Search results for: hybrid genetic algorithms
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4832

Search results for: hybrid genetic algorithms

3572 Multiobjective Economic Dispatch Using Optimal Weighting Method

Authors: Mandeep Kaur, Fatehgarh Sahib

Abstract:

The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

Procedia PDF Downloads 132
3571 Troubleshooting Petroleum Equipment Based on Wireless Sensors Based on Bayesian Algorithm

Authors: Vahid Bayrami Rad

Abstract:

In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

Procedia PDF Downloads 48
3570 A User Interface for Easiest Way Image Encryption with Chaos

Authors: D. López-Mancilla, J. M. Roblero-Villa

Abstract:

Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

Procedia PDF Downloads 471
3569 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

Abstract:

The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

Procedia PDF Downloads 158
3568 Systematic Taxonomy and Phylogenetic of Commercial Fish Species of Family Nemipetridae from Malaysian Waters and Neighboring Seas

Authors: Ayesha Imtiaz, Darlina Md. Naim

Abstract:

Family Nemipteridae is among the most abundantly distributed family in Malaysian fish markets due to its high contribution to landing sites of Malaysia. Using an advanced molecular approach that used two mitochondrial (Cytochrome oxidase c I and Cytochrome oxidase b) and one nuclear gene (Recombination activating gene, RAGI) to expose cryptic diversity and phylogenetic relationships among commercially important species of family Nemipteridae. Our research covered all genera (including 31 species out total 45 species) of family Nemipteridae, distributed in Malaysia. We also found certain type of geographical barriers in the South China sea that reduces dispersal and stops a few species to intermix. Northside of the South China Sea (near Vietnam) does not allow genetic diversity to mix with the Southern side of the South China sea (Sarawak) and reduces dispersal. Straits of Malacca reduce the intermixing genetic diversity of South China Sea and the Indian Ocean.

Keywords: Nemipteridae, RAG I, south east Asia, Malaysia

Procedia PDF Downloads 131
3567 Titanium Nitride @ Nitrogen-doped Carbon Nanocage as High-performance Cathodes for Aqueous Zn-ion Hybrid Supercapacitors

Authors: Ye Ling, Ruan Haihui

Abstract:

Aqueous Zn-ion hybrid supercapacitors (AZHSCs) pertain to a new type of electrochemical energy storage device that has received considerable attention. They integrate the advantages of high-energy Zn-ion batteries and high-power supercapacitors to meet the demand for low-cost, long-term durability, and high safety. Nevertheless, the challenge caused by the finite ion adsorption/desorption capacity of carbon electrodes gravely limits their energy densities. This work describes titanium nitride@nitrogen-doped carbon nanocage (TiN@NCNC) composite cathodes for AZHSCs to achieve a greatly improved energy density, and the composites can be facile synthesized based on the calcination of a mixture of tetrabutyl titanate and zeolitic imidazolate framework-8 in argon atmosphere. The resulting composites are featured by the ultra-fine TiN particles dispersed uniformly on the NCNC surfaces, enhancing the Zn2+ storage capabilities. Using TiN@NCNC cathodes, the AZHSCs can operate stably with a high energy density of 154 Wh kg-¹ at a specific power of 270 W kg-¹ and achieve a remarkable capacity retention of 88.9% after 104 cycles at 5 A g-¹. At an extreme specific power of 8.7 kW kg-1, the AZHSCs can retain an energy density of 97.2 Wh kg-1. With these results, we stress that the TiN@NCNC cathodes render high-performance AZHSCs, and the facile one-pot method can easily be scaled up, which enables AZHSCs a new energy-storage component for managing intermitted renewable energy sources.

Keywords: Zn-ion hybrid supercapacitors, ion absorption/desorption reactions, titanium nitride, zeolitic imidazolate framework-8

Procedia PDF Downloads 21
3566 Surface Modified Quantum Dots for Nanophotonics, Stereolithography and Hybrid Systems for Biomedical Studies

Authors: Redouane Krini, Lutz Nuhn, Hicham El Mard Cheol Woo Ha, Yoondeok Han, Kwang-Sup Lee, Dong-Yol Yang, Jinsoo Joo, Rudolf Zentel

Abstract:

