International Journal of Industrial Engineering‚ 18(4)‚ 169-179‚ 2011. A CASE STUDY ON EVALUATING PERSONNEL AND JOBS JOINTLY WITH FUZZY DISTANCE SETS İsmail Özdaban*‚ Coşkun Özkan** *Istanbul Technical University‚ Department of Industrial Engineering‚ Istanbul‚ Turkey. E-mail: iozdaban@artcraft.com.tr **Kocaeli University‚ Department of Industrial Engineering‚ Kocaeli‚ Turkey. E-mail: coskunozkan@kou.edu.tr In this research‚ a case study of fuzzy approach on personnel evaluation and job evaluation
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how you want to set things up and how many CPUs you will be using on the network. It’s called hybrid topology because two different kind of wire network if needed‚ and can’t be set up by the conventional process. Setting up a hybrid topology has some good and bad perspectives. The good things are effectiveness‚ flexibility‚ it is reliable and scalable. Some of the bad things about the hybrid topology set up are‚ expensive infrastructure‚ and hub. Also it is a very complex way to set up a network.
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this term in year 11 we have collected data from two different species of trees and compared this data in graphs and statistics. we needed to prove or decline that as trees grow larger there leavs get smaller due to the fluid flow within the tree TABLE OF CONTENTS Part A: INTRODUCTION EXPECTAIONS‚ PREDICTIONS AND ASSUMPTIONS PAGE 3 DATA SECONDARY DATA – STEM AND LEAF PLOT PAGE 4 SECONDARY DATA – LINE GRAPH AND OGIVES PAGE 6 SECONDARY DATA
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different conclusions from the same set of data. 2. Quantitative & Categorical Data – Two different types of data. 3. Categorical Graphs – Bar graphs & pie charts. 4. “Center” & “Spread” for Quantitative Data – Mean‚ median‚ standard deviation‚ etc. 5. Quantitative Graphs – DotPlots‚ StemPlots‚ Histograms‚ BoxPlots‚ Ogives. 6. Describing Quantitative Graphs – Shape‚ center‚ spread‚ symmetric vs. skewed‚ etc. 7. Comparative Plots – Graphs comparing two sets of data. 8. Reasoning – Propose an
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Mathematical ideas are often divided into two types‚ those that are continuous‚ and those that are discrete. An example of continuous is the number line. Between any two points‚ there are always more points. For discrete sets‚ this is not true. For instance‚ in baseball there are four bases. If you get a hit it is either a one-base hit (what we call a single)‚ a two-base hit‚ a three-base hit‚ or a home run. There is no such thing as a 2 1/2 base hit. Discrete things are found
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This work of QNT 351 Week 5 Learning Team Assignment - Analyzing and Interpreting Data consists of: Ask your instructor for specific information regarding the analysis you are required to perform for your data set. Combine your Week Two Learning Team assignment and Week Three findings with Week Five findings and make a recommendation to the research problem. Use the statistical tables given in the appendices of the textbook and a statistical analysis application: a Microsoft
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4 is greater than 3 ≫ Much greater than 100000 ≫ 45 100000 is much greater than number 45 < Less than 3 < 4 3 is less than 4 ≪ much less than 1 ≪ 100000 1 is much less than 100000 U union A U B A union B . Proper subset symbol Sets A B proper subset of sets A B ∫ Integral sign ∫ x2 dx = x3 / 3 Integration of x2 is x3 / 3 π Greek pi π = 3.14159 Use this value in formula λ lambda Λ = 70 cm Wavelength ratio ° Degree Symbols 45° Angle measure by degree φ Greek phi φ = 45° Angular variable
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Tan Hooi Gia Food and beverage: Juani Eyat Juleng (decide the menu) Set Designer: Phang Yuen Jun Event Planner: Kanagah A/P Raman Publicity: Sam Chee Xin Sponsorship: Yap Paul Yin 3.0 Other items to be discussed and decided The chairman asked the team members to do research on their individual role’s corresponding tasks. For the coming meeting‚ each of the members is able to propose his or her plan for the food menu‚ set design‚ events and publicity. They need to plan for the budget for
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Package ‘randomForest’ February 20‚ 2015 Title Breiman and Cutler ’s random forests for classification and regression Version 4.6-10 Date 2014-07-17 Depends R (>= 2.5.0)‚ stats Suggests RColorBrewer‚ MASS Author Fortran original by Leo Breiman and Adele Cutler‚ R port by Andy Liaw and Matthew Wiener. Description Classification and regression based on a forest of trees using random inputs. Maintainer Andy Liaw <andy_liaw@merck.com> License GPL (>= 2) URL http://stat-www.berkeley.edu/users/breiman/RandomForests
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populations and processed data. There are two different types of statistics‚ descriptive statistics and inferential statistics. Descriptive statistics utilizes numerical and graphical methods to look for patterns in a data set‚ to summarize the information revealed in a data set‚ and to present the information in a convenient form. Inferential statistics utilizes sample data to make
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