Search results for: diagnostics methods

Authors: Malika Yaici, Kamel Hariche

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In control engineering, systems described by matrix fractions are studied through properties of block roots, also called solvents. These solvents are usually dealt with in a block Vandermonde matrix form. Inverses and determinants of Vandermonde matrices and block Vandermonde matrices are used in solving problems of numerical analysis in many domains but require costly computations. Even though Vandermonde matrices are well known and method to compute inverse and determinants are many and, generally, based on interpolation techniques, methods to compute the inverse and determinant of a block Vandermonde matrix have not been well studied. In this paper, some properties of these matrices and iterative algorithms to compute the determinant and the inverse of a block Vandermonde matrix are given. These methods are deducted from the partitioned matrix inversion and determinant computing methods. Due to their great size, parallelization may be a solution to reduce the computations cost, so a parallelization of these algorithms is proposed and validated by a comparison using algorithmic complexity.

Keywords: block vandermonde matrix, solvents, matrix polynomial, matrix inverse, matrix determinant, parallelization

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Authors: Anthony Idowu Ajayi, Ezebunwa Ethelbert Nwokocha, Wilson Akpan, Oladele Vincent Adeniyi

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Studies on emergency contraception (EC) mostly utilise quantitative methods and focus on medically approved drugs for the prevention of unwanted pregnancies. This methodological bias necessarily obscures insider perspectives on sexual behaviour, particularly on why specific methods are utilized by women who seek to prevent unplanned pregnancies. In order to privilege this perspective, with a view to further enriching the discourse and policy on the prevention and management of unplanned pregnancies, this paper brings together the findings from several focus groups and in-depth interviews conducted amongst unmarried female undergraduate students in two Nigerian universities. The study found that while the research participants had good knowledge of the consequences of unprotected sexual intercourses - with abstinence and condom widely used - participants’ willingness to rely only on medically sound measures to prevent unwanted pregnancies was not always mediated by such knowledge. Some of the methods favored by participants appeared to be those commonly associated with people of low socio-economic status in the society where the study was conducted. Medically unsafe concoctions, some outright dangerous, were widely believed to be efficacious in preventing unwanted pregnancy. Furthermore, respondents’ narratives about their sexual behaviour revealed that inadequate sex education, socio-economic pressures, and misconceptions about the efficacy of “crude” emergency contraception methods were all interrelated. The paper therefore suggests that these different facets of the unplanned pregnancy problem should be the focus of intervention.

Keywords: unplanned pregnancy, unsafe abortion, emergency contraception, concoctions

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Silvia D. Vaca, Benjamin J. Kuo, Joao Ricardo N. Vissoci, Catherine A. Staton, Linda W. Xu, Michael Muhumuza, Hussein Ssenyonjo, John Mukasa, Joel Kiryabwire, Henry E. Rice, Gerald A. Grant, Michael M. Haglund

