Journal articles: 'Higuchi's algorithm'

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PARAMANATHAN, P., and R. UTHAYAKUMAR. "SIZE MEASURE RELATIONSHIP METHOD FOR FRACTAL ANALYSIS OF SIGNALS." Fractals 16, no. 03 (September 2008): 235–41. http://dx.doi.org/10.1142/s0218348x08003995.

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The fractal dimension of signals represents a powerful tool for analyzing the irregular behavior and state of the dynamical systems. Analysis of waveforms has been used to identify and distinguish specific complex patterns. A variety of algorithms are available for the computation of fractal dimension of waveforms. In this paper we evaluate the performance of our algorithm based on size measure relationship method, quantifying the synthetic waveforms and electroencephalographic signals. Compared to Katz's, Higuchi's and Petrosian's algorithm advantages of this method include greater speed and not affected by noise. The computation time for the algorithm suggested in this paper is much less than the other methods.

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BAUMERT, MATHIAS, VICO BAIER, and ANDREAS VOSS. "LONG-TERM CORRELATIONS AND FRACTAL DIMENSION OF BEAT-TO-BEAT BLOOD PRESSURE DYNAMICS." Fluctuation and Noise Letters 05, no. 04 (December 2005): L549—L555. http://dx.doi.org/10.1142/s0219477505003002.

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Arterial blood pressure is modulated by several physiological regulatory processes. The analysis of beat-to-beat blood pressure dynamics provides information about cardiovascular control and patho-physiological conditions. In this paper we investigated the long-term correlations and fractal dimension of systolic blood pressure time series applying detrended fluctuation analysis (DFA) and Higuchi's algorithm (HFD). Thirty-minute blood pressure recordings in 25 patients with dilated cardiomyopathy (DCM) and 27 healthy controls (CON) were analyzed. The DFA and HFD revealed multifractal features in the blood pressure dynamics of CON as well as of DCM. At small scales, DFA and HFD of CON were significantly different from those of CON, reflecting patho-physiological changes. In conclusion, scaling analysis of blood pressure dynamics might lead to an enhanced assessment of autonomic cardiovascular control in patients with DCM.

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KALAUZI, A., S. SPASIC, M. CULIC, G. GRBIC, and L. J. MARTAC. "CONSECUTIVE DIFFERENCES AS A METHOD OF SIGNAL FRACTAL ANALYSIS." Fractals 13, no. 04 (December 2005): 283–92. http://dx.doi.org/10.1142/s0218348x05002933.

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We propose a new method for calculating fractal dimension (DF) of a signal y(t), based on coefficients [Formula: see text], mean absolute values of its nth order derivatives (consecutive finite differences for sampled signals). We found that logarithms of [Formula: see text], n = 2,3,…,n max , exhibited linear dependence on n: [Formula: see text] with stable slopes and Y-intercepts proportional to signal DF values. Using a family of Weierstrass functions, we established a link between Y-intercepts and signal fractal dimension: [Formula: see text] and calculated parameters A(n max ) and B(n max ) for n max = 3,…,7. Compared to Higuchi's algorithm, advantages of this method include greater speed and eliminating the need to choose value for k max , since the smallest error was obtained with n max = 3.

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Moldovanu, Simona, Felicia Anisoara Damian Michis, Keka C. Biswas, Anisia Culea-Florescu, and Luminita Moraru. "Skin Lesion Classification Based on Surface Fractal Dimensions and Statistical Color Cluster Features Using an Ensemble of Machine Learning Techniques." Cancers 13, no. 21 (October 20, 2021): 5256. http://dx.doi.org/10.3390/cancers13215256.

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(1) Background: An approach for skin cancer recognition and classification by implementation of a novel combination of features and two classifiers, as an auxiliary diagnostic method, is proposed. (2) Methods: The predictions are made by k-nearest neighbor with a 5-fold cross validation algorithm and a neural network model to assist dermatologists in the diagnosis of cancerous skin lesions. As a main contribution, this work proposes a descriptor that combines skin surface fractal dimension and relevant color area features for skin lesion classification purposes. The surface fractal dimension is computed using a 2D generalization of Higuchi’s method. A clustering method allows for the selection of the relevant color distribution in skin lesion images by determining the average percentage of color areas within the nevi and melanoma lesion areas. In a classification stage, the Higuchi fractal dimensions (HFDs) and the color features are classified, separately, using a kNN-CV algorithm. In addition, these features are prototypes for a Radial basis function neural network (RBFNN) classifier. The efficiency of our algorithms was verified by utilizing images belonging to the 7-Point, Med-Node, and PH2 databases; (3) Results: Experimental results show that the accuracy of the proposed RBFNN model in skin cancer classification is 95.42% for 7-Point, 94.71% for Med-Node, and 94.88% for PH2, which are all significantly better than that of the kNN algorithm. (4) Conclusions: 2D Higuchi’s surface fractal features have not been previously used for skin lesion classification purpose. We used fractal features further correlated to color features to create a RBFNN classifier that provides high accuracies of classification.

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Khoa, Truong Quang Dang, Vo Quang Ha, and Vo Van Toi. "Higuchi Fractal Properties of Onset Epilepsy Electroencephalogram." Computational and Mathematical Methods in Medicine 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/461426.

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Epilepsy is a medical term which indicates a common neurological disorder characterized by seizures, because of abnormal neuronal activity. This leads to unconsciousness or even a convulsion. The possible etiologies should be evaluated and treated. Therefore, it is necessary to concentrate not only on finding out efficient treatment methods, but also on developing algorithm to support diagnosis. Currently, there are a number of algorithms, especially nonlinear algorithms. However, those algorithms have some difficulties one of which is the impact of noise on the results. In this paper, in addition to the use of fractal dimension as a principal tool to diagnose epilepsy, the combination between ICA algorithm and averaging filter at the preprocessing step leads to some positive results. The combination which improved the fractal algorithm become robust with noise on EEG signals. As a result, we can see clearly fractal properties in preictal and ictal period so as to epileptic diagnosis.

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Li, Zhiwei, Jun Li, Yousheng Xia, Pingfa Feng, and Feng Feng. "Variation Trends of Fractal Dimension in Epileptic EEG Signals." Algorithms 14, no. 11 (October 29, 2021): 316. http://dx.doi.org/10.3390/a14110316.

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Epileptic diseases take EEG as an important basis for clinical judgment, and fractal algorithms were often used to analyze electroencephalography (EEG) signals. However, the variation trends of fractal dimension (D) were opposite in the literature, i.e., both D decreasing and increasing were reported in previous studies during seizure status relative to the normal status, undermining the feasibility of fractal algorithms for EEG analysis to detect epileptic seizures. In this study, two algorithms with high accuracy in the D calculation, Higuchi and roughness scaling extraction (RSE), were used to study D variation of EEG signals with seizures. It was found that the denoising operation had an important influence on D variation trend. Moreover, the D variation obtained by RSE algorithm was larger than that by Higuchi algorithm, because the non-fractal nature of EEG signals during normal status could be detected and quantified by RSE algorithm. The above findings in this study could be promising to make more understandings of the nonlinear nature and scaling behaviors of EEG signals.

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Nikolopoulos, Dimitrios, Konstantinos Moustris, Ermioni Petraki, Dionysios Koulougliotis, and Demetrios Cantzos. "Fractal and Long-Memory Traces in PM10 Time Series in Athens, Greece." Environments 6, no. 3 (February 26, 2019): 29. http://dx.doi.org/10.3390/environments6030029.

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This work examines if chaos and long memory exist in PM10 concentrations recorded in Athens, Greece. The algorithms of Katz, Higuchi, and Sevcik were employed for the calculation of fractal dimensions and Rescaled Range (R/S) analysis for the calculation of the Hurst exponent. Windows of approximately two months’ duration were employed, sliding one sample forward until the end of each utilized signal. Analysis was applied to three long PM10 time series recorded by three different stations located around Athens. Analysis identified numerous dynamical complex fractal time-series segments with patterns of long memory. All these windows exhibited Hurst exponents above 0.8 and fractal dimensions below 1.5 for the Katz and Higuchi algorithms, and 1.2 for the Sevcik algorithm. The paper discusses the importance of threshold values for the postanalysis of the discrimination of fractal and long-memory windows. After setting thresholds, computational calculations were performed on all possible combinations of two or more techniques for the data of all or two stations under study. When all techniques were combined, several common dates were found for the data of the two combinations of two stations. When the three techniques were combined, more common dates were found if the Katz algorithm was not included in the meta-analysis. Excluding Katz’s algorithm, 12 common dates were found for the data from all stations. This is the first time that the results from sliding-window chaos and long-memory techniques in PM10 time series were combined in this manner.

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Panuszka, Ryszard, Zbigniew Damijan, and Cezary Kasprzak. "Fractal EEG analysis with Higuchi’s algorithm of low‐frequency noise exposition on humans." Journal of the Acoustical Society of America 115, no. 5 (May 2004): 2388. http://dx.doi.org/10.1121/1.4780443.

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GRACE ELIZABETH RANI, T. G., and G. JAYALALITHA. "COMPLEX PATTERNS IN FINANCIAL TIME SERIES THROUGH HIGUCHI’S FRACTAL DIMENSION." Fractals 24, no. 04 (December 2016): 1650048. http://dx.doi.org/10.1142/s0218348x16500481.

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This paper analyzes the complexity of stock exchanges through fractal theory. Closing price indices of four stock exchanges with different industry sectors are selected. Degree of complexity is assessed through Higuchi’s fractal dimension. Various window sizes are considered in evaluating the fractal dimension. It is inferred that the data considered as a whole represents random walk for all the four indices. Analysis of financial data through windowing procedure exhibits multi-fractality. Attempts to apply moving averages to reduce noise in the data revealed lower estimates of fractal dimension, which was verified using fractional Brownian motion. A change in the normalization factor in Higuchi’s algorithm did improve the results. It is quintessential to focus on rural development to realize a standard and steady growth of economy. Tools must be devised to settle the issues in this regard. Micro level institutions are necessary for the economic growth of a country like India, which would induce a sporadic development in the present global economical scenario.

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Feng, Feng, Meng Yuan, Yousheng Xia, Haoming Xu, Pingfa Feng, and Xinghui Li. "Roughness Scaling Extraction Accelerated by Dichotomy-Binary Strategy and Its Application to Milling Vibration Signal." Mathematics 10, no. 7 (March 29, 2022): 1105. http://dx.doi.org/10.3390/math10071105.

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Fractal algorithms for signal analysis are developed from geometric fractals and can be used to describe various complex signals in nature. A roughness scaling extraction algorithm with first-order flattening (RSE-f1) was shown in our previous studies to have a high accuracy, strong noise resistance, and a unique capacity to recognize the complexity of non-fractals that are common in signals. In this study, its disadvantage of a long calculation duration was addressed by using a dichotomy-binary strategy. The accelerated RSE-f1 algorithm (A-RSE-f1) retains the three above-mentioned advantages of the original algorithm according to theoretical analysis and artificial signal testing, while its calculation speed is significantly accelerated by 13 fold, which also makes it faster than the typical Higuchi algorithm. Afterwards, the vibration signals of the milling process are analyzed using the A-RSE-f1 algorithm, demonstrating the ability to distinguish different machining statuses (idle, stable, and chatter) effectively. The results of this study demonstrate that the RSE algorithm has been improved to meet the requirements of practical engineering with both a fast speed and a high performance.

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Ahammer, Helmut, Nikolaus Sabathiel, and Martin A. Reiss. "Is a two-dimensional generalization of the Higuchi algorithm really necessary?" Chaos: An Interdisciplinary Journal of Nonlinear Science 25, no. 7 (July 2015): 073104. http://dx.doi.org/10.1063/1.4923030.

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Garner, David M., Naiara Maria de Souza, and Luiz Carlos M. Vanderlei. "Heart Rate Variability Analysis: Higuchi and Katz’s Fractal Dimensions in Subjects with Type 1 Diabetes Mellitus." Romanian Journal of Diabetes Nutrition and Metabolic Diseases 25, no. 3 (September 1, 2018): 289–95. http://dx.doi.org/10.2478/rjdnmd-2018-0034.

