Search results for: proposed drought severity index

Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Jianli Jiang, Bai-Chen Xie

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The climate issue has aroused global concern. Achieving sustainable development is a good path for countries to mitigate environmental and climatic pressures, although there are many difficulties. The first step towards sustainable development is to evaluate the environmental efficiency of the energy industry with proper methods. The power sector is a major source of CO2, SO2, and NOx emissions. Evaluating the environmental efficiency (EE) of power systems is the premise to alleviate the terrible situation of energy and the environment. Data Envelopment Analysis (DEA) has been widely used in efficiency studies. However, measuring the efficiency of a system (be it a nation, region, sector, or business) is a challenging task. The classic DEA takes the decision-making units (DMUs) as independent, which neglects the interaction between DMUs. While ignoring these inter-regional links may result in a systematic bias in the efficiency analysis; for instance, the renewable power generated in a certain region may benefit the adjacent regions while the SO2 and CO2 emissions act oppositely. This study proposes a spatial network DEA (SNDEA) with a slack measure that can capture the spatial spillover effects of inputs/outputs among DMUs to measure efficiency. This approach is used to study the EE of China's power system, which consists of generation, transmission, and distribution departments, using a panel dataset from 2014 to 2020. In the empirical example, the energy and patent inputs, the undesirable CO2 output, and the renewable energy (RE) power variables are tested for a significant spatial spillover effect. Compared with the classic network DEA, the SNDEA result shows an obvious difference tested by the global Moran' I index. From a dynamic perspective, the EE of the power system experiences a visible surge from 2015, then a sharp downtrend from 2019, which keeps the same trend with the power transmission department. This phenomenon benefits from the market-oriented reform in the Chinese power grid enacted in 2015. The rapid decline in the environmental efficiency of the transmission department in 2020 was mainly due to the Covid-19 epidemic, which hinders economic development seriously. While the EE of the power generation department witnesses a declining trend overall, this is reasonable, taking the RE power into consideration. The installed capacity of RE power in 2020 is 4.40 times that in 2014, while the power generation is 3.97 times; in other words, the power generation per installed capacity shrank. In addition, the consumption cost of renewable power increases rapidly with the increase of RE power generation. These two aspects make the EE of the power generation department show a declining trend. Incorporation of the interactions among inputs/outputs into the DEA model, this paper proposes an efficiency evaluation method on the basis of the DEA framework, which sheds some light on efficiency evaluation in regional studies. Furthermore, the SNDEA model and the spatial DEA concept can be extended to other fields, such as industry, country, and so on.

Keywords: spatial network DEA, environmental efficiency, sustainable development, power system

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Authors: Senem Suna, Canan Ece Tamer, Ömer Utku Çopur

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In this research, dried linden (Tilia argentea) leaves and blossoms were used as a raw material for mineral enriched herbal tea beverage production. For this aim, %1 dried linden was infused with boiling water (100 °C) for 5 minutes. After cooling, sucrose, citric acid, ascorbic acid, natural lemon flavor and natural mineral water were added. Beverage samples were plate filtered, filled into 200-mL glass bottles, capped then pasteurized at 98 °C for 15 minutes. Water soluble dry matter, titratable acidity, ascorbic acid, pH, minerals (Fe, Ca, Mg, K, Na), color (L*, a*, b*), turbidity, bioaccessible phenolics and antioxidant capacity were analyzed. Water soluble dry matter, titratable acidity, and ascorbic were determined as 7.66±0.28 g/100 g, 0.13±0.00 g/100 mL, and 19.42±0.62 mg/100 mL, respectively. pH was measured as 3.69. Fe, Ca, Mg, K and Na contents of the beverage were determined as 0.12±0.00, 115.48±0.05, 34.72±0.14, 48.67±0.43 and 85.72±1.01 mg/L, respectively. Color was measured as 13.63±0.05, -4.33±0.05, and 3.06±0.05 for L*, a*, and b* values. Turbidity was determined as 0.69±0.07 NTU. Bioaccessible phenolics were determined as 312.82±5.91 mg GAE/100 mL. Antioxidant capacities of chemical (MetOH:H₂O:HCl) and physiological extracts (in vitro digestive enzymatic extraction) with DPPH (27.59±0.53 and 0.17±0.02 μmol trolox/mL), FRAP (21.01±0.97 and 13.27±0.19 μmol trolox/mL) and CUPRAC (44.71±9.42 and 2.80±0.64 μmol trolox/mL) methods were also evaluated. As a result, enrichment with natural mineral water was proposed for the development of functional and nutritional values together with a good potential for commercialization.

