Performance Assessment of Unsupervised Clustering Algorithms Combined MDL Index

Best clustering analysis should be resisting the presence of outliers and be less sensitive to initialization as well as the input sequence ordering. This chapter compares the performance among three of the unsupervised clustering algorithms: neural gas (NG), growing neural gas (GNG), and robust growing neural gas (RGNG). A complete explanation of NG and GNG algorithms is presented in the next comparison with RGNG. Another comparison due to the minimum description length (MDL) criterion between RGNG used MDL value as the clustering validity index versus GNG and NG combined with MDL. Statistical estimations are applied to explain the meaning of the output results when these algorithms are fed to the synthetic 2D dataset. The techniques introduced in this chapter are designed and implemented in a simple software package using a MATLAB-based graphical user interface (GUI) tool, which allows users to interact with the clustering techniques and output data easily

Design Graphical User Interface of Linear Algebra System Package by Using MATLAB

The Linear Algebra package offers routines to construct and manipulate Matrices and Vectors, compute standard operations, query results and solve linear algebra problems. This Linear Algebra package implements a vast array of common linear algebra functions. This library is intended to be completely self-contained and instructive to the interested user. In this paper a developed Software Package based on Graphical User Interface (GUI) using MATLAB is proposed which can be used for students and researchers in Mathematics. This package consists of two main modules; the first one deal with applying main important methods of linear algebra system (Gauss elimination, practical solution, least square solution and a square solution, Invertible).While in the second introduces some important explanation of linear algebra system as well as has created significant examination testing for students that related to linear algebra. In summary, this Software Package is designed and implemented in simple way and user friendly as well as it is very easy to use and apply any methods , so it can be easily used by students/ researchers using only standalone application or executable file (exe file) without installing MATLAB program

Relationship of vascular variations with liver remnant volume in living liver transplant donors

Background: In this study, we investigated the relationship between the portal vein and hepatic artery variations and the remaining liver volume in living donors in liver transplantation.Materials and methods: In the study, triphasic abdominal computed tomography images of 180 live liver donor candidates were analysed retrospectively. Portal veins were divided into four groups according to the Nakamura classification and seven groups according to the Michels classification. The relationship between vascular variations and remnant liver volume was compared statistically.Results: According to the Nakamura classification, there were 143 (79.4%) type A, 23 (12.7%) type B, 7 (3.9%) type C and 7 (3.9%) type D cases. Using the Michels classification, 129 (71%) type 1, 12 (6.7%) type 2, 24 (13%) type 3, 2 (2.2%) type 4, 10 (5.6%) type 5, 1 (0.6%) type 6, and 2 (1.1%) type 7 cases were detected. There was no significant difference in the percentage of the remaining volume of the left liver lobe between the groups (p = 0.055, p = 0.207, respectively).Conclusions: Variations in the hepatic artery and portal vein do not affect the remaining liver volume in liver transplantation donors

Interaction between Axons and Specific Populations of Surrounding Cells Is Indispensable for Collateral Formation in the Mammillary System

An essential phenomenon during brain development is the extension of long collateral branches by axons. How the local cellular environment contributes to the initial sprouting of these branches in specific points of an axonal shaft remains unclear.The principal mammillary tract (pm) is a landmark axonal bundle connecting ventral diencephalon to brainstem (through the mammillotegmental tract, mtg). Late in development, the axons of the principal mammillary tract sprout collateral branches at a very specific point forming a large bundle whose target is the thalamus. Inspection of this model showed a number of distinct, identified cell populations originated in the dorsal and the ventral diencephalon and migrating during development to arrange themselves into several discrete groups around the branching point. Further analysis of this system in several mouse lines carrying mutant alleles of genes expressed in defined subpopulations (including Pax6, Foxb1, Lrp6 and Gbx2) together with the use of an unambiguous genetic marker of mammillary axons revealed: 1) a specific group of Pax6-expressing cells in close apposition with the prospective branching point is indispensable to elicit axonal branching in this system; and 2) cooperation of transcription factors Foxb1 and Pax6 to differentially regulate navigation and fasciculation of distinct branches of the principal mammillary tract.Our results define for the first time a model system where interaction of the axonal shaft with a specific group of surrounding cells is essential to promote branching. Additionally, we provide insight on the cooperative transcriptional regulation necessary to promote and organize an intricate axonal tree

