Performance Based Grouping of Neighbors Students in Progressive Education Datasets

Now a day’s the educational organizations are facing the biggest challenges, of the massive growth of educational data. Further they do not have a good policy and to use this data for improving the quality of their managerial decisions in today’s scenario. The main goal of higher education institutions is to provide quality of education for their students. In general the educational database contains the important information for predicting a student’s performance, and this Prediction of student’s performance in educational environments is of utmost importance. The knowledge mining techniques has provided a decision making tool which can facilitate better resource utilization in terms of students performance. The knowledge mining techniques are more helpful in classifying educational database. In this paper the clustering task is used to assess student’s performance from education databases. By using this task we extract the knowledge that can describes students’ performance in end semester examination. Keywords – Educational datasets, knowledge mining, Decision Making, Data Classification, Performance Prediction

A Comprehensive Review of Recent Variants and Modifications of Firefly Algorithm

Swarm intelligence (SI) is an emerging field of biologically-inspired artificial intelligence based on the behavioral models of social insects such as ants, bees, wasps, termites etc. Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. Most SI algorithms have been developed to address stationary optimization problems and hence, they can converge on the (near-) optimum solution efficiently. However, many real-world problems have a dynamic environment that changes over time. In the last two decades, there has been a growing interest of addressing Dynamic Optimization Problems using SI algorithms due to their adaptation capabilities. This paper presents a broad review on two SI algorithms: 1) Firefly Algorithm (FA) 2) Flower Pollination Algorithm (FPA). FA is inspired from bioluminescence characteristic of fireflies. FPA is inspired from the the pollination behavior of flowering plants. This article aims to give a detailed analysis of different variants of FA and FPA developed by parameter adaptations, modification, hybridization as on date. This paper also addresses the applications of these algorithms in various fields. In addition, literatures found that most of the cases that used FA and FPA technique have outperformed compare to other metaheuristic algorithms

Bio-Based PLA Membranes for Ion Transport and Ion Filtration

Lithium-ion batteries require battery separators for both safety and electrochemical performance. Due to that, they have received a lot of attention. In order to prevent any electronic current from moving within the negative and positive electrodes and allow ions to flow through while avoidance of electric contact between them, a porous membrane used as a separator is positioned between the electrodes with opposing polarities. Accordingly, the objective of the present work is to build a biodegradable PLA based battery separator, which has exceptional thermal capabilities and can endure temperatures of up to 300°C. They also seem to serve as the least degree of barrier for the flow of an ionic current. In this study bio-polymer battery separator membranes were developed using PLA as matrix material and fillers such as Copper slag (CS) and Cardanol resin (CNSL). CS and CNSL were preferred for the reason to realize the concept of a wealth reclaimed from wastes that act as toughening and pore forming agent for PLA matrix. It is found that at PLA-CS film has more brittleness when compared to neat PLA and PLA-CNSL resin. On the other hand, PLA-CNSL films are the toughest ones. Overall, it has been demonstrated that obtaining more sustainable and high-performance is possible by the usage of such sustainable materials for futuristic developments

Peak Stir Zone Temperatures during Friction Stir Processing

The stir zone (SZ) temperature cycle was measured during the friction stir processing (FSP) of NiAl bronze plates. The FSP was conducted using a tool design with a smooth concave shoulder and a 12.7-mm step-spiral pin. Temperature sensing was accomplished using sheathed thermocouples embedded in the tool path within the plates, while simultaneous optical pyrometry measurements of surface temperatures were also obtained. Peak SZ temperatures were 990 ⁰Cto 1015 ⁰C (0.90 to 0.97 TMelt) and were not affected by preheating to 400⁰C, although the dwell time above 900 ⁰C was increased by the preheating. Thermocouple data suggested little variation in peak temperature across the SZ, although thermocouples initially located on the advancing sides and at the centerlines of the tool traverses were displaced to the retreating sides, precluding direct assessment of the temperature variation across the SZ. Microstructure-based estimates of local peak SZ temperatures have been made on these and on other similarly processed materials. Altogether, the peak-temperature determinations from these different measurement techniques are in close agreement

Study of dielectron production in C+C collisions at 1 AGeV

The emission of e+e- pairs from C+C collisions at an incident energy of 1 GeV per nucleon has been investigated. The measured production probabilities, spanning from the pi0-Dalitz to the rho/omega! invariant-mass region, display a strong excess above the cocktail of standard hadronic sources. The bombarding-energy dependence of this excess is found to scale like pion production, rather than like eta production. The data are in good agreement with results obtained in the former DLS experiment.Comment: submitted to Physics Letters

System Size and Energy Dependence of Jet-Induced Hadron Pair Correlation Shapes in Cu+Cu and Au+Au Collisions at sqrt(s_NN) = 200 and 62.4 GeV

We present azimuthal angle correlations of intermediate transverse momentum (1-4 GeV/c) hadrons from {dijets} in Cu+Cu and Au+Au collisions at sqrt(s_NN) = 62.4 and 200 GeV. The away-side dijet induced azimuthal correlation is broadened, non-Gaussian, and peaked away from \Delta\phi=\pi in central and semi-central collisions in all the systems. The broadening and peak location are found to depend upon the number of participants in the collision, but not on the collision energy or beam nuclei. These results are consistent with sound or shock wave models, but pose challenges to Cherenkov gluon radiation models.Comment: 464 authors from 60 institutions, 6 pages, 3 figures, 2 tables. Submitted to Physical Review Letters. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm