Distribution by Scientific Domains
Distribution within Engineering

Kinds of Algorithm

  • adaptation algorithm
  • adaptive algorithm
  • adaptive control algorithm
  • admission control algorithm
  • allocation algorithm
  • analysis algorithm
  • annealing algorithm
  • ant colony algorithm
  • approximation algorithm
  • assignment algorithm
  • automate algorithm
  • automatic algorithm
  • back-propagation algorithm
  • backpropagation algorithm
  • bootstrap algorithm
  • bound algorithm
  • branch-and-bound algorithm
  • branch-and-cut algorithm
  • branch-and-price algorithm
  • carlo algorithm
  • classification algorithm
  • clinical algorithm
  • clustering algorithm
  • colony algorithm
  • computational algorithm
  • computer algorithm
  • constant modulus algorithm
  • constructive algorithm
  • contact algorithm
  • control algorithm
  • correction algorithm
  • current algorithm
  • decomposition algorithm
  • deconvolution algorithm
  • design algorithm
  • detection algorithm
  • developed algorithm
  • diagnostic algorithm
  • differential evolution algorithm
  • dynamic programming algorithm
  • effective algorithm
  • efficient algorithm
  • element algorithm
  • em algorithm
  • estimation algorithm
  • evaluation algorithm
  • evolution algorithm
  • evolutionary algorithm
  • exact algorithm
  • expectation maximization algorithm
  • expectation-maximization algorithm
  • explicit algorithm
  • fast algorithm
  • filter algorithm
  • filtering algorithm
  • finite element algorithm
  • first algorithm
  • flow algorithm
  • general algorithm
  • generation algorithm
  • genetic algorithm
  • gradient algorithm
  • greedy algorithm
  • heuristic algorithm
  • hybrid algorithm
  • hybrid genetic algorithm
  • hybrid learning algorithm
  • identification algorithm
  • implicit algorithm
  • improved genetic algorithm
  • integration algorithm
  • interpolation algorithm
  • inversion algorithm
  • iteration algorithm
  • iterative algorithm
  • learning algorithm
  • least-square algorithm
  • machine learning algorithm
  • management algorithm
  • map algorithm
  • mapping algorithm
  • marquardt algorithm
  • mathematical algorithm
  • maximization algorithm
  • model algorithm
  • modified algorithm
  • modulus algorithm
  • monte carlo algorithm
  • multigrid algorithm
  • network algorithm
  • neural network algorithm
  • new algorithm
  • new genetic algorithm
  • newton algorithm
  • novel algorithm
  • numerical algorithm
  • optimization algorithm
  • original algorithm
  • parallel algorithm
  • path algorithm
  • pl algorithm
  • planning algorithm
  • point algorithm
  • polynomial time algorithm
  • polynomial-time algorithm
  • prediction algorithm
  • present algorithm
  • programming algorithm
  • projection algorithm
  • propagation algorithm
  • proposed algorithm
  • pso algorithm
  • raphson algorithm
  • rate algorithm
  • reconstruction algorithm
  • recursive algorithm
  • refinement algorithm
  • regression algorithm
  • robust algorithm
  • routing algorithm
  • same algorithm
  • sampling algorithm
  • scheduling algorithm
  • schwarz algorithm
  • screening algorithm
  • search algorithm
  • segmentation algorithm
  • selection algorithm
  • separation algorithm
  • sequential algorithm
  • shortest path algorithm
  • simple algorithm
  • simulated annealing algorithm
  • simulation algorithm
  • solution algorithm
  • standard algorithm
  • synthesis algorithm
  • therapeutic algorithm
  • time algorithm
  • tracking algorithm
  • treatment algorithm
  • tree algorithm
  • tuning algorithm
  • unified algorithm

  • Terms modified by Algorithm

  • algorithm approach
  • algorithm capable
  • algorithm consisting
  • algorithm design
  • algorithm development
  • algorithm performance
  • algorithm used
  • algorithm work

