Search results for: genome scale metabolic model

Authors: Michael Tilahun Mulugeta

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Pedestrians are the most vulnerable road users as they are more exposed to the risk of collusion. Pedestrian safety at road intersections still remains the most vital and yet unsolved issue in Addis Ababa, Ethiopia. One of the critical points in pedestrian safety is the occurrence of conflict between turning vehicle and pedestrians at un-signalized intersection. However, a better understanding of the factors that affect the likelihood of the conflicts would help provide direction for countermeasures aimed at reducing the number of crashes. This paper has sorted to explore a model to describe the relation between traffic conflicts and influencing factors using Multiple Linear regression methodology. In this research the main focus is to study the interaction of turning (left & right) vehicle with pedestrian at unsignalized intersections. The specific objectives also to determine factors that affect the number of potential conflicts and develop a model of potential conflict.

Keywords: potential, regression analysis, pedestrian, conflicts

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Didiosky Benítez-Erice, Frederik Questier, Dalgys Pérez-Luján

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This paper aims to present two models around the production of students’ experiential knowledge in the teaching-learning process of higher education: the teacher-centered production model and the student-centered production model. From a range of knowledge management and experiential learning theories, the paper elaborates into the nature of students’ experiential knowledge and proposes further adjustments of existing second-generation knowledge management theories taking into account the particularities of higher education. Despite its theoretical nature the paper can be relevant for future studies that stress student-driven improvement and innovation at higher education institutions.

Keywords: experiential knowledge, higher education, knowledge management, teaching-learning process

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Authors: Vivian A. Panes, Raymond John S. Rebong, Miel Q. Diaz

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Moringa oleifera Lam. is known mainly for its high nutritional value and medicinal properties contributing to its popular reputation as a 'miracle plant' in the tropical climates where it usually grows. The main objective of this study is to discover the genes and gene products involved in abiotic stress-induced activity that may impact the M. oleifera Lam. mature seeds as well as their corresponding functions. In this study, RNA-sequencing and de novo transcriptome assembly were performed using two assemblers, Trinity and Oases, which produced 177,417 and 120,818 contigs respectively. These transcripts were then subjected to various bioinformatics tools such as Blast2GO, UniProt, KEGG, and COG for gene annotation and the analysis of relevant metabolic pathways. Furthermore, FPKM analysis was performed to identify gene expression levels. The sequences were filtered according to the 'response to stress' GO term since this study dealt with stress response. Clustered Orthologous Groups (COG) showed that the highest frequencies of stress response gene functions were those of cytoskeleton which make up approximately 14% and 23% of stress-related sequences under Trinity and Oases respectively, recombination, repair and replication at 11% and 14% respectively, carbohydrate transport and metabolism at 23% and 9% respectively and defense mechanisms 16% and 12% respectively. KEGG pathway analysis determined the most abundant stress-response genes in the phenylpropanoid biosynthesis at counts of 187 and 166 pathways for Oases and Trinity respectively, purine metabolism at 123 and 230 pathways, and biosynthesis of antibiotics at 105 and 102. Unique and cumulative GO term counts revealed that majority of the stress response genes belonged to the category of cellular response to stress at cumulative counts of 1,487 to 2,187 for Oases and Trinity respectively, defense response at 754 and 1,255, and response to heat at 213 and 208, response to water deprivation at 229 and 228, and oxidative stress at 508 and 488. Lastly, FPKM was used to determine the levels of expression of each stress response gene. The most upregulated gene encodes for thiamine thiazole synthase chloroplastic-like enzyme which plays a significant role in DNA damage tolerance. Data analysis implies that M. oleifera stress response genes are directed towards the effects of climate change more than other stresses indicating the potential of M. oleifera for cultivation in harsh environments because it is resistant to climate change, pathogens, and foreign invaders.

Keywords: stress response, genes, Moringa oleifera, transcriptomics

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Authors: Vicente Espinola, Luis Torres, Christhian Gonzalez

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Entrepreneurship is a topic of current interest in Mexico and the World, which has been fostered through public policies with great impact on its generation. The strategies used in Mexico have not been successful, being motivational strategies aimed at the masses with the intention that someone in the process generates a venture. The strategies used for its development have been "picking of winners" favoring those who have already overcome the initial stages of undertaking without effective support. This situation shows a disarticulation that appears even more in social entrepreneurship; due to this, it is relevant to research on those elements that could develop them and thus integrate a model of entrepreneurship and social innovation for Mexico. Social entrepreneurship should be generating social innovation, which is translated into business models in order to make the benefits reach the population. These models are proposed putting the social impact before the economic impact, without forgetting its sustainability in the medium and long term. In this work, we present a simple model of innovation and social entrepreneurship for Guanajuato, Mexico. This algorithm was based on how social innovation could be generated in a systemic way for Mexico through different institutions that promote innovation. In this case, the technological parks of the state of Guanajuato were studied because these are considered one of the areas of Mexico where its main objectives are to make technology transfer to companies but overlooking the social sector and entrepreneurs. An experimental design of n = 60 was carried out with potential entrepreneurs to identify their perception of the social approach that the enterprises should have, the skills they consider required to create a venture, as well as their interest in generating ventures that solve social problems. This experiment had a 2K design, the value of k = 3 and the computational simulation was performed in R statistical language. A simple model of interconnected variables is proposed, which allows us to identify where it is necessary to increase efforts for the generation of social enterprises. The 96.67% of potential entrepreneurs expressed interest in ventures that solve social problems. In the analysis of the variables interaction, it was identified that the isolated development of entrepreneurial skills would only replicate the generation of traditional ventures. The variable of social approach presented positive interactions, which may influence the generation of social entrepreneurship if this variable was strengthened and permeated in the processes of training and development of entrepreneurs. In the future, it will be necessary to analyze the institutional actors that are present in the social entrepreneurship ecosystem, in order to analyze the interaction necessary to strengt the innovation and social entrepreneurship ecosystem.

Keywords: social innovation, model, entrepreneurship, technological parks

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Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

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The present work examines the suitability of a seasonal forecasting model downscaled with a very high spatial resolution in order to assess the energy performance and requirements of buildings. The application of the developed model is applied on Greece for a period and with a forecast horizon of 5 months in the future. Greece, as a country in the middle of a financial crisis and facing serious societal challenges, is also very sensitive to climate changes. The commonly used method for the correlation of climate change with the buildings energy consumption is the concept of Degree Days (DD). This method can be applied to heating and cooling systems for a better management of environmental, economic and energy crisis, and can be used as medium (3-6 months) planning tools in order to predict the building needs and country’s requirements for residential energy use.

Keywords: downscaled seasonal models, degree days, energy performance

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Authors: Lourenco Camnahas, Eileen Willis, Greg Fisher, Jessie Gunson, Pascale Dettwiller, Charlene Thornton

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Stock-out of pharmaceuticals is a common issue at all level of health services in Timor-Leste, a small post-conflict country. This lead to the research questions: what are the current methods used to quantify pharmaceutical supplies; what factors contribute to the on-going pharmaceutical stock-out? The study examined factors that influence the pharmaceutical supply chain system. Methodology: Privett and Goncalvez dependency model has been adopted for the design of the qualitative interviews. The model examines pharmaceutical supply chain management at three management levels: management of individual pharmaceutical items, health facilities, and health systems. The interviews were conducted in order to collect information on inventory management, logistics management information system (LMIS) and the provision of pharmaceuticals. Andersen' behavioural model for healthcare utilization also informed the interview schedule, specifically factors linked to environment (healthcare system and external environment) and the population (enabling factors). Forty health professionals (bureaucrats, clinicians) and six senior officers from a United Nations Agency, a global multilateral agency and a local non-governmental organization were interviewed on their perceptions of factors (healthcare system/supply chain and wider environment) impacting on stock out. Additionally, policy documents for the entire healthcare system, along with population data were collected. Findings: An analysis using Pozzebon’s critical interpretation identified a range of difficulties within the system from poor coordination to failure to adhere to policy guidelines along with major difficulties with inventory management, quantification, forecasting, and budgetary constraints. Weak logistics management information system, lack of capacity in inventory management, monitoring and supervision are additional organizational factors that also contributed to the issue. There were various methods of quantification of pharmaceuticals applied in the government sector, and non-governmental organizations. Lack of reliable data is one of the major problems in the pharmaceutical provision. Global Fund has the best quantification methods fed by consumption data and malaria cases. There are other issues that worsen stock-out: political intervention, work ethic and basic infrastructure such as unreliable internet connectivity. Major issues impacting on pharmaceutical quantification have been identified. However, current data collection identified limitations within the Andersen model; specifically, a failure to take account of predictors in the healthcare system and the environment (culture/politics/social. The next step is to (a) compare models used by three non-governmental agencies with the government model; (b) to run the Andersen explanatory model for pharmaceutical expenditure for 2 to 5 drug items used by these three development partners in order to see how it correlates with the present model in terms of quantification and forecasting the needs; (c) to repeat objectives (a) and (b) using the government model; (d) to draw a conclusion about the strength.

Keywords: inventory management, pharmaceutical forecasting and quantification, pharmaceutical stock-out, pharmaceutical supply chain management

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Authors: Daria Lozovskaia

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This paper is focused on the news coverage of public opinion polls about Russian full-scale invasion of Ukraine in Russian state-controlled media. After the announcement of the start of the so-called “Special Military Operation” on February 24, 2022, the number of publications of the results of public opinion polls increased many times over, and the poll numbers began to be discussed on social media and in the Kremlin’s official informational agenda. Headlines like "72 Percent of Russian Citizens Support the Operation " or "Russians Believe in Victory in the Special Military Operation" have become prominent parts of Russian state propaganda news stories and newspapers. At the same time, public opinion in Russia, as a concept and model, differs from the generally accepted democratic concept and has its own specifics. As a result, public opinion polls and their results, especially after February 24, have a number of features in the form of the dominance of the discourse of political elites in the media, which leads to a decrease in public awareness, the prevalence of the effect of joining the majority and a high number of non-responses due to fear of reprisals. The aim of this study was to determine the role of public opinion polls in the system of Russian war propaganda in Ukraine. For this purpose, were selected publications of the Russian media, the agenda of which corresponds to the official information policy of the Russian authorities. First, using frame analysis for the categories "Explicit trust", "Implicit trust", "Implicit distrust" and "Explicit distrust", provided by Irina Dusakova, the broadcast level of trust in the data of public opinion polls was determined. The results of this phase of the study showed that the Russian media broadcast an absolute level of confidence in public opinion polls regarding support for the war in Ukraine. The second stage of the study was the content analysis of publications. The categories of this analysis were derived from Anna Morelli's 10 Principles of Military Propaganda and Haavard Koppang's Definition of Propaganda to determine the purposes of the use of public opinion polls by Russian propaganda. The results of the study not only confirmed the widespread hypothesis that public opinion polls in Russia are used as a tool of state propaganda, but also showed that their purpose is to demonstrate the consolidation of society in support of the war and President Vladimir Putin.

Keywords: propaganda, public opinion, public opinion polls, Russian studies

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Authors: Yun Chen, David Penton, Fazlul Karim, Santosh Aryal, Shahriar Wahid, Peter Taylor, Susan M. Cuddy

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Droughts have severely affected Afghanistan over the last four decades, leading to critical food shortages where two-thirds of the country’s population are in a food crisis. Long years of conflict have lowered the country’s ability to deal with hazards such as drought, which can rapidly escalate into disasters. Understanding the spatial and temporal distribution of droughts is needed to be able to respond effectively to disasters and plan for future occurrences. This study used Standardized Precipitation Evapotranspiration Index (SPEI) at monthly, seasonal, and annual temporal scales to map the spatiotemporal change dynamics of drought characteristics (distribution, frequency, duration, and severity) in Afghanistan. SPEI indices were mapped for river basins, disaggregated into 189 sub-catchments, using monthly precipitation and potential evapotranspiration derived from temperature station observations from 1980 to 2017. The results show these multi-dimensional drought characteristics vary along different years, change among sub-catchments, and differ across temporal scales. During the 38 years, the driest decade and period are the 2000s and 1999–2022, respectively. The 2000–01 water year is the driest, with the whole country experiencing ‘severe’ to ‘extreme’ drought, more than 53% (87 sub-catchments) suffering the worst drought in history, and about 58% (94 sub-catchments) having ‘very frequent’ drought (7 to 8 months) or ‘extremely frequent’ drought (9 to 10 months). The estimated seasonal duration and severity present significant variations across the study area and throughout the study period. The nation also suffered from recurring droughts with varying length and intensity in 2004, 2006, 2008, and, most recently, 2011. There is a trend towards increasing drought with longer duration and higher severity extending all over sub-catchments from southeast to north and central regions. These datasets and maps help to fill the knowledge gap on detailed sub-catchment scale meteorological drought characteristics in Afghanistan. The study findings improve our understanding of the influences of climate change on drought dynamics and can guide catchment planning for reliable adaptation to and mitigation against future droughts.

Keywords: SPEI, precipitation, evapotranspiration, climate extremes

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

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Authors: Syed Irfan Raza Naqvi, Zheng Jiangbin, Ahmad Moshin, Pervez Akhter

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Currently, the IoT system depends on a centralized client-servant architecture that causes various scalability and privacy vulnerabilities. Distributed ledger technology (DLT) introduces a set of opportunities for the IoT, which leads to practical ideas for existing components at all levels of existing architectures. Blockchain Technology (BCT) appears to be one approach to solving several IoT problems, like Bitcoin (BTC) and Ethereum, which offer multiple possibilities. Besides, IoTs are resource-constrained devices with insufficient capacity and computational overhead to process blockchain consensus mechanisms; the traditional BCT existing challenge for IoTs is poor scalability, energy efficiency, and transaction fees. IOTA is a distributed ledger based on Direct Acyclic Graph (DAG) that ensures M2M micro-transactions are free of charge. IOTA has the potential to address existing IoT-related difficulties such as infrastructure scalability, privacy and access control mechanisms. We proposed an architecture, SLDBI: A Scalable, lightweight DAG-based Blockchain Design for Intelligent IoT Systems, which adapts the DAG base Tangle and implements a lightweight message data model to address the IoT limitations. It enables the smooth integration of new IoT devices into a variety of apps. SLDBI enables comprehensive access control, energy efficiency, and scalability in IoT ecosystems by utilizing the Masked Authentication Message (MAM) protocol and the IOTA Smart Contract Protocol (ISCP). Furthermore, we suggest proof-of-work (PoW) computation on the full node in an energy-efficient way. Experiments have been carried out to show the capability of a tangle to achieve better scalability while maintaining energy efficiency. The findings show user access control management at granularity levels and ensure scale up to massive networks with thousands of IoT nodes, such as Smart Connected Buildings (SCBDs).

Keywords: blockchain, IOT, direct acyclic graphy, scalability, access control, architecture, smart contract, smart connected buildings

Procedia PDF Downloads 107

Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: Han-Taw Chen, Chung-Hou Lai, Tzu-Hsiang Lin, Ge-Jang He

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This study applies the inverse method and three-dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a closed rectangular enclosure for various values of fin height. The inverse method with the finite difference method and the experimental temperature data is applied to determine the heat transfer coefficient. The k-ε turbulence model is used to obtain the heat transfer and fluid flow characteristics within the fins. To validate the accuracy of the results obtained, the comparison of the average heat transfer coefficient is made. The calculated temperature at selected measurement locations on the plate-fin is also compared with experimental data.

Keywords: inverse method, FLUENT, k-ε model, heat transfer characteristics, plate-fin heat sink

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Authors: H. Daaou Nedjari, O. Guerri, M. Saighi

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A numerical study was conducted to optimize the positioning of wind turbines over complex terrains. Thus, a two-dimensional disk model was used to calculate the flow velocity deficit in wind farms for both flat and complex configurations. The wind turbine wake was assessed using the hybrid methods that combine CFD (Computational Fluid Dynamics) with the actuator disc model. The wind turbine rotor has been defined with a thrust force, coupled with the Navier-Stokes equations that were resolved by an open source computational code (Code_Saturne V3.0 developed by EDF) The simulations were conducted in atmospheric boundary layer condition considering a two-dimensional region located at the north of Algeria at 36.74°N longitude, 02.97°E latitude. The topography elevation values were collected according to a longitudinal direction of 1km downwind. The wind turbine sited over topography was simulated for different elevation variations. The main of this study is to determine the topography effect on the behavior of wind farm wake flow. For this, the wake model applied in complex terrain needs to selects the singularity effects of topography on the vertical wind flow without rotor disc first. This step allows to determine the existence of mixing scales and friction forces zone near the ground. So, according to the ground relief the wind flow waS disturbed by turbulence and a significant speed variation. Thus, the singularities of the velocity field were thoroughly collected and thrust coefficient Ct was calculated using the specific speed. In addition, to evaluate the land effect on the wake shape, the flow field was also simulated considering different rotor hub heights. Indeed, the distance between the ground and the hub height of turbine (Hhub) was tested in a flat terrain for different locations as Hhub=1.125D, Hhub = 1.5D and Hhub=2D (D is rotor diameter) considering a roughness value of z0=0.01m. This study has demonstrated that topographical farm induce a significant effect on wind turbines wakes, compared to that on flat terrain.

Keywords: CFD, wind turbine wake, k-epsilon model, turbulence, complex topography

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Authors: Alan Collins

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This study explains how The People’s Tribunal empowered survivors of child abuse. It examines how People’s tribunals can be effective mean of empowerment; the challenges of empowerment – expectation v. reality; the findings and how they reflect other inquiry findings; and the importance of listening and learning from survivors. UKCSAPT “The People’s Tribunal” was established by survivors of child sex abuse and members of civil society to investigate historic cases of institutional sex abuse. The independent inquiry, led by a panel of four judges, listened to evidence spanning four decades from survivors and experts. A common theme throughout these accounts showed that a series of institutional failures prevented abuse from being reported; and that there are clear links between children being rendered vulnerable by these failures and predatory abuse on an organised scale. It made a series of recommendations including the establishment of a permanent and open forum for victims to share experiences and give evidence, better links between mental health services and police investigations, and training for police and judiciary professionals on the effects of undisclosed sexual abuse. The main findings of the UKCSAPT report were:-There are clear links between children rendered vulnerable by institutional failures and predatory abuse on an organised scale, even if these links often remain obscure. -UK governmental institutions have failed to provide survivors with meaningful opportunities for either healing or justice. -The vital mental health needs of survivors are not being met and this undermines both their psychological recovery and access to justice. -Police and other authorities often lack the training to understand the complex reasons for the inability of survivors to immediately disclose a history of abuse. -Without far-reaching changes in institutional culture and practices, the sexual abuse of children will continue to be a significant scourge in the UK. The report also outlined a series of recommendations for improving reporting and mental health provision, and access to justice for victims were made, including: -A permanent, government-funded popular tribunal should be established to enable survivors to come forward and tell their stories. -Survivors giving evidence should be assigned an advocate to assist their access to justice. -Mental health services should be linked to police investigations to help victims disclose abuse. -Victims who fear reprisals should be provided with a channel though which to give evidence anonymously.

