Search results for: real volume

Authors: Alemayehu Ambaw, Matia Mukama, Umezuruike Linus Opara

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This study introduces a comprehensive method for designing ventilated corrugated fiberboard carton for fresh fruit packaging utilising virtual prototyping. The technique efficiently assesses and analyses the mechanical and thermal capabilities of fresh fruit packing boxes prior to making production investments. Comprehensive structural, aerodynamic, and thermodynamic data from designs were collected and evaluated in comparison to real-world packaging needs. Physical prototypes of potential designs were created and evaluated afterward. The virtual prototype is created with computer-aided graphics, computational structural dynamics, and computational fluid dynamics technologies. The virtual prototyping quickly generated data on carton compression strength, airflow resistance, produce cooling rate, spatiotemporal temperature, and product quality map in the cold chain within a few hours. Six distinct designs were analysed. All the various carton designs showed similar effectiveness in preserving the quality of the goods. The innovative packaging box design is more compact, resulting in a higher freight density of 1720 kg more fruit per reefer compared to the commercial counterpart. The precooling process was improved, resulting in a 17% increase in throughput and a 30% reduction in power usage.

Keywords: postharvest, container logistics, space/volume usage, computational method, packaging technology

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Authors: Ahmed Z. Mazen, Nejat Rahmanian, Iqbal Mujtaba, Ali Hassanpour

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In oil and gas well drilling, the drill bit is an important part of the Bottom Hole Assembly (BHA), which is installed and designed to drill and produce a hole by several mechanisms. The efficiency of the bit depends on many drilling parameters such as weight on bit, rotary speed, and mud properties. When the bit is pulled out of the hole, the evaluation of the bit damage must be recorded very carefully to guide engineers in order to select the bits for further planned wells. Having a worn bit for hole drilling may cause severe damage to bit leading to cutter or cone losses in the bottom of hole, where a fishing job will have to take place, and all of these will increase the operating cost. The main factor to reduce the cost of drilling operation is to maximize the rate of penetration by analyzing real-time data to predict the drill bit wear while drilling. There are numerous models in the literature for prediction of the rate of penetration based on drilling parameters, mostly based on empirical approaches. One of the most commonly used approaches is Bourgoyne and Young model, where the rate of penetration can be estimated by the drilling parameters as well as a wear index using an empirical correlation, provided all the constants and coefficients are accurately determined. This paper introduces a new methodology to estimate the eight coefficients for Bourgoyne and Young model using the gPROMS parameters estimation GPE (Version 4.2.0). Real data collected form similar formations (12 ¼’ sections) in two different fields in Libya are used to estimate the coefficients. The estimated coefficients are then used in the equations and applied to nearby wells in the same field to predict the bit wear.

Keywords: Bourgoyne and Young model, bit wear, gPROMS, rate of penetration

Procedia PDF Downloads 154

Authors: V. Mentl, V. Koula, P. Mazal, J. Volák

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Nowadays, the acoustic emission is a widely recognized method of material damage investigation, mainly in cases of cracks initiation and growth observation and evaluation. This is highly important in structures, e.g. pressure vessels, large steam turbine rotors etc., applied both in classic and nuclear power plants. Nevertheless, the acoustic emission signals must be correlated with the real crack progress to be able to evaluate the cracks and their growth by this non-destructive technique alone in real situations and to reach reliable results when the assessment of the structures' safety and reliability is performed and also when the remaining lifetime should be evaluated. The main aim of this study was to propose a methodology for evaluation of the early manifestations of the fatigue cracks and their growth and thus to quantify the material damage by acoustic emission parameters. Specimens made of several steels used in the power producing industry were subjected to fatigue loading in the low- and high-cycle regimes. This study presents results of the crack growth rate measurement obtained by the classic compliance change method and the acoustic emission signal analysis. The experiments were realized in cooperation between laboratories of Brno University of Technology and West Bohemia University in Pilsen within the solution of the project of the Czech Ministry of Industry and Commerce: "A diagnostic complex for the detection of pressure media and material defects in pressure components of nuclear and classic power plants" and the project “New Technologies for Mechanical Engineering”.

Keywords: fatigue, crack growth rate, acoustic emission, material damage

Procedia PDF Downloads 371

Authors: Sagar Jitendra Mahendrakar

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Exploratory testing is a dynamic and adaptable method of software quality assurance that is frequently praised for its ability to find hidden flaws and improve the overall quality of the product. Instead of using preset test cases, exploratory testing allows testers to explore the software application dynamically. This is in contrast to scripted testing methodologies, which primarily rely on tester intuition, creativity, and adaptability. There are several tools and techniques that can aid testers in the exploratory testing process which we will be discussing in this talk.Tests of this kind are able to find bugs of this kind that are harder to find during structured testing or that other testing methods may have overlooked.The purpose of this abstract is to examine the nature and importance of exploratory testing in modern software development methods. It explores the fundamental ideas of exploratory testing, highlighting the value of domain knowledge and tester experience in spotting possible problems that may escape the notice of traditional testing methodologies. Throughout the software development lifecycle, exploratory testing promotes quick feedback loops and continuous improvement by giving testers the ability to make decisions in real time based on their observations. This abstract also clarifies the unique features of exploratory testing, like its non-linearity and capacity to replicate user behavior in real-world settings. Testers can find intricate bugs, usability problems, and edge cases in software through impromptu exploration that might go undetected. Exploratory testing's flexible and iterative structure fits in well with agile and DevOps processes, allowing for a quicker time to market without sacrificing the quality of the final product.

Keywords: exploratory, testing, automation, quality

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Authors: Gaspar J. Machado, Stéphane Clain, Raphael Loubère

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The goal of the present work is to numerically study steady-state nonlinear hyperbolic equations in the context of the finite volume framework. We will consider the unidimensional Burgers' equation as the reference case for the scalar situation and the unidimensional Euler equations for the vectorial situation. We consider two approaches to solve the nonlinear equations: a time marching algorithm and a direct steady-state approach. We first develop the necessary and sufficient conditions to obtain the existence and unicity of the solution. We treat regular examples and solutions with a steady shock and to provide very-high-order finite volume approximations we implement a method based on the MOOD technology (Multi-dimensional Optimal Order Detection). The main ingredient consists in using an 'a posteriori' limiting strategy to eliminate non physical oscillations deriving from the Gibbs phenomenon while keeping a high accuracy for the smooth part.

Keywords: Euler equations, finite volume, MOOD, steady-state

Procedia PDF Downloads 277

Authors: Tanuj Joshi

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Smart transportation is fast emerging as a solution to modern cities’ approach mobility issues, delayed emergency response rate and high congestion on streets. Present day scenario with Google Maps, Waze, Yelp etc. demonstrates how information and communications technologies controls the intelligent transportation system. This intangible and invisible infrastructure is largely guided by the big data analytics. On the other side, the exponential increase in Indian urban population has intensified the demand for better services and infrastructure to satisfy the transportation needs of its citizens. No doubt, India’s huge internet usage is looked as an important resource to guide to achieve this. However, with a projected number of over 40 billion objects connected to the Internet by 2025, the need for systems to handle massive volume of data (big data) also arises. This research paper attempts to identify the ways of exploiting the big data variables which will aid commuters on Indian tracks. This study explores real life inputs by conducting survey and interviews to identify which gaps need to be targeted to better satisfy the customers. Several experts at Mumbai Metropolitan Region Development Authority (MMRDA), Mumbai Metro and Brihanmumbai Electric Supply and Transport (BEST) were interviewed regarding the Information Technology (IT) systems currently in use. The interviews give relevant insights and requirements into the workings of public transportation systems whereas the survey investigates the macro situation.

Keywords: smart transportation, mobility issue, Mumbai transportation, big data, data analysis

Procedia PDF Downloads 178

Authors: Lojaine Okacha

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In the past half-century, researchers started paying attention to enhancing the performance of urban spaces. Their idea of performance comprised urban climate performance, space synthesis, economic performance, and enhancing the quality of life in space. However, they all agreed that the key to achieving any of the previously mentioned development projects is good governance. Having good governance allows citizens to participate freely in the urbanization or development projects within cities. Consequently, using the city resources and assets as efficiently as possible, and ensures the fulfillment of the users’ needs and requests. This paper aims to propose an effective participation framework to help citizens have their voices heard and participate in the decisions that will affect their living situation. The framework allows governments to use their public resources to their best. However, this study focuses on public participation in third-world countries with unitary decentralized governance systems such as Egypt. It summarizes the challenges facing the participation practices, identifies the keys to a successful participation process, and draws on dominant effective participation practice lying on the relationship between the levels of participation, stakeholders participating, the urban development stages, the city-systems, and participation process. These components are integrated to create a real-world effective participation Framework. The results of the analysis were incredible and produced a functional and progressive approach for effective public participation to introduce to the governments. The model itself is combined with additional principles allowing the best practice to the process. The framework is finally compared with a real case of urban development.

