Search results for: extreme gradient boosting

Authors: Elena Listo Ubeda, Miguel Marchamalo Sacristan

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The demand for water doubles every twenty years, at a rate which is twice as fast as the world´s population growth. Despite it´s great importance, water is one of the most degraded natural resources in the world, mainly because of the reduction of natural vegetation coverage, population growth, contamination and changes in the soil use which reduces its capacity to collect water. This situation is especially serious in Central America, as reflected in the Human Development reports. The objective of this project is to assist in the improvement of water production and quality in Central America. In order to do these two watersheds in Costa Rica were selected as experiments: that of the Virilla-Durazno River, located in the extreme north east of the central valley which has an Atlantic influence; and that of the Jabillo River, which flows directly into the Pacific. The Virilla river watershed is located over andisols, and that of the Jabillo River is over alfisols, and both are of great importance for water supply to the Greater Metropolitan Area and the future tourist resorts respectively, as well as for the production of agriculture, livestock and hydroelectricity. The hydrological reaction in different soil-cover complexes, varying from the secondary forest to natural vegetation and degraded pasture, was analyzed according to the evaluation of the properties of the soil, infiltration, soil compaction, as well as the effects of the soil cover complex on erosion, calculated by the C factor of the Revised Universal Soil Loss Equation (RUSLE). A water balance was defined for each watershed, in which the volume of water that enters and leaves were estimated, as well as the evapotranspiration, runoff, and infiltration. Two future scenarios, representing the implementation of reforestation and deforestation plans, were proposed, and were analyzed for the effects of the soil cover complex on the water balance in each case. The results obtained show an increase of the ground water recharge in the humid forest areas, and an extension of the study of the dry areas is proposed since the ground water recharge here is diminishing. These results are of great significance for the planning, design of Payment Schemes for Environmental Services and the improvement of the existing water supply systems. In Central America spatial planning is a priority, as are the watersheds, in order to assess the water resource socially and economically, and securing its availability for the future.

Keywords: Costa Rica, infiltration, soil, water

Procedia PDF Downloads 365

Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Ahmed Abdulfatah Yusuf, Collins Oduor Ondiek

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The automation of farming activities can have a transformational impact on the agricultural sector, especially from the emerging new technologies such as the Internet of Things (IoT). The system uses water level sensors and soil moisture sensors that measure the content of water in the soil as the values generated from the sensors enable the system to use an appropriate quantity of water, which avoids over or under irrigation. Due to the increase in the world’s population, there is a need to increase food production. With this demand in place, it is difficult to increase crop yield using the traditional manual approaches that lead to the wastage of water, thus affecting crop production. Food insecurity has become a scourge greatly affecting the developing countries and agriculture is an essential part of human life and tends to be the mainstay of the economy in most developing nations. Thus, without the provision of adequate food supplies, the population of those living in poverty is likely to multiply. The project’s main objective is to design and develop an IoT (Internet of Things) microcontroller-based Smart Irrigation System. In addition, the specific research objectives are to find out the challenges with traditional irrigation approaches and to determine the benefits of IoT-based smart irrigation systems. Furthermore, the system includes Arduino, a website and a database that works simultaneously in collecting and storing the data. The system is designed to pave the way in attaining the Sustainable Development Goal (SDG 1), which aims to end extreme poverty in all forms by 2030. The research design aimed at this project is a descriptive research design. Data was gathered through online questionnaires that used both quantitative and qualitative in order to triangulate the data. Out of the 32 questionnaires sent, there were 32 responses leading to a 100% response rate. In terms of sampling, the target group of this project is urban farmers, which account for about 25% of the population of Nairobi. From the findings of the research carried out, it is evident that there is a need to move away from manual irrigation approaches due to the high wastage of water to the use of smart irrigation systems that propose a better way of conserving water while maintaining the quality and moisture of the soil. The research also found out that urban farmers are willing to adopt this system to better their farming practices. However, this system can be improved in the future by incorporating it with other features and deploying it to a larger geographical area.

Keywords: crop production, food security, smart irrigation system, sustainable development goal

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Authors: Visvaganthie Moodley

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Language use and aesthetic appreciation are integral to meaning-making in prose, as they are in poetry. However, in comparison to poetic analysis, a literary analysis of prose that focuses on linguistics and stylistics is somewhat scarce as it generally requires the study of lengthy texts. Nevertheless, the effect of linguistic and stylistic features in prose as conscious design by authors for creating specific effects and conveying preconceived messages is drawing increasing attention of linguists and literary experts. A close examination of language use in prose can, among a host of literary purposes, convey emotive and cognitive values and contribute to making interpretations about how fictional characters are represented to the imaginative reader. This paper provides a literary analysis of Yann Martel’s narrative of a 14-year-old Indian boy, Pi, who had survived the wreck of a Japanese cargo ship, by focusing on his 227-day journey of tribulations, along with a Bengal tiger, on a lifeboat. The study favours a pluralistic approach blending literary criticism, linguistic analysis and stylistic description. It adopts Leech and Short’s (2007) broad framework of linguistic and stylistic categories (lexical categories, grammatical categories, figures of speech etc. [sic] and context and cohesion) as well as a range of other relevant linguistic phenomena to show how the narrator, Pi, and the author influence the reader’s interpretations of Pi’s character. Such interpretations are made using the lens of Freud’s psychoanalytical theory (which focuses on the interplay of the instinctual id, the ego and the moralistic superego) and Blake’s philosophy of innocence and experience (the two contrary states of the human soul). The paper traces Pi’s transformation from animal-loving, God-fearing vegetarian to brutal animal slayer and cannibal in his journey of survival. By a close examination of the linguistic and stylistic features of the narrative, it argues that, despite evidence of butchery and cannibalism, Pi’s gruesome behaviour is motivated by extreme physiological and psychological duress and not intentional malice. Finally, the paper concludes that the voice of the narrator, Pi, and that of the author, Martel, act as powerful persuasive agents in influencing the reader to respond with a sincere flow of sympathy for Pi and judge him as having retained his innocence in his instinctual need for survival.

