Search results for: art and technology

Authors: S. Farzad, M. Ali Mandegari, J. F. Görgens

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The South African Sugar Industry, which has a significant impact on the national economy, is currently facing problems due to increasing energy price and low global sugar price. The available bagasse is already combusted in low-efficiency boilers of the sugar mills while bagasse is generally recognized as a promising feedstock for second generation bioethanol production. Establishment of biorefinery annexed to the existing sugar mills, as an alternative for the revitalization of sugar industry producing biofuel and electricity has been proposed and considered in this study. Since the scale is an important issue in the feasibility of the technology, this study has taken into account a typical sugar mill with 300 ton/hr sugar cane capacity. The biorefinery simulation is carried out using Aspen PlusTM V8.6, in which the sugar mill’s power and steam demand has been considered. Hence, sugar mills in South Africa can be categorized as highly efficient, efficient, and not efficient with steam consumption of 33, 40, and 60 tons of steam per ton of cane and electric power demand of 10 MW; three different scenarios are studied. The sugar cane bagasse and tops/trash are supplied to the biorefinery process and the wastes/residues (mostly lignin) from the process are burnt in the CHP plant in order to produce steam and electricity for the biorefinery and sugar mill as well. Considering the efficient sugar mill, the CHP plant has generated 5 MW surplus electric powers, but the obtained energy is not enough for self-sufficiency of the plant (Biorefinery and Sugar mill) due to lack of 34 MW heat. One of the advantages of second generation biorefinery is its low impact on the environment and carbon footprint, thus the plant should be self-sufficient in energy without using fossil fuels. For this reason, a portion of fresh bagasse should be sent to the CHP plant to meet the energy requirements. An optimization procedure was carried out to find out the appropriate portion to be burnt in the combustor. As a result, 20% of the bagasse is re-routed to the combustor which leads to 5 tons of LP Steam and 8.6 MW electric power surpluses.

Keywords: biorefinery, sugarcane bagasse, sugar mill, energy analysis, bioethanol

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Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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Authors: Lixin Tian, Wei Xue

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Many jobs in society go underground, such as mine mining, tunnel construction and subways, which are vital to the development of society. Once accidents occur in these places, the interruption of traditional wired communication is not conducive to the development of rescue work. In order to realize the positioning, early warning and command functions of underground personnel and improve rescue efficiency, it is necessary to develop and design an emergency ground communication system. It is easy to be subjected to narrowband interference when performing conventional underground communication. Spreading communication can be used for this problem. However, general spread spectrum methods such as direct spread communication are inefficient, so it is proposed to use parallel combined spread spectrum (PCSS) communication to improve efficiency. The PCSS communication not only has the anti-interference ability and the good concealment of the traditional spread spectrum system, but also has a relatively high frequency band utilization rate and a strong information transmission capability. So, this technology has been widely used in practice. This paper presents a PCSS communication model-multiple detection parallel combined spread spectrum (MDPCSS) communication system. In this paper, the principle of MDPCSS communication system is described, that is, the sequence at the transmitting end is processed in blocks and cyclically shifted to facilitate multiple detection at the receiving end. The block diagrams of the transmitter and receiver of the MDPCSS communication system are introduced. At the same time, the calculation formula of the system bit error rate (BER) is introduced, and the simulation and analysis of the BER of the system are completed. By comparing with the common parallel PCSS communication, we can draw a conclusion that it is indeed possible to reduce the BER and improve the system performance. Furthermore, the influence of different pseudo-code lengths selected on the system BER is simulated and analyzed, and the conclusion is that the larger the pseudo-code length is, the smaller the system error rate is.

Keywords: cyclic shift, multiple detection, parallel combined spread spectrum, PN code

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Authors: Omvati Verma, Shyamashrre Roy

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A field experiment was conducted with three basal nitrogen levels (90, 120 and 150 kg N/ha) and five foliar application of urea (absolute control, water spray, 3% urea spray at anthesis, 7 and 14 days after anthesis) at G.B. Pant University of Agriculture & Technology, Pantnagar, U.S. Nagar (Uttarakhand) during rabi season in a factorial randomized block design with three replications. Results revealed that nitrogen application of 150 kg/ha produced the highest seed yield, straw and biological yield and it was significantly superior to 90 kg N/ha and was at par with 120 kg N/ha. The number of tillers increased significantly with increase in nitrogen doses up to 150 kg N/ha. Spike length, number of grains per spike, grain weight per spike and thousand seed weight showed significantly higher values with 120 kg N/ha than 90 kg N/ha and were at par with that of 150 kg N/ha. Also, plant height showed similar trend. Leaf area index and chlorophyll content showed significant increase with an increase in nitrogen levels at different stages. In the case of foliar spray treatments, urea spray at anthesis showed highest value for yield and yield attributes. In case of spike length and thousand seed weight, it was similar with the urea spray at 7 and 14 days after anthesis, but for rest of the yield attributes, it was significantly higher than rest of the treatments. Among seed quality parameters protein and sedimentation value showed significant increase due to increase in nitrogen rates whereas, starch and hectolitre weight had a decreasing trend. Wet gluten content was not influenced by nitrogen levels. Foliar urea spray at anthesis resulted in highest value of protein and hectolitre weight whereas, urea spray at 7 days after anthesis showed highest value of sedimentation value and wet gluten content.

