Search results for: sensory processing disorders
2306 An Overview of Suicidality in American Indians and Alaska Natives
Authors: Christopher S. Perez, Kendal C. Boyd
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global suicide rates have decreased in recent decades, rates in the United States have increased by 35.2 percent since 1999.American Indians and Alaska Natives (AI/AN) have the highest rates of suicide in the U.S., with approximately 22 suicides per 100,000 people as of 2019. AI/AN have experienced significant historical trauma resulting in disproportionate rates of substance abuse and mental disorders. This literature review aimed to identify the demographic and clinical risk and protective factors for American Indians and Alaska Natives and provide an overview of suicidality in this population. The literature reflected varying definitions of suicidality depending on region, with some AI/AN tribesconceptualizing suicide through a spiritual framework, while others defined suicide in the biomedical sense. Furthermore, AI/AN adults and adolescents experienced higher rates of suicidal ideation when compared to other racial groups. Religious preference, sexual orientation, prior suicidal behavior, psychiatric admission, history of abuse, substance abuse, family history of mental illness, family history of substance abuse, family history of suicidal behaviors, domestic violence, and trauma were discussed as factors related to suicidality. Recommendations included increasing access to and utilization of mental health and medical services, culturally adapting suicide prevention programs to AI/AN communities, increasing support for LGBTQ+ AI/AN, providing opportunities that reinforce ethnic identity, and post-hospitalization follow-up care. The following databases were utilized to obtain peer-reviewed articles for this literature review: Complementary Index, Academic Search Premier, Science Direct, PsycInfo, Social Sciences Citation Index, PsycArticles, PubMed, EbscoHost, and PsycBooks. Articles that examined Native populations outside of the United States did not cite a primary source and/or were published before 1990 were excluded.Keywords: alaska native, american indian, protective factors, risk factors, suicidality, suicide
Procedia PDF Downloads 1012305 Identification of ω-3 Fatty Acids Using GC-MS Analysis in Extruded Spelt Product
Authors: Jelena Filipovic, Marija Bodroza-Solarov, Milenko Kosutic, Nebojsa Novkovic, Vladimir Filipovic, Vesna Vucurovic
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Spelt wheat is suitable raw material for extruded products such as pasta, special types of bread and other products of altered nutritional characteristics compared to conventional wheat products. During the process of extrusion, spelt is exposed to high temperature and high pressure, during which raw material is also mechanically treated by shear forces. Spelt wheat is growing without the use of pesticides in harsh ecological conditions and in marginal areas of cultivation. So it can be used for organic and health safe food. Pasta is the most popular foodstuff; its consumption has been observed to rise. Pasta quality depends mainly on the properties of flour raw materials, especially protein content and its quality but starch properties are of a lesser importance. Pasta is characterized by significant amounts of complex carbohydrates, low sodium, total fat fiber, minerals, and essential fatty acids and its nutritional value can be improved with additional functional component. Over the past few decades, wheat pasta has been successfully formulated using different ingredients in pasta to cater health-conscious consumers who prefer having a product rich in protein, healthy lipids and other health benefits. Flaxseed flour is used in the production of bakery and pasta products that have properties of functional foods. However, it should be taken into account that food products retain the technological and sensory quality despite the added flax seed. Flaxseed contains important substances in its composition such as vitamins and minerals elements, and it is also an excellent source of fiber and one of the best sources of ω-3 fatty acids and lignin. In this paper, the quality and identification of spelt extruded product with the addition of flax seed, which is positively contributing to the nutritive and technology changes of the product, is investigated. ω-3 fatty acids are polyunsaturated essential fatty acids, and they must be taken with food to satisfy the recommended daily intake. Flaxseed flour is added in the quantity of 10/100 g of sample and 20/100 g of sample on farina. It is shown that the presence of ω-3 fatty acids in pasta can be clearly distinguished from other fatty acids by gas chromatography with mass spectrometry. Addition of flax seed flour influence chemical content of pasta. The addition of flax seed flour in spelt pasta in the quantities of 20g/100 g significantly increases the share of ω-3 fatty acids, which results in improved ratio of ω-6/ω-3 1:2.4 and completely satisfies minimum daily needs of ω-3 essential fatty acids (3.8 g/100 g) recommended by FDA. Flex flour influenced the pasta quality by increasing of hardness (2377.8 ± 13.3; 2874.5 ± 7.4; 3076.3 ± 5.9) and work of shear (102.6 ± 11.4; 150.8 ± 11.3; 165.0 ± 18.9) and increasing of adhesiveness (11.8 ± 20.6; 9.,98 ± 0.12; 7.1 ± 12.5) of the final product. Presented data point at good indicators of technological quality of spelt pasta with flax seed and that GC-MS analysis can be used in the quality control for flax seed identification. Acknowledgment: The research was financed by the Ministry of Education and Science of the Republic of Serbia (Project No. III 46005).Keywords: GC-MS analysis, ω-3 fatty acids, flex seed, spelt wheat, daily needs