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Abstract Background and aims: Statistical markers are valuable when assessing physiological status over periods of time and in certain disease states. We assess if type 1 diabetes mellitus promote modification in the autonomic nervous system using the main two types of algorithms to estimate a Fractal Dimension: Higuchi and Katz. Material and methods: 46 adults were divided into two equal groups. The autonomic evaluation consisted of recording heart rate variability (HRV) for 30 minutes in supine position in absence of any other stimuli. Fractal dimensions ought then able to determine which series of interbeat intervals are derived from diabetics’ or not. We then equated results to observe which assessment gave the greatest significance by One-way analysis of variance (ANOVA1), Kruskal-Wallis technique and Cohen’s d effect sizes. Results: Katz’s fractal dimension is the most robust algorithm when assisted by a cubic spline interpolation (6 Hz) to increase the number of samples in the dataset. This was categorical after two tests for normality; then, ANOVA1, Kruskal-Wallis and Cohen’s d effect sizes (p≈0.01 and Cohen’s d=0.814143 –medium effect size). Conclusion: Diabetes significantly reduced the chaotic response as measured by Katz’s fractal dimension. Katz’s fractal dimension is a viable statistical marker for subjects with type 1 diabetes mellitus.

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KLONOWSKI, W., P. STEPIEN, R. STEPIEN, R. SEDIVY, H. AHAMMER, and S. Z. SPASIC. "ANALYSIS OF ANAL INTRAEPITHELIAL NEOPLASIA IMAGES USING 1D AND 2D HIGUCHI’s FRACTAL DIMENSION METHODS." Fractals 26, no. 03 (June 2018): 1850021. http://dx.doi.org/10.1142/s0218348x18500214.

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The ILF (Image Landscapes’ Fractal Dimension) method and [Formula: see text] method obtained by a 2D generalization of Higuchi’s algorithm were applied to a set of 120 digital histological images of Anal Intraepithelial Neoplasia (AIN). The main goal of this research was to examine accuracy that means sensitivity and specificity of these methods and compare the applicability of both methods in the quantitative characterization and differentiation of clinical cases of AIN. Histological examination by an experienced pathologist revealed three grades of AIN tumors in the 120 histological slices: 36 of AIN1, 56 of AIN2 and 28 of AIN3. Statistical tests showed significant differences between calculated fractal dimension values in three datasets (AIN1, AIN2 and AIN3) using ILF and [Formula: see text] methods at the level of significance of 0.05. Application of the ILF and [Formula: see text] methods has an advantage when it comes to speed, accuracy, simplicity and time necessary for analysis. Both methods can be successfully applied for differentiation between AIN stages giving practically the same results. They can easily be adapted to other histological specimen.

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Colovini, T., F. Facciuto, M. E. Cabral, R. Parodi, M. I. Spengler, and D. Piskorz. "APPLICATION OF HIGUCHIʼS ALGORITHM IN CENTRAL BLOOD PRESSURE PULSE WAVES AND ITS POTENTIAL ASSOCIATION WITH HEMODYNAMIC PARAMETERS IN HYPERTENSIVE PATIENTS." Journal of Hypertension 37 (July 2019): e234. http://dx.doi.org/10.1097/01.hjh.0000573004.23278.99.

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MORENO-GOMEZ, ALEJANDRO, JOSE M. MACHORRO-LOPEZ, JUAN P. AMEZQUITA-SANCHEZ, CARLOS A. PEREZ-RAMIREZ, MARTIN VALTIERRA-RODRIGUEZ, and AURELIO DOMINGUEZ-GONZALEZ. "FRACTAL DIMENSION ANALYSIS FOR ASSESSING THE HEALTH CONDITION OF A TRUSS STRUCTURE USING VIBRATION SIGNALS." Fractals 28, no. 07 (November 2020): 2050127. http://dx.doi.org/10.1142/s0218348x20501273.

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During the last years, civil infrastructure has experienced an increasing development to satisfy the society’s demands such as communication, transportation, work and living spaces, among others. In this sense, the development and application of methods to guarantee the structure optimal operation, known as Structural Health Monitoring schemes, are necessary in order to avoid economic and human losses. Modern schemes employ the structure vibration response as any damage will modify the structure physical properties, which will be reflected in the vibration response. Thus, by measuring the waveform changes of the response, the structure condition can be determined. Considering this fact, this paper investigates the effectiveness of Katz fractal dimension, Higuchi fractal dimension, Box fractal dimension, Petrosian fractal dimension, and Sevcik fractal dimension which are nonlinear measurements to extract features of vibration signals in order to determine the health condition of a 3D 9-bay truss-type bridge. The obtained results show that the algorithms corresponding to Higuchi and Petrosian fractal dimension algorithms exceed the other nonlinear measurements in efficiency to discriminate between a healthy structure and a damage produced by corrosion.

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Demidova, Liliya A. "A Novel Approach to Decision-Making on Diagnosing Oncological Diseases Using Machine Learning Classifiers Based on Datasets Combining Known and/or New Generated Features of a Different Nature." Mathematics 11, no. 4 (February 4, 2023): 792. http://dx.doi.org/10.3390/math11040792.

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This paper deals with the problem of diagnosing oncological diseases based on blood protein markers. The goal of the study is to develop a novel approach in decision-making on diagnosing oncological diseases based on blood protein markers by generating datasets that include various combinations of features: both known features corresponding to blood protein markers and new features generated with the help of mathematical tools, particularly with the involvement of the non-linear dimensionality reduction algorithm UMAP, formulas for various entropies and fractal dimensions. These datasets were used to develop a group of multiclass kNN and SVM classifiers using oversampling algorithms to solve the problem of class imbalance in the dataset, which is typical for medical diagnostics problems. The results of the experimental studies confirmed the feasibility of using the UMAP algorithm and approximation entropy, as well as Katz and Higuchi fractal dimensions to generate new features based on blood protein markers. Various combinations of these features can be used to expand the set of features from the original dataset in order to improve the quality of the received classification solutions for diagnosing oncological diseases. The best kNN and SVM classifiers were developed based on the original dataset augmented respectively with a feature based on the approximation entropy and features based on the UMAP algorithm and the approximation entropy. At the same time, the average values of the metric MacroF1 - score used to assess the quality of classifiers during cross-validation increased by 16.138% and 7.910%, respectively, compared to the average values of this metric in the case when the original dataset was used in the development of classifiers of the same name.

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Simion, Adrian Gabriel, Ion Andronache, Helmut Ahammer, Marian Marin, Vlad Loghin, Iulia Daniela Nedelcu, Cristian Mihnea Popa, Daniel Peptenatu, and Herbert Franz Jelinek. "Particularities of Forest Dynamics Using Higuchi Dimension. Parâng Mountains as a Case Study." Fractal and Fractional 5, no. 3 (August 13, 2021): 96. http://dx.doi.org/10.3390/fractalfract5030096.

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The legal or illegal losses and the natural disturbance regime of forest areas in Romania generate major imbalances in territorial systems. The main purpose of the current research was to examine the dynamics of the complexity of forests under the influence of forest loss but also to compare the applicability of Higuchi dimension. In this study, two fractal algorithms, Higuchi 1D (H1D) and Higuchi 2D (H2D), were used to determine qualitative and quantitative aspects based on images obtained from a Geographic Information System (GIS) database. The H1D analysis showed that the impact of forest loss has led to increased fragmentation of the forests, generating a continuous increase in the complexity of forest areas. The H2D analysis identified the complexity of forest morphology by the relationship between each pixel and the neighboring pixels from analyzed images, which allowed us to highlight the local characteristics of the forest loss. The H1D and H2D methods showed that they have the speed and simplicity required for forest loss analysis. Using this methodology complementary to GIS analyses, a relevant status of how forest loss occurred and their impact on tree-cover dynamics was obtained.

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Saxena, Shikha, and Kamal Kant Gupta. "Artificial Neural Network analysis of EEG waves in complex partial seizure patients." Nepal Journal of Neuroscience 18, no. 1 (March 1, 2021): 15–21. http://dx.doi.org/10.3126/njn.v18i1.31668.

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Background: Brain dynamics associated with epilepsy remains limited. EEG-based epilepsy diagnosis and seizure detection is still in its infancy. The problem is further amplified for the design and development of automated algorithms, which requires a quantitative parametric representation of the qualitative or visual aspect of the markers. This study proposes an automatic classification system for epilepsy based on neural networks and EEG signals. Material and Method: The present study made use of EEG data from 16 controls and 16 temporal lobe epilepsy (TLE) patients in order to comparatively assess neural dynamics in normal healthy young adults and epileptic patients treated with anti-epileptic drugs in the context of resting state during eye close session. Such tangible differences could be appreciated through artificial neural network (ANN) classifiers. Results: During eye closed session of EEG in order to diagnose temporal lobe epileptic patient, the extracted features of EEG activity are given to the classifier algorithm for training and test performance. Artificial Neural Network (ANN) classifier was used for the diagnosis task. Fractal dimension (Katz, Higuchi and Permission entropy) were analyzed, in which the best results was observed in trained set of data of Katz (93.18%). Conclusion: Non-linear analysis plays an important role in prediction of complex partial seizure during interictal period.

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Rubega, Maria, Emanuela Formaggio, Franco Molteni, Eleonora Guanziroli, Roberto Di Marco, Claudio Baracchini, Mario Ermani, Nick S. Ward, Stefano Masiero, and Alessandra Del Felice. "EEG Fractal Analysis Reflects Brain Impairment after Stroke." Entropy 23, no. 5 (May 11, 2021): 592. http://dx.doi.org/10.3390/e23050592.

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Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.

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SPASIC, SLADJANA, SRDJAN KESIC, ALEKSANDAR KALAUZI, and JASNA SAPONJIC. "DIFFERENT ANESTHESIA IN RAT INDUCES DISTINCT INTER-STRUCTURE BRAIN DYNAMIC DETECTED BY HIGUCHI FRACTAL DIMENSION." Fractals 19, no. 01 (March 2011): 113–23. http://dx.doi.org/10.1142/s0218348x1100521x.

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The complexity, entropy and other non-linear measures of the electroencephalogram (EEG), such as Higuchi fractal dimension (FD), have been recently proposed as the measures of anesthesia depth and sedation. We hypothesized that during unconciousness in rats induced by the general anesthetics with opposite mechanism of action, behaviorally and poligraphically controlled as appropriately achieved stable anesthesia, we can detect distinct inter-structure brain dynamic using mean FDs. We used the surrogate data test for nonlinearity in order to establish the existence of nonlinear dynamics, and to justify the use of FD as a nonlinear measure in the time series analysis. The surrogate data of predefined probability distribution and autocorrelation properties have been generated using the algorithm of statically transformed autoregressive process (STAP). FD then is applied to quantify EEG signal complexity at the cortical, hippocampal and pontine level during stable general anesthesia (ketamine/xylazine or nembutal anesthesia). Our study showed for the first time that global neuronal inhibition caused by different mechanisms of anesthetic action induced distinct brain inter-structure complexity gradient in Sprague Dawley rats. EEG signal complexities were higher at cortical and hippocampal level in ketamine/xylazine vs. nembutal anesthesia, with the dominance of hippocampal complexity. In nembutal anesthesia the complexity dominance moved to pontine level, and ponto-hippocampo-cortical decreasing complexity gradient was established. This study has proved the Higuchi fractal dimension as a valuable tool for measuring the anesthesia induced inter-structure EEG complexity.

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Aguirre-López, Mario A., Miguel Angel Rodríguez-González, Roberto Soto-Villalobos, Laura Elena Gómez-Sánchez, Ángela Gabriela Benavides-Ríos, Francisco Gerardo Benavides-Bravo, Otoniel Walle-García, and María Gricelda Pamanés-Aguilar. "Statistical Analysis of PM10 Concentration in the Monterrey Metropolitan Area, Mexico (2010–2018)." Atmosphere 13, no. 2 (February 9, 2022): 297. http://dx.doi.org/10.3390/atmos13020297.