Keywords: public participation, good governance, urban development, city systems

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Authors: Mustafa Saeed Omar

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The formula which contains the maximum increase of mean bond length, melting entropy and critical particle radius is used to calculate lattice volume in nanoscale size crystals of Ga₂Se₃. This compound belongs to the binary group of III₂VI₃. The critical radius is calculated from the values of the first surface atomic layer height which is equal to 0.336nm. The size-dependent mean bond length is calculated by using an equation-free from fitting parameters. The size-dependent lattice parameter then is accordingly used to calculate the size-dependent lattice volume. The lattice size in the nanoscale region increases to about 77.6 A³, which is up to four times of its bulk state value 19.97 A³. From the values of the nanosize scale dependence of lattice volume, the nanoscale size dependence of melting temperatures is calculated. The melting temperature decreases with the nanoparticles size reduction, it becomes zero when the radius reaches to its critical value. Bulk melting temperature for Ga₂Se₃, for example, has values of 1293 K. From the size-dependent melting temperature and mean bond length, the size-dependent lattice thermal expansion is calculated. Lattice thermal expansion decreases with the decrease of nanoparticles size and reaches to its minimum value as the radius drops down to about 5nm.

Keywords: Ga₂Se₃, lattice volume, lattice thermal expansion, melting point, nanoparticles

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Authors: Muhammad Isa Khan, Jalil Ur Rehman, Muhammad Afzal Khan Rao, James Chow

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Purpose: This study investigates the dose-volume variations in planning target volume (PTV) and organs-at-risk (OARs) using different collimator angles for smart arc prostate volumetric modulated arc therapy (VMAT). Awareness of the collimator angle for PTV and OARs sparing is essential for the planner because optimization contains numerous treatment constraints producing a complex, unstable and computationally challenging problem throughout its examination of an optimal plan in a rational time. Materials and Methods: Single arc VMAT plans at different collimator angles varied systematically (0°-90°) were performed on a Harold phantom and a new treatment plan is optimized for each collimator angle. We analyzed the conformity index (CI), homogeneity index (HI), gradient index (GI), monitor units (MUs), dose-volume histogram, mean and maximum doses to PTV. We also explored OARs (e.g. bladder, rectum and femoral heads), dose-volume criteria in the treatment plan (e.g. D30%, D50%, V30Gy and V38Gy of bladder and rectum; D5%,V14Gy and V22Gy of femoral heads), dose-volume histogram, mean and maximum doses for smart arc VMAT at different collimator angles. Results: There was no significance difference found in VMAT optimization at all studied collimator angles. However, if 0.5% accuracy is concerned then collimator angle = 45° provides higher CI and lower HI. Collimator angle = 15° also provides lower HI values like collimator angle 45°. It is seen that collimator angle = 75° is established as a good for rectum and right femur sparing. Collimator angle = 90° and collimator angle = 30° were found good for rectum and left femur sparing respectively. The PTV dose coverage statistics for each plan are comparatively independent of the collimator angles. Conclusion: It is concluded that this study will help the planner to have freedom to choose any collimator angle from (0°-90°) for PTV coverage and select a suitable collimator angle to spare OARs.

Keywords: VMAT, dose-volume histogram, collimator angle, organs-at-risk

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Authors: Ashok K. Satapathy, Prerana Nashine

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Radiative heat transfer in participating medium was anticipated using the finite volume method. The radiative transfer equations are formulated for absorbing and anisotropically scattering and emitting medium. The solution strategy is discussed and the conditions for computational stability are conferred. The equations have been solved for transient radiative medium and transient radiation incorporated with transient conduction. Results have been obtained for irradiation and corresponding heat fluxes for both the cases. The solutions can be used to conclude incident energy and surface heat flux. Transient solutions were obtained for a slab of heat conducting in slab by thermal radiation. The effect of heat conduction during the transient phase is to partially equalize the internal temperature distribution. The solution procedure provides accurate temperature distributions in these regions. A finite volume procedure with variable space and time increments is used to solve the transient energy equation. The medium in the enclosure absorbs, emits, and anisotropically scatters radiative energy. The incident radiations and the radiative heat fluxes are presented in graphical forms. The phase function anisotropy plays a significant role in the radiation heat transfer when the boundary condition is non-symmetric.

Keywords: participating media, finite volume method, radiation coupled with conduction, heat transfer

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Authors: Mohamad H. Atyeh, Ahmad Khaldi

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The main objective of this research is to measure the relationship between the Kuwait stock Exchange (KSE) index and its two marketing sectors after the new market classification. The findings of this research are important for Public economic policy makers as they need to know if the new system (new classification) is efficient and to what level, to monitor the markets and intervene with appropriate measures. The data used are the daily index of the whole Kuwaiti market and the daily closing price, number of deals and volume of shares traded of two marketing sectors (consumer goods and consumer services) for the period from the 13th of May 2012 till the 12th of December 2016. The results indicate a positive direct impact of the closing price, volume and deals indexes of the consumer goods and the consumer services companies on the overall KSE index, volume and deals of the Kuwaiti stock market (KSE).

Keywords: correlation, market capitalization, Kuwait Stock Exchange (KSE), marketing sectors, stock performance

Procedia PDF Downloads 326

Authors: Susan Lee

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Situated learning principles are adopted in the design of the module, professional communication, in its iteration of tasks and assignments to create a learning environment that simulates workplace reality. The success of situated learning is met when students are able to transfer and apply their skills beyond the classroom, in their personal life, and workplace. The learning process should help students recognize the relevance and opportunities for application. In the module’s learning component on negotiation, cases are created based on scenarios inspired by industry practices. The cases simulate scenarios that students on the course may encounter when they enter the workforce when they take on executive roles in the real estate sector. Engaging in the cases has enhanced students’ learning experience as they apply interpersonal communication skills in negotiation contexts of executives. Through the process of case analysis, role-playing, and peer feedback, students are placed in an experiential learning space to think and act in a deliberate manner not only as students but as professionals they will graduate to be. The immersive skills practices enable students to continuously apply a range of verbal and non-verbal communication skills purposefully as they stage their negotiations. The theme in students' feedback resonates with their awareness of the authentic and workplace experiences offered through visceral role-playing. Students also note relevant opportunities for the future transfer of the skills acquired. This indicates that students recognize the possibility of encountering similar negotiation episodes in the real world and realize they possess the negotiation tools and communication skills to deliberately apply them when these opportunities arise outside the classroom.

Keywords: deliberate practice, interpersonal communication skills, role-play, situated learning

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Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Caridad Maylin-Aguilar, Beatriz Duarte-Monedero

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Problem-based learning (PBL) is a useful tool for adult and practice oriented audiences, as University students. As a consequence of the huge disruption caused by the COVID pandemic in the hospitality industry, hotels of all categories closed down in Spain from March 2020. Since that moment, the luxury segment was blooming with optimistic prospects for new openings. Hence, Hospitality students were expecting a positive situation in terms of employment and career development. By the beginning of the 2020-21 academic year, these expectations were seriously harmed. By October 2020, only 9 of the 32 hotels in the luxury segment were opened with an occupation rate of 9%. Shortly after, the evidence of a second wave affecting especially Spain and the homelands of incoming visitors bitterly smashed all forecasts. In accordance with the situation, a team of four professors and practitioners, from four different subject areas, developed a real case, inspired in one of these hotels, the 5-stars Emperatriz by Barceló. Students in their 2nd course were provided with real information as marketing plans, profit and losses and operational accounts, employees profiles and employment costs. The challenge for them was to act as consultants, identifying potential courses of action, related to best, base and worst case. In order to do that, they were organized in teams and supported by 4th course students. Each professor deployed the problem in their subject; thus, research on the customers behavior and feelings were necessary to review, as part of the marketing plan, if the current offering of the hotel was clear enough to guarantee and to communicate a safe environment, as well as the ranking of other basic, supporting and facilitating services. Also, continuous monitoring of competitors’ activity was necessary to understand what was the behavior of the open outlets. The actions designed after the diagnose were ranked in accordance with their impact and feasibility in terms of time and resources. Also they must be actionable by the current staff of the hotel and their managers and a vision of internal marketing was appreciated. After a process of refinement, seven teams presented their conclusions to Emperatriz general manager and the rest of professors. Four main ideas were chosen, and all the teams, irrespectively of authorship, were asked to develop them to the state of a minimum viable product, with estimations of impacts and costs. As the process continues, students are nowadays accompanying the hotel and their staff in the prudent reopening of facilities, almost one year after the closure. From a professor’s point of view, key learnings were 1.- When facing a real problem, a holistic view is needed. Therefore, the vision of subjects as silos collapses, 2- When educating new professionals, providing them with the resilience and resistance necessaries to deal with a problem is always mandatory, but now seems more relevant and 3.- collaborative work and contact with real practitioners in such an uncertain and changing environment is a challenge, but it is worth when considering the learning result and its potential.

Keywords: problem-based learning, hospitality recovery, collaborative learning, resilience

Procedia PDF Downloads 183

Authors: Tibor Ajtai, Máté Pintér, Noémi Utry, Gergely Kiss-Albert, Andrea Palágyi, László Manczinger, Csaba Vágvölgyi, Gábor Szabó, Zoltán Bozóki

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According to the best knowledge of the authors, here we experimentally demonstrate first, a quantified correlation between the real-time measured optical feature of the ambient and the off-line measured toxicity data. Finally, using these correlations we are presenting a novel methodology for real time characterisation of ambient toxicity based on the multi wavelength aerosol phase photoacoustic measurement. Ambient carbonaceous particulate matter is one of the most intensively studied atmospheric constituent in climate science nowadays. Beyond their climatic impact, atmospheric soot also plays an important role as an air pollutant that harms human health. Moreover, according to the latest scientific assessments ambient soot is the second most important anthropogenic emission source, while in health aspect its being one of the most harmful atmospheric constituents as well. Despite of its importance, generally accepted standard methodology for the quantitative determination of ambient toxicology is not available yet. Dominantly, ambient toxicology measurement is based on the posterior analysis of filter accumulated aerosol with limited time resolution. Most of the toxicological studies are based on operational definitions using different measurement protocols therefore the comprehensive analysis of the existing data set is really limited in many cases. The situation is further complicated by the fact that even during its relatively short residence time the physicochemical features of the aerosol can be masked significantly by the actual ambient factors. Therefore, decreasing the time resolution of the existing methodology and developing real-time methodology for air quality monitoring are really actual issues in the air pollution research. During the last decades many experimental studies have verified that there is a relation between the chemical composition and the absorption feature quantified by Absorption Angström Exponent (AAE) of the carbonaceous particulate matter. Although the scientific community are in the common platform that the PhotoAcoustic Spectroscopy (PAS) is the only methodology that can measure the light absorption by aerosol with accurate and reliable way so far, the multi-wavelength PAS which are able to selectively characterise the wavelength dependency of absorption has become only available in the last decade. In this study, the first results of the intensive measurement campaign focusing the physicochemical and toxicological characterisation of ambient particulate matter are presented. Here we demonstrate the complete microphysical characterisation of winter time urban ambient including optical absorption and scattering as well as size distribution using our recently developed state of the art multi-wavelength photoacoustic instrument (4λ-PAS), integrating nephelometer (Aurora 3000) as well as single mobility particle sizer and optical particle counter (SMPS+C). Beyond this on-line characterisation of the ambient, we also demonstrate the results of the eco-, cyto- and genotoxicity measurements of ambient aerosol based on the posterior analysis of filter accumulated aerosol with 6h time resolution. We demonstrate a diurnal variation of toxicities and AAE data deduced directly from the multi-wavelength absorption measurement results.

Keywords: photoacoustic spectroscopy, absorption Angström exponent, toxicity, Ames-test

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Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

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Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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Authors: Elham Taghizadeh, Mostafa Abedzadeh, Mostafa Setak

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Logistics network is expected that opened facilities work continuously for a long time horizon without any failure; but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize cost of facility locations, customers’ assignment, and inventory management decisions when facilities face failure risks and doesn’t work. In our model we assume when a facility is out of work, its customers may be reassigned to other operational facilities otherwise they must endure high penalty costs associated with losing service. For defining the model closer to real world problems, the model is proposed based on p-median problem and the facilities are considered to have limited capacities. We define a new binary variable (Z_is) for showing that customers are not assigned to any facilities. Our problem involve a bi-objective model; the first one minimizes the sum of facility construction costs and expected inventory holding costs, the second one function that mention for the first one is minimizes maximum expected customer costs under normal and failure scenarios. For solving this model we use NSGAII and MOSS algorithms have been applied to find the pareto- archive solution. Also Response Surface Methodology (RSM) is applied for optimizing the NSGAII Algorithm Parameters. We compare performance of two algorithms with three metrics and the results show NSGAII is more suitable for our model.

Keywords: joint inventory-location problem, facility location, NSGAII, MOSS

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Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

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In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

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Authors: Khaled Elbehiery, Hussam Elbehiery

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The success of education is dependent on evolution and adaptation, while the traditional system has worked before, one type of education evolved with the digital age is virtual education that has influenced efficiency in today’s learning environments. Virtual learning has indeed proved its efficiency to overcome the drawbacks of the physical environment such as time, facilities, location, etc., but despite what it had accomplished, the educational system over all is not adequate for being a productive system yet. Earning a degree is not anymore enough to obtain a career job; it is simply missing the skills and creativity. There are always two sides of a coin; a college degree or a specialized certificate, each has its own merits, but having both can put you on a successful IT career path. For many of job-seeking individuals across world to have a clear meaningful goal for work and education and positively contribute the community, a productive correlation and cooperation among employers, universities alongside with the individual technical skills is a must for generations to come. Fortunately, the proposed research “Entrepreneur Universal Education System” is an evolution to meet the needs of both employers and students, in addition to gaining vital and real-world experience in the chosen fields is easier than ever. The new vision is to empower the education to improve organizations’ needs which means improving the world as its primary goal, adopting universal skills of effective thinking, effective action, effective relationships, preparing the students through real-world accomplishment and encouraging them to better serve their organization and their communities faster and more efficiently.

Keywords: virtual education, academic degree, certificates, internship, amazon web services, Microsoft Azure, Google Cloud Platform, hybrid models

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Authors: Mahadehe Hassan

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In most countries manufacturing, trading and distribution of gasoline and diesel fuels belongs to the most important sectors of national economy. For Bangladesh, a robust, well-functioning, secure and smartly managed national fuel distribution chain is an essential precondition for achieving Government top priorities in development and modernization of transportation infrastructure, protection of national environment and population health as well as, very importantly, securing due tax revenue for the State Budget. Bangladesh is a developing country with complex fuel supply network, high fuel taxes incidence and – till now - limited possibilities in application of modern, automated technologies for Government national fuel market control. Such environment allows dishonest physical and legal persons and organized criminals to build and profit from illegal fuel distribution schemes and fuel illicit trade. As a result, the market transparency and the country attractiveness for foreign investments, law-abiding economic operators, national consumers, State Budget and the Government ability to finance development projects, and the country at large suffer significantly. Research shows that over 50% of retail petrol stations in major agglomerations of Bangladesh sell adulterated fuels and/or cheat customers on the real volume of the fuel pumped into their vehicles. Other forms of detected fuel illicit trade practices include misdeclaration of fuel quantitative and qualitative parameters during internal transit and selling of non-declared and smuggled fuels. The aim of the study is to recommend the implementation of a National Fuel Distribution Integrity Program (FDIP) in Bangladesh to address and resolve fuel adulteration and illicit trade problems. The program should be customized according to the specific needs of the country and implemented in partnership with providers of advanced technologies. FDIP should enable and further enhance capacity of respective Bangladesh Government authorities in identification and elimination of all forms of fuel illicit trade swiftly and resolutely. FDIP high-technology, IT and automation systems and secure infrastructures should be aimed at the following areas (1) fuel adulteration, misdeclaration and non-declaration; (2) fuel quality and; (3) fuel volume manipulation at retail level. Furthermore, overall concept of FDIP delivery and its interaction with the reporting and management systems used by the Government shall be aligned with and support objectives of the Vision 2041 and Smart Bangladesh Government programs.

Keywords: fuel adulteration, octane, kerosene, diesel, petrol, pollution, carbon emissions

Procedia PDF Downloads 75

Authors: Shafait Hussain Ali

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Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Ting-Yu Lin, Han-Liang Lin

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This article is about the urban form of visualization by Cityengine. City is composed of different domains, and each domain has its own fabric because of arrangement. For example, a neighborhood unit contains fabrics such as schools, street networks, residential and commercial spaces. Therefore, studying urban morphology can help us understand the urban form in planning process. Streets, plots, and buildings seem as urban fabrics, and they configure urban form. Traditionally, urban morphology usually discussed single parameter, which is building type, ignoring other parameters such as streets and plots. However, urban space is three-dimensional, instead of two-dimensional. People perceive urban space by their visualization. Therefore, using visualization can fill the gap between two dimensions and three dimensions. Hence, the study of urban morphology will strengthen the understanding of whole appearance of a city. Cityengine is a software which can edit, analyze and monitor the data and visualize the result for GIS, a common tool to analyze data and display the map for urban plan and urban design. Cityengine can parameterize the data of streets, plots and building types and visualize the result in three-dimensional way. The research will reappear the real urban form by visualizing. We can know whether the urban form can be parameterized and the parameterized result can match the real urban form. Then, visualizing the result by software in three dimension to analyze the rule of urban form. There will be three stages of the research. It will start with a field survey of Tainan East District in Taiwan to conclude the relationships between urban fabrics of street networks, plots and building types. Second, to visualize the relationship, it will turn the relationship into codes which Cityengine can read. Last, Cityengine will automatically display the result by visualizing.

Keywords: Cityengine, urban fabric, urban morphology, visual simulation

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Authors: Michael Vieth, Aric Schadler, Hubert Ballard, J. A. Bauer, Pratibha Thakkar

