Search results for: random loading

Authors: Benjamin Okike

Abstract:

There is a need to hide information along the superhighway. Today, information relating to the survival of individuals, organizations, or government agencies is transmitted from one point to another. Adversaries are always on the watch along the superhighway to intercept any information that would enable them to inflict psychological ‘injuries’ to their victims. But with information encryption, this can be prevented completely or at worst reduced to the barest minimum. There is no doubt that so many encryption techniques have been proposed, and some of them are already being implemented. However, adversaries always discover loopholes on them to perpetuate their evil plans. In this work, we propose the enhanced data encryption standard (EDES) that would deploy randomly generated numbers as an encryption method. Each time encryption is to be carried out, a new set of random numbers would be generated, thereby making it almost impossible for cryptanalysts to decrypt any information encrypted with this newly proposed method.

Keywords: encryption, enhanced data encryption, encryption techniques, information security

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Authors: Mohanad Alfach, Amjad Al Helwani

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Post-seismic observations of recent devastating earthquakes have shown that the behavior of the soil-pile-structure shows strong nonlinearity of soil and concrete under intensive seismic loading. Many of pile ruptures recently observed after the strong earthquake due to structural reasons (development of plastic hinges in the piles). The most likely reason for this rupture is the exceeding of maximum bending moment supported by the pile at several points. An analysis of these problems is necessary to take into account the nonlinearity of concrete, the strategy of strengthening the damaged piles and the interaction of these piles with the proposed strengthening by using micropiles. This study aims to investigate the interaction aspects for soil-piles- micropiles-structure using a global approach with a three dimensional finite difference code Flac 3D (Fast lagrangian analysis of continua in 3 dimensions).

Keywords: interaction, piles, micropiles, concrete, seismic, nonlinear, three-dimensional

Procedia PDF Downloads 258

Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: capacity-booking, SPA, monthly production planning, linear programming

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Authors: V. Benedico, C. Anacleto, A. Bearzi, L. Brice, V. Delahaye

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The aim in present paper is to construct an affordable and reliable commodity prices based on a recalculation of its cost through time which allows visualize the potential risks and thus, take more appropriate decisions regarding forecasts. Here attention has been focused on Levy model, more reliable and realistic than classical random Gaussian one as it takes into consideration observed abrupt jumps in case of sudden price variation. In application to Energy Trading sector where it has never been used before, equations corresponding to Levy model have been written for electricity pricing in European market. Parameters have been set in order to predict and simulate the price and its evolution through time to remarkable accuracy. As predicted by Levy model, the results show significant spikes which reach unconventional levels contrary to currently used Brownian model.

Keywords: commodity pricing, Lévy Model, price spikes, electricity market

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Authors: Keping Zuo, Jia Yin Chia, Gideon Praveen Kumar Vijayakumar, Foad Kabinejadian, Fangsen Cui, Pei Ho, Hwa Liang Leo

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Carotid artery is the major vessel supplying blood to the brain. Carotid artery stenosis is one of the three major causes of stroke and the stroke is the fourth leading cause of death and the first leading cause of disability in most developed countries. Although there is an increasing interest in carotid artery stenting for treatment of cervical carotid artery bifurcation therosclerotic disease, currently available bare metal stents cannot provide an adequate protection against the detachment of the plaque fragments over diseased carotid artery, which could result in the formation of micro-emboli and subsequent stroke. Our research group has recently developed a novel preferential covered-stent for carotid artery aims to prevent friable fragments of atherosclerotic plaques from flowing into the cerebral circulation, and yet retaining the ability to preserve the flow of the external carotid artery. The preliminary animal studies have demonstrated the potential of this novel covered-stent design for the treatment of carotid therosclerotic stenosis. The purpose of this study is to evaluate the biomechanical property of PU membrane of different concentration configurations in order to refine the stent coating technique and enhance the clinical performance of our novel carotid covered stent. Results from this study also provide necessary material property information crucial for accurate simulation analysis for our stents. Method: Medical grade Polyurethane (ChronoFlex AR) was used to prepare PU membrane specimens. Different PU membrane configurations were subjected to uniaxial test: 22%, 16%, and 11% PU solution were made by mixing the original solution with proper amount of the Dimethylacetamide (DMAC). The specimens were then immersed in physiological saline solution for 24 hours before test. All specimens were moistened with saline solution before mounting and subsequent uniaxial testing. The specimens were preconditioned by loading the PU membrane sample to a peak stress of 5.5 Mpa for 10 consecutive cycles at a rate of 50 mm/min. The specimens were then stretched to failure at the same loading rate. Result: The results showed that the stress-strain response curves of all PU membrane samples exhibited nonlinear characteristic. For the ultimate failure stress, 22% PU membrane was significantly higher than 16% (p<0.05). In general, our preliminary results showed that lower concentration PU membrane is stiffer than the higher concentration one. From the perspective of mechanical properties, 22% PU membrane is a better choice for the covered stent. Interestingly, the hyperelastic Ogden model is able to accurately capture the nonlinear, isotropic stress-strain behavior of PU membrane with R2 of 0.9977 ± 0.00172. This result will be useful for future biomechanical analysis of our stent designs and will play an important role for computational modeling of our covered stent fatigue study.

