Search results for: slice thickness accuracy

Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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Authors: Jyh-Ping Chen, Chia-Lin Sheu

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In this study, we propose to use electrospinning to fabricate porous nanofibrous membranes as postsurgical anti-adhesion barriers and to improve the properties of current post-surgical anti-adhesion products. We propose to combine FDA-approved biomaterials with anti-adhesion properties, polycaprolactone (PCL), polyethylene glycol (PEG), hyaluronic acid (HA) with silver nanoparticles (Ag) and ibuprofen (IBU), to produce anti-adhesion barrier nanofibrous membranes. For this purpose, PEG/PCL/Ag/HA/IBU core-shell nanofibers were prepared. The shell layer contains PEG + PCL to provide mechanical supports and Ag was added to the outer PEG-PCL shell layer during electrospinning to endow the nanofibrous membrane with anti-bacterial properties. The core contains HA to exert anti-adhesion and IBU to exert anti-inflammation effects, respectively. The nanofibrous structure of the membranes can reduce cell penetration while allowing nutrient and waste transports to prevent postsurgical adhesion. Nanofibers with different core/shell thickness ratio were prepared. The nanofibrous membranes were first characterized for their physico-chemical properties in detail, followed by in vitro cell culture studies for cell attachment and proliferation. The HA released from the core region showed extended release up to 21 days for prolonged anti-adhesion effects. The attachment of adhesion-forming fibroblasts is reduced using the nanofibrous membrane from DNA assays and confocal microscopic observation of adhesion protein vinculin expression. The Ag released from the shell showed burst release to prevent E Coli and S. aureus infection immediately and prevent bacterial resistance to Ag. Minimum cytotoxicity was observed from Ag and IBU when fibroblasts were culture with the extraction medium of the nanofibrous membranes. The peritendinous anti-adhesion model in rabbits and the peritoneal anti-adhesion model in rats were used to test the efficacy of the anti-adhesion barriers as determined by gross observation, histology, and biomechanical tests. Within all membranes, the PEG/PCL/Ag/HA/IBU core-shell nanofibers showed the best reduction in cell attachment and proliferation when tested with fibroblasts in vitro. The PEG/PCL/Ag/HA/IBU nanofibrous membranes also showed significant improvement in preventing both peritendinous and peritoneal adhesions when compared with other groups and a commercial adhesion barrier film.

Keywords: anti-adhesion, electrospinning, hyaluronic acid, ibuprofen, nanofibers

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Authors: Sankalp Devanand, Prateek Agasimani, Shamith V. S., Rohith Neeraje

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Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English-to-Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches, including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity, etc.

Keywords: machine translation, English to Sanskrit, natural language processing, word meaning retrieval, fastText embeddings

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Mohammad Ali Farrokhpour

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In the current decade and sustainable transportation systems, scooter sharing has attracted widespread attention as an environmentally-friendly means of public transportation which can help develop public transportation. The combination of scooters and subway in the area of sustainable transportation systems can provide a great many opportunities for developing access to public transportation. Of the challenges which have arisen and initiated discussions of interest about the implementation of a scooter-subway system to replace personal vehicles is the issue of routing in the aforementioned system. This has been chosen as the main subject of the present paper. Thus, the present paper provides an account for routing in this system. Because the issue of routing includes multiple factors such as time, costs, traffic, green spaces, etc., the above-mentioned problem is considered to be a multi-objective NP-hard optimization problem. For this purpose, the hybrid optimization approach of PSO-GA has been put forward in the present paper for the provided answers to be of higher accuracy and validity than those of normal optimization methods. The results obtained from modeling and problem solving for the case study in the MATLAB software are indicative of the efficiency and desirability of the model and the proposed approach for solving the model