To use Quantum Dots (QDs) in the two photon initiated polymerization technique (TPIP) for 3D patternings, QDs were modified on the surface with photosensitive end groups which are able to undergo a photopolymerization. We were able to fabricate fluorescent 3D lattice structures using photopatternable QDs by TPIP for photonic devices such as photonic crystals and metamaterials. The QDs in different diameter have different emission colors and through mixing of RGB QDs white light fluorescent from the polymeric structures has been created. Metamaterials are capable for unique interaction with the electrical and magnetic components of the electromagnetic radiation and for manipulating light it is crucial to have a negative refractive index. In combination with QDs via TPIP technique polymeric structures can be designed with properties which cannot be found in nature. This makes these artificial materials gaining a huge importance for real-life applications in photonic and optoelectronic. Understanding of interactions between nanoparticles and biological systems is of a huge interest in the biomedical research field. We developed a synthetic strategy of polymer functionalized nanoparticles for biomedical studies to obtain hybrid systems of QDs and copolymers with a strong binding network in an inner shell and which can be modified in the end through their poly(ethylene glycol) functionalized outer shell. These hybrid systems can be used as models for investigation of cell penetration and drug delivery by using measurements combination between CryoTEM and fluorescence studies.

Keywords: biomedical study models, lithography, photo induced polymerization, quantum dots

Procedia PDF Downloads 509
3565 Accounting for Downtime Effects in Resilience-Based Highway Network Restoration Scheduling

Authors: Zhenyu Zhang, Hsi-Hsien Wei

Abstract:

Highway networks play a vital role in post-disaster recovery for disaster-damaged areas. Damaged bridges in such networks can disrupt the recovery activities by impeding the transportation of people, cargo, and reconstruction resources. Therefore, rapid restoration of damaged bridges is of paramount importance to long-term disaster recovery. In the post-disaster recovery phase, the key to restoration scheduling for a highway network is prioritization of bridge-repair tasks. Resilience is widely used as a measure of the ability to recover with which a network can return to its pre-disaster level of functionality. In practice, highways will be temporarily blocked during the downtime of bridge restoration, leading to the decrease of highway-network functionality. The failure to take downtime effects into account can lead to overestimation of network resilience. Additionally, post-disaster recovery of highway networks is generally divided into emergency bridge repair (EBR) in the response phase and long-term bridge repair (LBR) in the recovery phase, and both of EBR and LBR are different in terms of restoration objectives, restoration duration, budget, etc. Distinguish these two phases are important to precisely quantify highway network resilience and generate suitable restoration schedules for highway networks in the recovery phase. To address the above issues, this study proposes a novel resilience quantification method for the optimization of long-term bridge repair schedules (LBRS) taking into account the impact of EBR activities and restoration downtime on a highway network’s functionality. A time-dependent integer program with recursive functions is formulated for optimally scheduling LBR activities. Moreover, since uncertainty always exists in the LBRS problem, this paper extends the optimization model from the deterministic case to the stochastic case. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. The proposed methods are tested using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that, in this case, neglecting the bridge restoration downtime can lead to approximately 15% overestimation of highway network resilience. Moreover, accounting for the impact of EBR on network functionality can help to generate a more specific and reasonable LBRS. The theoretical and practical values are as follows. First, the proposed network recovery curve contributes to comprehensive quantification of highway network resilience by accounting for the impact of both restoration downtime and EBR activities on the recovery curves. Moreover, this study can improve the highway network resilience from the organizational dimension by providing bridge managers with optimal LBR strategies.

Keywords: disaster management, highway network, long-term bridge repair schedule, resilience, restoration downtime

Procedia PDF Downloads 131
3564 Applying Sequential Pattern Mining to Generate Block for Scheduling Problems

Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

Abstract:

The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: combinatorial problems, sequential pattern mining, estimationof distribution algorithms, artificial chromosomes

Procedia PDF Downloads 582
3563 Modeling and Simulation of Vibratory Behavior of Hybrid Smart Composite Plate

Authors: Salah Aguib, Noureddine Chikh, Abdelmalek Khabli, Abdelkader Nour, Toufik Djedid, Lallia Kobzili

Abstract:

This study presents the behavior of a hybrid smart sandwich plate with a magnetorheological elastomer core. In order to improve the vibrational behavior of the plate, the pseudo‐fibers formed by the effect of the magnetic field on the elastomer charged by the ferromagnetic particles are oriented at 45° with respect to the direction of the magnetic field at 0°. Ritz's approach is taken to solve the physical problem. In order to verify and compare the results obtained by the Ritz approach, an analysis using the finite element method was carried out. The rheological property of the MRE material at 0° and at 45° are determined experimentally, The studied elastomer is prepared by a mixture of silicone oil, RTV141A polymer, and 30% of iron particles of total mixture, the mixture obtained is mixed for about 15 minutes to obtain an elastomer paste with good homogenization. In order to develop a magnetorheological elastomer (MRE), this paste is injected into an aluminum mold and subjected to a magnetic field. In our work, we have chosen an ideal percentage of filling of 30%, to obtain the best characteristics of the MRE. The mechanical characteristics obtained by dynamic mechanical viscoanalyzer (DMA) are used in the two numerical approaches. The natural frequencies and the modal damping of the sandwich plate are calculated and discussed for various magnetic field intensities. The results obtained by the two methods are compared. These off‐axis anisotropic MRE structures could open up new opportunities in various fields of aeronautics, aerospace, mechanical engineering and civil engineering.

Keywords: hybrid smart sandwich plate, vibratory behavior, FEM, Ritz approach, MRE

Procedia PDF Downloads 52
3562 Genetic Diversity of Tiger Groupers (Epinephelus fuscoguttatus) Challenged with Vibrio Parahaemolyticus and Exposed to Extreme Low Salinities

Authors: Hidayah Triana, Mahir S. Gani, Asmi Citra Malina, Hamka

Abstract:

This study was conducted to determine genetic diversity of tiger groupers that are resistant to V. parahaemolyticus and tolerant to low extreme salinities. This research is useful to obtain superior broodstock of fish. Tiger grouper used were 6 to 8 cm obtained from Brackish Water Aquaculture Research Center Gondol (Bali). This study consists of four stages: preliminary stage was adaptation of fish exposed to several concentrations of V. parahaemolyticus (103, 104, 105, 106, and 107 CFU / ml); second stage was test of Lethal Concentration (LC50) of bacteria to fish; third stage was salinity tolerance test (low salinity 12, 14 and 16 ppt) and fourth stage was analysis of DNA profiles. For DNA profiles analysis, genomic DNA of fish were extracted for PCR using primers YNZ-22 and UBC-122 and visualized by electrophoresis method. The results showed that Lethal concentration of bacteria (LC50) to fish was 1,56x106 CFU/ml. Furthermore, survival rate of groupers exposed with low salinities (12, 14, 16 ppt) survival rates were found to be 54,17 %, 66,67 % and 79,16 % respectively. Average of DNA fragment (5 fragments) generated from primer UBC-122 in the group of fish resistant to V.parahaemolyticus and tolerant to low salinities was similar to group of susceptible to low salinities. Primer YNZ-22 generated more diverse of DNA fragments (8,0 and 5,8 fragments) both in the group of fish tolerant and susceptible to low salinities compared to primer UBC-122 (5,0 fragments). Size of DNA 1.5 kb resulted from primer YNZ-22. Primer YNZ-22 generated 4 (50 %) and 3 (42,8 %) polymorfic fragments in the group of fish tolerant and susceptible to low salinities, respectively. Four (4) monomorfic fragments were found both in the group of fish tolerant and susceptible to low salinities. Primer UBC-122 generated 6 (85,7 %) and 9 (90,0 %) polymorfic fragments in the fish tolerant and susceptible to low salinities, respectively.

Keywords: genetic diversity, epinephelus fuscoguttatus, V. parahaemolyticus, PCR-RAPD, low extreme salinity

Procedia PDF Downloads 284
3561 Portfolio Optimization under a Hybrid Stochastic Volatility and Constant Elasticity of Variance Model

Authors: Jai Heui Kim, Sotheara Veng

Abstract:

This paper studies the portfolio optimization problem for a pension fund under a hybrid model of stochastic volatility and constant elasticity of variance (CEV) using asymptotic analysis method. When the volatility component is fast mean-reverting, it is able to derive asymptotic approximations for the value function and the optimal strategy for general utility functions. Explicit solutions are given for the exponential and hyperbolic absolute risk aversion (HARA) utility functions. The study also shows that using the leading order optimal strategy results in the value function, not only up to the leading order, but also up to first order correction term. A practical strategy that does not depend on the unobservable volatility level is suggested. The result is an extension of the Merton's solution when stochastic volatility and elasticity of variance are considered simultaneously.

Keywords: asymptotic analysis, constant elasticity of variance, portfolio optimization, stochastic optimal control, stochastic volatility

Procedia PDF Downloads 282
3560 A Weighted Sum Particle Swarm Approach (WPSO) Combined with a Novel Feasibility-Based Ranking Strategy for Constrained Multi-Objective Optimization of Compact Heat Exchangers

Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus

Abstract:

Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.

Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.

Procedia PDF Downloads 542
3559 Approximation Algorithms for Peak-Demand Reduction

Authors: Zaid Jamal Saeed Almahmoud

Abstract:

Smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing peak power consumption under a fixed delay requirement is a significant problem in the smart grid.For this problem, all appliances must be scheduled within a given finite time duration. We consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-hard, we analyze the performance of a version of the natural greedy heuristic for solving this problem. Our theoretical analysis and experimental results show that the proposed heuristic outperforms existing methods by providing a better approximation to the optimal solution.

Keywords: peak demand scheduling, approximation algorithms, smart grid, heuristics

Procedia PDF Downloads 81
3558 Optimization of Proton Exchange Membrane Fuel Cell Parameters Based on Modified Particle Swarm Algorithms

Authors: M. Dezvarei, S. Morovati

Abstract:

In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

Procedia PDF Downloads 333
3557 Comics as Third Space: An Analysis of the Continuous Negotiation of Identities in Postcolonial Philippines

Authors: Anna Camille V. Flores

Abstract:

Comics in the Philippines has taken on many uses for the Filipino people. They have been sources of entertainment, education, and political and social commentaries. History has been witnessed to the rise and fall of Philippine comics but the 21st century is seeing a revival of the medium and the industry. It is within this context that an inquiry about Filipino identity is situated. Employing the analytical framework of postcolonialism, particularly Homi K. Bhabha’s concepts of Hybridity and the Third Space, this study analyzes three contemporary Philippine comics, Trese, Filipino Heroes League, and Dead Balagtas. The study was able to draw three themes that represent how Filipinos inhabit hybrid worlds and hybridized identities. First, the third space emerged through the use of hybrid worlds in the comics. Second, (re)imagined communities are established through the use of intertextual signifiers. Third, (re)negotiated identities are expressed through visual and narrative devices such as the use of Philippine mythology, historical and contemporary contexts, and language. In conclusion, comics can be considered as Third Space where these identities have the agency and opportunity to be expressed and represented.

Keywords: comics, hybridity and third space, Philippine comics, postcolonialism

Procedia PDF Downloads 214
3556 Development of Portable Hybrid Renewable Energy System for Sustainable Electricity Supply to Rural Communities in Nigeria

Authors: Abdulkarim Nasir, Alhassan T. Yahaya, Hauwa T. Abdulkarim, Abdussalam El-Suleiman, Yakubu K. Abubakar

Abstract:

The need for sustainable and reliable electricity supply in rural communities of Nigeria remains a pressing issue, given the country's vast energy deficit and the significant number of inhabitants lacking access to electricity. This research focuses on the development of a portable hybrid renewable energy system designed to provide a sustainable and efficient electricity supply to these underserved regions. The proposed system integrates multiple renewable energy sources, specifically solar and wind, to harness the abundant natural resources available in Nigeria. The design and development process involves the selection and optimization of components such as photovoltaic panels, wind turbines, energy storage units (batteries), and power management systems. These components are chosen based on their suitability for rural environments, cost-effectiveness, and ease of maintenance. The hybrid system is designed to be portable, allowing for easy transportation and deployment in remote locations with limited infrastructure. Key to the system's effectiveness is its hybrid nature, which ensures continuous power supply by compensating for the intermittent nature of individual renewable sources. Solar energy is harnessed during the day, while wind energy is captured whenever wind conditions are favourable, thus ensuring a more stable and reliable energy output. Energy storage units are critical in this setup, storing excess energy generated during peak production times and supplying power during periods of low renewable generation. These studies include assessing the solar irradiance, wind speed patterns, and energy consumption needs of rural communities. The simulation results inform the optimization of the system's design to maximize energy efficiency and reliability. This paper presents the development and evaluation of a 4 kW standalone hybrid system combining wind and solar power. The portable device measures approximately 8 feet 5 inches in width, 8 inches 4 inches in depth, and around 38 feet in height. It includes four solar panels with a capacity of 120 watts each, a 1.5 kW wind turbine, a solar charge controller, remote power storage, batteries, and battery control mechanisms. Designed to operate independently of the grid, this hybrid device offers versatility for use in highways and various other applications. It also presents a summary and characterization of the device, along with photovoltaic data collected in Nigeria during the month of April. The construction plan for the hybrid energy tower is outlined, which involves combining a vertical-axis wind turbine with solar panels to harness both wind and solar energy. Positioned between the roadway divider and automobiles, the tower takes advantage of the air velocity generated by passing vehicles. The solar panels are strategically mounted to deflect air toward the turbine while generating energy. Generators and gear systems attached to the turbine shaft enable power generation, offering a portable solution to energy challenges in Nigerian communities. The study also addresses the economic feasibility of the system, considering the initial investment costs, maintenance, and potential savings from reduced fossil fuel use. A comparative analysis with traditional energy supply methods highlights the long-term benefits and sustainability of the hybrid system.

