Simulation of flowfields induced by wind blades based on a parallelized low-speed flow solver

In this study, a parallel computing technology is applied on the simulation of a wind turbine flow problem. A third-order Roe type flux limited splitting based on a pre-conditioning matrix with an explicit time marching method is used to solve the Navier–Stokes equations. The original FORTRAN code was parallelized with Message Passing Interface (MPI) language and tested on a 64-CPU IBM SP2 parallel computer. The test results show that a significant reduction of computing time in running the model and a super-linear speed up rate is achieved up to 32 CPUs at IBM SP2 processors. The speed up rate is as high as 49 for using IBM SP2 64 processors. The test shows very promising potential of parallel processing to provide prompt simulation of the current wind turbine problems.     

Structural planning and implementation of a microprocessor-based human-machine interface in a steam-explosion process application

In this paper, small-scale microprocessor-based human-machine interface (HMI) and programmable logic controller (PLC) standard software libraries are applied to plan, design, implement, and construct models for creating the modular application software. The graphical user interface (GUI) functions used in a specific biomass steam-explosion process, intended to be integrated with the PLC device for HMI, thereby providing excellent GUI-based supervision and control functions. Reviewing these specific case study results, we find that the major advantage is maximum system operating performance at minimum cost. Also, the GUI/HMI operation effectively provides user-friendly and reliable interactions. This GUI/HMI approach is a very cost-effective technique.     

Minimizing total weighted flowtime subject to minimum makespan on two identical parallel machines

We study the problem of scheduling n jobs on two identical parallel processors or machines where an optimal schedule is defined as one with the shortest total weighted flowtime (i.e., the sum of the weighted completion time of all jobs), among the set of schedules with minimum makespan (i.e., the completion time of the last job finished). We present a two phase non-linear Integer Programming formulation for its solution, admittedly not to be practical or useful in most cases, but theoretically interesting since it models the problem. Thus, as an alternative, we propose an optimization algorithm, for small problems, and a heuristic, for large problems, to find optimal or near optimal solutions. Furthermore, we perform a computational study to evaluate and compare the effectiveness of the two proposed methods.     

Autonomous rule induction from data with tolerances in customer relationship management

In this paper, application of the rough set theory (RST) to feature selection in customer relationship management (CRM) is introduced. Compared to other methods, the RST approach has the advantage of combining both qualitative and quantitative information in the decision analysis, which is extremely important for CRM. Automated decision support for CRM has been proposed in recent years. However, little work has been devoted to the development of computer-based systems to support CRM in rule induction. This paper presents a novel rough set based algorithm for automated decision support for CRM. Particularly, the approach is capable to handle real numbers instead of integer numbers through introduction of converted numbers involving tolerances. Being unique and useful in solving CRM problems, an alternative rule extraction algorithm (AREA) is presented for discovering preference-based rules according to the reducts which contain the maximum of strength index (SI) in the same case, where the data with tolerance. The empirical data set associated with CRM has proven the validity and reliability of these approaches. This research thus contributes to developing and validating a useful approach to automated decision support for CRM. This paper forms the basis for solving many other similar problems that occur in the service industry.     

Positioning strategic competitiveness of green business innovation capabilities using hybrid method

There are intensive studies on the issues of environment practice and business innovation capability, have been dealt with extensively from practitioners and academicians, however, studies on the evaluation of green business innovation capabilities (GBICs) are few. This study tackles the evaluation assessment using fuzzy set theory, analytical network process and importance–performance analysis. Specifically, this study is using the theoretical framework of GBICs and proposed hybrid approach, which are new in the theoretical and empirical literatures. An expert group was empirical assessment to the perception on PWB sector and a manufacturing firm is evaluated. The analytical results indicated that this proposed hybrid method is a suitable and effective method for identifying and analyzing the strategic competitiveness of GBICs at case firm, especially when evaluation criteria are dependent in uncertainty.     

