Search results for: maximum input

Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 229

Authors: Balwinder Singh

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The present research is a paper on the characterization of aluminum alloy-6063 hybrid metal matrix composites using three different reinforcement materials (SiC, red mud, and fly ash) through stir casting method. The red mud was used in solid form, and particle size range varies between 103-150 µm. During this investigation, fly ash is received from Guru Nanak Dev Thermal Plant (GNDTP), Bathinda. The study has been done by using Taguchi’s L9 orthogonal array by taking fraction wt.% (SiC 5%, 7.5%, and 10% and Red Mud and Fly Ash 2%, 4%, and 6%) as input parameters with their respective levels. The study of the mechanical properties (tensile strength, impact strength, and microhardness) has been done by using Analysis of Variance (ANOVA) with the help of MINITAB 17 software. It is revealed that silicon carbide is the most significant parameter followed by red mud and fly ash affecting the mechanical properties, respectively. The fractured surface morphology of the composites using Field Emission Scanning Electron Microscope (FESEM) shows that there is a good mixing of reinforcement particles in the matrix. Energy-dispersive X-ray spectroscopy (EDS) was performed to know the presence of the phases of the reinforced material.

Keywords: reinforcement, silicon carbide, fly ash, red mud

Procedia PDF Downloads 159

Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park

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In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.

Keywords: accuracy improvement, IR gas sensor, gas leak, detector

Procedia PDF Downloads 391

Authors: Nelson Lujara

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The paper presents a practical three-phase PWM inverter suitable for low voltage, low rating energy efficient systems. The work in the paper is conducted with the view to establishing the significance of the loss contribution from the PWM inverter in the determination of the complete losses of a photovoltaic (PV) array-powered induction motor drive water pumping system. Losses investigated include; conduction and switching loss of the devices and gate drive losses. It is found that the PWM inverter operates at a reasonable variable efficiency that does not fall below 92% depending on the load. The results between the simulated and experimental results for the system with or without a maximum power tracker (MPT) compares very well, within an acceptable range of 2% margin.

Keywords: energy, inverter, losses, photovoltaic

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Authors: Vivek Rangarajan, Kim G. Clarke

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Bacillus lipopeptides are biosurfactants with wide ranging applications in the medical, food, agricultural, environmental and cosmetic industries. They are produced as a mix of three families, surfactin, iturin and fengycin, each comprising a large number of homologues of varying functionalities. Consequently, the method and degree of purification of the lipopeptide cocktail becomes particularly important if the functionality of the lipopeptide end-product is to be maximized for the specific application. However, downstream processing of Bacillus lipopeptides is particularly challenging due to the subtle variations observed in the different lipopeptide homologues and isoforms. To date, the most frequently used lipopeptide purification operations have been acid precipitation, solvent extraction, membrane ultrafiltration, adsorption and size exclusion. RP-HPLC (reverse phase high pressure liquid chromatography) also has potential for fractionation of the lipopeptide homologues. In the studies presented here, membrane ultrafiltration and RP-HPLC were evaluated for lipopeptide purification to different degrees of purities for maximum functionality. Batch membrane ultrafiltration using 50 kDa polyether sulphone (PES) membranes resulted in lipopeptide recovery of about 68% for surfactin and 82 % for fengycin. The recovery was further improved to 95% by using size-conditioned lipopeptide micelles. The conditioning of lipopeptides with Ca2+ ions resulted in uniformly sized micelles with average size of 96.4 nm and a polydispersity index of 0.18. The size conditioning also facilitated removal of impurities (molecular weight ranging between 2335-3500 Da) through operation of the system under dia-filtration mode, in a way similar to salt removal from protein by dialysis. The resultant purified lipopeptide was devoid of macromolecular impurities and could ideally suit applications in the cosmetic and food industries. Enhanced purification using RP-HPLC was carried out in an analytical C18 column, with the aim to fractionate lipopeptides into their constituent homologues. The column was eluted with mobile phase comprising acetonitrile and water over an acetonitrile gradient, 35% - 80%, over 70 minutes. The gradient elution program resulted in as many as 41 fractions of individual lipopeptide homologues. The efficacy test of these fractions against fungal phytopathogens showed that first 21 fractions, identified to be homologues of iturins and fengycins, displayed maximum antifungal activities, suitable for biocontrol in the agricultural industry. Thus, in the current study, the downstream processing of lipopeptides leading to tailor-made products for selective applications was demonstrated using two major downstream unit operations.