Keywords: foregrounding, innocence and experience, lexis, literary analysis, psychoanalytical lens, style

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Authors: Haseen Siddiqui, Sanjay M. Mahajani

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Various important reactions in chemical and metallurgical industries fall in the category of gas-solid reactions. These reactions can be categorized as catalytic and non-catalytic gas-solid reactions. In gas-solid reaction systems, heat and mass transfer limitations put an appreciable influence on the rate of the reaction. The consequences can be unavoidable for overlooking such effects while collecting the reaction rate data for the design of the reactor. Pyrolysis reaction comes in this category that involves the production of gases due to the interaction of heat and solid substance. Pyrolysis is also an important step in the gasification process and therefore, the gasification reactivity majorly influenced by the pyrolysis process that produces the char, as a feed for the gasification process. Therefore, in the present study, a non-isothermal transient 1-D model is developed for a single biomass pellet to investigate the effect of heat and mass transfer limitations on the rate of pyrolysis reaction. The obtained set of partial differential equations are firstly discretized using the concept of ‘method of lines’ to obtain a set of ordinary differential equation with respect to time. These equations are solved, then, using MATLAB ode solver ode15s. The model is capable of incorporating structural changes, porosity variation, variation in various thermal properties and various pellet shapes. The model is used to analyze the effectiveness factor for different values of Lewis number and heat of reaction (G factor). Lewis number includes the effect of thermal conductivity of the solid pellet. Higher the Lewis number, the higher will be the thermal conductivity of the solid. The effectiveness factor was found to be decreasing with decreasing Lewis number due to the fact that smaller Lewis numbers retard the rate of heat transfer inside the pellet owing to a lower rate of pyrolysis reaction. G factor includes the effect of the heat of reaction. Since the pyrolysis reaction is endothermic in nature, the G factor takes negative values. The more the negative value higher will be endothermic nature of the pyrolysis reaction. The effectiveness factor was found to be decreasing with more negative values of the G factor. This behavior can be attributed to the fact that more negative value of G factor would result in more energy consumption by the reaction owing to a larger temperature gradient inside the pellet. Further, the analytical expressions are also derived for gas and solid concentrations and effectiveness factor for two limiting cases of the general model developed. The two limiting cases of the model are categorized as the homogeneous model and unreacted shrinking core model.

Keywords: effectiveness factor, G-factor, homogeneous model, lewis number, non-catalytic, shrinking core model

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Authors: Oshma Chakoory, Sophie Comtet-Marre, Pierre Peyret

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Metagenomic classifiers are widely used for the taxonomic profiling of metagenomic data and estimation of taxa relative abundance. Small subunit rRNA genes are nowadays a gold standard for the phylogenetic resolution of complex microbial communities, although the power of this marker comes down to its use as full-length. We benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then built a pipeline called RiboTaxa to generate a highly sensitive and specific metataxonomic approach. Using metagenomics data, RiboTaxa gave the best results compared to other tools (Kraken2, Centrifuge (1), METAXA2 (2), PhyloFlash (3)) with precise taxonomic identification and relative abundance description, giving no false positive detection. Using real datasets from various environments (ocean, soil, human gut) and from different approaches (metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not seen by current bioinformatics analysis opening new biological perspectives in human and environmental health. In a study focused on corals’ health involving 20 metagenomic samples (4), an affiliation of prokaryotes was limited to the family level with Endozoicomonadaceae characterising healthy octocoral tissue. RiboTaxa highlighted 2 species of uncultured Endozoicomonas which were dominant in the healthy tissue. Both species belonged to a genus not yet described, opening new research perspectives on corals’ health. Applied to metagenomics data from a study on human gut and extreme longevity (5), RiboTaxa detected the presence of an uncultured archaeon in semi-supercentenarians (aged 105 to 109 years) highlighting an archaeal genus, not yet described, and 3 uncultured species belonging to the Enorma genus that could be species of interest participating in the longevity process. RiboTaxa is user-friendly, rapid, allowing microbiota structure description from any environment and the results can be easily interpreted. This software is freely available at https://github.com/oschakoory/RiboTaxa under the GNU Affero General Public License 3.0.

Keywords: metagenomics profiling, microbial diversity, SSU rRNA genes, full-length phylogenetic marker

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Corina E. Niculaescu, Ivan Sangiorgi, Adrian R. Bell

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The COVID-19 pandemic has been life-changing in many aspects of people’s daily and social lives, but has it also changed attitudes towards investments? This paper explores the effect of the COVID-19 pandemic on retail investors’ levels of investments in the U.S. during the first COVID-19 wave in summer 2020. This is an unprecedented health crisis, which could lead to changes in investment behavior, including irrational behavior in retail investors. As such, this study aims to inform policymakers of what happened to investment decisions during the COVID-19 pandemic so that they can protect retail investors during extreme events like a global health crisis. The study aims to answer two research questions. First, was the level of investments affected by the COVID-19 pandemic, and if so, why? Second, how were investments affected by retail investors’ personal experience with COVID-19? The research analysis is based on primary survey data collected on the Amazon Mechanical Turk platform from a representative sample of U.S. respondents. Responses were collected between the 15th of July and 28th of August 2020 from 1,148 U.S. retail investors who hold mutual fund investments and a savings account. The research explores whether being affected by COVID-19, change in the level of savings, and risk capacity can explain the change in the level of investments by using regression analysis. The dependent variable is changed in investments measured as decrease, no change, and increase. For this reason, the methodology used is ordered probit regression models. The results show that retail investors in the U.S. increased their investments during the first wave of COVID-19, which is unexpected as investors are usually more cautious in crisis times. Moreover, the study finds that those who were affected personally by COVID-19 (e.g., tested positive) were more likely to increase their investments, which is irrational behavior and contradicts expectations. An increase in the level of savings and risk capacity was also associated with increased investments. Overall, the findings show that having personal experience with a health crisis can have an impact on one’s investment decisions as well. Those findings are important for both retail investors and policymakers, especially now that online trading platforms have made trading easily accessible to everyone. There are risks and potential irrational behaviors associated with investment decisions during times of crisis, and it is important that retail investors are aware of them before making financial decisions.