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Background: While delays to care exist in resource rich settings, greater delays are seen along the care continuum in low- and middle-income countries (LMICs) largely due to limited healthcare capacity to address the disproportional rates of traumatic brain injury (TBI) in Sub Saharan Africa (SSA). While many LMICs have government subsidized systems to offset surgical costs, the burden of securing funds by the patients for medications, supplies, and CT diagnostics poses a significant challenge to timely surgical interventions. In Kampala Uganda, the challenge of obtaining timely CT scans is twofold. First, due to a lack of a functional CT scanner at the tertiary hospital, patients need to arrange their own transportation to the nearby private facility for CT scans. Second, self-financing for the private CT scans ranges from $80 - $130, which is near the average monthly income in Kampala. These bottlenecks contribute significantly to the care continuum delays and are associated with poor TBI outcomes. Objective: The objectives of this study are to 1) describe the temporal delays through a modified three delays model that fits the context of neurosurgical interventions for TBI patients in Kampala and 2) investigate the association between delays and mortality. Methods: Prospective data were collected for 563 TBI patients presenting to a tertiary hospital in Kampala from 1 June – 30 November 2016. Four time intervals were constructed along five time points: injury, hospital arrival, neurosurgical evaluation, CT results, and definitive surgery. Time interval differences among mild, moderate and severe TBI and their association with mortality were analyzed. Results: The mortality rate of all TBI patients presenting to MNRH was 9.6%, which ranged from 4.7% for mild and moderate TBI patients receiving surgery to 81.8% for severe TBI patients who failed to receive surgery. The duration from injury to surgery varied considerably across TBI severity with the largest gap seen between mild TBI (174 hours) and severe TBI (69 hours) patients. Further analysis revealed care continuum differences for interval 3 (neurosurgical evaluation to CT result) and 4 (CT result to surgery) between severe TBI patients (7 hours for interval 3 and 24 hours for interval 4) and mild TBI patients (19 hours for interval 3, and 96 hours for interval 4). These post-arrival delays were associated with mortality for mild (p=0.05) and moderate TBI (p=0.03) patients. Conclusions: To our knowledge, this is the first analysis using a modified ‘three delays’ framework to analyze the care continuum of TBI patients in Uganda from injury to surgery. We found significant associations between delays and mortality for mild and moderate TBI patients. As it currently stands, poorer outcomes were observed for these mild and moderate TBI patients who were managed non-operatively or failed to receive surgery while surgical services were shunted to more severely ill patients. While well intentioned, high mortality rates were still observed for the severe TBI patients managed surgically. These results suggest the need for future research to optimize triage practices, understand delay contributors, and improve pre-hospital logistical referral systems.

Keywords: care continuum, global neurosurgery, Kampala Uganda, LMIC, Mulago, prospective registry, traumatic brain injury

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Authors: Yasin Akgül, Yusuf Polat, Emine Canbay, Ali Kılıç

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Wound dressings have strategically and economic importance considering increase of chronic wounds in the world. In this study, TPU nanofibrous membranes containing propolis as wound dressing are produced by two different methods. Firstly, TPU solution and propolis extract were mixed and this solution was electrospun. The other method is that TPU/propolis blend was centrifugally spun. Properties of nanofibrous membranes obtained by these methods were compared. While realizing the experiments, both systems were optimized to produce nanofibers with nearly same average fiber diameter.

Keywords: nanofiber, wound dressing, electrospinning, centrifugal spinning

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Authors: Mojtaba Saeedinezhad, Sarah Yousefi

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In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: Flóra Pomázi, Sándor Baranya, Zoltán Szalai

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A harmonized monitoring of the suspended sediment transport along such a large river as the world’s most international river, the Danube River, is a rather challenging task. The traditional monitoring method in Hungary is obsolete but using indirect measurement devices and techniques like optical backscatter sensors (OBS), laser diffraction or acoustic backscatter sensors (ABS) could provide a fast and efficient alternative option of direct methods. However, these methods are strongly sensitive to the particle characteristics (i.e. particle shape, particle size and mineral composition). The current method does not provide sufficient information about particle size distribution, mineral analysis is rarely done, and the shape of the suspended sediment particles have not been examined yet. The aims of the study are (1) to determine the particle characterisation of suspended sediment in the Danube River using advanced particle characterisation methods as laser diffraction and automated imaging, and (2) to perform a sensitivity analysis of the indirect methods in order to determine the impact of suspended particle characteristics. The particle size distribution is determined by laser diffraction. The particle shape and mineral composition analysis is done by the Morphologi G3ID image analyser. The investigated indirect measurement devices are the LISST-Portable|XR, the LISST-ABS (Sequoia Inc.) and the Rio Grande 1200 kHz ADCP (Teledyne Marine). The major findings of this study are (1) the statistical shape of the suspended sediment particle - this is the first research in this context, (2) the actualised particle size distribution – that can be compared to historical information, so that the morphological changes can be tracked, (3) the actual mineral composition of the suspended sediment in the Danube River, and (4) the reliability of the tested indirect methods has been increased – based on the results of the sensitivity analysis and the previous findings.