Keywords: bacillus lipopeptides, membrane ultrafiltration, purification, RP-HPLC

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Authors: Asmaa Shehata

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Prior research indicates that second language (L2) learners encounter difficulty in the distinguishing novel L2 contrasting sounds that are not contrastive in their native languages. L2 orthographic information, however, is found to play a positive role in the acquisition of non-native phoneme contrasts. While most studies have mainly involved a familiar written script (i.e., the Roman script), the influence of a foreign, unfamiliar script is still unknown. Therefore, the present study asks: Does unfamiliar L2 script play a role in creating distinct phonological representations of novel contrasting phonemes? It is predicted that subjects’ performance in the unfamiliar orthography group will outperform their counterparts’ performance in the control group. Thus, training that entails orthographic inputs can yield a significant improvement in L2 adult learners’ identification and lexical encoding of novel L2 consonant contrasts. Results are discussed in terms of their implications for the type of input introduced to L2 learners to improve their language learning.

Keywords: Arabic, consonant contrasts, foreign script, lexical encoding, orthography, word learning

Procedia PDF Downloads 256

Authors: Sirada Sripinun

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This work studied the isomerization of 1-butene over hydrotalcite catalyst. The experiments were conducted at various gas hourly space velocity (GHSV), reaction temperature, and feed concentration. No catalyst deactivation was observed over the reaction time of 16 hours. Two major reaction products were trans-2-butene and cis-2-butene. The reaction temperature played an important role on the reaction selectivity. At high operating temperatures, the selectivity of trans-2-butene was higher than the selectivity of cis-2-butene while it was opposite at a lower reaction temperature. In the range of operating conditions, the maximum conversion of 1-butene was found at 74% when T = 673 K and GHSV = 4 m3/h/kg-cat with trans- and cis-2-butene selectivities of 54% and 46% respectively. Finally, the kinetic parameters of the reaction were determined.

Keywords: hydrotalcite, isomerization, kinetic, 1-butene

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Authors: M. Sharif Imam Ibne Amir, Mohammad Masud Kamal Khan, Mohammad Golam Rasul, Raj H. Sharma, Fatema Akram

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Future flood can be predicted using the probable maximum flood (PMF). PMF is calculated using the historical discharge or rainfall data considering the other climatic parameter stationary. However, climate is changing globally and the key climatic variables are temperature, evaporation, rainfall and sea level rise (SLR). To develop scenarios to a basin or catchment scale these important climatic variables should be considered. Nowadays scenario based on climatic variables is more suitable than PMF. Six scenarios were developed for a large Fitzroy basin and presented in this paper.

Keywords: climate change, rainfall, potential evaporation, scenario, sea level rise (SLR), sub-catchment

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Steadyman Chikumba, Vasudeva Vereedhi Rao

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This paper reports on the synthesis of FeCrCoNiZn and its characterisation using SEM and nanoindentation. The high entropy alloy FeCrCoNiZn was fabricated using spark plasma sintering at a temperature of 1100ᵒC from powders mixed for 9 hours. The powders mixture was equimolar, and the resultant microstructure had a single crystalline structure when studied under SEM. Several nano Vickers hardness measurements were taken on a polished surface etched by Nital solution. The hardness ranged from 711 Vickers to a maximum of 1773.2. The alloy FeCrCoNiZn showed a nano hardness of 1070 Vickers and a modulus of elasticity of 460.4 MPa. The process managed to fabricate a very hard material that can find applications where wear resistance is desired.

