Journal articles: 'Worm Algorithm'

1

Rindlisbacher, Tobias, and Philippe de Forcrand. "Worm algorithm for theCPN−1model." Nuclear Physics B 918 (May 2017): 178–219. http://dx.doi.org/10.1016/j.nuclphysb.2017.02.021.

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Gaofei, Zheng, Wang Xiufeng, and Zhang Yanli. "The self-organizing worm algorithm." Journal of Systems Engineering and Electronics 18, no. 3 (September 2007): 650–54. http://dx.doi.org/10.1016/s1004-4132(07)60143-1.

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Delgado, Y., and A. Schmidt. "Worm Algorithm for Abelian Gauge-Higgs Models." Acta Physica Polonica B Proceedings Supplement 6, no. 3 (2013): 911. http://dx.doi.org/10.5506/aphyspolbsupp.6.911.

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Prokof'ev, N. V., B. V. Svistunov, and I. S. Tupitsyn. "“Worm” algorithm in quantum Monte Carlo simulations." Physics Letters A 238, no. 4-5 (February 1998): 253–57. http://dx.doi.org/10.1016/s0375-9601(97)00957-2.

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Kerl, John. "A worm algorithm for random spatial permutations." Physics Procedia 4 (2010): 61–65. http://dx.doi.org/10.1016/j.phpro.2010.08.009.

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Janke, Wolfhard, Thomas Neuhaus, and Adriaan M. J. Schakel. "Critical loop gases and the worm algorithm." Nuclear Physics B 829, no. 3 (April 2010): 573–99. http://dx.doi.org/10.1016/j.nuclphysb.2009.12.024.

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Yang, XinYu, Yi Shi, and HuiJun Zhu. "Detection and location algorithm against local-worm." Science in China Series F: Information Sciences 51, no. 12 (August 27, 2008): 1935–46. http://dx.doi.org/10.1007/s11432-008-0132-z.

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Salunkhe, Shamal, and Surendra Bhosale. "Nature Inspired Algorithm for Pixel Location Optimization in Video Steganography Using Deep RNN." International Journal on Engineering, Science and Technology 3, no. 2 (January 16, 2022): 146–54. http://dx.doi.org/10.46328/ijonest.67.

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The steganography is applied on text, image, video, and audio files. The steganography is useful for safe and secure data transmission. Video steganography is used to preserve confidential information of security applications. To improve security of the message, pixels locations are optimized using nature inspired algorithm. As conventional algorithms have a low convergence rate a new algorithm is proposed. A New algorithm is developed by combining two model algorithms namely, Water wave optimization (WWO) and Earth worm optimization (EWO) and is renamed as proposed Water-Earth Worm Optimization (WEWO) algorithm. The frames are preprocessed and extracted using Discrete Cosine transform (DCT) and Structured Similarity index (SSIM), respectively, as regular processing. For pixel prediction, the fitness function is obtained from neighborhood entropies in proposed algorithm. In this method, secret message is embedded with two level decomposition of Wavelet Transform (WT). In the proposed work is tested with ‘CAVIAR’ dataset. The Proposed WEWO-Deep RNN algorithm performance is tested with modular noises such as, pepper, salt and pepper noises. The proposed method gives enhanced performance, which is seen with the parameters, Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and Correlation Coefficient (CC) which defines image quality indices.

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Wang, Yifan, Prathamesh Pandit, Akhil Kandhari, Zehao Liu, and Kathryn A. Daltorio. "Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot." Biomimetics 5, no. 2 (June 5, 2020): 26. http://dx.doi.org/10.3390/biomimetics5020026.

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Inspired by earthworms, worm-like robots use peristaltic waves to locomote. While there has been research on generating and optimizing the peristalsis wave, path planning for such worm-like robots has not been well explored. In this paper, we evaluate rapidly exploring random tree (RRT) algorithms for path planning in worm-like robots. The kinematics of peristaltic locomotion constrain the potential for turning in a non-holonomic way if slip is avoided. Here we show that adding an elliptical path generating algorithm, especially a two-step enhanced algorithm that searches path both forward and backward simultaneously, can make planning such waves feasible and efficient by reducing required iterations by up around 2 orders of magnitude. With this path planner, it is possible to calculate the number of waves to get to arbitrary combinations of position and orientation in a space. This reveals boundaries in configuration space that can be used to determine whether to continue forward or back-up before maneuvering, as in the worm-like equivalent of parallel parking. The high number of waves required to shift the body laterally by even a single body width suggests that strategies for lateral motion, planning around obstacles and responsive behaviors will be important for future worm-like robots.

