From a Non-Local Ambrosio-Tortorelli Phase Field to a Randomized Part Hierarchy Tree

In its most widespread imaging and vision applications, Ambrosio and Tortorelli (AT) phase field is a technical device for applying gradient descent to Mumford and Shah simultaneous segmentation and restoration functional or its extensions. As such, it forms a diffuse alternative to sharp interfaces or level sets and parametric techniques. The functionality of the AT field, however, is not limited to segmentation and restoration applications. We demonstrate the possibility of coding parts—features that are higher level than edges and boundaries—after incorporating higher level influences via distances and averages. The iteratively extracted parts using the level curves with double point singularities are organized as a proper binary tree. Inconsistencies due to non-generic configurations for level curves as well as due to visual changes such as occlusion are successfully handled once the tree is endowed with a probabilistic structure. As a proof of concept, we present (1) the most probable configurations from our randomized trees; and (2) correspondence matching results between illustrative shape pairs. The work is a significant step towards establishing exponentially decaying diffuse distance fields as bridges between low level visual processing and shape computations.     

Variation of part thickness and compaction pressure in vacuum infusion process

In vacuum infusion (VI), it is difficult to manufacture a composite part with small dimensional tolerances, since the thickness of the part changes during resin injection. This change of thickness is due to the effect of varying compaction pressure on the upper mold part, a vacuum bag. In this study, random fabric layers with an embedded core distribution medium is used. The thickness of the composite part and resin pressure are monitored using multiple dial gages and pressure transducers; the results are compared with the model developed by Correia et al. [Correia NC, Robitaille F, Long AC, Rudd CD, Simacek P, Advani SG. Analysis of the vacuum infusion molding process: I. Analytical formulation. Composites Part A: Applied Science and Manufacturing 26, 2005. p. 1645–1656]. To use this model, two material characteristics databases are constructed based on the process parameters: (i) the thickness of a dry/wet fabric preform at different compaction pressures, and (ii) the permeability of the preform at different thicknesses. The dry-compacted preform under vacuum is further compacted due to fiber settling in wet form after resin reaches there; the part thickens afterwards as the resin pressure increases locally. The realistic model solution can be achieved only if the compaction characterization experiments are performed in such a way that the fabric is dry during loading, and wet during unloading, as in the actual resin infusion process. The model results can be used to design the process parameters such as vacuum pressure and locations of injection and ventilation tubes so that the dimensional tolerances can be kept small.     

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.     

艾哈迈德·阿德南·萨伊贡艺术中心,伊兹密尔,土耳其

<正>一座建筑的性能应当如何来衡量?除了通过统治当代建筑舆论的美学、技术以及经济价值来进行描述之外,我们还能够如何来阐释一座建筑,尤其是一座致力于庇护那些渴望展现自己的艺术家的建筑?有人会问成功的表演是如何实现的,表演者是如何进行伪装的、又是如何展现自己的?根据海德格尔的理论,当我们看不到钉子的时候,铁锤的表现才是成功的;钉子本身的出现通常表明出现了问题。     

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.     

Using directionality in mobile routing

The increased usage of directional methods of communications has prompted research into leveraging directionality in every layer of the network stack. In this paper, we explore the use of directionality in layer 3 to facilitate routing in highly mobile environments. We introduce Mobile Orthogonal Rendezvous Routing Protocol (MORRP) for mobile ad-hoc networks (MANETs). MORRP is a lightweight, but scalable routing protocol utilizing directional communications (such as directional antennas or free-space-optical transceivers) to relax information requirements such as coordinate space embedding, node localization, and mobility. This relaxation is done by introducing a novel concept called the directional routing table (DRT) which maps a set-of-IDs to each interface direction to provide probabilistic routing information based on interface direction. We show that MORRP achieves connectivity with high probability even in highly mobile environments while maintaining only probabilistic information about destinations. Additionally, we compare MORRP with various proactive, reactive, and position-based routing protocols using single omni-directional interfaces and multiple directional interfaces and show that MORRP gains over 10–14 × additional goodput vs. traditional protocols and 15–20% additional goodput vs. traditional protocols using multiple interfaces. MORRP scales well without imposing DHT-like graph structures (eg: trees, rings, torus etc). We also show that high connectivity can be achieved without the need to frequently disseminate node position resulting increased scalability even in highly mobile environments.     

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.