Algorithm For Automatic Generation Research Articles

An automatic quadrilateral mesh generation algorithm applied to 2-D overland flow simulations

This paper presents an automatic quadrilateral mesh generation algorithm to provide 2-D meshes for simulating overland flow and transport problems in watershed systems. The conformal mapping method is studied deeply and specific treatment strategies are established according to the width of rivers and the area of other water storage zones. A conformity treatment method is proposed to deal with the incompatibility problems during discretizing the complex geometry with a plurality of sub-domains. This method ensures grid conformity through removing certain overlapped nodes and creating new appropriate nodes on common boundaries of the multi-domain mesh. Aiming at the undesired deviation of mesh boundaries from geometric contours, a relative position-percent interpolation method is proposed and a supplementary match method related to dead ends is presented. And, the double effects of projection and smooth for boundary nodes are achieved. An objective function method is proposed to locally optimize the degenerated quadrilaterals located on concave or large-curvature curves. In order to accommodate the need for overland simulations, the 1-D/2-D correspondence on river reaches, junctions with and without storage, ponds, lakes, dead ends and control structures is established. Finally, practical applications are provided to demonstrate the accuracy and reliability of the quadrilateral meshing algorithms proposed in this paper.

Automatic Generation of Dynamic Skin Deformation for Animated Characters

Since non-automatic rigging requires heavy human involvements, and various automatic rigging algorithms are less efficient in terms of computational efficiency, especially for current curve-based skin deformation methods, identifying the iso-parametric curves and creating the animation skeleton requires tedious and time-consuming manual work. Although several automatic rigging methods have been developed, but they do not aim at curve-based models. To tackle this issue, this paper proposes a new rigging algorithm for automatic generation of dynamic skin deformation to quickly identify iso-parametric curves and create an animation skeleton in a few milliseconds, which can be seamlessly used in curve-based skin deformation methods to make the rigging process fast enough for highly efficient computer animation applications.

A unified algorithm to automatic semantic composition using multilevel workflow orchestration

As a result of state-of-the-art development in service oriented architecture, we need a composition framework and comprehensive algorithm to discover and compose the web services from different environments. In this paper, we present a unified semantic-oriented framework with corresponding algorithm for automatic web service composition that integrates the comprehensive process of modified multistage composition and rigor of web semantics. Our proposed unified algorithm introduces the novel features through modified five stage composition such as transformation of non-functional properties of user requirements to all stages, optimization and semantic validation of abstract workflows using workflow automata, annotating WSDL files with additional ontologies using ontology based service repository, adopting dynamic change of user requirements for discovering candidate services, and selecting most optimal services for concrete composition using non-functional properties are effectively represented. Feasible composition solution obtained for user complex requirements through semantic web service discovery mechanism for discovering and selecting the most suitable service candidates. Furthermore, our unified algorithm can provide a composition solution through wider acceptance of semantics-oriented documents such as web ontology language for services and web service modeling ontology. We evaluate the proposed unified algorithm for automatic generation of composition using our motivating scenario, namely, home loan approval inference process. We also evaluate algorithm for automated and dynamic composition on service repositories of various sizes in increasing the levels of nesting and present the performance results.

Formalization and acquisition of temporal knowledge for decision support in medical processes

Background: In medical practice, long term interventions are common and they require timely planning of the involved processes. Unfortunately, evidence-based statements about time are hard to find in Clinical Practice Guidelines (CPGs) and in other sources of medical knowledge. At the same time, health care centers use medical records and information systems to register data about clinical processes and patients, including time information about the encounters, prescriptions, and other clinical actions. Consequently, medical records and health care information systems are promising sources of data from which we can detect temporal medical knowledge.Objective: The objectives were to (1) Analyze and classify the sorts of time constraints in medical processes, (2) Propose a formalism to represent these sorts of clinical time constraints, (3) Use these formalisms to enable the automatic generation of temporal models from clinical data, and (4) Study the adherence of these intervention models to CPG recommendations.Methods: In order to achieve these objectives, we carried out four studies: The identification of the sort of times involved in the long-term diagnostic and therapeutic medical procedures of fifty patients, the supervision of the indications about time contained in six CPGs on chronic diseases, the study of the time structures of two standard data models, as well as ten languages to computerize CPGs. Based on the provided studies, we synthesized two representation formalisms: Micro- and macro-temporality. We developed three algorithms for automatic generation of generalized time constraints in the form of micro- and macro-temporalities from clinical databases, which were double tested.Results: A full classification of time constraints for medical procedures is proposed. Two formalisms called micro- and macro-temporality are introduced and validated to represent these time constraints. Time constraints were generated automatically from the data about 8781 Arterial Hypertension (AH) patients. The generated macro-temporalities restricted visits to be between 1–7 weeks, whereas CPGs recommend 2–4 weeks. Micro-temporal constraints on drug-dosage therapies distinguished between the initial dosage and the target dosage, with visits every 1–6 weeks, and 2–5 months, respectively. Our algorithms obtained semi-complete maps of dosage increments and the maximum dosages for 7 drug types. Data-based time limits for lifestyle change counsels and blood pressure (BP) check-ups were fixed to 6 and 3 months, for patients with low- and high-BP, respectively, when CPGs specify a general 3–6 month range.Conclusions: Experience-based temporal knowledge detected using our algorithms complements the evidence-based knowledge about clinical procedures contained in the CPGs. Our temporal model is simple and highly descriptive when dealing with general or specific time constraints’ representations, offering temporal knowledge representation of varying detail. Therefore, it is capable of capturing all the temporal knowledge we can find in medical procedures, when dealing with chronic diseases. With our model and algorithms, an adherence analysis emerges naturally to detect CPG-compliant interventions, but also deviations whose causes and possible rationales can call into question CPG recommendations (e.g., our analysis of AH patients showed that the time between visits recommended by CPGs were too long for a proper drug therapy decision, dosage titration, or general follow-up).