Keywords: linden, herbal tea beverage, bioaccessibility, antioxidant capacity

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Authors: Vandana Mohan, Ashwani Koul

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Aim: To evaluate the potential of Aqueous Tinospora cordifolia stem extract (Aq.Tc) and Arabinogalactan (AG) on pulmonary carcinogenesis and associated tumor markers. Background: Lung cancer is one of the most frequent malignancy with high mortality rate due to limitation of early detection resulting in low cure rates. Current research effort focuses on identifying some blood-based biomarkers like CEA, ctDNA and LDH which may have potential to detect cancer at an early stage, evaluation of therapeutic response and its recurrence. Medicinal plants and their active components have been widely investigated for their anticancer potentials. Aqueous preparation of T. Cordifolia extract is enriched in the polysaccharide fraction i.e., AG when compared with other types of extract. Moreover, reports are available of polysaccharide fraction of T. Cordifolia in in vitro lung cancer models which showed profound anti-metastatic activity against these cell lines. However, not much has been explored about its effect in in vivo lung cancer models and the underlying mechanism involved. Experimental Design: Mice were randomly segregated into six groups. Group I animals served as control. Group II animals were administered with Aq. Tc extract (200 mg/kg b.w.) p.o.on the alternate days. Group III animals were fed with AG (7.5 mg/kg b.w.) p.o. on the alternate days (thrice a week). Group IV animals were installed with Benzo(a)pyrene (50 mg/kg b.w.), i.p. twice within an interval of two weeks. Group V animals received Aq. Tc extract as in group II along with it B(a)P was installed after two weeks of Aq. Tc administration following the same protocol as for group IV. Group VI animals received AG as in group III along with it B(a)P was installed after two weeks of AG administration. Results: Administration of B(a)P to mice resulted in increased tumor incidence, multiplicity and pulmonary somatic index with concomitant increase in serum/plasma markers like CEA, ctDNA, LDH and TNF-α.Aq.Tc and AG supplementation significantly attenuated these alterations at different stages of tumorigenesis thereby showing potent anti-cancer effect in lung cancer. A pronounced decrease in serum/plasma markers were observed in animals treated with Aq.Tc as compared to those fed with AG. Also, extensive hyperproliferation of alveolar epithelium was prominent in B(a)P induced lung tumors. However, treatment of Aq.Tc and AG to lung tumor bearing mice exhibited reduced alveolar damage evident from decreased number of hyperchromatic irregular nuclei. A direct correlation between the concentration of tumor markers and the intensity of lung cancer was observed in animals bearing cancer co-treated with Aq.Tc and AG. Conclusion: These findings substantiate the chemopreventive potential of Aq.Tc and AG against lung tumorigenesis. Interestingly, Aq.Tc was found to be more effective in modulating the cancer as reflected by various observations which may be attributed to the synergism offered by various components of Aq.Tc. Further studies are in progress to understand the underlined mechanism in inhibiting lung tumorigenesis by Aq.Tc and AG.

Keywords: Arabinogalactan, Benzo(a)pyrene B(a)P, carcinoembryonic antigen (CEA), circulating tumor DNA (ctDNA), lactate dehydrogenase (LDH), Tinospora cordifolia

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Authors: Jonathan J. Foo, Keng Hao Chew

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Interest in virtual reality (VR) technologies as virtual learning environments have been on the rise in recent years. With thanks to the aggressively competitive consumer electronics environment, VR technology has been made affordable and accessible to the average person with developments like Google Cardboard and Oculus Go. While the promise of virtual access to unique virtual learning environments with the benefits of experiential learning sounds extremely attractive, there are still concerns over user comfort in the psychomotor, cognitive, and affective domains. Reports of motion sickness and short durations create doubt and have stunted its growth. In this paper, a multidimensional framework is proposed for the evaluation of VR learning environments within the three dimensions: tactual quality, didactic quality, and autodidactic quality. This paper further proposes a mixed-methods experimental research plan that sets out to evaluate a virtual reality training simulator in the context of amateur sports fencing. The study will investigate if an immersive VR learning environment can effectively simulate an authentic learning environment suitable for instruction, practice, and assessment while providing the user comfort in the tactual, didactic, and autodidactic dimensions. The models and recommendations developed for this study are designed in the context of fencing, but the potential impact is a guide for the future design and evaluation of all VR developments across sports and technical classroom education.

Keywords: autodidactic quality, didactic quality, tactual quality, virtual reality

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Authors: Aruha Khan, Brynn E. Kankel, Paraskevi Papadopoulou

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In recent years, extensive research upon ‘stress’ has provided insight into its two distinct guises, namely the short–term (fight–or–flight) response versus the long–term (chronic) response. Specifically, the long–term or chronic response is associated with the suppression or dysregulation of immune function. It is also widely noted that the occurrence of cancer is greatly correlated to the suppression of the immune system. It is thus necessary to explore the impact of long–term or chronic stress upon the prevalence and risk of cancer. To what extent can the dysregulation of immune function caused by long–term exposure to stress be controlled or minimized? This study focuses explicitly upon immunosuppression due to its ability to increase disease susceptibility, including cancer itself. Based upon an analysis of the literature relating to the fundamental structure of the immune system alongside the prospective linkage of chronic stress and the development of cancer, immunosuppression may not necessarily correlate directly to the acquisition of cancer—although it remains a contributing factor. A cross-sectional analysis of the survey data from the University of Tennessee Medical Center (UTMC) and Harvard Medical School (HMS) will provide additional supporting evidence (or otherwise) for the hypothesis of the study about whether immunosuppression (caused by the chronic stress response) notably impacts the prevalence of cancer. Finally, a multidimensional framework related to education on chronic stress and its effects is proposed.