Keywords: foliar application, nitrogenous fertilizer, seed quality, yield

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Authors: Nihar Kanta Patra, Akhtar Hussain

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This comprehensive study, through the perspective of librarians, explores the library as a metaphor and its profound significance in representing knowledge and learning. It delves into how librarians perceive the library as a metaphor and the ways in which it symbolizes the acquisition, preservation, and dissemination of knowledge. The research investigates the most common metaphors used to describe libraries, as witnessed by librarians, and analyzes how these metaphors reflect the evolving role of libraries in society. Furthermore, the study examines how the library metaphor influences the perception of librarians regarding academic libraries as physical places and academic library websites as virtual spaces, exploring their potential for learning and exploration. It investigates the evolving nature of the library as a metaphor over time, as seen by librarians, considering the changing landscape of information and technology. The research explores the ways in which the library metaphor has expanded beyond its traditional representation, encompassing digital resources, online connectivity, and virtual realms, and provides insights into its potential evolution in the future. Drawing on the experiences of librarians in their interactions with library users, the study uncovers any specific cultural or generational differences in how people interpret or relate to the library as a metaphor. It sheds light on the diverse perspectives and interpretations of the metaphor based on cultural backgrounds, educational experiences, and technological familiarity. Lastly, the study investigates the evolving roles of libraries as observed by librarians and explores how these changing roles can influence the metaphors we use to represent them. It examines the dynamic nature of libraries as they adapt to societal needs, technological advancements, and new modes of information dissemination. By analyzing these various dimensions, this research provides a comprehensive understanding of the library as a metaphor through the lens of librarians, illuminating its significance, evolution, and its transformative impact on knowledge, learning, and the changing role of libraries in society.

Keywords: library, librarians, metaphor, perception

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Authors: Sujin Hong, Seokyoon Moon, Heejoong Kim, Yunseok Lee, Youngjune Park

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Gas hydrate is an inclusion compound in which a low-molecular-weight gas or organic molecule is trapped inside a three-dimensional lattice structure created by water-molecule via intermolecular hydrogen bonding. It is generally formed at low temperature and high pressure, and exists as crystal structures of cubic systems − structure I, structure II, and hexagonal system − structure H. Many efforts have been made to apply them to various energy and environmental fields such as gas transportation and storage, CO₂ capture and separation, and desalination of seawater. Particularly, studies on the behavior of gas hydrates by new organic materials for CO₂ storage and various applications are underway. In this study, thermodynamic and spectroscopic analyses of the gas hydrate system were performed focusing on cyclopentanol, an organic molecule that forms gas hydrate at relatively low pressure. The thermodynamic equilibria of CH₄ and CO₂ hydrate systems including cyclopentanol were measured and spectroscopic analyses of XRD and Raman were performed. The differences in thermodynamic systems and formation kinetics of CO₂ added cyclopentane, cyclopentanol and cyclopentanone hydrate systems were compared. From the thermodynamic point of view, cyclopentanol was found to be a hydrate promotor. Spectroscopic analyses showed that cyclopentanol formed a hydrate crystal structure of cubic structure II in the presence of CH₄ and CO₂. It was found that the differences in the functional groups among the organic guest molecules significantly affected the rate of hydrate formation and the total amounts of CO₂ stored in the hydrate systems. The total amount of CO₂ stored in the cyclopentanone hydrate was found to be twice that of the amount of CO₂ stored in the cyclopentane and the cyclopentanol hydrates. The findings are expected to open up new opportunity to develop the gas hydrate based wastewater desalination technology.

Keywords: gas hydrate, CO₂, separation, desalination, formation kinetics, thermodynamic equilibria

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Authors: Dennis Schmickle

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Introductory statement: Augmented reality (AR) can be used to breathe life into traditional graphic design media, such as posters, book covers, and album art. AR superimposes a unique image/video on a user’s view of the real world, which makes it more immersive and realistic than traditional 2D media. This study developed a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. The results of this study suggest that AR can be an effective tool for teaching graphic design. Abstract: Traditional graphic design media, such as posters, book covers, and album art, could be considered to be “old media.” However, augmented reality (AR) can breathe life into these formats by making them more interactive and engaging for students and audiences alike. AR is a technology that superimposes a computer-generated image on a user’s view of the real world. This allows users to interact with digital content in a way that is more immersive and interactive than traditional 2D media. AR is becoming increasingly popular, as more and more people have access to smartphones and other devices that can support AR experiences. This study is comprised of a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. In these projects, students learn to create traditional design objects, such as posters, book covers, and album art. However, they are also required to create an animated version of their design and to use AR software to create an AR experience with which viewers can interact. The results of this study suggest that AR can be an effective and exciting tool for teaching graphic design. The students who participated in the study were able to learn the fundamental principles of graphic design, and they also developed the skills they need to create effective AR content. This study has implications for the future of graphic design education. As AR becomes more popular, it is likely that it will become an increasingly important tool for teaching graphic design.

