Search results for: facility performance evaluation

Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki

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With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.

Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)

Procedia PDF Downloads 192

Authors: Husam Abdulmuttaleb Hashim

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The environmental pollution problems represent a great challenge to the world, threatening to destroy all the evolution that mankind has reached, the organizations and associations that cares about environment are trying to warn the world from the forthcoming danger resulted from excessive use of nature resources and consuming it without looking to the damage happened as a result of unfair use of it. Most of the urban centers suffers from the environmental pollution problems and health, economic, and social dangers resulted from this pollution, and while the land use planning is responsible for distributing different uses in urban centers and controlling the interactions between these uses to reach a homogeneous and perfect state for the different activities in cities, the occurrence of environmental problems in the shade of existing land use planning operation refers to the disorder or insufficiency in this operation which leads to presence of such problems, and this disorder lays in lack of sufficient importance to the environmental considerations during the land use planning operations and setting up the master plan, so the research start to study this problem and finding solutions for it, the research assumes that using accurate and scientific methods in early stages of land use planning operation will prevent occurring of environmental pollution problems in the future, the research aims to study and show the importance of the environmental impact assessment method (EIA) as an important planning tool to investigate and predict the pollution ranges of the land use that has a polluting pattern in land use planning operation. This research encompasses the concept of environmental assessment and its kinds and clarifies environmental impact assessment and its contents, the research also dealt with urban planning concept and land use planning, it also dealt with the current situation of the case study (Al-Garma district) and the land use planning in it and explain the most polluting use on the environment which is the industrial land use represented in the tannery industries and then there was a stating of current situation of this land use and explaining its contents and environmental impacts resulted from it, and then we analyzed the tests applied by the researcher for water and soil, and perform environmental evaluation through applying environmental impact assessment matrix using the direct method to reveal the pollution ranges on the ambient environment of industrial land use, and we also applied the environmental and site limits and standards by using (GIS) and (AUTOCAD) to select the site of the best alternative of the industrial region in Al-Garma district after the research approved the unsuitability of its current site location for the environmental and site limitations, the research conducted some conclusions and recommendations regard clarifying the concluded facts and to set the proper solutions.

Keywords: EIA, pollution, tannery industry, land use planning

Procedia PDF Downloads 440

Authors: Hati̇ce Bi̇rtane, Asli Beyler Çi̇ği̇l, Memet Vezi̇r Kahraman

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Polyimide (PI) is one of the most important super-engineering materials because of its mechanical properties and its thermal stability. Electronic industry is the typical extensive applications of polyimides including interlayer insulation films, buffer coating, films, alpha-ray shielding films, and alignment films for liquid crystal displays. The mechanical and thermal properties of polymers are generally improved by the addition of inorganic additives. The challenges in this area of high-performance organic/inorganic hybrid materials are to obtain significant improvements in the interfacial adhesion between the polymer matrix and the reinforcing material since the organic matrix is relatively incompatible with the inorganic phase. In this study, modified nanodiamond was prepared from the reaction of nanodiamond and (3-Mercaptopropyl)trimethoxysilane. Poly(amic acid) was prepared from the reaction of 3,3',4,4'-Benzophenonetetracarboxylic dianhydride (BTDA) and 4,4'-Oxydianiline (ODA). Polyimide/modified nanodiamond hybrids were prepared by blending of poly(amic acid) and organically modified nanodiamond. The morphology of the Polyimide/ modified nanodiamond hybrids was characterized by scanning electron microscopy (SEM). Chemical structure of polyimide and Polyimide/modified nanodiamond hybrids was characterized by FTIR. FTIR results showed that the Polyimide/modified nanodiamond hybrids were successfully prepared. A thermal property of the Polyimide/modified nanodiamond hybrids was characterized by thermogravimetric analysis (TGA).

