Search results for: extended FIR filter

Authors: Yoshiaki Shikata

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A prioritized processor-sharing (PS) system with a maximum permissible sojourn time (MPST) is proposed. In this PS system, a higher-priority request is allocated a larger service ratio than a lower-priority request. Moreover, each request receiving service is guaranteed the maximum permissible sojourn time determined by each priority class, regardless of its service time. Arriving requests that cannot receive service due to this guarantee are rejected. We further propose a guarantee method for implementing such a system, and discuss performance evaluation procedures for the resulting system. Practical performance measures, such as the relationships between the loss probability or mean sojourn time of each class request and the maximum permissible sojourn time are evaluated via simulation. At the arrival of each class request, its acceptance or rejection is judged using extended sojourn times of all requests receiving service in the server. As the MPST increases, the mean sojourn time increases almost linearly. However, the logarithm of the loss probability decreases almost linearly. Moreover with an MPST, the difference in the mean sojourn time for different MPSTs increases with the traffic rate. Conversely, the difference in the loss probability for different MPSTs decreases as the traffic rate increases.

Keywords: prioritized processor sharing, priority ratio, permissible sojourn time, loss probability, mean sojourn time, simulation

Procedia PDF Downloads 190

Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

Procedia PDF Downloads 138

Authors: Mohamed Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Aziz, Mona Fawzy Al-Daghma

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Helical piles are widely used as axially and laterally loaded deep foundations. Once they are required to resist bearing combined loads (BCLs), as axial compression and lateral thrust, different behaviour is expected, necessitating further investigation. The objective of the present article is to clarify the behaviour of a single helical pile of different shaft rigidity embedded in cohesion-less soil and subjected to simultaneous or successive loading patterns of BCLs. The study was first developed analytically and extended numerically. The numerical analysis was further verified through a laboratory experimental program on a set of helical pile models. The results indicate highly interactive effects of the studied parameters, but it is obviously confirmed that the pile performance increases with both the increase of shaft rigidity and the change of BCLs loading pattern from simultaneous to successive. However, it is noted that the increase of vertical load does not always enhance the lateral capacity but may cause a decrement in lateral capacity, as observed with helical piles of flexible shafts. This study provides insightful information for the design of helical piles in structures loaded by complex sequence of forces, wind turbines, and industrial shafts.

Keywords: helical pile, lateral loads, combined loads, cohesion-less soil, analytical, numerical

Procedia PDF Downloads 62

Authors: Luma Al-Tamimi, Hassan Farhat, Wessam Hasan

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A three-dimensional (3D) hybrid quasi-steady thermal lattice Boltzmann model is developed to couple the effects of surfactant, temperature, interfacial tension, and contact angle. This 3D model is an extended scheme of a previously introduced two-dimensional (2D) hybrid lattice Boltzmann model. The 3D model is used to study the combined multi-physics effects on emulsion systems flowing in rectangular microchannels with and without confinements, where the suspended phase is made of droplets, plugs, or a mixture of both. The simulation results show that emulsion systems with plugs as the suspended phase are more efficient than with droplets, whereas mixed systems that form large plugs through coalescence have even greater efficiency. The 3D contact angle model generates matching results to those of the 2D model, which were validated with experiments. Furthermore, the effects of various confinements on adhering single drop systems are investigated for delineating their influence on the power required for transporting the suspended phase through the channel. It is shown that the deeper the constriction is, the lower the system efficiency. Increasing the surfactant concentration or fluid temperature in a channel with confinement carries a substantial positive effect on oil droplet transportation.

Keywords: lattice Boltzmann method, thermal, contact angle, surfactants, high viscosity ratio, porous media