Procedia PDF Downloads 1642304 Impact of Wastewater Irrigation on Soil and Vegetable Quality in Peri Urban Cropping System
Authors: Neelam Patel
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Farmers in peri-urban areas of developing countries depend on wastewater for Irrigation but with great environmental and health hazards. Since, irrigation with wastewater is growing in the developing countries but its suitability to environment and other health factors should be checked. Metal pollution is a very serious issue these days, various neuro, physical and mental disorders are prevailing due to the metal pollution. Waste water contaminated with heavy metals got accumulated in the soil and then bioaccumulated in the vegetables irrigated with waste water. A 3-year field experiment on cauliflower has been done by using wastewater with two different methods of irrigation i.e. Drip and Flood irrigation and checked the impact on the cauliflower and soil quality. Heavy metals (Cr, Cu, Ni, Zn and Pb) have been studied in wastewater used for the irrigation and their accumulation in the soil and vegetable was studied. The study reveals that the concentration of heavy metals increases by 100 times from initial in soil. After 3 years, the concentration of Copper(41 ppm) Chromium(39.4 ppm) Lead(62.2ppm) Zinc(100.5 ppm) and Nickel(75.7 ppm) in Flood irrigated soil while in Drip irrigated soil , Copper (36.4 ppm) Chromium(36.8 ppm) Lead(53.7 ppm) Zinc(70.3 ppm) and Nickel (53.9 ppm). In vegetable, the wastewater irrigated shows an increase in the concentration of metals with the time and the accumulation of Nickel (6.98ppm), Lead (30.18 ppm) and Zinc (55.83 ppm) in drip irrigated while in flood irrigated, Nickel (30.58 ppm), Lead (73.95ppm) Zinc (93.50 ppm) and Copper (54.58 ppm) in edible part of cauliflower which is above the permissible limits suggested by different international agencies. On other hand, the nutrients content i.e. Nitrogen, Phosphorus and Potassium in soil was increased in concentration with time. The study pointed out that the metal contaminated waste water consisting the nutrients in it but also heavy metals which causes health issues in human. While the increase in concentration of nutrients in the soil indirectly helpful to the farmers economically by restricting the use of fertilizers. But the metal pollution directly affects the health of human being. The different method of irrigation suggested that the drip irrigated vegetable acquired less metal then the flood one and is a better combo with the waste water for the irrigation.Keywords: drip irrigation, heavy metals, metal contamination, waste water
Procedia PDF Downloads 3302303 Psycho-Social Predictors of Health-Related Quality of Life among Persons Living with Benign Prostatic Hyperplasia in Ibadan, Nigeria
Authors: A. C. Obosi, H. O. Osinowo, L. I. Okeke
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Benign prostatic hyperplasia (BPH) is one among other prostate diseases with an increasing public health concern. The prevalence and increased psychological distress of BPH among men negatively impact on their health-related quality of life (HRQoL). Although several biomedical factors have been implicated in poor HRQoL among people with BPH, there is a dearth of research on the psychosocial factors predicting HRQoL among them especially in developing climes. This study, therefore, examined the psychosocial (knowledge, perceived stigma, depression, anxiety, perceived social support and illness acceptance) predictors of health-related quality of life among persons living with BPH in Ibadan, Nigeria. Biopsychosocial model and Health-related Quality of life guided this study which utilized ex-post facto design. Eighty-seven males living with BPH were purposively selected and actively participated in the study. Participants’ mean age was 61.77 ± 15.80 years. A standardized questionnaire comprising Socio-demographics and measures of health-related quality of life (α = 0.47); knowledge (α = 0.72); psychological distress (α = 0.95); perceived social support (α = 0.96) and Illness acceptance (α = 0.89) scales was utilized in the study. Data were content analysed, while bivariate correlation, hierarchical multiple regression and t-test for independent samples were computed at p < 0.05. Results revealed that 42.5% of the respondents reported poor HRQoL. Furthermore, age, length of illness, perceived stigma, depression, anxiety, knowledge, perceived social support and illness acceptance jointly predicted HRQoL significantly (R2=0.33, F(9,75)=4.05) and accounted for 33% variance in the total observed variance on HRQoL, while Illness acceptance (β=0.43), anxiety (β=-0.54), and perceived social support (β=0.16) had significant independent contributions to the observed variance on HRQoL. Illness acceptance, knowledge, perceived social support and psychological distress such as anxiety, depression and perceived stigma are important predictors of HRQoL. Therefore, it was recommended that urgent psychological intervention targeted at improving the quality of life of these persons be undertaken.Keywords: benign prostatic hyperplasia, Health-related quality of life, prostate disorders, psychosocial factors
