The utilization of soft transformation and genetic algorithm to model two sources of uncertainty of Indicator Kriging

Indicator Kriging (IK) is a geostatistical method that uses observation points to quantify the probabilities at which a set of thresholds are exceeded at unmeasured points. To improve IK accuracy, the interpolation process should consider its uncertainty sources. By doing this, we also maintain its ability to provide the conditional cumulative distribution function (ccdf), which is a reliable measure of local uncertainty. This study modeled two IK uncertainty sources, i.e., measurement errors attached to observation points and subjective threshold choices. Soft Indicator Kriging (SIK), which uses a soft transformation for observation points, considers the measurement errors of these two sources. To select the thresholds objectively, a genetic algorithm (GA) was performed to obtain the optimum set of thresholds related to an objective function, which minimized the mean absolute error (MAE).     

A case-based reasoning system development for statistical process control: Case representation and retrieval

Statistical process control (SPC) is a sub-area of statistical quality control. Considering the successful results of the SPC applications in various manufacturing and service industries, this field has attracted a large number of experts. Despite the development of knowledge in this field, it is hard to find a comprehensive perspective or model covering such a broad area and most studies related to SPC have focused only on a limited part of this knowledge area. According to many implemented cases in statistical process control, case-based reasoning (CBR) systems have been used in this study for developing of a knowledge-based system (KBS) for SPC to organize this knowledge area. Case representation and retrieval play an important role to implement a CBR system. Thus, a format for representing cases of SPC and the similarity measures for case retrieval are proposed in this paper.     

Inverse random under sampling for class imbalance problem and its application to multi-label classification

In this paper, a novel inverse random under sampling (IRUS) method is proposed for the class imbalance problem. The main idea is to severely under sample the majority class thus creating a large number of distinct training sets. For each training set we then find a decision boundary which separates the minority class from the majority class. By combining the multiple designs through fusion, we construct a composite boundary between the majority class and the minority class. The proposed methodology is applied on 22 UCI data sets and experimental results indicate a significant increase in performance when compared with many existing class-imbalance learning methods. We also present promising results for multi-label classification, a challenging research problem in many modern applications such as music, text and image categorization.     

Musculoskeletal disorders among female carpet weavers in Iran

The aim of this study was to determine factors associated with self-reported upper extremity musculoskeletal disorders (UEMSDs) among female carpet weavers. Data on demographic characteristics and workplace factors were collected from 626 female carpet weavers. Type of carpet weaving looms, weaving style (Persian vs. Turkish), daily working hours and work experience as well as personal factors including age and marital status were significantly and independently associated with self-reported UEMSDs (p < 0.05), while education, handedness and weight of weaving comb were not. A major finding of this study was the significant association between weaving style and UEMSDs. Better measures of the biomechanical requirements of carpet weaving tasks in Persian and Turkish weaving types are required to understand better their influences on the health of weavers and on UEMSDs in particular. Poor workstation design, in particular, design inappropriate for the anthropometric dimensions of weavers, was a major risk factor for musculoskeletal symptoms in carpet weaving. Therefore, this industry should develop equipment adapted to women's sizes and shapes. PRACTITIONER SUMMARY: This article provides an insight into the risk factors associated with self-reported UEMSDs among female carpet weavers, identifying major factors associated with upper extremity musculoskeletal symptoms and exploring guidelines for designing weaving workstations.     

Sequence-dependent group scheduling problem on unrelated-parallel machines

In this research we address a sequence-dependent group scheduling problem on a set of unrelated-parallel machines where the run time of each job differs on different machines. To benefit both producer and customers we attempt to minimize a linear combination of total weighted completion time and total weighted tardiness. Since the problem is shown to be NP-hard, meta-heuristic algorithms based on tabu search are developed to find the optimal/near optimal solution. For some small size yet complex problems, the results from these algorithms are compared to the optimal solutions found by CPLEX. The result obtained in all of these problems is that the tabu search algorithms could find solutions at least as good as CPLEX but in drastically shorter computational time, thus signifying the high degree of efficiency and efficacy attained by the former.     