Keywords: immune system, immunosuppression, long–term (chronic) stress, risk of cancer

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Authors: Saw Thiha, Jay Rajasekera

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A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Tim Crocker-Buque, Sandra Mounier-Jack, Natasha Howard

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Background: Due to both the increasing scale and speed of urbanisation, urban areas in low and middle-income countries (LMICs) host increasingly large populations of under-immunized children, with the additional associated risks of rapid disease transmission in high-density living environments. Multiple interdependent factors are associated with these coverage disparities in urban areas and most evidence comes from relatively few countries, e.g., predominantly India, Kenya, Nigeria, and some from Pakistan, Iran, and Brazil. This study aimed to identify, describe, and assess the main tools used to measure or improve coverage of immunisation services in poor urban areas. Methods: Authors used a qualitative review design, including academic and non-academic literature, to identify tools used to improve coverage of public health interventions in urban areas. Authors selected and extracted sources that provided good examples of specific tools, or categories of tools, used in a context relevant to urban immunization. Diagnostic (e.g., for data collection, analysis, and insight generation) and programme tools (e.g., for investigating or improving ongoing programmes) and interventions (e.g., multi-component or stand-alone with evidence) were selected for inclusion to provide a range of type and availability of relevant tools. These were then prioritised using a decision-analysis framework and a tool selection guide for programme managers developed. Results: Authors reviewed tools used in urban immunisation contexts and tools designed for (i) non-immunization and/or non-health interventions in urban areas, and (ii) immunisation in rural contexts that had relevance for urban areas (e.g., Reaching every District/Child/ Zone). Many approaches combined several tools and methods, which authors categorised as diagnostic, programme, and intervention. The most common diagnostic tools were cross-sectional surveys, key informant interviews, focus group discussions, secondary analysis of routine data, and geographical mapping of outcomes, resources, and services. Programme tools involved multiple stages of data collection, analysis, insight generation, and intervention planning and included guidance documents from WHO (World Health Organisation), UNICEF (United Nations Children's Fund), USAID (United States Agency for International Development), and governments, and articles reporting on diagnostics, interventions, and/or evaluations to improve urban immunisation. Interventions involved service improvement, education, reminder/recall, incentives, outreach, mass-media, or were multi-component. The main gaps in existing tools were an assessment of macro/policy-level factors, exploration of effective immunization communication channels, and measuring in/out-migration. The proposed framework uses a problem tree approach to suggest tools to address five common challenges (i.e. identifying populations, understanding communities, issues with service access and use, improving services, improving coverage) based on context and available data. Conclusion: This study identified many tools relevant to evaluating urban LMIC immunisation programmes, including significant crossover between tools. This was encouraging in terms of supporting the identification of common areas, but problematic as data volumes, instructions, and activities could overwhelm managers and tools are not always suitably applied to suitable contexts. Further research is needed on how best to combine tools and methods to suit local contexts. Authors’ initial framework can be tested and developed further.

Keywords: health equity, immunisation, low and middle-income countries, poverty, urban health

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Authors: Hasnizan Aksah, Adi Irfan Che Ani

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Refurbished historic government buildings should perform as intended to support the organization’s goals that enhance occupant satisfaction. However, these buildings may have issues associated with functional performance evaluation. The aim of this study is to develop a Post Occupancy Evaluation (POE) sustainability assessment tool for functional performance evaluation of refurbished historic government buildings. Developing an assessment tool requires a strategic methodology for a logical and cohesive tool that incorporating relevant theories and practical experiences. In this study, mixed method approaches use to collect all necessary data to achieve the objectives of this study. The design of sampling involves are interviews and survey questionnaires to relevant professionals in order to evaluate the criteria and problem encircled in functional performance evaluation. Then, the involvement of expert panels is required in establishing the assessment tool. During the process of investigation on the functional performance criteria, it was discovered that is seen to be critical in aspects of comfort, safety, and services. The proposed assessment tool has a significant role in providing opportunities for the improvement of building performance especially on functional performance for the future historic government building refurbishment project. It is hoped that the tool developed from this study will give benefits to related professionals, public agencies, local municipality, and relevant interested parties in historic building management.

Keywords: refurbished historic government buildings, functional performance, Post Occupancy Evaluation, sustainability

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Authors: M. Ananthakrishnan, Sunil K Patil, Koti Naveen, Inuganti Hemanth Kumar

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State estimation output of EMS forms the base case for all other advanced applications used in real time by a power system operator. Ensuring tuning of state estimator is a repeated process and cannot be left once a good solution is obtained. This paper attempts to demonstrate methods to improve state estimator solution by identifying incorrect modelling and telemetry inputs to the application. In this work, identification of database topology modelling error by plotting static network using node-to-node connection details is demonstrated with examples. Analytical methods to identify wrong transmission parameters, incorrect limits and mistakes in pseudo load and generator modelling are explained with various cases observed. Further, methods used for active and reactive power tuning using bus summation display, reactive power absorption summary, and transformer tap correction are also described. In a large power system, verifying all network static data and modelling parameter on regular basis is difficult .The proposed tuning methods can be easily used by operators to quickly identify errors to obtain the best possible state estimation performance. This, in turn, can lead to improved decision-support capabilities, ultimately enhancing the safety and reliability of the power grid.