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Air-quality monitoring and analysis are initial parts of a comprehensive strategy to prevent air pollution in cities. In such a context, statistical tools play an important role in determining the time-series trends, locating areas with high pollutant concentrations, and building predictive models. In this work, we analyzed the spatio-temporal behavior of the pollutant PM10 in the Monterrey Metropolitan Area (MMA), Mexico during the period 2010–2018 by applying statistical analysis to the time series of seven environmental stations. First, we used experimental variograms and scientific visualization to determine the general trends and variability in time. Then, fractal exponents (the Hurst rescaled range and Higuchi algorithm) were used to analyze the long-term dependence of the time series and characterize the study area by correlating that dependence with the geographical parameters of each environmental station. The results suggest a linear decrease in PM10 concentration, which showed an annual cyclicity. The autumn-winter period was the most polluted and the spring-summer period was the least. Furthermore, it was found that the highest average concentrations are located in the western and high-altitude zones of the MMA, and that average concentration is related in a quadratic way to the Hurst and Higuchi exponents, which in turn are related to some geographic parameters. Therefore, in addition to the results for the MMA, the present paper shows three practical statistical methods for analyzing the spatio-temporal behavior of air quality.

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Alhalaseh, Rania, and Suzan Alasasfeh. "Machine-Learning-Based Emotion Recognition System Using EEG Signals." Computers 9, no. 4 (November 30, 2020): 95. http://dx.doi.org/10.3390/computers9040095.

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Many scientific studies have been concerned with building an automatic system to recognize emotions, and building such systems usually relies on brain signals. These studies have shown that brain signals can be used to classify many emotional states. This process is considered difficult, especially since the brain’s signals are not stable. Human emotions are generated as a result of reactions to different emotional states, which affect brain signals. Thus, the performance of emotion recognition systems by brain signals depends on the efficiency of the algorithms used to extract features, the feature selection algorithm, and the classification process. Recently, the study of electroencephalography (EEG) signaling has received much attention due to the availability of several standard databases, especially since brain signal recording devices have become available in the market, including wireless ones, at reasonable prices. This work aims to present an automated model for identifying emotions based on EEG signals. The proposed model focuses on creating an effective method that combines the basic stages of EEG signal handling and feature extraction. Different from previous studies, the main contribution of this work relies in using empirical mode decomposition/intrinsic mode functions (EMD/IMF) and variational mode decomposition (VMD) for signal processing purposes. Despite the fact that EMD/IMFs and VMD methods are widely used in biomedical and disease-related studies, they are not commonly utilized in emotion recognition. In other words, the methods used in the signal processing stage in this work are different from the methods used in literature. After the signal processing stage, namely in the feature extraction stage, two well-known technologies were used: entropy and Higuchi’s fractal dimension (HFD). Finally, in the classification stage, four classification methods were used—naïve Bayes, k-nearest neighbor (k-NN), convolutional neural network (CNN), and decision tree (DT)—for classifying emotional states. To evaluate the performance of our proposed model, experiments were applied to a common database called DEAP based on many evaluation models, including accuracy, specificity, and sensitivity. The experiments showed the efficiency of the proposed method; a 95.20% accuracy was achieved using the CNN-based method.

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LI, JIN, XIAN ZHANG, JINZHE GONG, JINGTIAN TANG, ZHENGYONG REN, GUANG LI, YANLI DENG, and JIN CAI. "SIGNAL-NOISE IDENTIFICATION OF MAGNETOTELLURIC SIGNALS USING FRACTAL-ENTROPY AND CLUSTERING ALGORITHM FOR TARGETED DE-NOISING." Fractals 26, no. 02 (April 2018): 1840011. http://dx.doi.org/10.1142/s0218348x1840011x.

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A new technique is proposed for signal-noise identification and targeted de-noising of Magnetotelluric (MT) signals. This method is based on fractal-entropy and clustering algorithm, which automatically identifies signal sections corrupted by common interference (square, triangle and pulse waves), enabling targeted de-noising and preventing the loss of useful information in filtering. To implement the technique, four characteristic parameters — fractal box dimension (FBD), higuchi fractal dimension (HFD), fuzzy entropy (FuEn) and approximate entropy (ApEn) — are extracted from MT time-series. The fuzzy c-means (FCM) clustering technique is used to analyze the characteristic parameters and automatically distinguish signals with strong interference from the rest. The wavelet threshold (WT) de-noising method is used only to suppress the identified strong interference in selected signal sections. The technique is validated through signal samples with known interference, before being applied to a set of field measured MT/Audio Magnetotelluric (AMT) data. Compared with the conventional de-noising strategy that blindly applies the filter to the overall dataset, the proposed method can automatically identify and purposefully suppress the intermittent interference in the MT/AMT signal. The resulted apparent resistivity-phase curve is more continuous and smooth, and the slow-change trend in the low-frequency range is more precisely reserved. Moreover, the characteristic of the target-filtered MT/AMT signal is close to the essential characteristic of the natural field, and the result more accurately reflects the inherent electrical structure information of the measured site.

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Azizi, Tahmineh, and Sepideh Azizi. "The Fractal Nature of Drought: Power Laws and Fractal Complexity of Arizona Drought." European Journal of Mathematical Analysis 2 (May 27, 2022): 17. http://dx.doi.org/10.28924/ada/ma.2.17.

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In this study, we explore the possibility that the Drought Monitor database belongs to class of fractal process which can be characterized using a single scaling exponent. The Drought Monitor map identifies areas of drought and labels them by intensity: D0 abnormally dry, D1 moderate drought, D2 severe drought, D3 extreme drought, and D4 exceptional drought. The vibration analysis using power spectral densities (PSD) method has been carried out to discover whether some type of power-law scaling exists for various statistical moments at different scales of this database. We perform multi-fractal analysis to estimate the multi-fractal spectrum of each group. We apply Higuchi algorithm to find the fractal complexity of each group and then compare them for different time intervals. Our findings reveal that we have a wide range of exponents for D0-D4. Therefore, D0-D4 belong to class of multi-fractal process for which a large number of scaling exponents are required to characterize the scaling structure.

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Olejarczyk, Elzbieta, Filippo Zappasodi, Lorenzo Ricci, Annalisa Pascarella, Giovanni Pellegrino, Luca Paulon, Giovanni Assenza, and Franca Tecchio. "Functional Source Separation-Identified Epileptic Network: Analysis Pipeline." Brain Sciences 12, no. 9 (September 1, 2022): 1179. http://dx.doi.org/10.3390/brainsci12091179.

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This proof-of-concept (PoC) study presents a pipeline made by two blocks: 1. the identification of the network that generates interictal epileptic activity; and 2. the study of the time course of the electrical activity that it generates, called neurodynamics, and the study of its functional connectivity to the other parts of the brain. Network identification is achieved with the Functional Source Separation (FSS) algorithm applied to electroencephalographic (EEG) recordings, the neurodynamics quantified through signal complexity with the Higuchi Fractal Dimension (HFD), and functional connectivity with the Directed Transfer Function (DTF). This PoC is enhanced by the data collected before and after neuromodulation via transcranial Direct Current Stimulation (tDCS, both Real and Sham) in a single drug-resistant epileptic person. We observed that the signal complexity of the epileptogenic network, reduced in the pre-Real, pre-Sham, and post-Sham, reached the level of the rest of the brain post-Real tDCS. DTF changes post-Real tDCS were maintained after one month. The proposed approach can represent a valuable tool to enhance understanding of the relationship between brain neurodynamics characteristics, the effects of non-invasive brain stimulation, and epileptic symptoms.

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Molina-Tenorio, Yanqueleth, Alfonso Prieto-Guerrero, and Rafael Aguilar-Gonzalez. "Multiband Spectrum Sensing Based on the Sample Entropy." Entropy 24, no. 3 (March 15, 2022): 411. http://dx.doi.org/10.3390/e24030411.

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Cognitive radios represent a real alternative to the scarcity of the radio spectrum. One of the primary tasks of these radios is the detection of possible gaps in a given bandwidth used by licensed users (called also primary users). This task, called spectrum sensing, requires high precision in determining these gaps, maximizing the probability of detection. The design of spectrum sensing algorithms also requires innovative hardware and software solutions for real-time implementations. In this work, a technique to determine possible primary users’ transmissions in a wide frequency interval (multiband spectrum sensing) from the perspective of cognitive radios is presented. The proposal is implemented in a real wireless communications environment using low-cost hardware considering the sample entropy as a decision rule. To validate its feasibility for real-time implementation, a simulated scenario was first tested. Simulation and real-time implementations results were compared with the Higuchi fractal dimension as a decision rule. The encouraging results show that sample entropy correctly detects noise or a possible primary user transmission, with a probability of success around 0.99, and the number of samples with errors at the start and end of frequency edges of transmissions is, on average, only 12 samples.

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Shankar Beriha, Siba. "Computer Aided Diagnosis System To Distinguish Adhd From Similar Behavioral Disorders." Biomedical and Pharmacology Journal 11, no. 2 (June 12, 2018): 1135–41. http://dx.doi.org/10.13005/bpj/1474.

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ADHD is one of the most prevalent psychiatric disorder of childhood, characterized by inattention and distractibility, with or without accompanying hyperactivity. The main aim of this research work is to develop a Computer Aided Diagnosis (CAD) technique with minimal steps that can differentiate the ADHD children from the other similar children behavioral disorders such as anxiety, depression and conduct disorder based on the Electroencephalogram (EEG) signal features and symptoms. The proposed technique is based on soft computing and bio inspired computing algorithms. Four non-linear features are extracted from the EEG such as Higuchi fractal dimension, Katz fractal dimension, Sevick fractal dimension and Lyapunov exponent and 14 symptoms which are most important in differentiation are extracted by experts in the field of psychiatry. Particle Swarm Optimization (PSO) tuned Back Propagation Neural Network (BPNN) and PSO tuned Radial Basis Function (RBF) employed as a classifier. By investigating these integrated features, we obtained good classification accuracy. Simulation results suggest that the proposed technique offer high potential in the diagnosis of ADHD and may be a good preliminary assistant for psychiatrists in diagnosing high risk behavioral disorders of children.

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Seifi, Sepanta, Fereidoun Nowshiravan Rahatabad, and Zahra Einalou. "Detection of Different Levels of Multiple Sclerosis by Assessing Nonlinear Characteristics of Posture." International Clinical Neuroscience Journal 5, no. 4 (December 20, 2018): 115–20. http://dx.doi.org/10.15171/icnj.2018.23.

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Background: Multiple sclerosis (MS) is a chronic disorder of the central nervous system that affects various parts of the brain and the spinal cord, leading to interruptions of the nervous, defense and movement systems, which usually affect balance and gait. Considering that the diagnosis of MS and its classification is a function of the expertise of the physician, the use of creative methods can help physicians to diagnose and classify different levels of the disease. Methods: The primary objective of the present study was to detect different levels of MS disease based on the nonlinear evaluation of body features. To do so, we studied eight MS patients and posture information of these patients such as the center of pressure (COP) were recorded at different levels with various degrees of Expanded Disability Status Scale (EDSS) by a motion analyzer device, while subjects were standing on the force plate in the eyes-opened and eyes-closed modes. After extracting and validating features that are used to assess posture disorders and explain the balancing behavior, the support vector machine (SVM) was employed to classify different levels of disease. Using the Spearman correlation test, each feature evaluated by the EDSS test. Results: The features obtained from Higuchi’s fractal dimensional algorithm in both anteriorposterior and mediolateral directions of the COP, which were significant (P<0.05) were selected and provided to SVM and neural network for classification of different levels. It found that SVM outperformed neural network and was able to carry out the classification with the accuracy of 90.7%. Conclusion: As an intelligent method, the non-linear evaluation of body features such as dimensional fractal analysis of the COP can help physicians diagnose different levels of MS with greater precision.

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Bahramizadeh-Sajadi, Shima, Hamid Reza Katoozian, Mahtab Mehrabbeik, Alireza Baradaran-Rafii, Khosrow Jadidi, and Sajad Jafari. "A Fractal Approach to Nonlinear Topographical Features of Healthy and Keratoconus Corneas Pre- and Post-Operation of Intracorneal Implants." Fractal and Fractional 6, no. 11 (November 20, 2022): 688. http://dx.doi.org/10.3390/fractalfract6110688.