Keywords: route planning, scooter sharing, public transportation, sharing system

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Authors: Abdul Hakim Chikho

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Most international codes allow the use of an equivalent lateral load method for designing practical buildings to withstand earthquake actions. This method requires calculating an approximation to the fundamental mode period of vibrations of these buildings. Several empirical equations have been suggested to calculate approximations to the fundamental periods of different types of structures. Most of these equations are knowing to provide an only crude approximation to the required fundamental periods and repeating the calculation utilizing a more accurate formula is usually required. In this paper, a new formula to calculate a satisfactory approximation of the fundamental period of a practical building is proposed. This formula takes into account the mass and the stiffness of the building therefore, it is more logical than the conventional empirical equations. In order to verify the accuracy of the proposed formula, several examples have been solved. In these examples, calculating the fundamental mode periods of several farmed buildings utilizing the proposed formula and the conventional empirical equations has been accomplished. Comparing the obtained results with those obtained from a dynamic computer has shown that the proposed formula provides a more accurate estimation of the fundamental periods of practical buildings. Since the proposed method is still simple to use and requires only a minimum computing effort, it is believed to be ideally suited for design purposes.

Keywords: earthquake, fundamental mode period, design, building

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Authors: N. F. Hanna, A. M. Haridy

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One of the main drawbacks of the Modal Pushover Analysis (MPA) is the need to perform nonlinear time-history analysis, which complicates the analysis method and time. A simplified version of the MPA has been proposed based on the concept of the inelastic deformation ratio. Furthermore, the effect of the higher modes of vibration is considered by assuming linearly-elastic responses, which enables the use of standard elastic response spectrum analysis. In this thesis, the simplified MPA (SMPA) method is applied to determine the target global drift and the inter-story drifts of steel frame building. The effect of the higher vibration modes is considered within the framework of the SMPA. A comprehensive survey about the inelastic deformation ratio is presented. After that, a suitable expression from literature is selected for the inelastic deformation ratio and then implemented in the SMPA. The estimated seismic demands using the SMPA, such as target drift, base shear, and the inter-story drifts, are compared with the seismic responses determined by applying the standard MPA. The accuracy of the estimated seismic demands is validated by comparing with the results obtained by the nonlinear time-history analysis using real earthquake records.

Keywords: modal analysis, pushover analysis, seismic performance, target displacement

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Authors: M. R. Aher, R. B. Laware, G. S. Asane, B. S. Kuchekar

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Objective: Studies have shown that a new combination therapy with Artemisinin derivatives and curcumin is unique, with potential advantages over known ACTs. In present study an attempt was made to prepare microparticulate drug delivery system of Curcumin-Zn complex and evaluate it in combination with artemether for antimalarial activity. Material and method: Curcumin Zn complex was prepared and encapsulated using sodium alginate. Microparticles thus obtained are further coated with various enteric polymers at different coating thickness to control the release. Microparticles are evaluated for encapsulation efficiency, drug loading and in vitro drug release. Roentgenographic Studies was conducted in rabbits with BaSO 4 tagged formulation. Optimized formulation was screened for antimalarial activity using P. berghei-infected mice survival test and % paracetemia inhibition, alone (three oral dose of 5mg/day) and in combination with arthemether (i.p. 500, 1000 and 1500µg). Curcumin-Zn(II) was estimated in serum after oral administration to rats by using spectroflurometry. Result: Microparticles coated with Cellulose acetate phthalate showed most satisfactory and controlled release with 479 min time for 60% drug release. X-ray images taken at different time intervals confirmed the retention of formulation in GI tract. Estimation of curcumin in serum by spectroflurometry showed that drug concentration is maintained in the blood for longer time with tmax of 6 hours. The survival time (40 days post treatment) of mice infected with P. berghei was compared to survival after treatment with either Curcumin-Zn(II) microparticles artemether combination, curcumin-Zn complex and artemether. Oral administration of Curcumin-Zn(II)-artemether prolonged the survival of P.berghei-infected mice. All the mice treated with Curcumin-Zn(II) microparticles (5mg/day) artemether (1000µg) survived for more than 40 days and recovered with no detectable parasitemia. Administration of Curcumin-Zn(II) artemether combination reduced the parasitemia in mice by more than 90% compared to that in control mice for the first 3 days after treatment. Conclusion: Antimalarial activity of the curcumin Zn-artemether combination was more pronounced than mono therapy. A single dose of 1000µg of artemether in curcumin-Zn combination gives complete protection in P. berghei-infected mice. This may reduce the chances of drug resistance in malaria management.