Keywords: COVID-19, financial decision-making, health crisis retail investors, survey

Procedia PDF Downloads 174

Authors: A. G. Back

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In the context of global climate change, extreme weather events are increasingly intense and frequent, challenging the adaptability of urban space. In this sense, urban planning is a relevant instrument for addressing, in a systemic manner, various sectoral policies capable of linking the urban agenda to the reduction of social and environmental risks. The Master Plan of the Municipality of Sao Paulo, 2014, presents innovations capable of promoting the transition to sustainability in the urban space. Among such innovations, the following stand out: i) promotion of density in the axes of mass transport involving mixture of commercial, residential, services, and leisure uses (principles related to the compact city); ii) vulnerabilities reduction based on housing policies, including regular sources of funds for social housing and land reservation in urbanized areas; iii) reserve of green areas in the city to create parks and environmental regulations for new buildings focused on reducing the effects of heat island and improving urban drainage. However, long-term implementation involves distributive conflicts and may change in different political, economic, and social contexts over time. Thus, the central objective of this paper is to identify which factors limit or support the implementation of these policies. That is, to map the challenges and interests of converging and/or divergent urban actors in the sustainable urban development agenda and what resources they mobilize to support or limit these actions in the city of Sao Paulo. Recent proposals to amend the urban zoning law undermine the implementation of the Master Plan guidelines. In this context, three interest groups with different views of the city come into dispute: the real estate market, upper middle class neighborhood associations ('not in my backyard' movements), and social housing rights movements. This paper surveys the different interests and visions of these groups taking into account their convergences, or not, with the principles of sustainable urban development. This approach seeks to fill a gap in the international literature on the causes that underpin or hinder the continued implementation of policies aimed at the transition to urban sustainability in the medium and long term.

Keywords: adaptation, ecosystem-based adaptation, interest groups, urban planning, urban transition to sustainability

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Authors: Rajkumar Ghosh, Ananya Mukhopadhyay

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India has seen enormous urbanization in recent years, resulting in increased energy consumption and water demand in its metropolitan regions. Adoption of grid-connected solar rooftop systems and rainwater collection has gained significant popularity in urban areas to address these challenges while also boosting sustainability and environmental consciousness. Grid-connected solar rooftop systems offer a long-term solution to India's growing energy needs. Solar panels are erected on the rooftops of residential and commercial buildings to generate power by utilizing the abundant solar energy available across the country. Solar rooftop systems generate clean, renewable electricity, reducing reliance on fossil fuels and lowering greenhouse gas emissions. This is compatible with India's goal of reducing its carbon footprint. Urban residents and companies can save money on electricity by generating their own and possibly selling excess power back to the grid through net metering arrangements. India gives several financial incentives (subsidies 40% for system capacity 1 kW to 3 kW) to stimulate the building of solar rooftop systems, making them an economically viable option for city dwellers. India provides subsidies up to 70% to special states such as Uttarakhand, Sikkim, Himachal Pradesh, Jammu & Kashmir, and Lakshadweep. Incorporating solar rooftops into urban infrastructure contributes to sustainable urban expansion by alleviating pressure on traditional energy sources and improving air quality. Incorporating solar rooftops into urban infrastructure contributes to sustainable urban expansion by alleviating demand on existing energy sources and improving power supply reliability. Rainwater harvesting is another key component of India's sustainable urban development. It comprises collecting and storing rainwater for use in non-potable water applications such as irrigation, toilet flushing, and groundwater recharge. Rainwater gathering 2 helps to conserve water resources by lowering the demand for freshwater sources. This technology is crucial in water-stressed areas to ensure a sustainable water supply. Excessive rainwater runoff in metropolitan areas can lead to Urban flooding. Solar PV system with Rooftop Rainwater harvesting systems absorb and channel excess rainwater, which helps to reduce flooding and waterlogging in Smart cities. Rainwater harvesting systems are inexpensive and quick to set up, making them a tempting option for city dwellers and businesses looking to save money on water. Rainwater harvesting systems are now compulsory in several Indian states for specified types of buildings (bye law, Rooftop space ≥ 300 sq. m.), ensuring widespread adoption. Finally, grid-connected solar rooftop systems and rainwater collection are important to India's long-term urban development. They not only reduce the environmental impact of urbanization, but also empower individuals and businesses to control their energy and water requirements. The G20 summit will focus on green financing, fossil fuel phaseout, and renewable energy transition. The G20 Summit in New Delhi reaffirmed India's commitment to battle climate change by doubling renewable energy capacity. To address climate change and mitigate global warming, India intends to attain 280 GW of solar renewable energy by 2030 and Net Zero carbon emissions by 2070. With continued government support and increased awareness, these strategies will help India develop a more resilient and sustainable urban future.

Keywords: grid-connected solar PV system, rooftop rainwater harvesting, urban flood, groundwater, urban flooding, net zero carbon emission