Keywords: graphic design, augmented reality, print media, new media, AR, old media

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Authors: Krasimira Georgieva, Yordan Denev

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Many of thermosetting resins have application only in filled state, reinforced with different mineral fillers. The co-filling of polymers with mineral filler and gases creates a possibility for production of polymer composites materials with low density. This processing leads to forming of new materials – gas-filled plastics (polymer foams). The properties of these materials are determined mainly by the shape and size of internal structural elements (pores). The interactions on the phase boundaries have influence on the materials properties too. In the present work, the gas-filled urea-formaldehyde resins were reinforced by waste phosphogypsum. The waste phosphogypsum (CaSO₄.2H₂O) is a solid by-product in wet phosphoric acid production processes. The values of the interactions polymer-filler were increased by using two modifying agents: polyvinyl acetate for polymer matrix and sodium metasilicate for filler. Technological methods for gas-filling and recipes of urea-formaldehyde based materials with apparent density 20-120 kg/m³ were developed. The heat conductivity of the samples is between 0.024 and 0.029 W/m^oK. Tensile analyses were carried out at 10 and 50% deformation and show values 0.01-0.14 MPa and 0.01-0.09 MPa, respectively. The apparent density of obtained materials is between 20 and 92 kg/m³. The changes in the tensile properties and density of these materials according to sodium metasilicate content were studied too. The mechanism of phosphogypsum adsorption modification was studied using methods of FT-IR spectroscopy. The structure of the gas-filled urea-formaldehyde resins was described by results of electron scanning microscopy at three different magnification ratios – x50, x150 and x 500. The aim of present work is to study the possibility of the usage of phosphogypsum as mineral filler for urea-formaldehyde resins and development of a technology for the production of gas-filled reinforced polymer composite materials. The structure and the properties of obtained composite materials are suitable for thermal and sound insulation applications.

Keywords: urea formaldehyde resins, gas-filled thermostes, phosphogypsum, mechanical properties

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Authors: Targba Aondowase

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Undocumented migration along Nigeria’s boarder with Cameroon, Chad and Niger is a key issue in tackling the human security challenges in the region as the security situation cannot be contained without proper boarder control. The paper adopts migration systems theory which asserts that migration alters the social, cultural, economic, and institutional conditions at both the sending and receiving ends to explain the influence of unregistered migrants on institutional changes as it affects the security situation in Northern Nigeria. It was found that undocumented migration is majorly influenced by poverty, illegal trade, wars and asylum. The study also discovers that Nigerian boarders are porous with over 250 footpaths that link directly to Cameroon, Chad and Niger, making the proliferation of small arms and light weapons a transnational organized crime in the region. These porous borders are unmanned by security operatives with limited government presence in the boarder communities. The study also found that undocumented immigrants are easily integrated into the northern communities due to common religious beliefs and race where they carry out normal and civic functions without obstruction. The paper concluded that the level of undocumented migration in Northern Nigeria is high due to unmanned and porous borders. The paper therefore recommended that the security agencies should be strengthened through adequate funding, innovative technology, sound policies and proficient processes that will help protect the country’s borders. The National Populations Commission and the National Identity Management Commission should be strengthened to have a good data base of the country’s citizens and there should be international cooperation between the neighbouring countries to tackle illegal migration and illegal trade along the borders. The findings and recommendations of this paper will serve as a guide towards curtailing the impact of undocumented migration on human security in Northern Nigeria.

Keywords: human security, impact, migration, undocumented

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Authors: Temenuzhka Spasova, Nadya Yanakieva

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Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

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Authors: Yiseyon Sunday Hosu, Motebang Dominic Vincent Nakin, Elphina N. Cishe

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Universal access to clean and safe drinking water and basic sanitation is one of the targets of the 6th Sustainable Development Goals (SDGs). This paper explores the evidence-based indicators of Water Rights Acts (2013) among households in the rural communities in the Mthatha River catchment of OR Tambo District Municipality of South Africa. Daily access to minimum 25 litres/person and the factors influencing clean water access were investigated in the catchment. A total number of 420 households were surveyed in the upper, peri-urban, lower and coastal regions of Mthatha Rivier catchment. Descriptive and logistic regression analyses were conducted on the data collected from the households to elicit vital information on domestic water security among rural community dwellers. The results show that approximately 68 percent of total households surveyed have access to the required minimum 25 litre/person/day, with 66.3 percent in upper region, 76 per cent in the peri-urban, 1.1 percent in the lower and 2.3 percent in the coastal regions. Only 30 percent among the total surveyed households had access to piped water either in the house or public taps. The logistic regression showed that access to clean water was influenced by lack of water infrastructure, proximity to urban regions, daily flow of pipe-borne water, household size and distance to public taps. This paper recommends that viable integrated rural community-based water infrastructure provision strategies between NGOs and local authority and the promotion of point of use (POU) technologies to enhance better access to clean water.

