Algorithm

BIOINSPIRED SWARM BASED ROUTING ALGORITHMS IN VANETs Arshpreet Kaur*, Er. Navroz Kaur Kahlon** *(Computer Engineering Department, UCOE, Punjabi University, Patiala) ** (Asst. Prof. Computer Engineering Department, Punjabi University, Patiala) (Email: *arshrai90@gmail.com, **Kahlon.navroz3@gmail.com) Abstract-Vehicular Ad-hoc Networks (VANETs) play main role in the design and development of the Intelligent Transportation Systems (ITS) who improves the road safety and transportation productivity

December 2016 Term Paper 3 Page Update Bioinformatics Algorithms: Dr. Kate Cooper A Comparative Analysis of Force Directed Layout Algorithms for Biological Networks Brief Description: I will conduct a comparative analysis of multiple force-directed algorithms used to identify clusters in biological networks. The analysis will consider topics such as the algorithm process, amount of preprocessing, complexity, and flexibility of the algorithms for different types and sizes of data. K-Means, SPICi

Genetic Algorithms and its Applications to Cyber Security Paper By Sameera Chalamalasetty Guided By Dr. Mario A Garcia Abstract: Genetic algorithms (GAs) were initially proposed by John Holland, whose thoughts were connected and developed by Goldberg. GAs are a heuristic pursuit procedure

3. A Detailed Look Into a Simple Genetic Algorithm In order to demonstrate the structure of a GA, it's best to take a look at a simple program which aims to find the maximum value of a function. This example has been deconstructed from the source code provided in [7]. Note that employing a genetic algorithm for such a simple problem is actually unnecessary and time-consuming, and realistically would use a more straightforward approach. Genetic Algorithms are generally tailored to more complex non-linear

Ricardo Rigodon and Maulik Patel Homework 1 Due 9/15 1-6 A counter example for this algorithm can be shown as follows. U = {27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43} S1 = {27, 28} S2 = {29, 30, 31, 32} S3 = {33, 34, 35, 36, 37, 38, 39, 40, 41} S4 = {27, 28, 29, 30, 31, 32, 33, 34} S5 = {35, 36, 37, 38, 39, 40, 41, 42, 43} The correct answer for this is S4 and S5. However, the algorithm will choose S3, S2, and then S1 which is incorrect. S3 because it has the most uncovered

LIMITATIONS OF EVOLUTIONARY ALGORITHMS Evolutionary algorithms are very promising problem solving techniques but at the same time, they have a few limitations that can result in loss of efficiency. • Difficult parameter tuning: Any implementation of an Evolutionary algorithms will require the specification of various parameters, such as population size, mutation rate, and maximum run time, as well as the design of selection, recombination, and mutation procedures. Finding effective choices for these

Paper title: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy Method Introduction The goal of this study was to compare algorithms’ performance using the span of motion complexity and MLC modulation that may be expected during clinical practice. MLC plans and motion input Selected abdominal/thoracic and pelvic tumor motions were all obtained by Per Polsen [1, 2] as representing characteristic three-dimensional motion patterns for those

Application of DE Algorithm Nasim Taghizadeh Alamdari Department of Electrical Engineering University of North Dakota Grand Forks, ND, USA nasim.taghizadehalam@ndus.edu Dr. Eunjin Kim Department of Computer Science University of North Dakota Grand Forks, ND, USA ejkim@cs.und.edu Abstract—Differential Evolution (DE) is seemingly a standout amongst the most capable and flexible evolutionary optimizers for the nonstop parameter spaces as of late. Since the advancement of DE algorithm on late years

UTILITY OF COGNITIVE RADIO IN WBAN AND DISCUSSION OF DIFFERENT ALGORITHMS FOR THE SAME. Abstract−A WIRELESS BODY AREA NETWORK (WBAN) is a wireless sensor network technology that is confined to body of a person under supervision. As we use ISM band for transmission of information for WBAN thus it is a huge possibility that the transmission can undergo interference that affect the transmission. Hence there is a major utility of combining cognitive radio with WBAN. In this report, we discuss the role

Comparision of p-self Protection Problem Algorithms for Static Wireless Sensor Networks Nikitha Gullapalli Graduate Student, Dept. of Computer Science and Engineering, University of South Florida nikitha@mail.usf.edu Abstract — Wireless sensor networks are being widely used in many surveillance applications. Since sensor nodes are a critical part of sensor networks, certain level of protection needs to be provided to them. The self-protection problem focuses on using sensor nodes to provide