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Fractal dimension (FD) together with advances in imaging technologies has provided an increasing application of digital images to interpret biological phenomena. In ophthalmology, topography-based images are increasingly used in common practices of clinical settings. They provide detailed information about corneal surfaces. Few-micron alterations of the corneal geometry to the elevation and curvature cause a highly multifocal surface, change the corneal optical power up to several diopters, and therefore adversely affect the individual’s vision. Keratoconus (KCN) is a corneal disease characterized by a local alteration of the corneal anatomical and mechanical features. The formation of cone-shaped regions accompanied by thinning and weakening of the cornea are the major manifestations of KCN. The implantation of tiny arc-like polymeric sections, known as intracorneal implants, is considered to be effective in restoring the corneal curvature. This study investigated the FD nature of healthy corneas (n = 7) and compared it to the corresponding values before and after intracorneal implant surgery in KCN patients (n = 7). The generalized Hurst exponent, Higuchi, and Katz FDs were computed for topography-based parameters of corneal surfaces: front elevation (ELE-front), back elevation (ELE-back), and corneal curvature (CURV). The Katz FD showed better discriminating ability for the diseased group. It could reveal a significant difference between the healthy corneas and both pre- and post-implantation topographies (p < 0.001). Moreover, the Katz dimension varied between the topographic features of KCN patients before and after the treatment (p < 0.036). We propose to describe the curvature feature of corneal topography as a “strange attractor” with a self-similar (i.e., fractal) structure according to the Katz algorithm.

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Kudryavtsev, Nikolay, Varvara Safonova, and Albina Temerbekova. "On one approach to the detection of infrasonic signals of irregular natural phenomena in the instrumental observations time series at the student interdisciplinary testing ground." E3S Web of Conferences 270 (2021): 01026. http://dx.doi.org/10.1051/e3sconf/202127001026.

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The work is devoted to the analysis of time series and the problem of processing signals obtained as a result of the design approach implementation during the organization of instrumental observations of irregular natural phenomena at the student interdisciplinary testing ground. The objective of the work is to study the methods of processing noisy signals obtained as a result of monitoring the infrasonic environment, which make it possible to automate the search for fragments of the time series generated by irregular natural phenomena. At the beginning of the work, a brief explanation of the essence of the measuring scientific experiment carried out within the framework of the project approach used in the additional education of students and schoolchildren shall be given. The following is a review of publications describing various approaches to the analysis of nonstationary time series obtained in the process of instrumental observations. As the main method of time series analysis, it is proposed to use the algorithm for calculating the fractal dimension of the time series, proposed by T. Higuchi [1]. During studying of the time series of infrasonic signals, a number of regularities were discovered that contribute to the development of an original procedure for processing and transforming the signal under study, which makes it possible to determine the time intervals of fragments of the time series corresponding to the signals of the desired natural phenomena. The essence of the proposed approach lies in the preliminary preparation of the time series by processing the data with a simple normalized difference filter, previously smoothed by performing the coenvolution (convolution) operation with a Gaussian kernel; determining the step of segmenting the normalized time series, calculating fractal dimensions and averaged amplitudes for each of the segments of the time series and obtaining on their basis vectors of changes in dimensions and amplitudes with their subsequent element-wise multiplication. It is shown that the maximum values of the components of the resulting vector are indicators of timestamps for the location of the desired signals.

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Alqahtani, Sarra, and Rose Gamble. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 24-29 (2017); View Description Zero Trust Cloud Networks using Transport Access Control and High Availability Optical Bypass Switching Casimer DeCusatis, Piradon Liengtiraphan, Anthony Sager Adv. Sci. Technol. Eng. Syst. J. 2(3), 30-35 (2017); View Description A Derived Metrics as a Measurement to Support Efficient Requirements Analysis and Release Management Indranil Nath Adv. Sci. Technol. Eng. Syst. J. 2(3), 36-40 (2017); View Description Feedback device of temperature sensation for a myoelectric prosthetic hand Yuki Ueda, Chiharu Ishii Adv. Sci. Technol. Eng. Syst. J. 2(3), 41-40 (2017); View Description Deep venous thrombus characterization: ultrasonography, elastography and scattering operator Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier Adv. Sci. Technol. Eng. Syst. J. 2(3), 48-59 (2017); View Description Improving customs’ border control by creating a reference database of cargo inspection X-ray images Selina Kolokytha, Alexander Flisch, Thomas Lüthi, Mathieu Plamondon, Adrian Schwaninger, Wicher Vasser, Diana Hardmeier, Marius Costin, Caroline Vienne, Frank Sukowski, Ulf Hassler, Irène Dorion, Najib Gadi, Serge Maitrejean, Abraham Marciano, Andrea Canonica, Eric Rochat, Ger Koomen, Micha Slegt Adv. Sci. Technol. Eng. Syst. J. 2(3), 60-66 (2017); View Description Aviation Navigation with Use of Polarimetric Technologies Arsen Klochan, Ali Al-Ammouri, Viktor Romanenko, Vladimir Tronko Adv. Sci. Technol. Eng. Syst. J. 2(3), 67-72 (2017); View Description Optimization of Multi-standard Transmitter Architecture Using Single-Double Conversion Technique Used for Rescue Operations Riadh Essaadali, Said Aliouane, Chokri Jebali and Ammar Kouki Adv. Sci. Technol. Eng. Syst. J. 2(3), 73-81 (2017); View Description Singular Integral Equations in Electromagnetic Waves Reflection Modeling A. S. Ilinskiy, T. N. Galishnikova Adv. Sci. Technol. Eng. Syst. J. 2(3), 82-87 (2017); View Description Methodology for Management of Information Security in Industrial Control Systems: A Proof of Concept aligned with Enterprise Objectives. Fabian Bustamante, Walter Fuertes, Paul Diaz, Theofilos Toulqueridis Adv. Sci. Technol. Eng. Syst. J. 2(3), 88-99 (2017); View Description Dependence-Based Segmentation Approach for Detecting Morpheme Boundaries Ahmed Khorsi, Abeer Alsheddi Adv. Sci. Technol. Eng. Syst. J. 2(3), 100-110 (2017); View Description Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language Soufiane Farrah, Hanane El Manssouri, Ziyati Elhoussaine, Mohamed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 111-115 (2017); View Description Medical imbalanced data classification Sara Belarouci, Mohammed Amine Chikh Adv. Sci. Technol. Eng. Syst. J. 2(3), 116-124 (2017); View Description ADOxx Modelling Method Conceptualization Environment Nesat Efendioglu, Robert Woitsch, Wilfrid Utz, Damiano Falcioni Adv. Sci. Technol. Eng. Syst. J. 2(3), 125-136 (2017); View Description GPSR+Predict: An Enhancement for GPSR to Make Smart Routing Decision by Anticipating Movement of Vehicles in VANETs Zineb Squalli Houssaini, Imane Zaimi, Mohammed Oumsis, Saïd El Alaoui Ouatik Adv. Sci. Technol. Eng. Syst. J. 2(3), 137-146 (2017); View Description Optimal Synthesis of Universal Space Vector Digital Algorithm for Matrix Converters Adrian Popovici, Mircea Băbăiţă, Petru Papazian Adv. Sci. Technol. Eng. Syst. J. 2(3), 147-152 (2017); View Description Control design for axial flux permanent magnet synchronous motor which operates above the nominal speed Xuan Minh Tran, Nhu Hien Nguyen, Quoc Tuan Duong Adv. Sci. Technol. Eng. Syst. J. 2(3), 153-159 (2017); View Description A synchronizing second order sliding mode control applied to decentralized time delayed multi−agent robotic systems: Stability Proof Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 160-170 (2017); View Description Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor Martin F. Pico, Eduardo J. Adam Adv. Sci. Technol. Eng. Syst. J. 2(3), 171-181 (2017); View Description Development and Validation of a Heat Pump System Model Using Artificial Neural Network Nabil Nassif, Jordan Gooden Adv. Sci. Technol. Eng. Syst. J. 2(3), 182-185 (2017); View Description Assessment of the usefulness and appeal of stigma-stop by psychology students: a serious game designed to reduce the stigma of mental illness Adolfo J. Cangas, Noelia Navarro, Juan J. Ojeda, Diego Cangas, Jose A. Piedra, José Gallego Adv. Sci. Technol. Eng. Syst. J. 2(3), 186-190 (2017); View Description Kinect-Based Moving Human Tracking System with Obstacle Avoidance Abdel Mehsen Ahmad, Zouhair Bazzal, Hiba Al Youssef Adv. Sci. Technol. Eng. Syst. J. 2(3), 191-197 (2017); View Description A security approach based on honeypots: Protecting Online Social network from malicious profiles Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi, Habiba Chaoui Adv. Sci. Technol. Eng. Syst. J. 2(3), 198-204 (2017); View Description Pulse Generator for Ultrasonic Piezoelectric Transducer Arrays Based on a Programmable System-on-Chip (PSoC) Pedro Acevedo, Martín Fuentes, Joel Durán, Mónica Vázquez, Carlos Díaz Adv. Sci. Technol. Eng. Syst. J. 2(3), 205-209 (2017); View Description Enabling Toy Vehicles Interaction With Visible Light Communication (VLC) M. A. Ilyas, M. B. Othman, S. M. Shah, Mas Fawzi Adv. Sci. Technol. Eng. Syst. J. 2(3), 210-216 (2017); View Description Analysis of Fractional-Order 2xn RLC Networks by Transmission Matrices Mahmut Ün, Manolya Ün Adv. Sci. Technol. Eng. Syst. J. 2(3), 217-220 (2017); View Description Fire extinguishing system in large underground garages Ivan Antonov, Rositsa Velichkova, Svetlin Antonov, Kamen Grozdanov, Milka Uzunova, Ikram El Abbassi Adv. Sci. Technol. Eng. Syst. J. 2(3), 221-226 (2017); View Description Directional Antenna Modulation Technique using A Two-Element Frequency Diverse Array Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 227-232 (2017); View Description Classifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks Estefanía D. Avalos-Rivera, Alberto de J. Pastrana-Palma Adv. Sci. Technol. Eng. Syst. J. 2(3), 233-240 (2017); View Description Magnetically Levitated and Guided Systems Florian Puci, Miroslav Husak Adv. Sci. Technol. Eng. Syst. J. 2(3), 241-244 (2017); View Description Energy-Efficient Mobile Sensing in Distributed Multi-Agent Sensor Networks Minh T. Nguyen Adv. Sci. Technol. Eng. Syst. J. 2(3), 245-253 (2017); View Description Validity and efficiency of conformal anomaly detection on big distributed data Ilia Nouretdinov Adv. Sci. Technol. Eng. Syst. J. 2(3), 254-267 (2017); View Description S-Parameters Optimization in both Segmented and Unsegmented Insulated TSV upto 40GHz Frequency Juma Mary Atieno, Xuliang Zhang, HE Song Bai Adv. Sci. Technol. Eng. Syst. J. 2(3), 268-276 (2017); View Description Synthesis of Important Design Criteria for Future Vehicle Electric System Lisa Braun, Eric Sax Adv. Sci. Technol. Eng. Syst. J. 2(3), 277-283 (2017); View Description Gestural Interaction for Virtual Reality Environments through Data Gloves G. Rodriguez, N. Jofre, Y. Alvarado, J. Fernández, R. Guerrero Adv. Sci. Technol. Eng. Syst. J. 2(3), 284-290 (2017); View Description Solving the Capacitated Network Design Problem in Two Steps Meriem Khelifi, Mohand Yazid Saidi, Saadi Boudjit Adv. Sci. Technol. Eng. Syst. J. 2(3), 291-301 (2017); View Description A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks Mohammad Nurul Afsar Shaon, Ken Ferens Adv. Sci. Technol. Eng. Syst. J. 2(3), 302-320 (2017); View Description Real Time Advanced Clustering System Giuseppe Spampinato, Arcangelo Ranieri Bruna, Salvatore Curti, Viviana D’Alto Adv. Sci. Technol. Eng. Syst. J. 2(3), 321-326 (2017); View Description Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors Khalid Al-Mutib, Foudil Abdessemed Adv. Sci. Technol. Eng. Syst. J. 2(3), 327-337 (2017); View Description Validity of Mind Monitoring System as a Mental Health Indicator using Voice Naoki Hagiwara, Yasuhiro Omiya, Shuji Shinohara, Mitsuteru Nakamura, Masakazu Higuchi, Shunji Mitsuyoshi, Hideo Yasunaga, Shinichi Tokuno Adv. Sci. Technol. Eng. Syst. J. 2(3), 338-344 (2017); View Description The Model of Adaptive Learning Objects for virtual environments instanced by the competencies Carlos Guevara, Jose Aguilar, Alexandra González-Eras Adv. Sci. Technol. Eng. Syst. J. 2(3), 345-355 (2017); View Description An Overview of Traceability: Towards a general multi-domain model Kamal Souali, Othmane Rahmaoui, Mohammed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 356-361 (2017); View Description L-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits Yasushi Itoh, Hiroaki Takagi Adv. Sci. Technol. Eng. Syst. J. 2(3), 362-368 (2017); View Description Moving Towards Reliability-Centred Management of Energy, Power and Transportation Assets Kang Seng Seow, Loc K. Nguyen, Kelvin Tan, Kees-Jan Van Oeveren Adv. Sci. Technol. Eng. Syst. J. 2(3), 369-375 (2017); View Description Secure Path Selection under Random Fading Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 376-383 (2017); View Description Security in SWIPT with Power Splitting Eavesdropper Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 384-388 (2017); View Description Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 389-394 (2017); View Description Adaptive Discrete-time Fuzzy Sliding Mode Control For a Class of Chaotic Systems Hanene Medhaffar, Moez Feki, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 395-400 (2017); View Description Fault Tolerant Inverter Topology for the Sustainable Drive of an Electrical Helicopter Igor Bolvashenkov, Jörg Kammermann, Taha Lahlou, Hans-Georg Herzog Adv. Sci. Technol. Eng. Syst. J. 2(3), 401-411 (2017); View Description Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid Turgay Yalcin, Muammer Ozdemir Adv. Sci. Technol. Eng. Syst. J. 2(3), 412-419 (2017); View Description A Highly-Secured Arithmetic Hiding cum Look-Up Table (AHLUT) based S-Box for AES-128 Implementation Ali Akbar Pammu, Kwen-Siong Chong, Bah-Hwee Gwee Adv. Sci. Technol. Eng. Syst. J. 2(3), 420-426 (2017); View Description Service Productivity and Complexity in Medical Rescue Services Markus Harlacher, Andreas Petz, Philipp Przybysz, Olivia Chaillié, Susanne Mütze-Niewöhner Adv. Sci. Technol. Eng. Syst. J. 2(3), 427-434 (2017); View Description Principal Component Analysis Application on Flavonoids Characterization Che Hafizah Che Noh, Nor Fadhillah Mohamed Azmin, Azura Amid Adv. Sci. Technol. Eng. Syst. J. 2(3), 435-440 (2017); View Description A Reconfigurable Metal-Plasma Yagi-Yuda Antenna for Microwave Applications Giulia Mansutti, Davide Melazzi, Antonio-Daniele Capobianco Adv. Sci. Technol. Eng. Syst. J. 2(3), 441-448 (2017); View Description Verifying the Detection Results of Impersonation Attacks in Service Clouds." Advances in Science, Technology and Engineering Systems Journal 2, no. 3 (May 2017): 449–59. http://dx.doi.org/10.25046/aj020358.

