Exploiting parallelism: highly competitive semantic tree theorem prover

Semantic trees have often been used as a theoretical tool for showing the unsatisfiability of clauses in first-order predicate logic. Their practicality has been overshadowed, however, by other strategies. In this paper, we introduce unit clauses derived from resolutions when necessary to construct a semantic tree, leading to a strategy that combines the construction of semantic trees with resolution–refutation. The parallel semantic tree theorem prover, called PrHERBY, combines semantic trees and resolution–refutation methods. The parallel system is scalable by strategically selecting atoms with the help of dedicated resolutions. In addition, a parallel grounding scheme allows each system to have its own instance of generated atoms, thereby increasing the possibility of success. The PrHERBY system presented performs significantly better and generally finds proof using fewer atoms than the semantic tree prover, HERBY and its parallel version, PHERBY.     

加强PLC实践教学改革培养高素质创新型人才

可编程控制器是自动化专业中一门应用性很强的专业课程,其实践教学是培养学生实践动手能力和创新精神的重要途径。本文从课程实验、课程设计、课程实习、师资队伍建设和实践基地建设等方面,研究PLC实践教学改革,并在实践过程中使学生的工程素质和创新能力得到了明显提高。     

On the approximation of the slot occupancy pattern in a DQDB network

This paper presents a novel approach to DQDB modeling in underload conditions; the innovative aspect lies in the representation of the slot-occupancy-pattern process on the forward bus. In the literature this process has been often modeled as a Bernoulli process, implying that the status (empty/busy) of consecutive slots are independent. Results presented in this paper, however, show that even at light loads the interdependence between slots is significant. Our model captures some of this interdependence by using a discrete-time first-order Markov process for the slot-occupancy-pattern process on the forward bus. In the paper we identify a simplified DQDB network for which we derive a closed formula for the joint probability density function for the slot occupancy pattern of two consecutive slots. The accuracy of our results is investigated via simulation. Finally, an application of our first-order Markov model is shown through an investigation of the performance of a gateway concentrating several DQDB networks in a slotted trunk.     

Exploiting application locality to design low-complexity, highly performing, and power-aware embedded classifiers

Temporal and spatial locality of the inputs, i.e., the property allowing a classifier to receive the same samples over time-or samples belonging to a neighborhood-with high probability, can be translated into the design of embedded classifiers. The outcome is a computational complexity and power aware design particularly suitable for implementation. A classifier based on the gated-parallel family has been found particularly suitable for exploiting locality properties: Subclassifiers are generally small, independent each other, and controlled by a master-enabling module granting that only a subclassifier is active at a time, the others being switched off. By exploiting locality properties we obtain classifiers with accuracy comparable with the ones designed without integrating locality but gaining a significant reduction in computational complexity and power consumption.     

Smart monopole antenna with pattern and frequency reconfiguration characteristics based on programmable metasurface

Metasurfaces having ultrathin and planar structure with sub‐wavelength unit cell, have recently gained significant potential for use thanks to their control capabilities over the electromagnetic waves from microwave to the visible range. The structure and the dimensions of the sub‐wavelength elements determine the electromagnetic properties, capabilities, and functionalities of the metasurfaces providing a full control of the reflected and transmitted fields and these metasurfaces are referred to as analog metasurfaces. When adjustability is added to the unit cells, programmable or digital metasurfaces are obtained, allowing us to take multiple unique functionality advantages controlled by external stimuli. In this study, we propose a metasurface structure, also known as 1‐bit coding metasurface, which is controlled depending on the “On/Off” state. The “On/Off” state is controlled by a computer program using genetical algorithm. Depending on the operating state, electromagnetic waves can be manipulated and different functionalities of the metasurfaces can be realized. The contribution and innovation of the study is the demonstration of the beam rotation, resonance frequency shift and radiation pattern reconfiguration properties of a simple monopole antenna by using controllable metasurface composed of T shaped resonator and circular patch with an operating frequency between 4.3 and 5.6 GHz.     

Complex weight control of array pattern nulling

An efficient method based on the sequential quadratic programming (SQP) algorithm for the linear antenna arrays pattern synthesis with prescribed nulls in the interference direction and minimum side lobe levels by the complex weights of each array element is presented. In general, the pattern synthesis technique that generates a desired pattern is a greatly nonlinear optimization problem. SQP method is a versatile method to solve the general nonlinear constrained optimization problems and is much simpler to implement. It transforms the nonlinear minimization problem to a sequence of quadratic subproblem that is easier to solve, based on a quadratic approximation of the Lagrangian function. Several numerical results of Chebyshev pattern with the imposed single, multiple, and broad nulls sectors are provided and compared with published results to illustrate the performance of the proposed method. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007.     