Keywords: carotid artery, covered stent, nonlinear, hyperelastic, stress, strain

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Authors: Anam Noshaba, Mahr Muhammad Saeed Akhtar

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The aim of this study was to find out the relationship between quality education and organizational culture. The population of this study was all the teachers of Public Degree Colleges located in Punjab. A sample of 400 teachers was selected by using a simple random sampling technique. Quality Education Assessment Questionnaire (QEAQ) and Organizational Culture Assessment Instrument (OCAI) were used for data collection. Out of all, 90% of teachers responded. Findings showed that quality education and organizational culture are positively correlated. Results indicated that there is no difference in quality education and organizational culture by demographic variables of teachers. Future research is needed to study the viewpoint of other stakeholders of education regarding quality education and organizational culture.

Keywords: quality education, minimum quality standards, organizational culture, college level

Procedia PDF Downloads 138

Authors: Omid Naeemifar, Ibrahim Naeimifar, Roza Rahbari

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It has been shown that a certain collapse surface may be defined for loose sands in the three dimensional space in which the sample sand experiences collapse and instability leading to an unsteady and strain-softening behaviour. The unsteady state due to collapse surface may lead to such phenomena in the sand as liquefaction and flow behaviour during undrained loading. Investigating the existence of the collapse surface in Firoozkooh 161 sand and its different clay mixtures with various plasticities, the present study aims to carry out an in-depth investigation of the effects of clay percent and its plasticity on the clayey sand behaviours. The results obtained indicate that collapse surface characteristics largely depend on fine percent and its plasticity. Interesting findings are also reported in this paper on the effects of fine sand percent and its plasticity on the behavioural characteristics and liquefaction potential of clayey sands.

Keywords: critical state, collapse surface, liquefaction, clayey sand

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Authors: Aboussalih Amira, Zarza Tahar, Fedaoui Kamel, Baroura Lazhar, Hammoudi Salah

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316 L steel is a stainless steel frequently used in orthopedic surgery; in the design of implants (hip, knee, shoulder, ankle, etc.), in dental surgery, cardiology, ophthalmology. Before any use, it is essential to predict the macroscopic phenomenological behavior of the material, and to analyze its response. The behavior of 316 L steel in low cycle fatigue, under uniaxial cyclic loading of tension/compression, producing significant plastic deformations leading to material damage. This investigation allowed us to characterize the behavior of the 316L steel employed in the locking of the compression plates (LCP), of which they are generally used in orthopedics to stabilize the fractured bone parts. And to perceive the phenomenon of Ratcheting leading to the damage of LCP by an excess of plastic deformation under nonsymmetrical alternated imposed constraint in low cycle fatigue.

Keywords: 316L SS, locking compression plate, low cycle fatigue, ratcheting

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Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

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This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

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Authors: Onyekwere Okpara, Kingsley C. Izuogu

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This paper examined newspaper framing of President Buhari's handling of insecurity in Nigeria between January 2016-December 2017. The objectives were to examine the tone and sources of news frames used in reporting President Buhari's handling of insecurity in Nigeria. This paper did a content analysis of three newspapers-Daily Sun, The Nation, and the Leadership. Using a systematic random sampling, the study sampled a total of 732 editions of the selected newspapers and found out that the newspapers used neutral tone and government frame. The study, therefore, recommended that newspapers should improve their investigative reporting efforts.