Keywords: high entropy alloy, FeCrVNiZn, nanohardness, SEM

Procedia PDF Downloads 100

Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

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In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

Procedia PDF Downloads 253

Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

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With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

Procedia PDF Downloads 447

Authors: A. Bayat, R. Bello-Mendoza, D. G. Wareham

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Two major categories of green waste are fruit and vegetable (FV) waste and garden and yard (GY) waste. Although, anaerobic digestions (AD) is able to manage FV waste; there is less confidence in the conditions for AD to handle GY wastes (grass, leaves, trees and bush trimmings); mainly because GY contains lignin and other recalcitrant organics. GY in the dry state (TS ≥ 15 %) can be digested at mesophilic temperatures; however, little methane data has been reported under thermophilic conditions, where conceivably better methane yields could be achieved. In addition, it is suspected that at lower solids concentrations, the methane yield could be increased. As such, the aim of this research is to find the temperature and solids concentration conditions that produce the most methane; under two different temperature regimes (mesophilic, thermophilic) and three solids states (i.e. 'dry', 'semi-dry' and 'wet'). Twenty liters of GY waste was collected from a public park located in the northern district in Tehran. The clippings consisted of freshly cut grass as well as dry branches and leaves. The GY waste was chopped before being fed into a mechanical blender that reduced it to a paste-like consistency. An initial TS concentration of approximately 38 % was achieved. Four hundred mL of anaerobic inoculum (average total solids (TS) concentration of 2.03 ± 0.131 % of which 73.4% were volatile solid (VS), soluble chemical oxygen demand (sCOD) of 4.59 ± 0.3 g/L) was mixed with the GY waste substrate paste (along with distilled water) to achieve a TS content of approximately 20 %. For comparative purposes, approximately 20 liters of FV waste was ground in the same manner as the GY waste. Since FV waste has a much higher natural water content than GY, it was dewatered to obtain a starting TS concentration in the dry solid-state range (TS ≥ 15 %). Three samples were dewatered to an average starting TS concentration of 32.71 %. The inoculum was added (along with distilled water) to dilute the initial FV TS concentrations down to semi-dry conditions (10-15 %) and wet conditions (below 10 %). Twelve 1-L batch bioreactors were loaded simultaneously with either GY or FV waste at TS solid concentrations ranging from 3.85 ± 1.22 % to 20.11 ± 1.23 %. The reactors were sealed and were operated for 30 days while being immersed in water baths to maintain a constant temperature of 37 ± 0.5 °C (mesophilic) or 55 ± 0.5 °C (thermophilic). A maximum methane yield of 115.42 (L methane/ kg VS added) was obtained for the GY thermophilic-wet AD combination. Methane yield was enhanced by 240 % compared to the GY waste mesophilic-dry condition. The results confirm that high temperature regimes and small solids concentrations are conditions that enhance methane yield from GY waste. A similar trend was observed for the anaerobic digestion of FV waste. Furthermore, a maximum value of VS (53 %) and sCOD (84 %) reduction was achieved during the AD of GY waste under the thermophilic-wet condition.

Keywords: anaerobic digestion, thermophilic, mesophilic, total solids concentration

Procedia PDF Downloads 141

Authors: Chris J. Boreham, Dianne S. Edwards, Amber Jarrett, Justin Davies, Robert Poreda, Alex Sessions, John Eiler

