Pearson coefficient matrix for studying the correlation of community detection scores in multi-objective evolutionary algorithm

Assessing a community detection algorithm is a difficult task due to the absence of finding a standard definition for objective functions to accurately identify the structure of communities in complex networks. Traditional methods generally consider the detecting of community structure as a single objective issue while its optimization generally leads to restrict the solution to a specific property in the community structure. In the last decade, new community detection models have been developed. These are based on multi-objective formulation for the problem, while ensuring that more than one objective (normally two) can be simultaneously optimized to generate a set of non-dominated solutions. However the issue of which objectives should be co-optimized to enhance the efficiency of the algorithm is still an open area of research. In this paper, first we generate a candidate set of partitions by saving the last population that has been generated using single objective evolutionary algorithm (SOEA) and random partitions based on the true partition for a given complex network. We investigate the features of the structure of communities which found by fifteen existing objectives that have been used in literature for discovering communities. Then, we found the correlation between any two objectives using the pearson coefficient matrix. Extensive experiments on four real networks show that some objective functions have a strong correlation and others either neutral or weak correlations

Mathematical simulation of memristive for classification in machine learning

Over the last few years, neuromorphic computation has been a widely researched topic. One of the neuromorphic computation elements is the memristor. The memristor is a high density, analogue memory storage, and compliance with Ohm's law for minor potential changes. Memristive behaviour imitates synaptic behaviour. It is a nanotechnology that can reduce power consumption, improve synaptic modeling, and reduce data transmission processes. The purpose of this paper is to investigate a customized mathematical model for machine learning algorithms. This model uses a computing paradigm that differs from standard Von-Neumann architectures, and it has the potential to reduce power consumption and increasing performance while doing specialized jobs when compared to regular computers. Classification is one of the most interesting fields in machine learning to classify features patterns by using a specific algorithm. In this study, a classifier based memristive is used with an adaptive spike encoder for input data. We run this algorithm based on Anti-Hebbian and Hebbian learning rules. These investigations employed two of datasets, including breast cancer Wisconsin and Gaussian mixture model datasets. The results indicate that the performance of our algorithm that has been used based on memristive is reasonably close to the optimal solution

Evaluation of Surface hardness of Denture Base Acrylic Resin Modified with Different Techniques

Aims: Evaluation of the surface hardness of heat-treated acrylic resin after modifying it with three different techniques. Materials and Methods: Heat cured acrylic resin was modified by: (a) The copolymerization of acrylic resin with 5% and 10% of acrylic acid (AA), (b) The addition of 5% and 10% thermally activated zinc oxide (ZnO) and (c) The chemical bonding or engagement of Zinc ions into the polymer chain by an organic link, zinc diacrylate (ZDA) in 5% and 10%, to get a copolymer. The acrylic specimens have dimensions of (30, 15 and 3) ± 0.2 mm. Surface hardness was determined using a Durometer (Shore D) hardness tester. Results: There was general increase of the surface hardness of the experimental (modified) groups. A statical significant increase in the hardness of both acrylic groups modified by 10% ZnO and 10% ZDA compared to the control group and the remaining modified samples. Conclusion: Two techniques had significantly improved the hardness of heat cured acrylic resin; either by adding 10% by weight of thermally activated ZnO or by copolymerizing it with 10% by weight of ZDA to get poly (methyl methacrylate -co-zinc acrylate) copolymer

Modeling of Neuropathic Bladder Lesions Diagnosis Using Neural Network Algorithm.

The urinary bladder is probably the only visceral smooth-muscle organ that is under complete voluntary control from the cerebral cortex. Normal bladder function requires interaction of sensory and motor components of both the somatic and autonomic nervous system. Recent advances in the understanding of neural pathways and neurotransmitters have shown that most levels of the nervous system are involved in the regulation of voiding function. Therefore many neuralgic diseases causes changes in the bladder function [1]. In this paper, Number of patients selected from Ibn-Alkiff hospital (for treatment and rehabilitation of Spinal cord injuries), in Baghdad, who were referred to the urology department for complains of some urinary symptoms, and examined by cystometry in the urology out patient and/or inpatient department. These cases were selected randomly who already consult these departments and were followed up and managed by the expert urosurgeons. They were adults complaining of general neuropathic bladder disorder symptoms like frequency, urgency, dysuria, urinary incontinence and were diagnosed as having neuropathic bladder disease, whether: Upper motor neuropathic bladder lesions. Lower motor neuropathic bladder lesions. And finally they were examined by cystometry. The collections of data from patients were about: Accommodation (compliance). • Bladder capacity. • Contractility. • Sensation. • Voluntary control. These data with the final definition diagnosis about the neuropathic bladder lesion were processed to 3- layers Neural Network algorithm that was constructed in a matlab computer package. Consequently after all data processing, the neural network model was tested by its capability of processing an already diagnosed neuropathic bladder case and its accuracy in explaining the real neurological bladder behavior of that selected patien