Procedia PDF Downloads 2212302 Prediction of Vapor Liquid Equilibrium for Dilute Solutions of Components in Ionic Liquid by Neural Networks
Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi
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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.Keywords: ionic liquid, neural networks, VLE, dilute solution
Procedia PDF Downloads 3012301 Using the M-Learning to Support Learning of the Concept of the Derivative
Authors: Elena F. Ruiz, Marina Vicario, Chadwick Carreto, Rubén Peredo
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One of the main obstacles in Mexico’s engineering programs is math comprehension, especially in the Derivative concept. Due to this, we present a study case that relates Mobile Computing and Classroom Learning in the “Escuela Superior de Cómputo”, based on the Educational model of the Instituto Politécnico Nacional (competence based work and problem solutions) in which we propose apps and activities to teach the concept of the Derivative. M- Learning is emphasized as one of its lines, as the objective is the use of mobile devices running an app that uses its components such as sensors, screen, camera and processing power in classroom work. In this paper, we employed Augmented Reality (ARRoC), based on the good results this technology has had in the field of learning. This proposal was developed using a qualitative research methodology supported by quantitative research. The methodological instruments used on this proposal are: observation, questionnaires, interviews and evaluations. We obtained positive results with a 40% increase using M-Learning, from the 20% increase using traditional means.Keywords: augmented reality, classroom learning, educational research, mobile computing
Procedia PDF Downloads 3622300 Review of the Software Used for 3D Volumetric Reconstruction of the Liver
Authors: P. Strakos, M. Jaros, T. Karasek, T. Kozubek, P. Vavra, T. Jonszta
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In medical imaging, segmentation of different areas of human body like bones, organs, tissues, etc. is an important issue. Image segmentation allows isolating the object of interest for further processing that can lead for example to 3D model reconstruction of whole organs. Difficulty of this procedure varies from trivial for bones to quite difficult for organs like liver. The liver is being considered as one of the most difficult human body organ to segment. It is mainly for its complexity, shape versatility and proximity of other organs and tissues. Due to this facts usually substantial user effort has to be applied to obtain satisfactory results of the image segmentation. Process of image segmentation then deteriorates from automatic or semi-automatic to fairly manual one. In this paper, overview of selected available software applications that can handle semi-automatic image segmentation with further 3D volume reconstruction of human liver is presented. The applications are being evaluated based on the segmentation results of several consecutive DICOM images covering the abdominal area of the human body.Keywords: image segmentation, semi-automatic, software, 3D volumetric reconstruction
Procedia PDF Downloads 2922299 Effect of Kenaf Fibres on Starch-Grafted-Polypropylene Biopolymer Properties
Authors: Amel Hamma, Allesandro Pegoretti
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Kenaf fibres, with two aspect ratios, were melt compounded with two types of biopolymers named starch grafted polypropylene, and then blends compression molded to form plates of 1 mm thick. Results showed that processing induced variation of fibres length which is quantified by optical microscopy observations. Young modulus, stress at break and impact resistance values of starch-grafted-polypropylenes were remarkably improved by kenaf fibres for both matrixes and demonstrated best values when G906PJ were used as matrix. These results attest the good interfacial bonding between the matrix and fibres even in the absence of any interfacial modification. Vicat Softening Point and storage modules were also improved due to the reinforcing effect of fibres. Moreover, short-term tensile creep tests have proven that kenaf fibres remarkably improve the creep stability of composites. The creep behavior of the investigated materials was successfully modeled by the four parameters Burgers model.Keywords: creep behaviour, kenaf fibres, mechanical properties, starch-grafted-polypropylene
Procedia PDF Downloads 2332298 Reproducibility of Dopamine Transporter Density Measured with I-123-N-ω-Fluoropropyl-2β-Carbomethoxy-3β-(4-Iodophenyl)Nortropane SPECT in Phantom Studies and Parkinson’s Disease Patients
Authors: Yasuyuki Takahashi, Genta Hoshi, Kyoko Saito
