Modular design to support green life-cycle engineering

The severe competition in the market has driven enterprises to produce a wider variety of products to meet consumers’ needs. However, frequent variation of product specifications causes the assembly and disassembly of components and modules to become more and more complicated. As a result, the issue of product modular design is a problem worthy of concern. In this study, engineering attributes were added to the liaison graph model for the evaluation of part connections. The engineering attributes added, including contact type, combination type, tool type, and accessed direction, serve to offer designers criteria for evaluating the component liaison intensity during the design stage. A grouping genetic algorithm (GGA) is then employed for clustering the components and crossover mechanisms are modified according to the need of modular design. Furthermore, a reasonable green modular design evaluation is conducted using the green material cost analysis. According to the results, adjusted design proposals are suggested and materials that cause less pollution are recommended to replace the components with pollution values higher than those in the module. Finally, the authors use Borland C++ 6.0 to evaluate the system and clustering method. To illustrate the methodology proposed in this study, a table lamp is offered as an example.     

Analysis and synthesis of robust H ∞ static output feedback control subject to actuator saturation

In this article, static output feedback (SOF) control analysis and synthesis are conducted for a linear continuous-time system subject to actuator saturation with the H ^∞ setting. Typically, the SOF problem is nonconvex; the existence of SOF control can be expressed in terms of the solvability of bilinear matrix inequalities. The actuator saturation problem is also considered since the driving capacity of an actuator is limited in practical applications. Using the singular value decomposition approach, the H ^∞ SOF controller design problem with actuator saturation can be expressed in terms of an eigenvalue problem (EVP) which can be efficiently solved using the LMI toolbox in Matlab. The balance between the minimization of the attenuation level of the H ^∞ performance and the maximisation of the estimation of the domain of attraction is considered in our approach via solving the corresponding EVP. To illustrate the proposed design procedure for two types of prescribing shape reference set, two numerical examples are included.     

The Kuroshio variations from satellite-derived sea surface temperature and Argos satellite-tracking Lagrangian drifters

This study aimed to identify the spatial and temporal variations of the Kuroshio using satellite-derived Sea Surface Temperature (SST) data and a total of 585 Argos satellite-tracking Lagrangian drifters during 1987–2006 in the northwestern Pacific Ocean. The threshold of high surface velocity, more than 75 cm s^–1, was used to determine the location of the Kuroshio Current and found that its width ranged from 50 to 100 km. Moreover, this study first conducted a synoptic view for three predominant regions of the Kuroshio, including the area east of Taiwan, the area east of the East China Sea (ECS) and the area south of Japan. We found that the Kuroshio flows at a three-step increase in speed from upstream to downstream. The maximum mean surface velocity, 153 cm s^–1, occurred to the south of Japan. Furthermore, the higher surface velocity of the Kuroshio was usually during the summertime (from April to September). In addition, the four-cruise CTD (Conductivity, Temperature, Depth)-transect data observed in January 2005 were collected to identify and validate the path of the Kuroshio axes. The results showed that the measure of 17.5°C at a depth of 200 m could be regarded as an indicator of the Kuroshio axis, corresponding with the maximum surface velocities of the Argos drifters. The monthly satellite-derived SST values of the Kuroshio were usually more than 10°C, so it was difficult to find a specific isotherm to express the location of the Kuroshio. However, extensive Kuroshio fronts derived from satellite SST data were found in this study. These Kuroshio fronts, associated with high SST gradients, were usually located on the boundary between the warm water of the Kuroshio and the colder water of the shelf, corresponding with the boundary of high surface velocity of the Argos drifters. Consequently, this study suggests that these Kuroshio fronts can be regarded as an effective indicator of the Kuroshio paths and its main axes.     

Micromixing via recirculatory flow generated by an oscillatory microplate

Mixing in micro-environment has been explored in a number of studies. This study presents a unique approach of efficient mixing of two heterogeneous streams via two counter-rotating recirculatory streams induced by in-plane resonance of a rectangular microplate actuated via Lorentz force. The generated time-mean flow structure was interrogated for mixing efficacy over a range of excitation voltage, Reynolds number, and Pèclet number, along with numerical analysis to probe the time-mean flow physics. Results show that the recirculatory flow is generated at the plate’s edges due to local flow non-linearity, characteristic of acoustic streaming. The percentage of mixing, at one device length-scale downstream, attains 93% at a low Reynolds number of 0.0037 (based on mean velocity of 0.078 mm/s and channel height of 50 μm) at 8 V excitation. Further characterization via enhanced diffusivity shows a maximum of 80.7-fold increase. Comparison with other active mixers shows the current device achieves mixing in one of the shortest distances. The proposed approach is robust, tunable to attain desired mixing characteristics and essentially independent of the properties of the fluid medium, which should be useful in a number of microfluidic applications requiring fast mixing.     

Truss structure optimization using adaptive multi-population differential evolution

This paper applies multi-population differential evolution (MPDE) with a penalty-based, self-adaptive strategy—the adaptive multi-population differential evolution (AMPDE)—to solve truss optimization problems with design constraints. The self-adaptive strategy developed in this study is a new adaptive approach that adjusts the control parameters of MPDE by monitoring the number of infeasible solutions generated during the evolution process. Multiple different minimum weight optimization problems of the truss structure subjected to allowable stress, deflection, and kinematic stability constraints are used to demonstrate that the proposed algorithm is an efficient approach to finding the best solution for truss optimization problems. The optimum designs obtained by AMPDE are better than those found in the current literature for problems that do not violate the design constraints. We also show that self-adaptive strategy can improve the performance of MPDE in constrained truss optimization problems, especially in the case of simultaneous optimization of the size, topology, and shape of truss structures.     