Keywords: hybrid materials, nanodiamond, polyimide, polymer

Procedia PDF Downloads 228

Authors: Bastien Batardière, Joon Kwon

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For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

Procedia PDF Downloads 52

Authors: Carolina Pereira Lobato Costa, Cristina Pascual-González, Monica Echeverry, Javier LLorca, Carlos Gonzáléz, Juan Pedro Fernández-Bláquez

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Although the potential of PLA self-reinforced composites for bone applications, not much literature addresses optimal manufacturing conditions. In this regard, this paper describes the woven self-reinforced PLA composites manufacturing processes: the commingling of yarns, weaving, and hot pressing and characterizes the manufactured laminates. Different structures and properties can be achieved by varying the hot compaction process parameters (pressure, holding time, and temperature). The specimens manufactured were characterized in terms of thermal properties (DSC), microstructure (C-scan optical microscope and SEM), strength (tensile test), and biocompatibility (MTT assays). Considering the final device, 155 ℃ for 10 min at 2 MPa act as the more appropriate hot pressing parameters. The laminate produced with these conditions has few voids/porosity, a tensile strength of 30.39 ± 1.21 MPa, and a modulus of 4.09 ± 0.24 GPa. Subsequently to the tensile testing was possible to observe fiber pullout from the fracture surfaces, confirming that this material behaves as a composite. From the results, no single laminate can fulfill all the requirements, being necessary to compromise in function of the priority property. Further investigation is required to improve materials' mechanical performance. Subsequently, process parameters and materials configuration can be adjusted depending on the place and type of implant to suit its function.

Keywords: woven fabric, self-reinforced polymer composite, poly(lactic acid), biodegradable

Procedia PDF Downloads 180

Authors: Yu Zhao, Rainer Gruenheid, Gerhard Bauch

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In the microwave and millimeter-wave transmission region, substrate-integrated waveguide (SIW) is a very promising candidate for the development of circuits and components. It facilitates the transmission at the data rates in excess of 200 Gbit/s. An SIW mimics a rectangular waveguide by approximating the closed sidewalls with a via fence. This structure suppresses the low frequency components and makes the channel of the SIW a bandpass or high pass filter. This channel characteristic impedes the conventional baseband transmission using non-return-to-zero (NRZ) pulse shaping scheme. Therefore, mixers are commonly proposed to be used as carrier modulator and demodulator in order to facilitate a passband transmission. However, carrier modulation is not an energy efficient solution, because modulation and demodulation at high frequencies consume a lot of energy. For the first time to our knowledge, this paper proposes a spectrum shaping scheme of low complexity for the channel of SIW, namely spread reshaping code. It aims at matching the spectrum of the transmit signal to the channel frequency response. It facilitates the transmission through the SIW channel while it avoids using carrier modulation. In some cases, it even does not need equalization. Simulations reveal a good performance of this scheme, such that, as a result, eye opening is achieved without any equalization or modulation for the respective transmission channels.

Keywords: bandpass channel, eye-opening, switching frequency, substrate-integrated waveguide, spectrum shaping scheme, spread reshaping code

Procedia PDF Downloads 147

Authors: Lila Boulekbache-Makhlouf, Kahina Djaoud, Myriam Tazarourte, Samir Hadjal, Khodir Madani

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In Algeria, important quantities of secondary date variety (Phoenix dactylifera L.) are generated in each campaign; their chemical composition is similar to that of commercial dates. The present work aims to valorize this common date variety (Degla-Beida) which is often poorly exploited. In this context, we tried to prepare syrup from the secondary date variety and to evaluate the effect of conventional extraction (CE) or water bath extraction (WBE) and alternative extraction (microwaves assisted extraction (MAE), and ultrasounds assisted extraction (UAE)) on its total sugar content (TSC), using response surface methodology (RSM). Then, the analysis of individual sugars was performed by high-performance liquid chromatography (HPLC). Maximum predicted TSC recoveries under the optimized conditions for MAE, UAE and CE were 233.248 ± 3.594 g/l, 202.889 ± 5.797 g/l, and 233.535 ± 5.412 g/l, respectively, which were close to the experimental values: 233.796 ± 1.898 g/l; 202.037 ± 3.401 g/l and 234.380 ± 2.425 g/l. HPLC analysis revealed high similarity in the sugar composition of date juices obtained by MAE (60.11% sucrose, 16.64% glucose and 23.25% fructose) and CE (50.78% sucrose, 20.67% glucose and 28.55% fructose), although a large difference was detected for that obtained by UAE (0.00% sucrose, 46.94% glucose and 53.06% fructose). Microwave-assisted extraction was the best method for the preparation of date syrup with an optimal recovery of total sugar content. However, ultrasound-assisted extraction was the best one for the preparation of date syrup with high content of reducing sugars.

