Search results for: physiological signal

Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Radyah Ivan, Khanferyan Roman

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Milk and dairy products are an important component of a balanced diet. Dairy products represent a heterogeneous food group of solid, semi-solid and liquid, fermented or non-fermented foods, each differing in nutrients such as fat and micronutrient content. Deficiency of milk and dairy products contributes a impact on the main health parameters of the various age groups of the population. The goal of this study was to analyze of the frequency of the consumption of milk and various groups of dairy products by students and its association with their body mass index (BMI), body composition and other physiological parameters. 388 full-time students of the Medical Institute of RUDN University (185 male and 203 female, average age was 20.4+2.2 and 21.9+1.7 y.o., respectively) took part in the cross-sectional study. Anthropometric measurements, estimation of BMI and body composition were analyzed by bioelectrical impedance analysis. The frequency of consumption of the milk and various groups of dairy products was studied using a modified questionnaire on the frequency of consumption of products. Due to the questionnaire data on the frequency of consumption of the diary products, it have been demonstrated that only 11% of respondents consume milk daily, 5% - cottage cheese, 4% and 1% - fermented natural and with fillers milk products, respectively, hard cheese -4%. The study demonstrated that about 16% of the respondents did not consume milk at all over the past month, about one third - cottage cheese, 22% - natural sour-milk products and 18% - sour-milk products with various fillers. hard cheeses and pickled cheeses didn’t consume 9% and 26% of respondents, respectively. We demonstrated the gender differences in the characteristics of consumer preferences were revealed. Thus female students are less likely to use cream, sour cream, soft cheese, milk comparing to male students. Among female students the prevalence of persons with overweight was higher (25%) than among male students (19%). A modest inverse relationship was demonstrated between daily milk intake, BMI, body composition parameters and diary products consumption (r=-0.61 and r=-0.65). The study showed daily insufficient milk and dairy products consumption by students and due to this it have been demonstrated the relationship between the low and rare consumption of diary products and main parameters of indicators of physical activity and health indicators.

Keywords: frequency of consumption, milk, dairy products, physical development, nutrition, body mass index.

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Authors: Sathish Kumar Jayaraj

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The study of urban traffic dynamics, underpinned by the principles of fluid dynamics, offers a distinct perspective to comprehend and enhance the efficiency of traffic flow within bustling cityscapes. Leveraging the concept of the Traffic Flow Factor (TFF) as an analog to the Reynolds number, this research delves into the intricate interplay between traffic density, velocity, and road category, drawing compelling parallels to fluid dynamics phenomena. By introducing the notion of Vehicle Shearing Resistance (VSR) as an analogy to dynamic viscosity, the study sheds light on the multifaceted influence of traffic regulations, lane management, and road infrastructure on the smoothness and resilience of traffic flow. The TFF equation serves as a comprehensive metric for quantifying traffic dynamics, enabling the identification of congestion hotspots, the optimization of traffic signal timings, and the formulation of data-driven traffic management strategies. The study underscores the critical significance of integrating fluid dynamics principles into the domain of urban traffic management, fostering sustainable transportation practices, and paving the way for a more seamless and resilient urban mobility ecosystem.

Keywords: traffic flow factor (TFF), urban traffic dynamics, fluid dynamics principles, vehicle shearing resistance (VSR), traffic congestion management, sustainable urban mobility

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Authors: Pawan Kumar, Dhananjoy Shaw