Keywords: domestic water, household technology, water security, rural community

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Authors: Elif Tugce Aksun Tumerkan

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Although seafood is an important part of human diet and categorized highly traded food industry internationally, it is remain overlooked generally in the global food security aspect. Food product authentication is the main interest in the aim of both avoids commercial fraud and to consider the risks that might be harmful to human health safety. In recent years, with increasing consumer demand for regarding food content and it's transparency, there are some instrumental analyses emerging for determining food fraud depend on some analytical methodologies such as proteomic and metabolomics. While, fish and seafood consumed as fresh previously, within advanced technology, processed or packaged seafood consumption have increased. After processing or packaging seafood, morphological identification is impossible when some of the external features have been removed. The main fish and seafood quality-related issues are the authentications of seafood contents such as mislabelling products which may be contaminated and replacement partly or completely, by lower quality or cheaper ones. For all mentioned reasons, truthful consistent and easily applicable analytical methods are needed for assurance the correct labelling and verifying of seafood products. DNA-barcoding methods become popular robust that used in taxonomic research for endangered or cryptic species in recent years; they are used for determining food traceability also. In this review, when comparing the other proteomic and metabolic analysis, DNA-based methods are allowing a chance to identification all type of food even as raw, spiced and processed products. This privilege caused by DNA is a comparatively stable molecule than protein and other molecules. Furthermore showing variations in sequence based on different species and founding in all organisms, make DNA-based analysis more preferable. This review was performed to clarify the main advantages of using DNA-barcoding for determining seafood fraud among other techniques.

Keywords: DNA-barcoding, genetic analysis, food fraud, mislabelling, packaged seafood

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Authors: Carla Palencia-Aguilar

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Calculations of Net Carbon Balance can be obtained by means of Net Biome Productivity (NBP), Net Ecosystem Productivity (NEP), and Net Primary Production (NPP). The latter is an important component of the biosphere carbon cycle and is easily obtained data from MODIS MOD17A3HGF; however, the results are only available yearly. To overcome data availability, bands 33 to 36 from MODIS MYD021KM (obtained on a daily basis) were analyzed and compared with NPP data from the years 2000 to 2021 in 7 sites where surface mining takes place in the Colombian territory. Coal, Gold, Iron, and Limestone were the minerals of interest. Scales and Units as well as thermal anomalies, were considered for net carbon balance per location. The NPP time series from the satellite images were filtered by using two Matlab filters: First order and Discrete Transfer. After filtering the NPP time series, comparing the graph results from the satellite’s image value, and running a linear regression, the results showed R2 from 0,72 to 0,85. To establish comparable units among NPP and bands 33 to 36, the Greenhouse Gas Equivalencies Calculator by EPA was used. The comparison was established in two ways: one by the sum of all the data per point per year and the other by the average of 46 weeks and finding the percentage that the value represented with respect to NPP. The former underestimated the total CO2 emissions. The results also showed that coal and gold mining in the last 22 years had less CO2 emissions than limestone, with an average per year of 143 kton CO2 eq for gold, 152 kton CO2 eq for coal, and 287 kton CO2 eq for iron. Limestone emissions varied from 206 to 441 kton CO2 eq. The maximum emission values from unfiltered data correspond to 165 kton CO2 eq. for gold, 188 kton CO2 eq. for coal, and 310 kton CO2 eq. for iron and limestone, varying from 231 to 490 kton CO2 eq. If the most pollutant limestone site improves its production technology, limestone could count with a maximum of 318 kton CO2 eq emissions per year, a value very similar respect to iron. The importance of gathering data is to establish benchmarks in order to attain 2050’s zero emissions goal.

Keywords: carbon dioxide, NPP, MODIS, MINING

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Authors: Anucha Wittayakorn-Puripunpinyoo

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The research objectives were 1) to study the situation and its trend of agricultural product export of Thailand 2) to study the impact of agricultural product export on income of Thai economy 3) the impact of agricultural product export on employment of Thai economy and 4) to find out the recommendations of agricultural product export policy of Thailand. In this research, secondary data were collected as yearly time series data from 1990 to 2016 accounted for 27 years. Data were collected from the Bank of Thailand database. Primary data were collected from the steakholders of agricultural product export policy of Thailand. Data analysis was applied descriptive statistics such as arithmetic mean, standard deviation. The forecasting of agricultural product was applied Mote Carlo Simulation technique as well as time trend analysis. In addition, the impact of agricultural product export on income and employment by applying econometric model while the estimated parameters were utilized the ordinary least square technique. The research results revealed that 1) agricultural product export value of Thailand from 1990 to 2016 was 338,959.5 Million Thai baht with its growth rate of 4.984 percent yearly, in addition, the forecasting of agricultural product export value of Thailand has increased but its growth rate has been declined 2) the impact of agricultural product export has positive impact on income in Thai economy, increasing in agricultural product export of Thailand by 1 percent would lead income increased by 0.0051 percent 3) the impact of agricultural product export has positive impact on employment in Thai economy, increasing in agricultural product export of Thailand by 1 percent would lead income increased by 0.079 percent and 4) in the future, agricultural product export policy would focused on finished or semi-finished agricultural product instead of raw material by applying technology and innovation in to make value added of agricultural product export. The public agricultural product export policy would support exporters in private sector in order to encourage them as agricultural exporters in Thailand.

