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International Conference on Computer Science and Network Technology

作者： Wenzhong Yan Dongming Li Dept. of Comput. North China Inst. of Sci. & Technol. Beijing China

ISBN: (纸本)9781479905607

The chromosome segmentation is the most important step in the automatic chromosome analysis system. In this paper, a few basic chromosome segmentation algorithms are investigated firstly. As a common phenomenon, the partial touching and overlapping chromosomes occur in almost every metaphase images. So, as a difficult yet vital problem, the algorithms for overlapping chromosomes are discussed in detail. The principle and the realization of these algorithms are analyzed. Results of these algorithms are compared and discussed.

关键词： biology computing cellular biophysics image segmentation automatic chromosome analysis system chromosome images chromosome segmentation algorithm metaphase image overlapping chromosomes partial touching chromosomes segmentation algorithms Accuracy algorithm design and analysis Biological cells Classification algorithms Entropy Image segmentation Shape chromosome overlapping segmentation image segmentation algorithm design and analysis Chromosomes biology computing cellular biophysics cytology sorting algorithm segmentation Segmentation entropy

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Microwave technology for localization of traumatic intracranial bleedings - a numerical simulation study

Microwave technology for localization of traumatic intracran...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Stefan Candefjord Johan Winges Yinan Yu Thomas Rylander Tomas McKelvey Department of Signals and Systems Chalmers University of Technology

ISBN: (纸本)9781457702150

Traumatic brain injury (TBI) is a major public health problem worldwide. Intracranial bleedings represents the most serious complication of TBI and need to be surgically evacuated promptly to save lives and mitigate injury. Microwave technology (MWT) is promising as a complement to computed tomography (CT) to be used in road and air ambulances for early detection of intracranial bleedings. In this study, we perform numerical simulations to investigate if a classification algorithm based on singular value decomposition can distinguish between bleedings at different positions adjacent to the skull bone for a similar but simplified problem. The classification accuracy is 94-100 % for all classes, a result that encourages us to pursue our efforts with MWT for more realistic scenarios. This indicates that MWT has potential for localizing a detected bleeding, which would increase the diagnostic value of this technique.

关键词： Microwave technology Skull sorting algorithm Air Ambulances numerical simulation Singular value decomposition MEGAWATT THERMAL Hemorrhage diagnostic value Early Diagnosis Road X-Ray Computed Tomography

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Hardware Implementation of Ground Classification for a Walking Robot

Hardware Implementation of Ground Classification for a Walki...

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Workshop on Robot Motion and Control

作者： Krzysztof Walas Adam Schmidt Marek Kraft Michal Fularz Faculty of Electrical Engineering Poznan University of Technology

ISBN: (纸本)9781467355094

The mobile robot requires the knowledge about the ground type in front of it to efficiently negotiate diverse terrain types while working outdoors. This article presents the implementation of ground classification algorithms in a Field Programmable Gate Array structure. The terrain type classification is based on the signals acquired with force/torque sensor mounted on the walking robot foot. The hardware implementation allows for offloading of the resource demanding computations. The paper begins with a short presentation of the experimental setup. Then the classification algorithms are described. Finally the description of hardware implementation of the algorithms is given followed by the test results.

关键词： walking robots Field programmable gate arrays Computer hardware resource requirements UNLOADING sorting algorithm Mobile robots ground terrains type classification

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GA(M)E-QSAR: A Novel, Fully Automatic Genetic-algorithm-(Meta)-Ensembles Approach for Binary Classification in Ligand-Based Drug Design

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JOURNAL OF CHEMICAL INFORMATION AND MODELING 2012年第9期52卷 2366-2386页

作者： Perez-Castillo, Yunierkis Lazar, Cosmin Taminau, Jonatan Froeyen, Mathy Angel Cabrera-Perez, Miguel Nowe, Ann Vrije Univ Brussel Fac Sci Dept Comp Sci Computat Modeling Lab CoMo B-1050 Brussels Belgium Univ Cent Marta Abreu Villas Ctr Bioact Quim Mol Simulat & Drug Design Grp Santa Clara Cuba Katholieke Univ Leuven Rega Inst Med Res Med Chem Lab B-3000 Louvain Belgium Univ Miguel Hernandez Fac Pharm Dept Engn Pharm & Pharmaceut Technol Area Alicante 03550 Spain

Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

关键词： FULL-SCALE sorting algorithm chemical compounds Searches Binary useful area Drug Design weight sums Feature extraction Genetic algorithm (GA) Robustness

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Fine-sorting one-dimensional particle-in-cell algorithm with Monte-Carlo collisions on a graphics processing unit

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COMPUTER PHYSICS COMMUNICATIONS 2011年第10期182卷 2161-2167页

作者： Mertmann, Philipp Eremin, Denis Mussenbrock, Thomas Brinkmann, Ralf Peter Awakowicz, Peter Ruhr Univ Bochum Inst Elect Engn & Plasma Technol D-44801 Bochum Germany Ruhr Univ Bochum Inst Theoret Elect Engn D-44801 Bochum Germany

Particle-in-cell (PIC) simulations with Monte-Carlo collisions are used in plasma science to explore a variety of kinetic effects. One major problem is the long run-time of such simulations. Even on modern computer systems, PIC codes take a considerable amount of time for convergence. Most of the computations can be massively parallelized, since particles behave independently of each other within one time step. Current graphics processing units (GPUs) offer an attractive means for execution of the parallelized code. In this contribution we show a one-dimensional PIC code running on NVIDIA (R) GPUs using the CUDA (TM) environment. A distinctive feature of the code is that size of the cells that the code uses to sort the particles with respect to their coordinates is comparable to size of the grid cells used for discretization of the electric field. Hence, we call the corresponding algorithm "fine-sorting". Implementation details and optimization of the code are discussed and the speed-up compared to classical CPU approaches is computed. (C) 2011 Elsevier By. All rights reserved.

关键词： GPU PIC Particle-in-cell sorting algorithm CUDA

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Classification Based on Distribution of Average Matching Degree and Gaussian Function and Its Application to Intrusion Detection

Classification Based on Distribution of Average Matching Deg...

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Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE)

作者： Li, Yuhong Mabu, Shingo Lu, Nannan Hirasawa, Kotaro Waseda Univ Grad Sch Informat Prod & Syst Wakamatsu Ku Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9784907764401

With the rapid development of the Internet, Internet security is becoming an important problem recently. Therefore, many techniques for intrusion detection have been proposed to protect networks effectively. In this paper, a new classification model, named classification with average matching degree and gaussian function, is proposed and combined with the class association rule mining of Genetic Network Programming (GNP). The proposed classification algorithm can efficiently classify a new access data into a class of normal, misuse or anomaly. The simulations are based on NSL-KDD data set.

关键词： Data Security Gauss equation sorting algorithm Network security

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Multi-criteria inventory classification problem: A consensus approach

Multi-criteria inventory classification problem: A consensus...

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International Conference on Modeling, Simulation and Applied Optimization

作者： Imen Lajili Talel Ladhari M. Zied Babai Ecole Superieure des Sciences Economiques et Commerciales Combinatorial Optimization Research Group ROI Ecole Polytechnique de Tunisie BEM-Bordeaux Management School

ISBN: (纸本)9781467358125

In this paper, we consider the multi-criteria inventory classification problem. We propose a new classification algorithm referred to as Constructive_Order_Classification_algorithm (COCA). This algorithm is based on some simple priority rules and aims to standardize the classification and provide relative stability in the classification through a consensus process. An illustrative example is used to explain the different steps of the proposed algorithm.

