Search results for: multidimensional systems
4240 The Use of Artificial Intelligence in the Prevention of Micro and Macrovascular Complications in Type Diabetic Patients in Low and Middle-Income Countries
Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike
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Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes
Procedia PDF Downloads 1994239 Intelligent Quality Management System on the Example оf Bread Baking
Authors: Irbulat Utepbergenov, Lyazzat Issabekova, Shara Toybayeva
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This article discusses quality management using the bread baking process as an example. The baking process must be strictly controlled and repeatable. Automation and monitoring of quality management systems can help. After baking bread, quality control of the finished product should be carried out. This may include an evaluation of appearance, weight, texture, and flavor. It is important to continuously work to improve processes and products based on data and feedback from the quality management system. A method and model of automated quality management and an intelligent automated management system based on intelligent technologies are proposed, which allow to automate the processes of QMS implementation and support and improve the validity, efficiency, and effectiveness of management decisions by automating a number of functions of decision makers and staff. This project is supported by the grant of the Ministry of Education and Science of the Republic of Kazakhstan (Zhas Galym project No. AR 13268939 Research and development of digital technologies to ensure consistency of the carriers of normative documents of the quality management system).Keywords: automated control system, quality management, efficiency evaluation, bakery oven, intelligent system
Procedia PDF Downloads 404238 A Hybrid Digital Watermarking Scheme
Authors: Nazish Saleem Abbas, Muhammad Haris Jamil, Hamid Sharif
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Digital watermarking is a technique that allows an individual to add and hide secret information, copyright notice, or other verification message inside a digital audio, video, or image. Today, with the advancement of technology, modern healthcare systems manage patients’ diagnostic information in a digital way in many countries. When transmitted between hospitals through the internet, the medical data becomes vulnerable to attacks and requires security and confidentiality. Digital watermarking techniques are used in order to ensure the authenticity, security and management of medical images and related information. This paper proposes a watermarking technique that embeds a watermark in medical images imperceptibly and securely. In this work, digital watermarking on medical images is carried out using the Least Significant Bit (LSB) with the Discrete Cosine Transform (DCT). The proposed methods of embedding and extraction of a watermark in a watermarked image are performed in the frequency domain using LSB by XOR operation. The quality of the watermarked medical image is measured by the Peak signal-to-noise ratio (PSNR). It was observed that the watermarked medical image obtained performing XOR operation between DCT and LSB survived compression attack having a PSNR up to 38.98.Keywords: watermarking, image processing, DCT, LSB, PSNR
Procedia PDF Downloads 504237 Pancreatic Lipase and Cholesterol Esterase Inhibitors from Thai Medicinal Plants
Authors: Kwanchai Ratanamanee, Pattra Ahmadi Pirshahid, Yaowaluk Khamphan, Sirinan Thubthimthad
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Obesity is a main global health problem. The obesity rated has continued to be higher and higher. It causes to serious systems, diabetes, coronary artery disease, stroke, and some types of cancer. Oristat is one of the best drugs worldwide used as a pancreatic lipase inhibitor. To develop the new therapeutic drugs from medicinal plant always explored. In this study, 24 medicinal plants were investigated for their pancreatic lipase and cholesterol esterase inhibitory effects with Fluorometer assay and oristat as a positive control. It showed that the ethanolic extract of pods of Acacia concinna (Willd.) D.C., possess pancreatic lipase and cholesterol esterase inhibitory activities of IC50 at 2.73 and 3.77 mg/ml respectively as well as oral acute toxicity of the extract (LD50) was 6,300 mg/kg body weight. The extract of A.concinna should be further investigated in animal testing. The results of pancreatic lipase and cholesterol esterase inhibitor of the extracts will lead us to utilize A.concinna for developing as obesity dietary supplement from a medicinal plant.Keywords: Acacia concinna (Willd.) D. C., cholesterol esterase, obesity, pancreatic lipase
Procedia PDF Downloads 4804236 Optimized Dynamic Bayesian Networks and Neural Verifier Test Applied to On-Line Isolated Characters Recognition
Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou
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In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks
Procedia PDF Downloads 6194235 Development of Thermo-Regulating Fabric Using Microcapsules of Phase Change Material
Authors: D. Benmoussa, H. Hannache, O. Cherkaoui