Keywords: active power tuning, database modelling, reactive power, state estimator

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Authors: Jyoti Singh, Swati Dubey, Mukta Singh, R. P. Singh

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The freshwater microalgae Chlorella sp. is alluring considerable interest as a source for biofuel production due to its fast growth rate and high lipid content. Under nitrogen limited conditions, they can accumulate significant amounts of lipids. Thus, it is important to gain insight into the molecular mechanism of their lipid metabolism. In this study under nitrogen limited conditions, regular pattern of growth characteristics lipid accumulation and gene expression analysis of key regulatory genes of lipid biosynthetic pathway were carried out in microalgae Chlorella sp 3. Our results indicated that under nitrogen limited conditions there is a significant increase in the lipid content and lipid productivity, achieving 44.21±2.64 % and 39.34±0.66 mg/l/d at the end of the cultivation, respectively. Time-course transcript patterns of lipid biosynthesis genes i.e. acetyl coA carboxylase (accD) and diacylglycerol acyltransferase (dgat) showed that during late log phase of microalgae Chlorella sp.3 both the genes were significantly up regulated as compared to early log phase. Moreover, the transcript level of the dgat gene is two-fold higher than the accD gene. The results suggested that both the genes responded sensitively to the nitrogen limited conditions during the late log stage, which proposed their close relevance to lipid biosynthesis. Further, this transcriptome data will be useful for engineering microalgae species by targeting these genes for genetic modification to improve microalgal biofuel quality and production.

Keywords: biofuel, gene, lipid, microalgae

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Authors: Y. Kalachyova, O. Lyutakov, V. Svorcik

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One of the most significant obstacles for the application of surface enhanced Raman spectroscopy (SERS) is the poor reproducibility of SERS active substrates: SERS intensity can be varied from one substrate to another and moreover along the one substrate surface. High enhancement of the near-field intensity is the key factor for ultrasensitive SERS realization. SERS substrate can be prepared through introduction of highly ordered metal array, where light focusing is achieved through excitation of surface plasmon-polaritons (SPPs). In this work, we report the preparation of silver nanostructures with plasmon absorption peaks tuned by the metal arrangement. Excimer laser modification of poly(methyl methacrylate) followed by silver evaporation is proposed as an effective way for the creation of reproducible and effective surface plasmon-polaritons (SPP)-based SERS substrate. Theoretical and experimental studies were performed to optimize structure parameter for effective SPP excitation. It was found that the narrow range of grating periodicity and metal thickness exist, where SPPs can be most efficiently excited. In spite of the fact, that SERS response was almost always achieved, the enhancement factor was found to vary more with the effectivity of SPP excitation. When the real structure parameters were set to optimal for SPP excitation, a SERS enhancement factor was achieved up to four times. Theoretical and experimental investigation of SPP excitation on the two-dimensional periodical silver array was performed with the aim to make SERS response as high as possible.

Keywords: grating, nanostructures, plasmon-polaritons, SERS

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Authors: Leila Safazadeh, Brad Berron

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Self-assembled monolayers have tremendous impact in interfacial science, due to the unique opportunity they offer to tailor surface properties. Low-density self-assembled monolayers are an emerging class of monolayers where the environment-interfacing portion of the adsorbate has a greater level of conformational freedom when compared to traditional monolayer chemistries. This greater range of motion and increased spacing between surface-bound molecules offers new opportunities in tailoring adsorption phenomena in sensing systems. In particular, we expect low-density surfaces to offer a unique opportunity to intercalate surface bound ligands into the secondary structure of protiens and other macromolecules. Additionally, as many conventional sensing surfaces are built upon gold surfaces (SPR or QCM), these surfaces must be compatible with gold substrates. Here, we present the first stable method of generating low-density self assembled monolayer surfaces on gold for the analysis of their interactions with protein targets. Our approach is based on the 2:1 addition of thiol-yne chemistry to develop new classes of y-shaped adsorbates on gold, where the environment-interfacing group is spaced laterally from neighboring chemical groups. This technique involves an initial deposition of a crystalline monolayer of 1,10 decanedithiol on the gold substrate, followed by grafting of a low-packed monolayer on through a photoinitiated thiol-yne reaction in presence of light. Orthogonality of the thiol-yne chemistry (commonly referred to as a click chemistry) allows for preparation of low-density monolayers with variety of functional groups. To date, carboxyl, amine, alcohol, and alkyl terminated monolayers have been prepared using this core technology. Results from surface characterization techniques such as FTIR, contact angle goniometry and electrochemical impedance spectroscopy confirm the proposed low chain-chain interactions of the environment interfacing groups. Reductive desorption measurements suggest a higher stability for the click-LDMs compared to traditional SAMs, along with the equivalent packing density at the substrate interface, which confirms the proposed stability of the monolayer-gold interface. In addition, contact angle measurements change in the presence of an applied potential, supporting our description of a surface structure which allows the alkyl chains to freely orient themselves in response to different environments. We are studying the differences in protein adsorption phenomena between well packed and our loosely packed surfaces, and we expect this data will be ready to present at the GRC meeting. This work aims to contribute biotechnology science in the following manner: Molecularly imprinted polymers are a promising recognition mode with several advantages over natural antibodies in the recognition of small molecules. However, because of their bulk polymer structure, they are poorly suited for the rapid diffusion desired for recognition of proteins and other macromolecules. Molecularly imprinted monolayers are an emerging class of materials where the surface is imprinted, and there is not a bulk material to impede mass transfer. Further, the short distance between the binding site and the signal transduction material improves many modes of detection. My dissertation project is to develop a new chemistry for protein-imprinted self-assembled monolayers on gold, for incorporation into SPR sensors. Our unique contribution is the spatial imprinting of not only physical cues (seen in current imprinted monolayer techniques), but to also incorporate complementary chemical cues. This is accomplished through a photo-click grafting of preassembled ligands around a protein template. This conference is important for my development as a graduate student to broaden my appreciation of the sensor development beyond surface chemistry.