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Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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Changes in behaviour and physiology are the most important responses of marine life to anthropogenic impacts such as climate change and over-fishing. Behavioural changes (such as a shift in distribution or changes in phenology) can ensure that a species remains in an environment suited for its optimal physiological performance. However, if marine life is unable to shift their distribution, they are reliant on physiological adaptation (either by broadening their metabolic curves to tolerate a range of stressors or by shifting their metabolic curves to maximize their performance at extreme stressors). However, since there are links between fish physiology and behaviour, changes to either of these traits may have reciprocal interactions. This paper reviews the current knowledge of the links between the behaviour and physiology of fishes, discusses these in the context of exploitation and climate change, and makes recommendations for future research needs. The review revealed that our understanding of the links between fish behaviour and physiology is rudimentary. However, both are hypothesized to be linked to stress responses along the hypothalamic pituitary axis. The link between physiological capacity and behaviour is particularly important as both determine the response of an individual to a changing climate and are under selection by fisheries. While it appears that all types of capture fisheries are likely to reduce the adaptive potential of fished populations to climate stressors, angling, which is primarily associated with recreational fishing, may induce fission of natural populations by removing individuals with bold behavioural traits and potentially the physiological traits required to facilitate behavioural change. Future research should focus on assessing how the links between physiological capacity and behaviour influence catchability, the response to climate change drivers, and post-release recovery. The plasticity of phenotypic traits should be examined under a range of stressors of differing intensity in several species and life history stages. Future studies should also assess plasticity (fission or fusion) in the phenotypic structuring of social hierarchy and how this influences habitat selection. Ultimately, to fully understand how physiology is influenced by the selective processes driven by fisheries, long-term monitoring of the physiological and behavioural structure of fished populations, their fitness, and catch rates are required.

Keywords: climate change, metabolic shifts, over-fishing, phenotypic plasticity, stress response

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

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In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

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Authors: Ruchi B. Semwal, Deepak K. Semwal, Thobile A. N. Nkosi, Alvaro M. Viljoen

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The use of Lawsonia inermis L. (Lythraeae), commonly known as henna, has many medicinal benefits and is used as a remedy for the treatment of diarrhoea, cancer, inflammation, headache, jaundice and skin diseases in folk medicine. Although widely used for hair dyeing and temporary tattooing, henna body art has popularized over the last 15 years and changed from being a traditional bridal and festival adornment to an exotic fashion accessory. The naphthoquinone, lawsone, is one of the main constituents of the plant and responsible for its dyeing property. Henna leaves typically contain 1.8–1.9% lawsone, which is used as a marker compound for the quality control of henna products. Adulteration of henna with various toxic chemicals such as p-phenylenediamine, p-methylaminophenol, p-aminobenzene and p-toluenodiamine to produce a variety of colours, is very common and has resulted in serious health problems, including allergic reactions. This study aims to assess the quality of henna products collected from different parts of the world by determining the lawsone content, as well as the concentrations of any adulterants present. Ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to determine the lawsone concentrations in 172 henna products. Separation of the chemical constituents was achieved on an Acquity UPLC BEH C18 column using gradient elution (0.1% formic acid and acetonitrile). The results from UPLC-MS revealed that of 172 henna products, 11 contained 1.0-1.8% lawsone, 110 contained 0.1-0.9% lawsone, whereas 51 samples did not contain detectable levels of lawsone. High performance thin layer chromatography was investigated as a cheaper, more rapid technique for the quality control of henna in relation to the lawsone content. The samples were applied using an automatic TLC Sampler 4 (CAMAG) to pre-coated silica plates, which were subsequently developed with acetic acid, acetone and toluene (0.5: 1.0: 8.5 v/v). A Reprostar 3 digital system allowed the images to be captured. The results obtained corresponded to those from UPLC-MS analysis. Vibrational spectroscopy analysis (MIR or NIR) of the powdered henna, followed by chemometric modelling of the data, indicates that this technique shows promise as an alternative quality control method. Principal component analysis (PCA) was used to investigate the data by observing clustering and identifying outliers. Partial least squares (PLS) multivariate calibration models were constructed for the quantification of lawsone. In conclusion, only a few of the samples analysed contain lawsone in high concentrations, indicating that they are of poor quality. Currently, the presence of adulterants that may have been added to enhance the dyeing properties of the products, is being investigated.

Keywords: Lawsonia inermis, paraphenylenediamine, temporary tattooing, lawsone

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

Procedia PDF Downloads 47

Authors: Roni Granot, Erica Polini

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Music is often described in terms of non-auditory adjectives such as a rising melody, a bright sound, or a zigzagged contour. Such cross modal associations have been studied with simple isolated musical parameters, but only rarely in rich musical contexts. The current study probes cross sensory associations with polarity based dimensions by means of pairings of 10 adjectives: blunt-sharp, relaxed-tense, heavy-light, low (in space)-high, low (pitch)-high, big-small, hard-soft, active-passive, bright-dark, sad-happy. 30 participants (randomly assigned to one of two groups) were asked to rate one of 27 short saxophone improvisations on a 1 to 6 scale where 1 and six correspond to the opposite pole of each dimension. The 27 improvisations included three exemplars for each of three dimensions (size, brightness, sharpness), played by three different players. Here we focus on the question of whether ratings of scales corresponding with the musical dimension were consistently rated as such (e.g. music improvised to represent a white circle rated as bright in contrast with music improvised to represent a dark circle rated as dark). Overall the average scores by dimension showed an upward trend in the equivalent verbal scale, with a low rating for small, bright and sharp musical improvisations and higher scores for large, dark and blunt improvisations. Friedman tests indicate a statistically significant difference for brightness (χ2 (2) = 19.704, p = .000) and sharpness dimensions (χ2 (2) = 15.750, p = .000), but not for size (χ2 (2) = 1.444, p = .486). Post hoc analysis with Wilcoxon signed-rank tests within the brightness dimension, show significant differences among all possible parings resulted in significant differences: the rankings of 'bright' and 'dark' (Z = -3.310, p = .001), of 'bright' and 'medium' (Z = -2.438, p = .015) and of 'dark' and 'medium' music (Z = -2.714, p = .007); but only differences between the extreme contrasts within the sharpness dimension : 'sharp' and 'blunt' music (Z = -3.147, p = .002) and between 'sharp' and 'medium' music rated on the sharpness scale (Z = - 3.054, p = .002), but not between 'medium' and 'blunt' music (Z = -.982, p = .326). In summary our study suggests a privileged link between music and the perceptual and semantic domain of brightness. In contrast, size seems to be very difficult to convey in music, whereas sharpness seems to be mapped onto the two extremes (sharp vs. blunt) rather than continuously. This is nicely reflected in the musical literature in titles and texts which stress the association between music and concepts of light or darkness rather than sharpness or size.

