Automatic verification of functional programs

We propose an approach to verification of functional programs based on an example of methods and tools developed in functional programming. The program verification procedures and tools developed in the framework of this approach are described.Translated from Kibernetika, No. 4, pp. 30–39, July–August, 1990.     

Automatic extraction of functional parallelism from ordinaryprograms

Presents the hierarchical task graph (HTG) as an intermediate parallel program representation which encapsulates minimal data and control dependences, and which can be used for the extraction and exploitation of functional, or task-level parallelism. The hierarchical nature of the HTG facilitates efficient task-granularity control during code generation, and thus applicability to a variety of parallel architectures. The construction of the HTG at a given hierarchy level, the derivation of the execution conditions of tasks which maximizes task-level parallelism, and the optimization of these conditions which results in reducing synchronization overhead imposed by data and control dependences are emphasized. Algorithms for the formation of tasks and their execution conditions based on data and control dependence constraints are presented. The issue of optimization of such conditions is discussed, and optimization algorithms are proposed. The HTG is used as the intermediate representation of parallel Fortran and C programs for generating parallel source as well as parallel machine code     

基于序列匹配的自动评分算法设计

通过分析模拟训练设备的操作特点,以序列匹配方法为基础,结合模糊逻辑的思维,设计实现模拟训练设备操作教学考核的自动评分算法.该算法能对学员的操作过程进行自动评分.评分过程和评分结果表明,该算法对模拟设备具有普适性,符合人工评分的要求,能客观反映操作员的操作水平.     

Automatic support for usability evaluation

The main goal of the work is to propose a method to evaluate user interfaces using task models and logs generated from a user test of an application. The method can be incorporated into an automatic tool which gives the designer information useful to evaluate and improve the user interface. These results include an analysis of the tasks which have been accomplished, those which failed and those never tried, user errors and their type, time related information, task patterns among the accomplished tasks, and the available tasks from the current state of the user session. This information is also useful to an evaluator checking whether the specified usability goals have been accomplished     

Automatic regeneration of sequence programs for operating plants

Today, many plants built in the 1960s will probably be replaced or maintained. However, it is difficult to replace or maintain them because the installed sequential control logic documents are seldom still in existence. Therefore, we have proposed an automatic regeneration method (SPAIR) in order to solve this problem. SPAIR regenerates sequential control logic that is expressed on a ladder diagram from the input and output data of a target control unit and its supplementary specifications, which indicate the information about timers and interior coils. Time series data is compressed and translated into training data using the specifications. The training data are processed by inductive learning and transformed into control logic. We have developed the SPAR-System in order to edit all kinds of data, generate target logic for plants, and to easily verify the inferred logic simulation plant. Simulation experiments confirmed that control logic that is regenerated by SPAIR behaves in the same way as the installed control logic of a target plant model     

Discovering multi-label temporal patterns in sequence databases

Sequential pattern mining is one of the most important data mining techniques. Previous research on mining sequential patterns discovered patterns from point-based event data, interval-based event data, and hybrid event data. In many real life applications, however, an event may involve many statuses; it might not occur only at one certain point in time or over a period of time. In this work, we propose a generalized representation of temporal events. We treat events as multi-label events with many statuses, and introduce an algorithm called MLTPM to discover multi-label temporal patterns from temporal databases. The experimental results show that the efficiency and scalability of the MLTPM algorithm are satisfactory. We also discuss interesting multi-label temporal patterns discovered when MLTPM was applied to historical Nasdaq data.     

Mining sequential patterns from multidimensional sequence data

The problem addressed in This work is to discover the frequently occurred sequential patterns from databases. Although much work has been devoted to this subject, to the best of our knowledge, no previous research was able to find sequential patterns from d-dimensional sequence data, where d>2. Without such a capability, many practical data would be impossible to mine. For example, an online stock-trading site may have a customer database, where each customer may visit a Web site in a series of days; each day takes a series of sessions and each session visits a series of Web pages. Then, the data for each customer forms a 3-dimensional list, where the first dimension is days, the second is sessions, and the third is visited pages. To mine sequential patterns from this kind of sequence data, two efficient algorithms have been developed in This work.     