Keywords: low-density self-assembled monolayers, thiol-yne click reaction, molecular imprinting

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Authors: Lal Hussain, Wajid Aziz, Sajjad Ahmed Nadeem, Saeed Arif Shah, Abdul Majid

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Brain electrical activity as reflected in Electroencephalography (EEG) have been analyzed and diagnosed using various techniques. Among them, complexity measure, nonlinearity, disorder, and unpredictability play vital role due to the nonlinear interconnection between functional and anatomical subsystem emerged in brain in healthy state and during various diseases. There are many social and economical issues of alcoholic abuse as memory weakness, decision making, impairments, and concentrations etc. Alcoholism not only defect the brains but also associated with emotional, behavior, and cognitive impairments damaging the white and gray brain matters. A recently developed signal analysis method i.e. Multiscale Permutation Entropy (MPE) is proposed to estimate the complexity of long-range temporal correlation time series EEG of Alcoholic and Control subjects acquired from University of California Machine Learning repository and results are compared with MSE. Using MPE, coarsed grained series is first generated and the PE is computed for each coarsed grained time series against the electrodes O1, O2, C3, C4, F2, F3, F4, F7, F8, Fp1, Fp2, P3, P4, T7, and T8. The results computed against each electrode using MPE gives higher significant values as compared to MSE as well as mean rank differences accordingly. Likewise, ROC and Area under the ROC also gives higher separation against each electrode using MPE in comparison to MSE.

Keywords: electroencephalogram (EEG), multiscale permutation entropy (MPE), multiscale sample entropy (MSE), permutation entropy (PE), mann whitney test (MMT), receiver operator curve (ROC), complexity measure

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Authors: Tomasz Borowski, Dawid Sołoducha, Rafał Rakoczy, Marian Kordas

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The application of magnetic field is essential for a wide range of technologies or processes (i.e., magnetic hyperthermia, bioprocessing). From the practical point of view, bioprocess control is often limited to the regulation of temperature at constant values favourable to microbial growth. The main aim of this study is to determine the effect of various types of electromagnetic fields (i.e., static or alternating) on the heat transfer in a self-designed magnetically assisted reactor. The experimental set-up is equipped with a measuring instrument which controlled the temperature of the liquid inside the container and supervised the real-time acquisition of all the experimental data coming from the sensors. Temperature signals are also sampled from generator of magnetic field. The obtained temperature profiles were mathematically described and analyzed. The parameters characterizing the response to a step input of a first-order dynamic system were obtained and discussed. For example, the higher values of the time constant means slow signal (in this case, temperature) increase. After the period equal to about five-time constants, the sample temperature nearly reached the asymptotic value. This dynamical analysis allowed us to understand the heating effect under the action of various types of electromagnetic fields. Moreover, the proposed mathematical description can be used to compare the influence of different types of magnetic fields on heat transfer operations.

Keywords: heat transfer, magnetically assisted reactor, dynamical analysis, transient function

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Authors: Andriy Didenko, Zanin Kavazovic

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Engineering students often have certain difficulties in mastering major theoretical concepts in mathematical courses such as differential equations. Student projects were proposed to motivate students’ learning and can be used as a tool to promote students’ interest in the material. Authors propose a student project that includes the use of Microsoft Excel. This instructional tool is often overlooked by both educators and students. An integral component of the experimental part of such a project is the exploration of an interactive spreadsheet. The aim is to assist engineering students in better understanding of Euler’s method. This method is employed to numerically solve first order differential equations. At first, students are invited to select classic equations from a list presented in a form of a drop-down menu. For each of these equations, students can select and modify certain key parameters and observe the influence of initial condition on the solution. This will give students an insight into the behavior of the method in different configurations as solutions to equations are given in numerical and graphical forms. Further, students could also create their own equations by providing functions of their own choice and a variety of initial conditions. Moreover, they can visualize and explore the impact of the length of the time step on the convergence of a sequence of numerical solutions to the exact solution of the equation. As a final stage of the project, students are encouraged to develop their own spreadsheets for other numerical methods and other types of equations. Such projects promote students’ interest in mathematical applications and further improve their mathematical and programming skills.