Procedia PDF Downloads 174

Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

Procedia PDF Downloads 172

Authors: Adriano Trono, Federico Pinto, Diego Turello, Marcelo A. Ceballos

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Numerical modeling of dynamic soil-structure interaction problems requires an adequate representation of the unbounded characteristics of the ground, material non-linearity of soils, and geometrical non-linearities such as large displacements due to rocking of the structure. In order to account for these effects simultaneously, it is often required that the equations of motion are solved in the time domain. However, boundary conditions in conventional finite element codes generally present shortcomings in fully absorbing the energy of outgoing waves. In this sense, the Perfectly Matched Layers (PML) technique allows a satisfactory absorption of inclined body waves, as well as surface waves. However, the PML domain is inherently unstable, meaning that it its instability does not depend upon the discretization considered. One way to stabilize the PML domain is to use multiaxial stretching functions. This development is questionable because some Jacobian terms of the coordinate transformation are not accounted for. For this reason, the resulting absorbing layer element is often referred to as "uncorrected M-PML” in the literature. In this work, the strong formulation of the "corrected M-PML” absorbing layer is proposed using multiaxial stretching functions that incorporate all terms of the coordinate transformation. The results of the stable model are compared with reference solutions obtained from extended domain models.

Keywords: mixed finite elements, multiaxial stretching functions, perfectly matched layer, soil-structure interaction

Procedia PDF Downloads 66

Authors: Marta Błażkiewicz-Mazurek, Adam Konefał

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The project can be divided into three main parts: i. modeling the Cf-252 neutron source and conducting an experiment to verify the correctness of the obtained results, ii. design of the BNCT system infrastructure, iii. analysis of the results from the logical detector. Modeling of the Cf-252 source included designing the shape and size of the source as well as the energy and spatial distribution of emitted neutrons. Two options were considered: a point source and a cylindrical spatial source. The energy distribution corresponded to various spectra taken from specialized literature. Directionally isotropic neutron emission was simulated. The simulation results were compared with experimental values determined using the activation detector method using indium foils and cadmium shields. The relative fluence rate of thermal and resonance neutrons was compared in the chosen places in the vicinity of the source. The second part of the project related to the modeling of the BNCT infrastructure consisted of developing a simulation program taking into account all the essential components of this system. Materials with moderating, absorbing, and backscattering properties of neutrons were adopted into the project. Additionally, a gamma radiation filter was introduced into the beam output system. The analysis of the simulation results obtained using a logical detector located at the beam exit from the BNCT infrastructure included neutron energy and their spatial distribution. Optimization of the system involved changing the size and materials of the system to obtain a suitable collimated beam of thermal neutrons.

Keywords: BNCT, Monte Carlo, neutrons, simulation, modeling

Procedia PDF Downloads 28

Authors: Aderet Pantierer, Shmuel Pantierer, Atif Saeed, Amir Elzawawy

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In recent years, air travel has seen volatile growth. Due to this growth, the maximization of efficiency and space utilization has been a major issue for aircraft manufacturers. Elongation of the wingspan of aircraft has resulted in increased lift; and, thereby, efficiency. However, increasing the wingspan of aircraft has been detrimental to the manufacturing process and has led to airport congestion and required airport reconfiguration to accommodate the extended wingspans of aircraft. This project outlines differing wing configurations of a commercial aircraft and the effects on the aerodynamic loads produced. Multiple wing configurations are analyzed using Finite Element Models. These models are then validated by testing one wing configuration in a wind tunnel under laminar flow and turbulent flow conditions. The wing configurations to be tested include high and low wing aircraft, as well as various combinations of the two, including a unique model hereon referred to as an infinity wing. The infinity wing configuration consists of both a high and low wing, with the two wings connected by a vertical airfoil. This project seeks to determine if a wing configuration consisting of multiple airfoils produces more lift than the standard wing configurations and is able to provide a solution to manufacturing limitations as well as airport congestion. If the analysis confirms the hypothesis, a trade study will be performed to determine if and when an arrangement of multiple wings would be cost-effective.

Keywords: aerodynamics, aircraft design, aircraft efficiency, wing configuration, wing design

Procedia PDF Downloads 262

Authors: Nadia A. Mohamed, Zakaria El-Khayat, Wagdy K. B. Khalil, Mehrez E. El-Naggar