Keywords: agricultural product export, income, employment, Thai economy

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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Authors: Foteini Zagklavara, Peter Jimack, Nikil Kapur, Ozz Querin, Harvey Thompson

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The invention and development of the Polymerase Chain Reaction (PCR) technology have revolutionised molecular biology and molecular diagnostics. There is an urgent need to optimise their performance of those devices while reducing the total construction and operation costs. The present study proposes a CFD-enabled optimisation methodology for continuous flow (CF) PCR devices with serpentine-channel structure, which enables the trade-offs between competing objectives of DNA amplification efficiency and pressure drop to be explored. This is achieved by using a surrogate-enabled optimisation approach accounting for the geometrical features of a CF μPCR device by performing a series of simulations at a relatively small number of Design of Experiments (DoE) points, with the use of COMSOL Multiphysics 5.4. The values of the objectives are extracted from the CFD solutions, and response surfaces created using the polyharmonic splines and neural networks. After creating the respective response surfaces, genetic algorithm, and a multi-level coordinate search optimisation function are used to locate the optimum design parameters. Both optimisation methods produced similar results for both the neural network and the polyharmonic spline response surfaces. The results indicate that there is the possibility of improving the DNA efficiency by ∼2% in one PCR cycle when doubling the width of the microchannel to 400 μm while maintaining the height at the value of the original design (50μm). Moreover, the increase in the width of the serpentine microchannel is combined with a decrease in its total length in order to obtain the same residence times in all the simulations, resulting in a smaller total substrate volume (32.94% decrease). A multi-objective optimisation is also performed with the use of a Pareto Front plot. Such knowledge will enable designers to maximise the amount of DNA amplified or to minimise the time taken throughout thermal cycling in such devices.

Keywords: PCR, optimisation, microfluidics, COMSOL

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Authors: Ahmad Shahin, Fadi Chakik, Walid Moudani

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Our study is about elaborating a potential solution for a search engine that involves semantic technology to retrieve information and display it significantly. Semantic search engines are not used widely over the web as the majorities are still in Beta stage or under construction. Many problems face the current applications in semantic search, the major problem is to analyze and calculate the meaning of query in order to retrieve relevant information. Another problem is the ontology based index and its updates. Ranking results according to concept meaning and its relation with query is another challenge. In this paper, we are offering a light meta-engine (QESM) which uses Google search, and therefore Google’s index, with some adaptations to its returned results by adding multi-query expansion. The mission was to find a reliable ranking algorithm that involves semantics and uses concepts and meanings to rank results. At the beginning, the engine finds synonyms of each query term entered by the user based on a lexical database. Then, query expansion is applied to generate different semantically analogous sentences. These are generated randomly by combining the found synonyms and the original query terms. Our model suggests the use of semantic similarity measures between two sentences. Practically, we used this method to calculate semantic similarity between each query and the description of each page’s content generated by Google. The generated sentences are sent to Google engine one by one, and ranked again all together with the adapted ranking method (QESM). Finally, our system will place Google pages with higher similarities on the top of the results. We have conducted experimentations with 6 different queries. We have observed that most ranked results with QESM were altered with Google’s original generated pages. With our experimented queries, QESM generates frequently better accuracy than Google. In some worst cases, it behaves like Google.

Keywords: semantic search engine, Google indexing, query expansion, similarity measures

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Authors: Gus Salazar, Jeremy Bekker, Lauren Linford, Jared Warren

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Positive psychology practices allow for its principles to be applied to all people, regardless of their current level of functioning. To increase the dissemination of these practices, interventions are being adapted for use with digital technology, such as mobile apps. However, the research regarding positive psychology mobile app interventions is still in its infancy. In an effort to facilitate progress in this important area, we 1) conducted a qualitative review to summarize the current state of the positive psychology mobile app literature and 2) developed research-supported recommendations for positive psychology app development to maximize behavior change. In our literature review, we found that while positive psychology apps varied widely in content and purpose, there was a near-complete lack of research supporting their effectiveness. Most apps provided no rationale for the behavioral change techniques (BCTs) they employed in their app, and most did not develop their app with specific theoretical frameworks or design models in mind. Given this problem, we recommended four steps for effective positive psychology app design. First, developers must establish their app in a research-supported theory of change. Second, researchers must select appropriate behavioral change techniques which are consistent with their app’s goals. Third, researchers must leverage effective design principles. These steps will help mobile applications use data-driven methods for encouraging behavior change in their users. Lastly, we discuss directions for future research. In particular, researchers must investigate the effectiveness of various BCTs in positive psychology interventions. Although there is some research on this point, we do not yet clearly understand the mechanisms within the apps that lead to behavior change. Additionally, app developers must also provide data on the effectiveness of their mobile apps. As developers follow these steps for effective app development and as researchers continue to investigate what makes these apps most effective, we will provide millions of people in need with access to research-based mental health resources.