Keywords: student project, Euler's method, spreadsheet, engineering education

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Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

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Authors: Akram Abi, Mohammad Hossein Sarrafzadeh

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Because of their several advantages over chemical surfactants, biosurfactants have given rise to a growing interest in the past decades. Advantages such as lower toxicity, higher biodegradability, higher selectivity and applicable at extreme temperature and pH which enables them to be used in a variety of applications such as: enhanced oil recovery, environmental and pharmaceutical applications, etc. Bacillus subtilis produces a cyclic lipopeptide, called surfactin, which is one of the most powerful biosurfactants with ability to decrease surface tension of water from 72 mN/m to 27 mN/m. In addition to its biosurfactant character, surfactin exhibits interesting biological activities such as: inhibition of fibrin clot formation, lyses of erythrocytes and several bacterial spheroplasts, antiviral, anti-tumoral and antibacterial properties. Surfactin is an antibiotic substance and has been shown recently to possess anti-HIV activity. However, application of biosurfactants is limited by their high production cost. The cost can be reduced by optimizing biosurfactant production using cheap feed stock. Utilization of inexpensive substrates and unconventional carbon sources like urban or agro-industrial wastes is a promising strategy to decrease the production cost of biosurfactants. With suitable engineering optimization and microbiological modifications, these wastes can be used as substrates for large-scale production of biosurfactants. As an effort to fulfill this purpose, in this work we have tried to utilize olive oil as second carbon source and also yeast extract as second nitrogen source to investigate the effect on both biomass and biosurfactant production improvement in Bacillus subtilis cultures. Since the turbidity of the culture was affected by presence of the oil, optical density was compromised and no longer could be used as an index of growth and biomass concentration. Therefore, cell Dry Weight measurements with applying necessary tactics for removing oil drops to prevent interference with biomass weight were carried out to monitor biomass concentration during the growth of the bacterium. The surface tension and critical micelle dilutions (CMD-1, CMD-2) were considered as an indirect measurement of biosurfactant production. Distinctive and promising results were obtained in the cultures containing olive oil compared to cultures without it: more than two fold increase in biomass production (from 2 g/l to 5 g/l) and considerable reduction in surface tension, down to 40 mN/m at surprisingly early hours of culture time (only 5hr after inoculation). This early onset of biosurfactant production in this culture is specially interesting when compared to the conventional cultures at which this reduction in surface tension is not obtained until 30 hour of culture time. Reducing the production time is a very prominent result to be considered for large scale process development. Furthermore, these results can be used to develop strategies for utilization of agro-industrial wastes (such as olive oil mill residue, molasses, etc.) as cheap and easily accessible feed stocks to decrease the high costs of biosurfactant production.

Keywords: agro-industrial waste, bacillus subtilis, biosurfactant, fermentation, second carbon and nitrogen source, surfactin

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Authors: Lisha Tan, Yunbo Nie, Mohammad Rahnama

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This study investigates the feasibility of harnessing train-induced airflows in underground metro stations as a source of renewable energy. Field measurements were conducted at multiple SkyTrain stations to assess wind speed distributions caused by passing trains. The data revealed significant airflow velocities with multimodal characteristics driven by varying train operations. These airflow velocities represent substantial kinetic energy that can be converted into usable power. Calculations showed that wind power densities within the underground tunnels ranged from 0.97 W/m² to 3.46 W/m², based on average cubed wind speeds, indicating considerable energy content available for harvesting. A Bayesian method was utilized to model these wind speed distributions, effectively capturing the complex airflow patterns. Further analysis using RETScreen evaluated the cost-benefit and environmental impact of implementing energy harvesting systems. Preliminary results suggest that the proposed system could result in substantial energy savings, reduce CO₂ emissions, and provide a favorable payback period, highlighting the economic and environmental viability of integrating wind turbines into metro stations.

Keywords: train-induced airflows, renewable energy generation, wind power density, RETScreen

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Authors: K. Amanzoui, A. Erragh, M. Elharit, A. Afif, K. Elfakhr, S. Kalouch, A. Chlilek

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Orthopedic surgery is a provider of pre and postoperative bleeding; patients are exposed to several risks, and different measures are proposed to reduce bleeding during surgery, called the transfusion-sparing method, including tranexamic acid, which has shown its effectiveness in numerous studies. A prospective analytical study in 50 children was carried out in the orthopedic traumatology operating room of the EL HAROUCHI hospital of the CHU IBN ROCHD in Casablanca over a period of six months (April to October 2022). Two groups were randomized: one receiving tranexamic acid (Group A) and a non-receiving control group (Group B). The average age was 10.3 years, of which 58.8% were female. The first type of surgery was thoracolumbar scoliosis (52%). The average preoperative hemoglobin was 12.28 g/dl in group A, against 12.67 g/dl in the control group. There was no significant difference between the two groups (p=0.148). Mean intraoperative bleeding was 396.29 ml in group A versus 412 ml in the control group. No significant difference was observed for this parameter (p=0.632). The average hemoglobin level in the immediate postoperative period in our patients is 10.2 g/dl. In group A, it was 10.95 g/dl versus 10.93 g/dl in group B. At H24 postoperative, the mean hemoglobin value was 10.29 g/dl in group A against 9.5 g/dl in group B. For group A, the blood loss recorded during the first 24 hours was 209.43 ml, against 372 ml in group B, with a significant difference between the two groups (p=0.001). There is no statistically significant difference between the 2 groups in terms of the use of fillers, ephedrine or intraoperative transfusion. While for postoperative transfusion, we note the existence of a statistically significant difference between group A and group B. It is suggested that the use of tranexamic acid is an effective, simple, and low-cost way to limit postoperative blood loss and the need for transfusion.

