Search results for: one side class algorithm

Authors: E. Pretorius, A. M. Viljoen, M. van der Bank

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Introduction: The phytochemistry of Agathosma crenulata and A. betulina has been studied extensively, while their molecular analysis through DNA barcoding remains virtually unexplored. This technique can confirm the identity of plant species included in a herbal product, thereby ensuring the efficacy of the herbal product and the accuracy of its label. Materials and methods: Authentic Agathosma reference material of A. betulina (n=16) and A. crenulata (n=10) were obtained. Thirteen commercial products were purchased from various health shops around Johannesburg, South Africa, using the search term “Agathosma” or “Buchu.” The plastid regions matK and ycf1 were used to barcode the Buchu products, and BRONX analysis confirmed the taxonomic identity of the samples. UPLC-MS analyses were also performed. Results: Only (30/60) 60% of the traded samples tested from 13 suppliers contained A. betulina in their herbal products. Similar results were also obtained for the UPLC-MS analysis. Conclusion: In this study, we demonstrate the application of DNA barcoding in combination with phytochemical analysis to authenticate herbal products claiming to contain Agathosma plants as an ingredient in their products. This supports manufacturing efforts to ensure that herbal products that are safe for the consumer.

Keywords: Buchu, substitution, barcoding, BRONX algorithm, matK, ycf1, UPLC-MS

Procedia PDF Downloads 129

Authors: Pooja Kumari, Anandkumar Tengli

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Aurora kinase enzyme, a protein on overexpression, leads to metastasis and is extremely important for women’s health in terms of prevention or treatment. While creating a targeted technique, the aim of the work is to design purine molecules that inhibit in aurora kinase enzyme and helps to suppress breast cancer. Purine molecules attached to an amino acid in DNA block protein synthesis or halt the replication and metastasis caused by the aurora kinase enzyme. Various protein related to the overexpression of aurora protein was docked with purine molecule using Biovia Drug Discovery, the perpetual software. Various parameters like X-ray crystallographic structure, presence of ligand, Ramachandran plot, resolution, etc., were taken into consideration for selecting the target protein. A higher negative binding scored molecule has been taken for simulation studies. According to the available research and computational analyses, purine compounds may be powerful enough to demonstrate a greater affinity for the aurora target. Despite being clinically effective now, purines were originally meant to fight breast cancer by inhibiting the aurora kinase enzyme. In in-silico studies, it is observed that purine compounds have a moderate to high potency compared to other molecules, and our research into the literature revealed that purine molecules have a lower risk of side effects. The research involves the design, synthesis, and identification of active purine molecules against breast cancer. Purines are structurally similar to the normal metabolites of adenine and guanine; hence interfere/compete with protein synthesis and suppress the abnormal proliferation of cells/tissues. As a result, purine target metastasis cells and stop the growth of kinase; purine derivatives bind with DNA and aurora protein which may stop the growth of protein or inhibits replication and stop metastasis of overexpressed aurora kinase enzyme.

Keywords: aurora kinases, in silico studies, medicinal chemistry, combination therapies, chronic cancer, clinical translation

Procedia PDF Downloads 86

Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

Procedia PDF Downloads 199

Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

Procedia PDF Downloads 91

Authors: Elron Fouten

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Recently, debates surrounding the social relevance of psychology in South Africa have focussed on how the growing neoliberal rationality within academia has again resulted in the discipline catering to the needs of powerful social groupings to protect its own economic interests, rather than producing socially relevant knowledge. Consequently, this study aimed to conduct a content analysis of the recent research output of psychology masters students, to establish whether it has produced research that addresses local and national psychosocial issues and as such deemed socially relevant knowledge. The study sampled clinical, counselling, and research psychology masters theses from 16 South African universities submitted between 1998 and 2017. Overall, 2001 theses were sampled, which were analysed using qualitative content analysis predominantly based on the descriptive categories identified in similar studies using published journal articles. Results indicated that empirical qualitative theses, using systems-oriented theory and post-modern frameworks were most prevalent. Further, traditional topics within psychology had relatively more weighting compared to more social topics. Although a significant number of theses recruited participants from working-class or poor backgrounds, there was an overreliance on participants from urban areas located in some of the country’s wealthiest provinces. Despite a strong adult-centric focus, trends regarding participants’ race and gender roughly resembled current population demographics. Overall, the results indicate that psychology in South Africa, at least at university-level, is to some extent trying to engage with national psychosocial concerns. However, there are still several key areas which need to be addressed to ensure the continued social relevance of the discipline.