Disaster relief operations: past, present and future

The aim of the preface is to introduce the scope of this special issue (SI). We explain our editorial approach and summarise our findings based on articles included in this SI. Finally, we outline future research questions which stemmed out of the discussions of this SI

Genetic parameters and correlations for lactation milk yields according to lactation numbers in Jersey cows [Jersey i·neklerde laktasyon si{dotless}ralari{dotless}na göre laktasyon süt verimleri i·çin genetik parametreler ve korelasyonlar]

In this study, heritabilities, genetic and phenotypic correlations for lactation milk yields were estimated using 3630 305-day lactation milk yield records obtained from cows calved from 1984 to 2007 years in Jersey cattle herd of Karaköy Agricultural State Farm in Samsun. Calving year, calving month and lactation number were assumed as fixed effect factors in statistical analysis of data. Heritabilities, genetic and phenotypic correlations were estimated by derivative-free REML with the animal model. Analysis showed that the overall means of 305-day milk yield, lactation length, dry off period and calving interval were 3467 kg, 297 days, 70 days and 367 days, respectively. Variance analysis results showed that all of the fixed effect factors were statistically significant on lactation milk yields (P<0.001). REML estimates of heritability were 0.289, 0.319, 0.324, 0.331, 0.339, 0.357 and 0.379 for lactation milk yields (from the first to seventh lactation numbers, respectively). Genetic correlations among the first and sub-sequent lactation milk yields were 0.687, 0.676, 0.631, 0.601, 0.590 and 0.551, respectively. All genetic correlations were high and statistically significant (P<0.01). High genetic correlations among lactation numbers reflected that the first lactation milk yield of cows would be useful indicator for the sub-sequent lactations and selection of breeding stock

Design of a Machine Learning Based Predictive Analytics System for Spam Problem

Spamming is the act of abusing an electronic messaging system by sending unsolicited bulk messages. Filtering of these messages is merely another line of defence and does not prevent spam messages from circulating in email systems. This problem causes users to distrust email systems, suspect even legitimate emails and leads to substantial investment in technologies to counter the spam problem. Spammers threaten users by abusing the lack of accountability and verification features of communicating entities. To contribute to the fight against spamming, a cloud-based system that analyses the email server logs and uses predictive analytics with machine learning to build trust identities that model the email messaging behavior of spamming and legitimate servers has been designed. The system constructs trust models for servers, updating them regularly to tune the models. This study proposed that this approach will not only minimize the circulation of spam in email messaging systems, but will also be a novel step in the direction of trust identities and accountability in email infrastructure

High-energy kHz Yb:KYW dual-crystal regenerative amplifier

A highly stable Yb:KYW based dual crystal regenerative amplifier is demonstrated, which generates at 1 kHz 6.5-mJ pulses before and up to 4.7-mJ sub-ps pulses after compression with multilayer-dielectric gratings, respectively. The stretcher is compact and based on chirped-fiber Bragg gratings. In continuous-wave operation, 20 W are extracted with a slope efficiency of 40%. The experimental data are in agreement with detailed simulations of the laser dynamics

Design of a Machine Learning Based Predictive Analytics System for Spam Problem

Spamming is the act of abusing an electronic messaging system by sending unsolicited bulk messages. Filtering of these messages is merely another line of defence and does not prevent spam messages from circulating in email systems. This problem causes users to distrust email systems, suspect even legitimate emails and leads to substantial investment in technologies to counter the spam problem. Spammers threaten users by abusing the lack of accountability and verification features of communicating entities. To contribute to the fight against spamming, a cloud-based system that analyses the email server logs and uses predictive analytics with machine learning to build trust identities that model the email messaging behavior of spamming and legitimate servers has been designed. The system constructs trust models for servers, updating them regularly to tune the models. This study proposed that this approach will not only minimize the circulation of spam in email messaging systems, but will also be a novel step in the direction of trust identities and accountability in email infrastructure