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Objectives: The objective of this study was to evaluate the reproducibility of I-123-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4- iodophenyl) nortropane (I-123 FP-CIT) SPECT by using specific binding ratio (SBR) in phantom studies and Parkinson’s Disease (PD) patients. Methods: We made striatum phantom originally and confirmed reproducibility. The phantom studies changed head position and accumulation of FP-CIT, each. And image processing confirms influence on SBR by 30 cases. 30 PD received a SPECT for 3 hours post injection of I-123 FP-CIT 167MBq. Results: SBR decreased in rotatory direction by the patient position by the phantom studies. And, SBR improved the influence after the attenuation and the scatter correction in the cases (y=0.99x+0.57 r2=0.83). However, Stage II recognized dispersion in SBR by low accumulation. Conclusion: Than the phantom studies that assumed the normal cases, the SPECT image after the attenuation and scatter correction had better reproducibility.Keywords: 123I-FP-CIT, specific binding ratio, Parkinson’s disease
Procedia PDF Downloads 4302297 Metareasoning Image Optimization Q-Learning
Authors: Mahasa Zahirnia
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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process
Procedia PDF Downloads 2172296 Real-Time Lane Marking Detection Using Weighted Filter
Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan
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Nowadays, advanced driver assistance systems (ADAS) have become popular, since they enable safe driving. Lane detection is a vital step for ADAS. The performance of the lane detection process is critical to obtain a high accuracy lane departure warning system (LDWS). Challenging factors such as road cracks, erosion of lane markings, weather conditions might affect the performance of a lane detection system. In this paper, 1-D weighted filter based on row filtering to detect lane marking is proposed. 2-D input image is filtered by 1-D weighted filter considering four-pixel values located symmetrically around the center of candidate pixel. Performance evaluation is carried out by two metrics which are true positive rate (TPR) and false positive rate (FPR). Experimental results demonstrate that the proposed approach provides better lane marking detection accuracy compared to the previous methods while providing real-time processing performance.Keywords: lane marking filter, lane detection, ADAS, LDWS
Procedia PDF Downloads 1952295 Software-Defined Networks in Utility Power Networks
Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian
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Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller
Procedia PDF Downloads 1142294 Deep Learning-Based Classification of 3D CT Scans with Real Clinical Data; Impact of Image format
Authors: Maryam Fallahpoor, Biswajeet Pradhan
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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format
Procedia PDF Downloads 902293 Improving the Security of Internet of Things Using Encryption Algorithms
Authors: Amirhossein Safi
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Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.Keywords: internet of things, security, hybrid algorithm, privacy
Procedia PDF Downloads 4702292 Wireless Based System for Continuous Electrocardiography Monitoring during Surgery
Authors: K. Bensafia, A. Mansour, G. Le Maillot, B. Clement, O. Reynet, P. Ariès, S. Haddab
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This paper presents a system designed for wireless acquisition, the recording of electrocardiogram (ECG) signals and the monitoring of the heart’s health during surgery. This wireless recording system allows us to visualize and monitor the state of the heart’s health during a surgery, even if the patient is moved from the operating theater to post anesthesia care unit. The acquired signal is transmitted via a Bluetooth unit to a PC where the data are displayed, stored and processed. To test the reliability of our system, a comparison between ECG signals processed by a conventional ECG monitoring system (Datex-Ohmeda) and by our wireless system is made. The comparison is based on the shape of the ECG signal, the duration of the QRS complex, the P and T waves, as well as the position of the ST segments with respect to the isoelectric line. The proposed system is presented and discussed. The results have confirmed that the use of Bluetooth during surgery does not affect the devices used and vice versa. Pre- and post-processing steps are briefly discussed. Experimental results are also provided.Keywords: electrocardiography, monitoring, surgery, wireless system
Procedia PDF Downloads 3712291 Overview of Resources and Tools to Bridge Language Barriers Provided by the European Union
Authors: Barbara Heinisch, Mikael Snaprud
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A common, well understood language is crucial in critical situations like landing a plane. For e-Government solutions, a clear and common language is needed to allow users to successfully complete transactions online. Misunderstandings here may not risk a safe landing but can cause delays, resubmissions and drive costs. This holds also true for higher education, where misunderstandings can also arise due to inconsistent use of terminology. Thus, language barriers are a societal challenge that needs to be tackled. The major means to bridge language barriers is translation. However, achieving high-quality translation and making texts understandable and accessible require certain framework conditions. Therefore, the EU and individual projects take (strategic) actions. These actions include the identification, collection, processing, re-use and development of language resources. These language resources may be used for the development of machine translation systems and the provision of (public) services including higher education. This paper outlines some of the existing resources and indicate directions for further development to increase the quality and usage of these resources.Keywords: language resources, machine translation, terminology, translation