Keywords: dates, extraction, RSM, sugars, syrup

Procedia PDF Downloads 141

Authors: A. Das, L. Hitihamillage, S. Moridpour

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Natural disasters are inevitable to the biodiversity. Disasters such as flood, tsunami and tornadoes could be brutal, harsh and devastating. In Australia, flooding is a major issue experienced by different parts of the country. In such crisis, delays in evacuation could decide the life and death of the people living in those regions. Congestion management could become a mammoth task if there are no steps taken before such situations. In the past to manage congestion in such circumstances, many strategies were utilised such as converting the road shoulders to extra lanes or changing the road geometry by adding more lanes. However, expansion of road to resolving congestion problems is not considered a viable option nowadays. The authorities avoid this option due to many reasons, such as lack of financial support and land space. They tend to focus their attention on optimising the current resources they possess and use traffic signals to overcome congestion problems. Traffic Signal Management strategy was considered a viable option, to alleviate congestion problems in the City of Geelong, Victoria. Arterial road with signalised intersections considered in this paper and the traffic data required for modelling collected from VicRoads. Traffic signalling software SIDRA used to model the roads, and the information gathered from VicRoads. In this paper, various signal parameters utilised to assess and improve the corridor performance to achieve the best possible Level of Services (LOS) for the arterial road.

Keywords: congestion, constraints, management, LOS

Procedia PDF Downloads 377

Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

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This paper will focus on the suitability of a trapped vortex combustor as a candidate for gas turbine combustor objectives to minimize pressure drop across the combustor and investigate aerodynamic performance. Non-reacting simulation of axisymmetric cavity trapped vortex combustors were simulated to investigate the pressure drop for various cavity aspect ratios of 0.3, 0.6, and 1 and for air mass flow rates of 14 m/s, 28 m/s, and 42 m/s. A numerical study of an axisymmetric trapped vortex combustor was carried out by using two-dimensional and three-dimensional computational domains. A comparison study was conducted between Reynolds Averaged Navier Stokes (RANS) k-ε Realizable with enhanced wall treatment and RANS k-ω Shear Stress Transport (SST) models to find the most suitable turbulence model. It was found that the k-ω SST model gives relatively close results to experimental outcomes. The numerical results were validated and showed good agreement with the experimental data. Pressure drop rises with increasing air mass flow rate, and the lowest pressure drop was observed at 0.6 cavity aspect ratio for all air mass flow rates tested, which agrees with the experimental outcome. A mixing enhancement study showed that 30-degree angle air injectors provide improved fuel-air mixing.

Keywords: aerodynamic, computational fluid dynamics, propulsion, trapped vortex combustor

Procedia PDF Downloads 73

Authors: Jui-Chien Hsieh

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Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

Procedia PDF Downloads 104

Authors: Pablo Reyes, Vanessa Riveros Fiallo, Cesar Acevedo, Camila Castellanos, Catalina Moncaleano, Maria F. Parra, Laura Colmenares

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Social emotions are physiological, cognitive and behavioral phenomenon that intervene in the mechanisms of adaptation of individuals and their context. These are mediated by interpersonal relationship and language. Such emotions are subdivided into moral and comparison. The present research emphasizes two comparative emotions: Envy and Schadenfreude. Envy arises when a person lack of quality, possessions or achievements and these are superior in someone else. The Schadenfreude (SC) expresses the pleasure that someone experienced by the misfortune of the other. The relationship between both emotions has been questioned before. Hence there are reports showing that envy increases and modulates SC response. Other documents suggest that envy causes SC response. However, the methodological approach of the topic has been made through self-reports, as well as the hypothetical scenarios. Given this problematic, the neuroscience social framework provides an alternative and demonstrates that social emotions have neurophysiological correlates that can be measured. This is relevant when studying social emotions that are reprehensible like envy or SC are. When tested, the individuals tend to report low ratings due to social desirability. In this study, it was drawn up a proposal in research's protocol and the progress on its own piloting. The aim is to evaluate the effect of feeling envy and Schadenfreude has on the decision-making process, as well as the cooperative behavior in an economic game. To such a degree, it was proposed an experimental model that will provoke to feel envious by performing games against an unknown opponent. The game consists of asking general knowledge questions. The difficulty level in questions and the strangers' facial response have been manipulated in order to generate an ecological comparison framework and be able to arise both envy and SC emotions. During the game, an electromyography registry will be made for two facial muscles that have been associated with the expressiveness of envy and SC emotions. One of the innovations of the current proposal is the measurement of the effect that emotions have on a specific behavior. To that extent, it was evaluated the effect of each condition on the dictators' economic game. The main intention is to evaluate if a social emotion can modulate actions that have been associated with social norms, in the literacy. The result of the evaluation of a pilot model (without electromyography record and self-report) have shown an association between envy and SC, in a way that as the individuals report a greater sense of envy, the greater the chance to experience SC. The results of the economic game show a slight tendency towards profit maximization decisions. It is expected that at the time of using real cash this behavior will be strengthened and also to correlate with the responses of electromyography.