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In textiles, the major interest in microencapsulation is currently in the application of durable fragrances, skin softeners, phase-change materials, antimicrobial agents and drug delivery systems onto textile materials. In our research “Polyethylene Glycol” was applied as phase change material and it was encapsulated in polymethacrylic acid (PMA) by radical polymerization in suspension of methacrylic acid in presence of N,N'-methylenebisacrylamide (MBAM) as crosslinking agent. Thereafter the obtained microcapsule was modified by amidation with ethylenediamine as a spacer molecule. At the end of this spacer trichlorotriazine reactive group was fixed. Microcapsules were grafted onto cotton textile substrate. The surface morphologies of the microencapsulated phase change materials (micro PCMs) were studied by scanning electron microscopy (SEM). Thermal properties, thermal reliabilities and thermal stabilities of the as-prepared micro PCMs were investigated by differential scanning calorimetry (DSC) and thermogravmetric analysis (TGA). The results obtained show the obtaining microcapsules with a mean diameter of 10 µm and the resistance of the microcapsules is demonstrated by thermal analysis.Keywords: energy storage, microencapsulation, phase-change materials, thermogravmetric analysis (TGA)
Procedia PDF Downloads 6764234 E-Learning Network Support Services: A Comparative Case Study of Australian and United States Universities
Authors: Sayed Hadi Sadeghi
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This research study examines the current state of support services for e-network practice in an Australian and an American university. It identifies information that will be of assistance to Australian and American universities to improve their existing online programs. The study investigated the two universities using a quantitative methodological approach. Participants were students, lecturers and admins of universities engaged with online courses and learning management systems. The support services for e-network practice variables, namely academic support services, administrative support and technical support, were investigated for e-practice. Evaluations of e-network support service and its sub factors were above average and excellent in both countries, although the American admins and lecturers tended to evaluate this factor higher than others did. Support practice was evaluated higher by all participants of an American university than by Australians. One explanation for the results may be that most suppliers of the Australian university e-learning system were from eastern Asian cultural backgrounds with a western networking support perspective about e-learning.Keywords: support services, e-Network practice, Australian universities, United States universities
Procedia PDF Downloads 1644233 A Dynamic Approach for Evaluating the Climate Change Risks on Building Performance
Authors: X. Lu, T. Lu, S. Javadi
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A simple dynamic approach is presented for analyzing thermal and moisture dynamics of buildings, which is of particular relevance to understanding climate change impacts on buildings, including assessment of risks and applications of resilience strategies. With the goal to demonstrate the proposed modeling methodology, to verify the model, and to show that wooden materials provide a mechanism that can facilitate the reduction of moisture risks and be more resilient to global warming, a wooden church equipped with high precision measurement systems was taken as a test building for full-scale time-series measurements. Sensitivity analyses indicate a high degree of accuracy in the model prediction regarding the indoor environment. The model is then applied to a future projection of climate indoors aiming to identify significant environmental factors, the changing temperature and humidity, and effective response to the climate change impacts. The paper suggests that wooden building materials offer an effective and resilient response to anticipated future climate changes.Keywords: dynamic model, forecast, climate change impact, wooden structure, buildings
Procedia PDF Downloads 1534232 Distribution System Modelling: A Holistic Approach for Harmonic Studies
Authors: Stanislav Babaev, Vladimir Cuk, Sjef Cobben, Jan Desmet
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The procedures for performing harmonic studies for medium-voltage distribution feeders have become relatively mature topics since the early 1980s. The efforts of various electric power engineers and researchers were mainly focused on handling large harmonic non-linear loads connected scarcely at several buses of medium-voltage feeders. In order to assess the impact of these loads on the voltage quality of the distribution system, specific modeling and simulation strategies were proposed. These methodologies could deliver a reasonable estimation accuracy given the requirements of least computational efforts and reduced complexity. To uphold these requirements, certain analysis assumptions have been made, which became de facto standards for establishing guidelines for harmonic analysis. Among others, typical assumptions include balanced conditions of the study and the negligible impact of impedance frequency characteristics of various power system components. In latter, skin and proximity effects are usually omitted, and resistance and reactance values are modeled based on the theoretical equations. Further, the simplifications of the modelling routine have led to the commonly accepted practice of neglecting phase angle diversity effects. This is mainly associated with developed load models, which only in a handful of cases are representing the complete harmonic behavior of a certain device as well as