A new explicit method for the diffusion-convention equation

AbstractWe consider here the finite difference approximation to the diffusion-convection equation, from which new explicit formulation are obtained which are asymmetric. These explicit schemes can then be used to develop a new class of methods called Group Explicit as introduced in [2].Theoretical aspects of the stability, consistency, convergence and truncation errors of this new class of methods is briefly discussed and numerical evidence presented to confirm our recomendations

Voltage Variation Analysis by Using Gabor Transform

Voltage variations which include voltage sag, swell and interruption are simulated and analyzed in this paper. Various types of parametric equation are generated with the help of MATLAB software. Simulated signals are studies by using time-frequency distribution (TFD) technique. The TFD method used in this paper is the Gabor transform which is less applied by the researchers. The signal parameters used in this paper are the RMS voltage and instantaneous power can be extracted from the TFR to study the distinctives of the voltage variations. The parameters extracted can detect the voltage variation signals successfully. The voltage variation signals are successfully detected by using the K-Nearest Neighbors (kNN) algorithm with the implementation of signal parameters extracted as the input on the classifier. The voltage variations waveforms as well as the signal parameters obtained are suitable to be further analyzed

A Utilisation of Improved Gabor Transform for Harmonic Signals Detection and Classification Analysis

This paper presents a utilization of improved Gabor transform for harmonic signals detection and classification analysis in power distribution system.  The Gabor transform is one of time frequency distribution technique with a capability of representing signals in jointly time-frequency domain and known as time frequency representation (TFR). The estimation of spectral information can be obtained from TFR in order to identify the characteristics of the signals. The detection and classification of harmonic signals for 100 unique signals with numerous characteristic of harmonics with support of rule-based classifier and threshold setting that been referred to IEEE standard 1159 2009. The accuracy of proposed method is determined by using MAPE and the outcome demonstrate that the method gives high accuracy of harmonic signals classification. Additionally, Gabor transform also gives 100 percent correct classification of harmonic signals. It is verified that the proposed method is accurate and cost efficient in detecting and classifying harmonic signals in distribution system

Reduction of Limb Position Invariant of SEMG Signals for Improved Prosthetic Control using Spectrogram

Prostheses are artificial devices that replace a missing body part, which might be lost through injury, infection, or a condition present at birth. It is proposed to re-establish the normal functions of the missing body part and can be made by hand or with a computer-aided design. As per the World Health Organization, around 160,000 individuals in Malaysia are required to use prostheses. One of the elements that influence the current prosthesis control is that the variety in the limb position and normal use results in different electromyogram (EMG) signals with the same movement at various positions. Consequently, the objective of this study is to ensure that amputees can control their prosthetics in an exact manner regardless of their hand movement and limb position. The raw EMG signals are taken from eight different hand movements’ classes at five different limb positions and each of these hand movements has seven electrodes attach to it. This paper utilizes time-frequency distribution which is spectrogram to extract the EMG feature and six SVM classification learners; linear, quadratic, cubic, fine Gaussian, medium Gaussian, and coarse Gaussian were compared to find the most reasonable one for this application. The analysis performance is then verified based on classification accuracy. From the results, the overall accuracy for the classification is 65% (linear), 87.5% (quadratic) and 97.5% (cubic), 100% (fine Gaussian), 70% (medium Gaussian, and 45% (coarse Gaussian), respectively. It is believed that the study could fill in as knowledge to improve conventional prosthetic control strategies

Determining Best Window Size for an Improved Gabor Transform in EMG Signal Analysis

Electromyography EMG is a standout amongst the most regularly utilized tools to study human muscle condition. But due to the intricate attributes of the EMG itself, time-frequency distributions such as Gabor transform and spectrogram are more preferred than the simpler time distribution and frequency distribution. These techniques have been broadly utilized as it can provide both time and frequency information. However, both techniques have a fix window size for all frequency values, thus there exist a problem of determination of the window size, where excessively limit window and too wide window, will result in poor frequency resolution and time resolution, respectively. Along these lines, the point of this study is to choose the best window size so as to be utilized with Gabor transform to screen human muscle activity during core-lifting task. Four electrodes were placed on the right and left biceps brachii, and left and right erector spinae. In this study, the results of five acceptable window sizes (300, 400, 430, 450 and 520) were shown, despite the fact that other window sizes were also tested. Three criteria have been considered during the determination of the best window size, which are good time resolution, good frequency resolution, and high accuracy. Results demonstrate that window size of 450 is the best compared to others. As an additional analysis, the result is compared to a spectrogram and it can be seen that Gabor transform is better, as it has the flexibility in choosing the window size, thus affects the resolution and accuracy

Frequency Index for Learning Space in Higher Education Institutions

AbstractThe aim of this study is to measure the learning space usage rate based on the teaching and learning schedule (timetable) provided by the institutions. The Frequency Index of learning space is developed by analyzing the timetable data and the list of learning spaces available at the institution. The Frequency Index is classified according to the level of usage and the interval percentage according to learning space usage frequency. This classification of Frequency Index is expressed in terms of linguistic value and the color-coded key. From this index, the institution can identify whether the existing learning space is best used or vice versa, which in turn can be a reasonable basis for the institution in need of new learning space

Population Genetics of the Cave-dwelling Dusky Fruit Bat, Penthetor lucasi, Based on Four Populations in Malaysia

The population genetics of P. lucasi was inferred using 1,061 base pairs (bp) of the Cytochrome b mitochondrial gene. A total of 77 individuals were classified a priori according to their localities, namely, Miri, Kuching, Sri Aman and Kelantan. Results showed that the populations of P. lucasi were separated into two haplogroups, namely, Haplogroup 1 (found in Miri and Kuching populations) and Haplogroup 2 (Miri, Kuching, Sri Aman and Kelantan populations). This separation was supported by bootstrap values in the phylogenetics analyses (94.9% in the maximum likelihood and 100% in Bayesian). A high level of genetic divergence was detected between two haplogroups (3.88%) and this separation could be related to historical events which include multiple colonisation and Pleistocene refugia during the Last Glacial Maximum ice age period. High genetic divergence within Miri (4.93%) and Kuching (4.72%) populations could be due to the presence of a species complex within the P. lucasi populations. The presence of haplotypes from both the populations in Haplogroup 1 and Haplogroup 2 might be due to the ability of this particular species of bats to perform long-distance flight for foraging. A high gene flow between these populations suggests a widespread female gene flow of P. lucasi, judging from the distance of both localities. Meanwhile, the absence of a deep structure from the haplotype trees further proves that P. lucasi may have had wide dispersal ability since the Pleistocene has allowed for genetic exchange to occur between the regions in Malaysia

Spectrogram Based Window Selection for the Detection of Voltage Variation

This paper presents the application of spectrogram with K-nearest neighbors (KNN) and Support Vector Machine (SVM) for window selection and voltage variation classification. The voltage variation signals such as voltage sag, swell and interruption are simulated in Matlab and analyzed in spectrogram with different windows which are 256, 512 and 1024. The variations analyzed by spectrogram are displayed in time-frequency representation (TFR) and voltage per unit (PU) graphs. The parameters are calculated from the TFR obtained and be used as inputs for KNN and SVM classifiers. The signals obtained are then added with noise (0SNR and 20SNR) and used in classification. The tested data contain voltage variation signals obtained using the mathematical models simulated in Matlab and the signals added with noise. Classification accuracy of each window by each classifier is obtained and compared along with the TFR and voltage PU graphs to select the best window to be used to analyze the best window to be used to analyze the voltage variation signals in spectrogram. The results showed window 1024 is more suitable to be used