Search results for: 99.95% IoT data transmission savings
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26850

Search results for: 99.95% IoT data transmission savings

25170 Sampled-Data Control for Fuel Cell Systems

Authors: H. Y. Jung, Ju H. Park, S. M. Lee

Abstract:

A sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The sector bounded nonlinear systems, which have a feedback connection with a linear dynamical system and nonlinearity satisfying certain sector type constraints. Also, the sampled-data control scheme is very useful since it is possible to handle digital controller and increasing research efforts have been devoted to sampled-data control systems with the development of modern high-speed computers. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: sampled-data control, fuel cell, linear matrix inequalities, nonlinear control

Procedia PDF Downloads 565
25169 Development of Fluorescence Resonance Energy Transfer-Based Nanosensor for Measurement of Sialic Acid in vivo

Authors: Ruphi Naz, Altaf Ahmad, Mohammad Anis

Abstract:

Sialic acid (5-Acetylneuraminic acid, Neu5Ac) is a common sugar found as a terminal residue on glycoconjugates in many animals. Humans brain and the central nervous system contain the highest concentration of sialic acid (as N-acetylneuraminic acid) where these acids play an important role in neural transmission and ganglioside structure in synaptogenesis. Due to its important biological function, sialic acid is attracting increasing attention. To understand metabolic networks, fluxes and regulation, it is essential to be able to determine the cellular and subcellular levels of metabolites. Genetically-encoded fluorescence resonance energy transfer (FRET) sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. Taking this, we developed a genetically encoded FRET (fluorescence resonance energy transfer) based nanosensor to analyse the sialic acid level in living cells. Sialic acid periplasmic binding protein (sia P) from Haemophilus influenzae was taken and ligated between the FRET pair, the cyan fluorescent protein (eCFP) and Venus. The chimeric sensor protein was expressed in E. coli BL21 (DE3) and purified by affinity chromatography. Conformational changes in the binding protein clearly confirmed the changes in FRET efficiency. So any change in the concentration of sialic acid is associated with the change in FRET ratio. This sensor is very specific to sialic acid and found stable with the different range of pH. This nanosensor successfully reported the intracellular level of sialic acid in bacterial cell. The data suggest that the nanosensors may be a versatile tool for studying the in vivo dynamics of sialic acid level non-invasively in living cells

Keywords: nanosensor, FRET, Haemophilus influenzae, metabolic networks

Procedia PDF Downloads 132
25168 How Western Donors Allocate Official Development Assistance: New Evidence From a Natural Language Processing Approach

Authors: Daniel Benson, Yundan Gong, Hannah Kirk

Abstract:

Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

Procedia PDF Downloads 79
25167 Effect of Epoxy-ZrP Nanocomposite Top Coating on Inorganic Barrier Layer

Authors: Haesook Kim, Ha Na Ra, Mansu Kim, Hyun Gi Kim, Sung Soo Kim

Abstract:

Epoxy-ZrP (α-zirconium phosphate) nanocomposites were coated on inorganic barrier layer such as sputtering and atomic layer deposition (ALD) to improve the barrier properties and protect the layer. ZrP nanoplatelets were synthesized using a reflux method and exfoliated in the polymer matrix. The barrier properties of coating layer were characterized by measuring water vapor transmission rate (WVTR). The WVTR dramatically decreased after epoxy-ZrP nanocomposite coating, while maintaining the optical properties. It was also investigated the effect of epoxy-ZrP coating on inorganic layer after bending and reliability test. The optimal structure composed of inorganic and epoxy-ZrP nanocomposite layers was used in organic light emitting diodes (OLED) encapsulation.

Keywords: α-zirconium phosphate, barrier properties, epoxy nanocomposites, OLED encapsulation

Procedia PDF Downloads 357
25166 Contingency Screening Using Risk Factor Considering Transmission Line Outage

Authors: M. Marsadek, A. Mohamed

Abstract:

Power system security analysis is the most time demanding process due to large number of possible contingencies that need to be analyzed.  In a power system, any contingency resulting in security violation such as line overload or low voltage may occur for a number of reasons at any time.  To efficiently rank a contingency, both probability and the extent of security violation must be considered so as not to underestimate the risk associated with the contingency. This paper proposed a contingency ranking method that take into account the probabilistic nature of power system and the severity of contingency by using a newly developed method based on risk factor.  The proposed technique is implemented on IEEE 24-bus system.