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Drug nephrotoxicity is still a problem for patients who have taken drugs for elongated periods or permanently. Ultrasound-assisted sol−gel method was used to prepare hollow structured poroussilica nanoemulsion loaded with sodium salicylate as a model drug. The work was extended to achieve the target of the current work via investigating the protective role of this nanoemulsion model as anti-inflammatory drug or ginger for its antioxidant effect against cisplatin-induced nephrotoxicity in male albino rats. The results clarify that the nanoemulsion model was synthesized using ultrasonic assisted with small size and well stabilization as proved by TEM and DLS analysis. Additionally, blood urea nitrogen (BUN), Serum creatinine (SC) and Urinary total protein (UTP) were increased, and the level of creatinine clearance (Crcl) was decreased. All those were met with disorders in oxidative stress and downregulation in the expression of the nephrin gene. Also, histopathological changes of the kidney tissue were observed. These changes back to normal by treatment with silica nanoparticles loaded sodium salicylate (Si-Sc-NPs), ginger or both. Conclusions oil/water nanoemulsion of (Si-Sc NPs) and ginger showed a protective and promising preventive strategy against nephrotoxicity due to their antioxidant and anti-inflammatory effects, and that offers a new approach in attenuating drug induced nephrotoxicity.

Keywords: sodium salicylate nanoencapsulation, nephrin mRNA, drug nephrotoxicity, cisplatin, experimental rats

Procedia PDF Downloads 201

Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

Procedia PDF Downloads 73

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

Procedia PDF Downloads 325

Authors: Iyad M. Muslih, Yehya Abdellatif, Sara Qutishat

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Renewable energy and in particular solar photovoltaic energy is emerging as a reasonable power generation source. The intermittent and unpredictable nature of solar energy can represent a serious challenge to the utility grids, specifically at relatively high penetration. To minimize the impact of PV power systems on the grid, self-consumption is encouraged. Self-consumption can be improved by matching the PV power generation with the electrical load consumption profile. This study will focus in studying different load profiles and comparing them to typical solar PV power generation at the selected sites with the purpose of analyzing the mismatch in consumption load profile for different users; residential, commercial, and industrial versus the solar photovoltaic output generation. The PV array orientation can be adjusted to reduce the mismatch effects. The orientation shift produces a corresponding shift in the energy production curve. This shift has a little effect on the mismatch for residential loads due to the fact the peak load occurs at night due to lighting loads. This minor gain does not justify the power production loss associated with the orientation shift. The orientation shift for both commercial and industrial cases lead to valuable decrease in the mismatch effects. Such a design is worth considering for reducing grid penetration. Furthermore, the proposed orientation shift yielded better results during the summer time due to the extended daylight hours.

Keywords: grid impact, HOMER, power mismatch, solar PV energy

Procedia PDF Downloads 603

Authors: R. F. Vieira, S. A. Figueiredo, O. M. Freitas, V. F. Domingues, C. Delerue-Matos

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The presence of sulphur compounds like hydrogen sulphide and mercaptans is one of the reasons for waste-water treatment and waste management being associated with odour emissions. In this context having a quantifying method for these compounds helps in the optimization of treatment with the goal of their elimination, namely biofiltration processes. The aim of this study was the development of a method for quantification of odorous gases in waste treatment plants air samples. A method based on head space solid phase microextraction (HS-SPME) coupled with gas chromatography - flame photometric detector (GC-FPD) was used to analyse H2S and Metil Mercaptan (MM). The extraction was carried out with a 75-μm Carboxen-polydimethylsiloxane fiber coating at 22 ºC for 20 min, and analysed by a GC 2010 Plus A from Shimadzu with a sulphur filter detector: splitless mode (0.3 min), the column temperature program was from 60 ºC, increased by 15 ºC/min to 100 ºC (2 min). The injector temperature was held at 250 ºC, and the detector at 260 ºC. For calibration curve a gas diluter equipment (digital Hovagas G2 - Multi Component Gas Mixer) was used to do the standards. This unit had two input connections, one for a stream of the dilute gas and another for a stream of nitrogen and an output connected to a glass bulb. A 40 ppm H2S and a 50 ppm MM cylinders were used. The equipment was programmed to the selected concentration, and it automatically carried out the dilution to the glass bulb. The mixture was left flowing through the glass bulb for 5 min and then the extremities were closed. This method allowed the calibration between 1-20 ppm for H2S and 0.02-0.1 ppm and 1-3.5 ppm for MM. Several quantifications of air samples from inlet and outlet of a biofilter operating in a waste management facility in the north of Portugal allowed the evaluation the biofilters performance.