Keywords: envy, schadenfreude, electromyography, economic games

Procedia PDF Downloads 359

Authors: Z. Razi, S. M. J. Mortazavi, N. Shokrpour, Z. Shayan, F. Amiri

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Long-term exposure to low doses of ionizing radiation occurs in radiation health care workplaces. Although doses in health professions are generally very low, there are still matters of concern. The radiation safety program promotes occupational radiation safety through accurate and reliable monitoring of radiation workers in order to effectively manage radiation protection. To achieve this goal, it has become mandatory to implement health examination periodically. As a result, based on the hematological alterations, working populations with a common occupational radiation history are screened. This paper calls into question the effectiveness of blood component analysis as a screening program which is mandatory for medical radiation workers in some countries. This study details the distribution and trends of changes in blood components, including white blood cells (WBCs), red blood cells (RBCs) and platelets as well as received cumulative doses from occupational radiation exposure. This study was conducted among 199 participants and 100 control subjects at the medical imaging departments at the central hospital of Shiraz University of Medical Sciences during the years 2006–2010. Descriptive and analytical statistics, considering the P-value<0.05 as statistically significance was used for data analysis. The results of this study show that there is no significant difference between the radiation workers and controls regarding WBCs and platelet count during 4 years. Also, we have found no statistically significant difference between the two groups with respect to RBCs. Besides, no statistically significant difference was observed with respect to RBCs with regards to gender, which has been analyzed separately because of the lower reference range for normal RBCs levels in women compared to men and. Moreover, the findings confirm that in a separate evaluation between WBCs count and the personnel’s working experience and their annual exposure dose, results showed no linear correlation between the three variables. Since the hematological findings were within the range of control levels, it can be concluded that the radiation dosage (which was not more than 7.58 mSv in this study) had been too small to stimulate any quantifiable change in medical radiation worker’s blood count. Thus, use of more accurate method for screening program based on the working profile of the radiation workers and their accumulated dose is suggested. In addition, complexity of radiation-induced functions and the influence of various factors on blood count alteration should be taken into account.

Keywords: blood cell count, mandatory testing, occupational exposure, radiation

Procedia PDF Downloads 447

Authors: Sara Taghdisi, M. Mirmohammadi, M. Mokhtarian

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In 2013, the World Health Organization announced the cases of Cutaneous leishmaniasis infection in Iran between 69,000 to 113,000. The most common chemical drugs for Cutaneous leishmaniasis treatment are sodium stibogluconate, and meglumine antimonate, which not only have relatively many side effects, but also some species of the Leishmania genus have become resistant to them .The most prominent compound existing in different parts of the cotton plant is a yellow polyphenol called Gossypol. Gossypol is an extremely valuable compound and has anti-cancer properties. In the current project, Gossypol was extracted with a liquid-liquid extraction method in 120 minutes in the presence of Phosphoric acid from the cotton seed oil of Golestan beach varieties, then got crystallized in darkness using Acetic acid and isolated as Gossypol Acetic acid. The efficiency of the extracted crystal was obtained at 0.12+- 1.28. the cotton plant could be efficient in the treatment of Cutaneous leishmaniasis. The extract of the green-leaf cotton boll of Jargoyeh varieties was tested as an ointment on the target group of patients suffering from Cutaneous leishmaniasis resistant to drugs esistant to drugs by our colleagues in the research team. The results showed the Pearson's correlation coefficient of 0.72 between the two variables of wound diameter and the extract use over time which indicated the positive effect of this extract on the treatment of Cutaneous leishmaniasis was resistant to drugs.