Keywords: empowerment, survivors, sexual, abuse

Procedia PDF Downloads 244

Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

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Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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Authors: Shri Krishna Mishra

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In an educational context, technology can prompt interactive plight only when it is used in conjunction with interactive plight methods. This study, therefore, examines the relationships among components that contribute to higher levels of interactive plight and execution, such as interactive Plight methods, technology, intrinsic motivation and deep learning. 526 students participated in this study. With structural equation modelling, the authors test the conceptual model and identify satisfactory model fit. The results indicate that interactive Plight methods, technology and intrinsic motivation have significant relationship with interactive Plight; deep learning mediates the relationships of the other variables with Execution.

Keywords: searching the relationship among components, contribute to interactive plight, educational execution, intrinsic motivation

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Authors: Onder Turkmen, Musa Seymen, Sali Fidan, Mustafa Paksoy

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There is a requirement for registered edible seed pumpkin suitable for eating in Turkey. A total of 81 genotypes collected from the researchers in 2005 originated from Eskisehir, Konya, Nevsehir, Tekirdag, Sakarya, Kayseri and Kirsehir provinces were utilized. The used genetic materials were brought to S5 generation by the research groups among 2006 and 2010 years. In this research, S5 stage reached in the genotype given some of the morphological features, and selection of promising genotypes generated scale were made. Results showed that the A-1 (420), A-7 (410), A-8 (420), A-32 (420), B-17 (410), B-24 (410), B-25 (420), B-33 (400), C-24 (420), C-25 (410), C-26 (410) and C-30 (420) genotypes are expected to be promising varieties.

Keywords: candidate cultivar, edible seed pumpkin, morphologic parameters, selection

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

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First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Neda Jalaliyoon, Nooh Abu Bakar, Hamed Taherdoost

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The present research recommended balanced scorecard (BSC) framework to appraise the performance of the universities. As the original model of balanced scorecard has four perspectives in order to implement BSC in present research the same model with “financial perspective”, “customer”,” internal process” and “learning and growth” is used as well. With applying fuzzy Delphi method (FDM) and questionnaire sixteen measures of performance were identified. Moreover, with using the analytic network process (ANP) the weights of the selected indicators were determined. Results indicated that the most important BSC’s aspect were Internal Process (0.3149), Customer (0.2769), Learning and Growth (0.2049), and Financial (0.2033) respectively. The proposed BSC framework can help universities to enhance their efficiency in competitive environment.

Keywords: balanced scorecard, higher education, fuzzy delphi method, analytic network process (ANP)

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Authors: Ariba Siddiqui, Amber Khan

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The need for bio-implantable devices in the field of medical sciences has been increasing day by day; however, the charging of these devices is a major issue. Batteries, a very common method of powering the implants, have a limited lifetime and bulky nature. Therefore, as a replacement of batteries, acoustic power transfer (APT) technology is being accepted as the most suitable technique to wirelessly power the medical implants in the present scenario. The basic model of APT consists of piezoelectric transducers that work on the principle of converse piezoelectric effect at the transmitting end and direct piezoelectric effect at the receiving end. This paper provides mechanistic insight into the parameters affecting the design and efficient working of acoustic power transfer systems. The optimum design considerations have been presented that will help to compress the size of the device and augment the intensity of the pressure wave. A COMSOL model of the PZT (Lead Zirconate Titanate) transducer was developed. The model was simulated and analyzed on a frequency spectrum. The simulation results displayed that the efficiency of these devices is strongly dependent on the frequency of operation, and a wrong choice of the operating frequency leads to the high absorption of acoustic field inside the tissue (medium), poor power strength, and heavy transducers, which in effect influence the overall configuration of the acoustic systems. Considering all the tradeoffs, the simulations were performed again by determining an optimum frequency (900 kHz) that resulted in the reduction of the transducer's thickness to 1.96 mm and augmented the power strength with an intensity of 432 W/m². Thus, the results obtained after the second simulation contribute to lesser attenuation, lightweight systems, high power intensity, and also comply with safety limits provided by the U.S Food and Drug Administration (FDA). It was also found that the chosen operating frequency enhances the directivity of the acoustic wave at the receiver side.