  • Selected Abstracts


    JOURNAL OF RENAL CARE, Issue 2 2008
    Sharon Benton
    SUMMARY The paper describes the need for the introduction of an anaemia management algorithm. It discussed the problems which the unit had in constant reviewing and re-prescribing ESA to maintain optimum haemoglobin levels for the unit's patients. The method used to create and use the algorithm is explained. The findings demonstrate the beneficial effects of using the algorithm. The paper concludes with the recommendation that algorithms should be more widely used for better treatment outcomes. [source]


    Feng Ding
    ABSTRACT In this paper, using a polynomial transformation technique, we derive a mathematical model for dual-rate systems. Based on this model, we use a stochastic gradient algorithm to estimate unknown parameters directly from the dual-rate input-output data, and then establish an adaptive control algorithm for dual-rate systems. We prove that the parameter estimation error converges to zero under persistent excitation, and the parameter estimation based control algorithm can achieve virtually asymptotically optimal control and ensure the closed-loop systems to be stable and globally convergent. The simulation results are included. [source]


    M. Norrlöf
    ABSTRACT An Iterative Learning Control disturbance rejection approach is considered and it is shown that iteration variant learning filters can asymptotically give the controlled variable zero error and zero variance. Convergence is achieved with the assumption that the relative model error is less than one. The transient response of the suggested ILC algorithm is also discussed using a simulation example. [source]

    Using fractional exhaled nitric oxide to guide asthma therapy: design and methodological issues for ASthma TReatment ALgorithm studies

    P. G. Gibson Prof.
    Summary Background Current asthma guidelines recommend treatment based on the assessment of asthma control using symptoms and lung function. Noninvasive markers are an attractive way to modify therapy since they offer improvedselection of active treatment(s) based on individual response, and improvedtitration of treatment using markers that are better related to treatment outcomes. Aims: To review the methodological and design features of noninvasive marker studies in asthma. Methods Systematic assessment of published randomized trials of asthma therapy guided by fraction of exhaled nitric oxide(FENO). Results FENO has appeal as a marker to adjust asthma therapy since it is readily measured, gives reproducible results, and is responsive to changes in inhaled corticosteroid doses. However, the five randomised trials of FENO guided therapy have had mixed results. This may be because there are specific design and methodological issues that need to be addressed in the conduct of ASthma TReatment ALgorithm(ASTRAL) studies. There needs to be a clear dose response relationship for the active drugs used and the outcomes measured. The algorithm decision points should be based on outcomes in the population of interest rather than the range of values in healthy people, and the algorithm used needs to provide a sufficiently different result to clinical decision making in order for there to be any discernible benefit. A new metric is required to assess the algorithm performance, and the discordance:concordance(DC) ratio can assist with this. Conclusion Incorporating these design features into future FENO studies should improve the study performance and aid in obtaining a better estimate of the value of FENO guided asthma therapy. [source]

    A Complexity Model and a Polynomial Algorithm for Decision-Tree-Based Feature Construction

    Raymond L. Major
    Using decision trees as a concept description language, we examine the time complexity for learning Boolean functions with polynomial-sized disjunctive normal form expressions when feature construction is performed on an initial decision tree containing only primitive attributes. A shortcoming of several feature-construction algorithms found in the literature is that it is difficult to develop time complexity results for them. We illustrate a way to determine a limit on the number of features to use for building more concise trees within a standard amount of time. We introduce a practical algorithm that forms a finite number of features using a decision tree in a polynomial amount of time. We show empirically that our procedure forms many features that subsequently appear in a tree and the new features aid in producing simpler trees when concepts are being learned from certain problem domains. Expert systems developers can use a method such as this to create a knowledge base of information that contains specific knowledge in the form of If-Then rules. [source]