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Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats and is alterable with fitness, age and different medical conditions including withdrawal/retirement from games/sports. Objectives of the study were to develop (a) percentile norms of heart rate variability (HRV) variables derived from time domain analysis of the Indian sportspersons withdrawn from competitive games/sports pertaining to sympathetic and parasympathetic activity (b) percentile norms of heart rate variability (HRV) variables derived from frequency domain analysis of the Indian sportspersons withdrawn from competitive games/sports pertaining to sympathetic and parasympathetic activity. The study was conducted on 430 males. Ages of the sample ranged from 30 to 35 years of same socio-economic status. Date was collected using ECG polygraphs. Data were processed and extracted using frequency domain analysis and time domain analysis. Collected data were computed with percentile from one to hundred. The finding showed that the percentile norms of heart rate variability (HRV) variables derived from time domain analysis of the Indian sportspersons withdrawn from competitive games/sports pertaining to sympathetic and parasympathetic activity namely, NN50 count (ranged from 1 to 189 score as percentile range). pNN50 count (ranged from .24 to 60.80 score as percentile range). SDNN (ranged from 17.34 to 167.29 score as percentile range). SDSD (ranged from 11.14 to 120.46 score as percentile range). RMMSD (ranged from 11.19 to 120.24 score as percentile range) and SDANN (ranged from 4.02 to 88.75 score as percentile range). The percentile norms of heart rate variability (HRV) variables derived from frequency domain analysis of the Indian sportspersons withdrawn from competitive games/sports pertaining to sympathetic and parasympathetic activity namely Low Frequency (Normalized Power) ranged from 20.68 to 90.49 score as percentile range. High Frequency (Normalized Power) ranged from 14.37 to 81.60 score as percentile range. LF/ HF ratio(ranged from 0.26 to 9.52 score as percentile range). LF (Absolute Power) ranged from 146.79 to 5669.33 score as percentile range. HF (Absolute Power) ranged from 102.85 to 10735.71 score as percentile range and Total Power (Absolute Power) ranged from 471.45 to 25879.23 score as percentile range. Conclusion: The analysis documented percentile norms for time domain analysis and frequency domain analysis for versatile use and evaluation.

Keywords: RMSSD, Percentile, SDANN, HF, LF

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Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

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In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

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Authors: Toumi Farah, Charallah Salima

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In the Algerian Sahara, goat farming is predominant, and it’s associated with other types of breeding, particularly camel and sheep; it also constitutes a significant proportion of breeding exclusively goat. This Saharan goat is a small ruminant with a black dress with white’s spots, hanging ears, and a coat more or less long. It is known for its hardiness and resistance to adverse conditions of arid zones and its perfect ecophysiological adaptation to harsh environmental conditions. However, pregnancy alterations, particularly abortion, degrade its productivity and cause economic losses, having both direct and indirect effects on animal production, like the costs of veterinary interventions and the reconstitution of livestock. The purpose of this work is to study the histological aspect of the liver of goats’ aborted living under nomadic herds in the region of Béni-Abbès (30° 7' N, 2° 10 'O). The organs were collected in physiological serum, rinsed, and then fixed with formaldehyde (37°, diluted at 10%). After that, these samples were processed for a topographic study. The morphometric study of the liver was performed by using an image analysis and processing software "Image J"; the various measurements obtained are intended to specify the supposed stage of development according to the body weight. The histological structure of the liver shows that the hepatic parenchyma consists of vascular conjunctive spaces surrounded by Glisson’s capsule. The sinusoids and hepatic portal vein are full of red blood cells, representing sinusoidal congestion and a thrombosed vein. At high magnification, the blood vessels show the presence of vascular thrombosis and haemorrhage in some areas of the hepatic parenchyma. Morphometric analysis shows that the number of liver parenchymal cells and the diameter of liver vessels vary according to the stage of development. The results obtained will provide details of the anatomical and cellular elements that can be used in the diagnosis of early or late abortion and late embryonic death. It would be interesting to find, by immunohistochemistry, some inflammatory markers useful for monitoring the progress of pregnancy and bioindicators of fetomaternal distress.

Keywords: aborting goat, arid zone, liver, histopathology

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Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

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Authors: E. Ormeno, C. Gutigny, J. Ruffault, J. Madrigal, M. Guijarro, C. Lecareux, C. Ballini