Keywords: line overload, low voltage, probability, risk factor, severity

Procedia PDF Downloads 545
25165 Optimal Emergency Shipment Policy for a Single-Echelon Periodic Review Inventory System

Authors: Saeed Poormoaied, Zumbul Atan

Abstract:

Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.

Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.

Procedia PDF Downloads 141
25164 Compressed Suffix Arrays to Self-Indexes Based on Partitioned Elias-Fano

Authors: Guo Wenyu, Qu Youli

Abstract:

A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA

Procedia PDF Downloads 252
25163 Data, Digital Identity and Antitrust Law: An Exploratory Study of Facebook’s Novi Digital Wallet

Authors: Wanjiku Karanja

Abstract:

Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 123
25162 Wood as a Climate Buffer in a Supermarket

Authors: Kristine Nore, Alexander Severnisen, Petter Arnestad, Dimitris Kraniotis, Roy Rossebø

Abstract:

Natural materials like wood, absorb and release moisture. Thus wood can buffer indoor climate. When used wisely, this buffer potential can be used to counteract the outer climate influence on the building. The mass of moisture used in the buffer is defined as the potential hygrothermal mass, which can be an energy storage in a building. This works like a natural heat pump, where the moisture is active in damping the diurnal changes. In Norway, the ability of wood as a material used for climate buffering is tested in several buildings with the extensive use of wood, including supermarkets. This paper defines the potential of hygrothermal mass in a supermarket building. This includes the chosen ventilation strategy, and how the climate impact of the building is reduced. The building is located above the arctic circle, 50m from the coastline, in Valnesfjord. It was built in 2015, has a shopping area, including toilet and entrance, of 975 m². The climate of the area is polar according to the Köppen classification, but the supermarket still needs cooling on hot summer days. In order to contribute to the total energy balance, wood needs dynamic influence to activate its hygrothermal mass. Drying and moistening of the wood are energy intensive, and this energy potential can be exploited. Examples are to use solar heat for drying instead of heating the indoor air, and raw air with high enthalpy that allow dry wooden surfaces to absorb moisture and release latent heat. Weather forecasts are used to define the need for future cooling or heating. Thus, the potential energy buffering of the wood can be optimized with intelligent ventilation control. The ventilation control in Valnesfjord includes the weather forecast and historical data. That is a five-day forecast and a two-day history. This is to prevent adjustments to smaller weather changes. The ventilation control has three zones. During summer, the moisture is retained to dampen for solar radiation through drying. In the winter time, moist air let into the shopping area to contribute to the heating. When letting the temperature down during the night, the moisture absorbed in the wood slow down the cooling. The ventilation system is shut down during closing hours of the supermarket in this period. During the autumn and spring, a regime of either storing the moisture or drying out to according to the weather prognoses is defined. To ensure indoor climate quality, measurements of CO₂ and VOC overrule the low energy control if needed. Verified simulations of the Valnesfjord building will build a basic model for investigating wood as a climate regulating material also in other climates. Future knowledge on hygrothermal mass potential in materials is promising. When including the time-dependent buffer capacity of materials, building operators can achieve optimal efficiency of their ventilation systems. The use of wood as a climate regulating material, through its potential hygrothermal mass and connected to weather prognoses, may provide up to 25% energy savings related to heating, cooling, and ventilation of a building.

Keywords: climate buffer, energy, hygrothermal mass, ventilation, wood, weather forecast

Procedia PDF Downloads 216
25161 Recommendations for Data Quality Filtering of Opportunistic Species Occurrence Data

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

Abstract:

In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 203
25160 Thermal Stability and Insulation of a Cement Mixture Using Graphene Oxide Nanosheets

Authors: Nasser A. M. Habib

Abstract:

The impressive physical properties of graphene derivatives, including thermal properties, have made them an attractive addition to advanced construction nanomaterial. In this study, we investigated the impact of incorporating low amounts of graphene oxide (GO) into cement mixture nanocomposites on their heat storage and thermal stability. The composites were analyzed using Fourier transmission infrared, thermo-gravimetric analysis, and field emission scanning electron microscopy. Results showed that GO significantly improved specific heat by 32%, reduced thermal conductivity by 16%, and reduced thermal decomposition to only 3% at a concentration of 1.2 wt%. These findings suggest that the cement mixture can withstand high temperatures and may suit specific applications requiring thermal stability and insulation properties.