    Horizontal Roadway Curvature Computation Algorithm Using Vision Technology

    Yichang (James) Tsai
    However, collecting such data is time-consuming, costly, and dangerous using traditional, manual surveying methods. It is especially difficult to perform such manual measurement when roadways have high traffic volumes. Thus, it would be valuable for transportation agencies if roadway curvature data could be computed from photographic images taken using low-cost digital cameras. This is the first article that develops an algorithm using emerging vision technology to acquire horizontal roadway curvature data from roadway images to perform roadway safety assessment. The proposed algorithm consists of four steps: (1) curve edges image processing, (2) mapping edge positions from an image domain to the real-world domain, (3) calibrating camera parameters, and (4) calculating the curve radius and center from curve points. The proposed algorithm was tested on roadways having various levels of curves and using different image sources to demonstrate its capability. The ground truth curvatures for two cases were also collected to evaluate the error of the proposed algorithm. The test results are very promising, and the computed curvatures are especially accurate for curves of small radii (less than 66 m/200 ft) with less than 1.0% relative errors with respect to the ground truth data. The proposed algorithm can be used as an alternative method that complements the traditional measurement methods used by state DOTs to collect roadway curvature data. [source]

    Scalable Algorithm for Resolving Incorrect Occlusion in Dynamic Augmented Reality Engineering Environments

    Amir H. Behzadan
    As a result of introducing real-world objects into the visualization, less virtual models have to be deployed to create a realistic visual output that directly translates into less time and effort required to create, render, manipulate, manage, and update three-dimensional (3D) virtual contents (CAD model engineering) of the animated scene. At the same time, using the existing layout of land or plant as the background of visualization significantly alleviates the need to collect data about the surrounding environment prior to creating the final visualization while providing visually convincing representations of the processes being studied. In an AR animation, virtual and real objects must be simultaneously managed and accurately displayed to a user to create a visually convincing illusion of their coexistence and interaction. A critical challenge impeding this objective is the problem of incorrect occlusion that manifests itself when real objects in an AR scene partially or wholly block the view of virtual objects. In the presented research, a new AR occlusion handling system based on depth-sensing algorithms and frame buffer manipulation techniques was designed and implemented. This algorithm is capable of resolving incorrect occlusion occurring in dynamic AR environments in real time using depth-sensing equipment such as laser detection and ranging (LADAR) devices, and can be integrated into any mobile AR platform that allows a user to navigate freely and observe a dynamic AR scene from any vantage position. [source]

    Algorithm for Accurate Three-Dimensional Scene Graph Updates in High-Speed Animations of Previously Simulated Construction Operations

    Prasant V. Rekapalli
    Early efforts resulted in a scene graph and frame update algorithm that was capable of converting discrete information from simulation models into smooth and continuous 3D animations. That algorithm did not account for high speed or concurrent animation because the need to do so was not anticipated. Recent advances in computing power and an interest in using the technology for next generation applications now demand accurate high speed and concurrent animations. This article presents the design of the original algorithm at a previously undocumented level of detail and specificity, and that allows for the analysis of its shortcomings when used at high speeds or concurrently with simulation. Two subsequent but still inadequate designs of the algorithm are also presented and analyzed in detail so that they can serve as an illustration of the path toward the final design and place it in proper context. The article concludes with the final design and evaluation of the algorithm, which is accurate at very high animation speeds and supports concurrent animation of simulation models. [source]

    Algorithm for Spatial Clustering of Pavement Segments

    Chientai Yang
    This article formulates a new spatial search model for determining appropriate pavement preservation project termini. A spatial clustering algorithm using fuzzy c-mean clustering is developed to minimize the rating variation in each cluster (project) of pavement segments while considering minimal project scope (i.e., length) and cost, initial setup cost, and barriers, such as bridges. A case study using the actual roadway and pavement condition data in fiscal year 2005 on Georgia State Route 10 shows that the proposed algorithm can identify more appropriate segment clustering scheme, than the historical project termini. The benefits of using the developed algorithm are summarized, and recommendations for future research are discussed. [source]

    A Path-Based Algorithm for the Cross-Nested Logit Stochastic User Equilibrium Traffic Assignment

    Shlomo Bekhor
    A SUE assignment based on the Cross-Nested Logit (CNL) route choice model is presented. The CNL model can better represent route choice behavior compared to the Multinomial Logit (MNL) model, while keeping a closed form equation. The article uses a specific optimization formulation developed for the CNL model, and develops a path-based algorithm for the solution of the CNL-SUE problem based on adaptation of the disaggregate simplicial decomposition (DSD) method. The article illustrates the algorithmic implementation on a real size network and discusses the trade-offs between MNL-SUE and CNL-SUE assignment. [source]