Keywords: adult-centric, content analysis, relevance, psychosocial

Procedia PDF Downloads 141

Authors: Muhammad Abid

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The ultimate goal of this research was to produce a cold galvanizing compound (CGC) at reduced pigment volume concentration (PVC) to protect metallic structures from corrosion. The influence of the partial replacement of Zn dust by nano-layered graphene (NGr) and Zn metal nanoparticles on the electrochemical, morphological, rheological, and mechanical properties of CGC was investigated. EIS was used to explore the electrochemical nature of coatings. The EIS results revealed that the partial replacement of Zn by NGr and Zn nanoparticles enhanced the cathodic protection at reduced PVC (4:1) by improving the electrical contact between the Zn particles and the metal substrate. The Tafel scan was conducted to support the cathodic behaviour of the coatings. The sample formulated solely with Zn at PVC 4:1 was found to be dominated in physical barrier characteristics over cathodic protection. By increasing the concentration of NGr in the formulation, the corrosion potential shifted towards a more negative side. The coating with 1.5% NGr showed the highest galvanic action at reduced PVC. FE-SEM confirmed the interconnected network of conducting particles. The coating without NGr and Zn nanoparticles at PVC 4:1 showed significant gaps between the Zn dust particles. The novelty was evidenced when micrographs showed the consistent distribution of NGr and Zn nanoparticles all over the surface, which acted as a bridge between spherical Zn particles and provided cathodic protection at a reduced PVC. The layered structure of graphene also improved the physical shielding effect of the coatings, which limited the diffusion of electrolytes and corrosion products (oxides/hydroxides) into the coatings, which was reflected by the salt spray test. The rheological properties of coatings showed good liquid/fluid properties. All the coatings showed excellent adhesion but had different strength values. A real-time scratch resistance assessment showed all the coatings had good scratch resistance.

Keywords: protective coatings, anti-corrosion, galvanization, graphene, nanomaterials, polymers

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 409

Authors: Aafaf El Jazouli, Ahmed Barakat, Rida Khellouk

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Mapping of soil degradation is derived from field observations, laboratory measurements, and remote sensing data, integrated quantitative methods to map the spatial characteristics of soil properties at different spatial and temporal scales to provide up-to-date information on the field. Since soil salinity, texture and organic matter play a vital role in assessing topsoil characteristics and soil quality, remote sensing can be considered an effective method for studying these properties. The main objective of this research is to asses soil degradation by combining remote sensing data and laboratory analysis. In order to achieve this goal, the required study of soil samples was taken at 50 locations in the upper basin of Oum Er Rbia in the Middle Atlas in Morocco. These samples were dried, sieved to 2 mm and analyzed in the laboratory. Landsat 8 OLI imagery was analyzed using physical or empirical methods to derive soil properties. In addition, remote sensing can serve as a supporting data source. Deterministic potential (Spline and Inverse Distance weighting) and probabilistic interpolation methods (ordinary kriging and universal kriging) were used to produce maps of each grain size class and soil properties using GIS software. As a result, a correlation was found between soil texture and soil organic matter content. This approach developed in ongoing research will improve the prospects for the use of remote sensing data for mapping soil degradation in arid and semi-arid environments.

Keywords: Soil degradation, GIS, interpolation methods (spline, IDW, kriging), Landsat 8 OLI, Oum Er Rbia high basin

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Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva

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The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.

Keywords: epoxy resins, modification, vinyl-containing compounds, deformation, strength properties