Keywords: formulation, microparticulate drug delivery, antimalarial, pharmaceutics

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: A.D. Susanti, W. B. Sediawan, S.K. Wirawan, Budhijanto, Ritmaleni

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Oryzanol content in rice bran oil (RBO) naturally has high antioxidant activity. Its reviewed has several health properties and high interested in pharmacy, cosmetics, and nutrition’s. Because of the low concentration of oryzanol in crude RBO (0.9-2.9%) then its need to be further processed for practical usage, such as via adsorption process. In this study, investigation and adjustment of adsorption equilibrium models were conducted through the kinetic data approachments. Mathematical modeling on kinetics of batch adsorption of oryzanol separation from RBO has been set-up and then applied for equilibrium results. The size of adsorbent particles used in this case are usually relatively small then the concentration in the adsorbent is assumed to be not different. Hence, the adsorption rate is controlled by the rate of oryzanol mass transfer from the bulk fluid of RBO to the surface of silica gel. In this approachments, the rate of mass transfer is assumed to be proportional to the concentration deviation from the equilibrium state. The equilibrium models applied were Langmuir, coefficient distribution, and Freundlich with the values of the parameters obtained from equilibrium results. It turned out that the models set-up can quantitatively describe the experimental kinetics data and the adjustment of the values of equilibrium isotherm parameters significantly improves the accuracy of the model. And then the value of mass transfer coefficient per unit adsorbent mass (kca) is obtained by curve fitting.

Keywords: adsorption equilibrium, adsorption kinetics, oryzanol, rice bran oil

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Authors: Kossigan Bernard Dedey, David Grenier, Tiphaine Lucas

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Bread dough is often described as a dispersion of gas cells in a continuous gluten/starch matrix. The final bread crumb structure is strongly related to gas cell walls (GCWs) rupture during baking. At the end of proofing and during baking, part of the thinnest GCWs between expanding gas cells is reduced to a gluten film of about the size of a starch granule. When such size is reached gluten and starch granules must be considered as interacting phases in order to account for heterogeneities and appropriately describe GCW rupture. Among experimental investigations carried out to assess GCW rupture, no experimental work was performed to observe the GCW rupture in the baking conditions at GCW scale. In addition, attempts to numerically understand GCW rupture are usually not performed at the GCW scale and often considered GCWs as continuous. The most relevant paper that accounted for heterogeneities dealt with the gluten/starch interactions and their impact on the mechanical behavior of dough film. However, stress concentration in GCW was not discussed. In this study, both experimental and numerical approaches were used to better understand GCW rupture in bread dough during baking. Experimentally, a macro-scope placed in front of a two-chamber device was used to observe the rupture of a real GCW of 200 micrometers in thickness. Special attention was paid in order to mimic baking conditions as far as possible (temperature, gas pressure and moisture). Various differences in pressure between both sides of GCW were applied and different modes of fracture initiation and propagation in GCWs were observed. Numerically, the impact of gluten/starch interactions (cohesion or non-cohesion) and rheological moduli ratio on the mechanical behavior of GCW under unidirectional extension was assessed in 2D/3D. A non-linear viscoelastic and hyperelastic approach was performed to match the finite strain involved in GCW during baking. Stress concentration within GCW was identified. Simulated stresses concentration was discussed at the light of GCW failure observed in the device. The gluten/starch granule interactions and rheological modulus ratio were found to have a great effect on the amount of stress possibly reached in the GCW.