Keywords: insecurity, newspapers, framing, media

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Authors: Vinai K. Singh

Abstract:

In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Areeg Shermaddo

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Solar updraft power plants (SUPP) provide a great potential for green and environmentally friendly renewable power generation. An up to 1000 m high chimney represents one of the major parts of each SUPP, which consist of the main shell structure and the stiffening rings. Including the nonlinear material behavior in a simulation of the chimney is computationally a demanding task. However, allowing the formation of cracking in concrete leads to a more economical design of the structure. In this work, an FE model of a SUPP is presented incorporating the nonlinear material behavior. The effect of wind loading intensity on the structural response is explored. Furthermore, the influence of the stiffness of the ring beams on the global behavior is as well investigated. The obtained results indicate that the minimum reinforcement is capable of carrying the tensile stresses provided that the ring beams are rather stiff.

Keywords: ABAQUS, nonlinear analysis, ring beams, SUPP

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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Authors: Xiaolai Zhang, Haitao Zhang, Qiwen Sun, Weixin Qian, Weiyong Ying

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High temperature Fischer-Tropsch synthesis process use fixed fluidized bed as a reactor. In order to understand the flow behavior in the fluidized bed better, the research of how the radial velocity affect the entire flow field is necessary. Laser Doppler Velocimetry (LDV) was used to study the radial velocity distribution along the diameter direction of the cross-section of the particle in a fixed fluidized bed. The velocity in the cross-section is fluctuating within a small range. The direction of the speed is a random phenomenon. In addition to r/R is 1, the axial velocity are more than 6 times of the radial velocity, the radial velocity has little impact on the axial velocity in a fixed fluidized bed.

Keywords: Fischer-Tropsch synthesis, Fixed fluidized bed, LDV, Velocity

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Authors: Hung-Chi Chang

Abstract:

For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

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Authors: Ratanavadee Takerngsukvatana

Abstract:

The purposes of this research were to study reading behavior of undergraduate students at Suan Sunandha Rajabhat University. A stratified random sample of 380 participants was collected. A Likert five-scale questionnaire was developed to collect data and to obtain students’ opinions regarding their reading behavior. The findings revealed that the majority of respondents read mainly for academic purpose. They preferred to read magazines. The majority of respondents read an average of 3-7 pages a day. The places to read were home and library. Buying with their own money and borrowing from the library were two main sources of books. The suggested activity to promote is planning the curriculum to suit students’ reading behavior.

Keywords: reading, reading behavior, undergraduate students, Suan Sunandha Rajabhat University

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Authors: Manal A. Mohsen, Ahmed Tawfik

Abstract:

Hydrogen production from cake wastewater by anaerobic dark fermentation via upflow anaerobic staged reactor (UASR) was investigated in this study. The reactor was continuously operated for four months at constant hydraulic retention time (HRT) of 21.57 hr, PH value of 6 ± 0.6, temperature of 21.1°C, and organic loading rate of 2.43 gCOD/l.d. The hydrogen production was 5.7 l H₂/d and the hydrogen yield was 134.8 ml H₂ /g COD_removed. The system showed an overall removal efficiency of TCOD, TBOD, TSS, TKN, and Carbohydrates of 40 ± 13%, 59 ± 18%, 84 ± 17%, 28 ± 27%, and 85 ± 15% respectively during the long term operation period. Based on the available results, the system is not sufficient for the effective treatment of cake wastewater, and the effluent quality of UASR is not complying for discharge into sewerage network, therefore a post treatment is needed (not covered in this study).