Keywords: cottonseed oil, crystallization, gossypol, green-leaf

Procedia PDF Downloads 84

Authors: Mei Hong, Wei Liu, Xuemin Dai, Yanxiong Pan, Xiangling Ji

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Polyamic acid (PAA) is the precursor of polyimide (PI) prepared by a two-step method, its molecular weight and molecular weight distribution not only play an important role during the preparation and processing, but also influence the final performance of PI. However, precise characterization on molecular weight of PAA is still a challenge because of the existence of very complicated interactions in the solution system, including the electrostatic interaction, hydrogen bond interaction, dipole-dipole interaction, etc. Thus, it is necessary to establisha suitable strategy which can completely suppress these complex effects and get reasonable data on molecular weight. Herein, the gel permeation chromatography (GPC) coupled with differential refractive index (RI) and multi-angle laser light scattering (MALLS) detectors were applied to measure the molecular weight of (6FDA-DMB) PAA using different mobile phases, LiBr/DMF, LiBr/H3PO4/THF/DMF, LiBr/HAc/THF/DMF, and LiBr/HAc/DMF, respectively. It was found that combination of LiBr with HAc can shield the above-mentioned complex interactions and is more conducive to the separation of PAA than only addition of LiBr in DMF. LiBr/HAc/DMF was employed for the first time as a mild mobile phase to effectively separate PAA and determine its molecular weight. After a series of conditional experiments, 0.02M LiBr/0.2M HAc/DMF was fixed as an optimized mobile phase to measure the relative and absolute molecular weights of (6FDA-DMB) PAA prepared, and the obtained Mw from GPC-MALLS and GPC-RI were 35,300 g/mol and 125,000 g/mol, respectively. Particularly, such a mobile phase is also applicable to other PAA samples with different structures, and the final results on molecular weight are also reproducible.

Keywords: Polyamic acids, Polyelectrolyte effects, Gel permeation chromatography, Mobile phase, Molecular weight

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Authors: Alper Akin, Ibrahim Aydogdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teaching-learning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame

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Authors: Reza Hosseinpourpia, Stergios Adamopoulos, Carsten Mai

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Medium density fiberboard (MDF) is a common category of wood-based panels that are widely used in the furniture industry. Fine lignocellulosic fibres are combined with a synthetic resin, mostly urea formaldehyde (UF), and joined together under heat and pressure to form panels. Like solid wood, MDF is a hygroscopic material; therefore, its moisture content depends on the surrounding relative humidity and temperature. In addition, UF is a hydrophilic resin and susceptible to hydrolysis under certain conditions of elevated temperatures and humidity, which cause dimensional instability of the panels. The latter directly affect the performance of final products such as furniture, when they are used in situations of high relative humidity. Existing water-repellent formulations, such as paraffin, present limitations related to their non-renewable nature, cost and highest allowed added amount. Therefore, the aim of the present study was to test the suitability of renewable water repellents as alternative chemicals for enhancing the dimensional stability of MDF panels. A small amount of tall oil based formulations were used as water-repellent agents in the manufacturing of laboratory scale MDF. The effects on dimensional stability, internal bond strength and formaldehyde release of MDF were tested. The results indicated a good potential of tall oil as a bio-based substance of water repellent formulations for improving the dimensional stability of MDF.

Keywords: dimensional stability, medium density fiberboard, tall oil, urea formaldehyde

Procedia PDF Downloads 229

Authors: Hao Qu, Xiang Liu, Michael Crosby, Brian Kozak, Andreas K. Freund

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The outstanding performance of highly oriented pyrolytic graphite (HOPG) as an optical element for neutron beam conditioning is unequaled by any other crystalline material in the applications of monochromator, analyzer, and filter. This superiority stems from the favorable nuclear properties of carbon (small absorption and incoherent scattering cross-sections, big coherent scattering length) and the specific crystalline structure (small thermal diffuse scattering cross-section, layered crystal structure). The real crystal defect structure revealed by imaging techniques is correlated with the parameters used in the mosaic model (mosaic spread, mosaic block size, uniformity). The diffraction properties (rocking curve width as determined by both the intrinsic mosaic spread and the diffraction process, peak and integrated reflectivity, filter transmission) as a function of neutron wavelength or energy can be predicted with high accuracy and reliability by diffraction theory using empirical primary extinction coefficients extracted from a great amount of existing experimental data. The results of these calculations are given as graphs and tables permitting to optimize HOPG characteristics (mosaic spread, thickness, curvature) for any given experimental situation.