Keywords: dough, experimental, numerical, rupture

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Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

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Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

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Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: Lorenza Fabiocchi, Marco Mariani, Andrea Lucchini Huspek, Matteo Pozzi, Massimiliano Bestetti, Serena Graziosi, Nora Lecis

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Additive manufacturing of stainless steels is rapidly developing thanks to the ability to achieve complex designs effortlessly. Stainless steel 17-4PH is valued for its high strength and corrosion resistance, however intricate geometries are challenging to obtain due to rapid tool wear when machined. Binder jetting additive manufacturing was used to produce 17–4PH samples and pulsed electron beam surface treatment was investigated to enhance surface properties of components. The aim is to improve the tribological performance compared to the as-sintered condition and the H900 aging process, which optimizes hardness and wear resistance. Printed samples were sintered in a reducing atmosphere and superficially treated with an electron beam by varying the voltage (20 - 25 - 30 kV) and pulse count (20 – 40 pulses). Then, the surface was characterized from a microstructural and mechanical standpoint. Scratch tests were performed, and a reciprocating linear pin-on-disk wear test was conducted at 2 N and 10 Hz. Results showed that the voltage affects the roughness and thickness of the treated layer, whilst the number of pulses influences the hardening of the microstructure and consequently the wear resistance. Treated samples exhibited lower coefficients of friction compared to as-printed surfaces, though the values approached those of aged samples after the abrasion of the melted layer, indicating a deeper heat-affected zone formation. Different amounts of residual stress in the heat effected zone were individuated through the scratch tests. Still, the friction remained lower than that of as-printed specimens. This study demonstrates that optimizing electron beam parameters is vital for achieving surface performance comparable to bulk aging treatments, with significant implications for long-term wear resistance.

Keywords: low energy high current pulsed electron beam, tribology, binder jetting 3D printing, 17-4PH stainless steel

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Authors: Benny Benyamin Nasution, Rahmat Widia Sembiring, Abdul Rahman Dalimunthe, Nursiah Mustari, Nisfan Bahri, Berta br Ginting, Riadil Akhir Lubis, Rita Tavip Megawati, Indri Dithisari

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The earth coordinate system is an important part of an attempt for earthquake forecasting, such as the one using Single Layer Hierarchical Graph Neuron (SLHGN). However, there are a number of problems that need to be worked out before the coordinate system can be utilized for the forecaster. One example of those is that SLHGN requires that the focused area of an earthquake must be constructed in a grid-like form. In fact, within the current earth coordinate system, the same longitude-difference would produce different distances. This can be observed at the distance on the Equator compared to distance at both poles. To deal with such a problem, a coordinate system has been developed, so that it can be used to support the ongoing earthquake forecasting using SLHGN. Two important issues have been developed in this system: 1) each location is not represented through two-value (longitude and latitude), but only a single value, 2) the conversion of the earth coordinate system to the x-y cartesian system requires no angular formulas, which is therefore fast. The accuracy and the performance have not been measured yet, since earthquake data is difficult to obtain. However, the characteristics of the SLHGN results show a very promising answer.

Keywords: hierarchical graph neuron, multidimensional hierarchical graph neuron, single layer hierarchical graph neuron, natural disaster forecasting, earthquake forecasting, earth coordinate system

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Authors: Arturo S. Daag, Ira Karrel D. L. San Jose, Mike Gabriel G. Pedrosa, Ken Adrian C. Villarias, Rayfred P. Ingeniero, Cyrah Gale H. Rocamora, Margarita P. Dizon, Roland Joseph B. De Leon, Teresito C. Bacolcol

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The province of Leyte consists of various geomorphological landforms: These are: a) landforms of tectonic origin transect large part of the volcanic centers in upper Ormoc area; b) landforms of volcanic origin, several inactive volcanic centers located in Upper Ormoc are transected by Philippine Fault; c) landforms of volcano-denudational and denudational slopes dominates the area where most of the earthquake-induced landslide occurred; and d) Colluvium and alluvial deposits dominate the foot slope of Ormoc and Jaro-Pastrana plain. Earthquake ground acceleration and geotechnical properties of various landforms are crucial for landslide studies. To generate the landslide critical acceleration model of sliding block, various data were considered, these are: geotechnical data (i.e., soil and rock strength parameters), slope, topographic wetness index (TWI), landslide inventory, soil map, geologic maps for the calculation of the factor of safety. Horizontal-to-vertical spectral ratio (HVSR) surveying methods, refraction microtremor (ReMi), and three-component microtremor (3CMT) were conducted to measure site period and surface wave velocity as well as to create a soil thickness model. Critical acceleration model of various geomorphological unit using Remote Sensing, field geotechnical, geophysical, and geospatial data collected from the areas affected by the 06 July 2017 M6.5 Leyte earthquake. Spatial analysis of earthquake-induced landslide from the 06 July 2017, were then performed to assess the relationship between the calculated critical acceleration and peak ground acceleration. The observed trends proved helpful in establishing the role of critical acceleration as a determining factor in the distribution of co-seismic landslides.

Keywords: earthquake-induced landslide, remote sensing, geomorphology, seismic response

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Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

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Authors: Pandega Gama Mahardika, Muhammad Rifki Al Iksan, Datuk Fachrul Razy

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Oil And Gas Tanker Driver is a high-risk jobdesc. drivers drive with sleep circadian rhythm disturbances. Therefore, FAMOUS (Fatigue Management Online Ultimate System) conducted a diagnostic test on the effectiveness and accuracy of the Psychomotor vigilance test (PVT) in the field to capture the fatigue level of Oil And Gas Tanker Driver. Fatigue examination with the PVP method for 3 minutes using the Pertamina FAMOUS system (Fatigue Management Online Ultimate System). The research sample was Oil And Gas Tanker Driver Elnusa petrofin drivers as many as 2205 people. PVT is categorical data that states a driver has a low or high fatigue level. The quality of sleep at home was recorded by filling in a score of 1 = not well, 2 = not well, 3 = well, per person. A total of 1852 (84%) driver had a low fatigue level, while 353 (16%) driver had a high fatigue level. Poor sleep quality was experienced by 68 (79%) driver who had a high fatigue level. Oil And Gas Tanker Driver who slept soundly at home as many as 1804 (87%) had a low fatigue level. The correlation coefficient of sleep quality home and fatigue level is significant because it shows a probability value of 0.00 (p <5%). Fatigue level can be diagnosed through examining sleep quality, using FAMOUS Program for occupational medicine, particularly in the oil and gas sector.

Keywords: psychomotor vigilance test, fatigue, sleep, oil and gas tanker driver drivers, pertamina FAMOUS

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Authors: Dana M. Ragab, Jasim A. Ghaeb

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The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality

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Authors: Pranav Gunhal

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This paper presents an analysis of sentiment on Twitter towards the Karnataka elections held in 2023, utilizing transformer-based models specifically designed for sentiment analysis in Indic languages. Through an innovative data collection approach involving a combination of novel methods of data augmentation, online data preceding the election was analyzed. The study focuses on sentiment classification, effectively distinguishing between positive, negative, and neutral posts while specifically targeting the sentiment regarding the loss of the Bharatiya Janata Party (BJP) or the win of the Indian National Congress (INC). Leveraging high-performing transformer architectures, specifically IndicBERT, coupled with specifically fine-tuned hyperparameters, the AI models employed in this study achieved remarkable accuracy in predicting the INC’s victory in the election. The findings shed new light on the potential of cutting-edge transformer-based models in capturing and analyzing sentiment dynamics within the Indian political landscape. The implications of this research are far-reaching, providing invaluable insights to political parties for informed decision-making and strategic planning in preparation for the forthcoming 2024 Lok Sabha elections in the nation.

Keywords: sentiment analysis, twitter, Karnataka elections, congress, BJP, transformers, Indic languages, AI, novel architectures, IndicBERT, lok sabha elections

Procedia PDF Downloads 87

Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

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Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

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Authors: Alireza Hassanshahi, Xanthe Strudwick, Zlatko Kopecki, Allison J Cowin