Adaptive occupancy grid mapping with clusters

In this article, we describe an algorithm for acquiring occupancy grid maps with mobile robots. The standard occupancy grid mapping developed by Elfes and Moravec in the mid-1980s decomposes the high-dimensional mapping problem into many one-dimensional estimation problems, which are then tackled independently. Because of the independencies between neighboring grid cells, this often generates maps that are inconsistent with the sensor data. To overcome this, we propose a cluster that is a set of cells. The cells in the clusters are tackled dependently with another occupancy grid mapping with an expectation maximization (EM) algorithm. The occupancy grid mapping with an EM algorithm yields more consistent maps, especially in the cluster. As we use the mapping algorithm adaptively with clusters according to the sensor measurements, our mapping algorithm is faster and more accurate than previous mapping algorithms. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

Exploiting partial order with Quicksort

The widely known Quicksort algorithm does not attempt to actively take advantage of partial order in sorting data. A simple change can be made to the Quicksort strategy to give a bestcase performance of n, for ordered data, with a smooth transition to O(n log n) for random data. This algorithm (Transort) matches the performance of Sedgewick's claimed best implementation of Quicksort for random data.     

Efficient representative pattern mining based on weight and maximality conditions

As a core area in data mining, frequent pattern (or itemset) mining has been studied for a long time. Weighted frequent pattern mining prunes unimportant patterns and maximal frequent pattern mining discovers compact frequent patterns. These approaches contribute to improving mining performance by reducing the search space. However, we need to consider both the downward closure property and patterns' subset checking process when integrating these different methods in order to prevent unintended pattern losses. Moreover, it is also essential to extract valid patterns with faster runtime and less memory consumption. For this reason, in this paper, we propose more efficient maximal weighted frequent pattern (MWFP) mining approaches based on tree and array structures. We describe how to handle these problems more efficiently, maintaining the correctness of our method. We develop two types of maximal weighted frequent mining algorithms based on weight ascending order and support descending order and compare these two algorithms to conclude which is more suitable for MWFP mining. In addition, comprehensive tests in this paper show that our algorithms are more efficient and scalable than state‐of‐the‐art algorithms, and they also have the correctness of the MWFP mining in terms of their pattern generation results.     

Object relevance weight pattern mining for activity recognition and segmentation

Monitoring daily activities of a person has many potential benefits in pervasive computing. These include providing proactive support for the elderly and monitoring anomalous behaviors. A typical approach in existing research on activity detection is to construct sequence-based models of low-level activity features based on the order of object usage. However, these models have poor accuracy, require many parameters to estimate, and demand excessive computational effort. Many other supervised learning approaches have been proposed but they all suffer from poor scalability due to the manual labeling involved in the training process. In this paper, we simplify the activity modeling process by relying on the relevance weights of objects as the basis of activity discrimination rather than on sequence information. For each activity, we mine the web to extract the most relevant objects according to their normalized usage frequency. We develop a KeyExtract algorithm for activity recognition and two algorithms, MaxGap and MaxGain, for activity segmentation with linear time complexities. Simulation results indicate that our proposed algorithms achieve high accuracy in the presence of different noise levels indicating their good potential in real-world deployment.     

Exploiting reality with multicast groups

This article describes our investigation into developing large distributed simulations. The architecture we describe logically partitions virtual environments by associating spatial, temporal, and functional classes with network multicast groups. We exploit the actual characteristics of the real-world large scale environments being simulated by focusing or restricting an entity's processing and network resources to its area of interest via a local area-of-interest manager. For example, a simulated infantryman in a virtual environment doesn't need to know the condition of a simulated truck 20 virtual kilometres away     

Exploiting Loop Parallelism with Redundant Execution

In this paper,a new loop transformation is proposed that can expolit paralleism in loops which cannot be found by traditional methods.Then the method is extended to show how to achieve maximum speedup of loops if there are infinite processors and how to balance the workload of parallel sections in loops if there is fixed number of processors.     

抑制风噪声的频点离散值加权GCC-PHAT时延估计算法

针对麦克风阵列使用GCC-PHAT算法估计信号到达时差对加性噪声敏感,以及基于信噪比估计的连续值加权GCC-PHAT算法无法消除环境中类似风噪声的变化噪声干扰的情况,提出了一种抑制风噪声的频点加权GCC-PHAT算法。通过分析已有算法的不足,新算法选择使用离散频点加权,并通过信号频点间相干性量化值和时域关联性计算权值,去除风噪声干扰频点;同时估计声源信号活跃度,调整算法运算量。实验表明,与已有的GCCPHAT算法相比,新算法能有效消除风噪声对估计结果的干扰,同时降低运算负载。     

Design of miniaturized highly sensitive liquid sensor at microwave frequency

In this paper, we have presented a simple, miniaturized, and highly sensitive liquid sensor, which determines the dielectric properties of liquids at microwave frequency. In the proposed design, the concept of interdigital capacitor (IDC) is employed to construct the sensor. The proposed IDC based sensor responds differently depending on the liquids' dielectric property. The proposed structure utilizes the shift in resonance frequency and peak attenuation as the sensing parameter to determine the complex dielectric permittivity of the unknown liquids. The advantage of the proposed sensor structure lies in its compactness (0.08λ₀ × 0.08λ₀ × 0.003λ₀) and high sensitivity, 0.42%. The designed sensor can also be used in the biomedical field for noninvasive bio‐liquid characterization.     