Keywords: biofiltration, hydrogen sulphide, mercaptans, quantification

Procedia PDF Downloads 474

Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

Procedia PDF Downloads 194

Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

Procedia PDF Downloads 266

Authors: R. M. Noah, N. M. Nasir, M. R. Jais, M. S. S. Wahab, M. H. Abdullah, A. S. S. Raj

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Infectious diseases are getting more difficult to treat due to the resistant strains of bacteria. Current generations of antibiotics are most likely ineffective against multi-drug resistant strains bacteria. Thus, there is an urgent need in search of natural antibiotics in particular from medicinal plants. One of the common medicinal plants, Melaleuca cajuputi, has been reported to possess antibacterial properties. The study was conducted to evaluate and justify the presence of antibacterial activity of Melaleuca cajuputi essential oil (EO) against the multi-drug resistant bacteria. Clinical isolates obtained from the teaching hospital were re-assessed to confirm the exact identity of the bacteria to be tested, namely methicillin-resistant staphylococcus aureus (MRSA), carbapenem-resistant enterobacteriaceae (CRE), and extended-spectrum beta-lactamases producer (ESBLs). A well diffusion method was done to observe the inhibition zones of the essential oil against the bacteria. Minimum inhibitory concentration (MIC) was determined using the microdilution method in 96-well flat microplate. The absorbance was measured using a microplate reader. Minimum bactericidal concentration (MBC) was performed using the agar medium method. The zones of inhibition produced by the EO against MRSA, CRE, and ESBL were comparable to that of generic antibiotics used, gentamicin and augmentin. The MIC and MBC results highlighted the antimicrobial efficacy of the EO. The outcome of this study indicated that the EO of Melaleuca cajuputi had antibacterial activity on the multi-drug resistant bacteria. This finding was eventually substantiated by electron microscopy work.

Keywords: melaleuca cajuputi, antibacterial, resistant bacteria, essential oil

Procedia PDF Downloads 120

Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

Procedia PDF Downloads 467

Authors: Walaa Obaidallah Alqarafi, Wafaa Mohammed Fakieh, Alaa Abdallah Altassan

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Algebraic graph theory is defined as a bridge between algebraic structures and graphs. It has several uses in many fields, including chemistry, physics, and computer science. The prime graph is a type of graph associated with a ring R, where the vertex set is the whole ring R, and two vertices x and y are adjacent if either xRy=0 or yRx=0. However, the investigation of the prime graph over rings remains relatively limited. The behavior of this graph in extended rings, like R[x] and R[[x]], where R is a non-commutative ring, deserves more attention because of the wider applicability in algebra and other mathematical fields. To study the prime graphs over polynomials and power series rings, we used a combination of ring-theoretic and graph-theoretic techniques. This paper focuses on two invariants: the diameter and the girth of these graphs. Furthermore, the work discusses how the graph structures change when passing from R to R[x] and R[[x]]. In our study, we found that the set of strong zero-divisors of ring R represents the set of vertices in prime graphs. Based on this discovery, we redefined the vertices of prime graphs using the definition of strong zero divisors. Additionally, our results show that although the prime graphs of R[x] and R[[x]] are comparable to the graph of R, they have different combinatorial characteristics since these extensions contain new strong zero-divisors. In particular, we find conditions in which the diameter and girth of the graphs, as they expand from R to R[x] and R[[x]], do not change or do change. In conclusion, this study shows how extending a non-commutative ring R to R[x] and R[[x]] affects the structure of their prime graphs, particularly in terms of diameter and girth. These findings enhance the understanding of the relationship between ring extensions and graph properties.