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Studies have shown that Flightless (Flii) is elevated in human wounds, including burns, and reducing the level of Flii is a promising approach for improving wound repair and reducing scar formation. The most effective approach has been to neutralise Flii activity using localized, intradermal application of function blocking monoclonal antibodies. However, large surface area burns are difficult to treat by intradermal injection of therapeutics, so the aim of this study was to investigate if a systemic injection of a monoclonal antibody against Flii could improve healing in mice following burn injury. Flii neutralizing antibodies (FnAbs) were labelled with Alxa-Fluor-680 for biodistribution studies and the healing effects of systemically administered FnAbs to mice with burn injuries. A partial thickness, 7% (70mm2) total body surface area scald burn injury was created on the dorsal surface of mice (n=10/group), and 100µL of Alexa-Flour-680-labeled FnAbs were injected into the intraperitoneal cavity (IP) at time of injury. The burns were imaged on days 0, 1, 2, 3, 4, and 7 using IVIS Lumina S5 Imaging System, and healing was assessed macroscopically, histologically, and using immunohistochemistry. Fluorescent radiance efficiency measurements showed that IP injected Alexa-Fluor-680-FnAbs localized at the site of burn injury from day 1, remaining there for the whole 7-day study. The burns treated with FnAbs showed a reduction in macroscopic wound area and an increased rate of epithelialization compared to controls. Immunohistochemistry for NIMP-R14 showed a reduction in the inflammatory infiltrate, while CD31/VEGF staining showed improved angiogenesis post-systemic FnAb treatment. These results suggest that systemically administered FnAbs are active within the burn site and can improve healing outcomes. The clinical application of systemically injected Flii monoclonal antibodies could therefore be a potential approach for promoting the healing of large surface area burns immediately after injury.

Keywords: biodistribution, burn, flightless, systemic, fnAbs

Procedia PDF Downloads 179

Authors: Vitas Valinčius, Rolandas Uscila, Viktorija Grigaitienė, Žydrūnas Kavaliauskas, Romualdas Kėželis

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Determination of integral dynamical and energy characteristics of high-temperature gas flows is a very important task of gas-dynamic for hazardous substances destruction systems. They are also always necessary for the investigation of high-temperature turbulent flow dynamics, heat and mass transfer. It is well known that distribution of dynamical and thermal characteristics of high-temperature flows and jets is strongly related to heat flux variation over an imposed area of heating. As is visible from numerous experiments and theoretical considerations, the fundamental properties of an isothermal jet are well investigated. However, the establishment of regularities in high-temperature conditions meets certain specific behavior comparing with moderate-temperature jets and flows. Their structures have not been thoroughly studied yet, especially in the cases of plasma ambient. It is well known that the distribution of local plasma jet parameters in high temperature and isothermal jets and flows may significantly differ. High temperature axisymmetric air jet generated by atmospheric pressure DC arc plasma torch was investigated employing enthalpy probe 3.8∙10-3 m of diameter. Distribution of velocities and temperatures were established in different cross-sections of the plasma jet outflowing from 42∙10-3 m diameter pipe at the average mean velocity of 700 m∙s-1, and averaged temperature of 4000 K. It has been found that gas heating fractionally influences shape and values of a dimensionless profile of velocity and temperature in the main zone of plasma jet and has a significant influence in the initial zone of the plasma jet. The width of the initial zone of the plasma jet has been found to be lesser than in the case of isothermal flow. The relation between dynamical thickness and turbulent number of Prandtl has been established along jet axis. Experimental results were generalized in dimensionless form. The presence of convective heating shows that heat transfer in a moving high-temperature jet also occurs due to heat transfer by moving particles of the jet. In this case, the intensity of convective heat transfer is proportional to the instantaneous value of the flow velocity at a given point in space. Consequently, the configuration of the temperature field in moving jets and flows essentially depends on the configuration of the velocity field.

Keywords: plasma jet, plasma torch, heat transfer, enthalpy probe, turbulent number of Prandtl

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Authors: Palash Dey, Sudip Talukdar

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In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