Keywords: cake wastewater industry, chemical oxygen demand (COD), hydrogen production, up-flow anaerobic staged reactor (UASR)

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Authors: C. Tezara, H. Y. Lim, M. H. Yazdi, J. W. Lim, J. P. Siregar

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Natural fibre has become an element in human lives. A lot of researchers have conducted research about natural fibre reinforced polymer. Malaysian government has spent a lot of money on the research funding for researchers and academician especially research on kenaf fibre due to exclusion of tobacco from AFTA (Asean Free Trade Area) list. This work is to investigate the mechanical properties of kenaf fiber reinforced epoxy composite where short kenaf fibre was applied and the mechanical properties of 5%, 10% and 15% wt. of kenaf fibre were added into the mixture of epoxy resin. Hand lay-up process was selected in the fabrication of the specimen for testing. The tensile, flexural and impact test were conducted following ASTM D3039, ASTM D790 and ASTM D256 accordingly. From the experiment result, the effect of different fiber loading of the specimen on its mechanical properties would be analyzed and compared in the result and discussion.

Keywords: Kenaf fibre, epoxy, composite, fibre

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Authors: Victor Emeli, Akansel Cosgun

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This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).

Keywords: motion planning, path planning, push planning, robot navigation

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Authors: Khoa Tan Nguyen, Tuan Anh Le, Kihak Lee

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This paper presents the flexural response of Reinforced Geopolymer Concrete (RGPC) beams. A commercial finite element (FE) software ABAQUS has been used to perform a structural behavior of RGPC beams. Using parameters such: stress, strain, Young’s modulus, and Poisson’s ratio obtained from experimental results, a beam model has been simulated in ABAQUS. The results from experimental tests and ABAQUS simulation were compared. Due to friction forces at the supports and loading rollers; slip occurring, the actual deflection of RGPC beam from experimental test results were slightly different from the results of ABAQUS. And there is good agreement between the crack patterns of fly ash-based geopolymer concrete generated by FE analysis using ABAQUS, and those in experimental data.

Keywords: geopolymer concrete beam, finite element mehod, stress strain relation, modulus elasticity

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Authors: M. Baghdasaryan, A. Sukiasyan

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An algorithm for estimating the stable operation conditions of the synchronous motor of the ore mill electric drive is proposed. The stable operation conditions of the synchronous motor are revealed, taking into account the estimation of the q angle change and the technological factors. The stability condition obtained allows to ensure the stable operation of the motor in the synchronous mode, taking into account the nonlinear character of the mill loading. The developed algorithm gives an opportunity to present the undesirable phenomena, arising in the electric drive system. The obtained stability condition can be successfully applied for the optimal control of the electromechanical system of the mill.

Keywords: electric drive, synchronous motor, ore mill, stability, technological factors

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Authors: Kamal, Adil Ahmad

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Earthquakes are among the most versatile natural and dynamic processes, and hence a fractal model is considered to be the best representative of the same. We present a novel method to process and analyse information hidden in earthquake sequences using Fractal Dimensions and Iterative Function Systems (IFS). Spatial and temporal variations in the fractal dimensions of seismicity observed around the Indian peninsula in last 30 years are studied. This was used as a possible precursor before large earthquakes in the region. IFS images for observed seismicity in the Himalayan belt were also obtained. We scan the whole data set and coarse grain of a selected window to reduce it to four bins. A critical analysis of four-cornered chaos-game clearly shows that the spatial variation in earthquake occurrences in Himalayan range is not random. Two subzones of Himalaya have a tendency to follow each other in time.

Keywords: earthquakes, fractals, Himalaya, iterated function systems

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Authors: Almostafa Abdelaziz, Liang Guozhu, Anwer Elsayed

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The determination of grain geometry is an important and critical step in the design of solid propellant rocket motor. In this study, the design process involved parametric geometry modeling in CAD, MATLAB coding of performance prediction and 2D star grain ignition experiment. The 2D star grain burnback achieved by creating new surface via each web increment and calculating geometrical properties at each step. The 2D star grain is further modified to burn as a tapered 3D star grain. Zero dimensional method used to calculate the internal ballistic performance. Experimental and theoretical results were compared in order to validate the performance prediction of the solid rocket motor. The results show that the usage of 3D grain geometry will decrease the pressure inside the combustion chamber and enhance the volumetric loading ratio.