Procedia PDF Downloads 3202290 Residual Modulus of Elasticity of Self-Compacting Concrete Incorporated Unprocessed Waste Fly Ash after Expose to the Elevated Temperature
Authors: Mohammed Abed, Rita Nemes, Salem Nehme
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The present study experimentally investigated the impact of incorporating unprocessed waste fly ash (UWFA) on the residual mechanical properties of self-compacting concrete (SCC) after exposure to elevated temperature. Three mixtures of SCC have been produced by replacing the cement mass by 0%, 15% and 30% of UWFA. Generally, the fire resistance of SCC has been enhanced by replacing the cement up to 15% of UWFA, especially in case of residual modulus of elasticity which considers more sensitive than other mechanical properties at elevated temperature. However, a strong linear relationship has been observed between the residual flexural strength and modulus of elasticity, where both of them affected significantly by the cracks appearance and propagation as a result of elevated temperature. Sustainable products could be produced by incorporating unprocessed waste powder materials in the production of concrete, where the waste materials, CO2 emissions, and the energy needed for processing are reduced.Keywords: self-compacting high-performance concrete, unprocessed waste fly ash, fire resistance, residual modulus of elasticity
Procedia PDF Downloads 1362289 Characterization and Degradation Analysis of Tapioca Starch Based Biofilms
Authors: R. R. Ali, W. A. W. A. Rahman, R. M. Kasmani, H. Hasbullah, N. Ibrahim, A. N. Sadikin, U. A. Asli
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In this study, tapioca starch which acts as natural polymer was added in the blend in order to produce biodegradable product. Low density polyethylene (LDPE) and tapioca starch blends were prepared by extrusion and the test sample by injection moulding process. Ethylene vinyl acetate (EVA) acts as compatibilizer while glycerol as processing aid was added in the blend. The blends were characterized by using melt flow index (MFI), fourier transform infrared (FTIR) and the effects of water absorption to the sample. As the starch content increased, MFI of the blend was decreased. Tensile testing were conducted shows the tensile strength and elongation at break decreased while the modulus increased as the starch increased. For the biodegradation, soil burial test was conducted and the loss in weight was studied as the starch content increased. Morphology studies were conducted in order to show the distribution between LDPE and starch.Keywords: biopolymers, degradable polymers, starch based polyethylene, injection moulding
Procedia PDF Downloads 2882288 Efficient Layout-Aware Pretraining for Multimodal Form Understanding
Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose
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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention
Procedia PDF Downloads 1532287 Structural Characterization and Hot Deformation Behaviour of Al3Ni2/Al3Ni in-situ Core-shell intermetallic in Al-4Cu-Ni Composite
Authors: Ganesh V., Asit Kumar Khanra
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An in-situ powder metallurgy technique was employed to create Ni-Al3Ni/Al3Ni2 core-shell-shaped aluminum-based intermetallic reinforced composites. The impact of Ni addition on the phase composition, microstructure, and mechanical characteristics of the Al-4Cu-xNi (x = 0, 2, 4, 6, 8, 10 wt.%) in relation to various sintering temperatures was investigated. Microstructure evolution was extensively examined using X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), and transmission electron microscopy (TEM) techniques. Initially, under sintering conditions, the formation of "Single Core-Shell" structures was observed, consisting of Ni as the core with Al3Ni2 intermetallic, whereas samples sintered at 620°C exhibited both "Single Core-Shell" and "Double Core-Shell" structures containing Al3Ni2 and Al3Ni intermetallics formed between the Al matrix and Ni reinforcements. The composite achieved a high compressive yield strength of 198.13 MPa and ultimate strength of 410.68 MPa, with 24% total elongation for the sample containing 10 wt.