Search results for: direct voice input
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5761

Search results for: direct voice input

3691 Geophysical Methods and Machine Learning Algorithms for Stuck Pipe Prediction and Avoidance

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

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

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3690 Characterization of Aluminium Alloy 6063 Hybrid Metal Matrix Composite by Using Stir Casting Method

Authors: Balwinder Singh

Abstract:

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 144
3689 Research on Development and Accuracy Improvement of an Explosion Proof Combustible Gas Leak Detector Using an IR Sensor

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

Abstract:

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

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3688 Blue Hydrogen Production Via Catalytic Aquathermolysis Coupled with Direct Carbon Dioxide Capture Via Adsorption

Authors: Sherif Fakher

Abstract:

Hydrogen has been gaining a lot of global attention as an uprising contributor in the energy sector. Labeled as an energy carrier, hydrogen is used in many industries and can be used to generate electricity via fuel cells. Blue hydrogen involves the production of hydrogen from hydrocarbons using different processes that emit CO₂. However, the CO₂ is captured and stored. Hence, very little environmental damage occurs during the hydrogen production process. This research investigates the ability to use different catalysts for the production of hydrogen from different hydrocarbon sources, including coal, oil, and gas, using a two-step Aquathermolysis reaction. The research presents the results of experiments conducted to evaluate different catalysts and also highlights the main advantages of this process over other blue hydrogen production methods, including methane steam reforming, autothermal reforming, and oxidation. Two methods of hydrogen generation were investigated including partial oxidation and aquathermolysis. For those two reactions, the reaction kinetics, thermodynamics, and medium were all investigated. Following this, experiments were conducted to test the hydrogen generation potential from both methods. The porous media tested were sandstone, ash, and prozzolanic material. The spent oils used were spent motor oil and spent vegetable oil from cooking. Experiments were conducted at temperatures up to 250 C and pressures up to 3000 psi. Based on the experimental results, mathematical models were developed to predict the hydrogen generation potential at higher thermodynamic conditions. Since both partial oxidation and aquathermolysis require relatively high temperatures to undergo, it was important to devise a method by which these high temperatures can be generated at a low cost. This was done by investigating two factors, including the porous media used and the reliance on the spent oil. Of all the porous media used, the ash had the highest thermal conductivity. The second step was the partial combustion of part of the spent oil to generate the heat needed to reach the high temperatures. This reduced the cost of the heat generation significantly. For the partial oxidation reaction, the spent oil was burned in the presence of a limited oxygen concentration to generate carbon monoxide. The main drawback of this process was the need for burning. This resulted in the generation of other harmful and environmentally damaging gases. Aquathermolysis does not rely on burning, which makes it the cleaner alternative. However, it needs much higher temperatures to run the reaction. When comparing the hydrogen generation potential for both using gas chromatography, aquathermolysis generated 23% more hydrogen using the same volume of spent oil compared to partial oxidation. This research introduces the concept of using spent oil for hydrogen production. This can be a very promising method to produce a clean source of energy using a waste product. This can also help reduce the reliance on freshwater for hydrogen generation which can divert the usage of freshwater to other more important applications.

Keywords: blue hydrogen production, catalytic aquathermolysis, direct carbon dioxide capture, CCUS

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3687 The Effect of Pixelation on Face Detection: Evidence from Eye Movements

Authors: Kaewmart Pongakkasira

Abstract:

This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered.

Keywords: eye movements, face detection, face-shape information, pixelation

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3686 Shear Strength Envelope Characteristics of LimeTreated Clays

Authors: Mohammad Moridzadeh, Gholamreza Mesri

Abstract:

The effectiveness of lime treatment of soils has been commonly evaluated in terms of improved workability and increased undrained unconfined compressive strength in connection to road and airfield construction. The most common method of strength measurement has been the unconfined compression test. However, if the objective of lime treatment is to improve long-term stability of first-time or reactivated landslides in stiff clays and shales, permanent changes in the size and shape of clay particles must be realized to increase drained frictional resistance. Lime-soil interactions that may produce less platy and larger soil particles begin and continue with time under the highly alkaline pH environment. In this research, pH measurements are used to monitor chemical environment and progress of reactions. Atterberg limits are measured to identify changes in particle size and shape indirectly. Also, fully softened and residual strength measurements are used to examine an improvement in frictional resistance due to lime-soil interactions. The main variables are soil plasticity and mineralogy, lime content, water content, and curing period. Lime effect on frictional resistance is examined using samples of clays with different mineralogy and characteristics which may react with lime to various extents. Drained direct shear tests on reconstituted lime-treated clay specimens with various properties have been performed to measure fully softened shear strength. To measure residual shear strength, drained multiple reversal direct shear tests on precut specimens were conducted. This way, soil particles are oriented along the direction of shearing to the maximum possible extent and provide minimum frictional resistance. This is applicable to reactivated and part of first-time landslides. The Brenna clay, which is the highly plastic lacustrine clay of Lake Agassiz causing slope instability along the banks of the Red River, is one of the soil samples used in this study. The Brenna Formation characterized as a uniform, soft to firm, dark grey, glaciolacustrine clay with little or no visible stratification, is full of slickensided surfaces. The major source of sediment for the Brenna Formation was the highly plastic montmorillonitic Pierre Shale bedrock. The other soil used in this study is one of the main sources of slope instability in Harris County Flood Control District (HCFCD), i.e. the Beaumont clay. The shear strengths of untreated and treated clays were obtained under various normal pressures to evaluate the shear envelope nonlinearity.