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Hilool, Ali Khalid, Soukaena H. Hashem, and Shatha H. Jafer. "Intrusion detection system based on bagging with support vector machine." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 2 (November 1, 2021): 1100. http://dx.doi.org/10.11591/ijeecs.v24.i2.pp1100-1106.

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<p>Due to their rapid spread, computer worms perform harmful tasks in networks, posing a security risk; however, existing worm detection algorithms continue to struggle to achieve good performance and the reasons for that are: First, a large amount of irrelevant data affects classification accuracy. Second, individual classifiers do not detect all types of worms effectively. Third, many systems are based on outdated data, making them unsuitable for new worm species. The goal of the study is to use data mining algorithms to detect worms in the network because they have a high ability to detect new types accurately. The proposal is based on the UNSW NB15 dataset and uses a support vector machine to train and test the ensemble bagging algorithm. To detect various types of worms efficiently, the contribution suggests combining correlation and Chi2 feature selection method called Chi2-Corr to select relevant features and using support vector machine (SVM) in the bagging algorithm. The system achieved accuracy reaching 0.998 with Chi2-Corr, and 0.989, 0.992 with correlation and chi-square separately.</p>

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Lukyanov, A. S., and A. I. Starikov. "Improving the efficiency of calculation of gear trains and worm drives." Izvestiya MGTU MAMI 7, no. 4-2 (April 20, 2013): 417–20. http://dx.doi.org/10.17816/2074-0530-68367.

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The paper proposes an improved algorithm for calculating gear train and worm drive enabling comparative analysis and subsequent selection of materials from which the items will be made. On the base of the proposed algorithm, a program was designed for design and checking calculation of gear trains and worm drives.

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Navaezadeh, Sedigheh, Mehdi Sadeghzadeh, and Ali Harounabadi. "Increasing efficiency in Grid by using glow worm Algorithm." International Journal of Computer Applications Technology and Research 2, no. 5 (September 20, 2013): 606–8. http://dx.doi.org/10.7753/ijcatr0205.1015.

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Mayeli, Ali, Erfan Mehregan, and Mohsen Manna. "Using Glow-worm algorithm to predict companies’ financial distress." Revista de Investigaciones Universidad del Quindío 34, S3 (September 19, 2022): 178–85. http://dx.doi.org/10.33975/riuq.vol34ns3.1018.

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One important research issue in the risk management area is to predict the financial distress of companies. This case has received great attention from banks, companies, managers, and investors. Although there are many studies on this case, the hybrid models (mixed feature selection and classifier models) have been used by researchers in recent years. The main objective of this study is to propose a high-performance predictive model and compare its results with other models that are commonly used for financial distress prediction. To do this, the Glowworm optimization algorithm-based hybrid neural network model was employed. Moreover, the neural network and logistic regression model, which is one of the statistical classifier models were used. The results indicated that the glowworm optimization algorithm (also known as firefly optimization algorithm)-based hybrid neural network model had higher performance compared to the neural network and logistic regression models.

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Rindlisbacher, Tobias, Oscar Åkerlund, and Philippe de Forcrand. "Sampling of general correlators in worm-algorithm based simulations." Nuclear Physics B 909 (August 2016): 542–83. http://dx.doi.org/10.1016/j.nuclphysb.2016.05.026.

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Zhang, Wei, Timothy M. Garoni, and Youjin Deng. "A worm algorithm for the fully-packed loop model." Nuclear Physics B 814, no. 3 (June 2009): 461–84. http://dx.doi.org/10.1016/j.nuclphysb.2009.01.007.

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Peng, Sancheng, Min Wu, Guojun Wang, and Shui Yu. "Containing smartphone worm propagation with an influence maximization algorithm." Computer Networks 74 (December 2014): 103–13. http://dx.doi.org/10.1016/j.comnet.2014.09.004.

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Nykytyuk, S. O., I. M. Tsymbalyuk, Kh I. Dorozhovska, S. S. Levenets, T. O. Voroncova, and M. V. Dollinna. "Lymphadenopathy and worm infestation in children: the action algorithm." Modern pediatrics. Ukraine, no. 8(128) (December 28, 2022): 90–97. http://dx.doi.org/10.15574/sp.2022.128.90.

