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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Jiaqi Gu Rodrigo C. de Lamare Communications Research Group Department of Electronics University of York U.K.

ISBN: (纸本)9781479928941

In this work, we propose a cross-layer design strategy based on the parallel interference cancellation (PIC) detection technique and a multi-relay selection algorithm for the uplink of cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We devise a low-cost greedy list-based PIC (GL-PIC) strategy with RAKE receivers as the front-end that can approach the maximum likelihood detector performance. We also present a low-complexity multi-relay selection algorithm based on greedy techniques that can approach the performance of an exhaustive search. Simulations show an excellent bit error rate performance of the proposed detection and relay selection algorithms as compared to existing techniques.

关键词： selection algorithm CDMA mobile communications Direct-sequence code-division multiple access bit error rate performance RAKE receivers relay CANCELLATIONS up link Joints

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Effective Analysis of Feature selection algorithms for Network based Intrusion Detection System

Effective Analysis of Feature Selection Algorithms for Netwo...

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IEEE Bombay Section Signature Conference (IBSSC)

作者： Trupti Chandak Chaitanya Ghorpade Sanyam Shukla Computer Science and Engineering MANIT Bhopal India

ISBN: (纸本)9781538674765

Malicious activities can harm the security of the system. These activities must be avoided. Network traffic data can be monitored and analyzed by using intrusion detection system. Different data mining classification techniques are used to detect network attacks. Dimensionality reduction performs key role in the Intrusion Detection System, since detecting anomalies is time-consuming. Recently a lot of work has been done in feature selection. But, most of the authors have modified the KDD99 test dataset. Modification of training dataset is valid but modifying test dataset is against the machine learning ethics. This work comprises some of the recently proposed feature selection algorithm such as Information gain, Gain Ratio and Correlation-based feature selection with the objective of determining the reduced feature set. The performance is evaluated using a combination of any two feature selection technique. This study proposes a new heuristic based feature selection algorithm using naive Bayes classifier to detect the important reduced feature set. The results are evaluated on c4.5 decision tree classifier and the results are compared with the existing works. The evaluated results show that the proposed reduced feature set gives the effective and efficient performance.

关键词： Intrusion Detection System (IDS) Feature Reduction KDD99 Dataset Naive Bayes Classifier c4.5 Decision tree INTRUSION DETECTION SYSTEMS Feature extraction Bayesian classifier selection algorithm Accidents,emergencies and safety Dataset Network algorithms

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Predicting the Protein Tertiary Structure by Hybrid Clonal selection algorithms on 3D Square Lattice

Predicting the Protein Tertiary Structure by Hybrid Clonal S...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science

作者： Iryna Fefelova Andrey Fefelov Mariia Voronenko Alexander Kornelyuk Anatoliy Sachenko Eduard Ryzhkov Volodymyr Lytvynenko Department Informatics and Computer Science Kherson National Technical University Kherson Ukraine Department of Design Kherson National Technical University Kherson Ukraine Department of Protein Engineering and Bioinformatics Institute of Molecular Biology and Genetics Kyiv Ukraine Reseach Institute for Intelligent Computer Systems Ternopil National Economic University Ternopil Ukraine Department of economic and information security Dnipro State University of Internal Affairs Dnipro Ukraine

ISBN: (数字)9781728155661

ISBN: (纸本)9781728155678

The article considers the task of predicting the tertiary structure of a protein based on its primary sequence. The task of protein folding is solved by searching for conformation with minimal energy, if you look in terms of optimization problem. The work describes the use of a hybrid artificial immune system. In our work we try to combine clonal selection algorithms with differential and trigonometric differential evolution algorithms. We use special coding and decoding methods for individual individuals. The affinity function reduces the number of solutions with self-intersections (incorrect conformations) in the developed hybrid algorithms. We chose the hydrophobic-polar Dill model on a three-dimensional square lattice to test our algorithms. The study shows the advantages of the developed algorithms in comparison with other existing methods using experimental studies of test sequences.