Procedia PDF Downloads 253

Authors: Dugeree Otgongerel, Kyong Jin Cho, Yu-Han Kim, Sangmee Ahn Jo

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Excessive activation of glutamate receptor is thought to be involved in retinal ganglion cell (RGC) death after ischemia- reperfusion damage. Glutamate carboxypeptidase II (GCPII) is an enzyme responsible for the synthesis of glutamate. Several studies showed that inhibition of GCPII prevents or reduces cellular damage in brain diseases. Thus, in this study, we examined the expression of GCPII in rat retina and the role of GCPII in acute high IOP ischemia-reperfusion damage of eye by using a GCPII inhibitor, 2-(phosphonomethyl) pentanedioic acid (2-PMPA). Animal model of ischemia-reperfusion was induced by raising the intraocular pressure for 60 min and followed by reperfusion for 3 days. Rats were randomly divided into four groups: either intra-vitreous injection of 2-PMPA (11 or 110 ng per eye) or PBS after ischemia-reperfusion, 2-PMPA treatment without ischemia-reperfusion and sham-operated normal control. GCPII immunoreactivity in normal rat retina was detected weakly in retinal nerve fiber layer (RNFL) and retinal ganglionic cell layer (RGL) and also inner plexiform layer (IPL) and outer plexiform layer (OPL) strongly where are co-stained with an anti-GFAP antibody, suggesting that GCPII is expressed mostly in Muller and astrocytes. Immunostaining with anti-BRN antibody showed that ischemia- reperfusion caused RGC death (31.5 %) and decreased retinal thickness in all layers of damaged retina, but the treatment of 2-PMPA twice at 0 and 48 hour after reperfusion blocked these retinal damages. GCPII level in RNFL layer was enhanced after ischemia-reperfusion but was blocked by PMPA treatment. This result was confirmed by western blot analysis showing that the level of GCPII protein after ischemia- reperfusion increased by 2.2- fold compared to control, but this increase was blocked almost completely by 110 ng PMPA treatment. Interestingly, GFAP immunoreactivity in the retina after ischemia- reperfusion followed by treatment with PMPA showed similar pattern to GCPII, increase after ischemia-reperfusion but reduction to the normal level by PMPA treatment. Our data demonstrate that increase of GCPII protein level after ischemia-reperfusion injury is likely to cause glial activation and/or retinal cell death which are mediated by glutamate, and GCPII inhibitors may be useful in treatment of retinal disorders in which glutamate excitotoxicity is pathogenic.

Keywords: glutamate carboxypepptidase II, glutamate excitotoxicity, ischemia-reperfusion, retinal ganglion cell

Procedia PDF Downloads 344

Authors: S. H. Atef, N. H. Mahmoud, S. Abdrahman, A. Fattoh

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Background: The aim of the study is to assess the diagnostic value of fibrotest and hyaluronic acid in discriminate between insignificant and significant fibrosis. Also, to find out if these parameters could replace liver biopsy which is currently used for selection of chronic hepatitis C patients eligible for antiviral therapy. Study design: This study was conducted on 52 patients with HCV RNA detected by polymerase chain reaction (PCR) who had undergone liver biopsy and attending the internal medicine clinic at Ain Shams University Hospital. Liver fibrosis was evaluated according to the METAVIR scoring system on a scale of F0 to F4. Biochemical markers assessed were: alpha-2 macroglobulin (α2-MG), apolipoprotein A1 (Apo-A1), haptoglobin, gamma-glutamyl transferase (GGT), total bilirubin (TB) and hyaluronic acid (HA). The fibrotest score was computed after adjusting for age and gender. Predictive values and ROC curves were used to assess the accuracy of fibrotest and HA results. Results: For fibrotest, the observed area under curve for the discrimination between minimal or no fibrosis (F0-F1) and significant fibrosis (F2-F4) was 0.6736 for cutoff value 0.19 with sensitivity of 84.2% and specificity of 85.7%. For HA, the sensitivity was 89.5% and specificity was 85.7% and area under curve was 0.540 at the best cutoff value 71 mg/dL. Multi-use of both parameters, HA at 71 mg/dL with fibrotest score at 0.22 give a sensitivity 89.5%, specificity 100 and efficacy 92.3% (AUC 0.895). Conclusion: The use of both fibrotest score and HA could be as alternative to biopsy in most patients with chronic hepaitis C putting in consideration some limitations of the proposed markers in evaluating liver fibrosis.

