Genetic Parallel Programming: design and implementation

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.     

Achieving balance between proximity and diversity in multi-objective evolutionary algorithm

Currently, an alternative framework using the hypervolume indicator to guide the search for elite solutions of a multi-objective problem is studied in the evolutionary multi-objective optimization community very actively, comparing to the traditional Pareto dominance based approach. In this paper, we present a dynamic neighborhood multi-objective evolutionary algorithm based on hypervolume indicator (DNMOEA/HI), which benefits from both Pareto dominance and hypervolume indicator based frameworks. DNMOEA/HI is featured by the employment of hypervolume indicator as a truncation operator to prune the exceeded population, while a well-designed density estimator (i.e., tree neighborhood density) is combined with the Pareto strength value to perform fitness assignment. Moreover, a novel algorithm is proposed to directly evaluate the hypervolume contribution of a single individual. The performance of DNMOEA/HI is verified on a comprehensive benchmark suite, in comparison with six other multi-objective evolutionary algorithms. Experimental results demonstrate the efficiency of our proposed algorithm. Solutions obtained by DNMOEA/HI well approach the Pareto optimal front and are evenly distributed over the front, simultaneously.     

A multi-objective genetic algorithm approach to rule mining for affective product design

A novel multi-objective genetic algorithm (GA)-based rule-mining method for affective product design is proposed to discover a set of rules relating design attributes with customer evaluation based on survey data. The proposed method can generate approximate rules to consider the ambiguity of customer assessments. The generated rules can be used to determine the lower and upper limits of the affective effect of design patterns. For a rule-mining problem, the proposed multi-objective GA approach could simultaneously consider the accuracy, comprehensibility, and definability of approximate rules. In addition, the proposed approach can deal with categorical attributes and quantitative attributes, and determine the interval of quantitative attributes. Categorical and quantitative attributes in affective product design should be considered because they are commonly used to define the design profile of a product. In this paper, a two-stage rule-mining approach is proposed to generate rules with a simple chromosome design in the first stage of rule mining. In the second stage of rule mining, entire rule sets are refined to determine solutions considering rule interaction. A case study on mobile phones is used to demonstrate and validate the performance of the proposed rule-mining method. The method can discover rule sets with good support and coverage rates from the survey data.     

Oscillation and convergence behaviours exhibited in an ‘unstable’ second‐order digital filter with saturation‐type non‐linearity

This letter explains the oscillatory behaviours exhibited in a second‐order digital filter with saturation‐type non‐linearity via the Hopf bifurcation theorem. It is shown that depending on the bifurcation parameter, the state variables may converge to zero even when the eigenvalues of the system matrix are outside the unit circle. Copyright © 2004 John Wiley & Sons, Ltd. abstract     

Policy Based Mobility &; Flow Management for IPv6 Heterogeneous Wireless Networks

We propose a dynamic mobility management framework for Internet Protocol version 6 (IPv6) and policy enforcement enabled heterogenous wireless networks. Policies and policy rules are defined depending on network infrastructure facilities, service agreements and negotiation results. Each traffic is coupled with an identifiable traffic flow while the heterogenous interface flow bindings are regulated by polices. The network selection, flow distribution, handovers and mobility procedures are flexible and we propose to improve the decision making via Multiple Attributes Decision Making (MADM). Techniques considered in the framework include the IPv6 based Network Mobility (NEMO), multihoming capability, transparent vertical handovers, horizontal handovers and dynamic policy enforcement matching process to improve the Quality of Service (QoS), Quality of Experience (QoE) and ubiquitous connectivity. A experiment testbed and simulation models have been constructed to verify the mobility framework performance in a heterogeneous WiFi, WiMax and UMTS hybrid environment.     

The impact of property price on construction output

The interaction between the construction market and the overall economy has attracted much attention, but few studies have investigated the influence of the property market on the construction market in terms of property price. The disaggregated data of Hong Kong’s housing and retail construction sectors are collected to investigate the impact of property price on construction output. The newly developed autoregressive distributed lag (ARDL) bounds testing approach and the error correction (EC)-based Granger causality test are employed. The bounds testing results suggest that there exist stable long-run relationships between construction output and property price for both housing and retail construction sectors. Specifically, a 1.00% increase in the housing price and retail price lead to a 0.55% and 0.42% increase in construction outputs for the two sectors respectively. In addition, the Granger causality tests confirm a distinct long-run causal flow from property price to construction output. Furthermore, the proposed ARDL approach provides an effective method for forecasting construction output.     

An Amphiphilic BODIPY‐Porphyrin Conjugate: Intense Two‐Photon Absorption and Rapid Cellular Uptake for Two‐Photon‐Induced Imaging and Photodynamic Therapy

The new amphiphilic BODPY‐porphyrin conjugate BZnPP and its precursor BZnPH were synthesised, and their linear and two‐photon photophysical properties, together with their cellular uptake and photo‐cytotoxicity, were studied. This amphiphilic conjugate consists of a hydrophobic BODIPY moiety and a hydrophilic tetra(ethylene glycol) chain bridging a cationic triphenylphosphonium group to an amphiphilic porphyrin ZnP through acetylide linkers at its meso positions. A large two‐photon absorption cross‐section (σ=1725 GM) and a high singlet oxygen quantum yield (0.52) were recorded. Intense linear‐ and two‐photon‐induced red emissions were also observed for both BZnPP and BZnPH. Further in vitro studies showed that BZnPP exhibited very efficient cellular uptake and strong photocytotoxic but weak dark cytotoxic properties towards human breast carcinoma MCF‐7 cells. In summary, the two‐photon‐induced emission and the potent photo‐cytotoxicity of BZnPP make it an efficacious dual‐purpose tumour‐imaging and photodynamic therapeutic agent in the tissue‐transparent spectral windows.     

Binding Mode and Structure–Activity Relationships around Direct Inhibitors of the Nrf2–Keap1 Complex

An X‐ray crystal structure of Kelch‐like ECH‐associated protein (Keap1) co‐crystallised with (1S,2R)‐2‐[(1S)‐1‐[(1,3‐dioxo‐2,3‐dihydro‐1H‐isoindol‐2‐yl)methyl]‐1,2,3,4‐tetrahydroisoquinolin‐2‐carbonyl]cyclohexane‐1‐carboxylic acid (compound (S,R,S)‐ 1 a ) was obtained. This X‐ray crystal structure provides breakthrough experimental evidence for the true binding mode of the hit compound (S,R,S)‐ 1 a , as the ligand orientation was found to differ from that of the initial docking model, which was available at the start of the project. Crystallographic elucidation of this binding mode helped to focus and drive the drug design process more effectively and efficiently.     

The process modelling of epoxy dispensing for microchip encapsulation using fuzzy linear regression with fuzzy intervals

Epoxy dispensing is a popular way to perform microchip encapsulation for chip-on-board (COB) packages. However, the determination of the proper process parameters setting for a satisfactory encapsulation quality is difficult due to the complex behaviour of the encapsulant during the dispensing process and the inherent fuzziness of epoxy dispensing systems. Sometimes, the observed values from the process may be irregular. In conventional regression models, deviations between the observed values and the estimated values are supposed to have a probability distribution. However, when data is scattered, the obtained regression model has too wide of a possibility range. These deviations in processes such as epoxy dispensing can be regarded as system fuzziness that can be dealt with satisfactorily using a fuzzy regression method. In this paper, the fuzzy linear regression concept with fuzzy intervals and its application to the process modelling of epoxy dispensing for microchip encapsulation are described. Two fuzzy regression models, expressing the correlation between various process parameters and the two quality characteristics, respectively, were developed. Validation experiments were performed to demonstrate the effectiveness of the method for process modelling.     

2-Step self-assembly method to fabricate broadband omnidirectional antireflection coating in large scale

We have developed a simple and reproducible 2-step self-assembly method for the fabrication of broadband, omnidirectional antireflection coating on glass substrate with 4 in. size. The glass surface has been modified to be positively charged, then the negatively charged nano silica is self-assembled to the glass substrate by electrostatic attraction. The nanostructure on the glass substrate reduces the reflection significantly, which results in enhanced transmittance. Transmittance as high as 97.7% at 499 nm has been obtained for a double-side coated glass substrate. Obvious reduction in weighted reflectance is still observed up to 60° incident angle.