Keywords: behavioral change techniques, mobile app, mobile intervention, positive psychology

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Authors: Sreto Boljevic

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In the absence of considerable investment in electricity generation, transmission and distribution network (DN) capacity, the demand for electrical energy will quickly strain the capacity of the existing electrical power network. With anticipated growth and proliferation of Electric vehicles (EVs) and Heat pump (HPs) identified the likelihood that the additional load from EV changing and the HPs operation will require capital investment in the DN. While an area-wide implementation of EVs and HPs will contribute to the decarbonization of the energy system, they represent new challenges for the existing low-voltage (LV) network. Distributed energy resources (DER), operating both as part of the DN and in the off-network mode, have been offered as a means to meet growing electricity demand while maintaining and ever-improving DN reliability, resiliency and power quality. DN planning has traditionally been done by forecasting future growth in demand and estimating peak load that the network should meet. However, new problems are arising. These problems are associated with a high degree of proliferation of EVs and HPs as load imposes on DN. In addition to that, the promotion of electricity generation from renewable energy sources (RES). High distributed generation (DG) penetration and a large increase in load proliferation at low-voltage DNs may have numerous impacts on DNs that create issues that include energy losses, voltage control, fault levels, reliability, resiliency and power quality. To mitigate negative impacts and at a same time enhance positive impacts regarding the new operational state of DN, CHP system integration can be seen as best action to postpone/reduce capital investment needed to facilitate promotion and maximize benefits of EVs, HPs and RES integration in low-voltage DN. The aim of this paper is to generate an algorithm by using an analytical approach. Algorithm implementation will provide a way for optimal placement of the CHP system in the DN in order to maximize the integration of RES and increase in proliferation of EVs and HPs.

Keywords: combined heat & power (CHP), distribution networks, EVs, HPs, RES

Procedia PDF Downloads 202

Authors: Hassan Alhoujeiri, Angele Matrat, Sandra Beaufort, Claire joaniss Cassan, Jerome Silvester

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Aquaponics is a sustainable food production technology, and its transition to industrial-scale systems has created several challenges that require further investigation in order to make it a robust process. One of the critical concerns is the potential accumulation of compounds from veterinary treatments, phytosanitary agents, fish feed, or simply from contaminated water sources. The accumulation of these substances could negatively impact fish health, microbial biofilters, and plant growth, thereby disrupting the system’s overall balance and functionality. The lack of legislation and knowledge regarding the presence of such compounds in aquaponic systems raises concerns about their potential impact on both system balance and food safety. In this study, we focused on the effects of oxytetracycline (OTC), an antibiotic commonly used in aquaculture, on both the microbial biofilter and plant growth. Although OTC is rarely applied in aquaponics today, the fish compartment may need to be isolated from the system during treatment, as it inhibits specific bacterial populations, which could affect the microbial biofilter's efficiency. However, questions remain about the aquaponic system's tolerance threshold, particularly in cases of treatment or residual OTC traces post-treatment. This study results indicated a decline in microbial biofilter activity to 20% compared to the control, potentially corresponding to treatments of 41 mg/L of OTC. Analysis of microbial populations in the biofilter, using flow cytometry and microscopy (confocal and scanning electron microscopy), revealed an increase in bacterial mortality without disrupting the microbial biofilm. Additionally, OTC exposure led to noticeable changes in plant morphology (e.g., color) and growth, though it did not fully inhibit development. However, no significant effects were observed on seed germination at the tested concentrations despite a measurable impact on subsequent plant growth.

Keywords: aquaponic, oxytetracycline, nitrifying biofilter, plant, micropollutants, sustainability

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Authors: Borhan Marzougui

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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.

Keywords: IoT, DDoS, attacks, botnet, security, agents

Procedia PDF Downloads 143

Authors: Yehya Rasool, Mohit Agrawal

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The site characterization and site response analysis are the crucial steps for reliable seismic microzonation of an area. So, the basic parameters involved in these fundamental steps are required to be chosen properly in order to efficiently characterize the vulnerable sites of the study region. In this study, efforts are made to delineate the variations in the physical parameter of the soil for the summer and monsoon seasons of the year (2021) by using Horizontal-to-Vertical Spectral Ratios (HVSRs) recorded at five sites of the Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India. The data recording at each site was done in such a way that less amount of anthropogenic noise was recorded at each site. The analysis has been done for five seismic parameters like predominant frequency, H/V ratio, the phase velocity of Rayleigh waves, shear wave velocity (Vs), compressional wave velocity (Vp), and Poisson’s ratio for both the seasons of the year. From the results, it is observed that these parameters majorly vary drastically for the upper layers of soil, which in turn may affect the amplification ratios and probability of exceedance obtained from seismic hazard studies. The HVSR peak comes out to be higher in monsoon, with a shift in predominant frequency as compared to the summer season of the year 2021. Also, the drastic reduction in shear wave velocity (up to ~10 m) of approximately 7%-15% is also perceived during the monsoon period with a slight decrease in compressional wave velocity. Generally, the increase in the Poisson ratios is found to have higher values during monsoon in comparison to the summer period. Our study may be very beneficial to various agricultural and geotechnical engineering projects.