accounting on the harmonic interaction between grid harmonic voltages and harmonic currents. While these modelling practices were proven to be reasonably effective for medium-voltage levels, similar approaches have been adopted for low-voltage distribution systems. Given modern conditions and massive increase in usage of residential electronic devices, recent and ongoing boom of electric vehicles, and large-scale installing of distributed solar power, the harmonics in current low-voltage grids are characterized by high degree of variability and demonstrate sufficient diversity leading to a certain level of cancellation effects. It is obvious, that new modelling algorithms overcoming previously made assumptions have to be accepted. In this work, a simulation approach aimed to deal with some of the typical assumptions is proposed. A practical low-voltage feeder is modeled in PowerFactory. In order to demonstrate the importance of diversity effect and harmonic interaction, previously developed measurement-based models of photovoltaic inverter and battery charger are used as loads. The Python-based script aiming to supply varying voltage background distortion profile and the associated current harmonic response of loads is used as the core of unbalanced simulation. Furthermore, the impact of uncertainty of feeder frequency-impedance characteristics on total harmonic distortion levels is shown along with scenarios involving linear resistive loads, which further alter the impedance of the system. The comparative analysis demonstrates sufficient differences with cases when all the assumptions are in place, and results indicate that new modelling and simulation procedures need to be adopted for low-voltage distribution systems with high penetration of non-linear loads and renewable generation.Keywords: electric power system, harmonic distortion, power quality, public low-voltage network, harmonic modelling
Procedia PDF Downloads 1614231 Models, Methods and Technologies for Protection of Critical Infrastructures from Cyber-Physical Threats
Authors: Ivan Župan
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Critical infrastructure is essential for the functioning of a country and is designated for special protection by governments worldwide. Due to the increase in smart technology usage in every facet of the industry, including critical infrastructure, the exposure to malicious cyber-physical attacks has grown in the last few years. Proper security measures must be undertaken in order to defend against cyber-physical threats that can disrupt the normal functioning of critical infrastructure and, consequently the functioning of the country. This paper provides a review of the scientific literature of models, methods and technologies used to protect from cyber-physical threats in industries. The focus of the literature was observed from three aspects. The first aspect, resilience, concerns itself with the robustness of the system’s defense against threats, as well as preparation and education about potential future threats. The second aspect concerns security risk management for systems with cyber-physical aspects, and the third aspect investigates available testbed environments for testing developed models on scaled models of vulnerable infrastructure.Keywords: critical infrastructure, cyber-physical security, smart industry, security methodology, security technology
Procedia PDF Downloads 774230 PM Electrical Machines Diagnostic: Methods Selected
Authors: M. Barański
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This paper presents a several diagnostic methods designed to electrical machines especially for permanent magnets (PM) machines. Those machines are commonly used in small wind and water systems and vehicles drives. Those methods are preferred by the author in periodic diagnostic of electrical machines. The special attention should be paid to diagnostic method of turn-to-turn insulation and vibrations. Both of those methods were created in Institute of Electrical Drives and Machines Komel. The vibration diagnostic method is the main thesis of author’s doctoral dissertation. This is method of determination the technical condition of PM electrical machine basing on its own signals is the subject of patent application No P.405669. Specific structural properties of machines excited by permanent magnets are used in this method - electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical machines with permanent magnets and there was no method found to determine the technical condition of such machine basing on their own signals.Keywords: electrical vehicle, generator, main insulation, permanent magnet, thermography, turn-to-traction drive, turn insulation, vibrations
Procedia PDF Downloads 4024229 Deterministic Random Number Generator Algorithm for Cryptosystem Keys
Authors: Adi A. Maaita, Hamza A. A. Al Sewadi
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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfills Shannon’s principle of “confusion and diffusion”. ASCII code characters wereutilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.Keywords: cryptosystems, information security agreement, key distribution, random numbers
Procedia PDF Downloads 2694228 Achievable Average Secrecy Rates over Bank of Parallel Independent Fading Channels with Friendly Jamming
Authors: Munnujahan Ara
