Quality Indices for Aluminum Alloy Castings: A Critical Review

Several indices are available in the literature to assess the structural quality of cast Al alloys, especially Al-7 pct Si-Mg alloys that are based on tensile test results. Some of these indices, most notably the one developed by Drouzy et al., provide a number that necessarily does not have a physical meaning, whereas the others are a measure of what fraction of the expected tensile performance is achieved. These indices are analyzed in depth, their similarities and shortcomings are discussed in detail, and recommendations are made.     

Formal anonymity models for efficient privacy-preserving joins

Organizations, such as federally-funded medical research centers, must share de-identified data on their consumers to publicly accessible repositories to adhere to regulatory requirements. Many repositories are managed by third-parties and it is often unknown if records received from disparate organizations correspond to the same individual. Failure to resolve this issue can lead to biased (e.g., double counting of identical records) and underpowered (e.g., unlinked records of different data types) investigations. In this paper, we present a secure multiparty computation protocol that enables record joins via consumers’ encrypted identifiers. Our solution is more practical than prior secure join models in that data holders need to interact with the third party one time per data submission. Though technically feasible, the speed of the basic protocol scales quadratically with the number of records. Thus, we introduce an extended version of our protocol in which data holders append k-anonymous features of their consumers to their encrypted submissions. These features facilitate a more efficient join computation, while providing a formal guarantee that each record is linkable to no less than k individuals in the union of all organizations’ consumers. Beyond a theoretical treatment of the problem, we provide an extensive experimental investigation with data derived from the US Census to illustrate the significant gains in efficiency such an approach can achieve.     

A sufficient condition for additive -stability and application to reaction–diffusion models

The matrix A is said to be additively D-stable if A−D remains Hurwitz for all non-negative diagonal matrices D. In reaction–diffusion models, additive D-stability of the matrix describing the reaction dynamics guarantees the stability of the homogeneous steady-state, thus ruling out the possibility of diffusion-driven instabilities. We present a new criterion for additive D-stability using the concept of compound matrices. We first give conditions under which the second additive compound matrix has non-negative off-diagonal entries. We then use this Metzler property of the compound matrix to prove additive D-stability with the help of an additional determinant condition. This result is then applied to investigate the stability of cyclic reaction networks in the presence of diffusion. Finally, a reaction network structure that fails to achieve additive D-stability is exhibited.     

On evaluating Weibull fits to mechanical testing data

The use of coefficient of determination, R², and the Anderson–Darling (A²) hypothesis test to evaluate the goodness-of-fit to the two-parameter Weibull distribution was investigated. Results of Monte Carlo simulations for sample sizes between 5 and 100 indicated that guidelines provided previously in the literature are too conservative for sample sizes up to 80. New guidelines for the use of R² and A² for sample sizes between 5 and 100 have been developed. The two measures of goodness-of-fit were found to agree more than 95% of the time, regardless of sample size. The use of the new guidelines has been demonstrated on two datasets from the casting literature.     

Early prostate cancer diagnosis by using artificial neural networks and support vector machines

The aim of this study is to design a classifier based expert system for early diagnosis of the organ in constraint phase to reach informed decision making without biopsy by using some selected features. The other purpose is to investigate a relationship between BMI (body mass index), smoking factor, and prostate cancer. The data used in this study were collected from 300 men (100: prostate adenocarcinoma, 200: chronic prostatism or benign prostatic hyperplasia). Weight, height, BMI, PSA (prostate specific antigen), Free PSA, age, prostate volume, density, smoking, systolic, diastolic, pulse, and Gleason score features were used and independent sample t-test was applied for feature selection. In order to classify related data, we have used following classifiers; scaled conjugate gradient (SCG), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Levenberg–Marquardt (LM) training algorithms of artificial neural networks (ANN) and linear, polynomial, and radial based kernel functions of support vector machine (SVM). It was determined that smoking is a factor increases the prostate cancer risk whereas BMI is not affected the prostate cancer. Since PSA, volume, density, and smoking features were to be statistically significant, they were chosen for classification. The proposed system was designed with polynomial based kernel function, which had the best performance (accuracy: 79%). In Turkish Family Health System, family physician to whom patients are applied firstly, would contribute to extract the risk map of illness and direct patients to correct treatments by using expert system such proposed.     