Mining sequential patterns across multiple sequence databases

In this paper, given a set of sequence databases across multiple domains, we aim at mining multi-domain sequential patterns, where a multi-domain sequential pattern is a sequence of events whose occurrence time is within a pre-defined time window. We first propose algorithm Naive in which multiple sequence databases are joined as one sequence database for utilizing traditional sequential pattern mining algorithms (e.g., PrefixSpan). Due to the nature of join operations, algorithm Naive is costly and is developed for comparison purposes. Thus, we propose two algorithms without any join operations for mining multi-domain sequential patterns. Explicitly, algorithm IndividualMine derives sequential patterns in each domain and then iteratively combines sequential patterns among sequence databases of multiple domains to derive candidate multi-domain sequential patterns. However, not all sequential patterns mined in the sequence database of each domain are able to form multi-domain sequential patterns. To avoid the mining cost incurred in algorithm IndividualMine, algorithm PropagatedMine is developed. Algorithm PropagatedMine first performs one sequential pattern mining from one sequence database. In light of sequential patterns mined, algorithm PropagatedMine propagates sequential patterns mined to other sequence databases. Furthermore, sequential patterns mined are represented as a lattice structure for further reducing the number of sequential patterns to be propagated. In addition, we develop some mechanisms to allow some empty sets in multi-domain sequential patterns. Performance of the proposed algorithms is comparatively analyzed and sensitivity analysis is conducted. Experimental results show that by exploring propagation and lattice structures, algorithm PropagatedMine outperforms algorithm IndividualMine in terms of efficiency (i.e., the execution time).     

行为级模型功能比对验证的自动方法学

在混合信号芯片设计领域,Verilog/Systemverilog/VHDL等行为级模型被广泛应用于描述模拟和混合信号模块的电路特性,用以帮助实现更快速全面的全芯片功能验证。为了保证正确、有效和全面的全芯片功能验证,电路模块的行为级模型和晶体管级设计之间的功能比对验证(Behavior vs.Schematic,BVS)非常关键。在此之前,利用现有的EDA工具,只能进行逻辑状态的BVS矢量检查,而不能进行实数类型的矢量检查。为了更好地描述模拟和混合信号模块的行为特性,采用了Wreal模型和SV-UDT(Systemverilog-User Defined Type),因此对EDA工具提出了新的要求,需要其支持实数类型的矢量检查。本文描述了一种行为级模型功能比对验证的自动方法学,基于Cadence XPS仿真器的矢量检查功能,可以同时实现逻辑状态和实数类型的自动比对检查。实数类型矢量检查是向EDA供应商Cadence提出的一种新的概念和需求,且已经在XPS仿真器中成功实现。     

Automatic age estimation based on facial aging patterns

While recognition of most facial variations, such as identity, expression and gender, has been extensively studied, automatic age estimation has rarely been explored. In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. This paper proposes an automatic age estimation method named AGES (AGing pattErn Subspace). The basic idea is to model the aging pattern, which is defined as the sequence of a particular individual' s face images sorted in time order, by constructing a representative subspace. The proper aging pattern for a previously unseen face image is determined by the projection in the subspace that can reconstruct the face image with minimum reconstruction error, while the position of the face image in that aging pattern will then indicate its age. In the experiments, AGES and its variants are compared with the limited existing age estimation methods (WAS and AAS) and some well-established classification methods (kNN, BP, C4.5, and SVM). Moreover, a comparison with human perception ability on age is conducted. It is interesting to note that the performance of AGES is not only significantly better than that of all the other algorithms, but also comparable to that of the human observers.     

Structural-symmetry-related sequence patterns of the proteins of beta-propeller family

It is still not very clear to what extent and how does the amino acid sequences of proteins determine their tertiary structures. In this paper, we report our investigations of the sequence-structure relations of the proteins in the beta-propeller fold family, which adopt highly symmetrical tertiary structures while their sequences appear "random". We analyzed the amino acid sequences by using a similarity matrix plus Pearson correlation method and found that the sequences can show the same symmetries as their tertiary structures only if we deduce the conditions of sequence similarity. This suggests that some key residues may play an important role in the formation of the tertiary structures of these proteins.     

