First Level Arabic

http://deepblue.lib.umich.edu/bitstream/2027.42/94558/1/39015087418698.pd

Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms

Background: Data generated using ‘omics’ technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of subjects in the study. In this paper, we consider issues relevant in the design of biomedical studies in which the goal is the discovery of a subset of features and an associated algorithm that can predict a binary outcome, such as disease status. We compare the performance of four commonly used classifiers (K-Nearest Neighbors, Prediction Analysis for Microarrays, Random Forests and Support Vector Machines) in high-dimensionality data settings. We evaluate the effects of varying levels of signal-to-noise ratio in the dataset, imbalance in class distribution and choice of metric for quantifying performance of the classifier. To guide study design, we present a summary of the key characteristics of ‘omics’ data profiled in several human or animal model experiments utilizing high-content mass spectrometry and multiplexed immunoassay based techniques. Results: The analysis of data from seven ‘omics’ studies revealed that the average magnitude of effect size observed in human studies was markedly lower when compared to that in animal studies. The data measured in human studies were characterized by higher biological variation and the presence of outliers. The results from simulation studies indicated that the classifier Prediction Analysis for Microarrays (PAM) had the highest power when the class conditional feature distributions were Gaussian and outcome distributions were balanced. Random Forests was optimal when feature distributions were skewed and when class distributions were unbalanced. We provide a free open-source R statistical software library (MVpower) that implements the simulation strategy proposed in this paper. Conclusion: No single classifier had optimal performance under all settings. Simulation studies provide useful guidance for the design of biomedical studies involving high-dimensionality data

Utilization of crab shell-derived chitosan in nanoparticle synthesis for curcumin delivery

1183-1188Chitosan derived from crustaceans is biodegradable as well as biocompatible and can be made into nanoparticles when chelated with chelators, such as sodium tripolyphosphate and barium chloride. In this study, crab shells-derived chitosan was chelated using sodium trimetaphosphate to form nanoparticles. Curcumin was encapsulated into nanoparticles and characterized using Fourier transform infra-red spectroscopy, scanning electron microscopy, atomic force microscopy, and X-ray diffraction analysis. The particles were found to be 18 nm in size, while the curcumin-loaded particles were 25 nm in size. The particles were observed to encapsulate 90% of the drug used. The nanoparticles produced were analyzed for in vitro controlled drug release against Pseudomonas aeruginosa, Bacillus subtilis, and Candida albicans.</em

An Optimal Multi-System Control Measure Using the Approach of Conjugate Gradient Algorithm (CGA)

In this paper we examine the application of the classical conjugate gradient method to queue theory. The parameters of the symmetric definite positive linear operator of a quadratic cost functional were obtained from the various characteristic features of a multi-channel queue system. The outcome was tested with numerical values and a comparison was made for systems with two, three and four service points. The numerical computations were carried out in a Maple 14 environment. The results obtained validate previous work done with a singlechannel syste

Void Aware Position Based Opportunistic Routing for QoS in Mobile Ad Hoc Networks

Abstract The unique anywhere, anytime wireless communication support offers, tremendous potential for the next generation of applications in a Mobile Ad-hoc Network (MANET). The Quality of Service (QoS) has been the ever demanding task of wireless communication to satisfy the application requirements. Geographical routing employs a greedy forwarding technique to deliver the packets to the destination and to owe the communication void, it fails to render the expected level of QoS. Opportunistic routing technique effectively utilizes the advantages of broadcasting nature of the wireless medium and selects a set of forwarding candidates instead of relying on a greedy node. To improve the efficiency of QoS routing in sparse and highly dynamic network topology, this paper proposes the Void-Aware Position based Opportunistic Routing (VAPOR). The VAPOR maintains 2-hop neighbor information to take a routing decision, but it is limited to 1-hop information when the node density is high. It efficiently balances the storage overhead and communication delay due to void and it increases the network throughput even under a sparse network. To provide a certain assurance level for packet reachability, VAPOR decides the potential forwarders based on the forwarding probability that measures link stability, capacity, and connectivity factor. It adaptively favors a path that avoids frequent link failure and unreliable link usage. By limiting the propagation area of duplicate packets, VAPOR reduces wastage of network resources, and it takes the advantage of concurrent batch forwarding to avoid further duplication and unnecessary delay

Mechanical Properties of Cold-Drawn Low Carbon Steel for Nail Manufacture: Experimental Observation