    Bi-level Programming Formulation and Heuristic Solution Approach for Dynamic Traffic Signal Optimization

    Dazhi Sun
    Conventional methods of signal timing optimization assume given traffic flow pattern, whereas traffic assignment is performed with the assumption of fixed signal timing. This study develops a bi-level programming formulation and heuristic solution approach (HSA) for dynamic traffic signal optimization in networks with time-dependent demand and stochastic route choice. In the bi-level programming model, the upper level problem represents the decision-making behavior (signal control) of the system manager, while the user travel behavior is represented at the lower level. The HSA consists of a Genetic Algorithm (GA) and a Cell Transmission Simulation (CTS) based Incremental Logit Assignment (ILA) procedure. GA is used to seek the upper level signal control variables. ILA is developed to find user optimal flow pattern at the lower level, and CTS is implemented to propagate traffic and collect real-time traffic information. The performance of the HSA is investigated in numerical applications in a sample network. These applications compare the efficiency and quality of the global optima achieved by Elitist GA and Micro GA. Furthermore, the impact of different frequencies of updating information and different population sizes of GA on system performance is analyzed. [source]

    Searching for Better Negotiation Agreement Based on Genetic Algorithm

    Ren-Jye Dzeng
    In current practice, contractors negotiate with suppliers according to negotiators' experiences instead of extensive exploration of negotiable options and negotiators' preferences. Consequently, negotiators often reach suboptimal agreements, and leave money on the table. This research intends to help negotiators explore negotiable options by developing a computer system, named C-Negotiator, using the genetic algorithm. This article also describes experiments conducted to determine how much money was left on the table on typical realistic construction procurements. The result shows that C-Negotiator's negotiation improved the joint payoff of the contractor and supplier from 1.5% to 9.8% compared with conventional human negotiation. The improvement may increase for more complex negotiation problems with more options and complicated preferences or for inexperienced negotiators. [source]

    Hybrid Control of Smart Structures Using a Novel Wavelet-Based Algorithm

    Hongjin Kim
    A new hybrid control system is presented through judicious combination of a passive supplementary damping system with a semi-active TLCD system. The new model utilizes the advantages of both passive and semi-active control systems, thereby improving the overall performance, reliability, and operability of the control system during normal operations as well as a power or computer failure. The robust wavelet-hybrid feedback least mean square (LMS) control algorithm developed recently by the authors is used to find optimal values of the control parameters. The effectiveness and robustness of the proposed hybrid damper-TLCD system in reducing the vibrations under various seismic excitations are evaluated through numerical simulations performed for an eight-story frame using three different simulated earthquake ground accelerations. It is found that the new model is effective in significantly reducing the response of the structure under various seismic excitations. [source]

    Hybrid Meta-Heuristic Algorithm for the Simultaneous Optimization of the O,D Trip Matrix Estimation

    Antony Stathopoulos
    These include a genetic algorithm (GA), a simulated annealing (SA) algorithm, and a hybrid algorithm (GASA) based on the combination of GA and SA. The computational performance of the three algorithms is evaluated and compared by implementing them on a realistic urban road network. The results of the simulation tests demonstrate that SA and GASA produce a more accurate final solution than GA, whereas GASA shows a superior convergence rate, that is, faster improvement from the initial solution, in comparison to SA and GA. In addition, GASA produces a final solution that is more robust and less dependent on the initial demand pattern, in comparison to that obtained from a greedy search algorithm. [source]

    A Massively Parallel Time-Dependent Least-Time-Path Algorithm for Intelligent Transportation Systems Applications

    Athanasios Ziliaskopoulos
    This article is concerned with the problem of computing in parallel time-dependent least-time paths that can be used in real-time intelligent transportation systems applications. A message-passing scheme is presented, and its correctness is proved. The algorithm's computational complexity is shown to be O(|T|2|V|2), an improvement by |V| over the best-known sequential algorithm. The algorithm is implemented, coded, and computationally tested on actual and random networks with promising results. The algorithm is implemented on a CRAY-T3D supercomputer using a Parallel Virtual Machine environment that allows portability to lower-end multiprocessor machines. [source]