Robust State‐and‐Disturbance Observer Design for Linear Non‐minimum‐phase Systems

When there are external disturbances acting on the system, the conventional Luenberger observer design for state estimation usually results in a biased state estimate. This paper presents a robust state and disturbance observer design that gives both accurate state and disturbance estimates in the face of large disturbances. The proposed robust observer is structurally different from the conventional one in the sense that a disturbance estimation term is included in the observer equation. With this disturbance estimation term, the robust observer design problem is skillfully transformed into a disturbance rejection control problem. We then can utilize the standard H_∞ control design tools to optimize the robust observer between the disturbance rejection ability and noise immune ability. An important advantage of the proposed robust observer is that it applies to both minimum‐phase systems and non‐minimum phase systems.     

Per-stream loss behavior of ∑MAP/M/1/K queuing system with a random early detection mechanism

In this paper, the matrix-analytic approach is applied to explore the per-stream loss behavior of the multimedia traffic under RED scheme. We constructed a ∑MAP/M/1/K queuing model for the RED mechanism with multimedia traffic which follows a continuous-time Markovian arrival process (MAP). In addition to evaluating the long-term per-stream packet drop probabilities, we examine the bursty nature of per-stream packet drops by means of conditional statistics with respect to dropped periods and the probability that the queuing system stays in the dropped period. The dropped period corresponds to having more than a certain number of packets in router buffer; non-dropped period corresponds to the opposite. These performance measures describe the quality of service provided by the router to particular multimedia traffic streams in the presence of background multimedia traffic.     

Optimum Allocation Rule for Accelerated Degradation Tests With a Class of Exponential-Dispersion Degradation Models

Optimum allocation problem in accelerated degradation tests (ADTs) is an important task for reliability analysts. Several researchers have attempted to address this decision problem, but their results have been based only on specific degradation models. Therefore, they lack a unified approach toward general degradation models. This study proposes a class of exponential dispersion (ED) degradation models to overcome this difficulty. Assuming that the underlying degradation path comes from the ED class, we analytically derive the optimum allocation rules (by minimizing the asymptotic variance of the estimated q quantile of product's lifetime) for two-level and three-level ADT allocation problems whether the testing stress levels are prefixed or not. For a three-level allocation problem, we show that all test units should be allocated into two out of three stresses, depending on certain specific conditions. Two examples are used to illustrate the proposed procedure. Furthermore, the penalties of using nonoptimum allocation rules are also addressed. This study demonstrates that a three-level compromise plan with small proportion allocation in the middle stress, in general, is a good strategy for ADT allocation. Supplementary materials for this article are available online.     

In vitro comparative study of drug loading and delivery properties of bioresorbable microspheres and LC bead

Drug loadable bioresorbable microspheres (BRMS) are specially designed for the treatment of hypervascular tumors through arterial embolization. These microspheres consist of carboxymethyl chitosan crosslinked with carboxymethyl cellulose, and are available at different size ranges varying from 50 to 900?µm in diameter. Similar to commercially available non-resorbable drug eluting microspheres, LC Bead^® microspheres (LCB), BRMS were capable of loading more than 99?% of doxorubicin, an anticancer drug, from the solution within 2?h with highly similar kinetics (difference factor f ₁?=?0.36; similarity factor f ₂?=?97.99). Doxorubicin loaded BRMS exhibited the highest elution rate in the 30?% ethanol aqueous solution saturated with potassium chloride, and the elution time depended on the ratio between the amount of loaded BRMS and the volume of elution media. After injection through microcatheters, BRMS have a higher recovery rate of the microsphere weight than LCB (90.96 vs. 79.63?%, P?=?0.026). Although loaded BRMS eluted more drug into the injection medium than loaded LCB (8.63 vs. 3.80?%, P?=?0.0015), there was no significant difference in the drug delivery rate between BRMS and LCB (83.88 vs. 86.65?%, P?=?0.504). This study compares the loading capability as well as the drug delivery rate of BRMS and a commercial product under a condition simulating a transcatheter arterial chemoembolization procedure and demonstrates the potential of drug loaded BRMS for the treatment of hypervascular tumors such as hepatocellular carcinoma.