Multicamera people tracking with a probabilistic occupancy map

Given two to four synchronized video streams taken at eye level and from different angles, we show that we can effectively combine a generative model with dynamic programming to accurately follow up to six individuals across thousands of frames in spite of significant occlusions and lighting changes. In addition, we also derive metrically accurate trajectories for each one of them.Our contribution is twofold. First, we demonstrate that our generative model can effectively handle occlusions in each time frame independently, even when the only data available comes from the output of a simple background subtraction algorithm and when the number of individuals is unknown a priori. Second, we show that multi-person tracking can be reliably achieved by processing individual trajectories separately over long sequences, provided that a reasonable heuristic is used to rank these individuals and avoid confusing them with one another.     

Chaotic neural network controlled by particle swarm with decaying chaotic inertia weight for pattern recognition

This study introduces a new type of chaotic neural network, which is built upon perturbed Duffing oscillator. The neurons in this network behave collectively based on a modified version of Duffing map. The proposed neural processor can act chaotically at some areas of the state space. The network has some parameters, which can be adjusted for the system to behave either chaotically or periodically. This nonlinear network adopts the bifurcating behavior of the chaotic Duffing map for the most covered search in the neuronal search space. The neuron’s search space is controlled by swarming in the parameter space to settle the parameters of the network into the critical parameters. Swarming of the parameters is based on particle swarm optimization heuristic. The modified particle swarm adopts a decaying inertia weight based on chaotic logistic map to fast settle down into the attractors of periodic solutions. At last, the swarm-controlled neurochaotic processor is applied to build three models to control parameters of the network. Each model is trained to recognize a set of binary patterns that are as the form of alphabetic letters as a classical pattern recognition problem. A comparison study is then conducted among these three models, Hopfield network and a modified Hopfield model, which demonstrate all three models outperform Hopfiled model and are competitive and in most cases outperform the modified Hopfield model.     

图样匹配跳频系统的性能及图样码型选择

针对跳频通信在宽带噪声干扰和梳状干扰下误比特性能较差的问题,基于“信道即消息”的思想,提出了一种新的短波跳频通信技术——图样匹配跳频.以Williard码、Walsh码和Gold码为例,分析了几种图样码的特性及对系统抗干扰能力和信息速率的影响.提出了图样码的选取要求,结合系统的两种帧同步策略分别给出了图样码型,对FH/MFsK和图样匹配跳频系统进行了仿真对比.仿真结果表明,图样匹配跳频系统具有更强的抗干扰能力,在恶意干扰严重影响常规跳频的误码性能时,图样匹配跳频可以显著提升通信的可靠性.     

Exploiting GPUs with the Super Instruction Architecture

The Super Instruction Architecture (SIA) is a parallel programming environment designed for problems in computational chemistry involving complicated expressions defined in terms of tensors. Tensors are represented by multidimensional arrays which are typically very large. The SIA consists of a domain specific programming language, Super Instruction Assembly Language (SIAL), and its runtime system, Super Instruction Processor. An important feature of SIAL is that algorithms are expressed in terms of blocks (or tiles) of multidimensional arrays rather than individual floating point numbers. In this paper, we describe how the SIA was enhanced to exploit GPUs, obtaining speedups ranging from two to nearly four for computational chemistry calculations, thus saving hours of elapsed time on large-scale computations. The results provide evidence that the “programming-with-blocks” approach embodied in the SIA will remain successful in modern, heterogeneous computing environments.     

Topological indentation pattern design of plates for maximum frequency gap

The vibrational response of thin plates is improved by a new approach of indenting some portions along the normal direction so that the interval between two successive eigenfrequencies is enlarged while keeping their mass the same. Binary-coded genetic algorithm (GA) is used as the search algorithm. A stochastically-applied deterministic filter is developed like another genetic operator for GA to accelerate the convergence speed. The corresponding eigenfrequencies and their mode shapes are found by using finite element analysis. The results indicate significant improvement for the band-gap over no indentation designs and show the effectiveness of the new operator of GA.     

Exploiting multiple knowledge models in the development of real-time diagnostic expert systems for highly automated manufacturing plants

This paper describes the results of the DIREK Project (knowledge-based, real-time diagnosis and repair for a robotized handling and storage system), aimed at developing a real-time diagnosis system for a highly automated SNIA fibre spinning plant. The project effectively implemented a multi-model approach to diagnosis in manufacturing environments, exploiting structural, functional, behavioural and heuristic models. Among other things, particular emphasis has been placed on the plant behavioural model, which can be derived from the software code running on the PLCs which control an automated manufacturing facility. The existing diagnostic system is now operational at an SNIA plant in Italy, fully integrated with the factory environment and able to support different levels of users through distributed man-machine interfaces. The paper provides an insight into the theoretical background of the project and describes the adopted methodology, with special attention given to the knowledge acquisition problems arising in the development of the various knowledge models included in the diagnostic system. Furthermore, the architecture and functionalities of the existing system are described, along with the achieved benefits and further exploitation potential. Both IT and user perspectives are considered in the paper.