关键词： artificial immune systems biology computing evolutionary computation molecular biophysics optimisation proteins artificial immune systems biology computing evolutionary algorithm molecular biology selection algorithm algorithms Tertiary Protein Structure Clonal selection Proteins

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selection on k-dimensional meshes with multiple broadcasting

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COMPUTER JOURNAL 1996年第2期39卷 140-144页

作者： Pan, Y Hamdi, M Singh, G HONG KONG UNIV SCI & TECHNOL DEPT COMP SCIKOWLOONHONG KONG KANSAS STATE UNIV DEPT COMP & INFORMAT SCIMANHATTANKS 66506

Randomized selection algorithms on k-dimensional mesh-connected computers with multiple broadcasting are proposed in this paper. We first show that a leader can be elected in O(log N) time on any k-dimensional mesh-connected computers with multiple broadcasting of size N. We then shaw that we can find the p-ah smallest element among a data set of size N in O((log N+k+N-1/(k(k+1)) log N) expected time using a regular N-1/k x...x N-1/k k-dimensional mesh and in O((log N+k(2)N(1/(k2k))) log N) expected time rasing an irregular N-(2k-1k+1/(k2k))x N-(2k-2k+1/(k2k)) x...x N-(k+1/(k2k)) dimensional mesh, This leads to a selection algorithm, which runs In O((log N)(2)) expected time on a regular ((log N/log log N)(1/2)))-dimensional mesh ai on an irregular (log log N)-dimensional mesh each with N processors. To our best knowledge, this is the first polylogarithmic selection algorithm on meshes with multiple broadcasting.

关键词： algorithm broadcasting algorithms Computers selection algorithm Medical Subject Headings

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Dynamic waveform selection for manoeuvering target tracking in clutter

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IET RADAR SONAR AND NAVIGATION 2013年第7期7卷 815-825页

作者： Wang, Jiantao Qin, Yuliang Wang, Hongqiang Li, Xiang Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China

In recent years, cognitive radar (CR) with waveform diversity has exhibited significant performance improvements over the traditional fixed waveform radar and become an area of vigorous research and development. This study presents a dynamic waveform selection algorithm to strive for tracking error minimisation for CR manoeuvering target tracking in clutter. Based on the concepts of resolution cell and measurement extraction cell, the statistical characteristics of radar measurements are discussed without dependence upon the Cramer-Rao lower bound of the measurement errors and the high signal-to-noise ratio assumption. A particle filter combined with probabilistic data association is used as a tracker. To quantify the utility of available waveforms, the predicted tracking mean-square error, because of its dependence on actual future measurements, is approximated efficiently via Gaussian fitting of the prior density of the target state and statistical linearisation of the measurement equation. Monte Carlo simulation results show that the proposed dynamic waveform selection algorithm can improve tracking performance considerably, especially in terms of track loss probability.

关键词： waveforms waveform diversity Error measure Target tracking Radar measurement selection algorithm clutter data association resolution cell Particle filters

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A Proposed Method for Multi-Criteria Group Decision Making: An Application to Site selection

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APPLIED ARTIFICIAL INTELLIGENCE 2021年第7期35卷 505-519页

作者： Radwan, Nouran M. Elstohy, Rasha Hanna, Wael K. Sadat Acad Management Sci Comp & Informat Syst Dept Cairo Egypt Obour Inst Informat Syst Dept Cairo Egypt

In the real world, decision-making process is related to alternative evaluation with respect to multiple conflicting criteria. In this paper, a hybrid group approach to solve the site selection problem is developed by integrating two methods which are the Best Worst Method (BWM) and Evaluation based on Distance from Average (EDAS). The multi-criteria group decision-making methods aggregate expert preferences and present the best agreement. BWM method is used to do pairwise comparisons in a structured way to determine the criteria weight. EDAS is a method used for alternative ranking which is useful for the decision issues that contain conflicting criteria. In order to show the procedures and the application of the developed method, a case study for site selection of plastic manufacturing company is developed. A comparison made between the proposed method and the AHP method is developed to ensure that the proposed method offers reliable results. Also, sensitivity analysis is conveyed for robustness validation.