Automatic generation algorithm analysis of dance movements based on music–action association

With the rapid development of intelligent algorithm technology and big data technology, the dance is more and more urgent to get accurate analysis of optimization algorithm. It not only achieves the fusion of music and movement for the driven motion which provides a platform for integration, but also uses the optimization algorithm to realize an important project which produces the progress in the dance, the analysis of the dance is based on the generation method of creative methods. This paper designs and implements the automatic generation algorithm of genetic algorithm which is based on the basic design idea of dance movements, the design will be the triangle program as a typical example, and it’s generating test case as much as possible to complete path coverage in the specified range of data and input data. The experimental data shows that the algorithm generates test case which can not only complete the preset target path, and be able to complete a full. The generation of traversal target path meeting the required choreography. At the same time, the algorithm can coordinate the path of music and action to the greatest extent, and this algorithm lays the foundation for further integration of technology.

The Automation of Stochastization Algorithm with Use of SymPy Computer Algebra Library

SymPy computer algebra library is used for automatic generation of ordinary and stochastic systems of differential equations from the schemes of kinetic interaction. Schemes of this type are used not only in chemical kinetics but also in biological, ecological and technical models. This paper describes the automatic generation algorithm with an emphasis on application details.

Structure evolution-based design for low-pass IIR digital filters with the sharp transition band and the linear phase passband

Digital filters are generally designed by identifying the transfer functions. Most researches are focused on the goal of approaching the desired frequency response and take less additional consideration of structure characteristics. As a matter of fact, structure characteristics can greatly affect the performance of the digital filter. If only the frequency response is considered, the identified transfer function may not be the optimum. In this situation, structure synthesis is also limited by the form of the identified transfer function. This paper proposes a structure evolution-based optimization algorithm which allows the integrated consideration of structure issues and frequency response specifications in design stage. The method generates digital filter structures by a structurally automatic generation algorithm which can randomly generate and effectively represent digital structures. The structures, seen as chromosomes, are evolved over genetic algorithm for the search of the optimal solution in structure space. They are evaluated according to the mean square error between the designed and the desired frequency responses. Simulation results validate that the algorithm designs diversified structures of digital filters, and they meet target frequency specifications and structure constraints tightly. It is a promising way for optimized and automated design of digital filters.

Testing the Trustworthiness of IC Testing: An Oracle-Less Attack on IC Camouflaging

Test of integrated circuits (ICs) is essential to ensure their quality; the test is meant to prevent defective and out-of-spec ICs from entering into the supply chain. The test is conducted by comparing the observed IC output with the expected test responses for a set of test patterns; the test patterns are generated using automatic test pattern generation algorithms. Existing test-pattern generation algorithms aim to achieve higher fault coverage at lower test costs. In an attempt to reduce the size of test data, these algorithms reveal the maximum information about the internal circuit structure. This is realized through sensitizing the internal nets to the outputs as much as possible, unintentionally leaking the secrets embedded in the circuit as well. In this paper, we present HackTest, an attack that extracts secret information generated in the test data, even if the test data do not explicitly contain the secret. HackTest can break the existing intellectual property protection techniques, such as camouflaging, within 2 min for our benchmarks using only the camouflaged layout and the test data. HackTest applies to all existing camouflaged gate-selection techniques and is successful even in the presence of the state-of-the-art test infrastructure, i.e., test data compression circuits. Our attack necessitates that the IC test data generation algorithms can be reinforced with security.