Keywords: advanced particle characterisation, automated imaging, indirect methods, laser diffraction, mineral composition, suspended sediment

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Authors: Zuzana Tatarkova, Ivana Pilchova, Michal Cibulka, Martin Kolisek, Peter Racay, Peter Kaplan

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Introduction: Normal functioning of mitochondria is crucial for cardiac performance. Mitochondria undergo mitophagy and biogenesis, and mitochondrial proteins are subject to extensive post-translational modifications. The state of mitochondrial homeostasis reflects overall cellular fitness and longevity. Perturbed mitochondria produce less ATP, release greater amounts of reactive molecules, and are more prone to apoptosis. Therefore mitochondrial turnover is an integral aspect of quality control in which dysfunctional mitochondria are selectively eliminated through mitophagy. Currently, the progressive deterioration of physiological functions is seen as accumulation of modified/damaged proteins with limiting regenerative ability and disturbance of such affected protein-protein communication throughout aging in myocardial cells. Methodologies: For our study was used immunohistochemistry, biochemical methods: spectrophotometry, western blotting, immunodetection as well as more sophisticated 2D electrophoresis and mass spectrometry for evaluation protein-protein interactions and specific post-translational modification. Results and Discussion: Mitochondrial stress response to reactive species was evaluated as electron transport chain (ETC) complexes, redox-active molecules, and their possible communication. Protein-protein interactions revealed a strong linkage between age and ETC protein subunits. Redox state was strongly affected in senescent mitochondria with shift in favor of more pro-oxidizing condition within cardiomyocytes. Acute myocardial ischemia and ischemia-reperfusion (IR) injury affected ETC complexes I, II and IV with no change in complex III. Ischemia induced decrease in total antioxidant capacity, MnSOD, GSH and catalase activity with recovery in some extent during reperfusion. While MnSOD protein content was higher in IR group, activity returned to 95% of control. Nitric oxide is one of the biological molecules that can out compete MnSOD for superoxide and produce peroxynitrite. This process is faster than dismutation and led to the 10-fold higher production of nitrotyrosine after IR injury in adult with higher protection in senescent ones. 2D protein profiling revealed 140 mitochondrial proteins, 12 of them with significant changes after IR injury and 36 individual nitrotyrosine-modified proteins further identified by mass spectrometry. Linking these two groups, 5 proteins were altered after IR as well as nitrated, but only one showed massive nitration per lowering content of protein after IR injury in adult. Conclusions: Senescent cells have greater proportion of protein content, which might be modulated by several post-translational modifications. If these protein modifications are connected to functional consequences and protein-protein interactions are revealed, link may lead to the solution. Assume all together, dysfunctional proteostasis can play a causative role and restoration of protein homeostasis machinery is protective against aging and possibly age-related disorders. This work was supported by the project VEGA 1/0018/18 and by project 'Competence Center for Research and Development in the field of Diagnostics and Therapy of Oncological diseases', ITMS: 26220220153, co-financed from EU sources.

Keywords: aging heart, mitochondria, proteomics, redox state

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Authors: Xingyu Peng, Qingyuan Hu, Xuebin Zhu, Xi Yuan

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Neutron spectrometry has contributed much to the development of nuclear physics since 1932 and has also become an importance tool in several other fields, notably nuclear technology, fusion plasma diagnostics and radiation protection. Compared with neutron fluxes, neutron spectra can provide more detailed information on the internal physical process of neutron sources, such as fast neutron reactors, fusion plasma, fission-fusion hybrid reactors, and so on. However, high performance neutron spectrometer is not so commonly available as it requires the use of large and complex instrumentation. This work describes the development and characterization of a compact magnetic proton recoil (MPR) spectrometer for high-resolution measurements of fast neutron spectra. The compact MPR spectrometer is featured by its large recoil angle, small size permanent analysis magnet, short beam transport line and dual-purpose detector array for both steady state and pulsed neutron spectra measurement. A 3-dimensional electromagnetic particle transport code is developed to simulate the response function of the spectrometer. Simulation results illustrate that the performance of the spectrometer is mainly determined by n-p recoil foil and proton apertures, and an overall energy resolution of 3% is achieved for 14 MeV neutrons. Dedicated experiments using alpha source and mono-energetic neutron beam are employed to verify the simulated response function of the compact MPR spectrometer. These experimental results show a good agreement with the simulated ones, which indicates that the simulation code possesses good accuracy and reliability. The compact MPR spectrometer described in this work is a valuable tool for fast neutron spectra measurements for the fission or fusion devices.