Keywords: burnback analysis, rocket motor, star grain, three dimensional grains

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Authors: Juan P. Silva, T. R. Canchala, H. J. Lubberding, E. J. Peña, H. J. Gijzen

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This study measured the fluxes of greenhouse gases (GHGs) i.e. CO₂, CH₄ and N₂O from a tropical eutrophic freshwater wetland (“Sonso Lagoon”) which receives input loading nutrient from several sources i.e. agricultural run-off, domestic sewage, and a polluted river. The flux measurements were carried out at four different points using the static chamber technique. CO₂ fluxes ranged from -8270 to 12210 mg.m^-2.d^-1 (median = 360; SD = 4.11; n = 50), CH₄ ranged between 0.2 and 5270 mg.m^-2.d^-1 (median = 60; SD = 1.27; n = 45), and N₂O ranged from -31.12 to 15.4 mg N₂O m^-2.d^-1 (median = 0.05; SD = 9.36; n = 42). Although some negative fluxes were observed in the zone dominated by floating plants i.e. Eichornia crassipes, Salvinia sp., and Pistia stratiotes L., the mean values indicated that the Sonso Lagoon was a net source of CO₂, CH₄ and N₂O. In addition, an effect of the eutrophication on GHG emissions could be observed in the positive correlation found between CO₂, CH₄ and N₂O generation and COD, PO₄^-3, NH₃-N, TN and NO₃^-N. The eutrophication impact on GHG production highlights the necessity to limit the anthropic activities on freshwater wetlands.

Keywords: eutrophication, greenhouse gas emissions, freshwater wetlands, climate change

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Authors: Nagasamy Venkatesh Dhandapani

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This work aims at investigating the use of β-Cyclodextrin as a cross linker, in an attempt to formulate nanosponges containing ketoconazole. The nanosponges were prepared by cross-linking method. The excipients used in this study did not alter the physicochemical properties of a drug as revealed by FTIR spectroscopy. Studies on various formulation variables revealed that all the variables are inter-related with the formulation. The ideal batch among the formulation was selected based on the higher entrapment efficiency and drug loading. The in vitro release studies of ketoconazole nanosponges in hydrogel exhibited a sustained release over a period of 24 hours. Mathematical analysis of drug release from the formulation followed non-Fickian diffusion obeying first order kinetics. The anti-fungal activity of the formulation exhibited better zone of inhibition when compared to pure drug (ketoconazole) against Tinea corporis.

Keywords: nanosponges, beta-cyclodextrin, ketoconazole, tinea corporis

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Authors: A. H. Elkholy, A. H. Falah

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A new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well established formulae of spur gears. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Merbouha Barka, K. H. Benrahou, A. Fakrar, A. Tounsi, E. A. Adda Bedia

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This paper presents an analytical investigation on the buckling and postbuckling behaviors of thick functionally graded plates subjected to thermal load .Material properties are assumed to be temperature dependent, and graded in the thickness direction according to a simple power law distribution in terms of the volume fractions of constituents. The formulations are based on first order shear deformation plate theory taking into account Von Karman nonlinearity and initial geometrical imperfection. By applying Galerkin method, closed-form relations of postbuckling equilibrium paths for simply supported plates are determined. Analysis is carried out to show the effects of material and geometrical properties, in-plane boundary restraint, and imperfection on the buckling and postbuckling loading capacity of the plates.

Keywords: functionally graded materials, postbuckling, first order shear deformation theory, imperfection

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Authors: Güneş Aydın, Razi Kalantari Osgouei, Murat Emre Öztürk, Ahmad Partovi Meran, Ekrem Tüfekçi

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Advanced lightweight laminated composite shells are increasingly being used in all types of modern structures, for enhancing their structural efficiency and performance. Such thin-walled structures are susceptible to buckling when subjected to various loading. This paper focuses on the buckling of cylindrical shells under axial compression and torsional loads. Effects of fiber orientation on the maximum buckling load of carbon fiber reinforced polymer (CFRP) shells are optimized. Optimum fiber angles have been calculated analytically by using MATLAB program. Numerical models have been carried out by using Finite Element Method program ABAQUS. Results from analytical and numerical analyses are also compared.

Keywords: buckling, composite, cylindrical shell, finite element, compression, torsion, MATLAB, optimization

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Authors: Manpreet Kaur

Abstract:

When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

Procedia PDF Downloads 111