Keywords: audiovisual, brightness, cross-modal perception, cross-sensory correspondences, size, visual angularity

Procedia PDF Downloads 199

Authors: Asim Abbasi, Muhammad Sufyan, Iqra, Muhammad Ibrahim Shahid, Muhammad Ashfaq

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The foundation of human life on earth relies on many ecosystem services provided by insects of which pollination owes a vital role. The pollination service offered by insects has annual worth of approximately €153 billion. The majority of the flowering plants depends on entomophiles pollination for their reproduction and formation of seeds and fruits. The quantity and quality of insect pollination have multiple implications for stable ecosystem, diverse species level, food security and climate change resilience. The rapidly mounting human population, depletion of natural resources and the global climate change forced us to enter an era of pollination crisis. Climate change not only alters the phenology, population abundance and geographic ranges of different pollinators but also hinders their pollination activities. The successful pollination process relies heavily on the synchronization of biological events of pollinators with the phenological stages of the flowering plants. However, there are possibilities that impending climatic changes may result in asynchrony between plant-pollinators interactions and also mitigate the extent of pollination. The trophic mismatch mostly occurs when pollinators and plants inhabiting the same environment use different environmental cues to regulate their biological events, as these cues are not equally affected by climate change. Synchrony has also been disrupted when one of the interacting species has migratory nature and depend on cues for migration. Moreover, irregular rainfalls and up-surging temperature also disrupts the foraging behaviour of pollinators resulting in reduced flowers visits by insect. Climate change has a direct impact on the behavior and physiology of honey bees, the best known pollinators owing to their extreme floral fidelity. Rising temperature not only alleviates the quantity and quality of floral environment but also alters the bee’s colony harvesting and development ability. Furthermore, a possible earlier decline of flowers is expected in a growing season due to this rising temperature. This may also lead to disrupt the efficiency bumblebee queen that require a constant and adequate nectar and pollen supply throughout the entire growing season for healthy colony production. Considering the role of insect pollination in our ecosystem, their associated risks regarding climate change should be addressed properly for devising a well-focused research needed for their conservation.

Keywords: climate change, phenological, pollination, synchronization

Procedia PDF Downloads 202

Authors: Kang Lin Peng

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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.

Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature

Procedia PDF Downloads 100

Authors: Tingting Song

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Wetlands are significant ecosystems that provide a variety of ecosystem services for humans, such as, providing water and food resources, purifying water quality, regulating climate, protecting biodiversity, and providing cultural, recreational, and educational resources. Wetlands also provide benefits, such as reduction of flood, storm damage, and soil erosion. The flood protection ecosystem services of wetlands are often ignored. Due to climate change, the flood caused by extreme weather in recent years occur frequently. Flood has a great impact on people's production and life with more and more economic losses. This study area is in the Tone river basin in the Kanto area, Japan. It is the second-longest river with the largest basin area in Japan, and it is still suffering heavy economic losses from floods. Tone river basin is one of the rivers that provide water for Tokyo and has an important impact on economic activities in Japan. The purpose of this study was to investigate land-use changes of wetlands in the Tone River Basin, and whether there are spatial differences in the value of wetland functions in mitigating economic losses caused by floods. This study analyzed the land-use change of wetland in Tone River, based on the Landsat data from 1980 to 2020. Combined with flood economic loss, wetland area, GDP, population density, and other social-economic data, a geospatial weighted regression model was constructed to analyze the spatial difference of wetland ecosystem service value. Now, flood protection mainly relies on such a hard project of dam and reservoir, but excessive dependence on hard engineering will cause the government huge financial pressure and have a big impact on the ecological environment. However, natural wetlands can also play a role in flood management, at the same time they can also provide diverse ecosystem services. Moreover, the construction and maintenance cost of natural wetlands is lower than that of hard engineering. Although it is not easy to say which is more effective in terms of flood management. When the marginal value of a wetland is greater than the economic loss caused by flood per unit area, it may be considered to rely on the flood storage capacity of the wetland to reduce the impact of the flood. It can promote the sustainable development of wetlands ecosystem. On the other hand, spatial analysis of wetland values can provide a more effective strategy for flood management in the Tone river basin.

Keywords: wetland, geospatial weighted regression, ecosystem services, environment valuation

Procedia PDF Downloads 84

Authors: B. Gonzalez-Yebra, H. Barajas, P. Palomares, M. Hernandez, O. Torres, M. Ayala, A. L. González, G. Vazquez-Ortiz, M. L. Guzman