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In this paper, we investigate the effect of friendly jamming power allocation strategies on the achievable average secrecy rate over a bank of parallel fading wiretap channels. We investigate the achievable average secrecy rate in parallel fading wiretap channels subject to Rayleigh and Rician fading. The achievable average secrecy rate, due to the presence of a line-of-sight component in the jammer channel is also evaluated. Moreover, we study the detrimental effect of correlation across the parallel sub-channels, and evaluate the corresponding decrease in the achievable average secrecy rate for the various fading configurations. We also investigate the tradeoff between the transmission power and the jamming power for a fixed total power budget. Our results, which are applicable to current orthogonal frequency division multiplexing (OFDM) communications systems, shed further light on the achievable average secrecy rates over a bank of parallel fading channels in the presence of friendly jammers.Keywords: fading parallel channels, wire-tap channel, OFDM, secrecy capacity, power allocation
Procedia PDF Downloads 5124227 Kinematic Hardening Parameters Identification with Respect to Objective Function
Authors: Marina Franulovic, Robert Basan, Bozidar Krizan
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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.Keywords: genetic algorithm, kinematic hardening, material model, objective function
Procedia PDF Downloads 3344226 Cost-Effective Indoor-Air Quality (IAQ) Monitoring via Cavity Enhanced Photoacoustic Technology
Authors: Jifang Tao, Fei Gao, Hong Cai, Yuan Jin Zheng, Yuan Dong Gu
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Photoacoustic technology is used to measure effect absorption of a light by means of acoustic detection, which provides a high sensitive, low-cross response, cost-effective solution for gas molecular detection. In this paper, we proposed an integrated photoacoustic sensor for Indoor-air quality (IAQ) monitoring. The sensor consists of an acoustically resonant cavity, a high silicon acoustic transducer chip, and a low-cost light source. The light is modulated at the resonant frequency of the cavity to create an enhanced periodic heating and result in an amplified acoustic pressure wave. The pressure is readout by a novel acoustic transducer with low noise. Based on this photoacoustic sensor, typical indoor gases, including CO2, CO, O2, and H2O have been successfully detected, and their concentration are also evaluated with very high accuracy. It has wide potential applications in IAQ monitoring for agriculture, food industry, and ventilation control systems used in public places, such as schools, hospitals and airports.Keywords: indoor-air quality (IAQ) monitoring, photoacoustic gas sensor, cavity enhancement, integrated gas sensor
Procedia PDF Downloads 6594225 Predictability of Supply Chain in Indian Automobile Division
Authors: Dharamvir Mangal
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Supply chain management has increasingly become an inevitable challenge to most companies to continuously survive and prosper in the global chain-based competitive environment. The current challenges of the Indian automotive world, their implications on supply chain are summarized and analyzed in this paper. In this competitive era of ‘LPG’ i.e. Liberalization, Privatization and Globalization, modern marketing systems, introduction of products with short life cycles, and the discriminating expectations of customers have enforced business enterprises to invest in and focus attention on their Supply Chains (SCs) in order to meet out the level of customer’s satisfaction and to survive in the competitive market. In fact, many of trends in the auto industry are reinforcing the need to redefine supply chain strategies layouts, and operations etc. Many manufacturing operations are designed to maximize throughput and lower costs with modest considerations for the crash on inventory levels and distribution capabilities. To improve profitability and efficiency, automotive players are seeking ways to achieve operational excellence, reduce operating cost and enhance customer service through efficient supply chain management.Keywords: automotive industry, supply chain, challenges, market potential
Procedia PDF Downloads 3314224 Socio-Economic Modelling Approaches Linked to Water Quality: A Review
Authors: Aurelia Samuel
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Socio-economic modelling approaches linked to water management have contributed to impact assessments of agricultural policies and management practices on water quality at catchment level. With an increasing interest in informing water management policy that considers complex links between socioeconomic factors, climate change, agricultural production, and water quality, several models have been developed and applied in the literature to capture these relationships. This paper offers an overview of socio-economic approaches that have been incorporated within an integrated framework. It also highlights how data gaps on socio-economic factors have been addressed using forecasting techniques. Findings of the review show that while integrated frameworks have the potential to account for complexities within dynamic systems, they generally do not provide direct, measurable financial impact of socio-economic factors on biophysical water parameters that affect water quality. The paper concludes with a recommendation that modelling framework is kept simple to make it more transparent and easier to capture the most important relationship.Keywords: financial impact, integrated framework, socio-economic modelling, water quality