A team-oriented design methodology for mixed model assembly systems

Team-oriented approaches are widely being used in modern real life assembly systems, as are other modern systems. In this paper, first the literature of single and mixed model assembly line balancing, which plays an important role for the design of assembly systems, is reviewed. The associated literature matrixes reveal that team-oriented approaches do not have an intensive research area. Second, a team-oriented mathematical programming model for creating assembly teams (physical stations) in mixed model assembly lines is devised. Owing to the fact that this model is NP hard, a scheduling based heuristic algorithm is developed. The mixed model assembly line design methodology, which includes a team-oriented algorithm as a step, is proposed. Both model sequencing and worker transfer systems are included in the methodology. The algorithms for each step of the methodology are also coded by using MATLAB and MS Excel is used as the user interface. Furthermore, the presented methodology was applied in a chosen segment of a real life mixed model tractor assembly system.     

Preparation of PbS thin films: A new electrochemical route for underpotential deposition

Nanostructured thin films of lead sulfide have been synthesized by a new electrochemical approach based on the underpotential deposition (UPD) of Pb and S from the saturated solution of PbS containing excess of PbS particles as a source of Pb²⁺ and S²⁻ at various temperatures.We have demonstrated that this new electrochemical route is a simple method with several advantages, including better control of the growth conditions and a one-step process to obtain the nanostructures of PbS. Scanning probe microscopy studies indicate that the growth of PbS nanofilms follows a two-dimensional layer-by-layer growth kinetics at the beginning of electrodeposition but a three-dimensional growth dominates after the formation of the first few layers. The results of morphological and structural investigations reveal that PbS nanostructures grown by this method are single-crystalline in cubic structure and have a preferential orientation along the [2 0 0] direction. The optical absorption spectra of PbS nanostructures show the blue-shift with respect to those of the bulk counterpart, which are attributed as quantum-size effect.     

A quasi-static analysis for a class of induced-current EIT systems using discrete coils

A discrete coil EIT system is investigated for the general case of an eccentric circular inhomogeneity. The solution methodology of the forward problem of this system is explained. An optimization procedure using this forward problem solution is developed to find optimum currents that maximize the distinguishability. For an eccentric inhomogeneity problem, it is shown that the coil currents can be optimized to focus the current density in a region of interest. Optimum coil currents under limited peak coil currents constraint and limited total power constraint are obtained. Representative examples that demonstrate the performance of the system are presented.     

An alternative approach to fuzzy control charts: Direct fuzzy approach

The major contribution of fuzzy set theory lies in its capability of representing vague data. Fuzzy logic offers a systematic base to deal with situations, which are ambiguous or not well defined. In the literature, there exist few papers on fuzzy control charts, which use defuzziffication methods in the early steps of their algorithms. The use of defuzziffication methods in the early steps of the algorithm makes it too similar to the classical analysis. Linguistic data in those works are transformed into numeric values before control limits are calculated. Thus both control limits as well as sample values become numeric. In this paper, some contributions to fuzzy control charts based on fuzzy transformation methods are made by the use of α-cut to provide the ability of determining the tightness of the inspection: the higher the value of α the tighter inspection. A new alternative approach “Direct Fuzzy Approach (DFA)” is also developed in this paper. In contrast to the existing fuzzy control charts, the proposed approach is quite different in the sense it does not require the use of the defuzziffication. This prevents the loss of information included by the samples. It directly compares the linguistic data in fuzzy space without making any transformation. We use some numeric examples to illustrate the performance of the method and interpret its results.     

Cross-Layer Optimized Rate Adaptation and Scheduling for Multiple-User Wireless Video Streaming

We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a multi-objective optimization (MOO) framework that aims to serve the user with the least remaining playback time, highest delivered video seconds per transmission slot and maximum video quality. Experiments with the IS-856 (1timesEV-DO) standard numerology and ITU pedestrian A and vehicular B environments show significant improvements over the state-of- the-art wireless schedulers in terms of user QoS, QoS fairness, and the system throughput.