Procedia PDF Downloads 112

Authors: Panarat Saengpanya

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There were five objectives in this study including the study of housing type with water environment, the physical and mechanical properties of the buoy material, the mechanical properties of the buoy models, the floating of the buoy models and the relationship between the civil engineering parameters and the floating of the buoy. The buoy examples made from Expanded Polystyrene (EPS) covered by 5 mm thickness of mortar with the equal thickness on each side. Specimens are 0.05 m cubes tested at a displacement rate of 0.005 m/min. The existing test method used to assess the parameters relationship is ASTM C 109 to provide comparative results. The results found that the three type of housing with water environment were Stilt Houses, Boat House, and Floating House. EPS is a lightweight material that has been used in engineering applications since at least the 1950s. Its density is about a hundredth of that of mortar, while the mortar strength was found 72 times of EPS. One of the advantage of composite is that two or more materials could be combined to take advantage of the good characteristics of each of the material. The strength of the buoy influenced by mortar while the floating influenced by EPS. Results showed the buoy example compressed under loading. The Stress-Strain curve showed the high secant modulus before reached the peak value. The failure occurred within 10% strain then the strength reduces while the strain was continuing. It was observed that the failure strength reduced by increasing the total volume of examples. For the buoy examples with same area, an increase of the failure strength is found when the high dimension is increased. The results showed the relationship between five parameters including the floating level, the bearing capacity, the volume, the high dimension and the unit weight. The study found increases in high of buoy lead to corresponding decreases in both modulus and compressive strength. The total volume and the unit weight had relationship with the bearing capacity of the buoy.

Keywords: floating house, buoy, floating structure, EPS

Procedia PDF Downloads 146

Authors: Peter David Reiss

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The concept of the psychosis prodrome has allowed for the identification of adolescent and young adult patients who have a significantly elevated risk of developing schizophrenia spectrum disorders. A number of different interventions have been tested in order to prevent or delay progression of symptoms. To date, there has been no consistent meta-analytical evidence to support efficacy of antipsychotic treatment for patients in the prodromal state, and their use remains therefore inconclusive. Although antipsychotics may manage symptoms transiently, they have not been found to prevent or delay onset of psychotic disorders. Furthermore, pharmacological intervention in high-risk individuals remains controversial, because of the antipsychotic side effect profile in a population in which only about 20 to 35 percent will eventually convert to psychosis over a two-year period, with even after two years conversion rates not exceeding 30 to 40 percent. This general estimate is additionally problematic, in that it ignores the fact that there is significant variation in individual risk among clinical high-risk cases. The current lack of reliable tests for at-risk patients makes it difficult to justify individual treatment decisions. Preventive treatment should ideally be dictated by an individual’s risk while minimizing potentially harmful medication exposure. This requires more accurate predictive assessments by using valid and accessible prognostic markers. The following will compare prediction and risk modification potential of behavioral biomarkers such as disturbances of basic sense of self and emotion awareness, neurocognitive biomarkers such as attention, working and declarative memory, and neurophysiological biomarkers such as glutamatergic abnormalities and NMDA receptor dysfunction. Identification of robust biomarkers could therefore not only provide more reliable means of psychosis prediction, but also help test and develop new clinical interventions targeted at the prodromal state.

Keywords: at-risk mental state, biomarkers, glutamatergic system, NMDA receptor, psychosis prodrome, schizophrenia

Procedia PDF Downloads 195

Authors: Sutapa Som Chaudhury, Chitrangada Das Mukhopadhyay

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Alzheimer’s disease is a well-known form of dementia since its discovery in 1906. Current Food and Drug Administration approved medications e.g. cholinesterase inhibitors, memantine offer modest symptomatic relief but do not play any role in disease modification or recovery. In last three decades many small molecules, chaperons, synthetic peptides, partial β-secretase enzyme blocker have been tested for the development of a drug against Alzheimer though did not pass the 3rd clinical phase trials. Here in this study, we designed a PEGylated, aminogenic, tripeptidic polymer with two different molecular weights based on the aggregation prone amino acid sequence 17-20 in amyloid beta (Aβ) 1-42. Being conjugated with poly-ethylene glycol (PEG) which self-assembles into hydrophilic nanoparticles, these PEGylated tripeptides constitute a very good drug delivery system crossing the blood brain barrier while the peptide remains protected from proteolytic degradation and non-specific protein interactions. Moreover, being completely aminogenic they would not raise any side effects. These peptide inhibitors were evaluated for their effectiveness against Aβ42 fibrillation at an early stage of oligomer to fibril formation as well as preformed fibril clearance via Thioflavin T (ThT) assay, dynamic light scattering analyses, atomic force microscopy and scanning electron microscopy. The inhibitors were proved to be safe at a higher concentration of 20µM by the reduction assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) dye. Moreover, SHSY5Y neuroblastoma cells have shown a greater survivability when treated with the inhibitors following Aβ42 fibril and oligomer treatment as compared with the control Aβ42 fibril and/or oligomer treated neuroblastoma cells. These make the peptidic inhibitors a promising compound in the aspect of the discovery of alternative medication for Alzheimer’s disease.