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The origins of natural gases in the Amadeus Basin have been assessed using molecular and stable isotope (C, H, N, He) systematics. A dominant end-member thermogenic, oil-associated gas is considered for the Ordovician Pacoota−Stairway sandstones of the Mereenie gas and oil field. In addition, an abiogenic end-member is identified in the latest Proterozoic lower Arumbera Sandstone of the Dingo gasfield, being most likely associated with radiolysis of methane with polymerisation to wet gases. The latter source assignment is based on a similar geochemical fingerprint derived from the laboratory gamma irradiation experiments on methane. A mixed gas source is considered for the Palm Valley gasfield in the Ordovician Pacoota Sandstone. Gas wetness (%∑C₂−C₅/∑C₁−C₅) decreases in the order Mereenie (19.1%) > Palm Valley (9.4%) > Dingo (4.1%). Non-produced gases at Magee-1 (23.5%; Late Proterozoic Heavitree Quartzite) and Mount Kitty-1 (18.9%; Paleo-Mesoproterozoic fractured granitoid basement) are very wet. Methane thermometry based on clumped isotopes of methane (¹³CDH₃) is consistent with the abiogenic origin for the Dingo gas field with methane formation temperature of 254ᵒC. However, the low methane formation temperature of 57°C for the Mereenie gas suggests either a mixed thermogenic-biogenic methane source or there is no thermodynamic equilibrium between the methane isotopomers. The shallow reservoir depth and present-day formation temperature below 80ᵒC would support microbial methanogenesis, but there is no accompanying alteration of the C- and H-isotopes of the wet gases and CO₂ that is typically associated with biodegradation. The Amadeus Basin gases show low to extremely high inorganic gas contents. Carbon dioxide is low in abundance (< 1% CO₂) and becomes increasing depleted in ¹³C from the Palm Valley (av. δ¹³C 0‰) to the Mereenie (av. δ¹³C -6.6‰) and Dingo (av. δ¹³C -14.3‰) gas fields. Although the wide range in carbon isotopes for CO₂ is consistent with multiple origins from inorganic to organic inputs, the most likely process is fluid-rock alteration with enrichment in ¹²C in the residual gaseous CO₂ accompanying progressive carbonate precipitation within the reservoir. Nitrogen ranges from low−moderate (1.7−9.9% N₂) abundance (Palm Valley av. 1.8%; Mereenie av. 9.1%; Dingo av. 9.4%) to extremely high abundance in Magee-1 (43.6%) and Mount Kitty-1 (61.0%). The nitrogen isotopes for the production gases have δ¹⁵N = -3.0‰ for Mereenie, -3.0‰ for Palm Valley and -7.1‰ for Dingo, suggest all being mixed inorganic and thermogenic nitrogen sources. Helium (He) abundance varies over a wide range from a low of 0.17% to one of the world’s highest at 9% (Mereenie av. 0.23%; Palm Valley av. 0.48%, Dingo av. 0.18%, Magee-1 6.2%; Mount Kitty-1 9.0%). Complementary helium isotopes (R/Ra = ³He/⁴Hesample / ³He/⁴Heair) range from 0.013 to 0.031 R/Ra, indicating a dominant crustal origin for helium with a sustained input of radiogenic 4He from the decomposition of U- and Th-bearing minerals, effectively diluting any original mantle helium input. The high helium content in the non-produced gases compared to the shallower producing wells most likely reflects their stratigraphic position relative to the Tonian Bitter Springs Group with the former below and the latter above an effective carbonate-salt seal.

Keywords: amadeus gas, thermogenic, abiogenic, C, H, N, He isotopes

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: ionic liquid, neural networks, VLE, dilute solution

Procedia PDF Downloads 300

Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

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Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: Graphviz representation, semantic relatedness, similarity measurement, WordNet similarity

Procedia PDF Downloads 238

Authors: Hassan M. Elkamchouchi, Samy H. Darwish, Yasser H. Elkamchouchi, M. E. Morsy

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Methodology is suggested to design a linear rectangular microstrip array antenna based on Yagi antenna theory. The antenna with different directors' lengths as parasitic elements were designed, simulated, and analyzed using HFSS. The calculus and results illustrate the effectiveness of using specific parasitic elements to improve the directivity and gain for microstrip array antenna. The results have shown that the suggested methodology has the potential to be applied for improving the antenna performance. Maximum radiation intensity (Umax) of the order of 0.47w/st was recorded, directivity of 6.58dB, and gain better than 6.07dB are readily achievable for the antenna that working.

Keywords: directivity, director, microstrip antenna, gain improvment

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Authors: Kevin Wongleedee

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Food quality and risks are major concerns for inbound senior tourists when visiting tourist destinations in Thailand. The purposes of this study were to investigate food quality and risks perceived by inbound senior tourists. This paper drew upon data collection from an inbound senior tourist survey conducted in Thailand during summer 2013. Summer time in Thailand is a high season for inbound tourists. It is also a high risk period in which a variety food safety issues and incidents have often occurred. The survey was structured primarily to obtain inbound senior tourists’ concerns toward a variety of food quality and risks they encountered during their trip in Thailand. A total of 400 inbound senior tourists were elicited as data input for mean and standard deviation. The findings revealed that inbound tourists rated the overall food quality at a high level and the three most important perceived food risks were 1) unclean physical cooking facility, 2) toxic chemical handling, and 3) unclean water.