Procedia PDF Downloads 1514223 Path Integrals and Effective Field Theory of Large Scale Structure
Authors: Revant Nayar
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In this work, we recast the equations describing large scale structure, and by extension all nonlinear fluids, in the path integral formalism. We first calculate the well known two and three point functions using Schwinger Keldysh formalism used commonly to perturbatively solve path integrals in non- equilibrium systems. Then we include EFT corrections due to pressure, viscosity, and noise as effects on the time-dependent propagator. We are able to express results for arbitrary two and three point correlation functions in LSS in terms of differential operators acting on a triple K master intergral. We also, for the first time, get analytical results for more general initial conditions deviating from the usual power law P∝kⁿ by introducing a mass scale in the initial conditions. This robust field theoretic formalism empowers us with tools from strongly coupled QFT to study the strongly non-linear regime of LSS and turbulent fluid dynamics such as OPE and holographic duals. These could be used to capture fully the strongly non-linear dynamics of fluids and move towards solving the open problem of classical turbulence.Keywords: quantum field theory, cosmology, effective field theory, renormallisation
Procedia PDF Downloads 1354222 Artificial Intelligence and Cybernetics in Bertrand Russell’s Philosophy
Authors: Djoudi Ali
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In this article, we shall expose some of the more interesting interactions of philosophy and cybernetics, some philosophical issues arising in cybernetic systems, and some questions in philosophy of our daily life related to the artificial intelligence. Many of these are fruitfully explored in the article..This article will shed light also on the importance of science and technology in our life and what are the main problems of misusing the latest technologies known under artificial intelligence and cybernatics acoording to Bertrand Russell’s point of view; then to analyse his project of reforms inculding science progress risks , the article show also the whole aspect of the impact of technology on peace , nature and on individual daily behavior, we shall discuss all issues and defies imposing by this new era , The article will invest in showing what Russell will suggest to eliminate or to slow down the dangers of these changes and what are the main solutions to protect the indiviual’s rights and responsiblities In this article, We followed a different methodology, like analysis method and sometimes the historical or descriptive method, without forgetting criticizing some conclusions when it is logically needed In the end, we mentioned what is supposed to be solutions suggested by Bertrand Russell that should be taken into considerations during the next decades and how to protect our ennvironement and the human being of any risk of disappearingKeywords: artificial intelligence, technology, cybernetics, sience
Procedia PDF Downloads 1254221 Data Mining Meets Educational Analysis: Opportunities and Challenges for Research
Authors: Carla Silva
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Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.Keywords: data mining, research analysis, investment decision-making, educational research
Procedia PDF Downloads 3584220 Survey on Fiber Optic Deployment for Telecommunications Operators in Ghana: Coverage Gap, Recommendations and Research Directions
Authors: Francis Padi, Solomon Nunoo, John Kojo Annan
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The paper "Survey on Fiber Optic Deployment for Telecommunications Operators in Ghana: Coverage Gap, Recommendations and Research Directions" presents a comprehensive survey on the deployment of fiber optic networks for telecommunications operators in Ghana. It addresses the challenges encountered by operators using microwave transmission systems for backhauling traffic and emphasizes the advantages of deploying fiber optic networks. The study delves into the coverage gap, provides recommendations, and outlines research directions to enhance the telecommunications infrastructure in Ghana. Additionally, it evaluates next-generation optical access technologies and architectures tailored to operators' needs. The paper also investigates current technological solutions and regulatory, technical, and economical dimensions related to sharing mobile telecommunication networks in emerging countries. Overall, this paper offers valuable insights into fiber optic network deployment for telecommunications operators in Ghana and suggests strategies to meet the increasing demand for data and mobile applications.Keywords: survey on fiber optic deployment, coverage gap, recommendations, research directions
Procedia PDF Downloads 244219 Reduction of Energy Consumption Using Smart Home Techniques in the Household Sector
Authors: Ahmed Al-Adaileh, Souheil Khaddaj