Keywords: Alzheimer’s disease, alternative medication, amyloid beta, PEGylated peptide

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Authors: Nosakhare Enoma, Alphose Zingoni

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The requirements for various toroidal shell forms are increasing due to new applications, available storage space and the consideration of appearance. Because of the complexity of some of these structural forms, the finite element method is nowadays mainly used for their analysis, even for simple static studies. This paper presents an easy-to-use analytical algorithm for pressurized multi-segmented toroidal shells of revolution. The membrane solution, which acts as a particular solution of the bending-theory equations, is developed based on membrane theory of shells, and a general approach is formulated for quantifying discontinuity effects at the shell junctions using the well-known Geckeler’s approximation. On superimposing these effects, and applying the ensuing solution to the problem of the pressurized toroid with four segments, closed-form stress results are obtained for the entire toroid. A numerical example is carried out using the developed method. The analytical results obtained show excellent agreement with those from the finite element method, indicating that the proposed method can be also used for complementing and verifying FEM results, and providing insights on other related problems.

Keywords: bending theory of shells, membrane hypothesis, pressurized toroid, segmented toroidal vessel, shell analysis

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Authors: Vesna Lukovic

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Online platforms as new business models play an important role in today’s economy and the functioning of the EU’s internal market. In the travel industry, algorithms used by online platforms for short-stay accommodation provide suggestions and price information to travelers. Those suggestions and recommendations are displayed in search results via recommendation (ranking) systems. There has been a growing consensus that the current legal framework was not sufficient to resolve problems arising from platform practices. In order to enhance the potential of the EU’s Single Market, smaller businesses should be protected, and their rights strengthened vis-à-vis large online platforms. The Regulation (EU) 2019/1150 of the European Parliament and of the Council on promoting fairness and transparency for business users of online intermediation services aims to level the playing field in that respect. This research looks at Airbnb through the lenses of this regulation. The research explores key determinants and finds that although regulation is an important step in the right direction, it is not enough. It does not entail sufficient clarity obligations that would make online platforms an intermediary service which both accommodation providers and travelers could use with ease.

Keywords: algorithm, online platforms, ranking, consumers, EU regulation

Procedia PDF Downloads 130

Authors: Felix Givois, Nicolas R. Gauger, Matthias Kabel

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The efficient digital material characterization is of great interest to many fields of application. It consists of the following three steps. First, a 3D reconstruction of 2D scans must be performed. Then, the resulting gray-value image of the material sample is enhanced by image processing methods. Finally, partial differential equations (PDE) are solved on the segmented image, and by averaging the resulting solutions fields, effective properties like stiffness or conductivity can be computed. Due to the high resolution of current CT images, the latter is typically performed with matrix-free solvers. Among them, a solver that uses the explicit formula of the Green-Eshelby operator in Fourier space has been proposed by Moulinec and Suquet. Its algorithmic, most complex part is the Fast Fourier Transformation (FFT). In our talk, we will discuss the potential quantum advantage that can be obtained by replacing the FFT with the Quantum Fourier Transformation (QFT). We will especially show that the data transfer for noisy intermediate-scale quantum (NISQ) devices can be improved by using appropriate boundary conditions for the PDE, which also allows using semi-classical versions of the QFT. In the end, we will compare the results of the QFT-based algorithm for simple geometries with the results of the FFT-based homogenization method.

Keywords: most likelihood amplitude estimation (MLQAE), numerical homogenization, quantum Fourier transformation (QFT), NISQ devises

Procedia PDF Downloads 78

Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Hossam M. Abdallah, Ali M. El-Halawany, Gamal A. Mohamed, Khalid Z. Alshali, Zainy M. Banjar, Hany A. El-Bassossy