Keywords: food quality, inbound senior tourists, risks, Thailand

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Authors: Enrique Bazan-Zurita, Sittipong Jarernprasert, Jacobo Bielak

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We study the effects of soil-structure interaction (SSI) on the inelastic seismic response of a single-degree-of-freedom system whose hysteretic behaviour exhibits stiffness and/or strength degrading characteristics. Two sets of accelerograms are used as seismic input: the first comprising 87 record from stiff to medium stiff sites in California, and the second comprising 66 records from the soft lakebed of Mexico City. This study focuses in three seismic response parameters: ductility demand, inter-story drift, and total lateral displacement. The results allow quantitative estimates of changes in such parameters in an SSI system in comparison with those corresponding to the associated fixed-base system. We found that degrading features affect significantly both the response of fixed-base structures and the impact of soil-structure interaction. We propose a procedure to incorporate the results of this and similar studies in seismic design regulations for SSI system with anticipated nonlinear degrading behaviour.

Keywords: inelastic, seismic, building, foundation, interaction

Procedia PDF Downloads 286

Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan

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Nowadays, advanced driver assistance systems (ADAS) have become popular, since they enable safe driving. Lane detection is a vital step for ADAS. The performance of the lane detection process is critical to obtain a high accuracy lane departure warning system (LDWS). Challenging factors such as road cracks, erosion of lane markings, weather conditions might affect the performance of a lane detection system. In this paper, 1-D weighted filter based on row filtering to detect lane marking is proposed. 2-D input image is filtered by 1-D weighted filter considering four-pixel values located symmetrically around the center of candidate pixel. Performance evaluation is carried out by two metrics which are true positive rate (TPR) and false positive rate (FPR). Experimental results demonstrate that the proposed approach provides better lane marking detection accuracy compared to the previous methods while providing real-time processing performance.

Keywords: lane marking filter, lane detection, ADAS, LDWS

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Misook Ahn

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This study examines the Institutional Curriculum Repository (ICR) developed with MS SharePoint. The purpose of using MS SharePoint is to organize, share, and manage the curriculum data. The ICR aims to build a centralized curriculum infrastructure, preserve all curriculum materials, and provide academic service to users (faculty, students, or other agencies). The ICR collection includes core language curriculum materials developed by each language school—foreign language textbooks, language survival kits, and audio files currently in or not in use at the schools. All core curriculum materials with audio and video files have been coded, collected, and preserved at the ICR. All metadata for the collected curriculum materials have been input by language, code, year, book type, level, user, version, and current status (in use/not in use). The qualitative content analysis, including the survey data, is used to evaluate the effectiveness of using MS SharePoint for the repository system. This study explains how to manage and preserve curriculum materials with MS SharePoint, along with challenges and suggestions for further research. This study will be beneficial to other universities or organizations considering archiving or preserving educational materials.

Keywords: digital preservation, ms sharepoint, repository, curriculum materials

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Authors: Natalia Bustos Sierra, Katrien Tersago

