On problem transformability in VLSI

The two basic performance parameters that capture the complexity of any VLSI chip are the area of the chip,A, and the computation time,T. A systematic approach for establishing lower bounds onA is presented. This approach relatesA to the bisection flow, . A theory of problem transformation based on , which captures bothAT ² andA complexity, is developed. A fundamental problem, namely, element uniqueness, is chosen as a computational prototype. It is shown under general input/output protocol assumptions that any chip that decides ifn elements (each with (1+)lognbits) are unique must have =(nlogn), and thus, AT²=(n ²log² n), andA= (nlogn). A theory of VLSI transformability reveals the inherentAT ² andA complexity of a large class of related problems.This work was supported in part by the Semiconductor Research Corporation under contract RSCH 84-06-049-6.     

Swarm Intelligent Compressive Routing in Wireless Sensor Networks

This article proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs swarm intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate. The main contribution of this article is to extend swarm intelligence algorithms to build a routing tree in such a way that it can be utilized to maximize efficiency, thereby rectifying the delay problem of compressive sensing theory and improving the network lifetime. In addition, our approach offers accurate data recovery from small amounts of compressed data. Simulation results show that our approach can effectively extend the network lifetime of a large‐scale wireless sensor network.     

Effect of membrane characteristics on the performance of membrane bioreactors for oily wastewater treatment

Influence of membrane material and pore size on the performance of a submerged membrane bioreactor (sMBR) for oily wastewater treatment was investigated. The sMBR had a working volume of about 19 L with flat sheet modules at the same hydrodynamic conditions. Five types of micro- and ultra-polymeric membranes containing cellulose acetate (CA), cellulose nitrate (CN), polyamide (PA), polyvinylidene difluoride (PVDF) and polyethersulfone (PES) were used and their filtration performance in terms of permeability, permeate quality and fouling intensity were evaluated. Characterization of the membranes was done by performing some analysis such as pore size distribution; contact angle and scanning electronic microscopy (SEM) microphotograph on all membranes. The quality of permeates from each membrane was identified by measuring chemical oxygen demand (COD). The results showed more irreversible fouling intensity for membranes with larger pore size which can be due to more permeation of bioparticles and colloids inside the pores. Membrane characteristics have a major role in the preliminary time of the filtration before cake layer formation so that the PA with the highest hydrophilicity had the lowest permeability decline by fouling in this period. Also, the PVDF and PES membranes had better performance according to better permeate quality in the preliminary time of the filtration related to smaller pore size and also their better fouling resistance and chemical stability properties. However, all membranes resulted in the same permeability and permeate quality after cake layer formation. An overall efficiency of about 95% in COD removal was obtained for oily wastewater treatment by the membranes used in this study.     

“How do you know that I don’t understand?” A look at the future of intelligent tutoring systems

Many software systems would significantly improve performance if they could adapt to the emotional state of the user, for example if Intelligent Tutoring Systems (ITSs), ATM’s, ticketing machines could recognise when users were confused, frustrated or angry they could guide the user back to remedial help systems so improving the service. Many researchers now feel strongly that ITSs would be significantly enhanced if computers could adapt to the emotions of students. This idea has spawned the developing field of affective tutoring systems (ATSs): ATSs are ITSs that are able to adapt to the affective state of students. The term “affective tutoring system” can be traced back as far as Rosalind Picard’s book Affective Computing in 1997.This paper presents research leading to the development of Easy with Eve, an ATS for primary school mathematics. The system utilises a network of computer systems, mainly embedded devices to detect student emotion and other significant bio-signals. It will then adapt to students and displays emotion via a lifelike agent called Eve. Eve’s tutoring adaptations are guided by a case-based method for adapting to student states; this method uses data that was generated by an observational study of human tutors. This paper presents the observational study, the case-based method, the ATS itself and its implementation on a distributed computer systems for real-time performance, and finally the implications of the findings for Human Computer Interaction in general and e-learning in particular. Web-based applications of the technology developed in this research are discussed throughout the paper.     

Designing a cellular manufacturing system considering decision style,skill and job security by NSGA-II and response surface methodology

Cell formation is a traditional problem in cellular manufacturing systems that concerns the allocation of parts, operators and machines to the cells. This paper presents a new mathematical programming model for cell formation in which operators’ personality and decision-making styles, skill in working with machines, and also job security are incorporated simultaneously. The model involves the following five objectives: (1) minimising costs of adding new machines to and removing machines from the cells at the beginning of each period, (2) minimising total cost of material handling, (3) maximising job security, (4) minimising inconsistency of operators’ decision styles in cells and (5) minimising cost of suitable skill. On account of the NP-hard nature of the proposed model, NSGA-II as a powerful meta-heuristic approach is used for solving large-sized problems. Furthermore, response surface methodology (RSM) is used for tuning the parameters. Lastly, MOPSO and two scalarization methods are employed for validation of the results obtained. To the best of our knowledge, this is the first study that presents a multi-objective mathematical model for cell formation problem considering operators’ personality and skill, addition and removal of machines and job security.     

Cluster Size Optimization in Sensor Networks with Decentralized Cluster-Based Protocols

Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view.     

Thermal Stability Investigation of Synthesized Epoxy-Polyurethane/Silica Nanocomposites

Silicon - In this research, epoxy polyurethane-nano silica nanocomposites have been synthesized using an in-situ method, for which SiO2 nanocomposites had been initially ready in N,...     

Facile synthesis of different morphologies of Te-doped ZnO nanostructures

Te-doped ZnO nanostructures were synthesized by an annealing (vapor–solid) process under ambient conditions, and characterized in terms of their morphological, structural, compositional and optical properties. The structural and morphological characterizations revealed that the synthesized nanostructures were well-defined multipods, needles and spherical particles, and possessed well-crystalline ZnO wurtzite hexagonal phase. Also, in the X-ray diffraction studies, the presence of a shift in the peak positions towards a lower angle, and a decrease in the intensity, with an increase in the Te concentration, as compared to the undoped ZnO, were observed. The chemical composition confirmed the presence of Te, in the case of multipod and needle morphologies. The effect of doping on the crystalline quality and optical properties was also investigated, by using photoluminescence (PL) and Raman spectrometers. The Raman results demonstrated that the doped ZnO nanostructures had a lower crystalline quality than the undoped ZnO. Moreover, the PL results showed a decrease in the band gap for the doped ZnO nanostructures, in comparison to the undoped ZnO. A possible growth mechanism was also proposed.     

An optimal algorithm for rectilinear steiner trees for channels with obstacles

The channel rectilinear Steiner tree problem is to construct an optimal rectilinear Steiner tree interconnecting n terminals on the upper shore and the lower shore of a channel without crossing any obstacles inside the channel. However, intersecting boundaries of obstacles is allowed. We present an algorithm that computes an optimal channel rectilinear Steiner tree in O(F₁(k)n + F₂(k)) time, where k is the number of obstacles inside the channel and F₁ and F₂ are exponential functions of k. For any constant k the proposed algorithm runs in O(n) time.