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Leukemia arises by molecular alterations of the normal hematopoietic stem cell (HSC) transforming it into a leukemic stem cell (LSC) with high cell proliferation, self-renewal, and cell differentiation. Chronic myeloid leukemia (CML) originates from an LSC-leading to elevated proliferation of myeloid cells and acute lymphoblastic leukemia (ALL) originates from an LSC development leading to elevated proliferation of lymphoid cells. In both cases, LSC can be identified by multicolor flow cytometry using several antibodies. However, to date, LSC levels in peripheral blood (PB) are not established well enough in ALL and CML patients. On the other hand, the detection of the minimal residue disease (MRD) in leukemia is mainly based on the identification of the mRNA bcr-abl gene in CML patients and some other genes in ALL patients. There is no a properly biomarker to detect MDR in both types of leukemia. The objective of this study was to determine mRNA bcr-abl and the percentage of LSC in peripheral blood of patients with CML and ALL and identify a possible association between the amount of LSC in PB and clinical data. We included in this study 19 patients with Leukemia. A PB sample was collected per patient and leukocytes were obtained by Ficoll gradient. The immunophenotype for LSC CD34+ was done by flow cytometry analysis with CD33, CD2, CD14, CD16, CD64, HLA-DR, CD13, CD15, CD19, CD10, CD20, CD34, CD38, CD71, CD90, CD117, CD123 monoclonal antibodies. In addition, to identify the presence of the mRNA bcr-abl by RT-PCR, the RNA was isolated using TRIZOL reagent. Molecular (presence of mRNA bcr-abl and LSC CD34+) and clinical results were analyzed with descriptive statistics and a multiple regression analysis was performed to determine statistically significant association. In total, 19 patients (8 patients with ALL and 11 patients with CML) were analyzed, 9 patients with de novo leukemia (ALL = 6 and CML = 3) and 10 under treatment (ALL = 5 and CML = 5). The overall frequency of mRNA bcr-abl was 31% (6/19), and it was negative in ALL patients and positive in 80% in CML patients. On the other hand, LSC was determined in 16/19 leukemia patients (%LSC= 0.02-17.3). The Novo patients had higher percentage of LSC (0.26 to 17.3%) than patients under treatment (0 to 5.93%). The amount of LSC was significantly associated with the amount of LSC were: absence of treatment, the absence of splenomegaly, and a lower number of leukocytes, negative association for the clinical variables age, sex, blasts, and mRNA bcr-abl. In conclusion, patients with de novo leukemia had a higher percentage of circulating LSC than patients under treatment, and it was associated with clinical parameters as lack of treatment, absence of splenomegaly and a lower number of leukocytes. The mRNA bcr-abl detection was only possible in the series of patients with CML, and molecular detection of LSC could be identified in the peripheral blood of all leukemia patients, we believe the identification of circulating LSC may be used as biomarker for the detection of the MRD in leukemia patients.

Keywords: stem cells, leukemia, biomarkers, flow cytometry

Procedia PDF Downloads 338

Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

Procedia PDF Downloads 152

Authors: Sonia Bedhiaf-Romdhani

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The sheep (Ovis aries) was domesticated, approximately 11,000 years ago (YBP), in the Fertile Crescent from Asian Mouflon (Ovis Orientalis). The Northern African (NA) sheep is 7,000 years old, represents a remarkable diversity of sheep populations reared under traditional and low input farming systems (LIFS) over millennia. The majority of small ruminants in developing countries are encountered in low input production systems and the resilience of local communities in rural areas is often linked to the wellbeing of small ruminants. Regardless of the rich biodiversity encountered in sheep ecotypes there are four main sheep breeds in the country with 61,6 and 35.4 percents of Barbarine (fat tail breed) and Queue Fine de l’Ouest (thin tail breed), respectively. Phoenicians introduced the Barbarine sheep from the steppes of Central Asia in the Carthaginian period, 3000 years ago. The Queue Fine de l’Ouest is a thin-tailed meat breed heavily concentrated in the Western and the central semi-arid regions. The Noire de Thibar breed, involving mutton-fine wool producing animals, has been on the verge of extinction, it’s a composite black coated sheep breed found in the northern sub-humid region because of its higher nutritional requirements and non-tolerance of the prevailing harsher condition. The D'Man breed, originated from Morocco, is mainly located in the southern oases of the extreme arid ecosystem. A genetic investigation of Tunisian sheep breeds using a genome-wide scan of approximately 50,000 SNPs was performed. Genetic analysis of relationship between breeds highlighted the genetic differentiation of Noire de Thibar breed from the other local breeds, reflecting the effect of past events of introgression of European gene pool. The Queue Fine de l’Ouest breed showed a genetic heterogeneity and was close to Barbarine. The D'Man breed shared a considerable gene flow with the thin-tailed Queue Fine de l'Ouest breed. Native small ruminants breeds, are capable to be efficiently productive if essential ingredients and coherent breeding schemes are implemented and followed. Assessing the status of genetic variability of native sheep breeds could provide important clues for research and policy makers to devise better strategies for the conservation and management of genetic resources.

Keywords: sheep, farming systems, diversity, SNPs.

Procedia PDF Downloads 131

Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

Procedia PDF Downloads 153

Authors: Surupa Shaw, Debjyoti Banerjee

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Enhancing heat transfer in compact volumes is a challenge when constrained by cost issues, especially those associated with requirements for minimizing pumping power consumption. This is particularly acute for electronic chip cooling applications. Technological advancements in microelectronics have led to development of chip architectures that involve increased power consumption. As a consequence packaging, technologies are saddled with needs for higher rates of power dissipation in smaller form factors. The increasing circuit density, higher heat flux values for dissipation and the significant decrease in the size of the electronic devices are posing thermal management challenges that need to be addressed with a better design of the cooling system. Maximizing surface area for heat exchanging surfaces (e.g., extended surfaces or “fins”) can enable dissipation of higher levels of heat flux. Fractal structures have been shown to maximize surface area in compact volumes. Self-replicating structures at multiple length scales are called “Fractals” (i.e., objects with fractional dimensions; unlike regular geometric objects, such as spheres or cubes whose volumes and surface area values scale as integer values of the length scale dimensions). Fractal structures are expected to provide an appropriate technology solution to meet these challenges for enhanced heat transfer in the microelectronic devices by maximizing surface area available for heat exchanging fluids within compact volumes. In this study, the effect of different fractal micro-channel architectures and flow structures on the enhancement of transport phenomena in heat exchangers is explored by parametric variation of fractal dimension. This study proposes a model that would enable cost-effective solutions for thermal-fluid transport for energy applications. The objective of this study is to ascertain the sensitivity of various parameters (such as heat flux and pressure gradient as well as pumping power) to variation in fractal dimension. The role of the fractal parameters will be instrumental in establishing the most effective design for the optimum cooling of microelectronic devices. This can help establish the requirement of minimal pumping power for enhancement of heat transfer during cooling. Results obtained in this study show that the proposed models for fractal architectures of microchannels significantly enhanced heat transfer due to augmentation of surface area in the branching networks of varying length-scales.