    Automatic Palletizing of Concrete Pavement Blocks: An Algorithm for Near-Optimal Assembly

    Shraga Shoval
    Palletizing concrete pavement blocks is a labor-intensive task that requires high levels of workmanship, skill, and concentration. This article proposes an automatic system in which palettes with required design patterns are assembled automatically off-site and then shipped to the construction site. The efficiency of the assembly process can be improved by incorporating automatic equipment consisting of assembly heads and feeders. An algorithm was developed to determine the optimal layout of the feeders (of different blocks) around the palette and the exact assembly sequence of each layer of blocks. Experimental results show that the algorithm is near optimal and that the solutions provided by it reduce palletizing cycle time for various patterns and sizes of concrete block by 20 to 30 percent. [source]

    A formalized approach for designing a P2P-based dynamic load balancing scheme

    Hengheng Xie
    Abstract Quality of service (QoS) is attracting more and more attention in many areas, including entertainment, emergency services, transaction services, and so on. Therefore, the study of QoS-aware systems is becoming an important research topic in the area of distributed systems. In terms of load balancing, most of the existing QoS-related load balancing algorithms focus on Routing Mechanism and Traffic Engineering. However, research on QoS-aware task scheduling and service migration is very limited. In this paper, we propose a task scheduling algorithm using dynamic QoS properties, and we develop a Genetic Algorithm-based Services Migration scheme aiming to optimize the performance of our proposed QoS-aware distributed service-based system. In order to verify the efficiency of our scheme, we implement a prototype of our algorithm using a P2P-based JXTA technique, and do an emulation test and a simulation test in order to analyze our proposed solution. We compare our service-migration-based algorithm with non-migration and non-load-balancing approaches, and find that our solution is much better than the other two in terms of QoS success rate. Furthermore, in order to provide more solid proofs of our research, we use DEVS to validate our system design. Copyright © 2010 John Wiley & Sons, Ltd. [source]

    MRMOGA: a new parallel multi-objective evolutionary algorithm based on the use of multiple resolutions

    Antonio López Jaimes
    Abstract In this paper, we introduce MRMOGA (Multiple Resolution Multi-Objective Genetic Algorithm), a new parallel multi-objective evolutionary algorithm which is based on an injection island approach. This approach is characterized by adopting an encoding of solutions which uses a different resolution for each island. This approach allows us to divide the decision variable space into well-defined overlapped regions to achieve an efficient use of multiple processors. Also, this approach guarantees that the processors only generate solutions within their assigned region. In order to assess the performance of our proposed approach, we compare it to a parallel version of an algorithm that is representative of the state-of-the-art in the area, using standard test functions and performance measures reported in the specialized literature. Our results indicate that our proposed approach is a viable alternative to solve multi-objective optimization problems in parallel, particularly when dealing with large search spaces. Copyright © 2006 John Wiley & Sons, Ltd. [source]

    Solving the block,Toeplitz least-squares problem in parallel

    P. Alonso
    Abstract In this paper we present two versions of a parallel algorithm to solve the block,Toeplitz least-squares problem on distributed-memory architectures. We derive a parallel algorithm based on the seminormal equations arising from the triangular decomposition of the product TTT. Our parallel algorithm exploits the displacement structure of the Toeplitz-like matrices using the Generalized Schur Algorithm to obtain the solution in O(mn) flops instead of O(mn2) flops of the algorithms for non-structured matrices. The strong regularity of the previous product of matrices and an appropriate computation of the hyperbolic rotations improve the stability of the algorithms. We have reduced the communication cost of previous versions, and have also reduced the memory access cost by appropriately arranging the elements of the matrices. Furthermore, the second version of the algorithm has a very low spatial cost, because it does not store the triangular factor of the decomposition. The experimental results show a good scalability of the parallel algorithm on two different clusters of personal computers. Copyright © 2005 John Wiley & Sons, Ltd. [source]