Keywords: fibrotest, liver fibrosis, HCV RNA, biochemical markers

Procedia PDF Downloads 289

Authors: Amos Olajide Oluyege, Akpanobong Akpan Ekong, Emmanuel Uchechukwu Opara, Sunday Adeniyi Adedutan, Joseph Adeola Fuwape, Olawale John Olukunle

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This study was carried out to evaluate the influence of wood species and wood plastic ratio on the physical and mechanical properties of wood plastic composites (WPCs) produced from polyethylene terephthalate (PET) plastic bottle wastes and sawdust from three hardwood species, namely, Terminalia superba, Gmelina arborea, and Ceiba pentandra. The experimental WPCs were prepared from sawdust particle size classes of ≤ 0.5, 0.5 – 1.0, and 1.0 – 2.0 mm at wood/plastic ratios of 40:60, 50:50 and 60:40 (percentage by weight). The WPCs for each study variable combination were prepared in 3 replicates and laid out in a randomized complete block design (RCBD). The physical properties investigated water absorption (WA), linear expansion (LE) and thickness swelling (TS) while the mechanical properties evaluated were Modulus of Elasticity (MOE) and Modulus of Rupture (MOR). The mean values for WA, LE and TS ranged from 1.07 to 34.04, 0.11 to 1.76 and 0.11 to 4.05 %, respectively. The mean values of the three physical properties increased with decrease in wood plastic ratio. Wood plastic ratio of 40:60 at each particle size class generally resulted in the lowest values while wood plastic ratio of 60:40 had the highest values for each of the three species. For each of the physical properties, T. superba had the least mean values followed by G. arborea, while the highest values were observed C. pentandra. The mean values for MOE and MOR ranged from 458.17 to 1875.67 and 2.64 to 18.39 N/mm2, respectively. The mean values of the two mechanical properties decreased with increase in wood plastic ratio. Wood plastic ratio of 40:60 at each wood particle size class generally had the highest values while wood plastic ratio of 60:40 had the least values for each of the three species. For each of the mechanical properties, C. pentandra had the highest mean values followed by G. arborea, while the least values were observed T. superba. There were improvements in both the physical and mechanical properties due to decrease in sawdust particle size class with the particle size class of ≤ 0.5 mm giving the best result. The results of the Analysis of variance revealed significant (P < 0.05) effects of the three study variables – wood species, sawdust particle size class and wood/plastic ratio on all the physical and mechanical properties of the WPCs. It can be concluded from the results of this study that wood plastic composites from sawdust particle size ≤ 0.5 and PET plastic bottle wastes with acceptable physical and mechanical properties are better produced using 40:60 wood/plastic ratio, and that at this ratio, all the three species are suitable for the production of wood plastic composites.

Keywords: polyethylene terephthalate plastic bottle wastes, wood plastic composite, physical properties, mechanical properties

Procedia PDF Downloads 209

Authors: Nilanjana Chanda, Rangeet Bhattacharyya

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Grover’s search algorithm is the fastest possible quantum mechanical algorithm to search a certain element from an unstructured set of data of N items. The algorithm can determine the desired result in only O(√N) steps. It has been demonstrated theoretically and experimentally on two-qubit systems long ago. In this work, we investigate the fidelity of Grover’s search algorithm by implementing it on an open quantum system. In particular, we study with what accuracy one can estimate that the algorithm would deliver the searched state. In reality, every system has some influence on its environment. We include the environmental effects on the system dynamics by using a recently reported fluctuation-regulated quantum master equation (FRQME). We consider that the environment experiences thermal fluctuations, which leave its signature in the second-order term of the master equation through its appearance as a regulator. The FRQME indicates that in addition to the regular relaxation due to system-environment coupling, the applied drive also causes dissipation in the system dynamics. As a result, the fidelity is found to depend on both the drive-induced dissipative terms and the relaxation terms, and we find that there exists a competition between them, leading to an optimum drive amplitude for which the fidelity becomes maximum. For efficient implementation of the search algorithm, precise knowledge of this optimum drive amplitude is essential.

Keywords: dissipation, fidelity, quantum master equation, relaxation, system-environment coupling

Procedia PDF Downloads 110

Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

Procedia PDF Downloads 137