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.     

Marble mosaic tiling automation with a four degrees of freedom Cartesian robot

The art of mosaic has arisen thousands of years ago. Despite all those years and all the attention it has received till today, mosaic tiling is still being carried out manually and mosaic tiling processes have never been changed except the tool and material developments.     

Distributed Simulation and Middleware for Networked UAS

As a result of the advances in solid state, electronics, sensor, wireless communication technologies, as well as evolutions in the material science and manufacturing technologies, unmanned aerial vehicles (UAVs) and unmanned aerial systems (UAS) have become more accessible by civilian entities, industry, as well as academia. There is a high level of market driven standardisation in the electronics and mechanical components used on UAVs. However, the implemented software of a UAS does not exhibit the same level of standardisation and compartmentalisation. This is a major bottleneck limiting software maintenance, and software reuse across multiple UAS programs. This paper addresses the software development processes adapted by the Australian Centre for Field Robotics (ACFR) in major UAS projects. The presented process model promotes software reuse without sacrificing the reliability and safety of the networked UAS with particular emphasis on the role of distributed simulation and middleware in the development and maintenance processes.     

A genetic programming model for bankruptcy prediction: Empirical evidence from Iran

Prediction of corporate bankruptcy is a phenomenon of increasing interest to investors/creditors, borrowing firms, and governments alike. Timely identification of firms’ impending failure is indeed desirable. By this time, several methods have been used for predicting bankruptcy but some of them suffer from underlying shortcomings. In recent years, Genetic Programming (GP) has reached great attention in academic and empirical fields for efficient solving high complex problems. GP is a technique for programming computers by means of natural selection. It is a variant of the genetic algorithm, which is based on the concept of adaptive survival in natural organisms. In this study, we investigated application of GP for bankruptcy prediction modeling. GP was applied to classify 144 bankrupt and non-bankrupt Iranian firms listed in Tehran stock exchange (TSE). Then a multiple discriminant analysis (MDA) was used to benchmarking GP model. Genetic model achieved 94% and 90% accuracy rates in training and holdout samples, respectively; while MDA model achieved only 77% and 73% accuracy rates in training and holdout samples, respectively. McNemar test showed that GP approach outperforms MDA to the problem of corporate bankruptcy prediction.     

The hyperspherical acceleration effect particle swarm optimizer

This paper proposes Hyperspherical Acceleration Effect Particle Swarm Optimization (HAEPSO) for optimizing complex, multi-modal functions. The HAEPSO algorithm finds the particles that are trapped in deep local minima and accelerates them in the direction of global optima. This novel technique improves the efficiency by manipulating PSO parameters in hyperspherical coordinate system. Performance comparisons of HAEPSO are provided against different PSO variants on standard benchmark functions. Results indicate that the proposed algorithm gives robust results with good quality solution and faster convergence. The proposed algorithm is an effective technique for solving complex, higher dimensional multi-modal functions.     

Comparison of Conventional and Cross-Layer Multimedia Transport Schemes for Wireless Networks

Three competing schemes have been proposed for multimedia transport over broadband wireless channels: (a) traditional UDP (Postel, The User Datagram Protocol, 1980 [1]), (b) semi-cross-layer UDP-Lite (The Lightweight User Datagram Protocol, 2004 [2]), and (c) cross-layer header estimation (Khayam et al., IEEE Transactions on Multimedia 9(2):377–385, 2007 [3]; Khayam and Radha, IEEE Transactions on Wireless Communications 6(11):3946–3954, 2007 [4]). In all these schemes, corrupted and lost packets are recovered using FEC at the application layer. In this paper, we analytically and experimentally compare the performances of these broadband wireless multimedia schemes. First, we derive lower bounds on the excepted FEC redundancy required by ideal cross-layer header estimation, UDP and UDP-Lite over an arbitrary-order Markov wireless channel. We show that under realistic wireless channel conditions, the cross-layer header estimation scheme always requires lesser redundancy than UDP and UDP-Lite. We then propose a practical minimum distance decoding (MDD) header estimation scheme, which is receiver-based, low complexity and highly accurate. Trace-driven multimedia experiments over wireless LANs demonstrate that MDD header estimation requires significantly lesser FEC redundancy and renders better video quality than existing schemes.     

Edge-based Segmentation Using Robust Evolutionary Algorithm Applied to Medical Images

Although medical image segmentation is a hard task in image processing, it is possible to reduce its complexity by considering it as an optimization problem. This paper presents a robust evolutionary algorithm based on a cost minimization function to segment and to extract image edges. Since, the goal is to outperform a high edge detection quasi independent from the input problem characteristics, an adaptive detector is considered. As a first step, the main evolutionary algorithm parameters are highlighted based on an adaptive parameterization to overcome convergence problem. In a second stage, the reached optimal setting is applied on medical images to exhibit the quality of the proposed algorithm.     

Production of low cost self compacting concrete using bagasse ash

Self compacting concrete (SCC) is a development of conventional concrete, in which the use of vibrator for compaction is no more required. This property of self compacting concrete has made its use more attractive all over the world. But its initial higher supply cost over conventional concrete, has hindered its application to general construction. Therefore, for producing low cost SCC, it is prudent to look at the alternates to help reducing the SSC cost. This research is aimed at evaluating the usage of bagasse ash as viscosity modifying agent in SCC, and to study the relative costs of the materials used in SCC.In this research, the main variables are the proportion of bagasse ash, dosage of superplasticizer for flowability and water/binder ratio. The parameters kept constant are the amount of cement and water content.Test results substantiate the feasibility to develop low cost self compacting concrete using bagasse ash. In the fresh state of concrete, the different mixes of concrete have slump flow in the range of 333 mm to 815 mm, L-box ratio ranging from 0 to 1 and flow time ranging from 1.8 s to no flow (stucked). Out of twenty five different mixes, five mixes were found to satisfy the requirements suggested by European federation of national trade associations representing producers and applicators of specialist building products (EFNARC) guide for making self compacting concrete. The compressive strengths developed by the self compacting concrete mixes with bagasse ash at 28 days were comparable to the control concrete. Cost analysis showed that the cost of ingredients of specific self compacting concrete mix is 35.63% less than that of control concrete, both having compressive strength above 34 MPa.