Automatic evaluation of move-limits in structural optimization

The two-point exponential approximation method was introduced by Fadelet al. (1990) and tested on structural optimization problems with stress and displacement constraints. It was subsequently tested on problems with frequency constraints (Sareenet al. 1991). The results reported in earlier papers showed reductions in the number of iterations needed to reach an optimum, and a smoother convergence towards that optimum. The method, which consists in correcting Taylor series approximations using previous design history, is used in the present paper to automatically determine move-limits. Move-limits are the allowable changes in design variables during the optimization of the approximate problem. The exponents, computed in the two-point exponential approximation by matching slopes between two design iterations, are used as a measure of non-linearity of the objective function and constraints with respect to each of the design variables. The relationships between the move-limits and the exponents are established and individual move-limits are computed and applied to each design variable. The method is applied to two classical structural optimization examples. It provides the engineer with more flexibility when choosing the move-limits and typically converges in less iterations.     

Discovering periodic cluster patterns in event sequence databases

Applied Intelligence - Since periodic events are very common everywhere, periodic pattern mining is increasingly more important in today’s data mining domain. However, there is currently no...     

'Multifrequency' location and clustering of sequence patterns from proteins

In previous work, we have shown that a set of characteristics, defined as (code frequency) pairs, can be derived from a protein family by the use of a signal-processing method. This method enables the location and extraction of sequence patterns by taking into account each (code frequency) pair individually. In the present paper, we propose to extend this method in order to detect and visualize patterns by taking into account several pairs simultaneously. Two 'multifrequency' methods are described. The first one is based on a rewriting of the sequences with new symbols which summarize the frequency information. The second method is based on a clustering of the patterns associated with each pair. Both methods lead to the definition of significant consensus sequences. Some results obtained with calcium-binding proteins and serine proteases are also discussed.     

Automatic salient object sequence rebuilding for video segment analysis

Detection of salient object sequences from video data is challenging when the salient object changes between consecutive frames. In this study, we addressed the salient object sequence rebuilding problem with video segment analysis. We reformulated the problem as a binary labeling problem, analyzed the potential salient object sequences in the video using a clustering method, and separated the salient object sequence from the background by applying an energy optimization method. Our proposed approach determines whether temporal consecutive pixels belong to the same salient object sequence. The conditional random field is then learned to effectively integrate the salient features and the sequence consecutive constraints. A dynamic programming algorithm was developed to resolve the energy minimization problem efficiently. Experimental results confirmed the ability of our approach to address the salient object rebuilding problem in automatic visual attention applications and video content analysis.     

Automatic speech patterns recognition of commands using SVM and PSO

Multimedia Tools and Applications - This paper proposes the implementation of an Automatic Speech Recognition (ASR) process through extraction of Mel-Frequency Cepstral Coefficients (MFCCs) from...     

The significance of protein sequence similarities

A general method of assessing the significance of scored best local alignments, particularly suited to protein sequence comparisons, is described. The method establishes the parameters describing the distribution of the best results from any search program, provided that the set is sufficiently large and the majority of the alignments arise from unrelated sequences. The expected frequency of occurrence of any score can then be calculated, together with the number of standard deviations above expectation. These provide sensible measures of significance without additional search operations. However the biological significance of any alignment or set of alignments does not solely depend on the improbability of the alignment, but on all relevant factors known to the biologist.     

Automatic generation of colorful patterns with wallpaper symmetries from dynamics

A new algorithm is presented in this paper for the generation of colorful images with wallpaper symmetries by means of dynamical systems. Invariant functions are employed to construct density functions for the creation of colorful images.     

Automatic linguistic reporting of customer activity patterns in open malls

Multimedia Tools and Applications - In this work, we present a complete system to produce an automatic linguistic reporting about the customer activity patterns inside open malls, a mixed...     

Automatic creation of a talking head from a video sequence

In this paper, a real-time system to create a talking head from a video sequence without any user intervention is presented. In the proposed system, a probabilistic approach, to decide whether or not extracted facial features are appropriate for creating a three-dimensional (3-D) face model, is presented. Automatically extracted two-dimensional facial features from a video sequence are fed into the proposed probabilistic framework before a corresponding 3-D face model is built to avoid generating an unnatural or nonrealistic 3-D face model. To extract face shape, we also present a face shape extractor based on an ellipse model controlled by three anchor points, which is accurate and computationally cheap. To create a 3-D face model, a least-square approach is presented to find a coefficient vector that is necessary to adapt a generic 3-D model into the extracted facial features. Experimental results show that the proposed system can efficiently build a 3-D face model from a video sequence without any user intervention for various Internet applications including virtual conference and a virtual story teller that do not require much head movements or high-quality facial animation.