Keywords: neutron optics, pyrolytic graphite, mosaic spread, neutron scattering, monochromator, analyzer

Procedia PDF Downloads 126

Authors: Rabiatu Bonku, Faisal Alkaabneh

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Inspired by a food banks distribution operation for non-profit organization, we study a variant synchronized vehicle routing problem for equitable resource allocation. This research paper introduces a Mixed Integer Programming (MIP) model aimed at addressing the complex challenge of efficiently distributing vital resources, particularly for food banks serving vulnerable populations in urban areas. Our optimization approach places a strong emphasis on social equity, ensuring a fair allocation of food to partner agencies while minimizing wastage. The primary objective is to enhance operational efficiency while guaranteeing fair distribution and timely deliveries to prevent food spoilage. Furthermore, we assess four distinct models that consider various aspects of sustainability, including social and economic factors. We conduct a comprehensive numerical analysis using real-world data to gain insights into the trade-offs that arise, while also demonstrating the models’ performance in terms of fairness, effectiveness, and the percentage of food waste. This provides valuable managerial insights for food bank managers. We show that our proposed approach makes a significant contribution to the field of logistics optimization and social responsibility, offering valuable insights for improving the operations of food banks.

Keywords: food banks, humanitarian logistics, equitable resource allocation, synchronized vehicle routing

Procedia PDF Downloads 47

Authors: Fatih Topaloğlu

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Although philosophy is inherently a theoretical and intellectual activity, it should not be denied that environmental conditions influence the formation and shaping of philosophical thought. In this context, it should be noted that the Philosophy of Religion has been influential in the debates in the West, especially since the beginning of the 20th century, and that this influence has dimensions that cannot be limited to academic or intellectual fields. The issues and problems that fall within the field of interest of Philosophy of Religion are followed with interest by a significant proportion of society through popular publications. Philosophy of Religion has its share in many social, economic, cultural, scientific, political and ethical developments. Philosophy of Religion, in the most general sense, can be defined as a philosophical approach to religion or a philosophical way of thinking and discussing religion. Philosophy of Religion tries to explain the epistemological foundations of concepts such as belief and faith that shape religious life by revealing their meaning for the individual. Thus, Philosophy of Religion tries to evaluate the effect of beliefs on the individual's values, judgments and behaviours with a comprehensive and critical eye. The Philosophy of Religion, which tries to create new solutions and perspectives by applying the methods of philosophy to religious problems, tries to solve these problems not by referring to the holy book or religious teachings but by logical proofs obtained through the possibilities of reason and evidence filtered through the filter of criticism. Although there is no standard method for doing Philosophy of Religion, it can be said that an approach that can be expressed as thinking about religion in a rational, objective, and consistent way is generally accepted. The evaluations made within the scope of Philosophy of Religion have two stages. The first is the definition stage, and the second is the evaluation stage. In the first stage, the data of different scientific disciplines, especially other religious sciences, are utilized to define the issues objectively. In the second stage, philosophical evaluations are made based on this foundation. During these evaluations, the issue of how the relationship between religion and philosophy should be established is extremely sensitive. The main thesis of this paper is that the Philosophy of Religion, as a branch of philosophy, has been affected by the conditions caused by the historical experience through which it has passed and has differentiated its subjects and the methods it uses to realize its philosophical acts over time under the influence of these conditions. This study will attempt to evaluate the validity of this study based on the "Introduction to Philosophy of Religion" literature, which we assume reflects this differentiation. As a result of this examination will aim to reach some factual conclusions about the nature of both philosophical and religious thought, to determine the phases that the Philosophy of Religion as a discipline has gone through since the day it emerged, and to investigate the possibilities of a holistic view of the field.

Keywords: content analysis, culture, history, philosophy of religion, method

Procedia PDF Downloads 41

Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

Procedia PDF Downloads 175

Authors: Paul Dunst, Ing. Tobias Hemsel, Ing. Habil. Walter Sextro

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The use of fine powders with high cohesive and adhesive properties leads to challenges during transport, mixing and dosing in industrial processes, which have not been satisfactorily solved so far. Due to the increased contact forces at the transporting parts (e. g. pipe-wall and transport screws), conventional transport systems and also vibratory conveyors reach their limits. Often, flowability increasing additives that need to be removed again in later process steps are the only option to achieve wanted transport results. A rather new ultrasound-assisted powder transport system showed to overcome some of the issues by manipulating the effective friction between powder and transport pipe. Within this contribution, the transport mechanism will be introduced shortly, together with preliminary transport results. As the tangential force of the transport pipe and the powder is the main influencing factor within the transport process, a test stand for measuring tangential forces of a powder-wall contact in the presence of an ultrasonic vibration orthogonal to the contact plane was built. Measurements for a sample powder show that the effective tangential force can already be significantly reduced at very low ultrasonic amplitude. As a result of the measurements, an empirical model for the relationship of tangential force, contact parameters and ultrasonic excitation is presented. This model was used to adjust the driving parameters of the powder transport system, resulting in better performance.