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Fever is a common complaint in children with lymphadenopathy. Reactive lymphadenopathy is defined as the presence of one or more lymph nodes with a diameter of more than 1.5-2.0 cm. A thorough diagnosis of lymphadenitis accompanied by hyperthermic syndrome is necessary. Purpose - is to determine the diagnostic algorithm of actions based on the example of a clinical case of fever of unclear origin. Clinical case. The peculiarity of this case is a prolonged hyperthermic syndrome with lymphadenitis against the background of helminthic invasion (toxocarosis). During her stay in the hospital, the girl’s condition was serious due to hyperthermic syndrome and lymphadenopathy. The diagnostic algorithm for this condition in children is proposed. During the examination, a diagnosis of Reactive cervical lymphadenopathy of infectious-allergic genesis; concomitant - «Parasitic invasion is mixed (toxocariasis, ascariasis). Fever» was established. The child’s condition upon admission was severe, due to intoxication and hyperthermic syndrome. The treatment was effective, the patient’s condition improved during the hospitalization. But establishing a diagnosis required the cooperation of doctors of many specialties and a large number of additional examinations. Conclusions. Therefore, it is necessary to form the alertness of pediatricians to toxocarosis and increase the level of knowledge about the correct diagnostic algorithm in such cases. Informing health care professionals about such lymphadenopathy and helminthic infestation in children should help practitioners distinguish them from febrile reactions or other conditions and improve treatment outcomes. The research was carried out in accordance with the principles of the Declaration of Helsinki. Informed consent of the child’s parents was obtained for the research. No conflict of interests was declared by the authors.

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Layana Castro, Pablo E., Joan Carles Puchalt, Antonio García Garví, and Antonio-José Sánchez-Salmerón. "Caenorhabditis elegans Multi-Tracker Based on a Modified Skeleton Algorithm." Sensors 21, no. 16 (August 20, 2021): 5622. http://dx.doi.org/10.3390/s21165622.

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Automatic tracking of Caenorhabditis elegans (C. egans) in standard Petri dishes is challenging due to high-resolution image requirements when fully monitoring a Petri dish, but mainly due to potential losses of individual worm identity caused by aggregation of worms, overlaps and body contact. To date, trackers only automate tests for individual worm behaviors, canceling data when body contact occurs. However, essays automating contact behaviors still require solutions to this problem. In this work, we propose a solution to this difficulty using computer vision techniques. On the one hand, a skeletonization method is applied to extract skeletons in overlap and contact situations. On the other hand, new optimization methods are proposed to solve the identity problem during these situations. Experiments were performed with 70 tracks and 3779 poses (skeletons) of C. elegans. Several cost functions with different criteria have been evaluated, and the best results gave an accuracy of 99.42% in overlapping with other worms and noise on the plate using the modified skeleton algorithm and 98.73% precision using the classical skeleton algorithm.

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Y.K, Mogal. "A Multi-objective Optimization Approach for Design of Worm and Worm Wheel Based on Genetic Algorithm." Bonfring International Journal of Man Machine Interface 3, no. 1 (March 30, 2013): 08–12. http://dx.doi.org/10.9756/bijmmi.4403.

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Sheetal, Annabathula Phani, and Kongara Ravindranath. "High Efficient Virtual Machine Migration Using Glow Worm Swarm Optimization Method for Cloud Computing." Ingénierie des systèmes d information 26, no. 6 (December 27, 2021): 591–97. http://dx.doi.org/10.18280/isi.260610.

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In this paper, high efficient Virtual Machine (VM) migration using GSO algorithm for cloud computing is proposed. This algorithm contains 3 phases: (i) VM selection, (ii) optimum number of VMs selection, (iii) VM placement. In VM selection phase, VMs to be migrated are selected based on their resource utilization and fault probability. In phase-2, optimum number of VMs to be migrated are determined based on the total power consumption. In VM placement phase, Glowworm Swarm Optimization (GSO) is used for finding the target VMs to place the migrated VMs. The fitness function is derived in terms of distance between the main server and the other server, VM capacity and memory size. Then the VMs with best fitness functions are selected as target VMs for placing the migrated VMs. The proposed algorithms are implemented in Cloudsim and performance results show that PEVM-GSO algorithm attains reduced power consumption and response delay with improved CPU utilization.

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ZUO, Jia-liang, Ya-nan KOU, Ren-nong YANG, Ying ZHANG, Pei HOU, and Li-bing HUANG. "Comprehensive tolerance warning method of worm based on greedy algorithm." Journal of Computer Applications 30, no. 2 (March 23, 2010): 529–31. http://dx.doi.org/10.3724/sp.j.1087.2010.00529.

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Rasheed, M. M., O. Ghazali, and N. M. Norwawi. "Server Scanning Worm Detection by using Intelligent Failure Connection Algorithm." Research Journal of Information Technology 2, no. 4 (April 1, 2010): 228–34. http://dx.doi.org/10.3923/rjit.2010.228.234.