Keywords: tranexamic acid, blood loss, orthopedic surgery, children

Procedia PDF Downloads 69

Authors: Rajani S. Pujar, Pandurangarao N. Kulkarni

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Increased temporal masking affects the speech perception in persons with sensorineural hearing impairment especially under adverse listening conditions. This paper presents a cascaded scheme, which employs a noise reduction algorithm as well as temporal splitting of the speech signal. Earlier investigations have shown that by splitting the speech temporally and presenting alternate segments to the two ears help in reducing the effect of temporal masking. In this technique, the speech signal is processed by two fading functions, complementary to each other, and presented to left and right ears for binaural dichotic presentation. In the present study, half cosine signal is used as a fading function with crossover gain of 6 dB for the perceptual balance of loudness. Temporal splitting is combined with noise reduction algorithm to improve speech perception in the background noise. Two noise reduction schemes, namely spectral subtraction and Wiener filter are used. Listening tests were conducted on six normal-hearing subjects, with sensorineural loss simulated by adding broadband noise to the speech signal at different signal-to-noise ratios (∞, 3, 0, and -3 dB). Objective evaluation using PESQ was also carried out. The MOS score for VCV syllable /asha/ for SNR values of ∞, 3, 0, and -3 dB were 5, 4.46, 4.4 and 4.05 respectively, while the corresponding MOS scores for unprocessed speech were 5, 1.2, 0.9 and 0.65, indicating significant improvement in the perceived speech quality for the proposed scheme compared to the unprocessed speech.

Keywords: MOS, PESQ, spectral subtraction, temporal splitting, wiener filter

Procedia PDF Downloads 327

Authors: K. P. Farsana

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Belief in supernatural causation of mental illnesses and resort to religious and faith healing as the method of intervention still continue in many parts of the world. The proposed study intended to find out the belief and causation on health and illness and utilization of religious and faith healing, its implications, and associated socio-cultural and religious factors among Mappila Muslims of Malabar, Kerala, a southern state of India.Thangals are the endogamous community in Kerala, of Yemeni heritage who claim direct descent from the Prophet Mohammed’s family. Because of their sacrosanct status, many Thangal works as religious healers in Malabar, Northern Kerala. Using the case of one Thangal healer as an illustration of the many religious healers in Kerala who engage in the healing practices, it is intended, in this paper to illustrate the religious and ritual healing practices among Mappila Muslims of Malabar. It was found that the majority of the Mappila Muslims believed in supernatural causation on illness, and majority of them consulted religious and faith healers for various health problems before seeking professional help, and a considerable proportion continued to believe in the healing efficiency of the religious and faith healing. A significant proportion of the population found religious and faith healing practices are supportive and more acceptable within the community. Religion and belief system play an important role in the heath seeking behavior of a person.

Keywords: religious and faith healing, mental illness, Mappila Muslims, Malabar

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Authors: Y. T. Gebreslassie, Abrha Tadesse, R. C. Saini, Rishi Pal

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Caffeine, known chemically as 3,7-dihydro-1,3,7-trimethyl-1H-purine-2,6-dione, is a naturally occurring alkaloid classified as an N-methyl derivative of xanthine. Given its widespread use in coffee and other caffeine-containing products, it is the most commonly consumed psychoactive substance in everyday human life. This research aimed to develop a cost-effective, sensitive, and easily manufacturable sensor for the detection of caffeine. Antraquinone-modified carbon paste electrode (AQMCPE) was fabricated, and the electrochemical behavior of caffeine on this electrode was investigated using cyclic voltammetry (CV) and square wave voltammetry (SWV) in a solution of 0.1M perchloric acid at pH 0.56. The modified electrode displayed enhanced electrocatalytic activity towards caffeine oxidation, exhibiting a two-fold increase in peak current and an 82 mV shift of the peak potential in the negative direction compared to an unmodified carbon paste electrode (UMCPE). Exploiting the electrocatalytic properties of the modified electrode, SWV was employed for the quantitative determination of caffeine. Under optimized experimental conditions, a linear relationship between peak current and concentration was observed within the range of 2.0 x 10⁻⁶ to 1.0× 10⁻⁴ M, with a correlation coefficient of 0.998 and a detection limit of 1.47× 10⁻⁷ M (signal-to-noise ratio = 3). Finally, the proposed method was successfully applied to the quantitative analysis of caffeine in pharmaceutical formulations, yielding recovery percentages ranging from 95.27% to 106.75%.

Keywords: antraquinone-modified carbon paste electrode, caffeine, detection, electrochemical sensor, quantitative analysis

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Authors: Michael Gerges, Ograbe Ahiakwo, Martin Jaeger, Ahmad Asaad

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Recent advances of Building Information Modeling (BIM) especially in the Middle East have increased remarkably. Dubai has been taking a lead on this by making it mandatory for BIM to be adopted for all projects that involve complex architecture designs. This is because BIM is a dynamic process that assists all stakeholders in monitoring the project status throughout different project phases with great transparency. It focuses on utilizing information technology to improve collaboration among project participants during the entire life cycle of the project from the initial design, to the supply chain, resource allocation, construction and all productivity requirements. In view of this trend, the paper examines the extent of applying BIM in the State of Kuwait, by exploring practitioners’ perspectives on BIM, especially their perspectives on main barriers and main advantages. To this end structured interviews were carried out based on questionnaires and with a range of different construction professionals. The results revealed that practitioners perceive improved communication and mitigated project risks by encouraged collaboration between project participants. However, it was also observed that the full implementation of BIM in the State of Kuwait requires concerted efforts to make clients demanding BIM, counteract resistance to change among construction professionals and offer more training for design team members. This paper forms part of an on-going research effort on BIM and its application in the State of Kuwait and it is on this basis that further research on the topic is proposed.