    An Approximate Bayesian Algorithm for Combining Forecasts,

    DECISION SCIENCES, Issue 3 2001
    Kim-Hung Li
    Abstract In this paper we propose a consensus forecasting method based on a convex combination of individual forecast densities. The exact Bayesian updating of the convex combination weights is very complex and practically prohibitive. We propose a simple sequential updating alternative method based on function approximation. Several examples illustrate the method. [source]

    Algorithm of first-aid management of dental trauma for medics and corpsmen

    Yehuda Zadik
    The recommended management of tooth avulsion, subluxation and luxation, crown fracture and lip, tongue or gingival laceration included in the algorithm. Along with a list of after-hour dental clinics, this symptoms- and clinical-appearance-based algorithm is suited to tuck easily into a pocket for quick utilization by medics/corpsmen in an emergency situation. Although the algorithm was developed for the usage of military non-dental health-care providers, this method could be adjusted and employed in the civilian environment as well. [source]

    Results of a Survey of 5,700 Patient Monopolar Radiofrequency Facial Skin Tightening Treatments: Assessment of a Low-Energy Multiple-Pass Technique Leading to a Clinical End Point Algorithm

    INTRODUCTION Monopolar radiofrequency is an effective means of nonsurgical facial skin tightening. OBJECTIVE The objective of this study was to determine whether using larger tips at lower energy and multiple passes, using patient feedback on heat sensation and treating to a clinical end point of visible tightening, would yield better results than single passes with small tips at high energy, as measured by patient and physician satisfaction. METHODS Fourteen physicians from four specialties were surveyed to determine the answers to the following three questions. (1) Is patient's feedback on heat sensation a valid and preferred method for optimal energy selection? (2) Do multiple passes at moderate energy settings yield substantial and consistent efficacy? (3) Is treating to a clinical end point of visible tightening predictable of results? RESULTS A total of 5,700 patient treatments were surveyed. Comparisons were made using the original algorithm of high-energy, single pass to the new algorithm of lower energy and multiple passes with visible tightening as the end point of treatment. Using the original treatment algorithm, 26% of patients demonstrated immediate tightening, 54% observed skin tightening 6 months after treatment, 45% found the procedure too painful, and 68% of patients found the treatment results met their expectations. With the new multiple-pass algorithm, 87% observed immediate tightening, 92% had the tightening six months after treatment, 5% found the procedure too painful, while 94% found the treatment results met their expectations. CONCLUSIONS Patient feedback on heat sensation is a valid, preferable method for optimal energy selection in monopolar radiofrequency skin-tightening treatments. [source]

    The usage of a simplified self-titration dosing guideline (303 Algorithm) for insulin detemir in patients with type 2 diabetes , results of the randomized, controlled PREDICTIVEÔ 303 study