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23

Ghelase, Daniela, and Luiza Daschievici. "ASPECTS REGARDING OPTIMAL DESIGN FOR THE WORM-GEAR DRIVE." International Journal of Modern Manufacturing Technologies 13, no. 3 (December 25, 2021): 59–65. http://dx.doi.org/10.54684/ijmmt.2021.13.3.59.

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It is known that, from the point of view of the accuracy of a machine-tool, at its design, the dynamic behaviour of each element of the kinematic chains prevails. Worm-gear drives are widely used in the different machine-tools and robots. Therefore, it is important that during meshing, as far as possible, there are no vibrations, shocks, power losses, noise and low durability. These requirements can be met if, for example, the gear ratio is constant during meshing, without transmission errors, which means that the worm-gear drive should have a high accuracy. The accuracy improvement of the worm-gear drive has long been a focus of attention for machine-tools designers. Thus, this paper presents various approaches to solving such problems, based on modelling and simulation, such as: estimating the load share of worm-gear drives and to calculate the instantaneous tooth meshing stiffness and loaded transmission errors; the desired worm-gear drive design configuration by altering the optimum set of worm-gear drive design parameters which are suitable for the required performance by associating it with SVM (Support Vector Machine); optimization approach for design of worm-gear drive based on Genetic Algorithm; design optimization of worm-gear drive with reduced power loss; etc. The optimization of the worm-gear design is an important problem for the research because the design variables are correlated to each other. An optimal design algorithm developed by the authors of this paper, for worm-gear drive, is also presented.

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Tang, Yuqi. "Detection and Prevention to Network Worm Virus Based on Segmentation Algorithm." International Journal of Security and Its Applications 9, no. 9 (September 30, 2015): 123–30. http://dx.doi.org/10.14257/ijsia.2015.9.9.11.

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Huang, Chu, Sencun Zhu, Quanlong Guan, and Yongzhong He. "A software assignment algorithm for minimizing worm damage in networked systems." Journal of Information Security and Applications 35 (August 2017): 55–67. http://dx.doi.org/10.1016/j.jisa.2017.05.004.

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Mercado, Ydalia Delgado, Christof Gattringer, and Alexander Schmidt. "Surface worm algorithm for abelian Gauge–Higgs systems on the lattice." Computer Physics Communications 184, no. 6 (June 2013): 1535–46. http://dx.doi.org/10.1016/j.cpc.2013.02.001.

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Du, Yi-Hong, and Shi-Hua Liu. "Epidemic Model of Algorithm-Enhanced Dedicated Virus through Networks." Security and Communication Networks 2018 (June 7, 2018): 1–7. http://dx.doi.org/10.1155/2018/4691203.

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Wi-Fi networks almost cover all active areas around us and, especially in some densely populated regions, Wi-Fi signals are strongly overlapped. The broad and overlapped coverage brings much convenience at the cost of great security risks. Conventionally, a worm virus can infect a router and then attack other routers within its signal coverage. Nowadays, artificial intelligence enables us to solve problems efficiently from available data via computer algorithm. In this paper, we endow the virus with some abilities and present a dedicated worm virus which can pick susceptible routers with kernel density estimation (KDE) algorithm as the attacking tasks automatically. This virus can also attack lower-encryption-level routers first and acquire fast-growing numbers of infected routers on the initial stage. We simulate an epidemic behavior in the collected spatial coordinate of routers in a typical area in Beijing City, where 56.0% routers are infected in 18 hours. This dramatical defeat benefits from the correct infection seed selection and a low-encryption-level priority. This work provides a framework for a computer-algorithm-enhanced virus exploration and gives some insights on offence and defence to both hackers and computer users.

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Said, Mokhtar, Ali M. El-Rifaie, Mohamed A. Tolba, Essam H. Houssein, and Sanchari Deb. "An Efficient Chameleon Swarm Algorithm for Economic Load Dispatch Problem." Mathematics 9, no. 21 (November 1, 2021): 2770. http://dx.doi.org/10.3390/math9212770.