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32

Abdelhedi, Fatma, and Nabil Derbel. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 24-29 (2017); View Description Zero Trust Cloud Networks using Transport Access Control and High Availability Optical Bypass Switching Casimer DeCusatis, Piradon Liengtiraphan, Anthony Sager Adv. Sci. Technol. Eng. Syst. J. 2(3), 30-35 (2017); View Description A Derived Metrics as a Measurement to Support Efficient Requirements Analysis and Release Management Indranil Nath Adv. Sci. Technol. Eng. Syst. J. 2(3), 36-40 (2017); View Description Feedback device of temperature sensation for a myoelectric prosthetic hand Yuki Ueda, Chiharu Ishii Adv. Sci. Technol. Eng. Syst. J. 2(3), 41-40 (2017); View Description Deep venous thrombus characterization: ultrasonography, elastography and scattering operator Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier Adv. Sci. Technol. Eng. Syst. J. 2(3), 48-59 (2017); View Description Improving customs’ border control by creating a reference database of cargo inspection X-ray images Selina Kolokytha, Alexander Flisch, Thomas Lüthi, Mathieu Plamondon, Adrian Schwaninger, Wicher Vasser, Diana Hardmeier, Marius Costin, Caroline Vienne, Frank Sukowski, Ulf Hassler, Irène Dorion, Najib Gadi, Serge Maitrejean, Abraham Marciano, Andrea Canonica, Eric Rochat, Ger Koomen, Micha Slegt Adv. Sci. Technol. Eng. Syst. J. 2(3), 60-66 (2017); View Description Aviation Navigation with Use of Polarimetric Technologies Arsen Klochan, Ali Al-Ammouri, Viktor Romanenko, Vladimir Tronko Adv. Sci. Technol. Eng. Syst. J. 2(3), 67-72 (2017); View Description Optimization of Multi-standard Transmitter Architecture Using Single-Double Conversion Technique Used for Rescue Operations Riadh Essaadali, Said Aliouane, Chokri Jebali and Ammar Kouki Adv. Sci. Technol. Eng. Syst. J. 2(3), 73-81 (2017); View Description Singular Integral Equations in Electromagnetic Waves Reflection Modeling A. S. Ilinskiy, T. N. Galishnikova Adv. Sci. Technol. Eng. Syst. J. 2(3), 82-87 (2017); View Description Methodology for Management of Information Security in Industrial Control Systems: A Proof of Concept aligned with Enterprise Objectives. Fabian Bustamante, Walter Fuertes, Paul Diaz, Theofilos Toulqueridis Adv. Sci. Technol. Eng. Syst. J. 2(3), 88-99 (2017); View Description Dependence-Based Segmentation Approach for Detecting Morpheme Boundaries Ahmed Khorsi, Abeer Alsheddi Adv. Sci. Technol. Eng. Syst. J. 2(3), 100-110 (2017); View Description Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language Soufiane Farrah, Hanane El Manssouri, Ziyati Elhoussaine, Mohamed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 111-115 (2017); View Description Medical imbalanced data classification Sara Belarouci, Mohammed Amine Chikh Adv. Sci. Technol. Eng. Syst. J. 2(3), 116-124 (2017); View Description ADOxx Modelling Method Conceptualization Environment Nesat Efendioglu, Robert Woitsch, Wilfrid Utz, Damiano Falcioni Adv. Sci. Technol. Eng. Syst. J. 2(3), 125-136 (2017); View Description GPSR+Predict: An Enhancement for GPSR to Make Smart Routing Decision by Anticipating Movement of Vehicles in VANETs Zineb Squalli Houssaini, Imane Zaimi, Mohammed Oumsis, Saïd El Alaoui Ouatik Adv. Sci. Technol. Eng. Syst. J. 2(3), 137-146 (2017); View Description Optimal Synthesis of Universal Space Vector Digital Algorithm for Matrix Converters Adrian Popovici, Mircea Băbăiţă, Petru Papazian Adv. Sci. Technol. Eng. Syst. J. 2(3), 147-152 (2017); View Description Control design for axial flux permanent magnet synchronous motor which operates above the nominal speed Xuan Minh Tran, Nhu Hien Nguyen, Quoc Tuan Duong Adv. Sci. Technol. Eng. Syst. J. 2(3), 153-159 (2017); View Description A synchronizing second order sliding mode control applied to decentralized time delayed multi−agent robotic systems: Stability Proof Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 160-170 (2017); View Description Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor Martin F. Pico, Eduardo J. Adam Adv. Sci. Technol. Eng. Syst. J. 2(3), 171-181 (2017); View Description Development and Validation of a Heat Pump System Model Using Artificial Neural Network Nabil Nassif, Jordan Gooden Adv. Sci. Technol. Eng. Syst. J. 2(3), 182-185 (2017); View Description Assessment of the usefulness and appeal of stigma-stop by psychology students: a serious game designed to reduce the stigma of mental illness Adolfo J. Cangas, Noelia Navarro, Juan J. Ojeda, Diego Cangas, Jose A. Piedra, José Gallego Adv. Sci. Technol. Eng. Syst. J. 2(3), 186-190 (2017); View Description Kinect-Based Moving Human Tracking System with Obstacle Avoidance Abdel Mehsen Ahmad, Zouhair Bazzal, Hiba Al Youssef Adv. Sci. Technol. Eng. Syst. J. 2(3), 191-197 (2017); View Description A security approach based on honeypots: Protecting Online Social network from malicious profiles Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi, Habiba Chaoui Adv. Sci. Technol. Eng. Syst. J. 2(3), 198-204 (2017); View Description Pulse Generator for Ultrasonic Piezoelectric Transducer Arrays Based on a Programmable System-on-Chip (PSoC) Pedro Acevedo, Martín Fuentes, Joel Durán, Mónica Vázquez, Carlos Díaz Adv. Sci. Technol. Eng. Syst. J. 2(3), 205-209 (2017); View Description Enabling Toy Vehicles Interaction With Visible Light Communication (VLC) M. A. Ilyas, M. B. Othman, S. M. Shah, Mas Fawzi Adv. Sci. Technol. Eng. Syst. J. 2(3), 210-216 (2017); View Description Analysis of Fractional-Order 2xn RLC Networks by Transmission Matrices Mahmut Ün, Manolya Ün Adv. Sci. Technol. Eng. Syst. J. 2(3), 217-220 (2017); View Description Fire extinguishing system in large underground garages Ivan Antonov, Rositsa Velichkova, Svetlin Antonov, Kamen Grozdanov, Milka Uzunova, Ikram El Abbassi Adv. Sci. Technol. Eng. Syst. J. 2(3), 221-226 (2017); View Description Directional Antenna Modulation Technique using A Two-Element Frequency Diverse Array Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 227-232 (2017); View Description Classifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks Estefanía D. Avalos-Rivera, Alberto de J. Pastrana-Palma Adv. Sci. Technol. Eng. Syst. J. 2(3), 233-240 (2017); View Description Magnetically Levitated and Guided Systems Florian Puci, Miroslav Husak Adv. Sci. Technol. Eng. Syst. J. 2(3), 241-244 (2017); View Description Energy-Efficient Mobile Sensing in Distributed Multi-Agent Sensor Networks Minh T. Nguyen Adv. Sci. Technol. Eng. Syst. J. 2(3), 245-253 (2017); View Description Validity and efficiency of conformal anomaly detection on big distributed data Ilia Nouretdinov Adv. Sci. Technol. Eng. Syst. J. 2(3), 254-267 (2017); View Description S-Parameters Optimization in both Segmented and Unsegmented Insulated TSV upto 40GHz Frequency Juma Mary Atieno, Xuliang Zhang, HE Song Bai Adv. Sci. Technol. Eng. Syst. J. 2(3), 268-276 (2017); View Description Synthesis of Important Design Criteria for Future Vehicle Electric System Lisa Braun, Eric Sax Adv. Sci. Technol. Eng. Syst. J. 2(3), 277-283 (2017); View Description Gestural Interaction for Virtual Reality Environments through Data Gloves G. Rodriguez, N. Jofre, Y. Alvarado, J. Fernández, R. Guerrero Adv. Sci. Technol. Eng. Syst. J. 2(3), 284-290 (2017); View Description Solving the Capacitated Network Design Problem in Two Steps Meriem Khelifi, Mohand Yazid Saidi, Saadi Boudjit Adv. Sci. Technol. Eng. Syst. J. 2(3), 291-301 (2017); View Description A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks Mohammad Nurul Afsar Shaon, Ken Ferens Adv. Sci. Technol. Eng. Syst. J. 2(3), 302-320 (2017); View Description Real Time Advanced Clustering System Giuseppe Spampinato, Arcangelo Ranieri Bruna, Salvatore Curti, Viviana D’Alto Adv. Sci. Technol. Eng. Syst. J. 2(3), 321-326 (2017); View Description Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors Khalid Al-Mutib, Foudil Abdessemed Adv. Sci. Technol. Eng. Syst. J. 2(3), 327-337 (2017); View Description Validity of Mind Monitoring System as a Mental Health Indicator using Voice Naoki Hagiwara, Yasuhiro Omiya, Shuji Shinohara, Mitsuteru Nakamura, Masakazu Higuchi, Shunji Mitsuyoshi, Hideo Yasunaga, Shinichi Tokuno Adv. Sci. Technol. Eng. Syst. J. 2(3), 338-344 (2017); View Description The Model of Adaptive Learning Objects for virtual environments instanced by the competencies Carlos Guevara, Jose Aguilar, Alexandra González-Eras Adv. Sci. Technol. Eng. Syst. J. 2(3), 345-355 (2017); View Description An Overview of Traceability: Towards a general multi-domain model Kamal Souali, Othmane Rahmaoui, Mohammed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 356-361 (2017); View Description L-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits Yasushi Itoh, Hiroaki Takagi Adv. Sci. Technol. Eng. Syst. J. 2(3), 362-368 (2017); View Description Moving Towards Reliability-Centred Management of Energy, Power and Transportation Assets Kang Seng Seow, Loc K. Nguyen, Kelvin Tan, Kees-Jan Van Oeveren Adv. Sci. Technol. Eng. Syst. J. 2(3), 369-375 (2017); View Description Secure Path Selection under Random Fading Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 376-383 (2017); View Description Security in SWIPT with Power Splitting Eavesdropper Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 384-388 (2017); View Description Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 389-394 (2017); View Description Adaptive Discrete-time Fuzzy Sliding Mode Control For a Class of Chaotic Systems Hanene Medhaffar, Moez Feki, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 395-400 (2017); View Description Fault Tolerant Inverter Topology for the Sustainable Drive of an Electrical Helicopter Igor Bolvashenkov, Jörg Kammermann, Taha Lahlou, Hans-Georg Herzog Adv. Sci. Technol. Eng. Syst. J. 2(3), 401-411 (2017); View Description Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid Turgay Yalcin, Muammer Ozdemir Adv. Sci. Technol. Eng. Syst. J. 2(3), 412-419 (2017); View Description A Highly-Secured Arithmetic Hiding cum Look-Up Table (AHLUT) based S-Box for AES-128 Implementation Ali Akbar Pammu, Kwen-Siong Chong, Bah-Hwee Gwee Adv. Sci. Technol. Eng. Syst. J. 2(3), 420-426 (2017); View Description Service Productivity and Complexity in Medical Rescue Services Markus Harlacher, Andreas Petz, Philipp Przybysz, Olivia Chaillié, Susanne Mütze-Niewöhner Adv. Sci. Technol. Eng. Syst. J. 2(3), 427-434 (2017); View Description Principal Component Analysis Application on Flavonoids Characterization Che Hafizah Che Noh, Nor Fadhillah Mohamed Azmin, Azura Amid Adv. Sci. Technol. Eng. Syst. J. 2(3), 435-440 (2017); View Description A Reconfigurable Metal-Plasma Yagi-Yuda Antenna for Microwave Applications Giulia Mansutti, Davide Melazzi, Antonio-Daniele Capobianco Adv. Sci. Technol. Eng. Syst. J. 2(3), 441-448 (2017); View Description Verifying the Detection Results of Impersonation Attacks in Service Clouds Sarra Alqahtani, Rose Gamble Adv. Sci. Technol. Eng. Syst. J. 2(3), 449-459 (2017); View Description Image Segmentation Using Fuzzy Inference System on YCbCr Color Model Alvaro Anzueto-Rios, Jose Antonio Moreno-Cadenas, Felipe Gómez-Castañeda, Sergio Garduza-Gonzalez Adv. Sci. Technol. Eng. Syst. J. 2(3), 460-468 (2017); View Description Segmented and Detailed Visualization of Anatomical Structures based on Augmented Reality for Health Education and Knowledge Discovery Isabel Cristina Siqueira da Silva, Gerson Klein, Denise Munchen Brandão Adv. Sci. Technol. Eng. Syst. J. 2(3), 469-478 (2017); View Description Intrusion detection in cloud computing based attack patterns and risk assessment Ben Charhi Youssef, Mannane Nada, Bendriss Elmehdi, Regragui Boubker Adv. Sci. Technol. Eng. Syst. J. 2(3), 479-484 (2017); View Description Optimal Sizing and Control Strategy of renewable hybrid systems PV-Diesel Generator-Battery: application to the case of Djanet city of Algeria Adel Yahiaoui, Khelifa Benmansour, Mohamed Tadjine Adv. Sci. Technol. Eng. Syst. J. 2(3), 485-491 (2017); View Description RFID Antenna Near-field Characterization Using a New 3D Magnetic Field Probe Kassem Jomaa, Fabien Ndagijimana, Hussam Ayad, Majida Fadlallah, Jalal Jomaah Adv. Sci. Technol. Eng. Syst. J. 2(3), 492-497 (2017); View Description Design, Fabrication and Testing of a Dual-Range XY Micro-Motion Stage Driven by Voice Coil Actuators Xavier Herpe, Matthew Dunnigan, Xianwen Kong Adv. Sci. Technol. Eng. Syst. J. 2(3), 498-504 (2017); View Description Self-Organizing Map based Feature Learning in Bio-Signal Processing Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily Adv. Sci. Technol. Eng. Syst. J. 2(3), 505-512 (2017); View Description A delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances." Advances in Science, Technology and Engineering Systems Journal 2, no. 3 (June 2016): 513–19. http://dx.doi.org/10.25046/aj020366.