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Mediterranean plant species feature numerous metabolic and morpho-physiological responses crucial to survive under both, typical Mediterranean drought conditions and future aggravated drought expected by climate change. Whether these adaptive responses will, in turn, increase the ecosystem perturbation in terms of fire hazard, is an issue that needs to be addressed. The aim of this study was to test whether recurrent and aggravated drought in the Mediterranean area favors the accumulation of waxes in leaf litter, with an eventual increase of litter flammability. The study was conducted in 2017 in a garrigue in Southern France dominated by Quercus coccifera, where two drought treatments were used: a treatment with recurrent aggravated drought consisting of ten rain exclusion structures which withdraw part of the annual precipitation since January 2012, and a natural drought treatment where Q. coccifera stands are free of such structures and thus grow under natural precipitation. Waxes were extracted with organic solvent and analyzed by GC-MS and litter flammability was assessed through measurements of the ignition delay, flame residence time and flame intensity (flame height) using an epiradiator as well as the heat of combustion using an oxygen bomb calorimeter. Results show that after 5 years of rain restriction, wax content in the cuticle of leaf litter increases significantly compared to shrubs growing under natural precipitation, in accordance with the theoretical knowledge which expects increases of cuticle waxes in green leaves in order to limit water evapotranspiration. Wax concentrations were also linearly and positively correlated to litter flammability, a correlation that lies on the high flammability own to the long-chain alkanes (C25-C31) found in leaf litter waxes. This innovative investigation shows that climate change is likely to favor ecosystem fire hazard through accumulation of highly flammable waxes in litter. It also adds valuable information about the types of metabolites that are associated with increasing litter flammability, since so far, within the leaf metabolic profile, only terpene-like compounds had been related to plant flammability.

Keywords: cuticular waxes, drought, flammability, litter

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

Procedia PDF Downloads 178

Authors: Noura El-Ahmady El-Naggar

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L-asparaginase is an important enzyme as therapeutic agents used in combination therapy with other drugs in the treatment of acute lymphoblastic leukemia in children. L-asparaginase producing actinomycete strain, NEAE-K, was isolated from soil sample and identified on the basis of morphological, cultural, physiological and biochemical properties, together with 16S rDNA sequence as new subsp. Streptomyces rochei subsp. chromatogenes NEAE-K and sequencing product (1532 bp) was deposited in the GenBank database under accession number KJ200343. The study was conducted to screen parameters affecting the production of L-asparaginase by Streptomyces rochei subsp. chromatogenes NEAE-K on solid state fermentation using Plackett–Burman experimental design. Sixteen different independent variables including incubation time, moisture content, inoculum size, temperature, pH, soybean meal+ wheat bran, dextrose, fructose, L-asparagine, yeast extract, KNO3, K2HPO4, MgSO4.7H2O, NaCl, FeSO4. 7H2O, CaCl2, and three dummy variables were screened in Plackett–Burman experimental design of 20 trials. The most significant independent variables affecting enzyme production (dextrose, L-asparagine and K2HPO4) were further optimized by the central composite design. As a result, a medium of the following formula is the optimum for producing an extracellular L-asparaginase by Streptomyces rochei subsp. chromatogenes NEAE-K from solid state fermentation: g/L (soybean meal+ wheat bran 15, dextrose 3, fructose 4, L-asparagine 8, yeast extract 2, KNO3 1, K2HPO4 2, MgSO4.7H2O 0.5, NaCl 0.1, FeSO4. 7H2O 0.02, CaCl2 0.01), incubation time 7 days, moisture content 50%, inoculum size 3 mL, temperature 30°C, pH 8.5.

Keywords: streptomyces rochei subsp. chromatogenes neae-k, 16s rrna, identification, solid state fermentation, l-asparaginase production, plackett-burman design, central composite design

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Authors: Richa Dhingra, Monika, Manav Malhotra, Tilak Raj Bhardwaj, Neelima Dhingra

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5-Alpha-reductases (5AR), a membrane bound, NADPH dependent enzyme and convert male hormone testosterone (T) into more potent androgen dihydrotestosterone (DHT). DHT is the required for the development and function of male sex organs, but its overproduction has been found to be associated with physiological conditions like Benign Prostatic Hyperplasia (BPH). Thus the inhibition of 5ARs could be a key target for the treatment of BPH. In present study, 2D and 3D Quantitative Structure Activity Relationship (QSAR) pharmacophore models have been generated for 5AR based on known inhibitory concentration (IC₅₀) values with extensive validations. The four featured 2D pharmacophore based PLS model correlated the topological interactions (–OH group connected with one single bond) (SsOHE-index); semi-empirical (Quadrupole2) and physicochemical descriptors (Mol. wt, Bromines Count, Chlorines Count) with 5AR inhibitory activity, and has the highest correlation coefficient (r² = 0.98, q² =0.84; F = 57.87, pred r² = 0.88). Internal and external validation was carried out using test and proposed set of compounds. The contribution plot of electrostatic field effects and steric interactions generated by 3D-QSAR showed interesting results in terms of internal and external predictability. The well validated 2D Partial Least Squares (PLS) and 3D k-nearest neighbour (kNN) models were used to search novel 5AR inhibitors with different chemical scaffold. To gain more insights into the molecular mechanism of action of these steroidal derivatives, molecular docking and in silico absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Studies have revealed the hydrophobic and hydrogen bonding of the ligand with residues Alanine (ALA) 63A, Threonine (THR) 60A, and Arginine (ARG) 456A of 4AT0 protein at the hinge region. The results of QSAR, molecular docking, in silico ADME studies provide guideline and mechanistic scope for the identification of more potent 5-Alpha-reductase inhibitors (5ARI).