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Hypertension and vascular dysfunction are major components and complications of many diseases like metabolic syndrome. In addition, vascular dysfunction is considered the initial step in diabetic atherosclerosis, the main etiology for mortality and a great percent of morbidity in diabetic patients. In spite of the significant developments in antidiabetic therapy, diabetic complications, particularly seen in long-term diabetes, continue to be seriously deleterious. Herbal drugs are prescribed widely in treatment of different aliment because of their effectiveness, fewer side effects and relatively low cost. Nine plants belong to five different families grown in Kingdom of Saudi Arabia were evaluated for their effect on exaggerated vasoconstriction and impaired relaxation in aortae isolated from metabolic syndrome rats. The aerial parts of Onopordum ambiguum Fresen. (OA), Astragalus abyssinicus Steud. (AA), Pulicaria Arabica Cass. (PA), Echinops sheilae Kit Tan (ES), Aizoon canariense L. (AC), Cleome viscosa L. (CV), Chrozophora oblongifolia (Delile) A.Juss. ex Spreng (CO), Centaurea pseudosinaica Mouterde (CP) and Tephrosia nubica Baker (TN) were dried and extracted with methanol. The effect of thirty minute incubation with the total extracts (10-330 µg/ml) or their fractions on the exaggerated vasoconstriction response to phenylephrine (10nM to 10microM) and impaired vasodilation to acetylcholine (10-330 µg /ml) of aortae isolated from metabolic syndrome animals was studied. Incubating aortae isolated from metabolic syndrome animals with total methanol extract of OA, AA, PA, AC, CV, and TN at concentrations (10-330 microgram/ml) in the organ bath led to concentration dependent alleviation of exaggerated vasoconstriction response to phenylephrine without having beneficial effect on impaired vasodilation to acetylcholine. In conclusion, addition of OA, AA, PA, AC, CV and TN to the standard therapies may provide superior means to alleviate the associated vascular complications.

Keywords: vascular dysfunction, exaggerated vasoconstriction, metabolic syndrome, Saudi plants

Procedia PDF Downloads 279

Authors: Afsaneh Soltani, Zahra Mohajer

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Migraine is one of the most common chronic neurological diseases. Migraines affect different aspects of life. Severe migraine headaches lead to dysfunction, a reduced presence at work, and decreased ability to think and make decisions. Non-pharmacological treatments play a very important role in controlling and preventing migraine headaches. A healthy lifestyle helps control migraine headaches. Migraine headaches can be reduced by following these steps: Avoiding stress, eating regularly and avoiding hunger and thirst, avoiding stimulants such as chocolate, caffeine, and cigarettes, following a regular bedtime routine, or avoiding sleep deprivation. Exercise a lot, and do regular exercise (and prevent obesity). Non-pharmacological treatment is especially important in pregnant women and children because in these cases, medical treatments are not preferred due to the many side effects. Exercise is one of the most effective and uncomplicated non-pharmacological alternatives in the treatment of migraine headaches. Exercising for episodic migraines is a safe, effective, and promising complementary treatment option. Numerous studies have shown that aerobic exercise reduces the severity and duration of migraine headaches. Effective aerobic exercise includes cycling and brisk walking. Exercise improves the quality of life and reduces the use of medication in people with migraines. Patients who exercise have fewer migraine days, resulting in better personal, social, and occupational performance. Several studies have shown that pain intensity and frequency in patients who exercise regularly decreased significantly after exercise compared to controls who did not exercise. According to a study, regular exercise reduces the levels of interleukins, especially IL-12P70, which reduces anxiety and reduces the number of days of migraine in patients. An article has shown that endurance exercise reduces the number of migraine days and also increases cerebrovascular health in migraine patients. According to studies, the minimum duration of exercise to achieve a positive effect of exercise in patients with migraine is 3 months (12 weeks) and 40 minutes three times a week.

Keywords: exercise, headache, migraine, physical activity

Procedia PDF Downloads 107

Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

Procedia PDF Downloads 134

Authors: M. Iruleswari, A. Jeyapaul Murugan

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Most fundamental part used in many Digital Signal Processing (DSP) application is a Finite Impulse Response (FIR) filter because of its linear phase, stability and regular structure. Designing a high-speed and hardware efficient FIR filter is a very challenging task as the complexity increases with the filter order. In most applications the higher order filters are required but the memory usage of the filter increases exponentially with the order of the filter. Using multipliers occupy a large chip area and need high computation time. Multiplier-less memory-based techniques have gained popularity over past two decades due to their high throughput processing capability and reduced dynamic power consumption. This paper describes the design and implementation of highly efficient Look-Up Table (LUT) based circuit for the implementation of FIR filter using Distributed arithmetic algorithm. It is a multiplier less FIR filter. The LUT can be subdivided into a number of LUT to reduce the memory usage of the LUT for higher order filter. Analysis on the performance of various filter orders with different address length is done using Xilinx 14.5 synthesis tool. The proposed design provides less latency, less memory usage and high throughput.