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Introduction: Congenital diaphragmatic hernia (CDH) is a condition characterized by the herniation of abdominal contents into the thoracic cavity requiring postnatal surgical repair. Previous literature suggests improved CDH outcomes at high-volume regional referral centers compared to low-volume centers. The purpose of this study was to examine CDH outcomes at Kentucky Children’s Hospital (KCH), a low-volume center, compared to the Congenital Diaphragmatic Hernia Study Group (CDHSG). Methods: A retrospective chart review was performed at KCH from 2007-2019 for neonates with CDH, and then subdivided into two cohorts: those requiring ECMO therapy and those not requiring ECMO therapy. Basic demographic data and measures of mortality and morbidity including ventilator days and length of stay were compared to the CDHSG. Measures of morbidity for the ECMO cohort including duration of ECMO, clinical bleeding, intracranial hemorrhage, sepsis, need for continuous renal replacement therapy (CRRT), need for sildenafil at discharge, timing of surgical repair, and total ventilator days were collected. Statistical analysis was performed using IBM SPSS Statistics version 28. One-sample t-tests and one-sample Wilcoxon Signed Rank test were utilized as appropriate.Results: There were a total of 27 neonatal patients with CDH at KCH from 2007-2019; 9 of the 27 required ECMO therapy. The birth weight and gestational age were similar between KCH and the CDHSG (2.99 kg vs 2.92 kg, p =0.655; 37.0 weeks vs 37.4 weeks, p =0.51). About half of the patients were inborn in both cohorts (52% vs 56%, p =0.676). KCH cohort had significantly more Caucasian patients (96% vs 55%, p=<0.001). Unadjusted mortality was similar in both groups (KCH 70% vs CDHSG 72%, p =0.857). Using ECMO utilization (KCH 78% vs CDHSG 52%, p =0.118) and need for surgical repair (KCH 95% vs CDHSG 85%, p =0.060) as proxy for severity, both groups’ mortality were comparable. No significant difference was noted for pulmonary outcomes such as average ventilator days (KCH 43.2 vs. CDHSG 17.3, p =0.078) and home oxygen dependency (KCH 44% vs. CDHSG 24%, p =0.108). Average length of hospital stay for patients treated at KCH was similar to CDHSG (64.4 vs 49.2, p=1.000). Conclusion: Our study demonstrates that outcome in CDH patients is independent of center’s case volume status. Management of CDH with a standardized approach in a low-volume center can yield similar outcomes. This data supports the treatment of patients with CDH at low-volume centers as opposed to transferring to higher-volume centers.

Keywords: ECMO, case volume, congenital diaphragmatic hernia, congenital diaphragmatic hernia study group, neonate

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Authors: Marie Madeleine Nanga Ndjang, Julie Mathilde Klang, Edwin M. Mmutlane, Derek Tantoh Ndinteh, Eugenie Kayitesi, Francois Ngoufack Zambou

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Gluten intolerance and the unavailability of wheat flour in some parts of the world have led to the development of gluten-free bread. However, gluten-free bread generally results in a low specific volume, and to remedy this, the use of hydrocolloids and bases has proved to be very successful. Thus, the present study aims to determine the optimal proportions of gum extract of Triumffetapentendraand sodium bicarbonate in breadmaking of a composite flour based on sour cassava starch, peanut, and cowpea flour. To achieve this, a BoxBenkhendesign was used, the variable being the amount of extract gums, the amount of bicarbonate, and the amount of water. The responses evaluated were the specific volume and texture properties (Hardness, Cohesiveness, Consistency, Elasticity, and Masticability). The specific volume was done according to standard methods of AACC and the textural properties by a texture analyzer. It appears from this analysis that the specific volume is positively influenced by the incorporation of extract gums, bicarbonate, and water. The hardness, consistency, and plasticity increased with the incorporation rate of extract gums but reduced with the incorporation rate of bicarbonate and water. On the other hand, Cohesion and elasticity increased with the incorporation rate of bicarbonate and water but reduced with the incorporation of extract gum. The optimate proportions of extract gum, bicarbonate, and water are 0.28;1.99, and 112.5, respectively. This results in a specific volume of 1.51; a hardness of 38.51; a cohesiveness of 0.88; a consistency of 32.86; an elasticity of 5.57, and amasticability of 162.35. Thus, this analysis suggests that gum extracts and sodium bicarbonate can be used to improve the quality of gluten-free bread.

Keywords: box benkhen design, bread-making, gums, textures properties, specific volume

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Authors: Boroka Gács, Tibor Szolcsányi, Árpad Csathó

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Background: Individuals frequently show habituation to repeated noxious heat. However, given the defensive function of human pain processing, it is reasonable to assume that individuals imagine that they would become increasingly sensitive to repeated thermal pain stimuli. To the best of the authors' knowledge, no previous studies have, however, been addressed to this assumption. Therefore, in the current study, we investigated how healthy human individuals imagine the intensity of repeated thermal pain stimulations, and compared this with the intensity ratings given after physically induced thermal pain trials. Methods: Healthy participants (N = 20) gave pain intensity ratings in two conditions: imagined and real thermal pain. In the real pain condition thermal pain stimuli of two intensities (minimal and moderate pain) were delivered in four consecutive trials. The duration of the peak temperature was 20s, and stimulation was always delivered to the same location. In each trial, participants rated the pain intensity twice, 5s and 15s after the onset of the peak temperature. In the imagined pain condition, participants were subjected to a reference pain stimulus and then asked to imagine and rate the same sequence of stimulations as in the induced pain condition. Results: Ratings of imagined pain and physically induced pain followed opposite courses over repeated stimulation: Ratings of imagined pain indicated sensitization whereas ratings for physically induced pain indicated habituation. The findings were similar for minimal and moderate pain intensities. Conclusions: The findings suggest that, rather than habituating to pain, healthy individuals imagine that they would become increasingly sensitive to repeated thermal pain stimuli.