Keywords: cement mixture composite, graphene oxide, thermal decomposition, thermal conductivity

Procedia PDF Downloads 69
25159 Data Quality Enhancement with String Length Distribution

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 318
25158 Microstructural and Transport Properties of La0.7Sr0.3CoO3 Thin Films Obtained by Metal-Organic Deposition

Authors: K. Daoudi, Z. Othmen, S. El Helali, M.Oueslati, M. Oumezzine

Abstract:

La0.7Sr0.3CoO3 thin films have been epitaxially grown on LaAlO3 and SrTiO3 (001) single-crystal substrates by metal organic deposition process. The structural and micro structural properties of the obtained films have been investigated by means of high resolution X-ray diffraction, Raman spectroscopy and transmission microscopy observations on cross-sections techniques. We noted a close dependence of the crystallinity on the used substrate and the film thickness. By increasing the annealing temperature to 1000ºC and the film thickness to 100 nm, the electrical resistivity was decreased by several orders of magnitude. The film resistivity reaches approximately 3~4 x10-4 Ω.cm in a wide interval of temperature 77-320 K, making this material a promising candidate for a variety of applications.

Keywords: cobaltite, thin films, epitaxial growth, MOD, TEM

Procedia PDF Downloads 333
25157 Soil Transmitted Helminth Infection and Associated Risk Factors among School Children in a Selected Barangay in the Philippines

Authors: Gil Soriano, Aubreyrose Casilang

Abstract:

Soil-transmitted helminth infection remains to be one of the leading public health problem worldwide, which is common in the rural developing regions especially among children. This study aimed to detect the presence of soil transmitted helminths among children and its associated transmission factors. Descriptive cross sectional research was the design used in the study and questionnaires were administered. Stool samples were collected among the samples (n=108) and were analyzed using kato thick method. Results showed that 61 out of 108 respondents are infected by soil transmitted helminth infection with A. lumbricoides the highest, followed by hookworm and T. trichuria. Parent's educational attainment, hand washing practices, and water sources were found to be associated with presence of Soil Transmitted Helminth infection.

Keywords: associated risk factors, barangay, school children, soil transmitted helminth infection

Procedia PDF Downloads 214
25156 Temporally Coherent 3D Animation Reconstruction from RGB-D Video Data

Authors: Salam Khalifa, Naveed Ahmed

Abstract:

We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

Procedia PDF Downloads 373
25155 Determining Abnomal Behaviors in UAV Robots for Trajectory Control in Teleoperation

Authors: Kiwon Yeom

Abstract:

Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

Procedia PDF Downloads 167
25154 The Impact of Hospital Intensive Care Unit Window Design on Daylighting and Energy Performance in Desert Climate

Authors: A. Sherif, H. Sabry, A. Elzafarany, M. Gadelhak, R. Arafa, M. Aly

Abstract:

This paper addresses the design of hospital Intensive Care Unit windows for the achievement of visual comfort and energy savings. The aim was to identify the window size and shading system configurations that could fulfill daylighting adequacy, avoid glare and reduce energy consumption. The study focused on addressing the effect of utilizing different shading systems in association with a range of Window-to-Wall Ratios (WWR) in different orientations under the desert clear-sky of Cairo, Egypt. The results of this study demonstrated that solar penetration is a critical concern affecting the design of ICU windows in desert locations, as in Cairo, Egypt. Use of shading systems was found to be essential in providing acceptable daylight performance and energy saving. Careful positioning of the ICU window towards a proper orientation can dramatically improve performance. It was observed that ICU windows facing the north direction enjoyed the widest range of successful window configuration possibilities at different WWRs. ICU windows facing south enjoyed a reasonable number of configuration options as well. By contrast, the ICU windows facing the east orientation had a very limited number of options that provide acceptable performance. These require additional local shading measures at certain times due to glare incidence. Moreover, use of horizontal sun breakers and solar screens to protect the ICU windows proved to be more successful than the other alternatives in a wide range of Window to Wall Ratios. By contrast, the use of light shelves and vertical shading devices seemed questionable.