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Outcomes of exhaustion of natural resources started influencing each spirit on this planet. Energy is an essential factor in this aspect. To restore the circumstance to the appropriate track, all attempts must focus on two fundamental branches: producing electricity from clean and renewable reserves and decreasing the overall unnecessary consumption of energy. The focal point of this paper will be on lessening the power consumption in the household's segment. This paper is an attempt to give a clear understanding of a framework called Reduction of Energy Consumption in Household Sector (RECHS) and how it should help householders to reduce their power consumption by substituting their household appliances, turning-off the appliances when stand-by modus is detected, and scheduling their appliances operation periods. Technically, the framework depends on utilizing Z-Wave compatible plug-ins which will be connected to the usual house devices to gauge and control them remotely and semi-automatically. The suggested framework underpins numerous quality characteristics, for example, integrability, scalability, security and adaptability.Keywords: smart energy management systems, internet of things, wireless mesh networks, microservices, cloud computing, big data
Procedia PDF Downloads 1984218 Protective Role of Peroxiredoxin V against Ischemia/Reperfusion-Induced Acute Kidney Injury in Mice
Authors: Eun Gyeong Lee, Ji Young Park, Hyun Ae Woo
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Reactive oxygen species (ROS) production is involved in ischemia/reperfusion (I/R) injury in kidney of mice. Oxidative stress develops from an imbalance between ROS production and reduced antioxidant defenses. Many enzymatic and nonenzymatic antioxidant systems including peroxiredoxins (Prxs) are present in kidney to maintain an appropriate level of ROS and prevent oxidative damage. Prxs are a family of peroxidases that reduce peroxides, with a conserved cysteine residue serving as the site of oxidation by peroxides. In this study, we examined the protective role of Prx V against I/R-induced acute kidney injury (AKI) using Prx V wild type (WT) and knockout (KO) mice. We compared the response of Prx V WT and KO mice in mice model of I/R injury. Renal structure, functions, oxidative stress markers, protein levels of oxidative damage marker were worse in Prx V KO mice. Ablation of Prx V enhanced susceptibility to I/R-induced oxidative stress. Prx V KO mice were seen to have more severe renal damage than Prx V WT mice in mice model of I/R injury. Our results demonstrate that Prx V is protective against I/R-induced AKI.Keywords: peroxiredoxin, ischemia/reperfusion, kidney, oxidative stress
Procedia PDF Downloads 3874217 Environmentally Sustainable Transparent Wood: A Fully Green Approach from Bleaching to Impregnation for Energy-Efficient Engineered Wood Components
Authors: Francesca Gullo, Paola Palmero, Massimo Messori
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Transparent wood is considered a promising structural material for the development of environmentally friendly, energy-efficient engineered components. To obtain transparent wood from natural wood materials two approaches can be used: i) bottom-up and ii) top-down. Through the second method, the color of natural wood samples is lightened through a chemical bleaching process that acts on chromophore groups of lignin, such as the benzene ring, quinonoid, vinyl, phenolics, and carbonyl groups. These chromophoric units form complex conjugate systems responsible for the brown color of wood. There are two strategies to remove color and increase the whiteness of wood: i) lignin removal and ii) lignin bleaching. In the lignin removal strategy, strong chemicals containing chlorine (chlorine, hypochlorite, and chlorine dioxide) and oxidizers (oxygen, ozone, and peroxide) are used to completely destroy and dissolve the lignin. In lignin bleaching methods, a moderate reductive (hydrosulfite) or oxidative (hydrogen peroxide) is commonly used to alter or remove the groups and chromophore systems of lignin, selectively discoloring the lignin while keeping the macrostructure intact. It is, therefore, essential to manipulate nanostructured wood by precisely controlling the nanopores in the cell walls by monitoring both chemical treatments and process conditions, for instance, the treatment time, the concentration of chemical solutions, the pH value, and the temperature. The elimination of wood light scattering is the second step in the fabrication of transparent wood materials, which can be achieved through two-step approaches: i) the polymer impregnation method and ii) the densification method. For the polymer impregnation method, the wood scaffold is treated with polymers having a corresponding refractive index (e.g., PMMA and epoxy resins) under vacuum to obtain the transparent composite material, which can finally be pressed to align the cellulose fibers and reduce interfacial defects in order to have a finished product with high transmittance (>90%) and excellent light-guiding. However, both the solution-based bleaching and the impregnation processes used to produce transparent wood generally consume large amounts of energy and chemicals, including some toxic or pollutant agents, and are difficult to scale up industrially. Here, we report a method to produce optically transparent wood by modifying the lignin structure with a chemical reaction at room temperature using small amounts of hydrogen peroxide in an alkaline environment. This method preserves the lignin, which results only deconjugated and acts as a binder, providing both a strong wood scaffold and suitable porosity for infiltration of biobased polymers while reducing chemical consumption, the toxicity of the reagents used, polluting waste, petroleum by-products, energy and processing time. The resulting transparent wood demonstrates high transmittance and low thermal conductivity. Through the combination of process efficiency and scalability, the obtained materials are promising candidates for application in the field of construction for modern energy-efficient buildings.Keywords: bleached wood, energy-efficient components, hydrogen peroxide, transparent wood, wood composites