Keywords: 5α-reductase inhibitor, benign prostatic hyperplasia, ligands, molecular docking, QSAR

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Authors: Pavel Damborsky, Martina Zamorova, Jaroslav Katrlik

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Prostate cancer is annually the most common newly diagnosed cancer among men. An extensive number of evidence suggests that traditional serum Prostate-specific antigen (PSA) assay still suffers from a lack of sufficient specificity and sensitivity resulting in vast over-diagnosis and overtreatment. Thus, the early-stage detection of prostate cancer (PCa) plays undisputedly a critical role for successful treatment and improved quality of life. Over the last decade, particular altered glycans have been described that are associated with a range of chronic diseases, including cancer and inflammation. These glycans differences enable a distinction to be made between physiological and pathological state and suggest a valuable biosensing tool for diagnosis and follow-up purposes. Aberrant glycosylation is one of the major characteristics of disease progression. Consequently, the aim of this study was to develop a more reliable tool for early-stage PCa diagnosis employing lectins as glyco-recognition elements. Biosensor and biochip technology putting to use lectin-based glyco-profiling is one of the most promising strategies aimed at providing fast and efficient analysis of glycoproteins. The proof-of-concept experiments based on sandwich assay employing anti-PSA antibody and an aptamer as a capture molecules followed by lectin glycoprofiling were performed. We present a lectin-based biosensing assay for glycoprofiling of serum biomarker PSA using different biosensor and biochip platforms such as label-free surface plasmon resonance (SPR) and microarray with fluorescent label. The results suggest significant differences in interaction of particular lectins with PSA. The antibody-based assay is frequently associated with the sensitivity, reproducibility, and cross-reactivity issues. Aptamers provide remarkable advantages over antibodies due to the nucleic acid origin, stability and no glycosylation. All these data are further step for construction of highly selective, sensitive and reliable sensors for early-stage diagnosis. The experimental set-up also holds promise for the development of comparable assays with other glycosylated disease biomarkers.

Keywords: biomarker, glycosylation, lectin, prostate cancer

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Authors: Muhammad A. Alsubaie

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An iterative learning control framework designed in state feedback structure suffers a lack in investigating load disturbance considerations. The presented work discusses the controller previously designed, highlights the disturbance problem, finds new conditions using singular value principle to assure safe operation conditions with error convergence and reference tracking under the influence of load disturbance. It is known that periodic disturbances can be represented by a delay model in a positive feedback loop acting on the system input. This model can be manipulated by isolating the delay model and finding a controller for the overall system around the delay model to remedy the periodic disturbances using the small signal theorem. The overall system is the base for control design and load disturbance investigation. The major finding of this work is the load disturbance condition found which clearly sets safe operation condition under the influence of load disturbances such that the error tends to nearly zero as the system keeps operating trial after trial.

Keywords: iterative learning control, singular values, state feedback, load disturbance

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Authors: Annika J. Meyer, Tom Piechotta