Keywords: Brenna clay, friction resistance, lime treatment, residual

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3685 Stable Tending Control of Complex Power Systems: An Example of Localized Design of Power System Stabilizers

Authors: Wenjuan Du

Abstract:

The phase compensation method was proposed based on the concept of the damping torque analysis (DTA). It is a method for the design of a PSS (power system stabilizer) to suppress local-mode power oscillations in a single-machine infinite-bus power system. This paper presents the application of the phase compensation method for the design of a PSS in a multi-machine power system. The application is achieved by examining the direct damping contribution of the stabilizer to the power oscillations. By using linearized equal area criterion, a theoretical proof to the application for the PSS design is presented. Hence PSS design in the paper is an example of stable tending control by localized method.

Keywords: phase compensation method, power system small-signal stability, power system stabilizer

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3684 Effects of Unfamiliar Orthography on the Lexical Encoding of Novel Phonological Features

Authors: Asmaa Shehata

Abstract:

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 244
3683 Transport Related Air Pollution Modeling Using Artificial Neural Network

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

Abstract:

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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3682 Aerodynamic Sound from a Sawtooth Plate with Different Thickness

Authors: Siti Ruhliah Lizarose Samion, Mohamed Sukri Mat Ali

Abstract:

The effect of sawtooth plate thickness on the aerodynamic noise generated in flow at a Reynolds number of 150 is numerically investigated. Two types of plate thickness (hthick=0.2D and hthin=0.02D) are proposed. Flow simulations are carried out using Direct Numerical Simulation, whereas the calculation of aerodynamic noise radiated from the flow is solved using Curle’s equation. It is found that the flow behavior of thin sawtooth plate, consisting counter-rotating-vortices, is more complex than that of the thick plate. This then explains well the generated sound in both plates cases. Sound generated from thin plat is approximately 0.5 dB lower than the thick plate. Findings from current study provide better understanding of the flow and noise behavior in edge serrations via understanding the case of a sawtooth plate.

Keywords: aerodynamic sound, bluff body, sawtooth plate, Curle analogy

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3681 The Relationship between Organizational Climate with Job Burnout and Job Satisfaction in Employees of Tehran Electric Company

Authors: Zeinab Amini Moghaddam, Alireza Dehkhodania

Abstract:

Nowadays, organizations have found a high status in the cultural and social structures of societies. The purpose of current study is to investigate the relationship between organizational climate with job burnout as well as job satisfaction. The research method is descriptive and correlational. The population of the study includes all employees in Tehran Electric Company, which equals 1984 people in 2018. The sampling was performed in the form of a consensus, and all employees were regarded as samples. The data gathering tools consist of three questionnaires of Smith’s Job Satisfaction Questionnaire, Halpin and Craft's Occupational climate, and Maslach and Jackson's Job burnout. The results showed that there was a direct and positive relationship between organizational climate and job burnout, as well as job satisfaction. The organizational climate variable could successfully predict job satisfaction. It was also able to predict job burnout.

Keywords: organizational climate, job burnout, job satisfaction, descriptive, correlational

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3680 Mechanical Properties of a Soil Stabilized With a Portland Cement

Authors: Ahmed Emad Ahmed, Mostafa El Abd, Ahmed Wakeb, Moahmmed Eissa

Abstract:

Soil modification and reinforcing aims to increase soil shear strength and stiffness. In this report, different amounts of cement were added to the soil to explore its effect on shear strength and penetration using 3 tests. The first test is proctor compaction test which was conducted to determine the optimal moisture content and maximum dry density. The second test was direct shear test which was conducted to measure shear strength of soil. The third experiment was California bearing ratio test which was done to measure the penetration in soil. Each test was done different amount of times using different amounts of cement. The results from every test show that cement improve soil shear strength properties and stiffness.

Keywords: soil stabilized, soil, mechanical properties of soil, soil stabilized with a portland cement

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3679 Sensor Fault-Tolerant Model Predictive Control for Linear Parameter Varying Systems

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

Abstract:

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

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3678 Performance of Neural Networks vs. Radial Basis Functions When Forming a Metamodel for Residential Buildings

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

Abstract:

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

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3677 Preliminary Prospecting on the Distribution of the Disease of Citrus Tristeza Orchards in the Province of Chlef

Authors: Ibrahim Djelloul Berkane

Abstract:

A survey was conducted to assess the presence of the virus in Citrus tristeza one of the main citrus regions of Algeria, namely the Chlef region, using the technique of Direct Tissue Print Immunoprinting Assay (DTBIA) and the Double Sandwich ELISA antibodies. A nursery citrus, lumber yards, and commercial orchards, which are the main varieties cultivated citrus were subjected to samples collected samples for laboratory analysis. 0.91% of the plants tested orchards were infected with CTV, while no positive case was detected at the nursery the yard, however, it is reported that an alarming rate of 10,5% of orchards tested at the common Chettia were infected with tristeza virus. The investigation was launched to identify the vector species tristeza revealed the presence of a vector is important Aphis gossypii.