Development of an algorithm for automatic elaboration, representation and dissemination of landslide monitoring data

ABSTRACTDespite the support of technological improvements in hazard monitoring and management, the aspect of dissemination of scientific data is still underestimated. Hazard monitoring systems are usually organized in complex networks, composed of automatized procedures in order to capture, pre-process, elaborate, transfer the monitoring result data and to generate warnings. However, a well-organized communication strategy leads to success in hazard management, especially concerning emergency conditions. In this paper, we present an approach for monitoring results dissemination in the form of single-page informative bulletin, composed of synthetic information dedicated to non-expert receivers. We developed an automatic methodology for fast and efficient data analysis and proper elaboration and dissemination, and we integrated all these elements into an algorithm for automatic bulletin generation. Our purpose was to construct a configurable tool that could be easily adapted to the hazard conditions under study. Afterwards, we applied the developed algorithm to landslide monitoring data-set. We validated the proposed approach by verifying the consistency of the model. Our methodology shows how to integrate a variety of information relative to landslide evolution, and it can be a convenient support for the management of natural hazards especially during critical situations.

2D automatic body-fitted structured mesh generation using advancing extraction method

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like topography with extrusion-like structures (i.e., branches or tributaries) and intrusion-like structures (i.e., peninsula or dikes). With the AEM, the hierarchical levels of sub-domains can be identified, and the block boundary of each sub-domain in convex polygon shape in each level can be extracted in an advancing scheme. In this paper, several examples were used to illustrate the effectiveness and applicability of the proposed algorithm for automatic structured mesh generation, and the implementation of the method.

Gene Expression Programming: A Survey [Review Article

Abstract Gene Expression Programming (GEP) is a popular and established evolutionary algorithm for automatic generation of computer programs. In recent decades, GEP has undergone rapid advancements and developments. A number of enhanced GEPs have been proposed to date and the real world applications that use them are also multiplying fast. In view of the steadfast growth of GEP and its importance to both the academia and industry, here a review on GEP is considered. In particular, this paper presents a comprehensive review on the recent progress of GEP. The state-of-the-art approaches of GEP, with enhanced designs from six aspects, i.e., encoding design, evolutionary mechanism design, adaptation design, cooperative co-evolutionary design, constant creation design, and parallel design, are presented. The theoretical studies and intriguing representative applications of GEP are given. Finally, a discussion of potential future research directions of GEP is also provided.

오픈 소스 Netgen 라이브러리 기반의 관상동맥 형상 비정렬 격자 자동 생성 기법 연구

In the present work, the algorithm for automatic tetrahedral mesh generation of the coronary artery geometry is proposed using open source software, Netgen library with LGPL license. Automatic processes include volume mesh generation and assignment of the boundary conditions, which are necessary for CFD simulation using in-house code. Automatic volume mesh generation is conducted based on Netgen library using STL-formatted file with surface elements information which is obtained through special treatment of coronary computed tomography angiography(CCTA) of the patient. For automatic assignments of the boundary conditions such as inlet, outlets and wall, the radius, the coordinate of center points and the normal vectors are used. With the arbitrary surface element, if two calculations are within the criteria; 1) the inner product with normal vector of selected surface element and one of inlet/outlet, 2)the distance between the selected element and the center point, the selected element is assigned inlet or outlet. Others which are not satisfied with above conditions are treated as the wall. The proposed algorithm is tested in the sample coronary artery. It is confirmed that generated volume mesh and boundary conditions are working well as the input file of in-house code.

Assessment of the Isometry of the Anterolateral Ligament in a 3-Dimensional Weight-Bearing Computed Tomography Simulation

To simulate the most isometric insertion points of the anterolateral ligament (ALL) in a weight-bearing 3-dimensional computed tomography (CT) model using previously published anatomic landmarks and to define radiographic landmarks, which make for an easier identification of the optimal insertion points. The most isometric femoral insertion points were analyzed for 10 individuals, using data of weight-bearing CT scans in increasing knee flexion positions. An automatic string generation algorithm helped identify isometrically optimal points using an isometric score (0 indicating optimal isometry). Subsequently, a general femoral insertion point was determined, which preserved the isometry in all tested individuals. Based on the femoral insertion point, we assessed the influence of varying tibial insertion points on the isometric behavior of the ALL. The defined femoral insertion point, which preserved the isometry in all analyzed individuals, had a median isometric score between 0.167× 10-3 and 0.559× 10-3. The average distance from the most prominent point of the lateral epicondyle was 9.7mm (standard deviation [SD], 1.6) in a straight superior direction. In a straight lateral radiographic view, this point is located exactly at the intersection of a tangent set between the posterior cortex of the femur and a second perpendicular line intersecting at the level of the most (superior-) posterior point of the Blumensaat line. The best isometric behavior was found on the anatomically defined mean tibial insertion point, located at 37% of the width of the tibial plateau, which worsened gradually if corrected to anterior or posterior. We determined femoral and tibial insertion points as well as radiographic landmarks for the reconstruction of the ALL that are based on published anatomic descriptions and preserve isometry in all analyzed individuals in this study. This study provides new information, which might be helpful to define isometrically optimal insertion points for ALL reconstruction.