Procedia PDF Downloads 554216 Identifying Degradation Patterns of LI-Ion Batteries from Impedance Spectroscopy Using Machine Learning
Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee
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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis
Procedia PDF Downloads 1504215 Microstrip Bandpass Filter with Wide Stopband and High Out-of-Band Rejection Based on Inter-Digital Capacitor
Authors: Mohamad Farhat, Bal Virdee
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This paper present a compact Microstrip Bandpass filter exhibiting a very wide stop band and high selectivity. The filter comprises of asymmetric resonator structures, which are interconnected by an inter-digital capacitor to enable the realization of a wide bandwidth with high rejection level. High selectivity is obtained by optimizing the parameters of the interdigital capacitor. The filter has high out-of-band rejection (> 30 dB), less than 0.6 dB of insertion-loss, up to 5.5 GHz spurii free, and about 18 dB of return-loss. Full-wave electromagnetic simulator ADSTM (Mom) is used to analyze and optimize the prototype bandpass filter. The proposed technique was verified practically to validate the design methodology. The experimental results of the prototype circuit are presented and a good agreement was obtained comparing with the simulation results. The dimensions of the proposed filter are 32 x 24 mm2.The filter’s characteristics and compact size make it suitable for wireless communication systems.Keywords: asymmetric resonator, bandpass filter, microstrip, spurious suppression, ultra-wide stop band
Procedia PDF Downloads 1894214 An Integrated Approach to the Carbonate Reservoir Modeling: Case Study of the Eastern Siberia Field
Authors: Yana Snegireva
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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model
Procedia PDF Downloads 764213 Optimizing Telehealth Internet of Things Integration: A Sustainable Approach through Fog and Cloud Computing Platforms for Energy Efficiency
Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo
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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.Keywords: energy-efficient, fog computing, IoT, telehealth
Procedia PDF Downloads 794212 The Study on Life of Valves Evaluation Based on Tests Data
Authors: Binjuan Xu, Qian Zhao, Ping Jiang, Bo Guo, Zhijun Cheng, Xiaoyue Wu
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Astronautical valves are key units in engine systems of astronautical products; their reliability will influence results of rocket or missile launching, even lead to damage to staff and devices on the ground. Besides failure in engine system may influence the hitting accuracy and flight shot of missiles. Therefore high reliability is quite essential to astronautical products. There are quite a few literature doing research based on few failure test data to estimate valves’ reliability, thus this paper proposed a new method to estimate valves’ reliability, according to the corresponding tests of different failure modes, this paper takes advantage of tests data which acquired from temperature, vibration, and action tests to estimate reliability in every failure modes, then this paper has regarded these three kinds of tests as three stages in products’ process to integrate these results to acquire valves’ reliability. Through the comparison of results achieving from tests data and simulated data, the results have illustrated how to obtain valves’ reliability based on the few failure data with failure modes and prove that the results are effective and rational.Keywords: censored data, temperature tests, valves, vibration tests
Procedia PDF Downloads 3474211 Comparison between Post- and Oxy-Combustion Systems in a Petroleum Refinery Unit Using Modeling and Optimization
Authors: Farooq A. Al-Sheikh, Ali Elkamel, William A. Anderson
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A fluidized catalytic cracking unit (FCCU) is one of the effective units in many refineries. Modeling and optimization of FCCU were done by many researchers in past decades, but in this research, comparison between post- and oxy-combustion was studied in the regenerator-FCCU. Therefore, a simplified mathematical model was derived by doing mass/heat balances around both reactor and regenerator. A state space analysis was employed to show effects of the flow rates variables such as air, feed, spent catalyst, regenerated catalyst and flue gas on the output variables. The main aim of studying dynamic responses is to figure out the most influencing variables that affect both reactor/regenerator temperatures; also, finding the upper/lower limits of the influencing variables to ensure that temperatures of the reactors and regenerator work within normal operating conditions. Therefore, those values will be used as side constraints in the optimization technique to find appropriate operating regimes. The objective functions were modeled to be maximizing the energy in the reactor while minimizing the energy consumption in the regenerator. In conclusion, an oxy-combustion process can be used instead of a post-combustion one.Keywords: FCCU modeling, optimization, oxy-combustion, post-combustion
Procedia PDF Downloads 211