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Economic Load Dispatch (ELD) is a complicated and demanding problem for power engineers. ELD relates to the minimization of the economic cost of production, thereby allocating the produced power by each unit in the most possible economic manner. In recent years, emphasis has been laid on minimization of emissions, in addition to cost, resulting in the Combined Economic and Emission Dispatch (CEED) problem. The solutions of the ELD and CEED problems are mostly dominated by metaheuristics. The performance of the Chameleon Swarm Algorithm (CSA) for solving the ELD problem was tested in this work. CSA mimics the hunting and food searching mechanism of chameleons. This algorithm takes into account the dynamics of food hunting of the chameleon on trees, deserts, and near swamps. The performance of the aforementioned algorithm was compared with a number of advanced algorithms in solving the ELD and CEED problems, such as Sine Cosine Algorithm (SCA), Grey Wolf Optimization (GWO), and Earth Worm Algorithm (EWA). The simulated results established the efficacy of the proposed CSA algorithm. The power mismatch factor is the main item in ELD problems. The best value of this factor must tend to nearly zero. The CSA algorithm achieves the best power mismatch values of 3.16×10−13, 4.16×10−12 and 1.28×10−12 for demand loads of 700, 1000, and 1200 MW, respectively, of the ELD problem. The CSA algorithm achieves the best power mismatch values of 6.41×10−13 , 8.92×10−13 and 1.68×10−12 for demand loads of 700, 1000, and 1200 MW, respectively, of the CEED problem. Thus, the CSA algorithm was found to be superior to the algorithms compared in this work.

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Kim, Jihwan, and Hyeongcheol Lee. "Motor position control algorithm for an automated manual transmission of the agricultural tractor." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229, no. 18 (October 9, 2015): 3341–49. http://dx.doi.org/10.1177/0954406215610360.

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This paper presents a motor position control algorithm for an automated manual transmission (AMT) of the agricultural tractor, based on modified linear quadratic tracking (LQT). In this paper, the modified LQT is derived from the conventional LQT by applying the Luenberger observer in order to design an output feedback controller. A dynamic model of the actuator is derived to represent characteristics of the worm geared DC motor and the proposed control algorithm is applied and tuned with the model. The proposed position control algorithm of the worm geared motor using the modified LQT can improve disturbance rejection performance without changing the hardware configuration of the AMT. The simulation results show the validity of the proposed control algorithm.

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S.Abdulrasool, A., and S. M. Abbas. "Reservoir Computing: Size and Connectivity Optimization using the "Worm Algorithm"." International Journal of Computer Applications 69, no. 4 (May 17, 2013): 18–22. http://dx.doi.org/10.5120/11830-7532.

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Goranin, N., and A. Cenys. "Genetic algorithm based Internet worm propagation strategy modeling under pressure of countermeasures." Journal of Engineering Science and Technology Review 2, no. 1 (June 2009): 43–47. http://dx.doi.org/10.25103/jestr.021.08.

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ShunChieh Lin, ChunHo Tung, DingAn Chiang, and ChungI Chang. "A Modified Two-phase Knowledge Acquisition Algorithm to Construct Worm Knowledge Base." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 3, no. 3 (April 30, 2011): 136–46. http://dx.doi.org/10.4156/aiss.vol3.issue3.17.

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LI, Qiang, and Yang XIANG. "An Algorithm of Online Accumulation for Reconstructing the Path of Worm Propagation." Journal of Software 21, no. 4 (March 11, 2010): 802–15. http://dx.doi.org/10.3724/sp.j.1001.2010.03514.

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Korzec, Tomasz, Ingmar Vierhaus, and Ulli Wolff. "Performance of a worm algorithm in ϕ4 theory at finite quartic coupling." Computer Physics Communications 182, no. 7 (July 2011): 1477–80. http://dx.doi.org/10.1016/j.cpc.2011.03.018.

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Qin, Jianhua, Wenrong Wang, and Xiao Liu. "Parameter Tuning of Brushless DC Motor for Improving Control Effect with Worm Algorithm." European Journal of Electrical Engineering 23, no. 3 (June 21, 2021): 229–35. http://dx.doi.org/10.18280/ejee.230307.

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Aiming at the problem of low control precision and small applicable scope caused by adjusting control parameters in Ziegler-Nichols (ZN) method, a parameter tuning method based on Worm algorithm (WOA) is proposed for Brushless DC motor. Firstly, the model of speed control is established by proportional integral method for Brushless DC motor with two - phase conduction and three - phase full bridge drive. Then the fitness function of the controller is constructed by the Integral Absolute Error (IAE). Finally, the early optimization process, the later movement rule and the peak extraction rule are determined for WOA, and the controller parameter tuning process is designed. Simulation results under constant and sinusoidal conditions show the effectiveness of the proposed method. WOA was compared with ZN, genetic algorithm (GA), differential evolution algorithm (DE) and particle swarm optimization algorithm (PSO) in the experiment. The experimental results show that the control effect (CE) of WOA under uniform speed has been improved by 2.56% on average, and has been improved by 16.93% on average under sinusoidal speed. Compared with previous methods, this method can be used for parameter adjustment of complex control with higher control precision.