Keywords: daylighting, desert, energy efficiency, shading

Procedia PDF Downloads 431
25153 Multidimensional Item Response Theory Models for Practical Application in Large Tests Designed to Measure Multiple Constructs

Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

Abstract:

This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

Procedia PDF Downloads 443
25152 Analysis of Production Forecasting in Unconventional Gas Resources Development Using Machine Learning and Data-Driven Approach

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 196
25151 Sustainability in Retaining Wall Construction with Geosynthetics

Authors: Sateesh Kumar Pisini, Swetha Priya Darshini, Sanjay Kumar Shukla

Abstract:

This paper seeks to present a research study on sustainability in construction of retaining wall using geosynthetics. Sustainable construction is a way for the building and infrastructure industry to move towards achieving sustainable development, taking into account environmental, socioeconomic and cultural issues. Geotechnical engineering, being very resource intensive, warrants an environmental sustainability study, but a quantitative framework for assessing the sustainability of geotechnical practices, particularly at the planning and design stages, does not exist. In geotechnical projects, major economic issues to be addressed are in the design and construction of stable slopes and retaining structures within space constraints. In this paper, quantitative indicators for assessing the environmental sustainability of retaining wall with geosynthetics are compared with conventional concrete retaining wall through life cycle assessment (LCA). Geosynthetics can make a real difference in sustainable construction techniques and contribute to development in developing countries in particular. Their imaginative application can result in considerable cost savings over the use of conventional designs and materials. The acceptance of geosynthetics in reinforced retaining wall construction has been triggered by a number of factors, including aesthetics, reliability, simple construction techniques, good seismic performance, and the ability to tolerate large deformations without structural distress. Reinforced retaining wall with geosynthetics is the best cost-effective and eco-friendly solution as compared with traditional concrete retaining wall construction. This paper presents an analysis of the theme of sustainability applied to the design and construction of traditional concrete retaining wall and presenting a cost-effective and environmental solution using geosynthetics.

Keywords: sustainability, retaining wall, geosynthetics, life cycle assessment

Procedia PDF Downloads 2060
25150 Nonlinear Dynamic Response of Helical Gear with Torque-Limiter

Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

Abstract:

This paper investigates the nonlinear dynamic response of a mechanical torque limiter which is used to protect drive parts from overload (helical transmission gears). The system is driven by four excitations: two external excitations (aerodynamics torque and force) and two internal excitations (two mesh stiffness fluctuations). In this work, we develop a dynamic model with lumped components and 28 degrees of freedom. We use the Runge Kutta step-by-step time integration numerical algorithm to solve the equations of motion obtained by Lagrange formalism. The numerical results have allowed us to identify the sources of vibration in the wind turbine. Also, they are useful to help the designer to make the right design and correctly choose the times for maintenance.

Keywords: two-stage helical gear, lumped model, dynamic response, torque-limiter

Procedia PDF Downloads 353
25149 Carrier Communication through Power Lines

Authors: Pavuluri Gopikrishna, B. Neelima

Abstract:

Power line carrier communication means audio power transmission via power line and reception of the amplified audio power at the receiver as in the form of speaker output signal using power line as the channel medium. The main objective of this suggested work is to transmit our message signal after frequency modulation by the help of FM modulator IC LM565 which gives output proportional to the input voltage of the input message signal. And this audio power is received from the power line by the help of isolation circuit and demodulated from IC LM565 which uses the concept of the PLL and produces FM demodulated signal to the listener. Message signal will be transmitted over the carrier signal that will be generated from the FM modulator IC LM565. Using this message signal will not damage because of no direct contact of message signal from the power line, but noise can disturb our information.

Keywords: amplification, fm demodulator ic 565, fm modulator ic 565, phase locked loop, power isolation

Procedia PDF Downloads 552
25148 The Prospect of Income Contingent Loan in Malaysia Higher Education Financing Using Deterministic and Stochastic Methods in Modelling Income

Authors: Syaza Isma, Timothy Higgins

Abstract:

In Malaysia, increased take-up rates of tertiary student borrowing, and reliance on retirement savings to fund children's education show the importance of public higher education financing schemes (PTPTN). PTPTN has been operating for 2 decades now; however, there are some critical issues and challenges that include low loan recovery and loan default that suggest a detailed consideration of student loan/financing scheme alternatives is crucial. In addition, the decline in funding level per student following introduction of the new PTPTN full and partial loan scheme has raised ongoing concerns over the sustainability of the scheme to provide continuous financial assistance to students in tertiary education. This research seeks to assess these issues that put greater efficiency in an effort to ensure equitable access to student funding for current and future generations. We explore the extent of repayment hardship under the current loan arrangements that presumably led to low recovery from the borrowers, particularly low-income graduates. The concept of manageable debt exists in the design of income-contingent repayment schemes, as practiced in Australia, New Zealand, UK, Hungary, USA (in limited form), the Netherlands, and South Korea. Can Income Contingent Loans (ICL) offer the best practice for an education financing scheme, and address the issue of repayment hardship and concurrently, can a properly designed ICL scheme provide a solution to the current issues and challenges facing Malaysia student financing? We examine the different potential ICL models using deterministic and stochastic approach to simulate income of graduates.

Keywords: deterministic, income contingent loan, repayment burden, simulation, stochastic

Procedia PDF Downloads 230
25147 Assessing Household Energy Savings and Consumer Behavior in Padang City

Authors: Prima Fithri, Lusi Susanti, Karin Bestarina

Abstract:

Indonesia's electrification ratio is still around 80.1%, which means that approximately 19.9% of households in Indonesia have not been getting the flow of electrical energy. Household electricity consumptions in Indonesia are generally still dominated by the public urban. In the city of Padang, West Sumatera, Indonesia, about 94.10% are power users of government services (PLN). The most important thing of the issue is human resources efficient energy. Consumer behavior in utilizing electricity becomes significant. Intensive questioner survey, in-depth interview and statistical analysis are carried out to collect scientific evidences of the behavioral based changes instruments to reduce electricity consumption in household sector. The questioner was developed to include five factors assuming affect the electricity consumption pattern in household sector. They are: attitude, energy price, household income, knowledge and other determinants. The survey was carried out in Padang, West Sumatra Province Indonesia. About 210 questioner papers were proportionally distributed to households in 11 districts in Padang. Stratified sampling was used as a method to select respondents. The results show that the household size, income, payment methods and size of house are factors affecting electricity saving behavior in residential sector. Household expenses on electricity are strongly influenced by gender, type of job, level of education, size of house, income, payment method and level of installed power. These results provide a scientific evidence for stakeholders on the potential of controlling electricity consumption and designing energy policy by government in residential sector.

Keywords: electricity, energy saving, household, behavior, policy

Procedia PDF Downloads 523
25146 Procedure Model for Data-Driven Decision Support Regarding the Integration of Renewable Energies into Industrial Energy Management

Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

Procedia PDF Downloads 435
25145 Dissimilarity-Based Coloring for Symbolic and Multivariate Data Visualization

Authors: K. Umbleja, M. Ichino, H. Yaguchi

Abstract:

In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

Procedia PDF Downloads 170
25144 Experimental Investigation of Absorbent Regeneration Techniques to Lower the Cost of Combined CO₂ and SO₂ Capture Process

Authors: Bharti Garg, Ashleigh Cousins, Pauline Pearson, Vincent Verheyen, Paul Feron

Abstract:

The presence of SO₂ in power plant flue gases makes flue gas desulfurization (FGD) an essential requirement prior to post combustion CO₂ (PCC) removal facilities. Although most of the power plants worldwide deploy FGD in order to comply with environmental regulations, generally the achieved SO₂ levels are not sufficiently low for the flue gases to enter the PCC unit. The SO₂ level in the flue gases needs to be less than 10 ppm to effectively operate the PCC installation. The existing FGD units alone cannot bring down the SO₂ levels to or below 10 ppm as required for CO₂ capture. It might require an additional scrubber along with the existing FGD unit to bring the SO₂ to the desired levels. The absence of FGD units in Australian power plants brings an additional challenge. SO₂ concentrations in Australian power station flue gas emissions are in the range of 100-600 ppm. This imposes a serious barrier on the implementation of standard PCC technologies in Australia. CSIRO’s developed CS-Cap process is a unique solution to capture SO₂ and CO₂ in a single column with single absorbent which can potentially bring cost-effectiveness to the commercial deployment of carbon capture in Australia, by removing the need for FGD. Estimated savings of removing SO₂ through a similar process as CS-Cap is around 200 MMUSD for a 500 MW Australian power plant. Pilot plant trials conducted to generate the proof of concept resulted in 100% removal of SO₂ from flue gas without utilising standard limestone-based FGD. In this work, removal of absorbed sulfur from aqueous amine absorbents generated in the pilot plant trials has been investigated by reactive crystallisation and thermal reclamation. More than 95% of the aqueous amines can be reclaimed back from the sulfur loaded absorbent via reactive crystallisation. However, the recovery of amines through thermal reclamation is limited and depends on the sulfur loading on the spent absorbent. The initial experimental work revealed that reactive crystallisation is a better fit for CS-Cap’s sulfur-rich absorbent especially when it is also capable of generating K₂SO₄ crystals of highly saleable quality ~ 99%. Initial cost estimation carried on both the technologies resulted in almost similar capital expenditure; however, the operating cost is considerably higher in thermal reclaimer than that in crystalliser. The experimental data generated in the laboratory from both the regeneration techniques have been used to generate the simulation model in Aspen Plus. The simulation model illustrates the economic benefits which could be gained by removing flue gas desulfurization prior to standard PCC unit and replacing it with a CS-Cap absorber column co-capturing CO₂ and SO₂, and it's absorbent regeneration system which would be either reactive crystallisation or thermal reclamation.