Keywords: neutron spectrometry, magnetic proton recoil spectrometer, neutron spectra, fast neutron

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Authors: Nasrud Din, Fawad Saeed, Sajid Hussain, Rai Muhammad Dawood Sultan, Premkumar Sellan, Qasim Khan, Wei Lei

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The continuously increasing external quantum efficiencies of Perovskite light-emitting diodes (LEDs) have received significant interest in the scientific community. The need for monitoring and medical diagnostics has experienced a steady growth in recent years, primarily caused by older people and an increasing number of heart attacks, tumors, and cancer disorders among patients. The application of Perovskite near-infrared light-emitting diode (PeNIRLEDs) has exhibited considerable efficacy in bioimaging, particularly in the visualization and examination of blood arteries, blood clots, and tumors. PeNIRLEDs exhibit exciting potential in the field of blood vessel imaging because of their advantageous attributes, including improved depth penetration and less scattering in comparison to visible light. In this study, we synthesized FAPbI₃ Perovskite doped with different concentrations of 5-Aminovaleric acid (5-AVA) 1-6 mg. The incorporation of 5-AVA as a dopant during the FAPbI₃ Perovskite formation influences the FAPbI3 Perovskite’s structural and optical properties, improving its stability, photoluminescence efficiency, and charge transport characteristics. We found a resulting PL emission peak wavelength of 850 nm and bandwidth of 44 nm, along with a calculated quantum yield of 75%. The incorporation of 5-AVA-modified FAPbI₃ Perovskite into LEDs will show promising results, enhancing device efficiency, color purity, and stability. Making it suitable for various medical applications, including subcutaneous deep vein imaging, blood flow visualization, and tumor illumination.

Keywords: perovskite light-emitting diodes, deep vein imaging, blood flow visualization, tumor illumination

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Intanri Kurniati, Raja Iqbal Mulya Harahap, Agustyas Tjiptaningrum, Reni Zuraida

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Background: Diabetes mellitus is still increasing and has become a health and social burden in the world. It is known that glycation among various proteins is increased in diabetic patients compared with non-diabetic subjects. Some of these glycated proteins are suggested to be involved in the development and progression of chronic diabetic complications. Among these glycated proteins, glycated hemoglobin (HbA1C) is commonly used as the gold standard index of glycemic control in the clinical setting. HbA1C testing has some methods, and the most commonly used is immunoturbidimetry. This research aimed to compare the HbA1c level between immunoturbidimetry and HbA1C level in T2DM patients. Methods: This research involves 77 patients from Abd Muluk Hospital Bandar Lampung; the patient was asked for consent in this research, then underwent phlebotomy to be tested for HbA1C; the sample was then examined for HbA1C with Turbidimetric Inhibition Immunoassay (TINIA) and High-Performance Liquid Chromatography (HPLC) method. Result: Mean± SD of the samples with the TINIA method was 9.2±1,2; meanwhile, the level HbA1C with the HPLC method is 9.6±1,2. The t-test showed no significant difference between the group subjects. (p<0.05). It was proposed that the two methods have high suitability in testing, and both are eligibly used for the patient. Discussion: There was no significant difference among research subjects, indicating that the high conformity of the two methods is suitable to be used for monitoring patients clinically. Conclusion: There is increasing in HbA1C level in a patient with T2DM measured with HPLC and or Turbidimetric Inhibition Immunoassay (TINIA) method, and there were no significant differences among those methods.