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Litvin, F. L., and V. Kin. "Computerized Simulation of Meshing and Bearing Contact for Single-Enveloping Worm-Gear Drives." Journal of Mechanical Design 114, no. 2 (June 1, 1992): 313–16. http://dx.doi.org/10.1115/1.2916948.

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Single-enveloping worm-gear drives are considered. A general approach to computerized simulation of meshing for such misaligned drives is proposed. The proposed algorithm makes it possible to determine the transfer point where ideal line contact turns into real point contact and the transmission errors and the shift of bearing contact caused by the misalignment. Numerical examples for involute worm-gear drives are presented.

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Su, Fei, Wen Jing Xu, Zhao Wen Lin, and Yan Ma. "Internet Worm Modeling and Analysis in IPv6 Networks." Advanced Materials Research 268-270 (July 2011): 1514–19. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1514.

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With the development of IPv6, it is taken as a natural cover to defend against Internet worm due to its huge address space. We demonstrate that an intelligent worm can compromise the IPv6 network according to using adaptive means. Based on the analysis of the scanning strategies in IPv6 network and correlative typical propagation technologies, a general worm model named Next Generation Internet worm model (NGIWM) is established for analyzing the propagation of IPv6 worm which is made up of three layers. The three layers have the function to accelerate the spread of NGIWM, and make NGIWM has the capability to form large scale of prevalence. The result indicates the rationality of scanning strategies and the effectiveness of the propagation compared to IPv4 network worm. The simulation shows that the implementation of NGIWM has the potential to become a major threat to IPv6 network. The performance of the worm depends heavily on domain name generator algorithm and scanning strategies in local network. We also analyze the effect of experiment parameters on the model in the simulation part. In the future, detailed implementation of the proposed model and more defense mechanisms are to be studied.

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Cai, Shan Le, Yan Wei Cai, and Wen Tao Huang. "The Optimization of Tooth Form Fitting Error on Worm Type Shaving Cutter." Advanced Materials Research 591-593 (November 2012): 356–60. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.356.

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In order to solve the flank concave problem of the rotary gear shaving cutter, a new worm type shaving cutter has been manufactured, which will be used on a gear hobbing achieving freedom shaving. And its tooth precision can reach 6-7 level. The main contents includes the worm normal section curve equation of the worm type shaving cutter involutes, the optimization of tooth fitting error and the linear fitting of the tooth curve of the normal section by the MATLAB genetic algorithm toolbox. According to GB/T6084-2001 hob series standard, the results showed that the error theory is less than 1/6 of the AA level.

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Yu, Dexin, Xuesong Zhang, Guangdong Tian, Zhigang Jiang, Zhiming Liu, Tiangang Qiang, and Changshu Zhan. "Disassembly Sequence Planning for Green Remanufacturing Using an Improved Whale Optimisation Algorithm." Processes 10, no. 10 (October 3, 2022): 1998. http://dx.doi.org/10.3390/pr10101998.

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Currently, practical optimisation models and intelligent solution algorithms for solving disassembly sequence planning are attracting more and more attention. Based on the importance of energy efficiency in product disassembly and the trend toward green remanufacturing, this paper proposes a new optimisation model for the energy-efficient disassembly sequence planning. The minimum energy consumption is used as the evaluation criterion for disassembly efficiency, so as to minimise the energy consumption during the dismantling process. As the proposed model is a complex optimization problem, called NP-hard, this study develops a new extension of the whale optimisation algorithm to allow it to solve discrete problems. The whale optimisation algorithm is a recently developed and successful meta-heuristic algorithm inspired by the behaviour of whales rounding up their prey. We have improved the whale optimisation algorithm for predation behaviour and added a local search strategy to improve its performance. The proposed algorithm is validated with a worm reducer example and compared with other state-of-the-art and recent metaheuristics. Finally, the results confirm the high solution quality and efficiency of the proposed improved whale algorithm.

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TEODOR, VIRGIL GABRIEL, GEORGIANA-ALEXANDRA MOROSANU, NICUSOR BAROIU, RAZVAN SEBASTIAN CRACIUN, and VIOREL PAUNOIU. "PROFILING OF THE HOB TOOL FOR WORM SHAFTS DEFORMATION." Journal of Engineering Studies and Research 28, no. 4 (February 9, 2023): 131–41. http://dx.doi.org/10.29081/jesr.v28i4.015.