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It is currently proven that both extremes of temperature are associated with increased mortality and that air pollution is associated with temperature. This relationship is complex, and in countries with important seasonal variations in weather such as Belgium, some effects can appear as non-significant when the analysis is done over the entire year. We, therefore, analyzed the effect of short-term outdoor air pollution exposure on cardiovascular mortality during the warmer and colder months separately. We used daily cardiovascular deaths from acute cardiovascular diagnostics according to the International Classification of Diseases, 10th Revision (ICD-10: I20-I24, I44-I49, I50, I60-I66) during the period 2008-2013. The environmental data were population-weighted concentrations of particulates with an aerodynamic diameter less than 10 µm (PM₁₀) and less than 2.5 µm (PM₂.₅) (daily average), nitrogen dioxide (NO₂) (daily maximum of the hourly average) and ozone (O₃) (daily maximum of the 8-hour running mean). A Generalized linear model was applied adjusting for the confounding effect of season, temperature, dew point temperature, the day of the week, public holidays and the incidence of influenza-like illness (ILI) per 100,000 inhabitants. The relative risks (RR) were calculated for an increase of one interquartile range (IQR) of the air pollutant (μg/m³). These were presented for the four hottest months (June, July, August, September) and coldest months (November, December, January, February) in Belgium. We applied both individual lag model and unconstrained distributed lag model methods. The cumulative effect of a four-day exposure (day of exposure and three consecutive days) was calculated from the unconstrained distributed lag model. The IQR for PM₁₀, PM₂.₅, NO₂, and O₃ were respectively 8.2, 6.9, 12.9 and 25.5 µg/m³ during warm months and 18.8, 17.6, 18.4 and 27.8 µg/m³ during cold months. The association with CV mortality was statistically significant for the four pollutants during warm months and only for NO₂ during cold months. During the warm months, the cumulative effect of an IQR increase of ozone for the age groups 25-64, 65-84 and 85+ was 1.066 (95%CI: 1.002-1.135), 1.041 (1.008-1.075) and 1.036 (1.013-1.058) respectively. The cumulative effect of an IQR increase of NO₂ for the age group 65-84 was 1.066 (1.020-1.114) during warm months and 1.096 (1.030-1.166) during cold months. The cumulative effect of an IQR increase of PM₁₀ during warm months reached 1.046 (1.011-1.082) and 1.038 (1.015-1.063) for the age groups 65-84 and 85+ respectively. Similar results were observed for PM₂.₅. The short-term effect of air pollution on cardiovascular mortality is greater during warm months for lower pollutant concentrations compared to cold months. Spending more time outside during warm months increases population exposure to air pollution and can, therefore, be a confounding factor for this association. Age can also affect the length of time spent outdoors and the type of physical activity exercised. This study supports the deleterious effect of air pollution on cardiovascular mortality (CV) which varies according to season and age groups in Belgium. Public health measures should, therefore, be adapted to seasonality.

Keywords: air pollution, cardiovascular, mortality, season

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Riccardo Loggia, Francesca Pizzimenti, Francesco Lelli, Luigi Martirano

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Recent air emission regulations point toward the complete electrification of road vehicles. An increasing number of users are beginning to prefer full electric or hybrid, plug-in vehicle solutions, incentivized by government subsidies and the lower cost of electricity compared to gasoline or diesel. However, it is necessary to optimize charging stations so that they can simultaneously satisfy as many users as possible. The purpose of this paper is to present optimization algorithms that enable simultaneous charging of multiple electric vehicles while ensuring maximum performance in relation to the type of charging station.

Keywords: electric vehicles, charging stations, sharing model, fast charging, car park, power profiles

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Authors: Guo-Ming Sung, Ramavath Naga Raju Naik

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This paper presents a low power, high speed, sense-amplifier based flip-flop (SAFF). The flip-flop’s power con-sumption and delay are greatly reduced by employing a new conditionally precharge sense-amplifier stage and a single-ended latch stage. Glitch-free and contention-free latch operation is achieved by using a conditional cut-off strategy. The design uses fewer transistors, has a lower clock load, and has a simple structure, all of which contribute to a near-zero setup time. When compared to previous flip-flop structures proposed for similar input/output conditions, this design’s performance and overall PDP have improved. The post layout simulation of the circuit uses 2.91µW of power and has a delay of 65.82 ps. Overall, the power-delay product has seen some enhancements. Cadence Virtuoso Designing tool with CMOS 90nm technology are used for all designs.

Keywords: high-speed, low-power, flip-flop, sense-amplifier

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Authors: Ajoy Kumar Das, Prasenjit Dey

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Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nano particles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

Keywords: forced convection, square cylinder, nanofluid, neural network

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Sawsan Eissa, Omnia Kabbany

Abstract:

The coastline of Togo has been historically suffering from erosion for decades, which requires a solution to help control and reduce the erosion to allow for the development of the coastal area. A morpho-dynamic model using X-beach software was developed for the Western 14 Km of the Togolese coast. The model was coupled with the hydrodynamic module of DELFT 3D, flow, and the Wave module, SWAN. The data used as input included a recent bathymetric survey, a recent shoreline topographic survey, aerial photographs, ERA 5 water level and wave data, and recent test results of seabed samples. A number of scenarios were modeled: do nothing scenario, groynes, detached breakwaters system with different crest levels and alignments. The findings showed that groynes is not expected to be effective for protection against erosion, and that the best option is a system of detached breakwater, partially emerged-partially submerged couples with periodical maintenance.

Keywords: hydrodynamics, morphology, Togo, Delft3D, SWAN, XBeach, coastal erosion, detached breakwaters

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