关键词： Taxonomy sorting algorithm priority rule coca CONSENT ORDER AND COMPLIANCE AGREEMENT inventories

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Evaluation of Fall Detection Classification Approaches

Evaluation of Fall Detection Classification Approaches

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4th International Conference on Intelligent and Advanced Systems (ICIAS) and A Conference of World Engineering, Science and Technology Congress (ESTCON)

作者： Kerdegari, Hamideh Samsudin, Khairulmizam Ramli, Abdul Rahman Mokaram, Saeid Univ Putra Malaysia Dept Comp & Commun Syst Comp Syst Lab Serdang Malaysia Univ Putra Malaysia Inst Adv Technol Intelligent Syst & Robot Lab Serdang Malaysia

ISBN: (纸本)9781457719677

As we grow old, our desire for being independence does not decrease while our health needs to be monitored more frequently. Accidents such as falling can be a serious problem for the elderly. An accurate automatic fall detection system can help elderly people be safe in every situation. In this paper a waist worn fall detection system has been proposed. A tri-axial accelerometer (ADXL345) was used to capture the movement signals of human body and detect events such as walking and falling to a reasonable degree of accuracy. A set of laboratory-based falls and activities of daily living (ADL) were performed by healthy volunteers with different physical characteristics. This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. The aim of this paper is to investigate the performance of different classification algorithms for a set of recorded acceleration data. The algorithms are Multilayer Perceptron, Naive Bayes, Decision tree, Support Vector Machine, ZeroR and OneR. The acceleration data with a total data of 6962 instances and 29 attributes were used to evaluate the performance of the different classification algorithm. Results show that the Multilayer Perceptron algorithm is the best option among other mentioned algorithms, due to its high accuracy in fall detection.

关键词： sorting algorithm Falling Activities of Daily Living Detection systems Accidental Falls total Information aged person Multilayer perceptrons Autumn Human Body

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A Power Wheelchair Controlled using Hand Gestures, a Single sEMG Sensor, and Guided Under-determined Source Signal Separation

A Power Wheelchair Controlled using Hand Gestures, a Single ...

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4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) / Symposium on Surgical Robotics

作者： Rivera, Luis A. DeSouza, Guilherme N. Univ Missouri Dept Elect & Comp Engn Columbia MO 65211 USA

ISBN: (纸本)9781457712005

Surface Electromyographic signals (sEMG) find applications in many areas such as rehabilitation, prosthesis and human-machine interaction. Systems reliant on these muscle-generated electrical signals require some form of machine learning algorithm for recognition of specific patterns of muscle activity. Those systems vary in terms of the signal detection methods, the feature selection and the classification algorithm used, however, in all those cases, the use of multiple sensors is a constant requirement. In this paper, we present a power wheelchair control system that relies on a single sEMG sensor and a new technique for signature recognition called Guided Under-determined Source Signal Separation (GUSSS). Compared to other approaches in the literature, the proposed technique achieves comparable results even when using a simple distance classifier and a very small number of features.

关键词： Electric wheelchair SEMA5B gene Source separation sorting algorithm Machine learning algorithms Hand Sensors Gestures Feature extraction

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A Novel Parallel Approach of Radix Sort with Bucket Partition Preprocess

A Novel Parallel Approach of Radix Sort with Bucket Partitio...

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14th IEEE International Conference on High Performance Computing and Communications (HPCC) / IEEE 9th International Conference on Embedded Software and Systems (ICESS)

作者： Zhang, Keliang Wu, Baifeng Fudan Univ Sch Comp Sci Shanghai 201203 Peoples R China

ISBN: (纸本)9780769547497

Radix sort is an important sorting algorithm which is widely used in applications such as binary search and database. The most important advantage of radix sort is its time complexity is O(n), lower than other sorting algorithms based on comparison operation. However, a factor that hampers its application is long execution time of its loop body. In this paper, based on data level parallelism idea, we present a new parallel radix sort algorithm. In this algorithm, each iteration of loop can be fully parallelized via thounds of concurrent threads, eliminating the original performance bottleneck. Furthermore, it is a scalable algoirthm, which means the performance of algorithm can be linearly improved with the increase of core number of modern many-core processors. Experiment results show the efficiency of the algorihtm.

关键词： radix sorting sorting algorithm caliber number Binary search algorithm efficiency Loops execution time complexity classes algorithms ALEMBIC buckets

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