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The paper presents an algorithm for profiling the hob tool designed to generate by plastic deformation the worm shafts from the composition of worm-wheel gear type, used in the seat adjustment mechanisms of some Audi and Mercedes cars. The active surface of the hob tool is a cylindrical helical surface of constant pitch. Two such tandem tools are used for deformation, the semi-finished product being positioned between them. During generation, the tools rotate around their own axes, which, combined with their helical surface, causes a helical movement of the blank. The active surfaces of the tools are mutually winding on the helical flanks of the generated worm. In the paper, two applications were developed for the generation of worms whose dimensions were determined by 3D scanning.

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Spada, Gabriele, Stefano Giorgini, and Sebastiano Pilati. "Path-Integral Monte Carlo Worm Algorithm for Bose Systems with Periodic Boundary Conditions." Condensed Matter 7, no. 2 (March 29, 2022): 30. http://dx.doi.org/10.3390/condmat7020030.

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We provide a detailed description of the path-integral Monte Carlo worm algorithm used to exactly calculate the thermodynamics of Bose systems in the canonical ensemble. The algorithm is fully consistent with periodic boundary conditions, which are applied to simulate homogeneous phases of bulk systems, and it does not require any limitation in the length of the Monte Carlo moves realizing the sampling of the probability distribution function in the space of path configurations. The result is achieved by adopting a representation of the path coordinates where only the initial point of each path is inside the simulation box, the remaining ones being free to span the entire space. Detailed balance can thereby be ensured for any update of the path configurations without the ambiguity of the selection of the periodic image of the particles involved. We benchmark the algorithm using the non-interacting Bose gas model for which exact results for the partition function at finite number of particles can be derived. Convergence issues and the approach to the thermodynamic limit are also addressed for interacting systems of hard spheres in the regime of high density.

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Wang, Yifan, Zehao Liu, Akhil Kandhari, and Kathryn A. Daltorio. "Obstacle Avoidance Path Planning for Worm-like Robot Using Bézier Curve." Biomimetics 6, no. 4 (September 30, 2021): 57. http://dx.doi.org/10.3390/biomimetics6040057.

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Worm-like robots have demonstrated great potential in navigating through environments requiring body shape deformation. Some examples include navigating within a network of pipes, crawling through rubble for search and rescue operations, and medical applications such as endoscopy and colonoscopy. In this work, we developed path planning optimization techniques and obstacle avoidance algorithms for the peristaltic method of locomotion of worm-like robots. Based on our previous path generation study using a modified rapidly exploring random tree (RRT), we have further introduced the Bézier curve to allow more path optimization flexibility. Using Bézier curves, the path planner can explore more areas and gain more flexibility to make the path smoother. We have calculated the obstacle avoidance limitations during turning tests for a six-segment robot with the developed path planning algorithm. Based on the results of our robot simulation, we determined a safe turning clearance distance with a six-body diameter between the robot and the obstacles. When the clearance is less than this value, additional methods such as backward locomotion may need to be applied for paths with high obstacle offset. Furthermore, for a worm-like robot, the paths of subsequent segments will be slightly different than the path of the head segment. Here, we show that as the number of segments increases, the differences between the head path and tail path increase, necessitating greater lateral clearance margins.

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Parveen, Katheeja, Sheik Abdul Khader, and Munir Ahamed Rabbani. "Energy aware improved least and most significant bit arbitration algorithm for WORM tags." Egyptian Informatics Journal 13, no. 2 (July 2012): 75–83. http://dx.doi.org/10.1016/j.eij.2012.04.003.

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Hattori, Kiyohiko, Eri Homma, Toshinori Kagawa, Masayuki Otani, Naoki Tatebe, Yasunori Owada, Lin Shan, Katsuhiro Temma, and Kiyoshi Hamaguchi. "Generalized measuring-worm algorithm: high-accuracy mapping and movement via cooperating swarm robots." Artificial Life and Robotics 21, no. 4 (September 1, 2016): 451–59. http://dx.doi.org/10.1007/s10015-016-0301-x.

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Mohan, L. V., and M. S. Shunmugam. "An orthogonal array based optimization algorithm for computer-aided measurement of worm surface." International Journal of Advanced Manufacturing Technology 30, no. 5-6 (November 12, 2005): 434–43. http://dx.doi.org/10.1007/s00170-005-0097-7.

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Makadia, Jiten, and C. D. Sankhavara. "Optimization of Shell and Tube Heat Exchanger Using Alpha Tuning Elephant Herding Optimization (EHO) Technique." International Journal of Engineering Research in Africa 52 (January 2021): 92–101. http://dx.doi.org/10.4028/www.scientific.net/jera.52.92.

