of nanochannels, which enhanced adsorption capacity. Moreover, the composite comprising 0.4% wt. a-MWCNT provided over 99% of Cr (VI) removal from 50 mg L⁻¹ Cr (VI) solution within five minutes of contact time. Redlich–Peterson and Radke–Prausnitz isotherm models provided the highest conformity to adsorption data. Maximum chromate sorption capacity of CS/PVA/a-MWCNT composite film was determined as 134.2 mg g⁻¹ being 172% higher than that of CS/PVA. Regeneration was best achieved in 1.0 M NaOH and the composite was shown to retain at least 70% of its original capacity after five consecutive adsorption–desorption cycles.     

Using an artificial bee colony algorithm for the optimal placement of viscous dampers in planar building frames

In this study, an Artificial Bee Colony Algorithm (ABCA) is used to obtain the optimal size and location of viscous dampers in planar buildings to reduce the damage to the frame systems during an earthquake. The transfer function amplitude of the top displacement and the elastic base shear force evaluated at the first natural circular frequency of structures are chosen as objective functions. The damper coefficients of the added viscous dampers are taken into consideration as design variables in a planar building frame. Transfer function amplitude of the top displacement and the amplitude of the elastic base shear force at the fundamental natural frequency are minimized under an active constraint on sum of the damper coefficients of the added dampers. According to two specified objective functions, an optimization algorithm based on the ABCA is proposed. The proposed method is verified by a gradient-based algorithm; steepest direction search algorithm (SDSA). The proposed ABCA and the SDSA are applied to find the optimal damper distribution for a nine-storey planar building then the optimal damper allocation obtained from the ABCA is investigated to rehabilitate models of irregular planar buildings. The validity of the proposed method was demonstrated through a time history analysis of the optimal damper designs, which were determined based on the frequency domain using the ABCA. The numerical results of the proposed optimal damper design method show that the use of the ABCA can be a practical and powerful tool to determine the optimal damper allocation in planar building structures.     

Multi-Modal Dialog Scene Detection Using Hidden Markov Models for Content-Based Multimedia Indexing

A class of audio-visual data (fiction entertainment: movies, TV series) is segmented into scenes, which contain dialogs, using a novel hidden Markov model-based (HMM) method. Each shot is classified using both audio track (via classification of speech, silence and music) and visual content (face and location information). The result of this shot-based classification is an audio-visual token to be used by the HMM state diagram to achieve scene analysis. After simulations with circular and left-to-right HMM topologies, it is observed that both are performing very good with multi-modal inputs. Moreover, for circular topology, the comparisons between different training and observation sets show that audio and face information together gives the most consistent results among different observation sets.     

Analyzing IT maintenance outsourcing decision from a knowledge management perspective

IT outsourcing is a complex and opaque decision problem. Managers facing a decision about IT outsourcing have difficulty in framing what needs to be thought about further in their discourses. Framing is one of the most crucial steps of human decision making and needs to be assisted to better understand a decision situation. In this research, we examine a number of decision primitives in the context of an IT outsourcing decision situation. We demonstrate how the decision primitives can be employed so that managers can probe deep to better understand a decision situation and to establish a decision basis. In the organizational setting, we exemplify the use of the decision primitives in relation to the perceived outsourcing implications for the managers looking for assistance in accommodating a knowledge management perspective on IT outsourcing. Consequently, we induce insight and a guideline on how to use knowledge management for effective outsourcing in one of the leading financial institutes in Europe.

Coordinating metaheuristic agents with swarm intelligence

Coordination of multi agent systems remains as a problem since there is no prominent method suggests any universal solution. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisation problems using metaheuristic algorithms. An idea for coordinating metaheuristic agents borrowed from swarm intelligence is introduced in this paper. This swarm intelligence-based coordination framework has been implemented as swarms of simulated annealing agents collaborated with particle swarm optimization for multidimensional knapsack problem. A comparative performance analysis is also reported highlighting that the implementation has produced much better results than the previous works.     

Adaptive Q control for tapping-mode nanoscanning using a piezoactuated bimorph probe

A new approach, called adaptive Q control, for tapping-mode atomic force microscopy (AFM) is introduced and implemented on a homemade AFM setup utilizing a laser Doppler vibrometer and a piezoactuated bimorph probe. In standard Q control, the effective Q factor of the scanning probe is adjusted prior to the scanning depending on the application. However, there is a trade-off in setting the effective Q factor of an AFM probe. The Q factor is either increased to reduce the tapping forces or decreased to increase the maximum achievable scan speed. Realizing these two benefits simultaneously using standard Q control is not possible. In adaptive Q control, the Q factor of the probe is set to an initial value as in standard Q control, but then modified on the fly during scanning when necessary to achieve this goal. In this article, we present the basic theory behind adaptive Q control, the electronics enabling the online modification of the probe's effective Q factor, and the results of the experiments comparing three different methods: scanning (a) without Q control, (b) with standard Q control, and (c) with adaptive Q control. The results show that the performance of adaptive Q control is superior to the other two methods.     

A simulated annealing algorithm for multi-agent systems: a job-shop scheduling application

In this paper, a parallel implementation of the modular simulated annealing algorithm for classical job-shop scheduling is presented. The implementation is for a multi agent system running on the distributed resource machine, which is a novel, scalable, distributed virtual machine based on Java technology. The problems tackled are well known, difficult benchmarks, widely used to measure the efficiency of metaheuristics with respect to both the quality of the solutions and the central processing unit time. The empirical results obtained show that the method proposed is successful in comparison with a sequential version of modular simulated annealing algorithm and other methods described in the literature.