Keywords: diabetes mellitus, glycated albumin, HbA1C, HPLC, immunoturbidimetry

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Climatic factors are the subject of considerable research, both methodologically and instrumentally. Under the effect of climate change, the approach to climate parameters with precision remains one of the main objectives of the scientific community. This is from the perspective of assessing climate change and its repercussions on humans and the environment. However, many regions of the world suffer from a severe lack of reliable instruments that can make up for this deficit. Alternatively, the use of empirical methods becomes the only way to assess certain parameters that can act as climate indicators. Several scientific methods are used for the evaluation of evapotranspiration which leads to its evaluation either directly at the level of the climatic stations or by empirical methods. All these methods make a point approach and, in no case, allow the spatial variation of this parameter. We, therefore, propose in this paper the use of three sources of information (network of weather stations of Meteo France, World Databases, and Moodis satellite images) to evaluate spatial evapotranspiration (ETP) using the Turc method. This first step will reflect the degree of relevance of the indirect (satellite) methods and their generalization to sites without stations. The spatial variation representation of this parameter using the geographical information system (GIS) accounts for the heterogeneity of the behaviour of this parameter. This heterogeneity is due to the influence of site morphological factors and will make it possible to appreciate the role of certain topographic and hydrological parameters. A phase of predicting the evolution over the medium and long term of evapotranspiration under the effect of climate change by the application of the Intergovernmental Panel on Climate Change (IPCC) scenarios gives a realistic overview as to the contribution of aquatic systems to the scale of the region.

Keywords: climate change, ETP, MODIS, GIEC scenarios

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Authors: Arash Jafari, Mehdi Taghaddosi, Azin Parvin

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In the paper, our purpose is to enhance the ability to solve a nonlinear differential equation which is about the motion of an incompressible fluid flow going down of an inclined plane without thermal effect with a simple and innovative approach which we have named it new method. Comparisons are made amongst the Numerical, new method, and HPM methods, and the results reveal that this method is very effective and simple and can be applied to other nonlinear problems. It is noteworthy that there are some valuable advantages in this way of solving differential equations, and also most of the sets of differential equations can be answered in this manner which in the other methods they do not have acceptable solutions up to now. A summary of the excellence of this method in comparison to the other manners is as follows: 1) Differential equations are directly solvable by this method. 2) Without any dimensionless procedure, we can solve equation(s). 3) It is not necessary to convert variables into new ones. According to the afore-mentioned assertions which will be proved in this case study, the process of solving nonlinear equation(s) will be very easy and convenient in comparison to the other methods.

Keywords: viscos fluid, incompressible fluid flow, inclined plane, nonlinear phenomena

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Authors: Balazs Somodi, Balazs Kovesdi

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In the research praxis of civil engineering the statistical evaluation of experimental and numerical investigations is an essential task in order to compare the experimental and numerical resistances of a specific structural problem with the proposed resistances of the standards. However, in the standards and in the international literature there are several different safety factor evaluation methods that can be used to check the necessary safety level (e.g.: 5% quantile level, 2.3% quantile level, 1‰ quantile level, γM partial safety factor, γM* partial safety factor, β reliability index). Moreover, in the international literature different calculation methods could be found even for the same safety factor as well. In the present study the flexural buckling resistance of high strength steel (HSS) welded closed sections are analyzed. The authors investigated the flexural buckling resistances of the analyzed columns by laboratory experiments. In the present study the safety levels of the obtained experimental resistances are calculated based on several safety approaches and compared with the EN 1990. The results of the different safety approaches are compared and evaluated. Based on the evaluation tendencies are identified and the differences between the statistical evaluation methods are explained.

Keywords: flexural buckling, high strength steel, partial safety factor, statistical evaluation

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Authors: Deborah Amas

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Global accreditation standards require Higher Education Institutions to ensure social work students develop self-awareness by reflecting on their personal values and critically evaluating how these influence their thinking for professional practice. The knowledge base indicates there are benefits and vulnerabilities for students when they self-reflect and more needs to be understood about the learning environments that nurture self-awareness. The connection between teaching methods and self-awareness is of interest in this paper which reports findings from an on-line survey with students on BA and MA qualifying social work programs in an English university (n=120). Students were asked about the importance of self-awareness and their experiences of teaching methods for self-reflection. Generally, students thought that self-awareness is of high importance in their education. Students also shared stories that illuminated deeper feelings about the potential risks associated with self-disclosure. The findings indicate that students appreciate safe opportunities for self-reflection, but can be wary of associated assessments or feeling judged. The research supports arguments to qualitatively improve facilitation of self-awareness through the curriculum.