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Swarm Intelligence algorithms like PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization), ABC (Artificial Bee Colony), Glow-worm swarm Optimization, etc. have been utilized by researchers for solving optimization problems. This work presents the application of a novel modified EHO (Elephant Herding Optimization) for cost optimization of shell and tube heat exchanger. A comparison of the results obtained by EHO in two benchmark problems shows that it is superior to those obtained with genetic algorithm and particle swarm optimization. The overall cost reduction is 13.3 % and 9.68% for both the benchmark problem compared to PSO. Results indicate that EHO can be effectively utilized for solving real-life optimization problems.

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Seyed Mahmood Hashemi. "An approach for stock buying with evolutionary optimization algorithms." World Journal of Advanced Engineering Technology and Sciences 7, no. 2 (November 30, 2022): 071–78. http://dx.doi.org/10.30574/wjaets.2022.7.2.0038.

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Providing stock buying with more profit for buyer is challenging procedure in buying operation. In other words, buyers expect more profit with less cost. Many influence parameters cause this procedure being attractive. One of them is liquidity. There are some measurements for liquidity. With complete and detailed model and with detailed variables and in the static environment (with no changing in conditions), we can use common approach for optimization to buy proper stocks, but in a dynamic environment (which many of circumstances are changed) with incomplete models and with noisy variables (probably), common approaches cannot satisfy all requirements. In spite of common approaches for optimization, we can use Evolutionary Optimization Algorithms. In this paper, three evolutionary optimization algorithms (Particle Swarm Optimization, The Wale Optimization algorithm and the Worm Optimization algorithm), in multi-objective mode, are used to buy the stocks of three Iranian banks and then benefits and weakness of evolutionary algorithms are compared.

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Hu, Hangyu, Mingda Wang, Mingyu Ouyang, and Guangmin Hu. "Toward Network Worm Victims Identification Based on Cascading Motif Discovery." Electronics 8, no. 2 (February 5, 2019): 183. http://dx.doi.org/10.3390/electronics8020183.

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Network worms spread widely over the global network within a short time, which are increasingly becoming one of the most potential threats to network security. However, the performance of traditional packet-oriented signature-based methods is questionable in the face of unknown worms, while anomaly-based approaches often exhibit high false positive rates. It is a common scenario that the life cycle of network worms consists of the same four stages, in which the target discovery phase and the transferring phase have specific interactive patterns. To this end, we propose Network Flow Connectivity Graph (NFCG) for identifying network worm victims. We model the flow-level interactions as graph and then identify sets of frequently occurring motifs related to network worms through Cascading Motif Discovery algorithm. In particular, a cascading motif is jointly extracted from graph target discovery phase and transferring phase. If a cascading motif exists in a connected behavior graph of one host, the host would be identified as a suspicious worm victim; the excess amount of suspicious network worm victims is used to reveal the outbreak of network worms. The simulated experiments show that our proposed method is effective and efficient in network worm victims’ identification and helpful for improving network security.

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Shvalb, Nir, Boaz Ben Moshe, and Oded Medina. "A real-time motion planning algorithm for a hyper-redundant set of mechanisms." Robotica 31, no. 8 (June 11, 2013): 1327–35. http://dx.doi.org/10.1017/s0263574713000489.

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SUMMARYWe introduce a novel probabilistic algorithm (CPRM) for real-time motion planning in the configuration space${\EuScript C}$. Our algorithm differs from a probabilistic road map (PRM) algorithm in the motion between a pair of anchoring points (local planner) which takes place on the boundary of the obstacle subspace${\EuScript O}$. We define a varying potential fieldfon ∂${\EuScript O}$as a Morse function and follow$\vec{\nabla} f$. We then exemplify our algorithm on a redundant worm climbing robot withndegrees of freedom and compare our algorithm running results with those of the PRM.

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Yin, Xin, Tadahiro Fujimoto, Norishige Chiba, and Hiromi T. Tanaka. "Modeling of Wood Aging Caused by Biological Deterioration." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 2 (March 20, 2008): 125–31. http://dx.doi.org/10.20965/jaciii.2008.p0125.

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We propose visually simulating wood aging by microorganisms using an ant colony optimization algorithm to generate wood aging patterns. Ants deposit pheromone similar to termites and wood deterioration caused by termites is simulated using this algorithm. Patterns generated by this algorithm resemble many pattern in nature, meaning ant paths are representative of worm paths and ant pheromones are representative of microorganism growth. We demonstrate the effectiveness of this technique in experiments.

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Journal articles on the topic 'Worm Algorithm'

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