Keywords: combined capture, cost analysis, crystallisation, CS-Cap, flue gas desulfurisation, regeneration, sulfur, thermal reclamation

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25143 Improving Ghana's Oil Industry Through Integrated Operations

Authors: Esther Simpson, Evans Addo Tetteh

Abstract:

One of the most important sectors in Ghana’s economy is the oil and gas sector. Effective supply chain management is required to ensure the timely delivery of these products to the end users, given the rise in nationwide demand for petroleum products. Contrarily, freight forwarding plays a crucial role in facilitating intra- and intra-country trade, particularly the movement of oil goods. Nevertheless, there has not been enough scientific study done on how marketing, supply chain management, and freight forwarding are integrated in the oil business. By highlighting possible areas for development in the supply chain management of petroleum products, this article seeks to close this gap. The study was predominantly qualitative and featured semi-structured interviews with influential figures in the oil and gas sector, such as marketers, distributors, freight forwarders, and regulatory organizations. The purpose of the interviews was to determine the difficulties and possibilities for enhancing the management of the petroleum products supply chain. Thematic analysis was used to examine the data obtained in order to find patterns and themes that arose. The findings from the study revealed that the oil sector faced a number of issues in terms of supply chain management. Inadequate infrastructure, insufficient storage facilities, a lack of cooperation among parties, and an inadequate regulatory framework were among the obstacles. Furthermore, the study indicated significant prospects for enhancing petroleum product supply chain management, such as the integration of more advanced digital technologies, the formation of strategic alliances, and the adoption of sustainable practices in petroleum product supply chain management. The study's conclusions have far-reaching ramifications for the oil and gas sector, freight forwarding, and Ghana’s economy as a whole. Marketing, supply chain management, and freight forwarding has high prospects from being integrated to improve the efficiency of the petroleum product supply chain, resulting in considerable cost savings for the industry. Furthermore, the use of sustainable practices will improve the industry's sustainability and lessen the environmental effect of the petroleum product supply chain. Based on the findings, we propose that stakeholders in Ghana’s oil and gas sector work together and collaborate to enhance petroleum supply chain management. This collaboration should include the use of digital technologies, the formation of strategic alliances, and the implementation of sustainable practices. Moreover, we urge that governments establish suitable rules to guarantee the efficient and sustainable management of petroleum product supply chains. In conclusion, the integration and combination of marketing, supply chain management, and freight forwarding in the oil business gives a tremendous opportunity for enhancing petroleum product supply chain management. The study's conclusions have far-reaching ramifications for the sector, freight forwarding, and the economy as a whole. Using sustainable practices, integrating digital technology, and forming strategic alliances will improve the efficiency and sustainability of the petroleum product supply chain. We expect that this conference paper will encourage more study and collaboration among oil and gas sector stakeholders to improve petroleum supply chain management.

Keywords: collaboration, logistics, sustainability, supply chain management

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25142 The Impact of Data Science on Geography: A Review

Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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25141 Developing Structured Sizing Systems for Manufacturing Ready-Made Garments of Indian Females Using Decision Tree-Based Data Mining

Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

Procedia PDF Downloads 134