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Biran, Yahav, George Collins, Borky John M, and Joel Dubow. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 24-29 (2017); View Description Zero Trust Cloud Networks using Transport Access Control and High Availability Optical Bypass Switching Casimer DeCusatis, Piradon Liengtiraphan, Anthony Sager Adv. Sci. Technol. Eng. Syst. J. 2(3), 30-35 (2017); View Description A Derived Metrics as a Measurement to Support Efficient Requirements Analysis and Release Management Indranil Nath Adv. Sci. Technol. Eng. Syst. J. 2(3), 36-40 (2017); View Description Feedback device of temperature sensation for a myoelectric prosthetic hand Yuki Ueda, Chiharu Ishii Adv. Sci. Technol. Eng. Syst. J. 2(3), 41-40 (2017); View Description Deep venous thrombus characterization: ultrasonography, elastography and scattering operator Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier Adv. Sci. Technol. Eng. Syst. J. 2(3), 48-59 (2017); View Description Improving customs’ border control by creating a reference database of cargo inspection X-ray images Selina Kolokytha, Alexander Flisch, Thomas Lüthi, Mathieu Plamondon, Adrian Schwaninger, Wicher Vasser, Diana Hardmeier, Marius Costin, Caroline Vienne, Frank Sukowski, Ulf Hassler, Irène Dorion, Najib Gadi, Serge Maitrejean, Abraham Marciano, Andrea Canonica, Eric Rochat, Ger Koomen, Micha Slegt Adv. Sci. Technol. Eng. Syst. J. 2(3), 60-66 (2017); View Description Aviation Navigation with Use of Polarimetric Technologies Arsen Klochan, Ali Al-Ammouri, Viktor Romanenko, Vladimir Tronko Adv. Sci. Technol. Eng. Syst. J. 2(3), 67-72 (2017); View Description Optimization of Multi-standard Transmitter Architecture Using Single-Double Conversion Technique Used for Rescue Operations Riadh Essaadali, Said Aliouane, Chokri Jebali and Ammar Kouki Adv. Sci. Technol. Eng. Syst. J. 2(3), 73-81 (2017); View Description Singular Integral Equations in Electromagnetic Waves Reflection Modeling A. S. Ilinskiy, T. N. Galishnikova Adv. Sci. Technol. Eng. Syst. J. 2(3), 82-87 (2017); View Description Methodology for Management of Information Security in Industrial Control Systems: A Proof of Concept aligned with Enterprise Objectives. Fabian Bustamante, Walter Fuertes, Paul Diaz, Theofilos Toulqueridis Adv. Sci. Technol. Eng. Syst. J. 2(3), 88-99 (2017); View Description Dependence-Based Segmentation Approach for Detecting Morpheme Boundaries Ahmed Khorsi, Abeer Alsheddi Adv. Sci. Technol. Eng. Syst. J. 2(3), 100-110 (2017); View Description Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language Soufiane Farrah, Hanane El Manssouri, Ziyati Elhoussaine, Mohamed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 111-115 (2017); View Description Medical imbalanced data classification Sara Belarouci, Mohammed Amine Chikh Adv. Sci. Technol. Eng. Syst. J. 2(3), 116-124 (2017); View Description ADOxx Modelling Method Conceptualization Environment Nesat Efendioglu, Robert Woitsch, Wilfrid Utz, Damiano Falcioni Adv. Sci. Technol. Eng. Syst. J. 2(3), 125-136 (2017); View Description GPSR+Predict: An Enhancement for GPSR to Make Smart Routing Decision by Anticipating Movement of Vehicles in VANETs Zineb Squalli Houssaini, Imane Zaimi, Mohammed Oumsis, Saïd El Alaoui Ouatik Adv. Sci. Technol. Eng. Syst. J. 2(3), 137-146 (2017); View Description Optimal Synthesis of Universal Space Vector Digital Algorithm for Matrix Converters Adrian Popovici, Mircea Băbăiţă, Petru Papazian Adv. Sci. Technol. Eng. Syst. J. 2(3), 147-152 (2017); View Description Control design for axial flux permanent magnet synchronous motor which operates above the nominal speed Xuan Minh Tran, Nhu Hien Nguyen, Quoc Tuan Duong Adv. Sci. Technol. Eng. Syst. J. 2(3), 153-159 (2017); View Description A synchronizing second order sliding mode control applied to decentralized time delayed multi−agent robotic systems: Stability Proof Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 160-170 (2017); View Description Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor Martin F. Pico, Eduardo J. Adam Adv. Sci. Technol. Eng. Syst. J. 2(3), 171-181 (2017); View Description Development and Validation of a Heat Pump System Model Using Artificial Neural Network Nabil Nassif, Jordan Gooden Adv. Sci. Technol. Eng. Syst. J. 2(3), 182-185 (2017); View Description Assessment of the usefulness and appeal of stigma-stop by psychology students: a serious game designed to reduce the stigma of mental illness Adolfo J. Cangas, Noelia Navarro, Juan J. Ojeda, Diego Cangas, Jose A. Piedra, José Gallego Adv. Sci. Technol. Eng. Syst. J. 2(3), 186-190 (2017); View Description Kinect-Based Moving Human Tracking System with Obstacle Avoidance Abdel Mehsen Ahmad, Zouhair Bazzal, Hiba Al Youssef Adv. Sci. Technol. Eng. Syst. J. 2(3), 191-197 (2017); View Description A security approach based on honeypots: Protecting Online Social network from malicious profiles Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi, Habiba Chaoui Adv. Sci. Technol. Eng. Syst. J. 2(3), 198-204 (2017); View Description Pulse Generator for Ultrasonic Piezoelectric Transducer Arrays Based on a Programmable System-on-Chip (PSoC) Pedro Acevedo, Martín Fuentes, Joel Durán, Mónica Vázquez, Carlos Díaz Adv. Sci. Technol. Eng. Syst. J. 2(3), 205-209 (2017); View Description Enabling Toy Vehicles Interaction With Visible Light Communication (VLC) M. A. Ilyas, M. B. Othman, S. M. Shah, Mas Fawzi Adv. Sci. Technol. Eng. Syst. J. 2(3), 210-216 (2017); View Description Analysis of Fractional-Order 2xn RLC Networks by Transmission Matrices Mahmut Ün, Manolya Ün Adv. Sci. Technol. Eng. Syst. J. 2(3), 217-220 (2017); View Description Fire extinguishing system in large underground garages Ivan Antonov, Rositsa Velichkova, Svetlin Antonov, Kamen Grozdanov, Milka Uzunova, Ikram El Abbassi Adv. Sci. Technol. Eng. Syst. J. 2(3), 221-226 (2017); View Description Directional Antenna Modulation Technique using A Two-Element Frequency Diverse Array Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 227-232 (2017); View Description Classifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks Estefanía D. Avalos-Rivera, Alberto de J. Pastrana-Palma Adv. Sci. Technol. Eng. Syst. J. 2(3), 233-240 (2017); View Description Magnetically Levitated and Guided Systems Florian Puci, Miroslav Husak Adv. Sci. Technol. Eng. Syst. J. 2(3), 241-244 (2017); View Description Energy-Efficient Mobile Sensing in Distributed Multi-Agent Sensor Networks Minh T. Nguyen Adv. Sci. Technol. Eng. Syst. J. 2(3), 245-253 (2017); View Description Validity and efficiency of conformal anomaly detection on big distributed data Ilia Nouretdinov Adv. Sci. Technol. Eng. Syst. J. 2(3), 254-267 (2017); View Description S-Parameters Optimization in both Segmented and Unsegmented Insulated TSV upto 40GHz Frequency Juma Mary Atieno, Xuliang Zhang, HE Song Bai Adv. Sci. Technol. Eng. Syst. J. 2(3), 268-276 (2017); View Description Synthesis of Important Design Criteria for Future Vehicle Electric System Lisa Braun, Eric Sax Adv. Sci. Technol. Eng. Syst. J. 2(3), 277-283 (2017); View Description Gestural Interaction for Virtual Reality Environments through Data Gloves G. Rodriguez, N. Jofre, Y. Alvarado, J. Fernández, R. Guerrero Adv. Sci. Technol. Eng. Syst. J. 2(3), 284-290 (2017); View Description Solving the Capacitated Network Design Problem in Two Steps Meriem Khelifi, Mohand Yazid Saidi, Saadi Boudjit Adv. Sci. Technol. Eng. Syst. J. 2(3), 291-301 (2017); View Description A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks Mohammad Nurul Afsar Shaon, Ken Ferens Adv. Sci. Technol. Eng. Syst. J. 2(3), 302-320 (2017); View Description Real Time Advanced Clustering System Giuseppe Spampinato, Arcangelo Ranieri Bruna, Salvatore Curti, Viviana D’Alto Adv. Sci. Technol. Eng. Syst. J. 2(3), 321-326 (2017); View Description Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors Khalid Al-Mutib, Foudil Abdessemed Adv. Sci. Technol. Eng. Syst. J. 2(3), 327-337 (2017); View Description Validity of Mind Monitoring System as a Mental Health Indicator using Voice Naoki Hagiwara, Yasuhiro Omiya, Shuji Shinohara, Mitsuteru Nakamura, Masakazu Higuchi, Shunji Mitsuyoshi, Hideo Yasunaga, Shinichi Tokuno Adv. Sci. Technol. Eng. Syst. J. 2(3), 338-344 (2017); View Description The Model of Adaptive Learning Objects for virtual environments instanced by the competencies Carlos Guevara, Jose Aguilar, Alexandra González-Eras Adv. Sci. Technol. Eng. Syst. J. 2(3), 345-355 (2017); View Description An Overview of Traceability: Towards a general multi-domain model Kamal Souali, Othmane Rahmaoui, Mohammed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 356-361 (2017); View Description L-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits Yasushi Itoh, Hiroaki Takagi Adv. Sci. Technol. Eng. Syst. J. 2(3), 362-368 (2017); View Description Moving Towards Reliability-Centred Management of Energy, Power and Transportation Assets Kang Seng Seow, Loc K. Nguyen, Kelvin Tan, Kees-Jan Van Oeveren Adv. Sci. Technol. Eng. Syst. J. 2(3), 369-375 (2017); View Description Secure Path Selection under Random Fading Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 376-383 (2017); View Description Security in SWIPT with Power Splitting Eavesdropper Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 384-388 (2017); View Description Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 389-394 (2017); View Description Adaptive Discrete-time Fuzzy Sliding Mode Control For a Class of Chaotic Systems Hanene Medhaffar, Moez Feki, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 395-400 (2017); View Description Fault Tolerant Inverter Topology for the Sustainable Drive of an Electrical Helicopter Igor Bolvashenkov, Jörg Kammermann, Taha Lahlou, Hans-Georg Herzog Adv. Sci. Technol. Eng. Syst. J. 2(3), 401-411 (2017); View Description Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid Turgay Yalcin, Muammer Ozdemir Adv. Sci. Technol. Eng. Syst. J. 2(3), 412-419 (2017); View Description A Highly-Secured Arithmetic Hiding cum Look-Up Table (AHLUT) based S-Box for AES-128 Implementation Ali Akbar Pammu, Kwen-Siong Chong, Bah-Hwee Gwee Adv. Sci. Technol. Eng. Syst. J. 2(3), 420-426 (2017); View Description Service Productivity and Complexity in Medical Rescue Services Markus Harlacher, Andreas Petz, Philipp Przybysz, Olivia Chaillié, Susanne Mütze-Niewöhner Adv. Sci. Technol. Eng. Syst. J. 2(3), 427-434 (2017); View Description Principal Component Analysis Application on Flavonoids Characterization Che Hafizah Che Noh, Nor Fadhillah Mohamed Azmin, Azura Amid Adv. Sci. Technol. Eng. Syst. J. 2(3), 435-440 (2017); View Description A Reconfigurable Metal-Plasma Yagi-Yuda Antenna for Microwave Applications Giulia Mansutti, Davide Melazzi, Antonio-Daniele Capobianco Adv. Sci. Technol. Eng. Syst. J. 2(3), 441-448 (2017); View Description Verifying the Detection Results of Impersonation Attacks in Service Clouds Sarra Alqahtani, Rose Gamble Adv. Sci. Technol. Eng. Syst. J. 2(3), 449-459 (2017); View Description Image Segmentation Using Fuzzy Inference System on YCbCr Color Model Alvaro Anzueto-Rios, Jose Antonio Moreno-Cadenas, Felipe Gómez-Castañeda, Sergio Garduza-Gonzalez Adv. Sci. Technol. Eng. Syst. J. 2(3), 460-468 (2017); View Description Segmented and Detailed Visualization of Anatomical Structures based on Augmented Reality for Health Education and Knowledge Discovery Isabel Cristina Siqueira da Silva, Gerson Klein, Denise Munchen Brandão Adv. Sci. Technol. Eng. Syst. J. 2(3), 469-478 (2017); View Description Intrusion detection in cloud computing based attack patterns and risk assessment Ben Charhi Youssef, Mannane Nada, Bendriss Elmehdi, Regragui Boubker Adv. Sci. Technol. Eng. Syst. J. 2(3), 479-484 (2017); View Description Optimal Sizing and Control Strategy of renewable hybrid systems PV-Diesel Generator-Battery: application to the case of Djanet city of Algeria Adel Yahiaoui, Khelifa Benmansour, Mohamed Tadjine Adv. Sci. Technol. Eng. Syst. J. 2(3), 485-491 (2017); View Description RFID Antenna Near-field Characterization Using a New 3D Magnetic Field Probe Kassem Jomaa, Fabien Ndagijimana, Hussam Ayad, Majida Fadlallah, Jalal Jomaah Adv. Sci. Technol. Eng. Syst. J. 2(3), 492-497 (2017); View Description Design, Fabrication and Testing of a Dual-Range XY Micro-Motion Stage Driven by Voice Coil Actuators Xavier Herpe, Matthew Dunnigan, Xianwen Kong Adv. Sci. Technol. Eng. Syst. J. 2(3), 498-504 (2017); View Description Self-Organizing Map based Feature Learning in Bio-Signal Processing Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily Adv. Sci. Technol. Eng. Syst. J. 2(3), 505-512 (2017); View Description A delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances Fatma Abdelhedi, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 513-519 (2017); View Description Modelization of cognition, activity and motivation as indicators for Interactive Learning Environment Asmaa Darouich, Faddoul Khoukhi, Khadija Douzi Adv. Sci. Technol. Eng. Syst. J. 2(3), 520-531 (2017); View Description Homemade array of surface coils implementation for small animal magnetic resonance imaging Fernando Yepes-Calderon, Olivier Beuf Adv. Sci. Technol. Eng. Syst. J. 2(3), 532-539 (2017); View Description An Encryption Key for Secure Authentication: The Dynamic Solution Zubayr Khalid, Pritam Paul, Khabbab Zakaria, Himadri Nath Saha Adv. Sci. Technol. Eng. Syst. J. 2(3), 540-544 (2017); View Description Multi-Domain Virtual Network Embedding with Coordinated Link Mapping Shuopeng Li, Mohand Yazid Saidi, Ken Chen Adv. Sci. Technol. Eng. Syst. J. 2(3), 545-552 (2017); View Description Semantic-less Breach Detection of Polymorphic Malware in Federated Cloud." Advances in Science, Technology and Engineering Systems Journal 2, no. 3 (June 2017): 553–61. http://dx.doi.org/10.25046/aj020371.