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Unmanned Aerial Vehicles (UAVs) have increasingly become vital tools in various applications, including surveillance, search and rescue, and environmental monitoring. One common approach to ensure redundant communication systems when flying beyond visual line of sight is for UAVs to employ multiple mobile data modems by different providers. Although widely adopted, this approach suffers from several drawbacks, such as high costs, added weight and potential increases in signal interference. In light of these challenges, this paper proposes a communication framework intermeshing mobile networks and LoRa (Long Range) technology—a low-power, long-range communication protocol. LoRaWAN (Long Range Wide Area Network) is commonly used in Internet of Things applications, relying on stationary gateways and Internet connectivity. This paper, however, utilizes the underlying LoRa protocol, taking advantage of the protocol’s low power and long-range capabilities while ensuring efficiency and reliability. Conducted in collaboration with the Potsdam Fire Department, the implementation of mobile network technology in combination with the LoRa protocol in small UAVs (take-off weight < 0.4 kg), specifically designed for search and rescue and area monitoring missions, is explored. This research aims to test the viability of LoRa as an additional redundant communication system during UAV flights as well as its intermeshing with the primary, mobile network-based controller. The methodology focuses on direct UAV-to-UAV and UAV-to-ground communications, employing different spreading factors optimized for specific operational scenarios—short-range for UAV-to-UAV interactions and long-range for UAV-to-ground commands. This explored use case also dramatically reduces one of the major drawbacks of LoRa communication systems, as a line of sight between the modules is necessary for reliable data transfer. Something that UAVs are uniquely suited to provide, especially when deployed as a swarm. Additionally, swarm deployment may enable UAVs that have lost contact with their primary network to reestablish their connection through another, better-situated UAV. The experimental setup involves multiple phases of testing, starting with controlled environments to assess basic communication capabilities and gradually advancing to complex scenarios involving multiple UAVs. Such a staged approach allows for meticulous adjustment of parameters and optimization of the communication protocols to ensure reliability and effectiveness. Furthermore, due to the close partnership with the Fire Department, the real-world applicability of the communication system is assured. The expected outcomes of this paper include a detailed analysis of LoRa's performance as a communication tool for UAVs, focusing on aspects such as signal integrity, range, and reliability under different environmental conditions. Additionally, the paper seeks to demonstrate the cost-effectiveness and operational efficiency of using a single type of communication technology that reduces UAV payload and power consumption. By shifting from traditional cellular network communications to a more robust and versatile cellular and LoRa-based system, this research has the potential to significantly enhance UAV capabilities, especially in critical applications where reliability is paramount. The success of this paper could pave the way for broader adoption of LoRa in UAV communications, setting a new standard for UAV operational communication frameworks.

Keywords: LoRa communication protocol, mobile network communication, UAV communication systems, search and rescue operations

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Authors: Wei-Kuang Liu, Ya-Hsu Chiang

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In the coming of an aging society, the issues of living quality, health care, and social security for the elderly have been gradually taken seriously. In order to maintain favorable living condition, urban societies are also facing the challenge of disasters caused by extreme climate change. However, in the practice of disaster prevention, elderly people are always weak due to their physiological conditions. That is to say, in the planning of resilient urbanism, the aging society is relatively in need of more care. Thus, this research aims to map areas where have high-density elderly population and fragile environmental condition in Taiwan, and to understand the actual situation of disaster prevention management in these areas, so as to provide suggestions for the development of intellectual resilient urban management. The research takes the cities of Taoyuan and Taichung as examples for explorations. According to GIS mapping of areas with high aging index, high-density population and high flooding potential, the communities of Sihai and Fuyuan in Taoyuan and the communities of Taichang and Nanshih in Taichung are highlighted. In these communities, it can be found that there are more elderly population and less labor population with high-density living condition. In addition, they are located in the areas where they have experienced severe flooding in the recent past. Based on a series of interviews with community organizations, there is only one community out of the four using flood information mobile app and Line messages for the management of disaster prevention, and the others still rely on the traditional approaches that manage the works of disaster prevention by their community security patrol teams and community volunteers. The interview outcome shows that most elderly people are not interested in learning the use of intellectual devices. Therefore, this research suggests to keep doing the GIS mapping of areas with high aging index, high-density population and high flooding potential for grasping the high-risk communities and to help develop smart monitor and forecast systems for disaster prevention practice in these areas. Based on case-study explorations, the research also advises that it is important to develop easy-to-use bottom-up and two-way immediate communication mechanism for the management of aging society’s disaster prevention.