Delamination-and electromigration-related failures in solar panels—a review

The reliability of photovoltaic (PV) modules operating under various weather conditions attracts the manufacturer’s concern since several studies reveal a degradation rate higher than 0.8% per year for the silicon-based technology and reached up to 2.76% per year in a harsh climate. The lifetime of the PV modules is decreased because of numerous degradation modes. Electromigration and delamination are two failure modes that play a significant role in PV modules’ output power losses. The correlations of these two phenomena are not sufficiently explained and understood like other failures such as corrosion and potential-induced degradation. Therefore, in this review, we attempt to elaborate on the correlation and the influence of delamination and electromigration on PV module components such as metallization and organic materials to ensure the reliability of the PV modules. Moreover, the effects, causes, and the sites that tend to face these failures, particularly the silicon solar cells, are explained in detail. Elsewhere, the factors of aging vary as the temperature and humidity change from one country to another. Hence, accelerated tests and the standards used to perform the aging test for PV modules have been covered in this review

Transmission Control Protocol Performance Monitoring for Simulated Wired University Computer Network using OPNET

Computer networks need protocols to govern all transmission and presentation processes. The transmission control protocol (TCP) is one of the most important protocols that have the compatibility to work with all types of computer networks, overcoming all architectural and operating system differences. Nowadays, networks depend on the TCP protocol to control data flow between all types of connected computers, whether it is client or server, over any type of media whether it is wired or wireless networks, for all network topologies. A simulation of a university campus network has been conducted to determine TCP protocol features; those features are taken into consideration as one of the most important network parameters. In all digital networks, the data transmission is not a continuous transmission – instead, it is a discreet transmission, presenting itself as packets. These packets transfer and propagate within the network between computers, and network nodes using the TCP protocol depending on the address, which is embedded in its header. TCP has a great influence on the network speed. The network simulator OPNET provides an easy way of campus design, predicting, and estimating the performance of networks in a university campus environment. In this research, wiredconnections reach all computer network users at fixed points to maintain higher Mbps and ensure reliable communications between all the campus network nodes, as well as to increase the overall network performance taking into account the future expansions for the university campus network design

Evaluate the Shear Bond Strength for Alkasite in Comparison with other Esthetic Restorative Materials

Aims: To assess and compare the shear bond strength of alkasite restoration, as well as, to compare the shear bond strength between alkasite with and without bonding. Materials and methods: Twenty-five permanent maxillary premolars were used in which, with diamond disks, their buccal surfaces were flattened until a clear superficial dentinal surface could be seen. Samples were randomly assigned to five groups (n=5). Group 1: alkasite without adhesive, Group 2: alkasite with adhesive, Group 3: Nanohybrid composite, Group 4: Glass ionomer cement, and Group 5: Resin modified glass inomer cement. Following the recommendations of the manufacturers, cylinders of the five restorative materials were bonded to the buccal surfaces. Following 24 hours storage at 37°C. The evaluation of shear bond strength was employed by the use of the universal testing machine. Under a stereomicroscope (×20), the fracture mode was determined. Data were statistically analyzed using a nonparametric independent sample Kruskal-Wallis test at the confidence level of 95%. Result: There were statistical differences among groups and there was a significant difference between the alkasite with and without bonding. Conclusion: Alkasite with bonding showed a higher shear bond strength in comparison with GIC and resin-modified GIC, but still lower than that of nanohybrid composite Moreover, the shear bond strength of alkasite highly improved with the use of bonding

Performance analysis of MPI approaches and PThread in multi-core system

Comparison among the HPC techniques has been made in order to address the highest and lowest performance of each in terms of execution time, speedup and efficiency when it is used with the HPc multicore system. The matrix multiplication in a variant size is used as a common complex task to examine the performance of each approach. FSKTM server has been used as an HPC multicore system to perform the approaches and tasks. Based on the results, it shows that Hybrid MPI/OpenMP approach is the best in terms of execution time, speed up and efficiency than other approaches when the matrix size is very high (>1024×1024 size). Furthermore, the results show that the compiler version has a significant impact over the performance of Pthread. With a new compiler, the performance becomes much better due to the improvement in code translation

Anti-Search for the Glueball Candidate f_J(2220) in Two-Photon Interactions

Using 13.3 fb^{-1} of e^+e^- data recorded with the CLEO II and CLEO II.V detector configurations at CESR, we have searched for f_J(2220) decays to K^0_{S} K^0_{S} in untagged two-photon interactions. We report an upper limit on the product of the two-photon partial width and the branching fraction, Gamma_gamma gamma cdot B (f_J(2220) to K^0_{S} K^0_{S}) of less than 1.1 eV at the 95% C.L: systematic uncertainties are included. This dataset is four times larger than that used in the previous CLEO publication.Comment: 10 pages postscript, also available through http://w4.lns.cornell.edu/public/CLNS, Submitted to PRD (R