    L. Meneghini
    The Predictable Results and Experience in Diabetes through Intensification and Control to Target: An International Variability Evaluation 303 (PREDICTIVEÔ 303) Study (n = 5604) evaluated the effectiveness of insulin detemir, a long-acting basal insulin analogue, using a simplified patient self-adjusted dosing algorithm (303 Algorithm group) compared with standard-of-care physician-driven adjustments (Standard-of-care group) in a predominantly primary care setting, over a period of 6 months. Insulin detemir was to be started once-daily as add-on therapy to any other glucose-lowering regimens or as a replacement of prestudy basal insulin in patients with type 2 diabetes. Investigator sites rather than individual patients were randomized to either the 303 Algorithm group or the Standard-of-care group. Patients from the 303 Algorithm group sites were instructed to adjust their insulin detemir dose every 3 days based on the mean of three ,adjusted' fasting plasma glucose (aFPG) values (capillary blood glucose calibrated to equivalent plasma glucose values) using a simple algorithm: mean aFPG < 80 mg/dl (<4.4 mmol/l), reduce dose by 3 U; aFPG between 80 and 110 mg/dl (4.4,6.1 mmol/l), no change; and aFPG > 110 mg/dl (>1.1 mmol/l), increase dose by 3 U. The insulin detemir dose for patients in the Standard-of-care group was adjusted by the investigator according to the standard of care. Mean A1C decreased from 8.5% at baseline to 7.9% at 26 weeks for the 303 Algorithm group and from 8.5 to 8.0% for the Standard-of-care group (p = 0.0106 for difference in A1C reduction between the two groups). Mean FPG values decreased from 175 mg/dl (9.7 mmol/l) at baseline to 141 mg/dl (7.8 mmol/l) for the 303 Algorithm group and decreased from 174 mg/dl (9.7 mmol/l) to 152 mg/dl (8.4 mmol/l) for the Standard-of-care group (p < 0.0001 for difference in FPG reduction between the two groups). Mean body weight remained the same at 26 weeks in both groups (change from baseline 0.1 and ,0.2 kg for the 303 Algorithm group and the Standard-of-care group respectively). At 26 weeks, 91% of the patients in the 303 Algorithm group and 85% of the patients in the Standard-of-care group remained on once-daily insulin detemir administration. The rates of overall hypoglycaemia (events/patient/year) decreased significantly from baseline in both groups [from 9.05 to 6.44 for the 303 Algorithm group (p = 0.0039) and from 9.53 to 4.95 for the Standard-of-care group (p < 0.0001)]. Major hypoglycaemic events were rare in both groups (0.26 events/patient/year for the 303 Algorithm group and 0.20 events/patient/year for the Standard-of-care group; p = 0.2395). In conclusion, patients in the 303 Algorithm group achieved comparable glycaemic control with higher rate of hypoglycaemia as compared with patients in the Standard-of-care group, possibly because of more aggressive insulin dose adjustments. The vast majority of the patients in both groups were effectively treated with once-daily insulin detemir therapy. The use of insulin detemir in this predominantly primary care setting achieved significant improvements in glycaemic control with minimal risk of hypoglycaemia and no weight gain. [source]

    Improvement of information filtering by independent components selection

    Takeru Yokoi
    Abstract We propose an improvement of an information filtering process with independent components selection. The independent components are obtained by Independent Components Analysis and considered as topics. Selection of independent components is an efficient method of improving the accuracy of the information filtering for the purpose of extraction of similar topics by focusing on their meanings. To achieve this, we select the topics by Maximum Distance Algorithm with Jensen-Shannon divergence. In addition, document vectors are represented by the selected topics. We create a user profile from transformed data with a relevance feedback. Finally, we sort documents by the user profile and evaluate the accuracy by imputation precision. We carried out an evaluation experiment to confirm the validity of the proposed method considering meanings of components used in this experiment. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(2): 49,56, 2008; Published online in Wiley InterScience ( DOI 10.1002/eej.20519 [source]

    A design for robust power system stabilizer by means of H, control and particle swarm optimization method

    Yoshifumi Zoka
    Abstract This paper proposes two types of PSS design methods that take into account robustness for comparably large power systems. The first one is a design method based on , control theory and the second one is a parameter determination method for a standard PSS by using Particle Swarm Optimization (PSO). In order to deal with large-scale systems, a reduced model is developed to get the target system which preserves major oscillation modes only. The major oscillation modes are selected by using the residue concept, and the PSS is designed based on the target system. In order to verify effectiveness, the proposed methods are compared with the other previously proposed method based on a Genetic Algorithm (GA) through many numerical simulations. © 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(8): 34,43, 2008; Published online in Wiley InterScience ( DOI 10.1002/ecj.10132 [source]

    Virus-evolutionary linear genetic programming

    Kenji Tamura
    Abstract Many kinds of evolutionary methods have been proposed. GA and GP in particular have demonstrated their effectiveness in various problems recently, and many systems have been proposed. One is Virus-Evolutionary Genetic Algorithm (VE-GA), and the other is Linear Genetic Programming in C (LGPC). The performance of each system has been reported. VE-GA is the coevolution system of host individuals and virus individuals. That can spread schema effectively among the host individuals by using virus infection and virus incorporation. LGPC implements the GP by representing the individuals to one dimension as if GA. LGPC can reduce a search cost of pointer and save machine memory, and can reduce the time to implement GP programs. We have proposed that a system introduce virus individuals in LGPC, and analyzed the performance of the system on two problems. Our system can spread schema among the population, and search solution effectively. The results of computer simulation show that this system can search for solution depending on LGPC applying problem's character compared with LGPC. © 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(1): 32, 39, 2008; Published online in Wiley InterScience ( DOI 10.1002/eej.10030 [source]