% Ni. Additionally, there was a substantial increase in hardness, reaching 124.21 HV, which is 2.4 times higher than that of the base aluminum. Nanoindentation studies showed hardness values of 1.54, 4.65, 21.01, 13.16, 5.52, 6.27, and 8.39GPa corresponding to α-Al matrix, Ni, Al3Ni2, Ni and Al3Ni2 interface, Al3Ni, and their respective interfaces. Even at 200°C, it retained 54% of its room temperature strength (90.51 MPa). To investigate the deformation behavior of the composite material, experiments were conducted at deformation temperatures ranging from 300°C to 500°C, with strain rates varying from 0.0001s-1 to 0.1s-1. A sine-hyperbolic constitutive equation was developed to characterize the flow stress of the composite, which exhibited a significantly higher hot deformation activation energy of 231.44 kJ/mol compared to the self-diffusion of pure aluminum. The formation of Al2Cu intermetallics at grain boundaries and Al3Ni2/Al3Ni within the matrix hindered dislocation movement, leading to an increase in activation energy, which might have an adverse effect on high-temperature applications. Two models, the Strain-compensated Arrhenius model and the Artificial Neural Network (ANN) model, were developed to predict the composite's flow behavior. The ANN model outperformed the Strain-compensated Arrhenius model with a lower average absolute relative error of 2.266%, a smaller root means square error of 1.2488 MPa, and a higher correlation coefficient of 0.9997. Processing maps revealed that the optimal hot working conditions for the composite were in the temperature range of 420-500°C and strain rates between 0.0001s-1 and 0.001s-1. The changes in the composite microstructure were successfully correlated with the theory of processing maps, considering temperature and strain rate conditions. The uneven distribution in the shape and size of Core-shell/Al3Ni intermetallic compounds influenced the flow stress curves, leading to Dynamic Recrystallization (DRX), followed by partial Dynamic Recovery (DRV), and ultimately strain hardening. This composite material shows promise for applications in the automobile and aerospace industries.Keywords: core-shell structure, hot deformation, intermetallic compounds, powder metallurgy
Procedia PDF Downloads 232286 Method for Improving Antidepressants Adherence in Patients with Depressive Disorder: Systemic Review and Meta-Analysis
Authors: Juntip Kanjanasilp, Ratree Sawangjit, Kanokporn Meelap, Kwanchanok Kruthakool
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Depression is a common mental health disorder. Antidepressants are effective pharmacological treatments, but most patients have low medication adherence. This study aims to systematic review and meta-analysis what method increase the antidepressants adherence efficiently and improve clinical outcome. Systematic review of articles of randomized controlled trials obtained by a computerized literature search of The Cochrane, Library, Pubmed, Embase, PsycINFO, CINAHL, Education search, Web of Science and ThaiLIS (28 December 2017). Twenty-three studies were included and assessed the quality of research by ROB 2.0. The results reported that printing media improved in number of people who had medication adherence statistical significantly (p= 0.018), but education, phone call, and program utilization were no different (p=0.172, p=0.127, p=0.659). There was no significant difference in pharmacist’s group, health care team’s group and physician’s group (p=0.329, p=0.070, p=0.040). Times of intervention at 1 month and 6 months improved medication adherence significantly (p= 0.0001, p=0.013). There was significantly improved adherence in single intervention (p=0.027) but no different in multiple interventions (p=0.154). When we analyzed medication adherence with the mean score, no improved adherence was found, not relevant with who gives the intervention and times to intervention. However, the multiple interventions group was statistically significant improved medication adherence (p=0.040). Phone call and the physician’s group were statistically significant improved clinical outcomes in number of improved patients (0.025 and 0.020, respectively). But in the pharmacist’s group and physician’s group were not found difference in the mean score of clinical outcomes (p=0.993, p=0.120, respectively). Times to intervention and number of intervention were not significant difference than usual care. The overall intervention can increase antidepressant adherence, especially the printing media, and the appropriate timing of the intervention is at least 6 months. For effective treatment, the provider should have experience and expert in caring for patients with depressive disorders, such as a psychiatrist. Medical personnel should have knowledge in caring for these patients also.Keywords: depression, medication adherence, clinical outcomes, systematic review, meta-analysis
Procedia PDF Downloads 1352285 Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images
Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar
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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages
Procedia PDF Downloads 2742284 A Strategy Therapy for Retinitis Pigmentosa Induced by Argon Laser in Rabbits by High Dose Adult Stem Cells
Authors: Hager E. Amer, Hany El Saftawy, Laila Rashed, Ahmed M. Ata, Fatma Metwally, Hesham Mettawei, Hossam E. Sayed, Tamer Adel, Kareem M. El Sawah