Keywords: HVSR, shear wave velocity profile, Poisson ratio, microtremor data

Procedia PDF Downloads 90

Authors: Masomeh Jamshid Nejad

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Nowadays, statistical literacy is no longer a necessary skill but an essential skill with broad applications across diverse fields, especially in operational decision areas such as business management, finance, and economics. As such, learning and deep understanding of statistical concepts are essential in the context of business studies. One of the crucial topics in statistical theory and its application is the normal distribution, often called a bell-shaped curve. To interpret data and conduct hypothesis tests, comprehending the properties of normal distribution (the mean and standard deviation) is essential for business students. This requires undergraduate students in the field of economics and business management to visualize and work with data following a normal distribution. Since technology is interconnected with education these days, it is important to teach statistics topics in the context of Python, R-studio, and Microsoft Excel to undergraduate students. This research endeavours to shed light on the effect of Excel-based instruction on learners’ knowledge of statistics, specifically the central concept of normal distribution. As such, two groups of undergraduate students (from the Business Management program) were compared in this research study. One group underwent Excel-based instruction and another group relied only on traditional teaching methods. We analyzed experiential data and BBA participants’ responses to statistic-related questions focusing on the normal distribution, including its key attributes, such as the mean and standard deviation. The results of our study indicate that exposing students to Excel-based learning supports learners in comprehending statistical concepts more effectively compared with the other group of learners (teaching with the traditional method). In addition, students in the context of Excel-based instruction showed ability in picturing and interpreting data concentrated on normal distribution.

Keywords: statistics, excel-based instruction, data visualization, pedagogy

Procedia PDF Downloads 53

Authors: Weldeabrha Kiros Kidanemaryam, DepaTesfay Kelali Gidey, Yikaalo Welu Kidanemariam

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Dairy services are considered as sources of income, employment, nutrition and health for smallholder rural and urban farmers. The main objective of this study is to assess the interlinkage of dairy farms and small-scale dairy processing in Mekelle, Tigray. To achieve the stated objective, a descriptive research approach was employed where data was collected from 45 dairy farmers and 40 small-scale processors and analyzed by calculating the mean values and percentages. Findings show that the dairy business in the study area is characterized by a shortage of feed and water for the farm. The dairy farm is dominated by breeds of hybrid type, followed by the so called ‘begait’. Though the farms have access to medication and vaccination for the cattle, they fell short of hygiene practices, reliable shade for the cattle and separate space for the claves. The value chain at the milk production stage is characterized by a low production rate, selling raw milk without adding value and a very meager traditional processing practice. Furthermore, small-scale milk processors are characterized by collecting milk from farmers and producing cheese, butter, ghee and sour milk. They do not engage in modern milk processing like pasteurized milk, yogurt and table butter. Most small-scale milk processors are engaged in traditional production systems. Additionally, the milk consumption and marketing part of the chain is dominated by the informal market (channel), where market problems, lack of skill and technology, shortage of loans and weak policy support are being faced as the main challenges. Based on the findings, recommendations and future research areas are forwarded.

Keywords: value-chain, dairy, milk production, milk processing

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Authors: June-Jei Kuo, Yi-Chuan Hsieh

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Because of the rapid growth of information technology, more and more libraries introduce the new information retrieval systems to enhance the users’ experience, improve the retrieval efficiency, and increase the applicability of the library resources. Nevertheless, few of them are discussed the usability from the users’ aspect. The aims of this study are to understand that the scenario of the information retrieval system utilization, and to know why users are willing to continuously use the web-scale discovery system to improve the web-scale discovery system and promote their use of university libraries. Besides of questionnaires, observations and interviews, this study employs both Information System Success Model introduced by DeLone and McLean in 2003 and the flow theory to evaluate the system quality, information quality, service quality, use, user satisfaction, flow, and continuing to use web-scale discovery system of students from National Chung Hsing University. Then, the results are analyzed through descriptive statistics and structural equation modeling using AMOS. The results reveal that in web-scale discovery system, the user’s evaluation of system quality, information quality, and service quality is positively related to the use and satisfaction; however, the service quality only affects user satisfaction. User satisfaction and the flow show a significant impact on continuing to use. Moreover, user satisfaction has a significant impact on user flow. According to the results of this study, to maintain the stability of the information retrieval system, to improve the information content quality, and to enhance the relationship between subject librarians and students are recommended for the academic libraries. Meanwhile, to improve the system user interface, to minimize layer from system-level, to strengthen the data accuracy and relevance, to modify the sorting criteria of the data, and to support the auto-correct function are required for system provider. Finally, to establish better communication with librariana commended for all users.