Keywords: aging society, disaster prevention, GIS, resilient, Taiwan

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Authors: Jamal R. Elbergali

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Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero-Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol (x ̃_(N_T )), then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, modulation, zero forcing (ZF), OSIC, ZF-IC, spatial multiplexing (SM)

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

Procedia PDF Downloads 462

Authors: Cheng-Chen Hsu

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Background: The ratio of the length of the second finger (index finger, 2D) to the fourth finger (ring finger, 4D) (2D:4D) is a putative marker of prenatal hormones. A low 2D:4D ratio is related to high prenatal testosterone (PT) levels. Physiological research has suggested that a low 2D:4D ratio is correlated with high sports ability. Aim: To examine the association between cardiorespiratory fitness and 2D:4D. Methods: Assessment of 2D:4D; Images of hands were collected from participants using a computer scanner. Hands were placed lightly on the surface of the plate. Image analysis was performed using Image-Pro Plus 5.0 software. Feature points were marked at the tip of the finger and at the center of the proximal crease on the second and fourth digits. Actual measurement was carried out automatically, 2D:4D was calculated by dividing 2nd by 4th digit length. YMCA 3-min Step Test; The test involves stepping up and down at a rate of 24 steps/min for 3 min; a tape recording of the correct cadence (96 beats/min) is played to assist the participant in keeping the correct pace. Following the step test, the participant immediately sits down and, within 5 s, the tester starts counting the pulse for 1 min. The score for the test, the total 1-min postexercise heart rate, reflects the heart’s ability to recover quickly. Statistical Analysis ; Pearson’s correlation (r) was used for assessing the relationship between age, physical measurements, one-minute heart rate after YMCA 3-minute step test (HR) and 2D:4D. An independent-sample t-test was used for determining possible differences in HR between subjects with low and high values of 2D:4D. All statistical analyses were carried out with SPSS 18 for Window. All P-values were two-tailed at P = 0.05, if not reported otherwise. Results: A median split by 2D:4D was applied, resulting in a high and a low group. One-minute heart rate after YMCA 3-minute step test was significantly difference between groups of male right-hand 2D:4D (p = 0.024). However, no difference in left-hand 2D:4D values between groups in male, and no digit ratio difference between groups in female. Conclusion: The results showed that cardiopulmonary fitness is related to right 2D:4D, only in men. We argue that prenatal testosterone may have an effect on cardiorespiratory fitness in male but not in female.

Keywords: college students, digit ratio, finger, step test, fitness

Procedia PDF Downloads 276

Authors: Sílvia tuyà Viñas, Bruno Fernández-Valdés, Carla Pérez-Chirinos, Monica Morral-Yepes, Lucas del Campo Montoliu, Gerard Moras Feliu

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Some researchers stated that whole body vibration (WBV) generates postural destabilization, although there is no extensive research. Therefore, the aim of this study was to analyze movement variability when performing a half-squat with a different type of ballasts and rhythms with (V) and without (NV) WBV in male athletes using entropy. Twelve experienced in strength training males (age: 21.24  2.35 years, height: 176.83  5.80 cm, body mass: 70.63  8.58 kg) performed a half-squat with weighted vest (WV), dumbbells (D), and a bar with the weights suspended with elastic bands (B), in V and NV at 40 bpm and 60 bpm. Subjects performed one set of twelve repetitions of each situation, composed by the combination of the three factors. The movement variability was analyzed by calculating the Sample Entropy (SampEn) of the total acceleration signal recorded at the waist. In V, significant differences were found between D and WV (p<0.001; ES: 2.87 at 40 bpm; p<0.001; ES: 3.17 at 60 bpm) and between the B and WV at both rhythms (p<0.001; ES: 3.12 at 40 bpm; p<0.001; ES: 2.93 at 60 bpm) and a higher SampEn was obtained at 40 bpm with all ballasts (p<0.001; ES of WV: 1.22; ES of D: 4.49; ES of B: 4.03). No significant differences were found in NV. WBV is a disturbing and destabilizing stimulus. Strength and conditioning coaches should choose the combination of ballast and rhythm of execution according to the level and objectives of each athlete.