Keywords: habituation, imagined pain, pain perception, thermal stimulation

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Authors: Claire Biasco, Thaier Hayajneh

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A smart city is the integration of digital technologies in urban environments to enhance the quality of life. Smart cities capture real-time information from devices, sensors, and network data to analyze and improve city functions such as traffic analysis, public safety, and environmental impacts. Current smart cities face controversy due to their reliance on real-time data tracking and surveillance. Internet of Things (IoT) devices and blockchain technology are converging to reshape smart city infrastructure away from its centralized model. Connecting IoT data to blockchain applications would create a peer-to-peer, decentralized model. Furthermore, blockchain technology powers the ability for IoT device data to shift from the ownership and control of centralized entities to individuals or communities with Decentralized Autonomous Organizations (DAOs). In the context of smart cities, DAOs can govern cyber-physical systems to have a greater influence over how urban services are being provided. This paper will explore how the core components of a smart city now apply to DAOs. We will also analyze different definitions of DAOs to determine their most important aspects in relation to smart cities. Both categorizations will provide a solid foundation to conduct a cybersecurity assessment of DAOs in smart cities. It will identify the benefits and risks of adopting DAOs as they currently operate. The paper will then provide several mitigation methods to combat cybersecurity risks of DAO integrations. Finally, we will give several insights into what challenges will be faced by DAO and blockchain spaces in the coming years before achieving a higher level of maturity.

Keywords: blockchain, IoT, smart city, DAO

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Authors: Amir Saber Gharamaleki, Beitollah Alipour, Zeinab Faghfoori, Ahmad YariKhosroushahi

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Colorectal cancer (CRC) is one of the most prevalent cancers and intestinal microbial community plays an important role in colorectal tumorigenesis. Probiotics have recently been assessed as effective anti-proliferative agents and thus this study was performed to examine whether CRC undergo apoptosis by treating with isolated Iranian native dairy yeast, Kluyveromyces marxianus YAS, secretion metabolites. The cytotoxicity assessments on cells (HT-29, Caco-2) were accomplished through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay as well as qualitative DAPI (4',6-diamidino-2-phenylindole staining) and quantitative (flow cytometry assessments) evaluations of apoptosis. To evaluate the main mechanism of apoptosis, Real time PCR method was applied. Kluyveromyces marxianus YAS secretions (IC50) showed significant cytotoxicity against HT-29 and Caco-2 cancer cell lines (66.57 % and 66.34 % apoptosis) similar to 5-Fluorouracil (5-FU) while apoptosis only was developed in 27.57 % of KDR normal cells. The prophylactic effects of Kluyveromyces marxianus (PTCC 5195), as a reference yeast, was not similar to Kluyveromyces marxianus YAS indicating strain dependency of bioactivities on CRC disease prevention. Based on real time PCR results, the main cytotoxicity is related to apoptosis phenomenon and the core related mechanism is depended on the overexpression of BAX, CASP 9, CASP 8 and CASP 3 inducing apoptosis genes. However, several investigations should be conducted to precisely determine the effective compounds to be used as anticancer therapeutics in the future.

Keywords: anticancer, anti-proliferative, apoptosis, cytotoxicity, yeast

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Authors: Amita Jain, Shantanu Prakash, Suruchi Shukla

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Introduction: Acute encephalitis syndrome (AES) is a complex multi etiology syndrome posing a great public health problem in the northern part of India. Japanese encephalitis (JE) virus is an established etiology of AES in this region. Recently, Scrub typhus (ST) is being recognized as an emerging aetiology of AES in JE endemic belt. This study was conducted to establish the direct evidence of Central nervous system invasion by Orientia tsutsugamushi leading to AES. Methodology: A total of 849 cases with clinical diagnosis of AES were enrolled from six districts (Deoria and its adjoining area) of the traditional north Indian Japanese encephalitis (JE) belt. Serum and Cerebrospinal fluid samples were collected and tested for major agent causing acute encephalitis. AES cases either positive for anti-ST IgM antibodies or negative for all tested etiologies were investigated for ST-DNA by real-time PCR. Results: Of these 505 cases, 250 patients were laboratory confirmed for O. tsutsugamushi infection either by anti-ST IgM antibodies positivity (n=206) on serum sample or by ST-DNA detection by real-time PCR assay on CSF sample (n=2) or by both (n=42).Total 29 isolate could be sequenced for 56KDa gene. Conclusion: All the strains were found to cluster with Gilliam strains. The majority of the isolates showed a 97–99% sequence similarity with Thailand and Cambodian strains. Gilliam strain of O.tsusugamushi is an emerging as one of the major aetiologies leading to AES in northern part of India.

Keywords: acute encephalitis syndrome, O. tsutsugamushi, Gilliam strain, North India, cerebrospinal fluid

Procedia PDF Downloads 250