Keywords: prime graph, diameter, girth, polynomial ring, power series ring

Procedia PDF Downloads 17

Authors: Hwasuk Jung, Seoi Lee, Dongchoon Ryou, Pyungjong Yoo, Seokmo Lee

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The Nakdong River being used as drinking water sources for Pusan metropolitan city has the vulnerability of water management due to the fact that industrial areas are located in the upper Nakdong River. Most citizens of Busan think that the water quality of Nakdong River is not good, so they boil or use home filter to drink tap water, which causes unnecessary individual costs to Busan citizens. We need to diversify water intake to reduce the cost and to change the weak water source. Under this background, this study was carried out for the environmental accounting of Namgang dam water treatment system compared to Nakdong River water treatment system by using emergy analysis method to help making reasonable decision. Emergy analysis method evaluates quantitatively both natural environment and human economic activities as an equal unit of measure. The emergy transformity of Namgang dam’s water was 1.16 times larger than that of Nakdong River’s water. Namgang Dam’s water shows larger emergy transformity than that of Nakdong River’s water due to its good water quality. The emergy used in making 1 m3 tap water from Namgang dam water treatment system was 1.26 times larger than that of Nakdong River water treatment system. Namgang dam water treatment system shows larger emergy input than that of Nakdong river water treatment system due to its construction cost of new pipeline for intaking Namgang daw water. If the Won used in making 1 m3 tap water from Nakdong river water treatment system is 1, Namgang dam water treatment system used 1.66. If the Em-won used in making 1 m3 tap water from Nakdong river water treatment system is 1, Namgang dam water treatment system used 1.26. The cost-benefit ratio of Em-won was smaller than that of Won. When we use emergy analysis, which considers the benefit of a natural environment such as good water quality of Namgang dam, Namgang dam water treatment system could be a good alternative for diversifying intake source.

Keywords: emergy, emergy transformity, Em-won, water treatment system

Procedia PDF Downloads 302

Authors: Ali Saghaei, Negar Ghotbeddin, Ebrahim Rajabzadeh Ghatrami, Milad Maniat

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The use of herbs as natural additives in fish diets are used to enhance the efficiency and safety systems. The use of herbs, garlic, due to the structure and composition of it has beneficial role in human nutrition and animal nutrition. This study was conducted evaluate the effect different levels of garlic (Allium sativum) powder on the some serum biochemical parameters of Oscar fish (Astronotus ocellatus). Fish were divided into four groups fed on diets containing garlic in different levels; 5 g kg˗1, 10 g kg-1, 20 g kg-1, 30 g kg-1 diet and the control group diet was without garlic. A total number of 300 fish was used and Triplicate groups of Oscar fish with initial weight of 12.43±0.24 g were hand-fed to visual satiation at three meals per day. The experiment extended for two months. Total Protein (TP), Albumin (ALB), Globulin (GLB) and Albumin/Globulin (A/G) ratio, were determined. Based on the results, no significant differences were seen among treatments and control groups during the experimental period for TP, ALB, GLB, and A/G ratio (p > 0.05). Although, the highest amount of serum total protein and globulin levels were observed in diet containing 10 g kg-1 of garlic. Also, the highest value of albumin and A/G were observed in diet containing 20 g kg-1 of garlic, but there were no significant difference with other treatments. The results of this study show that addition of garlic Allium sativum to fish diet can improve fish health.

Keywords: garlic (Allium sativum), serum, Oscar fish (Astronotus ocellatus), iran

Procedia PDF Downloads 480

Authors: Mehrnaz Farzingohar, Mehran Yasemi, Ahmad Savari

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The oil products are imported and exported via Rajaee’s tanker terminal. Within loading and discharging in several cases the oil is released into the berths and made oil spills. The spills are distributed within short time and seriously affected Rajaee port’s environment and even extended areas. The trajectory and fate of oil spills investigated by modeling and parted by three risk levels base on the modeling results. First GNOME (General NOAA Operational Modeling Environment) applied to trajectory the liquid oil. Second, ALOHA (Areal Location Of Hazardous Atmosphere) air quality model, is integrated to predict the oil evaporation path within the air. Base on the identified zones the high risk areas are signed by colored dots which their densities calculated and clarified on a map which displayed the harm places. Wind and water circulation moved the pollution to the East of Rajaee Port that accumulated about 12 km of coastline. Approximately 20 km of north east of Qeshm Island shore is covered by the three levels of risky areas. Since the main wind direction is SSW the pollution pushed to the east and the highest risk zones formed on the crests edges hence the low risk appeared on the concavities. This assessment help the management and emergency systems to monitor the exposure places base on the priority factors and find the best approaches to protect the environment.