Keywords: acoustic power, bio-implantable, COMSOL, Lead Zirconate Titanate, piezoelectric, transducer

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

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Authors: Emilia K. H. Danielsson-Waters, Malaz Elsaddig, Kevin Jones

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Unfortunately, it is well known that neonatal deaths are a common and potentially preventable occurrence across the world. Neonatal resuscitation is a simple and inexpensive intervention that can effectively reduce this rate, and can be taught and implemented globally. This project is a follow-on from one in 2012, which found that neonatal resuscitation simulation was valuable for education, but would be better improved by being delivered by local staff. Methods: This study involved auditing the neonatal admission and death records within a rural Ugandan hospital, alongside implementing a Train-The-Trainer teaching scheme to teach Neonatal Resuscitation. One local doctor was trained for simulating neonatal resuscitation, whom subsequently taught an additional 14 staff members in one-afternoon session. Participants were asked to complete questionnaires to assess their knowledge and confidence pre- and post-simulation, and a survey to identify barriers and drivers to simulation. Results: The results found that the neonatal mortality rate in this hospital was 25% between July 2016- July 2017, with birth asphyxia, prematurity and sepsis being the most common causes. Barriers to simulation that were identified predominantly included a lack of time, facilities and opportunity, yet all members stated simulation was beneficial for improving skills and confidence. The simulation session received incredibly positive qualitative feedback, and also a 0.58-point increase in knowledge (p=0.197) and 0.73-point increase in confidence (0.079). Conclusion: This research shows that it is possible to create a teaching scheme in a rural hospital, however, many barriers are in place for its sustainability, and a larger sample size with a more sensitive scale is required to achieve statistical significance. This is undeniably important, because teaching neonatal resuscitation can have a direct impact on neonatal mortality. Subsequently, recommendations include that efforts should be put in place to create a sustainable training scheme, for example, by employing a resuscitation officer. Moreover, neonatal resuscitation teaching should be conducted more frequently in hospitals, and conducted in a wider geographical context, including within the community, in order to achieve its full effect.

Keywords: neonatal resuscitation, sustainable medical education, train-the-trainer, Uganda

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Authors: Hsueh-Cheng Yang

Abstract:

The generation and design of compound involute spur gearings can be used in gear pump. A compound rack cutter with asymmetric involute teeth is presented for determining the mathematical model of compound gear pumps. This paper covers the following topics: (a) generation and geometry of compound rack cutter is presented and used to generate a compound gear and a compound pinion. (b) Based on the developed compound gears, stress analysis was performed for the symmetric gears and the asymmetric gears. Comparing the results of the stress analysis for the asymmetric involute teeth is superior to the symmetric involute teeth. A numerical example that illustrates the developed compound rack cutter is represented.

Keywords: compound, involute teeth, gear pump, rack cutter

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Authors: T. Yu, L. Audibert, J. F. Chaix, D. Komatitsch, V. Garnier, J. M. Henault