Keywords: powder transport, ultrasound, friction, friction manipulation, vibratory conveyor

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Authors: Ayman M. Ibrahim, Jinpeng Cai, Peilun Shen, Dianwen Liu

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The difference in promoting sulfurization between different ammonium salts and its anion's effect on the sulfurization of the malachite surface was systematically studied. Therefore, this study takes malachite, a typical copper oxide mineral, as the research object, field emission scanning electron microscopy and energy-dispersive X-ray analysis (FESEM‒EDS), X-ray photoelectron spectroscopy (XPS), and other analytical and testing methods, as well as pure mineral flotation experiments, were carried out to examine the superiority of the ammonium salts as the sulfurizing reagent of malachite at the microscopic level. Additionally, the promoting effects of ammonium sulfate and ammonium phosphate on the malachite sulfurization of xanthate-flotation were compared systematically from the microstructure of sulfurized products, elemental composition, chemical state of characteristic elements, and hydrophobicity surface evolution. The FESEM and AFM results presented that after being pre-treated with ammonium salts, the adhesion of sulfurized products formed on the mineral surface was denser; thus, the flake radial dimension product was significantly greater. For malachite sulfurization flotation, the impact of ammonium phosphate in promoting sulfurization is weaker than ammonium sulfate. The reason may be that hydrolyzing phosphate consumes a substantial quantity of H+ in the solution, which hastens the formation of the copper-sulfur products, decreasing the adhesion stability of copper-sulfur species on the malachite surface.

Keywords: sulfurization flotation, adsorption characteristics, malachite, hydrophobicity

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

Procedia PDF Downloads 159

Authors: Kristine Vike-Jonas, Susana V. Gonzalez, Olav L. Bakkerud, Karoline S. Gjelstad, Shazia N. Aslam, Øyvind Mikkelsen, Alexandros Asimakopoulos

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P-hydrobenzoic acid esters (parabens), paraben metabolites, and triclocarban (TCC) are a group of synthetic antimicrobials classified as endocrine disrupting chemicals (EDCs) and emerging pollutants. The aim of this study was to investigate the levels of these compounds in sediment near the effluent of a wastewater treatment plant (WWTP) in the Trondheim Fjord, Norway. Paraben, paraben metabolites, and TCC are high volume production chemicals that are found in a range of consumer products, especially pharmaceuticals and personal care products (PCPs). In this study, six parabens (methyl paraben; MeP, ethyl paraben; EtP, propyl paraben; PrP, butyl paraben; BuP, benzyl paraben; BezP, heptyl paraben; HeP), four paraben metabolites (4-hydroxybenzoic acid; 4-HB, 3,4-dihydroxybenzoic acid; 3,4-DHB, methyl protocatechuic acid; OH-MeP, ethyl protocatechuic acid; OH-EtP) and TCC were determined by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in 64 sediment samples from 10 different locations outside Trondheim, Norway. Of these 11 target analytes, four were detected in 40 % or more of the samples. The sum of six parabens (∑Parabens), four paraben metabolites (∑Metabolites) and TCC in sediment ranged from 4.88 to 11.56 (mean 6.81) ng/g, 52.16 to 368.28 (mean 93.89) ng/g and 0.53 to 3.65 (mean 1.50) ng/g dry sediment, respectively. Pearson correlation coefficients indicated that TCC was positively correlated with OH-MeP, but negatively correlated with 4-HB. To the best of the author’s knowledge, this is the first time parabens, paraben metabolites and TCC have been reported in the Trondheim Fjord.

