Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton

Performing heavy physical tasks, overhead work and long working hours are some examples of activities that can lead to musculoskeletal problems in humans. To overcome this issue, automated robots such as the upper-limb exoskeleton is used to assist humans while performing tasks. However, several concerns in developing the exoskeleton have been raised such as the control strategies used. In this study, a control strategy known as the extended de-weight fuzz was proposed to ensure that the exoskeleton could be maneuvered to the desired position with the least number of errors and minimum torque requirement. The extended de-weight fuzzy is a combination of the fuzzy-based PD and fuzzy-based de-weight controller systems. The extended de-weight fuzzy was then compared with the fuzzy-based PD and PID controllers, and the performances of these controllers were compared in terms of their deviations and required torques to perform tasks. The findings show that the proposed control strategy performs better than the fuzzy-based PD and PID controller systems

Wheeling Charges Methodology for Deregulated Electricity Markets using Tracing-based Postage Stamp Methods

MW-mile and Postage-stamp methods is traditionally used by electric utilities to determine a fixed transmission cost among users of firm transmission service. MW-Mile method is charging the users by determining the actual paths the power follows through the network. However, this method is not sufficient to recover the total transmission system cost. To recover the total transmission system cost, the Postage Stamp Method is adopted. This method is simple but its main drawback is that the charges paid by each user do not reflect the actual use of the network but based on the average usage of the entire network. This paper proposes a new wheeling charges methodology using tracing-based postage stamp methods. The proposed method allocates transmission costs among the generators proportional to the total power delivered to the load through transmission lines. The proposed method incorporates with generalised generation distribution factors to trace the contribution of each generator to the line flow. One unique feature of the proposed method is the consideration of the local load on the power flow allocation. Two case studies of 3-bus and IEEE 14-bus systems are used to illustrate the proposed method. Results show that the proposed method provides fair and equitable wheeling charges to generators reflecting the actual usage of the transmission system

Performance evaluation of m3 bottleneck based heuristic for M1M2M3 flow shop

This project investigates the possibility of developing scheduling heuristic using bottleneck approach for a three machine flow shop scheduling with the tendency of dominant machine at the first process. Due to the re-entrant and permutation nature of the process routing, the actual bottlenecks were identified as M3 and it utilized makespan algorithms to identify bottleneck categories. Using these conditions, a new bottleneck based heuristic which called BB is developed and tested using Macro Programming in Microsoft Excel. The main objective of this project is to evaluate the performance of M3 bottleneck-based heuristic for M1M2M3 flow shop problems. A total of 3000 simulations were conducted using randomly data in order to evaluate the accuracy of the heuristic. The heuristic performance was evaluated for six and ten job problems. The dominance level groups are divided into levels of weak, medium and strong dominance. For each job problem, the BB results were compared against the results of complete enumeration and lower bound analysis. The results suggested that BB heuristic is very effective in solving scheduling problems within the strong P3 dominance level range

Pareto Autonomous Local Search

This paper presents a study for the dynamic selection of operators in a local search process. The main purpose is to propose a generic autonomous local search method which manages operator selection from a set of available operators, built on neighborhood relations and neighbor selection functions, using the concept of Pareto dominance with respect to quality and diversity. The latter is measured using two different metrics. This control method is implemented using the Comet language in order to be easily introduced in various constraint local search algorithms. Focusing on permutation-based problems, experimental results are provided for the QAP and ATSP to assess the method’s effectiveness

Improvement on the innovational outlier detection procedure in a bilinear model

This paper considers the problem of outlier detection in bilinear time series data with special focus on BL(1,0,1,1) and BL(1,1,1,1) models. In the previous study, the formulations of effect of innovational outlier on the observations and residuals from the process had been developed and the corresponding least squares estimator of outlier effect had been derived. Consequently, an outlier detection procedure employing bootstrap-based procedure to estimate the variance of the estimator had been proposed. In this paper, we proposed to use the mean absolute deviance and trimmed mean formula to estimate the variance to improve the performances of the procedure. Via simulation, we showed that the procedure based on the trimmed mean formula has successfully improved the performance of the procedure

Air-conditioned university laboratories: Comparing CO2 measurement for centralized and split-unit systems

Universities are designed for higher education learning, and improving university indoor air quality (IAQ) is essential to the enhanced performances of students and staff members alike. The majority of IAQ problems are due to inadequate ventilation in university buildings. Carbon Dioxide (CO2) measurements have become a commonly used screening test of IAQ because measurement levels can be used to evaluate the amount of ventilation and general comfort. This paper examines CO2 field measurement for undergraduate practical classes. Ten air conditioned laboratories with ventilation were chosen for CO2 field measurement. CO2 was monitored under indoor and outdoor conditions. Indoor CO2 concentration for Laboratories 1 and 10 is observed to be higher than 1000 ppm which indicated inadequate ventilation, while other laboratories showed CO2 concentrations less than 1000 ppm. Air capacity and outdoor air were calculated based on the design documentation. A comparison between design and actual outdoor air/person values indicates that the air conditioning systems of the laboratories had adequate ventilation

NAIP-Deletion Analysis in Malaysian Patients with Spinal Muscular Atrophy

Spinal Muscular Atrophy (SMA) is an autosomal recessive disease, which ischaracterized by degeneration of the anterior horn cells of the spinal cord. SMA isclassified into 3 clinical subtypes, type I (severe), type II (intermediate), and type III(mild). Two genes, SMN1 and NAIP, have been identified as SMA-related genes. TheSMN1 gene is now recognized as a responsible gene for the disease because it is deletedor mutated in most SMA patients. However, the role of the NAIP gene in SMA has notbeen fully clarified. To clarify the contribution of NAIP to the disease severity of SMA,we studied the relationship between NAIP-deletion and clinical phenotype in Malaysianpatients. A total of 39 patients lacking SMN1 (12 type I, 19 type II, and 8 type IIIpatients) were enrolled into this study. Seven out of 12 patients with type I SMA(~60%) showed NAIP deletion. On the contrary, only 2 out of 20 type II patients andnone of type III patients showed NAIP deletion. There was a statistically significantdifference in NAIP-deletion frequency among the clinical subtypes (Fisher's exactprobability test, p value = 0.014). In conclusion, according to our data that NAIPdeletion was more frequent in type I SMA than in type II-III SMA, the NAIP gene maybe a modifying factor for disease severity of SMA

Factual approach for tropical forest parameters measurement and monitoring: future option with a focus on synergetic use of airborne and terrestrial LiDAR technologies

Forest biomass and carbon are critical for ecological monitoring, and yet poorly modelled in complex ecosystems such as the tropical rainforests. To overcome this challenge incurred due to the complex biophysical properties of tropical forests, Airborne and Terrestrial LiDAR (Light Detection and Ranging) technologies have been used combinedly. Airborne LiDAR data ‘from above’ are largely restricted to analyses of lower canopy layer trees. Its combination with Terrestrial LiDAR allows the assessment of tree crowns under the upper canopy layer, thus opening up new possibilities for a more complete assessment of all the trees in a multi-layer stand. In this study, Airborne LiDAR was used for upper canopy tree measurements while Terrestrial LiDAR was complimented for lower canopy layer trees. The result showed that LiDAR-based tree measurements of DBH and height were highly accurate. We highly improved the accuracy of estimated above-ground biomass (AGB)/carbon from 87% of Terrestrial and 90% of Airborne LiDAR-based estimates to 97% through combining the use of the two technologies. This approach contributes to the development of efficient techniques for forest monitoring systems and bears the potential to extend the modelling options from remote sensing data to understory layer trees. © 2021 Informa UK Limited, trading as Taylor & Francis Group