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%)

Effectiveness of tramadol/paracetamol compared with etoricoxib as postoperative analgesia in daycare surgery

Objective: The objective was to evaluate the effectiveness of a fixed, tramadol/paracetamol combination when compared with etoricoxib as postoperative analgesia following day care surgery.Design: This was a prospective, randomised, single-blind study.Setting and subjects: Sixty-two patients were randomised to receive either etoricoxib (n = 29) or tramadol/paracetamol (n = 33) by mouth prior to surgery. Patients were given general anaesthesia with fentanyl for intraoperative and rescue analgesia.Outcome measures: The primary efficacy variables that were investigated were total pain relief and sum of pain intensity differences at 1, 2, 3, 4, 6, 24 and 48 hours. Data were collected by an independent observer through an interview or by telephone after discharge.Results: Total pain relief (p-value 0.001) was significantly different between the two groups for the first four hours. The total dose of fentanyl use was comparable between the two groups. There was also a significant difference in the occurrence of nausea with tramadol/paracetamol (p-value 0.001), and dizziness with etoricoxib (p-value 0.024).Conclusion: Tramadol/paracetamol provided significantly better pain relief than etoricoxib in the early postoperative period.Keywords: daycare surgery, etoricoxib, paracetamol, postoperative analgesia, tramado

Modal analysis of multistage gear systems coupled with gearbox vibrations

An analytical procedure to simulate vibrations in gear transmission systems is presented. This procedure couples the dynamics of the rotor-bearing gear system with the vibration in the gear box structure. The model synthesis method is used in solving the overall dynamics of the system, and a variable time-stepping integration scheme is used in evaluating the global transient vibration of the system. Locally each gear stage is modeled as a multimass rotor-bearing system using a discrete model. The modal characteristics are calculated using the matrix-transfer technique. The gearbox structure is represented by a finite element models, and modal parameters are solved by using NASTRAN. The rotor-gear stages are coupled through nonlinear compliance in the gear mesh while the gearbox structure is coupled through the bearing supports of the rotor system. Transient and steady state vibrations of the coupled system are examined in both time and frequency domains. A typical three-geared system is used as an example for demonstration of the developed procedure

Study on PZT4/VF₂/VF₃ piezoelectric 0-3 composites

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Thermal hysteresis in the permittivity and polarization of lead zirconate titanate/vinylidenefloride-trifluoroethylene 0-3 composites

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Properties of nanocrystalline PT powder and PT/P(VDF-TrFE) 0-3 nanocomposites

Author name used in this publication: Y. ChenAuthor name used in this publication: H. L. W. ChanAuthor name used in this publication: C. L. ChoyVersion of RecordPublishe

3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks

Standard 3D convolution operations require much larger amounts of memory and computation cost than 2D convolution operations. The fact has hindered the development of deep neural nets in many 3D vision tasks. In this paper, we investigate the possibility of applying depthwise separable convolutions in 3D scenario and introduce the use of 3D depthwise convolution. A 3D depthwise convolution splits a single standard 3D convolution into two separate steps, which would drastically reduce the number of parameters in 3D convolutions with more than one order of magnitude. We experiment with 3D depthwise convolution on popular CNN architectures and also compare it with a similar structure called pseudo-3D convolution. The results demonstrate that, with 3D depthwise convolutions, 3D vision tasks like classification and reconstruction can be carried out with more light-weighted neural networks while still delivering comparable performances.Comment: Work in progres

Effect of target material on the laser induced pressure pulse measurements for thick P(VDF-TrFE) copolymers

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Nanoparticle-induced resonant tunneling behaviors in small molecule organic light-emitting devices

We report a hybrid nanoparticle/organic device with strong resonant tunneling behavior by introducing ligand-capped Ag nanoparticles between indium tin oxide and hole transport layer in small molecule organic light-emitting devices. The dependences of resonant tunneling current on the thickness of the organic layers are investigated. For the optimized device, a peak-to-valley current ratio as high as 4.5 and narrow peak width about 1.8 V are obtained. Combining with the analysis of current-voltage behavior, the mechanism based on the charge trapping effect of Ag nanoparticles is proposed to interpret the operation of the hybrid device. Finally, the emission characteristics of hybrid devices are also studied. © 2009 American Institute of Physics.published_or_final_versio