The role of drying-control chemical additives on the preparation of sol-gel derived PLZT thin films

Films of Pb _x/100La _x/100(Zr _y/100Ti _z/100)_1–x/400O₃ with x=8, y=65 and z=35 (PLZT(8/65/35)) with a single perovskite structural phase were successfully prepared by using drying-control chemical additives in sol-gel processing followed by rapid thermal annealing at 600 °C for only 1 min on Si(Pt) substrates. The roles of the drying-control chemical additives ethylene glycol and formamide in the gel preparation were studied. The hysteresis loop of PLZT(8/65/35) thin film was measured. The remanent polarization and coercive field were found to be about 1.3 C cm^–2 and 15 kVcm^–1, respectively.     

Effect of NaCl on nitrate removal from ion-exchange spent brine in the membrane biofilm reactor (MBfR)

The H(2)-based membrane biofilm reactor was used to remove nitrate from synthetic ion-exchange brine at NaCl concentrations from ～3 to 30 g/L. NaCl concentrations below 20 g/L did not affect the nitrate removal flux as long as potassium was available to generate osmotic tolerance for high sodium, the H(2) pressure was adequate, and membrane fouling was eliminated. Operating pHs of 7-8 and periodic citric acid washes controlled membrane fouling and enabled reactor operation for 650 days. At 30 psig H(2) and high nitrate loading rates of 15 to 80 g/m(2) d, nitrate removal fluxes ranged from 2.5 to ～6 g/m(2) d, which are the highest fluxes observed when treating 30 g/L IX brine. However, percent removals were low, and the H(2) pressure probably limited the removal flux.     

Discovering business intelligence from online product reviews: A rule-induction framework

Online product reviews are a major source of business intelligence (BI) that helps managers and marketers understand customers’ concerns and interests. The large volume of review data makes it difficult to manually analyze customers’ concerns. Automated tools have emerged to facilitate this analysis, however most lack the capability of extracting the relationships between the reviews’ rich expressions and the customer ratings. Managers and marketers often resort to manually read through voluminous reviews to find the relationships. To address these challenges, we propose the development of a new class of BI systems based on rough set theory, inductive rule learning, and information retrieval methods. We developed a new framework for designing BI systems that extract the relationship between the customer ratings and their reviews. Using reviews of different products from Amazon.com, we conducted both qualitative and quantitative experiments to evaluate the performance of a BI system developed based on the framework. The results indicate that the system achieved high accuracy and coverage related to rule quality, and produced interesting and informative rules with high support and confidence values. The findings have important implications for market sentiment analysis and e-commerce reputation management.     

Memory access schedule minimization for embedded systems

The growing gap between microprocessor speed and DRAM speed is a major problem that computer designers are facing. In order to narrow the gap, it is necessary to improve DRAM’s speed and throughput. To achieve this goal, this paper proposes techniques to take advantage of the characteristics of the 3-stage access of contemporary DRAM chips by grouping the accesses of the same row together and interleaving the execution of memory accesses from different banks. A family of Bubble Filling Scheduling (BFS) algorithms are proposed in this paper to minimize memory access schedule length and improve memory access time for embedded systems.When the memory access trace is known in some application-specific embedded systems, this information can be fully utilized to generate efficient memory access schedules. The offline BFS algorithm can generate schedules which are 47.49% shorter than in-order scheduling and 8.51% shorter than existing burst scheduling on average. When memory accesses are received by the single memory controller in real time, the memory accesses have to be scheduled as they come. The online BFS algorithm in this paper serves this purpose and generates schedules which are 58.47% shorter than in-order scheduling and 4.73% shorter than burst scheduling on average. To improve the memory throughput and further reduce the memory access schedule, an architecture with dual memory controllers is proposed. According to the experimental results, the dual controller algorithm can generate schedules which are 62.89% shorter than in-order scheduling, 14.23% shorter than burst scheduling, and 10.07% shorter than single controller BFS algorithms on average.     

Evaluating gallium-doped ZnO top electrode thickness for achieving a good switch-ability in ZnO2/ZnO bilayer transparent valence change memory

Gallium doped ZnO (GZO) top electrode thickness dependence of resistive switching characteristic of GZO/ZnO₂/ZnO/ITO transparent valence change memory device is investigated. The thickness of the GZO top electrode modulates the resistance of the pristine device. Devices made with thicker GZO layer have higher leakage current; thus, require higher current compliance. An excessively high current compliance leads to a device breakdown upon reset process. Conversely, a very low current compliance may form a tiny conducting filament and is difficult to rejuvenate after the rupture; thus, its cycle-to-cycle characteristic shows a decaying behavior. Nevertheless, transparent valence change devices with a stable endurance and sufficient memory window that operate at a moderate level of current compliance are successfully fabricated by employing an appropriate thickness of the top electrode. We suggest that a good switch-ability of transparent valence change memory devices are strongly affected by the thickness of the top electrode.