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Linear Ultrasonic Techniques play a major role in Non-Destructive Evaluation (NDE) for civil engineering structures in concrete since they can meet operational requirements. Interpretation of ultrasonic measurements could be improved by a better understanding of ultrasonic wave propagation in a multiple scattering medium. This work aims to develop a 2D numerical model of ultrasonic wave propagation in a heterogeneous medium, like concrete, integrating the multiple scattering phenomena in SPECFEM software. The coherent field of multiple scattering is obtained by averaging numerical wave fields, and it is used to determine the effective phase velocity and attenuation corresponding to an equivalent homogeneous medium. First, this model is applied to one scattering element (a cylinder) in a homogenous medium in a linear-elastic system, and its validation is completed thanks to the comparison with analytical solution. Then, some cases of multiple scattering by a set of randomly located cylinders or polygons are simulated to perform parametric studies on the influence of frequency and scatterer size, concentration, and shape. Also, the effective properties are compared with the predictions of Waterman-Truell model to verify its validity. Finally, the mortar viscoelastic behavior is introduced in the simulation in order to considerer the dispersion and the attenuation due to porosity included in the cement paste. In the future, different steps will be developed: The comparisons with experimental results, the interpretation of NDE measurements, and the optimization of NDE parameters before an auscultation.

Keywords: attenuation, multiple-scattering medium, numerical modeling, phase velocity, ultrasonic measurements

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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Authors: Behzad Hajalilou, Nasim Hajalilou, Saeid Ansari

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The study area is located in East Azerbaijan province, north of Ahar city, and 1/100000 geological map of Varzgan. This region is located in the middle of Iran zone. Ali Javad Porphyry copper-gold ore deposit has been created in a magmatic complex containing intrusive masses, combining Granodiorite and quartz Monzonite that penetrates into the Eocene volcanic aggregate. The most important mineralization includes primary oxides minerals (magnetite), sulfide (pyrite, chalcopyrite, Molybdenite, Bornite, Chalcocite, Covollite), secondary oxide or hydroxide minerals (hematite, goethite, limonite), and carbonate (malachite and Azurite). The mineralization forms into the vein-veinlets and scattered system. The alterations observed in the region include intermediate Argillic, advanced Argillic, Phyllic, silica, Propylitic, chlorite and Potassic. The 3D model of mineralization of the Alijavad is provided by Data DATAMINE software and based on the study of 700 polished sections of 32 drilled boreholes in the region. This model is completely compatible with the model provided by Lowell and Gilbert for the mineralization of porphyry copper deposits of quartz Monzonite type. The estimated cumulative residual value of copper for Ali Javad deposit is 81.5 million tons with 0.75 percent of copper, and for gold is 8.37 million tons with 1.8 ppm.

Keywords: porphyry copper, mineralization, Ali Javad, modeling, reserve estimation

Procedia PDF Downloads 203

Authors: Alireza Monzavi Chaleshtori, Mahnaz Aliakbari Dehkordi, Maryam Aliakbari, Solmaz Seyed Mostafaii

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Objective: Considering the growing obesity among children and the role of mother's psychological factors as well as the need to prevent childhood obesity, this study aimed to investigate the mediating role of mother's self-efficacy in the relationship between mother's stress and depression and child obesity. Method: For this purpose, in a descriptive-correlation study, 222 mothers and children aged 1 to 5 years in Tehran, who had the opportunity to answer an online questionnaire, were selected by random sampling and to the depression scales of the Kroenke and Spitzer Patient Health Questionnaire, Cohen's stress and Self-efficacy of Berkeley mothers answered. Pearson correlation test and path analysis were used for data analysis. Findings: The findings showed that maternal depression had an indirect and significant effect on child obesity, and the effect of stress and depression on child obesity was indirect and non-significant. Therefore, the model has a good fit with the research data, and stress and depression indirectly predicted child obesity with the mediating role of self-efficacy. Conclusion: The hypothesized model tested based on mother's stress and depression with the mediating role of mother's self-efficacy was a good model in explaining the prediction of child obesity. Based on the findings of this research, a practical framework can be provided to explain the psychological factors of the mother in relation to child obesity and its treatment.

Keywords: stress, self-efficacy, child obesity, depression

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Authors: Vinayak Bassi, Rajpreet Singh

Abstract:

Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

Procedia PDF Downloads 146