Keywords: reflection, self-awareness, self-reflection, social work education

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Authors: N. Chetty, K. Singh

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In this work, the relationship between the melanin content in a tissue and subsequent absorption of light through that tissue was determined using a digital camera. This technique proved to be simple, cost effective, efficient and reliable. Tissue phantom samples were created using milk and soy sauce to simulate the optical properties of melanin content in human tissue. Increasing the concentration of soy sauce in the milk correlated to an increase in melanin content of an individual. Two methods were employed to measure the light transmitted through the sample. The first was direct measurement of the transmitted intensity using a conventional lux meter. The second method involved correctly calibrating an ordinary digital camera and using image analysis software to calculate the transmitted intensity through the phantom. The results from these methods were then graphically compared to the theoretical relationship between the intensity of transmitted light and the concentration of absorbers in the sample. Conclusions were then drawn about the effectiveness and efficiency of these low cost methods.

Keywords: tissue phantoms, scattering coefficient, albedo, low-cost method

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Authors: Suzanne Zazycki, Bamidele Osamika, Heather Craska, Kaelyn Conaway, Reena Murphy, Stephanie Spence

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Invasive Plant Species (IPS) are an important component of effective preservation and conservation of natural lands management. IPS are non-native plants which can aggressively encroach upon native species and pose a significant threat to the ecology, public health, and social welfare of a community. The presence of IPS in U.S. nature preserves has caused economic costs, which has estimated to exceed $26 billion a year. While different methods have been identified to control IPS, few methods have been recognized for early detection of IPS. This study examined identified methods for early detection of IPS in Hueston Woods State Nature Preserve. Mixed methods research design was adopted in this four-phased study. The first phase entailed data gathering, the phase described the characteristics and qualities of IPS and the importance of early detection (ED). The second phase explored ED methods, Geographic Information Systems (GIS) and Citizen Science were discovered as ED methods for IPS. The third phase of the study involved the creation of hotspot maps to identify likely areas for IPS growth. While the fourth phase involved testing and evaluating mobile applications that can support the efforts of citizen scientists in IPS detection. Literature reviews were conducted on IPS and ED methods, and four regional experts from ODNR and Miami University were interviewed. A questionnaire was used to gather information about ED methods used across the state. The findings revealed that geospatial methods, including Unmanned Aerial Vehicles (UAVs), Multispectral Satellites (MSS), and Normalized Difference Vegetation Index (NDVI), are not feasible for early detection of IPS, as they require GIS expertise, are still an emerging technology, and are not suitable for every habitat for the ED of IPS. Therefore, Other ED methods options were explored, which include predicting areas where IPS will grow, which can be done through monitoring areas that are like the species’ native habitat. Through literature review and interviews, IPS are known to grow in frequently disturbed areas such as along trails, shorelines, and streambanks. The research team called these areas “hotspots” and created maps of these hotspots specifically for HW NP to support and narrow the efforts of citizen scientists and staff in the ED of IPS. The results further showed that utilizing citizen scientists in the ED of IPS is feasible, especially through single day events or passive monitoring challenges. The study concluded that the creation of hotspot maps to direct the efforts of citizen scientists are effective for the early detection of IPS. Several recommendations were made, among which is the creation of hotspot maps to narrow the ED efforts as citizen scientists continues to work in the preserves and utilize citizen science volunteers to identify and record emerging IPS.

Keywords: early detection, hueston woods state nature preserve, invasive plant species, hotspots

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Authors: Emily Hickmann, Peggy Richter, Maren Kaehlig, Hannes Schlieter

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Patient engagement is a cornerstone of high-quality care and essential for patients with chronic diseases to achieve improved health outcomes. Through digital transformation, possibilities to engage patients in their personal healthcare have multiplied. However, the exploitation of this potential is still lagging. To support the transmission of patient engagement theory into practice, this paper’s objective is to give a state-of-the-art overview of patient engagement tools and methods. A systematic literature review was conducted. Overall, 56 tools and methods were extracted and synthesized according to the four attributes of patient engagement, i.e., personalization, access, commitment, and therapeutic alliance. The results are discussed in terms of their potential to be implemented in digital health solutions under consideration of the “computers are social actors” (CASA) paradigm. It is concluded that digital health can catalyze patient engagement in practice, and a broad future research agenda is formulated.