Keywords: finite impulse response, distributed arithmetic, field programmable gate array, look-up table

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Authors: Shanza Akram, Samir Salah, Imran Saleem, Jassim Abdou, Ashraf Al Zaabi

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Estimated prevalence of asthma in UAE is around 10% (900,000 people). Patients with persistent symptoms despite using high dose ICS plus a second controller +/- Oral steroids are considered to have severe asthma. Omalizumab (Xolair) is an anti-IgE monoclonal antibody approved as add-on therapy for severe allergic asthma. The objective of our study was to obtain baseline characteristics of our local cohort, to determine the efficacy of omalizumab based on clinical outcomes pre and post 52 weeks of treatment and to assess safety and tolerability. Medical records of patients receiving omalizumab therapy for asthma at Zayed Military Hospital, Abu Dhabi were retrospectively reviewed. Patients fulfilling the criteria for severe allergic asthma as per GINA guidelines were included. Asthma control over 12 months pre and post omalizumab were analyzed by taking into account the number of exacerbations, hospitalizations, maintenance of medication dosages, the need for reliever therapy and PFT’s. 21 patients (5 females) with mean age 41 years were included. The mean duration of therapy was 22 months. 19 (91%) patients had Allergic Rhinitis/Sinusitis. Mean serum total IgE level was 648 IU/ml (65-1859). 11 (52%) patients were on oral maintenance steroids pre-treatment. 7 patients managed to stop steroids on treatment while 4 were able to decrease the dosage. Mean exacerbation rate decreased from 5 per year pre-treatment to 1.36 while on treatment. The number of hospitalizations decreased from a mean of 2 per year to 0.9 per year. Reliever inhaler usage decreased from mean of 40 to 15 puffs per week.2 patients discontinued therapy, 1 due to lack of benefit (2 doses) and 2nd due to severe persistent side effects. Patient compliance was poor in some cases. Treatment with omalizumab reduced the number of exacerbations, hospitalizations, maintenance and reliever medications, and is generally well tolerated. Our results show that there is room for improved documentation in terms of symptom recording and use of rescue medication at our institution. There is also need for better patient education and counseling in order to improve compliance.

Keywords: asthma, exacerbations, omalizumab, IgE

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Authors: Foyezunnesa Setu, S. M. Sharifuzzaman

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Cephalopods, belonging to the taxonomic class Cephalopoda under the phylum Mollusca, have a global distribution and are particularly common in the coastal waters of Bangladesh, specifically in the southeast and southwest regions. Identifying them can be difficult due to their pliable anatomical characteristics. Due to the presence of concealed cephalopod species within the orders Sepioidea, Teuthoidea, and Octopoda, these groupings of invertebrates, which share common characteristics, are frequently misidentified as distinct entities. Until now, cephalopods have been ignored because there is not enough knowledge about the specific species and the necessary preliminary research has not been done. This study offers a systematic description of various cephalopod species found along the south eastern coast of Bangladesh. A combined total of 25 cuttlefish specimens, four squid specimens, and five octopus specimens were gathered from the shores of Saint Martin's Island and Cox's Bazar. Based on morphological analysis, a total of 14 cephalopod species are identified. These species include Sepia aculeata, Sepia esculenta, Sepia pharaonis, Sepia prashadi, Sepiella inermis, Sepiella japonica, Uroteuthis duvauceli, Doryteuthis singhalensis, Sepioteuthis sepioidea, Eupryma stenodactyla, Amphioctopus aegina, Callistoctopus macropus, Octopus ceynea, and Octopus vulgaris. Six newly discovered species, including Sepia prashadi, Sepiella japonica, Sepioteuthis sepioidea, Eupryma stenodactyla, Callistoctopus macropus, and Octopus ceynea, have been identified in Bangladesh. Taxonomically, the identification of cephalopods is difficult due to the significant resemblance between species and the scarcity of information and preparatory research. This study offers significant insights about the cephalopod fauna found in the northern region of the Bay of Bengal.