Keywords: fractals, microelectronics, constructal theory, heat transfer enhancement, pumping power enhancement

Procedia PDF Downloads 301

Authors: Cassandra Hansen, Paul Doherty, Chris Ferner, German Whitley, Holly Torpey

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Wildfire is a natural and inevitable occurrence, yet changing climatic conditions have increased the severity, frequency, and risk to human populations in the wildland/urban interface (WUI) of the Western United States. Rapid dissemination of accurate wildfire information is critical to both the Incident Management Team (IMT) and the affected community. With the advent of increasingly sophisticated information systems, GIS can now be used as a web platform for sharing geographic information in new and innovative ways, such as virtual story map applications. Crowdsourced information can be extraordinarily useful when coupled with authoritative information. Information abounds in the form of social media, emergency alerts, radio, and news outlets, yet many of these resources lack a spatial component when first distributed. In this study, we describe how twenty-eight volunteer GIS professionals across nine Geographic Area Coordination Centers (GACC) sourced, curated, and distributed Volunteered Geographic Information (VGI) from authoritative social media accounts focused on disseminating information about wildfires and public safety. The combination of fire progression maps with VGI incident information helps answer three critical questions about an incident, such as: where the first started. How and why the fire behaved in an extreme manner and how we can learn from the fire incident's story to respond and prepare for future fires in this area. By adding a spatial component to that shared information, this team has been able to visualize shared information about wildfire starts in an interactive map that answers three critical questions in a more intuitive way. Additionally, long-term social and technical impacts on communities are examined in relation to situational awareness of the disaster through map layers and agency links, the number of views in a particular region of a disaster, community involvement and sharing of this critical resource. Combined with a GIS platform and disaster VGI applications, this workflow and information become invaluable to communities within the WUI and bring spatial awareness for disaster preparedness, response, mitigation, and recovery. This study highlights progression maps as the ultimate storytelling mechanism through incident case studies and demonstrates the impact of VGI and sophisticated applied cartographic methodology make this an indispensable resource for authoritative information sharing.

Keywords: storytelling, wildfire progression maps, volunteered geographic information, spatial and temporal

Procedia PDF Downloads 154

Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

Procedia PDF Downloads 48

Authors: C. J. Tien, C. S. Chen, S. F. Huang, Z. X. Wang

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Algae in soil ecosystems can produce organic matters and oxygen by photosynthesis. Heterocyst-forming cyanobacteria can fix nitrogen to increase soil nitrogen contents. Secretion of mucilage by some algae increases the soil water content and soil aggregation. These actions will improve soil quality and fertility, and further increase abundance and diversity of soil microorganisms. In addition, some mixotrophic and heterotrophic algae are able to degrade petroleum hydrocarbons. Therefore, the objectives of this study were to analyze the effects of algal addition on the degradation of total petroleum hydrocarbons (TPH), diversity and activity of bacteria and algae in the diesel-contaminated soil under different nutrient contents and frequency of plowing and irrigation in order to assess the potential bioremediation technique using edaphic algae. The known amount of diesel was added into the farmland soil. This diesel-contaminated soil was subject to five settings, experiment-1 with algal addition by plowing and irrigation every two weeks, experiment-2 with algal addition by plowing and irrigation every four weeks, experiment-3 with algal and nutrient addition by plowing and irrigation every two weeks, experiment-4 with algal and nutrient addition by plowing and irrigation every four weeks, and the control without algal addition. Soil samples were taken every two weeks to analyze TPH concentrations, diversity of bacteria and algae, and catabolic genes encoding functional degrading enzymes. The results show that the TPH removal rates of five settings after the two-month experimental period were in the order: experiment-2 > expermient-4 > experiment-3 > experiment-1 > control. It indicated that algal addition enhanced the degradation of TPH in the diesel-contaminated soil, but not for nutrient addition. Plowing and irrigation every four weeks resulted in more TPH removal than that every two weeks. The banding patterns of denaturing gradient gel electrophoresis (DGGE) revealed an increase in diversity of bacteria and algae after algal addition. Three petroleum hydrocarbon-degrading algae (Anabaena sp., Oscillatoria sp. and Nostoc sp.) and two added algal strains (Leptolyngbya sp. and Synechococcus sp.) were sequenced from DGGE prominent bands. The four hydrocarbon-degrading bacteria Gordonia sp., Mycobacterium sp., Rodococcus sp. and Alcanivorax sp. were abundant in the treated soils. These results suggested that growth of indigenous bacteria and algae were improved after adding edaphic algae. Real-time polymerase chain reaction results showed that relative amounts of four catabolic genes encoding catechol 2, 3-dioxygenase, toluene monooxygenase, xylene monooxygenase and phenol monooxygenase were appeared and expressed in the treated soil. The addition of algae increased the expression of these genes at the end of experiments to biodegrade petroleum hydrocarbons. This study demonstrated that edaphic algae were suitable biomaterials for bioremediating diesel-contaminated soils with plowing and irrigation every four weeks.

Keywords: catabolic gene, diesel, diversity, edaphic algae

Procedia PDF Downloads 259

Authors: Pulcherie Matsodoum Nguemte, Adrien Wanko Ngnien, Guy Valerie Djumyom Wafo, Ives Magloire Kengne Noumsi, Pierre Francois Djocgoue

Abstract:

The identification of plant species with the capacity to grow on hydrocarbon-polluted soils is an essential step for phytoremediation. In view of developing phytoremediation in Cameroon, floristic surveys have been conducted in 4 cities (Douala, Yaounde, Limbe, and Kribi). In each city, 13 hydrocarbon-polluted, as well as unpolluted sites (control), have been investigated using quadrat method. 106 species belonging to 76 genera and 30 families have been identified on hydrocarbon-polluted sites, unlike the control sites where floristic diversity was much higher (166 species contained in 125 genera and 50 families). Poaceae, Cyperaceae, Asteraceae and Amaranthaceae have higher taxonomic richness on polluted sites (16, 15,10 and 8 taxa, respectively). Shannon diversity index of the hydrocarbon-polluted sites (1.6 to 2.7 bits/ind.) were significantly lower than the control sites (2.7 to 3.2 bits/ind.). Based on a relative frequency > 10% and abundance > 7%, this study highlights more than ten plants predisposed to be effective in the cleaning-up attempts of soils contaminated by hydrocarbons. Based on the floristic indicators, 6 species (Eleusine indica (L.) Gaertn., Cynodon dactylon (L.) Pers., Alternanthera sessilis (L.) R. Br. ex DC †, Commelinpa benghalensis L., Cleome ciliata Schum. & Thonn. and Asystasia gangetica (L.) T. Anderson) were selected for a study to determine their capacity to remediate a soil contaminated with fuel oil (82.5 ml/ kg of soil). The experiments lasting 150 days takes into account three modalities - Tn: uncontaminated soils planted (6) To contaminated soils unplanted (3) and Tp: contaminated soil planted (18) – randomized arranged. 3 on 6 species (Eleusine indica, Cynodon dactylon, and Alternanthera sessilis) survived the climatic and soil conditions. E. indica presents a significantly higher growth rate for density and leaf area while C. dactylon had a significantly higher growth rate for stem size and leaf numbers. A. sessilis showed stunted growth and development throughout the experimental period. The species Eleusine indica (L.) Gaertn. and Cynodon dactylon (L.) Pers. can be qualified as polluo-tolerant plant species; polluo-tolerance being the ability of a species to survive and develop in the midst subject to extreme physical and chemical disturbances.

Keywords: Cameroon, cleaning-up, floristic surveys, phytoremediation

Procedia PDF Downloads 224

Authors: Moses Jenkins

Abstract:

Much of the focus when improving energy efficiency in buildings fall on the raising of standards within new build dwellings. However, as a significant proportion of the building stock across Europe is of historic or traditional construction, there is also a pressing need to improve the thermal performance of structures of this sort. On average, around twenty percent of buildings across Europe are built of historic masonry construction. In order to meet carbon reduction targets, these buildings will require to be retrofitted with insulation to improve their thermal performance. At the same time, there is also a need to balance this with maintaining the ability of historic masonry construction to allow moisture movement through building fabric to take place. This moisture transfer, often referred to as 'breathable construction', is critical to the success, or otherwise, of retrofit projects. The significance of this paper is to demonstrate that substantial thermal improvements can be made to historic buildings whilst avoiding damage to building fabric through surface or interstitial condensation. The paper will analyze the results of a wide range of retrofit measures installed to twenty buildings as part of Historic Environment Scotland's technical research program. This program has been active for fourteen years and has seen interventions across a wide range of building types, using over thirty different methods and materials to improve the thermal performance of historic buildings. The first part of the paper will present the range of interventions which have been made. This includes insulating mass masonry walls both internally and externally, warm and cold roof insulation and improvements to floors. The second part of the paper will present the results of monitoring work which has taken place to these buildings after being retrofitted. This will be in terms of both thermal improvement, expressed as a U-value as defined in BS EN ISO 7345:1987, and also, crucially, will present the results of moisture monitoring both on the surface of masonry walls the following retrofit and also within the masonry itself. The aim of this moisture monitoring is to establish if there are any problems with interstitial condensation. This monitoring utilizes Interstitial Hygrothermal Gradient Monitoring (IHGM) and similar methods to establish relative humidity on the surface of and within the masonry. The results of the testing are clear and significant for retrofit projects across Europe. Where a building is of historic construction the use of materials for wall, roof and floor insulation which are permeable to moisture vapor provides both significant thermal improvements (achieving a u-value as low as 0.2 Wm²K) whilst avoiding problems of both surface and intestinal condensation. As the evidence which will be presented in the paper comes from monitoring work in buildings rather than theoretical modeling, there are many important lessons which can be learned and which can inform retrofit projects to historic buildings throughout Europe.

Keywords: insulation, condensation, masonry, historic

Procedia PDF Downloads 151

Authors: Ala’a F. Jaber, Bara’ah A. Bsharat, Noor T. Ismael

Abstract:

Background: Sensory processing is a fundamental skill needed for the successful performance of daily living activities. These skills are impaired as parts of the neurodevelopmental process issues among children with autism spectrum disorder (ASD). This systematic review aimed to summarize the evidence on the differences in sensory processing and motor characteristic between children with ASD and children with TD. Method: This systematic review followed the guidelines of the preferred reporting items for systematic reviews and meta-analysis. The search terms included sensory, motor, condition, and child-related terms or phrases. The electronic search utilized Academic Search Ultimate, CINAHL Plus with Full Text, ERIC, MEDLINE, MEDLINE Complete, Psychology, and Behavioral Sciences Collection, and SocINDEX with full-text databases. The hand search included looking for potential studies in the references of related studies. The inclusion criteria included studies published in English between years 2009-2020 that included children aged 3-18 years with a confirmed ASD diagnosis, according to the DSM-V criteria, included a control group of typical children, included outcome measures related to the sensory processing and/or motor functions, and studies available in full-text. The review of included studies followed the Oxford Centre for Evidence-Based Medicine guidelines, and the Guidelines for Critical Review Form of Quantitative Studies, and the guidelines for conducting systematic reviews by the American Occupational Therapy Association. Results: Eighty-eight full-text studies related to the differences between children with ASD and children with TD in terms of sensory processing and motor characteristics were reviewed, of which eighteen articles were included in the quantitative synthesis. The results reveal that children with ASD had more extreme sensory processing patterns than children with TD, like hyper-responsiveness and hypo-responsiveness to sensory stimuli. Also, children with ASD had limited gross and fine motor abilities and lower strength, endurance, balance, eye-hand coordination, movement velocity, cadence, dexterity with a higher rate of gait abnormalities than children with TD. Conclusion: This systematic review provided preliminary evidence suggesting that motor functioning should be addressed in the evaluation and intervention for children with ASD, and sensory processing should be supported among children with TD. More future research should investigate whether how the performance and engagement in daily life activities are affected by sensory processing and motor skills.

Keywords: sensory processing, occupational therapy, children, motor skills

Procedia PDF Downloads 109