Electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Universiti Tun Hussein Onn Malaysia (UTHM) is a developing Malaysian Technical University. There is a great development of UTHM since its formation in 1993. Therefore, it is crucial to have accurate future electricity consumption forecasting for its future energy management and saving. Even though there are previous works of electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS), but most of their data are multivariate data. In this study, we have only univariate data of UTHM electricity consumption from January 2009 to December 2018 and wish to forecast 2019 consumption. The univariate data was converted to multivariate and ANFIS was chosen as it carries both advantages of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS). ANFIS yields the MAPE between actual and predicted electricity consumption of 0.4002% which is relatively low if compared to previous works of UTHM electricity forecasting using time series model (11.14%), and first-order fuzzy time series (5.74%), and multiple linear regression (10.62%)

Structural, optical, magnetic and electrical properties of Zn1-x Co (x) O thin films

Despite a considerable effort aiming at elucidating the nature of ferromagnetism in ZnO-based magnetic semiconductor, its origin still remains debatable. Although the observation of above room temperature ferromagnetism has been reported frequently in the literature by magnetometry measurement, so far there has been no report on correlated ferromagnetism in magnetic, optical and electrical measurements. In this paper, we investigate systematically the structural, optical, magnetic and electrical properties of Zn1-x Co (x) O:Al thin films prepared by sputtering with x ranging from 0 to 0.33. We show that correlated ferromagnetism is present only in samples with x > 0.25. In contrast, samples with x < 0.2 exhibit weak ferromagnetism only in magnetometry measurement which is absent in optical and electrical measurements. We demonstrate, by systematic electrical transport studies that carrier localization indeed occurs below 20-50 K for samples with x < 0.2; however, this does not lead to the formation of ferromagnetic phase in these samples with an electron concentration in the range of 6 x 10(19) cm(-3) 1 x 10(20) cm(-3). Detailed structural and optical transmission spectroscopy analyses revealed that the anomalous Hall effect observed in samples with x > 0.25 is due to the formation of secondary phases and Co clusters.Comment: 28 pages, 8 figure

Opinion diversity and community formation in adaptive networks

It is interesting and of significant importance to investigate how network structures co-evolve with opinions. The existing models of such co-evolution typically lead to the final states where network nodes either reach a global consensus or break into separated communities, each of which holding its own community consensus. Such results, however, can hardly explain the richness of real-life observations that opinions are always diversified with no global or even community consensus, and people seldom, if not never, totally cut off themselves from dissenters. In this article, we show that, a simple model integrating consensus formation, link rewiring and opinion change allows complex system dynamics to emerge, driving the system into a dynamic equilibrium with co-existence of diversified opinions. Specifically, similar opinion holders may form into communities yet with no strict community consensus; and rather than being separated into disconnected communities, different communities remain to be interconnected by non-trivial proportion of inter-community links. More importantly, we show that the complex dynamics may lead to different numbers of communities at steady state with a given tolerance between different opinion holders. We construct a framework for theoretically analyzing the co-evolution process. Theoretical analysis and extensive simulation results reveal some useful insights into the complex co-evolution process, including the formation of dynamic equilibrium, the phase transition between different steady states with different numbers of communities, and the dynamics between opinion distribution and network modularity, etc.Comment: 12 pages, 8 figures, Journa

Dominant Eigenvalue-Eigenvector Pair Estimation via Graph Infection

We present a novel method to estimate the dominant eigenvalue and eigenvector pair of any non-negative real matrix via graph infection. The key idea in our technique lies in approximating the solution to the first-order matrix ordinary differential equation (ODE) with the Euler method. Graphs, which can be weighted, directed, and with loops, are first converted to its adjacency matrix A. Then by a naive infection model for graphs, we establish the corresponding first-order matrix ODE, through which A's dominant eigenvalue is revealed by the fastest growing term. When there are multiple dominant eigenvalues of the same magnitude, the classical power iteration method can fail. In contrast, our method can converge to the dominant eigenvalue even when same-magnitude counterparts exist, be it complex or opposite in sign. We conduct several experiments comparing the convergence between our method and power iteration. Our results show clear advantages over power iteration for tree graphs, bipartite graphs, directed graphs with periods, and Markov chains with spider-traps. To our knowledge, this is the first work that estimates dominant eigenvalue and eigenvector pair from the perspective of a dynamical system and matrix ODE. We believe our method can be adopted as an alternative to power iteration, especially for graphs.Comment: 13 pages, 8 figures, 3 table

Pulse-delay light cure on marginal adaptation of compomer

published_or_final_versio

The Learner’s Engagement in the Learning Process designed based on the Experiential Learning theory in Post Graduate Program at Open University Malaysia

The purpose of this study was to: 1. observe the level of engagement in a learning process in ‘grasp experience’ and ‘transform experience’ section. 2. evaluate the level of engagement in an online forum between ‘grasp experience’ and ‘transform experience’ section. 3. clarify the level of engagement through the posting in an online forum, which reflects the actual ‘experience.

Nanoscale technologies: nano-knitting, healing powers and hemostasis

Session 2 - Nanotechnology / Vision Restoration: Clinical Usespostprin

Nanoparticles in optic nerve trauma: nanoscaffolding, visualization and regeneration

Session 1 - Nanotechnology / Vision Restoration: Concepts, Possibilities, Challengespostprin