Keywords: cephalopods, new records, northern bay of bengal, taxonomic identification

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Authors: Feyzan Tuzkaya, Nihan S. Soylu, Caglar Solak, Mehmet Peker, Hilal Peker, Kemal Ozeralp, Ceren Mete, Ezgi Mehmetoglu, Mehmet Karasu, Cihan Elci, Ece Akca, Melek Goregenli

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Perception, evaluation and representation of the environment have been the subject of many disciplines including psychology, geography and architecture. In environmental and social psychology literature there are several evidences which suggest that cognitive representations about a place consisted of not only geographic items but also social and cultural. Mental representations of residence area or a country is influenced and determined by social-demographics, the physical and social context. Thus, all mental representations of a given place are also social representations. Cognitive maps are the main and common instruments that are used to identify spatial images and the difference between physical and subjective environments. The aim of the current study is investigating the mental and social representations of Turkey in university students’ minds. Data was collected from 249 university students from different departments (i.e. psychology, geography, history, tourism departments) of Ege University. Participants were requested to reflect Turkey in their mind onto the paper drawing sketch maps. According to the results, cognitive maps showed geographic aspects of Turkey as well as the context of symbolic, cultural and political reality of Turkey. That is to say, these maps had many symbolic and verbal items related to critics on social and cultural problems, ongoing ethnic and political conflicts, and actual political agenda of Turkey. Additionally, one of main differentiations in these representations appeared in terms of the East and West side of the Turkey, and the representations of the East and West was varied correspondingly participants’ cultural background, their ethnic values, and where they have born. The results of the study were discussed in environmental and social psychological perspective considering cultural and social values of Turkey and current political circumstances of the country.

Keywords: cognitive maps, East, West, politics, social representations, Turkey

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Authors: Anamika A. Sharma, Arezou Ahmadi R. A., Narendra B. Parihar, Manjusha Sajith

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Introduction: Hemodialysis is the most effective therapeutic technique for patient with ESRD second to renal transplantation. However it is a lifelong therapy which requires frequent hospital, or dialysis centers visits mainly twice and thrice weekly, thus considerably changes the normal way of patient’s living. So this study aimed to Assess Health-Related Quality of life in End-Stage Renal Disease (ESRD) Undergoing Twice and Thrice weekly Hemodialysis. Method: A prospective observational, cross-sectional study was carried out from September 2016 to April 2017 in end-stage renal disease patients undergoing hemodialysis. Socio-demographic and clinical details of patients were obtained from the medical records. WHOQOL-BREF questionnaire was used to Access Health-Related Quality Of Life. Quality of Life scores of Twice weekly and Thrice weekly hemodialysis was analyzed by Kruskal Wallis Test. Results: Majority of respondents were male (72.55%), married (89.31%), employed (58.02%), belong to middle class (71.00%) and resides in rural area (58.78%). The mean ages in the patient undergoing twice weekly and thrice weekly hemodialysis were 51.89 ± 15.64 years and 51.33 ± 15.70 years respectively. Average Quality of Life scores observed in twice weekly and thrice weekly hemodialysis was 52.07 ± 13.30 (p=0.0037) and 52.87 ± 13.47 (p=0.0004) respectively. The hemoglobin of thrice weekly dialysis patients (10.28 gm/dL) was high as compared to twice weekly dialysis (9.23 gm/dL). Patients undergoing thrice weekly dialysis had improved serum urea, serum creatinine values (95.85 mg/dL, 8.32 mg/dL) as compared to twice weekly hemodialysis ( 104.94 mg/dL, 8.68 mg/dL). Conclusion: Our study concluded that there was no significant difference between overall Health-Related Quality Of Life in twice weekly and thrice weekly hemodialysis. Frequent hemodialysis was associated with improved control of hypertension, serum urea, serum creatinine levels.

Keywords: end stage renal disease, health related quality of life, twice weekly hemodialysis, thrice weekly hemodialysis

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Authors: Ruth Lorivi, Jianzheng Li, John J. Ambuchi, Kaiwen Deng