关键词： Decision-making Site selection selection algorithm Best worst method

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Monotonicity of the χ2 -statistic and Feature selection

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Annals of Data Science 2022年第6期9卷 1223-1241页

作者： Kamalov, Firuz Leung, Ho Hon Moussa, Sherif Canadian University Dubai Dubai United Arab Emirates UAE University Al Ain United Arab Emirates

Feature selection is an important preprocessing step in analyzing large scale data. In this paper, we prove the monotonicity property of the χ2-statistic and use it to construct a more robust feature selection method. In particular, we show that χY,X12≤χY,(X1,X2)2. This result indicates that a new feature should be added to an existing feature set only if it increases the χ2-statistic beyond a certain threshold. Our stepwise feature selection algorithm significantly reduces the number of features considered at each stage making it more efficient than other similar methods. In addition, the selection process has a natural stopping point thus eliminating the need for user input. Numerical experiments confirm that the proposed algorithm can significantly reduce the number of features required for classification and improve classifier accuracy. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Feature selection χ2-statistic Machine learning Big data Statistic Monotonic function Feature selection Classification selection algorithm

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Energy-aware secondary user selection in cognitive sensor networks

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IET WIRELESS SENSOR SYSTEMS 2014年第2期4卷 86-96页

作者： Zahmati, Amir Sepasi Fernando, Xavier Grami, Ali Ryerson Univ Dept Elect & Comp Engn Toronto ON M5B 2K3 Canada Univ Ontario Fac Engn & Appl Sci Inst Technol Oshawa ON L1H 7K4 Canada

In cognitive radio, accurate spectrum sensing is essential to optimally use the available spectrum opportunities. On the other hand, energy is a scarce resource especially in cognitive sensor networks. In this study, the authors combine both these conflicting requirements and propose an energy-aware secondary user selection algorithm for cognitive sensor networks. First, an optimisation problem is solved to obtain the minimum required number of cognitive users, whereas satisfying the system requirements. Second, the most eligible cognitive users are identified through a probability-based approach. They study two extreme cases by focusing on either energy or accuracy parameters. By numerical analysis, it is shown that the accuracy benchmark is increased by as much as 39% by only considering the sensing accuracy, and the energy benchmark is reduced by as low as 76% by only considering the remaining level of energy. In addition, they conduct computer simulation and compare the network's lifetime at several sensing accuracy thresholds. It is elaborated that greater sensing accuracy thresholds lead to longer network lifetime. Finally, the effects of several fusion rules on the proposed method are studied through simulation and numerical analyses. It is discussed that the Majority rule has the best performance among the examined rules.

关键词： system requirements Sensor networks Numerical Analysis Energy sources optimum performance extreme case selection algorithm

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Using farmland prices to evaluate cost-efficiency of national versus regional reserve selection in Denmark

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BIOLOGICAL CONSERVATION 2006年第4期128卷 455-466页

作者： Strange, N Rahbek, C Jepsen, JK Lund, MP Royal Vet & Agr Univ Dept Econ Policy & Planning DK-1958 Frederiksberg Denmark

The current study focuses on the influence of geopolitical coordination of conservation strategies on cost and efficiency in terms of species representation when selecting network of protected areas. Conservation policies in the EU are implemented at many different administrative levels: from the European Union and national levels, to regional or/county levels within member countries. This arise the question what size of efficiency gains could be achieved if planning of conservation priorities could be coordinated between geopolitical units. Using data for the nationwide distribution of 763 species, representing all Danish species within eight taxa, we compared illustrative costs for the addition of new areas to the existing conservation network in order to ensure full coverage of all species. We found that the cost of independent regional planning is 20-fold higher than an inter-regional and nationally co-ordinated strategy. we also found that substituting land prices for a simple land-area measure in our analyses increased the expected conservation costs differential significantly, without increasing coverage of species representations. We suggest that in economic and biodiversity terms it can largely be a win-win situation to set a common goal, to develop priority-strategies, and to coordinate actions at higher rather than lower levels of administration. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： nature conservation regional vs. national strategies priorities selection algorithm efficiency conservation cost Denmark

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algorithmic Patient selection for Minimally Invasive Versus Open Lumbar Interbody Fusion Surgery

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NEUROSURGERY CLINICS OF NORTH AMERICA 2023年第4期34卷 599-607页

作者： Goldberg, Jacob L. Hussain, Ibrahim Fu, Kai-Ming Virk, Michael S. New York Presbyterian Hosp Dept Nerosurg Weill Cornell Med Ctr 525 E 68th StBox 99 New York NY 10065 USA

Evidenced-based data-driven decision-making algorithms guide patient and approach selection for adultspinal deformitysurgery. algorithms are continually refined as surgical goals and intraoperative technology evolve.

关键词： Minimally invasive spine surgery Spine deformity selection algorithm

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