Keywords: chronic diseases, digitalization, patient-centeredness, patient empowerment, patient engagement

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Authors: S. Cencek, A. Markun

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Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

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Authors: Chidiebere Samuel Ijeoma

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The impact and importance of technology in all domains of existence cannot be overemphasized. It is like a double-edged sword which can be both constructive and destructive. The paper, therefore, tends to evaluate the impact of technology so far in the teaching and learning of French language in Nigeria. According to the study, the traditional methods of teaching French as a Foreign Language and recognized as our cultural methods of knowledge transfer are being fast replaced by digitalization in teaching. This, the research tends to portray and suggest the best way forward. In the Nigerian Primary Education System, the use of some local and cultural Instructional materials (teaching aids) is now almost history which the paper frowns at. Consequently, the study has these questions to ask?; Where are the chalks and blackboards? Where are the ‘Handworks’ (local brooms) submitted by school children as part of their Continuous Assessment? Finally, the research is in no way against the application of technology in the Nigerian French Language Teaching System but tries to draw a curtain between Technological methods of teaching French as a Foreign Language and the Original Nigerian System of teaching the language before the arrival of technology.

Keywords: French language teaching, future, impact, importance of technology

Procedia PDF Downloads 343

Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

Abstract:

This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

Procedia PDF Downloads 189

Authors: Basant Singh Sikarwar, Mukesh Roy, Ayush Goyal, Priya Ranjan

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This work combines two bodies of knowledge which includes biomedical basis of blood stain formation and fluid communities’ wisdom that such formation of blood stain depends heavily on physical properties. Moreover biomedical research tells that different patterns in stains of blood are robust indicator of blood donor’s health or lack thereof. Based on these valuable insights an innovative screening tool is proposed which can act as an aide in the diagnosis of diseases such Anemia, Hyperlipidaemia, Tuberculosis, Blood cancer, Leukemia, Malaria etc., with enhanced confidence in the proposed analysis. To realize this powerful technique, simple, robust and low-cost micro-fluidic devices, a micro-capillary viscometer and a pendant drop tensiometer are designed and proposed to be fabricated to measure the viscosity, surface tension and wettability of various blood samples. Once prognosis and diagnosis data has been generated, automated linear and nonlinear classifiers have been applied into the automated reasoning and presentation of results. A support vector machine (SVM) classifies data on a linear fashion. Discriminant analysis and nonlinear embedding’s are coupled with nonlinear manifold detection in data and detected decisions are made accordingly. In this way, physical properties can be used, using linear and non-linear classification techniques, for screening of various diseases in humans and cattle. Experiments are carried out to validate the physical properties measurement devices. This framework can be further developed towards a real life portable disease screening cum diagnostics tool. Small-scale production of screening cum diagnostic devices is proposed to carry out independent test.

Keywords: blood, physical properties, diagnostic, nonlinear, classifier, device, surface tension, viscosity, wettability

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Authors: Shukran M. Dadayev

Abstract:

To author's best knowledge, in this paper, the Basic Properties and Research methods of a Fundamental Particle is studied for the first time. That's to say, Fundamental Particle has not been discovered in the Nature yet. Because Fundamental Particle consists of specific Physical, Geometrical and Internal bases. Geometrical and Internal characteristics that are considered significant for the elementary and fundamental particles aren’t basic properties, characteristics or criteria of a Fundamental Particle. Of course, completely new Physical and Visual experimental methods of Quantum mechanics and Behavioral-Physical investigations of Particles are needed to study and discover the Fundamental Particle. These are new Physical, Visual and Behavioral-Physical experimental methods for describing and discovering the Fundamental Particle in the Nature and Microworld. Fundamental Particle consists of the same Energy-Mass-Motion system and a symmetry of Energy-Mass-Motion. Fundamental Particle supplies each of the elementary particles with the same Energy-Mass-Motion system at the same time and regulates each of the particles. Fundamental Particle gives Energy, Mass and Motion to each particles at the same time, each of the Particles consists of acquired Energy-Mass-Motion system and symmetry. Energy, Mass, Motion given by the Fundamental Particle to the particles are Symmetrical Equivalent and they remain in their primary shapes in all cases. Fundamental Particle gives Energy-Mass-Motion system and symmetry consisting of different measures and functions to each of the particles. The Motion given by the Fundamental Particle to the particles is Gravitation, Gravitational Interaction not only gives Motion, but also cause Motion by attracting. All Substances, Fields and Cosmic objects consist of Energy-Mass-Motion. The Field also includes specific Mass. They are always Energetic, Massive and Active. Fundamental Particle establishes the bases of the Nature. Supplement and Regulating of all the particles existing in the Nature belongs to Fundamental Particle.

Keywords: basic properties of a fundamental particle, behavioral-physical and visual methods, energy-mass-motion system and symmetrical equivalence, fundamental particle

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

Procedia PDF Downloads 527

Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni

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Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.

Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM

Procedia PDF Downloads 315

Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

Abstract:

The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: Arpita Saha, Satish Chandra, Indrajit Ghosh

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Delay implicates the time loss of a traveler while crossing an intersection. Efficiency of traffic operation at signalized intersections is assessed in terms of delay caused to an individual vehicle. Highway Capacity Manual (HCM) method and Webster’s method are the most widely used in India for delay estimation purpose. However, in India, traffic is highly heterogeneous in nature with extremely poor lane discipline. Therefore, to explore best delay estimation technique for Indian condition, a comparison was made. In this study, seven signalized intersections from three different cities where chosen. Data was collected for both during morning and evening peak hours. Only under saturated cycles were considered for this study. Delay was estimated based on the field data. With the help of Simpson’s 1/3 rd rule, delay of under saturated cycles was estimated by measuring the area under the curve of queue length and cycle time. Moreover, the field observed delay was compared with the delay estimated using HCM, Webster, Probabilistic, Taylor’s expansion and Regression methods. The drawbacks of the existing delay estimation methods to be use in Indian heterogeneous traffic conditions were figured out, and best method was proposed. It was observed that direct estimation of delay using field measured data is more accurate than existing conventional and modified methods.

Keywords: delay estimation technique, field delay, heterogeneous traffic, signalised intersection

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Authors: Narayanappa Devakumar, Chengalappa Seenappa

Abstract:

The field experiments were conducted during Rabi 2013 and summer 2014 at College of Sericulture, Chintamani, Chickaballapur district, Karnataka, India to find out the response of mulberry to different methods, levels of irrigation and mulching. The results showed that leaf yield and water productivity of mulberry were significantly influenced by different methods, levels of irrigation and mulching. Subsurface drip with lower level of irrigation at 0.8 CPE (Cumulative Pan Evaporation) recorded higher leaf yield and water productivity (42857 kg ha-1 yr-1and 364.41 kg hacm-1) than surface drip with higher level of irrigation at 1.0 CPE (38809 kg ha-1 yr-1 and 264.10 kg hacm-1) and micro spray jet (39931 kg ha-1 yr-1 and 271.83 kg hacm-1). Further, subsurface drip recorded minimum water used to produce one kg of leaf and to earn one rupee of profit (283 L and 113 L) compared to surface drip (390 L and 156 L) and micro spray jet (379 L and 152 L) irrigation methods. Mulberry leaf yield increased and water productivity decreased with increased levels of irrigation. However, these results indicated that irrigation of mulberry with subsurface drip increased leaf yield and water productivity by saving 20% of irrigation water than surface drip and micro spray jet irrigation methods in Eastern Dry Zone (EDZ) of Karnataka.

Keywords: cumulative pan evaporation, mulaberry, subsurface drip irrigation, water productivity

Procedia PDF Downloads 266