Combined quasi-static backward modeling and look-ahead fuzzy control of vehicles

Vehicle modeling can play an important role in vehicle power train design, control and energy management investigation. This paper presents a method for vehicle power train modeling. The key feature of the method is its presentation of the dynamic of vehicle based on the road information. This ability makes the method suitable for look-ahead energy management and fuel economy optimal control problems. With the aid of a road slope database, road geometry ahead of the vehicle is extracted. A fuzzy controller is developed that receives this information and controls the velocity of the vehicle with respect to its fuel consumption. In order to maintain the operation of the combustion engine near its efficient region, the fuzzy controller commands a continuously variable transmission. Simulations are carried out using real road data. The results are presented and discussed.     

Estimating the stresses in cantilever beam loaded by a parabolically distributed load with Airy stress functions

This study presents three mathematical methods namely the polynomial stress function approach, the Fourier series form approach and the approximated equations form approach for finding the stress distribution in a cantilever beam with rectangular cross section loaded by a parabolically distributed load. By taking the stress function as a polynomial of the seventh degree, it is attempted to find the coefficients either in complete or in full shape of the polynomial. In the Fourier series approach, the load is discreted to unlimited series of harmonic loads and superposing resultant stresses is the affect of parabolically distributed load on the beam. The resultant stresses are compared with some approximated stress formulas which have been provided before. Finite element analysis are done for square, short, medium and long cantilever beams and the mathematical results of stress distribution in five different height of the beam was compared with FEM results. It was found good results for τ _yy and τ _xy in all cross section of the beams and acceptable results for τ _xx only in y = 0. It is found that discreting loads to even a limit number of harmonic loads and superposing the resultant stresses can give the distribution of τ _yy and τ _xy with the acceptable precision in medium and long cantilever beams with rectangular cross section.     

Effect of Multi-Wall Carbon Nanotubes on the Mechanical Properties of Natural Rubber

Multi-walled carbon nanotubes (MWNTs) were used to prepare natural rubber (NR) nanocomposites. Our first efforts to achieve nanostructures in MWNTs/NR nanocomposites were formed by incorporating carbon nanotubes in a polymer solution and subsequently evaporating the solvent. Using this technique, nanotubes can be dispersed homogeneously in the NR matrix in an attempt to increase the mechanical properties of these nanocomposites. The properties of the nanocomposites such as tensile strength, tensile modulus, elongation at break and hardness were studied. Mechanical test results show an increase in the initial modulus for up to 12 times in relation to pure NR. In addition to mechanical testing, the dispersion state of the MWNTs into NR studied by Transmission Electron Microscopy (TEM) in order to understand the morphology of the resulting system     

Evaluation of Al and Some of Its Alloys as Anode Materials vs γ-MnO2 as Cathode Material and Ore Produced γ-MnO2 vs Zn Anode in KOH Solution

In this study electrochemical performance of Al and some of its alloys (Al-Zn, Al-Mg and Al-Mn) anodes vs MnO2 cathode were carried out in alkaline solution. The results show that the Al-Zn alloy anode has the best cell capacity among the other alloys. Cell capacity values go in the order Al-Zn＞Al-Mg＞Al＞Al-Mn. This result is probably related to the nature of passive films formed on the surface of the alloys which examined by scanning electron microscopy (SEM). SEM morphologies of Al and its alloys showed coarse grains of passive films formed on the surface of these anode materials while Al-Mn morphology shows a needle-like structure.Electrolytic manganese dioxide (EMD) produced by electrodepositing on platinum anode from liquor resulting from reduction of low grade pyrolusite ore (β-MnO2) by sulfur slag was characterized as cathode in alkaline Zn-MnO2 batteries. Ore produced sample (EMD1) was performed well in comparison with EMD standard (EMD2) (commercial battery grade electrolytic manganese dioxide, TOSOH-Hellas GH-S). SEM morphology of Zn anode after cell reaction was carried out and showed that Zn anode has fine grains of passive film on its surface.     

实时多处理器系统中基于能量节约的动态调度算法

当前处理器由于较高的能量消耗。导致处理器热量散发的提高及系统可靠性的降低，已经成为目前计算机领域较为关心的问题．然而目前一些有效降低能量消耗的技术大多针对单处理器系统，较少考虑多处理器系统．本文提出的调度算法针对多处理器系统，以最短任务优先调度为基础，结合其它有效技术，如共享空闲时间回收等，使得实时任务在其截止期内完成的同时能够有效地减低整个系统的能量消耗．针对独立任务集及具有依赖关系的任务集，本文提出两种算法：STFBA1及STFBA2（Shortest Task First—Based Algorithm）．与目前所知的有效算法相比，我们的算法具有更好的性能（调度长度及能量消耗）．