Scalable Parallel Numerical CSP Solver

We present a parallel solver for numerical constraint satisfaction problems (NCSPs) that can scale on a number of cores. Our proposed method runs worker solvers on the available cores and simultaneously the workers cooperate for the search space distribution and balancing. In the experiments, we attained up to 119-fold speedup using 256 cores of a parallel computer.Comment: The final publication is available at Springe

Global Optimization based on Contractor Programming: an Overview of the IBEX library

International audienceIBEX is an open-source C++ library for constraint processing over real numbers. It provides reliable algorithms for handling non-linear constraints. In particular, roundoff errors are also taken into account. It is based on interval arithmetic and affine arithmetic. The main feature of IBEX is its ability to build strategies declaratively through the contractor programming paradigm. It can also be used as a black-box solver or with an AMPL interface. Two emblematic problems that can be addressed are: (i) System solving: A guaranteed enclosure for each solution of a system of (nonlinear) equations is calculated; (ii) Global optimization: A global minimizer of some function under non-linear constraints is calculated with guaranteed and reliable bounds on the objective minimum

Scalable Parallel Numerical Constraint Solver Using Global Load Balancing

We present a scalable parallel solver for numerical constraint satisfaction problems (NCSPs). Our parallelization scheme consists of homogeneous worker solvers, each of which runs on an available core and communicates with others via the global load balancing (GLB) method. The parallel solver is implemented with X10 that provides an implementation of GLB as a library. In experiments, several NCSPs from the literature were solved and attained up to 516-fold speedup using 600 cores of the TSUBAME2.5 supercomputer.Comment: To be presented at X10'15 Worksho

Long Text Generation via Adversarial Training with Leaked Information

Automatically generating coherent and semantically meaningful text has many applications in machine translation, dialogue systems, image captioning, etc. Recently, by combining with policy gradient, Generative Adversarial Nets (GAN) that use a discriminative model to guide the training of the generative model as a reinforcement learning policy has shown promising results in text generation. However, the scalar guiding signal is only available after the entire text has been generated and lacks intermediate information about text structure during the generative process. As such, it limits its success when the length of the generated text samples is long (more than 20 words). In this paper, we propose a new framework, called LeakGAN, to address the problem for long text generation. We allow the discriminative net to leak its own high-level extracted features to the generative net to further help the guidance. The generator incorporates such informative signals into all generation steps through an additional Manager module, which takes the extracted features of current generated words and outputs a latent vector to guide the Worker module for next-word generation. Our extensive experiments on synthetic data and various real-world tasks with Turing test demonstrate that LeakGAN is highly effective in long text generation and also improves the performance in short text generation scenarios. More importantly, without any supervision, LeakGAN would be able to implicitly learn sentence structures only through the interaction between Manager and Worker.Comment: 14 pages, AAAI 201

Methods, systems, and devices for pairing vagus nerve stimulation with motor therapy in stroke patients

A method of treating motor deficits in a stroke patient, comprising assessing a patient's motor deficits, determining therapeutic goals for the patient, based on the patient's motor deficits, selecting therapeutic tasks based on the therapeutic goals, performing each of the selected therapeutic tasks repetitively, observing the performance of the therapeutic tasks, initiating the stimulation of the vagus nerve manually at approximately a predetermined moment during the performance of the therapeutic tasks, stimulating the vagus nerve of the patient during the performance of the selected therapeutic tasks, and improving the patient's motor deficits.Board of Regents, University of Texas Syste

Diversification and Intensification in Hybrid Metaheuristics for Constraint Satisfaction Problems