Keywords: accelerometry, destabilization, entropy, movement variability, resistance training

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Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: A. I. A. Rahman, Sh-Hussain Salleh, K. Ahmad, K. Anuar

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Analysis of vocal fold vibration is essential for understanding the mechanism of voice production and for improving clinical assessment of voice disorders. This paper presents a Dynamic Time Warping (DTW) based approach to analyze and objectively classify vocal fold vibration patterns. The proposed technique was designed and implemented on a Glottal Area Waveform (GAW) extracted from high-speed laryngeal images by delineating the glottal edges for each image frame. Feature extraction from the GAW was performed using Linear Predictive Coding (LPC). Several types of voice reference templates from simulations of clear, breathy, fry, pressed and hyperfunctional voice productions were used. The patterns of the reference templates were first verified using the analytical signal generated through Hilbert transformation of the GAW. Samples from normal speakers’ voice recordings were then used to evaluate and test the effectiveness of this approach. The classification of the voice patterns using the technique of LPC and DTW gave the accuracy of 81%.

Keywords: dynamic time warping, glottal area waveform, linear predictive coding, high-speed laryngeal images, Hilbert transform

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Authors: Neetu Manocha

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Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

Procedia PDF Downloads 143

Authors: Yuying Liu

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Despite the increasing popularity of Chinese and the recognition of the growing commodifying ideology of Chinese language in many contexts (Liu and Gao, 2020; Guo, Shin and Shen 2020), the ideological orientations of the Chinese diaspora community towards the Chinese language remain under-researched. This research contributes seeks to bridge this gap by investigating the micro-level language ideologies embedded in the Chinese complementary schools in the Republic of Ireland. Informed by Ruíz’s (1984) metaphorical representations of language, 11 Chinese complementary schools’ websites were analysed as discursive texts that signal the language policy and ideology to prospective learners and parents were analysed. The results of the analysis suggest that a move from a portrayal of Chinese as linked to student heritage identity, to the commodification of linguistic and cultural diversity, is evident. It denotes the growing commodifying ideology among the Chinese complementary schools in the Republic of Ireland. The changing profile of the complementary school, from serving an ethnical community to teaching Chinese as a foreign language for the wider community, indicates the possibility of creating the a positive synergy between the Complementary school and the mainstream education. This study contributes to the wider discussions of language ideology and language planning, with regards to modern language learning and heritage language maintenance.

Keywords: the Chinese language;, Chinese as heritage language, Chinese as foreign language, Chinese community schools

Procedia PDF Downloads 143

Authors: Omer Abdalla Ishag, Magdi Baker Amien

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Physicians used the stethoscope for listening patient heart sounds in order to make a diagnosis. However, the determination of heart conditions by acoustic stethoscope is a difficult task so it requires special training of medical staff. This study developed an accurate model for analyzing the phonocardiograph signal based on PC and DSP processor. The system has been realized into two phases; offline and real time phase. In offline phase, 30 cases of heart sounds files were collected from medical students and doctor's world website. For experimental phase (real time), an electronic stethoscope has been designed, implemented and recorded signals from 30 volunteers, 17 were normal cases and 13 were various pathologies cases, these acquired 30 signals were preprocessed using an adaptive filter to remove lung sounds. The background noise has been removed from both offline and real data, using wavelet transform, then graphical and statistics features vector elements were extracted, finally a look-up table was used for classification heart sounds cases. The obtained results of the implemented system showed accuracy of 90%, 80% and sensitivity of 87.5%, 82.4% for offline data, and real data respectively. The whole system has been designed on TMS320VC5509a DSP Platform.

Keywords: code composer studio, heart sounds, phonocardiograph, wavelet transform

Procedia PDF Downloads 454

Authors: Nishaben Dholakiya, Anirban Roy, Ranjan Dey

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The unprecedented rise in global temperatures has triggered complex changes in marine ecosystems, necessitating a deeper understanding of seawater's thermophysical properties by experimentally measuring ultrasonic velocity and density at varying temperatures and salinity. This study investigates the critical relationship between temperature variations and molecular-level interactions in Arabian Sea surface waters, specifically focusing on internal pressure (π) and cohesion energy density (CED) as key indicators of ecosystem disruption. Our experimental findings reveal that elevated temperatures significantly reduce internal pressure, weakening the intermolecular forces that maintain seawater's structural integrity. This reduction in π correlates directly with decreased habitat stability for marine organisms, particularly affecting pressure-sensitive species and their physiological processes. Similarly, the observed decline in cohesion energy density at higher temperatures indicates a fundamental shift in water molecule organization, impacting the dissolution and distribution of vital nutrients and gases. These molecular-level changes cascade through the ecosystem, affecting everything from planktonic organisms to complex food webs. By employing advanced machine learning techniques, including Stacked Ensemble Machine Learning (SEML) and AdaBoost (AB), we developed highly accurate predictive models (>99% accuracy) for these thermophysical parameters. The results provide crucial insights into the mechanistic relationship between climate warming and marine ecosystem degradation, offering valuable data for environmental policymaking and conservation strategies. The novelty of this research serves as no such thermodynamic investigation has been conducted before in literature, whereas this research establishes a quantitative framework for understanding how molecular-level changes in seawater properties directly influence marine ecosystem stability, emphasizing the urgent need for climate change mitigation efforts.