Keywords: web-scale discovery system, discovery system, information system success model, flow theory, academic library

Procedia PDF Downloads 103

Authors: Tuji Jemal Ahmed

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This paper is to provides a comprehensive review of current research works on foodborne illness and food safety, including the risks associated with foodborne illnesses, the latest research on food safety, and the mitigation strategies used to prevent and control foodborne illnesses. Foodborne illness is a major public health concern that affects millions of people every year. As foodborne illnesses have grown more common and dangerous in recent years, it is vital that we research and build upon methods to ensure food remains safe throughout consumption. Additionally, this paper will discuss future directions for food safety research, including emerging technologies, changes in regulations and standards, and collaborative efforts to improve food safety. The first section of the paper provides an overview of the risks of foodborne illness, including a definition of foodborne illness, the causes of foodborne illness, the types of foodborne illnesses, and high-risk foods for foodborne illness, Health Consequences of Foodborne Illness. The second section of the paper focuses on current research on food safety, including the role of regulatory agencies in food safety, food safety standards and guidelines, emerging food safety concerns, and advances in food safety technology. The third section of the paper explores mitigation strategies for foodborne illness, including preventative measures, hazard analysis and critical control points (HACCP), good manufacturing practices (GMPs), and training and education. Finally, this paper examines future directions for food safety research, including hurdle technologies and their impact on food safety, changes in food safety regulations and standards, collaborative efforts to improve food safety, and research gaps and areas for further exploration. In general, this work provides a comprehensive review of current research and future directions in food safety and understanding the risks associated with foodborne illness. The implications of the assessment for food safety and public health are discussed, as well as recommended for research scholars.

Keywords: food safety, foodborne illness, technologies, mitigation

Procedia PDF Downloads 107

Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

Procedia PDF Downloads 128

Authors: Andrew C. Eloka Eboka, Freddie L. Inambao

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Comparative investigation and assessment of microalgal technology as a biodiesel production option was studied alongside other second generation feedstocks. This was carried out by comparing the fuel properties of species of Chlorella vulgaris, Duneliella spp, Synechococus spp and Senedesmus spp with the feedstock of Jatropha (ex-basirika variety), Hura crepitans, rubber and Natal mahogany seed oils. The micro-algae were cultivated in an open pond using a photobioreactor (New Brunsink set-up model BF-115 Bioflo/CelliGen made in the US) with operating parameters: 14L capacity, working volume of 7.5L media, including 10% inoculum, at optical density of 3.144 @540nm and light intensity of 200 lux, for 23 and 16 days respectively. Various produced/accumulated biomasses were harvested by draining, flocculation, centrifugation, drying and then subjected to lipid extraction processes. The oils extracted from the algae and feedstocks were characterised and used to produce biodiesel fuels, by the transesterification method, using modified optimization protocol. Fuel properties of the final biodiesel products were evaluated for chemo-physical and fuel properties. Results revealed Chlorella vulgaris as the best strain for biomass cultivation, having the highest lipid productivity (5.2mgL-1h-1), the highest rate of CO2 absorption (17.85mgL-1min-1) and the average carbon sequestration in the form of CO2 was 76.6%. The highest biomass productivity was 35.1mgL-1h-1 (Chlorella), while Senedesmus had the least output (3.75mgL-1h-1, 11.73mgL-1min-1). All species had good pH value adaptation, ranging from 6.5 to 8.5. The fuel properties of the micro-algal biodiesel in comparison with Jatropha, rubber, Hura and Natal mahogany were within ASTM specification and AGO used as the control. Fuel cultivation from microalgae is feasible and will revolutionise the biodiesel industry.

Keywords: biodiesel, fuel properties, microalgae, second generation, seed oils, feedstock, photo-bioreactor, open pond

Procedia PDF Downloads 363

Authors: Ozgu Hafizoglu

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An analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with physical, behavioral, principal relations that are essential to learning, discovery, and innovation. The Cognitive Model of Analogy (CMA) leads and creates patterns of pathways to transfer information within and between domains in science, just as happens in the brain. The connectome of the brain shows how the brain operates with mental leaps between domains and mental hops within domains and the way how analogical reasoning mechanism operates. This paper demonstrates the CMA as an evolutionary approach to science, technology, and life. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions in the new era, especially post-pandemic. In this paper, we will reveal how to draw an analogy to scientific research to discover new systems that reveal the fractal schema of analogical reasoning within and between the systems like within and between the brain regions. Distinct phases of the problem-solving processes are divided thusly: stimulus, encoding, mapping, inference, and response. Based on the brain research so far, the system is revealed to be relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain’s mechanism in macro context; brain and spinal cord, and micro context: glia and neurons, relative to matching conditions of analogical reasoning and relational information, encoding, mapping, inference and response processes, and verification of perceptual responses in four-term analogical reasoning. Finally, we will relate all these terminologies with these mental leaps, mental maps, mental hops, and mental loops to make the mental model of CMA clear.

Keywords: analogy, analogical reasoning, brain connectome, cognitive model, neurons and glia, mental leaps, mental hops, mental loops

Procedia PDF Downloads 165

Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

Procedia PDF Downloads 377