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Nitrogen removal from wastewater is accomplished by nitrification and denitrification processes. Successful denitrification requires carbon, therefore, if placed after biochemical oxygen demand (BOD) and nitrification process, a carbon source has to be re-introduced into the water. To avoid adding a carbon source, denitrification is usually placed before BOD and nitrification processes. This process however involves recycling the nitrified effluent. In this study wood chips were used as internal carbon source which enabled placement of denitrification after BOD and nitrification process without effluent recycling. To investigate the efficiency of a wood packed aerobic-anaerobic baffled reactor on carbon and nutrients removal from domestic wastewater, a three compartment baffled reactor was presented. Each of the three compartments was packed with 329 g wood chips 1x1cm acting as an internal carbon source for denitrification. The proposed mode of operation was aerobic-anoxic-anaerobic (OAA) with no effluent recycling. The operating temperature, hydraulic retention time (HRT), dissolved oxygen (DO) and pH were 24 ± 2 ℃, 24 h, less than 4 mg/L and 7 ± 1 respectively. The removal efficiencies of chemical oxygen demand (COD), ammonia nitrogen (NH₄⁺-N) and total nitrogen (TN) attained was 99, 87 and 83% respectively. TN removal rate was limited by nitrification as 97% of ammonia converted into nitrate and nitrite was denitrified. These results show that application of wood chips in wastewater treatment processes is an efficient internal carbon source. 

Keywords: aerobic-anaerobic baffled reactor, denitrification, nitrification, wood chip

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Authors: Dharshika Rajalingam, Jeffery W. Peng

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Acinetobacter baumannii is a challenging threat to global health, recognized as a multidrug-resistant pathogen. -lactamase is one of the principal resistant mechanisms developed by A. baumannii to survive against -lactam antibiotics. OXA24/40 is one of the types of -lactamases, a well-documented carbapenem hydrolyzing class D -lactamases (CHDL). It was revealed that OXA24/40 showed resistivity against doripenem, one of the carbapenems, by two different mechanisms as hydrolysis and -lactonization. Furthermore, it undergoes genetic mutations to broaden the -lactamase activity to survive against antibiotic environments. One of the crucial characterizations of prokaryotes to develop adaptation is post-translational modification (PTM), mainly phosphorylation. However, the PTM of OXA24/40 is an unknown feature, and the impact of PTM on antibiotic resistivity is yet to be explored. We approached these hypotheses using NMR and MS techniques and found that the OXA24/40 could be phosphorylated in vitro. The Ser81 at the active STFK motif of OXA24/40 of catalytic pocket was identified as the site of phosphorylation using 1D 31P NMR experiment, whereas S81 is required to form an acyl-enzyme complex between enzyme and -lactam antibiotics. The activity of completely phosphorylated OXA24/40 wild type against doripenem revealed that the phosphorylation of active Ser inactivates the -lactamases activity of OXA24/40. The 1D 1H CPMG NMR-based activity assay of phosphorylated OXA24/40 against doripenem confirmed that both deactivating mechanisms are inhibited by phosphorylation. Carbamylated Lysine at the active STFK motif is one of the critical features of CHDL required for the acylation and deacylation reactions of the enzyme. The 1D 13C NMR experiment confirmed that the K84 of phosphorylated OXA24/40 is de-carbamylated. Phosphorylation of OXA24/40 affects both active S81 and carbamylated K84 of OXA24 that are required for the resistivity of -lactamase. So, phosphorylation could be one of the reasons for the genetic mutation of OXA24/40 for the development of antibiotic resistivity. Further research can lead to an understanding of the effect of phosphorylation on the clinical mutants of the OXA24-like -lactamase family on the broadening of -lactamase activity.

Keywords: OXA24/40, phosphorylation, clinical mutants, resistivity

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Authors: T. Wanyama, B. Far

Abstract:

Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

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Authors: Qintao Shen, Lei Luo, Jun Ma, Jie Yu, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Control Flow Integrity (CFI) is one of the most promising technique to defend Code-Reuse Attacks (CRAs). Traditional CFI Systems and recent Context-Sensitive CFI use coarse control flow graphs (CFGs) to analyze whether the control flow hijack occurs, left vast space for attackers at indirect call-sites. Coarse CFGs make it difficult to decide which target to execute at indirect control-flow transfers, and weaken the existing CFI systems actually. It is an unsolved problem to extract CFGs precisely and perfectly from binaries now. In this paper, we present an algorithm to get a more precise CFG from binaries. Parameters are analyzed at indirect call-sites and functions firstly. By comparing counts of parameters prepared before call-sites and consumed by functions, targets of indirect calls are reduced. Then the control flow would be more constrained at indirect call-sites in runtime. Combined with CCFI, we implement our policy. Experimental results on some popular programs show that our approach is efficient. Further analysis show that it can mitigate COOP and other advanced attacks.

Keywords: contex-sensitive, CFI, binary analysis, code reuse attack

Procedia PDF Downloads 323