Keywords: thermophysical properties, Arabian Sea, internal pressure, cohesion energy density, machine learning

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Authors: Gulnaz Khan, Meha F. Aftab, Munazza Murtaza, Rizwana S. Waraich

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Advanced glycation end products (AGEs) precursor and its abnormal accumulation cause damage to various tissues and organs. AGEs have pathogenic implication in several diseases including diabetes. Existing AGEs inhibitors are not in clinical use, and there is a need for development of novel inhibitors. The present investigation aimed at identifying the novel AGEs inhibitors and assessing their mechanism of action for treating insulin resistance in mice model of diabetes. Novel derivatives of benzylidene of indan-1,3-dione were synthesized. The compounds were selected to study their action mechanism in improving insulin resistance, in vitro, in human hepatocytes and murine adipocytes and then, in vivo, in mice genetic model of diabetes (db/db). Mice were treated with novel derivatives of benzylidene of indane 1,3-dione. AGEs mediated ROS production was measured by dihydroethidium fluorescence assay. AGEs level in the serum of treated mice was observed by ELISA. Gene expression of receptor for AGEs (RAGE), PPAR-gamma, TNF-alpha and GLUT-4 was evaluated by RT-PCR. Glucose uptake was measured by fluorescent method. Microscopy was used to analyze glycogen synthesis in muscle. Among several derivatives of benzylidene of indan-1,3-dione, IDD-24, demonstrated highest inhibition of AGESs. IDD-24 significantly reduced AGEs formation and expression of receptor for advanced glycation end products (RAGE) in fat, liver of db/db mice. Suppression of AGEs mediated ROS production was also observed in hepatocytes and fat cell, after treatment with IDD-24. Glycogen synthesis was increased in muscle tissue of mice treated with IDD-24. In adipocytes, IDD-24 prevented AGEs induced reduced glucose uptake. Mice treated with IDD-24 exhibited increased glucose tolerance, serum adiponectin levels and decreased insulin resistance. The result of present study suggested that IDD-24 can be a possible treatment target to address glycotoxins induced insulin resistance.

Keywords: advance glycation end product, hyperglycemia, indan-1, 3-dione, insulin resistance

Procedia PDF Downloads 160

Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

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Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

Procedia PDF Downloads 550

Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

Abstract:

Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

Procedia PDF Downloads 99

Authors: Loïc Warscotte, Jehan Boreux

Abstract:

The scientific literature of changepoint detection is vast. Today, a lot of methods are available to detect abrupt changes or slight drift in a signal, based on CUSUM or EWMA charts, for example. However, these methods rely on strong assumptions, such as the stationarity of the stochastic underlying process, or even the independence and Gaussian distributed noise at each time. Recently, the breakthrough research on locally stationary processes widens the class of studied stochastic processes with almost no assumptions on the signals and the nature of the changepoint. Despite the accurate description of the mathematical aspects, this methodology quickly suffers from impractical time and space complexity concerning the signals with high-rate data collection, if the characteristics of the process are completely unknown. In this paper, we then addressed the problem of making this theory usable to our purpose, which is monitoring a high-speed weigh-in-motion system (HS-WIM) towards direct enforcement without supervision. To this end, we first compute bounded approximations of the initial detection theory. Secondly, these approximating bounds are empirically validated by generating many independent long-run stochastic processes. The abrupt changes and the drift are both tested. Finally, this relaxed methodology is tested on real signals coming from a HS-WIM device in Belgium, collected over several months.

Keywords: changepoint, weigh-in-motion, process, non-parametric

Procedia PDF Downloads 84