Abstract: The objective of this study is to investigate the influence of service situation on the mechanical properties of plain nails manufactured from low carbon steel. The influence of the degree of cold drawing on the mechanical properties and strain hardening of the material is investigated by tensile test experimentation. The stress-strain relationships of the cold-drawn low carbon steel were investigated over the 20, 25, 40 and 55% degree of drawn deformation for the manufacture of 4, 3, 2½ and 2 inches nails, respectively. The true stress-strain curves were analyzed to obtain the yield strength and tensile strength of the cold drawn steel. It is shown that the yield strength, tensile strength, hardness and toughness of the low carbon steel reduce with increasing degree of cold-drawn deformation. The micrographs of the deformed samples obtained using optical microscope shows that the grain structure elongates in the direction of the drawing operation and misorientation of the grains set in at 40 and 55% degree of deformation. The difference in yield strength was attributed to the strain hardening, resulting from the different degrees of drawn deformation

Performance Comparison Between HMLP, MLP And Recurrent Networks With Applications To Carbon Monoxide Concentrations Forecasting.

This paper compares the performance of Hybrid Multilayered Perceptron (HMLP) network, Multilayered Perceptron (MLP) network and Recurrent network. These networks are used to model and forecast carbon monoxide (CO) concentration

Subjective logic based trust model for geographic routing in mobile ad hoc networks

Uobičajeni modeli pouzdanosti ne uspijevaju izraziti pojam nesigurnosti tijekom uspostavljanja pouzdanih odnosa između pokretnih čvorova. Nadalje, nedostaje im uvažavanje značajki okoline u ocjeni pouzdanosti. U radu se predlaže model pouzdanosti zasnovan na subjektivnoj logici u POR (SLT-POR) koji u modelu integrira pouzdanost zasnovanu na kontekstu i onu zasnovanu na ponašanju. Pouzdanost zasnovana na ponašanju uključuje fuziju evidencije zasnovane na subjektivnoj logici u evaluaciji indirektne pouzdanosti kako bi se eksplicitno predstavilo i upravljalo neznanjem kao nesigurnošću. Odnos pouzdanosti između čvorova ne može uvijek odražavati stvarni odnos te stoga provedena odluka iz izvedenog odnosa pouzdanosti nije uvijek točna. Teorija subjektivne logike uključuje dinamičkog operatora osnovne brzine koji procjenjuje očekivanje mišljenja i bavi se nesigurnošću u skupljanju podataka. U mjerenju pouzdanost zasnovane na obilježjima konteksta, SLT-POR procjenjuje vrijednost pouzdanosti zasnovane na kontekstu uporabom kontekstualnih obilježja svakog čvora u nizu pozitivnog pouzdanog djelovanja. SLT-POR u procjeni pouzdanosti pazi da snaga baterije uključuje vijek trajanja čvora, pridaje važnost pouzdanosti zasnovanoj na kontekstu kao i onoj zasnovanoj na ponašanju kako bi učinkovito izračunao ukupnu pouzdanost čvora. Rezultati simulacije pokazuju da je omjer isporuke paketa predloženog SLT-POR visok, čak i ako je 50 % svih čvorova maliciozno te da je bolji od sustava CAST - Context-Aware Security and Trust.In the past decades, several trust models have been proposed to enhance the security of Mobile Ad hoc Networks (MANETs). The conventional trust models fail to express the notion of uncertainty during the establishment of trust relationships between mobile nodes. Furthermore, they lack in considering the context attributes in trust evaluation. This paper proposes a subjective logic based trust model in POR (SLT-POR) that integrates both the behavioural and context based trust in trust model. The behavioural based trust incorporates subjective logic based evidence fusion in indirect trust evaluation to explicitly represent and manage ignorance as uncertainty. The trust relationship between nodes cannot always reflect the actual relationship and consequently the executed decision from the extracted trust relationship is not always accurate. The subjective logic theory includes a dynamic base rate operator that evaluates an expectation of an opinion and handles the uncertainty in evidence collection. In context, attributes based trust measurement, the SLT-POR estimates a context based trust value using the contextual attributes of each node in the trusted positive progress set. The SLT-POR considers the battery power to include node’s lifetime in the trustworthiness estimation. It assigns a weight for both behaviour and context based trust to efficiently calculate total trustworthiness of a node. The simulation results demonstrate that the packet delivery ratio of the proposed SLT-POR is high even if 50 % of total nodes are malicious and outperforms Context-Aware Security and Trust (CAST) framework

Report on widespread occurrence of colonial epizoan ascidian Didemnum sp. in the seagrass beds of Gulf of Mannar

The seagrass beds of Gulf of Mannar are one of the major habitats of the Sea cow Dugong dugon. This species is a herbivore that has become more vulnerable in the recent decades caused by habitat degradation due to anthropogenic activities. Ecologically, seagrass beds play several roles such as primary producers, food for herbivores, trapping sediments, preventing erosion and providing shelter for juvenile fishes. Seagrasses also serve as a substrate for fouling organisms, usually epiphytes such as barnacles, polychaetes, ascidians etc