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Aim: The purpose of this study is to regenerate the damaged photoreceptor cells as a result of argon laser as a model of Retinitis Pigmentosa in rabbits' retina by using adult stem cells from rabbits' bone marrow. Background: Retinitis pigmentosa (RP) is a group of inherited disorders that primarily affect photoreceptor and pigment epithelium function. RP leads to loss of the rod outer segment and shorten the photoreceptor layer and expose the photoreceptor cell body to high-pressure levels in oxygen (oxidative stress) leads to apoptosis to the rod and cone cells. In particular, there is no specific treatment for retinitis pigmentosa. Materials and Methods: Forty Two Giant (Rex) rabbits were used in this experiment divided into 3 groups: Group 1: Control (6 rabbits), Group 2: Argon laser radiated as a model of retinitis pigmentosa (12 rabbits), Group 3: Laser radiated and treated by 6 million stem cells (12 rabbits). The last two groups are divided each into two subgroups each subgroup contains 6 rabbits, the ophthalmological examination was performed on rabbits, blood samples and retina samples were taken after 25 days and after 36 days from the laser radiation (10 days and 21 days after stem cells insertion in group 3) to perform the biochemical analysis. Results: Compared to control Group, a decrease of ERG wave amplitude and antioxidant substances (Glutathione) in blood and retina in group 2, and an increase of oxidative stress substances (Nitric oxide, Malonaldehyde, and carponyl protein) and apoptotic substances (Advanced glycation end product and M-metalloproteinase) in blood and retina. Compared to group 2, mostly increases of antioxidant substances and ERG wave amplitude in group 3, and mostly decreases in oxidative stress substances and apoptotic substances. Conclusion: Insertion of 6 million stem cells intravitreous gives good results in regeneration of the damaged photoreceptor cells after 21 days.Keywords: retinitis pigmentosa, stem cells, argon laser, oxidative stress, apoptosis
Procedia PDF Downloads 1992283 Neuropsychological Assessment and Rehabilitation Settings for Developmental Dyslexia in Children in Greece: The Use of Music at Intervention Protocols
Authors: Argyris B. Karapetsas, Rozi M. Laskaraki, Aikaterini A. Karapetsa, Maria Bampou, Valentini N. Vamvaka
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The main aim of the current protocol is the contribution of neuropsychology in both assessment and rehabilitation settings for children with dyslexia. Objectives: The purpose of this study was to evaluate the significant role of neuropsychological assessment including both Psychometric and electrophysiological tests as well as to investigate the effectiveness of an Auditory Training program, designed via Music designed for children with Developmental Dyslexia (DD). Materials: In our study, participated 45 third-, and fourth-grade students with DD and a matched control group (n=45). Method: At the first phase of the protocol, children underwent a clinical assessment, including both electrophysiological, i.e. Event Related Potentials (ERPs) esp. P300 waveform, and psychometric tests, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Assessment’s results confirmed statistically significant lower performance for children with DD for all tests, compared to the typical readers of the control group. After evaluation, a subgroup of children with DD participated in a Rehabilitation Program including digitized musical auditory training activities. Results: The electrophysiological recordings after the intervention revealed shorter, almost similar, P300 latency values for children with DD to those of the control group, indicating the beneficial effects of the Intervention, thus enabling children develop reading skills and become successful readers. Discussion: Similar research data confirm the crucial role of neuropsychology in both diagnosis and treatment of common disorders, observed in children. Indeed, as for DD, there is growing evidence that brain activity dysfunction does occur, as it is confirmed by neuropsychological assessment and also musical auditory training may have remedial effects. Conclusions: The outcomes of the current study suggest that due to the neurobiological origin of DD, neuropsychology may give the means in both neuropsychological assessment and rehabilitation, enabling professionals to cope with cerebral dysfunction and recovery more efficiently.Keywords: diagnosis, dyslexia, ERPs, Music, neuropsychology, rehabilitation
Procedia PDF Downloads 1352282 Monocular 3D Person Tracking AIA Demographic Classification and Projective Image Processing
Authors: McClain Thiel
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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.Keywords: monocular distancing, computer vision, facial analysis, 3D localization
Procedia PDF Downloads 1432281 Using a Robot Companion to Detect and Visualize the Indicators of Dementia Progression and Quality of Life of People Aged 65 and Older
Authors: Jeoffrey Oostrom, Robbert James Schlingmann, Hani Alers
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This document depicts the research into the indicators of dementia progression, the automation of quality of life assignments, and the visualization of it. To do this, the Smart Teddy project was initiated to make a smart companion that both monitors the senior citizen as well as processing the captured data into an insightful dashboard. With around 50 million diagnoses worldwide, dementia proves again and again to be a bothersome strain on the lives of many individuals, their relatives, and society as a whole. In 2015 it was estimated that dementia care cost 818 billion U.S Dollars globally. The Smart Teddy project aims to take away a portion of the burden from caregivers by automating the collection of certain data, like movement, geolocation, and sound-levels. This paper proves that the Smart Teddy has the potential to become a useful tool for caregivers but won’t pose as a solution. The Smart Teddy still faces some problems in terms of emotional privacy, but its non-intrusive nature, as well as diversity in usability, can make up for it.Keywords: dementia care, medical data visualization, quality of life, smart companion