Keywords: parabens, liquid chromatography, sediment, tandem mass spectrometry

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Uyanga Jadamba

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Globalisation of the world economy has necessitated the development and implementation of a comparable and understandable reporting language suitable for use by all reporting entities. The International Accounting Standard Board (IASB) provides an international reporting language that lets all users understand the financial information of their business and potentially allows them to have access to finance at an international level. The study is based on logistic regression analysis to investigate the factors for the adoption of theInternational Financial Reporting Standard for Small and Medium sized Entities (IFRS for SMEs). The study started with a list of 217 countries from World Bank data. Due to the lack of availability of data, the final sample consisted of 136 countries, including 60 countries that have adopted the IFRS for SMEs and 76 countries that have not adopted it yet. As a result, the study included a period from 2010 to 2020 and obtained 1360 observations. The findings confirm that the adoption of the IFRS for SMEs is significantly related to the existence of national reporting standards, law enforcement quality, common law (legal system), and extent of disclosure. It means that the likelihood of adoption of the IFRS for SMEs decreases if the country already has a national reporting standard for SMEs, which suggests that implementation and transitional costs are relatively high in order to change the reporting standards. The result further suggests that the new standard adoption is easier in countries with constructive law enforcement and effective application of laws. The finding also shows that the adoption increases if countries have a common law system which suggests that efficient reportingregulations are more widespread in these countries. Countries with a high extent of disclosing their financial information are more likely to adopt the standard than others. The findings lastly show that the audit qualityand primary education levelhave no significant impact on the adoption.One possible explanation for this could be that accounting professionalsfrom in developing countries lacked complete knowledge of the international reporting standards even though there was a requirement to comply with them. The study contributes to the literature by providing factors that impact the adoption of the IFRS for SMEs. It helps policymakers to better understand and apply the standard to improve the transparency of financial statements. The benefit of adopting the IFRS for SMEs is significant due to the relaxed and tailored reporting requirements for SMEs, reduced burden on professionals to comply with the standard, and provided transparent financial information to gain access to finance.The results of the study are useful toemerging economies where SMEs are dominant in the economy in informing its evaluation of the adoption of the IFRS for SMEs.

Keywords: IFRS for SMEs, international financial reporting standard, adoption, institutional factors

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Authors: P. Makendran, M. Pragadeesh, N. Narash, N. Manikandan, A. Rajasri, V. Sanal Kumar

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The growing severity of government-obligatory emissions legislation has required continuous improvement in catalysts performance and the associated reactor systems. IC engines emit a lot of harmful gases into the atmosphere. These gases are toxic in nature and a catalytic converter is used to convert these toxic gases into less harmful gases. The catalytic converter converts these gases by Oxidation and reduction reaction. Stoichiometric engines usually use the three-way catalyst (TWC) for simultaneously destroying all of the emissions. CO and NO react to form CO2 and N2 over one catalyst, and the remaining CO and HC are oxidized in a subsequent one. Literature review reveals that typically precious metals are used as a catalyst. The actual reactor is composed of a washcoated honeycomb-style substrate, with the catalyst being contained in the washcoat. The main disadvantage of a catalytic converter is that it exerts a back pressure to the exhaust gases while entering into them. The objective of this paper is to optimize the back pressure developed by the catalytic converter through geometric optimization of catalystic converter. This can be achieved by designing a catalyst with a optimum cone angle and a more surface area of the catalyst substrate. Additionally, the arrangement of the pores in the catalyst substrate can be changed. The numerical studies have been carried out using k-omega turbulence model with varying inlet angle of the catalytic converter and the length of the catalyst substrate. We observed that the geometry optimization is a meaningful objective for the lucrative design optimization of a catalytic converter for industrial applications.

Keywords: catalytic converter, emission control, reactor systems, substrate for emission control

Procedia PDF Downloads 891

Authors: Francesca Schiavello

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This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

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Authors: Parker Townes, Prabdeep Panesar, Chunlin Liu, Soo Youn Lee, Dan Devoe, Paul D. Arnold, Jennifer Crosbie, Russell Schachar

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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are impairing childhood neurodevelopmental disorders with problems in executive functions. Executive functions are higher-level mental processes essential for daily functioning and goal attainment. There is genetic and neural overlap between ADHD and ASD. The aim of this meta-analysis was to evaluate if pediatric ASD and ADHD have distinct executive function profiles. This review was completed following Cochrane guidelines. Fifty-eight articles were identified through database searching, followed by a blinded screening in duplicate. A meta-analysis was performed for all task performance metrics evaluated by at least two articles. Forty-five metrics from 24 individual tasks underwent analysis. No differences were found between youth with ASD and ADHD in any domain under direct comparison. However, individuals with ASD and ADHD exhibited deficient attention, flexibility, visuospatial abilities, working memory, processing speed, and response inhibition compared to controls. No deficits in planning were noted in either disorder. Only 11 studies included a group with comorbid ASD+ADHD, making it difficult to determine whether common executive function deficits are a function of comorbidity. Further research is needed to determine if comorbidity accounts for the apparent commonality in executive function between ASD and ADHD.

Keywords: autism spectrum disorder, ADHD, neurocognition, executive function, youth

Procedia PDF Downloads 65