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Yang, Xiaomin, Yongbing Xiang, and Bingzhen Jiang. "On multi-fault detection of rolling bearing through probabilistic principal component analysis denoising and Higuchi fractal dimension transformation." Journal of Vibration and Control, February 1, 2021, 107754632198952. http://dx.doi.org/10.1177/1077546321989527.

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Bearing multi-fault detection from stochastic vibration signal is still a thorny task to dispose of because of the complex interplay between different fault components under severe noise interference. In such case, conventional techniques such as filter processing and envelope demodulation may cause undesired results. To overcome the limitation, this article explores a filtering-free technique combined probabilistic principal component analysis denoising with the Higuchi fractal dimension transformation to diagnose the bearing multi-faults. Fractal theory is used to optimize the model parameters and stabilize the random vibrational signal for fast Fourier transform spectrum analysis. Noise interference in the Higuchi transformation is capped using a probabilistic principal component analysis model whose parameters are optimized through embedding dimension Cao algorithm and correlation dimension Grassberger and Procaccia algorithm. The fault diagnostic scheme mainly falls into three steps. First, the original vibration signal is truncated into a series of sub-signal segments by moving window whose length is determined as twice the value of maximum time delay that is provided by examining the steady Higuchi fractal dimension value of a raw signal in a process of plotting the fractal dimension over a range of time delay. Then, the Higuchi approach is used to estimate the average fractal dimension for each segment to create a quasi-stationary Higuchi fractal dimension sequence on which, finally, the fault features are straightforwardly extracted by the fast Fourier transform algorithm. The effectiveness of the proposed method is validated using simulated and experimental compound bearing fault vibration signals. Some fault components may be clouded if applied Higuchi fractal dimension alone because of the noise interference, but using the probabilistic principal component analysis–Higuchi fractal dimension method leads to clear diagnostic results. It indicates that the proposed approach can be incorporated into bearing multi-fault extraction from raw vibration signals.

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Radhakrishnan, Menaka, Daehan Won, Thanga Aarthy Manoharan, Varsha Venkatachalam, Renuka Mahadev Chavan, and Harathi Devi Nalla. "Investigating electroencephalography signals of autism spectrum disorder (ASD) using Higuchi Fractal Dimension." Biomedical Engineering / Biomedizinische Technik, August 31, 2020. http://dx.doi.org/10.1515/bmt-2019-0313.

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AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder with a deficit of social relationships, interaction, sense of imagination, and constrained interests. Early diagnosis of ASD will aid in devising appropriate training procedures and placing those children in the normal stream. The objective of this research is to analyze the brain response for auditory/visual stimuli in Typically Developing (TD) and children with autism through electroencephalography (EEG). Brain dynamics in the EEG signal can be analyzed well with the help of nonlinear feature primitives. Recent research reveals that, application of fractal-based techniques proves to be effective to estimate of degree of nonlinearity in a signal. This research attempts to analyze the effect of brain dynamics with Higuchi Fractal Dimension (HFD). Also, the performance of the fractal based techniques depends on the selection of proper hyper-parameters involved in it. One of the key parameters involved in computation of HFD is the time interval parameter ‘k’. Most of the researches arbitrarily fixes the value of ‘k’ in the range of all channels. This research proposes an algorithm to estimate the optimal value of the time parameter for each channel. Sub-band analysis was also carried out for the responding channels. Statistical analysis on the experimental reveals that a difference of 30% was observed between autistic and Typically Developing children.

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Borri, Alessandro, Antonio Cerasa, Paolo Tonin, Luigi Citrigno, and Camillo Porcaro. "Characterizing Fractal Genetic Variation in the Human Genome from the Hapmap Project." International Journal of Neural Systems, May 12, 2022. http://dx.doi.org/10.1142/s0129065722500289.

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Over the last decades, the exuberant development of next-generation sequencing has revolutionized gene discovery. These technologies have boosted the mapping of single nucleotide polymorphisms (SNPs) across the human genome, providing a complex universe of heterogeneity characterizing individuals worldwide. Fractal dimension (FD) measures the degree of geometric irregularity, quantifying how “complex” a self-similar natural phenomenon is. We compared two FD algorithms, box-counting dimension (BCD) and Higuchi’s fractal dimension (HFD), to characterize genome-wide patterns of SNPs extracted from the HapMap data set, which includes data from 1184 healthy subjects of eleven populations. In addition, we have used cluster and classification analysis to relate the genetic distances within chromosomes based on FD similarities to the geographical distances among the 11 global populations. We found that HFD outperformed BCD at both grand average clusterization analysis by the cophenetic correlation coefficient, in which the closest value to 1 represents the most accurate clustering solution (0.981 for the HFD and 0.956 for the BCD) and classification (79.0% accuracy, 61.7% sensitivity, and 96.4% specificity for the HFD with respect to 69.1% accuracy, 43.2% sensitivity, and 94.9% specificity for the BCD) of the 11 populations present in the HapMap data set. These results support the evidence that HFD is a reliable measure helpful in representing individual variations within all chromosomes and categorizing individuals and global populations.