Automatic superpixel generation algorithm based on a quadric error metric in 3D space

As a preprocessing step for computer vision tasks, research on generating superpixels of an image has been widely conducted recently. In this paper, we propose a fully automatic superpixel generation algorithm by simplifying the 3D triangle mesh modeled from a 2D input image. The simplification is performed based on a modified quadric error metric (QEM) method. The pipeline of our algorithm is simple. Given an image, we first turn it into a 2D triangle mesh and then lift the mesh to 3D based on the gray values of the image. We then simplify the 3D mesh based on the modified QEM method which encodes the features in the image intrinsically to ensure feature-aware superpixels. After obtaining the simplified mesh, we map it back to the 2D image to generate triangular-shaped superpixels. Our algorithm is fully automatic. The number of superpixels can be controlled intuitively. Experimental results demonstrate the effectiveness of our approach.

Character based ASCII Encryption & Decryption on cloud system

This paper proposed a algorithm for automatic key generation which generate from an integer value to create more secure communication over cloud architecture. Character based ASCII encryption scheme is used to satisfy the current requirement to establish secure communication. In this work we have a byte level security at each level of data transmission. It helps to create batter security to perform encryption & decryption over cloud infrastructure i.e., from this work we have technique through which we generate private key which help to establish secure communication between two or more node while they are communicating over cloud system.

Software Testing Using Genetic Algorithms

This paper presents a set of methods that uses a genetic algorithm for automatic test-data generation in software testing. For several years researchers have proposed several methods for generating test data which had different drawbacks. In this paper, we have presented various Genetic Algorithm (GA) based test methods which will be having different parameters to automate the structural-oriented test data generation on the basis of internal program structure. The factors discovered are used in evaluating the fitness function of Genetic algorithm for selecting the best possible Test method. These methods take the test populations as an input and then evaluate the test cases for that program. This integration will help in improving the overall performance of genetic algorithm in search space exploration and exploitation fields with better convergence rate.

Enhanced Cortical Thickness Measurements for Rodent Brains via Lagrangian-based RK4 Streamline Computation.

The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the the previous cortical thickness analysis pipeline.

Automatic generation of smart earthquake-resistant building system: Hybrid system of base-isolation and building-connection.

A base-isolated building may sometimes exhibit an undesirable large response to a long-duration, long-period earthquake ground motion and a connected building system without base-isolation may show a large response to a near-fault (rather high-frequency) earthquake ground motion. To overcome both deficiencies, a new hybrid control system of base-isolation and building-connection is proposed and investigated. In this new hybrid building system, a base-isolated building is connected to a stiffer free wall with oil dampers. It has been demonstrated in a preliminary research that the proposed hybrid system is effective both for near-fault (rather high-frequency) and long-duration, long-period earthquake ground motions and has sufficient redundancy and robustness for a broad range of earthquake ground motions.An automatic generation algorithm of this kind of smart structures of base-isolation and building-connection hybrid systems is presented in this paper. It is shown that, while the proposed algorithm does not work well in a building without the connecting-damper system, it works well in the proposed smart hybrid system with the connecting damper system.

Selected ICAR Data from the SAPA-Project: Development and Initial Validation of a Public-Domain Measure

These data were collected during the initial evaluation of the International Cognitive Ability Resource (ICAR) project. ICAR is an international collaborative effort to develop open-source public-domain tools for cognitive ability assessment, including tools that can be administered in non-proctored environments (e.g., online administration) and those which are based on automatic item generation algorithms. These data provide initial validation of the first four ICAR item types as reported in Condon & Revelle [1]. The 4 item types contain a total of 60 items: 9 Letter and Number Series items, 11 Matrix Reasoning items, 16 Verbal Reasoning items and 24 Three-dimensional Rotation items. Approximately 97,000 individuals were administered random subsets of these 60 items using the Synthetic Aperture Personality Assessment method between August 18, 2010 and May 20, 2013. The data are available in rdata and csv formats and are accompanied by documentation stored as a text file. Re-use potential includes a wide range of structural and item-level analyses.

Research on Community Competition and Adaptive Genetic Algorithm for Automatic Generation of Tang Poetry

As there are many researches about traditional Tang poetry, among which automatically generated Tang poetry has arouse great concern in recent years. This study presents a community-based competition and adaptive genetic algorithm for automatically generating Tang poetry. The improved algorithm with community-based competition that has been added aims to maintain the diversity of genes during evolution; meanwhile, the adaptation means that the probabilities of crossover and mutation are varied from the fitness values of the Tang poetry to prevent premature convergence and generate better poems more quickly. According to the analysis of experimental results, it has been found that the improved algorithm is superior to the conventional method.