Procedia PDF Downloads 1422280 Development of a Wind Resource Assessment Framework Using Weather Research and Forecasting (WRF) Model, Python Scripting and Geographic Information Systems
Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang
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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software
Procedia PDF Downloads 4432279 Simulation Study of the Microwave Heating of the Hematite and Coal Mixture
Authors: Prasenjit Singha, Sunil Yadav, Soumya Ranjan Mohantry, Ajay Kumar Shukla
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Temperature distribution in the hematite ore mixed with 7.5% coal was predicted by solving a 1-D heat conduction equation using an implicit finite difference approach. In this work, it was considered a square slab of 20 cm x 20 cm, which assumed the coal to be uniformly mixed with hematite ore. It was solved the equations with the use of MATLAB 2018a software. Heat transfer effects in this 1D dimensional slab convective and the radiative boundary conditions are also considered. Temperature distribution obtained inside hematite slab by considering microwave heating time, thermal conductivity, heat capacity, carbon percentage, sample dimensions, and many other factors such as penetration depth, permittivity, and permeability of coal and hematite ore mixtures. The resulting temperature profile can be used as a guiding tool for optimizing the microwave-assisted carbothermal reduction process of hematite slab was extended to other dimensions as well, viz., 1 cm x 1 cm, 5 cm x 5 cm, 10 cm x 10 cm, 20 cm x 20 cm. The model predictions are in good agreement with experimental results.Keywords: hematite ore, coal, microwave processing, heat transfer, implicit method, temperature distribution
Procedia PDF Downloads 1692278 Early Detection of Lymphedema in Post-Surgery Oncology Patients
Authors: Sneha Noble, Rahul Krishnan, Uma G., D. K. Vijaykumar
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Breast-Cancer related Lymphedema is a major problem that affects many women. Lymphedema is the swelling that generally occurs in the arms or legs caused by the removal of or damage to lymph nodes as a part of cancer treatment. Treating it at the earliest possible stage is the best way to manage the condition and prevent it from leading to pain, recurrent infection, reduced mobility, and impaired function. So, this project aims to focus on the multi-modal approaches to identify the risks of Lymphedema in post-surgical oncology patients and prevent it at the earliest. The Kinect IR Sensor is utilized to capture the images of the body and after image processing techniques, the region of interest is obtained. Then, performing the voxelization method will provide volume measurements in pre-operative and post-operative periods in patients. The formation of a mathematical model will help in the comparison of values. Clinical pathological data of patients will be investigated to assess the factors responsible for the development of lymphedema and its risks.Keywords: Kinect IR sensor, Lymphedema, voxelization, lymph nodes
Procedia PDF Downloads 1402277 Getting to Know the Types of Asphalt, Its Manufacturing and Processing Methods and Its Application in Road Construction
Authors: Hamid Fallah
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Asphalt is generally a mixture of stone materials with continuous granulation and a binder, which is usually bitumen. Asphalt is made in different shapes according to its use. The most familiar type of asphalt is hot asphalt or hot asphalt concrete. Stone materials usually make up more than 90% of the asphalt mixture. Therefore, stone materials have a significant impact on the quality of the resulting asphalt. According to the method of application and mixing, asphalt is divided into three categories: hot asphalt, protective asphalt, and cold asphalt. Cold mix asphalt is a mixture of stone materials and mixed bitumen or bitumen emulsion whose raw materials are mixed at ambient temperature. In some types of cold asphalt, the bitumen may be heated as necessary, but other materials are mixed with the bitumen without heating. Protective asphalts are used to make the roadbed impermeable, increase its abrasion and sliding resistance, and also temporarily improve the existing asphalt and concrete surfaces. This type of paving is very economical compared to hot asphalt due to the speed and ease of implementation and the limited need for asphalt machines and equipment. The present article, which is prepared in descriptive library form, introduces asphalt, its types, characteristics, and its application.Keywords: asphalt, type of asphalt, asphalt concrete, sulfur concrete, bitumen in asphalt, sulfur, stone materials
Procedia PDF Downloads 71