Keywords: oil spill, modeling, pollution, risk assessment

Procedia PDF Downloads 385

Authors: Evy Latifah, Eli Korlina, Hanik Anggraeni, Kuntoro Boga, Joko Mariyono

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During the rainy season, the tomato plants are vulnerable to various diseases. A disease that attacks the leaves of tomato plants (foliar diseases) such as late blight (Phytophtora infestans) and spotting bacteria (bacterial spot / Xanthomonas sp.) In addition, there is a disease that attacks the roots such as fusarium and bacterial wilt. If not immediately anticipated, it will decrease the quality and quantity of crop yields. In fact, it can lead to crop failure. The aim of this research is to know the production of tomato grafting by using Timoty and CLN 3024 tomatoes at rain shelter during rainy season in lowland. Data were analyzed using analysis of variance and tested further by Least Significant Difference (LSD) level of 5 %. The parameters measured were plant height (cm), stem diameter (cm), number of fruit space, canopy extended, number of branches, number of productive branches, and the number of stem segments. The results show at the beginning of growth until the end of the treatment without grafting with relative rain shelter displays the highest plant height. This was followed by extensive crop canopy. For tomato grafting and non-grafting using rain shelter able to produce the number of branches and number of productive branches at most. While at the end of the growth in the number of productive branches generated as much. Highest production of tomatoes produced by tomato dig rafting to use the shelter.

Keywords: field trail, wet and dry season, production, diseases, rain shelter

Procedia PDF Downloads 227

Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 131

Authors: Muhammad Saad Aslam

Abstract:

In 2021, our organization has launched our proprietary mobile App i.e. Farm Intelligence platform, an industrial-first precision agriculture solution, to Pakistan. It was piloted at 47 locations (spanning around 1,200 hectares of land), addressing growers’ pain points by bringing the benefits of precision agriculture to their doorsteps. This year, we have extended its reach by more than 10 times (nearly 130,000 hectares of land) in almost 600 locations across the country. The project team selected highly infested areas to set up traps, which then enabled the sales team to initiate evidence-based conversations with the grower community about preventive crop protection products that includes pesticides and insecticides. Mega farmer meeting field visits and demonstrations plots coupled with extensive marketing activities, were setup to include farmer community. With the help of App real-time pest monitoring (using heat maps and infestation prediction through predictive analytics) we have equipped our growers with on spot insights that will help them optimize pesticide applications. Heat maps allow growers to identify infestation hot spots to fine-tune pesticide delivery, while predictive analytics enable preventive application of pesticides before the situation escalates. Ultimately, they empower growers to keep their crops safe for a healthy harvest.

Keywords: precision pest management, precision agriculture, real time pest tracking, pest forecasting

Procedia PDF Downloads 88

Authors: Ayesha Aihetasham, Najma Arshad, Sobia Khan

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Damage causes by subterranean termites are of major concern today. Termites majorly treated with pesticides resulted in several problems related to health and environment. For this reason, plant-derived natural products specifically essential oils have been evaluated in order to control termites. The aim of the present study was to investigate the antitermitic potential of six essential oils on Heterotermes indicola subterranean termite. No-choice bioassay was used to assess the termiticidal action of essential oils. Further, gut from each set of treated termite group was extracted and analyzed for reduction in number of protozoa and bacteria by protozoal count method using haemocytometer and viable bacterial plate count (dilution method) respectively. In no-choice bioassay it was found that Foeniculum vulgare oil causes high degree of mortality 90 % average mortality at 10 mg oil concentration (10mg/0.42g weight of filter paper). Least mortality appeared to be due to Citrus sinensis oil (43.33 % average mortality at 10 mg/0.42g). The highest activity verified to be of Foeniculum vulgare followed by Eruca sativa, Trigonella foenum-graecum, Peganum harmala, Syzygium cumini and Citrus sinensis. The essential oil which caused maximum reduction in number of protozoa was P. harmala followed by T. foenum-graecum and E. sativa. In case of bacterial count E. sativa oil indicated maximum decrease in bacterial number (6.4×10⁹ CFU/ml). It is concluded that F. vulgare, E. sativa and P. harmala essential oils are highly effective against H. indicola termite and its gut microflora.