Metaheuristics are used to find feasible solutions to hard Combinatorial Optimization Problems (COPs). Constraint Satisfaction Problems (CSPs) may be formulated as COPs, where the objective is to reduce the number of violated constraints to zero. The popular puzzle Sudoku is an NP-complete problem that has been used to study the effectiveness of metaheuristics in solving CSPs. Applying the Simulated Annealing (SA) metaheuristic to Sudoku has been shown to be a successful method to solve CSPs. However, the ‘easy-hard-easy’ phase-transition behavior frequently attributed to a certain class of CSPs makes finding a solution extremely difficult in the hard phase because of the vast search space, the small number of solutions and a fitness landscape marked by many plateaus and local minima. Two key mechanisms that metaheuristics employ for searching are diversification and intensification. Diversification is the method of identifying diverse promising regions of the search space and is achieved through the process of heating/reheating. Intensification is the method of finding a solution in one of these promising regions and is achieved through the process of cooling. The hard phase area of the search terrain makes traversal without becoming trapped very challenging. Running the best available method - a Constraint Propagation/Depth-First Search algorithm - against 30,000 benchmark problem-instances, 20,240 remain unsolved after ten runs at one minute per run which we classify as very hard. This dissertation studies the delicate balance between diversification and intensification in the search process and offers a hybrid SA algorithm to solve very hard instances. The algorithm presents (a) a heating/reheating strategy that incorporates the lowest solution cost for diversification; (b) a more complex two-stage cooling schedule for faster intensification; (c) Constraint Programming (CP) hybridization to reduce the search space and to escape a local minimum; (d) a three-way swap, secondary neighborhood operator for a low expense method of diversification. These techniques are tested individually and in hybrid combinations for a total of 11 strategies, and the effectiveness of each is evaluated by percentage solved and average best run-time to solution. In the final analysis, all strategies are an improvement on current methods, but the most remarkable results come from the application of the “Quick Reset” technique between cooling stages

Depth and Size Limits for the Visibility of Veins Using the VeinViewer Imaging System

Administration of fluids or medication and blood draw procedures require the nurse or the phlebotomist to access the veins in patients at hospitals or phlebotomy centers. It is important to minimize the discomfort associated with sticking needles in the patient more than once and most often, necessary to find an appropriate vein within few minutes. However, problems involved in accessing veins in pediatric and obese patients make it very difficult to perform a successful stick in a short time. The VeinViewer Imaging System is an infrared imaging device that provides the nurses and phlebotomists a means for locating veins in the very first attempt and within a few seconds. A camera captures an image of the veins illuminated by infrared light and a contrast-enhanced image of the veins is projected back onto the patient’s skin in real-time using a projector, after being processed by a computer. Each vein in the VeinViewer image appears with different contrast against the background skin. To evaluate the performance of the device, a thorough investigation of the properties of the vein affecting its contrast can be of immense value. The goal of this research is to determine quantitatively the effect of physical properties of veins such as depth and diameter on its visibility in the VeinViewer image. The results of this study can be interpreted to understand the biological phenomena influencing the quality of the VeinViewer image. An extension of this study may lead to advancement in the hardware or software which potentially will benefit the phlebotomists and physicians

Severe birth prematurity : a case study of a boy’s psychoeducational support needs

Abstract: This study conducted research related to severe premature birth and the neurodevelopmental disorders that may be associated with it. Severely premature born children, born before the gestational age of 28 weeks, are at an increased risk of developmental delays. These delays may manifest as physical difficulties, learning disabilities, attention deficits, hyperactivity, and behavioural and social problems. Learners with barriers to learning present challenges for teachers due to these developmental delays and comorbid disorders associated with premature birth. The challenges are further intensified by large class sizes, and limited resources. Teachers are generally ill-equipped to meet the demands of the learners in an inclusive situation, in diverse classrooms. It is difficult to differentiate the content and the pace of the curriculum. This study explored the psycho-educational support needs of Lebo (pseudonym), who was born severely premature. The study was conducted in a LSEN class in a mainstream primary school in the south of Johannesburg. ..M.Ed. (Inclusive Education

Dry-Ice Blasting of Auto Robotic Assemblies

Welding robots are extensively applied in the automotive assemblies and Spot Welding is the most common welding application practiced in the auto stamping assembly manufacturing. Though adaptive resistance welding control automatically compensates to keep production and quality up to the levels needed as welding gun tips undergo wear so that the welds remain reliable; the system cannot compensate for deterioration caused by the slag and spatter on the part holding fixtures, sensors, and gun tips. To cleanse welding robots of slag and spatter, dry-ice blasting has proven to be an effective antidote. This paper describes Spot welding process, analyses the slag and spatter formation during robotic welding of stamping assemblies, and concludes that the dry ice blasting processs utility in cleansing of welding robots in auto stamping plant operations is preeminent