Keywords: building information modeling, BIM, construction industry, Kuwait

Procedia PDF Downloads 378

Authors: María José Carrero, Ana M. Borreguero, Juan F. Rodríguez, María M. Velencoso, Ángel Serrano, María Jesús Ramos

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Flame-retardants are incorporated in different materials in order to reduce the risk of fire, either by providing increased resistance to ignition, or by acting to slow down combustion and thereby delay the spread of flames. In this work, polyether polyols with fire retardant properties were synthesized due to their wide application in the polyurethanes formulation. The combustion of polyurethanes is primarily dependent on the thermal properties of the polymer, the presence of impurities and formulation residue in the polymer as well as the supply of oxygen. There are many types of flame retardants, most of them are phosphorous compounds of different nature and functionality. The addition of these compounds is the most common method for the incorporation of flame retardant properties. The employment of glycerol phosphate sodium salt as initiator for the polyol synthesis allows obtaining polyols with phosphate groups in their structure. However, some of the critical points of the use of glycerol phosphate salt are: the lower reactivity of the salt and the necessity of a solvent (dimethyl sulfoxide, DMSO). Thus, the main aim in the present work was to determine the amount of the solvent needed to get a good solubility of the initiator salt. Although the anionic polymerization mechanism of polyether formation is well known, it seems convenient to clarify the role that DMSO plays at the starting point of the polymerization process. Regarding the fact that the catalyst deprotonizes the hydroxyl groups of the initiator and as a result of this, two water molecules and glycerol phosphate alkoxide are formed. This alkoxide, together with DMSO, has to form a homogeneous mixture where the initiator (solid) and the propylene oxide (PO) are soluble enough to mutually interact. The addition rate of PO increased when the solvent/initiator ratios studied were increased, observing that it also made the initiation step shorter. Furthermore, the molecular weight of the polyol decreased when higher solvent/initiator ratios were used, what revealed that more amount of salt was activated, initiating more chains of lower length but allowing to react more phosphate molecules and to increase the percentage of phosphorous in the final polyol. However, the final phosphorous content was lower than the theoretical one because only a percentage of salt was activated. On the other hand, glycerol phosphate disodium salt was still partially insoluble in DMSO studied proportions, thus, the recovery and reuse of this part of the salt for the synthesis of new flame retardant polyols was evaluated. In the recovered salt case, the rate of addition of PO remained the same than in the commercial salt but a shorter induction period was observed, this is because the recovered salt presents a higher amount of deprotonated hydroxyl groups. Besides, according to molecular weight, polydispersity index, FT-IR spectrum and thermal stability, there were no differences between both synthesized polyols. Thus, it is possible to use the recovered glycerol phosphate disodium salt in the same way that the commercial one.

Keywords: DMSO, fire retardants, glycerol phosphate disodium salt, recovered initiator, solvent

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Authors: Ashraf Osman

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Effective deployable bridges that are characterized by an increased capacity to weight ratio are recently needed for post-disaster rapid mobility and military operations. In deployable bridging, replacing metals as the fabricating material with advanced composite laminates as lighter alternatives with higher strength is highly advantageous. This article presents a hierarchical optimization strategy of a composite bridge treadway considering maximum strength design and bridge weight minimization. Shape optimization of a generic deployable bridge beam cross-section is performed to achieve better stress distribution over the bridge treadway hull. The developed cross-section weight is minimized up to reserving the margins of safety of the deployable bridging code provisions. Hence, the strength of composite bridge plates is maximized through varying the plies orientation. Different loading cases are considered of a tracked vehicle patch load. The orthotropic plate properties of a composite sandwich core are used to simulate the bridge deck structural behavior. Whereas, the failure analysis is conducted using Tsai-Wu failure criterion. The naturally inspired particle swarm optimization technique is used in this study. The proposed technique efficiently reduced the weight to capacity ratio of the developed bridge beam.

Keywords: CFRP deployable bridges, disaster relief, military bridging, optimization of composites, particle swarm optimization

Procedia PDF Downloads 141

Authors: Ghulam Haider Haidaree, Nsenda Lukumwena

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Today the world of research enjoys abundant data, available in virtually any field, technology, science, and business, politics, etc. This is commonly referred to as big data. This offers a great deal of precision and accuracy, supportive of an in-depth look at any decision-making process. When and if well used, Big Data affords its users with the opportunity to produce substantially well supported and good results. This paper leans extensively on big data to investigate possible smart solutions to urban mobility and related issues, namely road traffic accidents, its casualties, and fatalities based on multiple factors, including age, gender, location occurrences of accidents, etc. Multiple technologies were used in combination to produce an Information Communication Technology (ICT) based solution with embedded technology. Those technologies include principally Geographic Information System (GIS), Orange Data Mining Software, Bayesian Statistics, to name a few. The study uses the Leeds accident 2016 to illustrate the thinking process and extracts thereof a model that can be tested, evaluated, and replicated. The authors optimistically believe that the proposed model will significantly and smartly help to flatten the curve of road traffic accidents in the fast-growing population densities, which increases considerably motor-based mobility.

Keywords: accident factors, geographic information system, information communication technology, mobility

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Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

Procedia PDF Downloads 504