    Minimisation of end-to-end delay in reconfigurable WDM networks using genetic algorithms

    Ramón J. Durán Barroso
    A new genetic algorithm (GA) is proposed to design logical topologies for wavelength-routed optical networks (WRONs) with the objective of minimising the end-to-end delay. Two versions of the algorithm, called D-GALD (Delay-optimised Genetic Algorithm for Logical topology Design), have been developed. The first one minimises the average end-to-end delay of the packets transported by the network, while the second one minimises the average delay of the most delayed traffic flow. By means of a simulation study, we show that the logical topologies designed by D-GALD support more than 50 per cent higher traffic load,without causing network instability,than those ones designed by other heuristics. Moreover, the utilisation of D-GALD leads to reductions of up to 15 per cent in the average end-to-end delay and around 30 per cent in the average end-to-end delay of the most delayed traffic flow. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    BEAST decoding for block codes

    Irina E. Bocharova
    BEAST is a Bidirectional Efficient Algorithm for Searching code Trees. In this paper, it is used for decoding block codes over a binary-input memoryless channel. If no constraints are imposed on the decoding complexity (in terms of the number of visited nodes during the search), BEAST performs maximum-likelihood (ML) decoding. At the cost of a negligible performance degradation, BEAST can be constrained to perform almost-ML decoding with significantly reduced complexity. The benchmark for the complexity assessment is the number of nodes visited by the Viterbi algorithm operating on the minimal trellis of the code. The decoding complexity depends on the trellis structure of a given code, which is illustrated by three different forms of the generator matrix for the (24, 12, 8) Golay code. Simulation results that assess the error-rate performance and the decoding complexity of BEAST are presented for two longer codes. Copyright © 2004 AEI [source]

    QoS in IntServ-based IP networks: the peak rate policing

    Lorenzo Battaglia
    In the last few years, IP has moved towards resource reservation, with the task to guarantee in the future Quality of Service (QoS). This has led to flow admission control algorithms based on the negotiation of standardised traffic parameters. QoS can be guaranteed in any network, a priori from the used technology, only if the used admission control algorithm wisely shares the network's resources among the users. Any admission control algorithm on its turn can do so, only if every user respects the negotiated traffic parameters. Since any user could, maliciously or not, send at a higher rate than negotiated, i.e. use a higher share of resources than the negotiated one, in every network in which admission control is performed, a policing algorithm is used. An ideal policer should guarantee to reject no packet of a well-behaved user and police contract violation as rigidly as possible. All this independently of the characteristics of the monitored stream and of the background traffic. This holds also for Integrated Services (IS) based IP networks. In these networks, every user negotiates a peak and an average rate. In this paper we present the solution to the peak rate policing issue. We adapt the Generic Cell Rate Algorithm (GCRA), well-known policer used in ATM networks, to police the peak rate of flows of packets with variable length. We intuitively call this modified GCRA Generic Packet Rate Algorithm (GPRA) and dimension its parameters so that independently of the characteristics of the policed flow and of the background traffic, no packets of a well-behaved user are rejected and that the flows of any misbehaving user are rigidly policed. Copyright © 2003 AEI. [source]

    Multi-Period Planning of Survivable WDM Networks

    Mario Pickavet
    This paper presents a new heuristic algorithm useful for long-term planning of survivable WDM networks. A multi-period model is formulated that combines network topology design and capacity expansion. The ability to determine network expansion schedules of this type becomes increasingly important to the telecommunications industry and to its customers. The solution technique consists of a Genetic Algorithm that allows to generate several network alternatives for each time period simultaneously and shortest-path techniques to deduce from these alternatives a least-cost network expansion plan over all time periods. The multi-period planning approach is illustrated on a realistic network example. Extensive simulations on a wide range of problem instances are carried out to assess the cost savings that can be expected by choosing a multi-period planning approach instead of an iterative network expansion design method. [source]