Keywords: aphis, chlef, citrus, DAS-ELISA, DTBIA, tristeza

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3676 A Novel Multi-Block Selective Mapping Scheme for PAPR Reduction in FBMC/OQAM Systems

Authors: Laabidi Mounira, Zayani Rafk, Bouallegue Ridha

Abstract:

Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC/OQAM) is presently known as a sustainable alternative to conventional Orthogonal Frequency Division Multiplexing (OFDM) for signal transmission over multi-path fading channels. Like all multicarrier systems, FBMC/OQAM suffers from high Peak to Average Power Ratio (PAPR). Due to the symbol overlap inherent in the FBMC/OQAM system, the direct application of conventional OFDM PAPR reduction scheme is far from being effective. This paper suggests a novel scheme termed Multi-Blocks Selective Mapping (MB-SLM) whose simulation results show that its performance in terms of PAPR reduction is almost identical to that of OFDM system.

Keywords: FBMC/OQAM, multi-blocks, OFDM, PAPR, SLM

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3675 The Synopsis of the AI-Powered Therapy Web Platform ‘Free AI Therapist'

Authors: Arwa Alnowaiser, Hala Shoukri

Abstract:

The ‘FreeAITherapist’ is an artificial intelligence application that uses the power of AI to offer advice and mental health counseling to its users through its chatbot services. The AI therapist is designed to understand users' issues, concerns, and problems and respond appropriately; it provides empathy and guidance and uses evidence-based therapeutic techniques. With its user-friendly platform, it ensures accessibility for individuals in need, regardless of their geographical location. This website was created in direct response to the growing demand for mental health support, aiming to provide a cost-effective and confidential solution. Through promising confidentiality, it considers user privacy and data security. The ‘FreeAITherapist’ strives to bridge the gap in mental health services, offering a reliable resource for individuals seeking guidance and counseling to improve their overall well-being.

Keywords: artificial intelligence, mental health, AI therapist, website, counseling

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3674 Co-Design of Accessible Speech Recognition for Users with Dysarthric Speech

Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

Abstract:

Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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3673 Gas Systems of the Amadeus Basin, Australia

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

Abstract:

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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3672 Prediction of Vapor Liquid Equilibrium for Dilute Solutions of Components in Ionic Liquid by Neural Networks

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

Abstract:

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

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3671 Cartel Formation with Differentiated Products, Asymmetric Cost, and Quantity Competition: The Case of Three Firms

Authors: Burkhard Hehenkamp, Tahmina Faizi

Abstract:

In this paper, we analyze the formation of cartels along with the stability of the cartel for the case of three firms that produce differentiated products and differ in their cost of production. Both cost and demand are linear, and firms compete in quantities once a cartel has been formed (or not). It turns out that the degree of product differentiation has a direct effect on the incentive to form a cartel. Firstly, when goods are complements or close substitutes, firms form a grand coalition. Secondly, for weak and medium substitutes, the firm with the lowest cost prefers to remain independent, while both other firms form a coalition. We also find that the producer profit of the stable coalition structure is nonmonotonic in the degree of product differentiation.

Keywords: collusion, cartel formation, cartel stability, differentiated market, quantity competition, oligopolies

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3670 Measuring Text-Based Semantics Relatedness Using WordNet

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

Abstract:

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

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3669 An Investigation of Food Quality and Risks in Thailand: A Case of Inbound Senior Tourists

Authors: Kevin Wongleedee

Abstract:

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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3668 Soil-Structure Interaction in Stiffness and Strength Degrading Systems

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

Abstract:

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 269
3667 Real-Time Lane Marking Detection Using Weighted Filter

Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan

Abstract:

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

Procedia PDF Downloads 174
3666 Digital Cinema Watermarking State of Art and Comparison

Authors: H. Kelkoul, Y. Zaz

Abstract:

Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: digital cinema, watermarking, wavelet DWT, spread spectrum, JPEG2000 MPEG4

Procedia PDF Downloads 236
3665 User Intention Generation with Large Language Models Using Chain-of-Thought Prompting Title

Authors: Gangmin Li, Fan Yang

Abstract:

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

Procedia PDF Downloads 24
3664 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning

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

Abstract:

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

Procedia PDF Downloads 362
3663 The Effectiveness of Using MS SharePoint for the Curriculum Repository System

Authors: Misook Ahn

Abstract:

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

Procedia PDF Downloads 85
3662 A Low Power and High-Speed Conditional-Precharge Sense Amplifier Based Flip-Flop Using Single Ended Latch

Authors: Guo-Ming Sung, Ramavath Naga Raju Naik

Abstract:

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

Procedia PDF Downloads 142