Keywords: bacterial count, essential oils, Heterotermes indicola, protozoal count

Procedia PDF Downloads 243

Authors: Sylvia Graczka

Abstract:

Waste related environmental problems are not only exploding but are also spotlighted for capacity shortages in recycling, as China announced its ban on waste imports. According to the waste hierarchy, prevention is the primary solution for waste, and also the cheapest. Waste related environmental pollution as externality puts an ever-growing burden on communities bearing the social costs. Economic policies often claim to be pro-environment, this often appears only theoretically, or at the level of principles. There are few concrete occurrences of tools in economic policies, such as green taxes, that are truly effective in stimulating the shift towards waste reduction. The paper presents theoretical economic policy tools based on literature review, and case studies on applied economic policy tools by analyzing policy papers, strategies in force, in line with ‘polluter pays’ and ‘extended producer responsibility’ principles. The study also emphasizes the differences between the broader notion of waste reduction and that of waste minimization, parallel to the difference between resource efficiency and resource savings. It also puts the issue in the context of neoclassical environmental economics and ecological economics, to present alternatives in approach. The research concludes in identifying effective economic policy tools that support the reduction of material use, and the prevention of waste. Consumer and producer awareness of waste problems and consciousness related to their choices are inevitable to make economic policy tools work effectively.

Keywords: economic policy, producer responsibility, resource efficiency, waste prevention

Procedia PDF Downloads 149

Authors: Vedant Janapaty

Abstract:

Estuaries are wetlands where fresh water from streams mixes with salt water from the sea. Also known as “kidneys of our planet”- they are extremely productive environments that filter pollutants, absorb floods from sea level rise, and shelter a unique ecosystem. However, eutrophication and loss of native species are ailing our wetlands. There is a lack of uniform data collection and sparse research on correlations between satellite data and in situ measurements. Remote sensing (RS) has shown great promise in environmental monitoring. This project attempts to use satellite data and correlate metrics with in situ observations collected at five estuaries. Images for satellite data were processed to calculate 7 bands (SIs) using Python. Average SI values were calculated per month for 23 years. Publicly available data from 6 sites at ELK was used to obtain 10 parameters (OPs). Average OP values were calculated per month for 23 years. Linear correlations between the 7 SIs and 10 OPs were made and found to be inadequate (correlation = 1 to 64%). Fourier transform analysis on 7 SIs was performed. Dominant frequencies and amplitudes were extracted for 7 SIs, and a machine learning(ML) model was trained, validated, and tested for 10 OPs. Better correlations were observed between SIs and OPs, with certain time delays (0, 3, 4, 6 month delay), and ML was again performed. The OPs saw improved R² values in the range of 0.2 to 0.93. This approach can be used to get periodic analyses of overall wetland health with satellite indices. It proves that remote sensing can be used to develop correlations with critical parameters that measure eutrophication in situ data and can be used by practitioners to easily monitor wetland health.

Keywords: estuary, remote sensing, machine learning, Fourier transform

Procedia PDF Downloads 102

Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

Procedia PDF Downloads 41

Authors: Mebarek Boukelkoul, Abdelhalim Haroun

Abstract:

By means of the first principle calculation, we have investigated the structural, magnetic and magneto-optical properties of the ultra-thin films of Fen/Cu(001) with (n=1, 2, 3). We adopted a relativistic approach using DFT theorem with local spin density approximation (LSDA). The electronic structure is performed within the framework of the Spin-Polarized Relativistic (SPR) Linear Muffin-Tin Orbitals (LMTO) with the Atomic Sphere Approximation (ASA) method. During the variational principle, the crystal wave function is expressed as a linear combination of the Bloch sums of the so-called relativistic muffin-tin orbitals centered on the atomic sites. The crystalline structure is calculated after an atomic relaxation process using the optimization of the total energy with respect to the atomic interplane distance. A body-centered tetragonal (BCT) pseudomorphic crystalline structure with a tetragonality ratio c/a larger than unity is found. The magnetic behaviour is characterized by an enhanced magnetic moment and a ferromagnetic interplane coupling. The polar magneto-optical Kerr effect spectra are given over a photon energy range extended to 15eV and the microscopic origin of the most interesting features are interpreted by interband transitions. Unlike thin layers, the anisotropy in the ultra-thin films is characterized by a perpendicular magnetization which is perpendicular to the film plane.

Keywords: ultrathin films, magnetism, magneto-optics, pseudomorphic structure

Procedia PDF Downloads 334

Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

Procedia PDF Downloads 296