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Inayat, Samsoon, Surjeet Singh, Arashk Ghasroddashti, Qandeel, Pramuka Egodage, Ian Q. Whishaw, and Majid H. Mohajerani. "A Matlab-based toolbox for characterizing behavior of rodents engaged in string-pulling." eLife 9 (June 26, 2020). http://dx.doi.org/10.7554/elife.54540.

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String-pulling by rodents is a behavior in which animals make rhythmical body, head, and bilateral forearm as well as skilled hand movements to spontaneously reel in a string. Typical analysis includes kinematic assessment of hand movements done by manually annotating frames. Here, we describe a Matlab-based software that allows whole-body motion characterization using optical flow estimation, descriptive statistics, principal component, and independent component analyses as well as temporal measures of Fano factor, entropy, and Higuchi fractal dimension. Based on image-segmentation and heuristic algorithms for object tracking, the software also allows tracking of body, ears, nose, and forehands for estimation of kinematic parameters such as body length, body angle, head roll, head yaw, head pitch, and path and speed of hand movements. The utility of the task and software is demonstrated by characterizing postural and hand kinematic differences in string-pulling behavior of two strains of mice, C57BL/6 and Swiss Webster.

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Amrabadi, Touraj, Elham Jalilnejad, Seyed Mohammad Amin Ojagh, and Farzaneh Vahabzadeh. "Application of TOPSIS algorithm in describing bacterial cellulose-based composite hydrogel performance in incorporating methylene blue as a model drug." Scientific Reports 13, no. 1 (February 16, 2023). http://dx.doi.org/10.1038/s41598-023-29865-6.

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AbstractA multi-component hydrogel was developed using bacterial cellulose, alginate, and gelatin with the aid of glycerol as trihydric alcohol which participates in re-distribution of hydrogen bonds in the test system. FTIR, XRD, SEM, and TGA as instrumental techniques were used to structurally characterize the physical/chemical properties of the formed composite hydrogel. By using an exponential equation, swelling behavior of the hydrogel was evaluated. By incorporating a model drug (methylene blue—MB) in the formed hydrogel, experiments were directed to study release characteristics of the MB where the medium solution for the release was prepared at four different pHs. The maximum cumulative drug release at pH 2.8, 6, 7.4, and 9 were 42.8, 63, 80, and 84.5%, respectively. Data fitting process was carried out using five kinetic models (Korsmeyer-Peppas, Higuchi, Hopfenberg, zero-order, and first-order equations) and the preferred kinetic model at each pH was estimated by applying TOPSIS algorithmic technique. The adsorption capacity of the hydrogel in relation to MB was determined while thermodynamic properties of this relationship were quantified ($$\Delta{\text{H}}_{\text{ad}}^{0}= \text{ } -\text{99.95 kJ} \, {\text{mo}}{\text{l}}^{-{1}}$$ Δ H ad 0 = - 99.95 kJ mol - 1 and $$\Delta{\text{S}}_{\text{ad}}^{0}= -\text{0.237 kJ} \, {\text{mo}}{\text{l}}^{-{1}} {\text{K}}^{-{1}}$$ Δ S ad 0 = - 0.237 kJ mol - 1 K - 1 ). The results of the present study were in favor of the potential usage of the developed composite hydrogel in drug delivery systems.

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Torabi, Ali, and Mohammad Reza Daliri. "Applying nonlinear measures to the brain rhythms: an effective method for epilepsy diagnosis." BMC Medical Informatics and Decision Making 21, no. 1 (September 24, 2021). http://dx.doi.org/10.1186/s12911-021-01631-6.

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Abstract Background Epilepsy is a neurological disorder from which almost 50 million people have been suffering. These statistics indicate the importance of epilepsy diagnosis. Electroencephalogram (EEG) signals analysis is one of the most common methods for epilepsy characterization; hence, various strategies were applied to classify epileptic EEGs. Methods In this paper, four different nonlinear features such as Fractal dimensions including Higuchi method (HFD) and Katz method (KFD), Hurst exponent, and L-Z complexity measure were extracted from EEGs and their frequency sub-bands. The features were ranked later by implementing Relieff algorithm. The ranked features were applied sequentially to three different classifiers (MLPNN, Linear SVM, and RBF SVM). Results According to the dataset used for this study, there are five classification problems named ABCD/E, AB/CD/E, A/D/E, A/E, and D/E. In all cases, MLPNN was the most accurate classifier. Its performances for mentioned classification problems were 99.91%, 98.19%, 98.5%, 100% and 99.84%, respectively. Conclusion The results demonstrate that KFD is the highest-ranking feature; In addition, beta and theta sub-bands are the most important frequency bands because, for all cases, the top features were KFDs extracted from beta and theta sub-bands. Moreover, high levels of accuracy have been obtained just by using these two features which reduce the complexity of the classification.

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"Mathematical Modeling of Stress Using Fractal Geometry; The Power Laws and Fractal Complexity of Stress." Advances in Neurology and Neuroscience 5, no. 3 (August 30, 2022). http://dx.doi.org/10.33140/an.05.03.04.

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In this study, we analyze the physiological data during real-world driving tasks to determine whether driver’s relative stress is mono-fractal or multi-fractal. We use the PhysioNet database including long term ECG recordings from 15 healthy volunteers, taken while they were driving on a prescribed route including city streets and highways in and around Boston, Massachusetts. The vibration analysis such as power spectral densities (PSD) analysis has been performed to estimate the exponent from realizations of these pro- cesses and to find out if the signal of interest exhibits a power-law PSD. Multifractal dynamics of heartbeat interval signals have been assessed by multifractal spectrum analysis to explore the possibility that ECG recordings belong to class of multi-fractal process for which a large number of scaling exponents are re- quired to characterize their scaling structures. We apply Higuchi algorithm to find the fractal complexity of each cardiac rhythm for different time intervals. According to our analysis, we investigate that driver’s ECG signals under relative stress follows fractal behavior unlike control healthy signals which are multi-fractal. Our findings provide a comprehensive framework for detect stress and differentiate people who experience stress with normal people without stress which is crucial in finding the best diagnostic and controlling strat- egy in fight against many health problems due to stress, such as high blood pressure, heart disease, obesity and diabetes. Moreover, being able to recognize stress can help us to manage it.

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Moctezuma, Luis Alfredo, and Marta Molinas. "Towards a minimal EEG channel array for a biometric system using resting-state and a genetic algorithm for channel selection." Scientific Reports 10, no. 1 (September 10, 2020). http://dx.doi.org/10.1038/s41598-020-72051-1.

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Abstract We present a new approach for a biometric system based on electroencephalographic (EEG) signals of resting-state, that can identify a subject and reject intruders with a minimal subset of EEG channels. To select features, we first use the discrete wavelet transform (DWT) or empirical mode decomposition (EMD) to decompose the EEG signals into a set of sub-bands, for which we compute the instantaneous and Teager energy and the Higuchi and Petrosian fractal dimensions for each sub-band. The obtained features are used as input for the local outlier factor (LOF) algorithm to create a model for each subject, with the aim of learning from it and rejecting instances not related to the subject in the model. In search of a minimal subset of EEG channels, we used a channel-selection method based on the non-dominated sorting genetic algorithm (NSGA)-III, designed with the objectives of minimizing the required number EEG channels and increasing the true acceptance rate (TAR) and true rejection rate (TRR). This method was tested on EEG signals from 109 subjects of the public motor movement/imagery dataset (EEGMMIDB) using the resting-state with the eyes-open and the resting-state with the eyes-closed. We were able to obtain a TAR of $$1.000 \pm 0.000$$ 1.000 ± 0.000 and TRR of $$0.998 \pm 0.001$$ 0.998 ± 0.001 using 64 EEG channels. More importantly, with only three channels, we were able to obtain a TAR of up to $$0.993 \pm 0.01$$ 0.993 ± 0.01 and a TRR of up to $$0.941 \pm 0.002$$ 0.941 ± 0.002 for the Pareto-front, using NSGA-III and DWT-based features in the resting-state with the eyes-open. In the resting-state with the eyes-closed, the TAR was $$0.997 \pm 0.02$$ 0.997 ± 0.02 and the TRR $$0.950 \pm 0.05,$$ 0.950 ± 0.05 , also using DWT-based features from three channels. These results show that our approach makes it possible to create a model for each subject using EEG signals from a reduced number of channels and reject most instances of the other 108 subjects, who are intruders in the model of the subject under evaluation. Furthermore, the candidates obtained throughout the optimization process of NSGA-III showed that it is possible to obtain TARs and TRRs above 0.900 using LOF and DWT- or EMD-based features with only one to three EEG channels, opening the way to testing this approach on bigger datasets to develop a more realistic and usable EEG-based biometric system.

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Rykhalska, Anna Kostiantynivna, Kateryna Olehivna Ivanko, Nataliia Heorhiivna Ivanushkina, and Dmytro Olehovych Ivanko. "Detection of Episodes of Sleep Apnea and Hypopnea in ECG and EEG Signals by Machine Learning." Microsystems, Electronics and Acoustics 27, no. 1 (April 29, 2022). http://dx.doi.org/10.20535/2523-4455.mea.251487.

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The article is devoted to the application of machine learning methods for computerized detection of sleep apnea episodes based on the analysis of single-channel signals of the electrocardiogram (ECG) and electroencephalogram (EEG). To study the possibilities of machine learning to detect apnea based on ECG and EEG analysis, we used Apnea-ECG database and MIT-BIH polysomnographic database from PhysioNet, which contain annotations to each minute of records indicating the presence or absence of apnea/hypopnea at the current time. In order to apply machine learning methods to the problem of automated detection of sleep apnea/hypopnea episodes in ECG and EEG signals, long-term polysomnograms available in MIT-BIH polysomnographic database were segmented according to annotations into shorter sections lasting 30 seconds each. The study used 267 segments lasting 30 seconds for the class "norm", 258 segments for the class "apnea" and 273 segments for the class "hypopnea", a total of 798 simultaneous ECG and EEG recordings. The aim of this work is to identify and compare informative signs of sleep apnea episodes in terms of heart rate variability (HRV) and brain electrical activity, as well as the choice of classification methods that provide the highest accuracy for this task. Features of cardiorhythmograms in time and frequency domains, spectral-temporal and wavelet characteristics, as well as parameters of EEG signals based on energy ratio of EEG rhythms, Hearst index, Higuchi fractal dimension and sample entropy for EEG signals are considered. Using different sets of features, the accuracy of classifiers based on decision trees, discriminant analysis, support vector machines, k-nearest neighbor method, and ensemble training was determined. Based on this, combination of features and classifiers is proposed, which provides the highest accuracy of recognition of sleep apnea episodes according to single-channel ECG and EEG signals, taken separately and in the case of a combination of their features. The best results of classification of signals "norm", "apnea" and "hypopnea" were obtained for the model trained using weighted method k nearest neighbors with 25 features of HRV: the total percentage of correctly identified cases for three classes was 99.9% (797 correctly identified cases of 798). By reducing the number of HRV parameters to 9, the best machine learning result was achieved using the bagging ensemble algorithm with 30 decision trees: the total percentage of correctly identified cases for all three classes was 99.4% (793 correctly identified cases from 798: for "norm" - 265 cases from 267, for "apnea" - 257 cases from 258, for "hypopnea" - 271 cases from 273). The use of EEG parameters as features for apnea/hypopnea recognition showed worse results compared to HRV parameters. In this case, the best result of machine learning was achieved using support vector machines with quadratic kernel function: the total percentage of correctly identified cases for three classes was 91.9% and the signals corresponding to norm were most badly recognized (27 cases were classified as hypopnea, and in 9 cases - as sleep apnea). The combination of HRV and EEG parameters gave the best accuracy of 99.1%, but the results are comparable to using only HRV parameters. The obtained results indicate that HRV parameters allow recognizing sleep apnea and hypopnea with higher accuracy than EEG parameters, but EEG signal undoubtedly reflects signs of sleep apnea/hypopnea and also can be used for apnea recognition.

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Journal articles on the topic 'Higuchi's algorithm'

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