Keywords: renewable energy, solar panel, wind turbine, hybrid system, generator

Procedia PDF Downloads 12
3555 Analysis of Fixed Beamforming Algorithms for Smart Antenna Systems

Authors: Muhammad Umair Shahid, Abdul Rehman, Mudassir Mukhtar, Muhammad Nauman

Abstract:

The smart antenna is the prominent technology that has become known in recent years to meet the growing demands of wireless communications. In an overcrowded atmosphere, its application is growing gradually. A methodical evaluation of the performance of Fixed Beamforming algorithms for smart antennas such as Multiple Sidelobe Canceller (MSC), Maximum Signal-to-interference ratio (MSIR) and minimum variance (MVDR) has been comprehensively presented in this paper. Simulation results show that beamforming is helpful in providing optimized response towards desired directions. MVDR beamformer provides the most optimal solution.

Keywords: fixed weight beamforming, array pattern, signal to interference ratio, power efficiency, element spacing, array elements, optimum weight vector

Procedia PDF Downloads 163
3554 Effect of CYP2B6 c.516G>T and c.983T>C Single Nucleotide Polymorphisms on Plasma Nevirapine Levels in Zimbabwean HIV/AIDS Patients

Authors: Doreen Duri, Danai Zhou, Babil Stray-Pedersen, Collet Dandara

Abstract:

Given the high prevalence of HIV/AIDS in sub-Saharan Africa, and the elusive search for a cure, understanding the pharmacogenetics of currently used drugs is critical in populations from the most affected regions. Compared to Asian and Caucasian populations, African population groups are more genetically diverse, making it difficult to extrapolate findings from one ethnic group to another. This study aimed to investigate the role of genetic variation in CYP2B6 (c.516G>T and c.983T>C) single nucleotide polymorphisms on plasma nevirapine levels among HIV-infected adult Zimbabwean patients. Using a cross-sectional study, patients on nevirapine-containing HAART, having reached steady state (more than six weeks on treatment) were recruited to participate. Blood samples were collected after patients provided consent and samples were used to extract DNA for genetic analysis or to measure plasma nevirapine levels. Genetic analysis was carried out using PCR and RFLP or Snapshot for the two single nucleotide polymorphisms; CYP2B6 c.516G>T and c.983T>C, while LC-MS/MS was used in analyzing nevirapine concentration. CYP2B6 c.516G>T and c.983T>C significantly predicted plasma nevirapine concentration with the c.516T and c.983T being associated with elevated plasma nevirapine concentrations. Comparisons of the variant allele frequencies observed in this group to those reported in some African, Caucasian and Asian populations showed significant differences. We conclude that pharmacogenetics of nevirapine can be creatively used to determine patients who are likely to develop nevirapine-associated side effects as well as too low plasma concentrations for viral suppression.

Keywords: allele frequencies, genetically diverse, nevirapine, single nucleotide polymorphism

Procedia PDF Downloads 440
3553 Colored Image Classification Using Quantum Convolutional Neural Networks Approach

Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

Abstract:

Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

Procedia PDF Downloads 106
3552 Machine Learning Algorithms for Rocket Propulsion

Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

Abstract:

In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

Procedia PDF Downloads 97
3551 TMIF: Transformer-Based Multi-Modal Interactive Fusion for Rumor Detection

Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

Abstract:

The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

Procedia PDF Downloads 209
3550 Integrated Management System of Plant Genetic Resources: Collection, Conservation, Regeneration and Characterization of Cucurbitaceae and Solanaceae of DOA Genebank, Thailand

Authors: Kunyaporn Pipithsangchan, Alongkorn Korntong, Assanee Songserm, Phatchara Piriyavinit, Saowanee Dechakampoo

Abstract:

The Kingdom of Thailand is one of the South East Asian countries. From its area of 514,000 square kilometers (51 million ha), at least 18,000 plant species (8% of the world total) have been estimated to be found in the country. As a result, the conservation of plant genetic diversity, particularly food crops, is becoming important and is an assurance for the national food security. Department of Agriculture Genebank or DOA Genebank, Thailand is responsible for the conservation of plant germplasm by participating and accomplishing several collaborative projects both at national and international levels. Integrated Management System of Plant Genetic Resources or IMPGR is one of the most outstandingly successful cooperation. It is a multilateral project under the Asian Food and Agriculture Cooperation Initiative (AFACI) supported by the Rural Development Administration (RDA) of South Korea. The member countries under the project consist of 11 nations namely Bangladesh, Cambodia, Indonesia, Laos PDR, Mongolia, Nepal, Philippines, Sri Lanka, Thailand, Vietnam and South Korea. The project enabled the members to jointly address the global issues in plant genetic resource (PGR) conservation and strengthen their network in this aspect. The 1st phase of IMPGR project, entitled 'Collection, Conservation, Regeneration and Characterization of Cucurbitaceae and Solanaceae 2012-2014', comprises three main objectives that are: 1) To improve management in storage facilities, collection, and regeneration, 2) To improve linkage between Genebank and material sources (for regeneration), and 3) To improve linkage between Genebank and other field crop or/and horticultural research centers. The project was done for three years from 2012 to 2014. The activities of the project can be described as following details: In the 1st year, there were 9 target provinces for completing plant genetic resource survey and collection. 108 accessions of PGR were collected. In the 2nd year, PGR were continuously surveyed and collected from 9 provinces. The total number of collection was 140 accessions. In addition, the process of regeneration of 237 accessions collected from 1st and 2nd year was started at several sites namely Biotechnology Research and Development Office, Sukothai Horticultural Research Center, Tak Research, and Development Center and Nakhon Ratchasima Research and Development Center. In the 3rd year, besides survey and collection of 115 accessions from 9 target provinces, PGR characterization and evaluation were done for 206 accessions. Moreover, safety duplication of 253 PGR at the World Seed Vault, RDA, was also done according to Standard Agreement on Germplasm Safety Duplication between Department of Agriculture, Ministry of Agriculture and Cooperatives, the Kingdom of Thailand and the National Agrobiodiversity Center, Rural Development Administration of the Republic of Korea. The success of the 1st phase project led to the second phase which entitled 'Collection and Characterization for Effective Conservation of Local Capsicum spp., Solanum spp. and Lycopersicon spp. in Thailand 2015-2017'.

Keywords: characterization, conservation, DOA genebank, plant genetic resources

Procedia PDF Downloads 167
3549 Rare DCDC2 Mutation Causing Renal-Hepatic Ciliopathy

Authors: Atitallah Sofien, Bouyahia Olfa, Attar Souleima, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

Abstract:

Introduction: Ciliopathies are a spectrum of diseases that have in common a defect in the synthesis of ciliary proteins. It is a rare cause of neonatal cholestasis. Clinical presentation varies extremely, and the main affected organs are the kidneys, liver, and pancreas. Methodology: This is a descriptive case report of a newborn who was admitted for exploration of neonatal cholestasis in the Paediatric Department C at the Children’s Hospital of Tunis, where the investigations concluded with a rare genetic mutation. Results: This is the case of a newborn male with no family history of hepatic and renal diseases, born to consanguineous parents, and from a well-monitored uneventful pregnancy. He developed jaundice on the second day of life, for which he received conventional phototherapy in the neonatal intensive care unit. He was admitted at 15 days for mild bronchiolitis. On clinical examination, intense jaundice was noted with normal stool and urine colour. Initial blood work showed an elevation in conjugated bilirubin and a high gamma-glutamyl transferase level. Transaminases and prothrombin time were normal. Abdominal sonography revealed hepatomegaly, splenomegaly, and undifferentiated renal cortex with bilateral medullar micro-cysts. Kidney function tests were normal. The infant received ursodeoxycholic acid and vitamin therapy. Genetic testing showed a homozygous mutation in the DCDC2 gene that hadn’t been documented before confirming the diagnosis of renal-hepatic ciliopathy. The patient has regular follow-ups, and his conjugated bilirubin and gamma-glutamyl transferase levels have been decreasing. Conclusion: Genetic testing has revolutionized the approach to etiological diagnosis in pediatric cholestasis. It enables personalised treatment strategies to better enhance the quality of life of patients and prevent potential complications following adequate long-term monitoring.

Keywords: cholestasis, newborn, ciliopathy, DCDC2, genetic

Procedia PDF Downloads 48
3548 An Argument for Agile, Lean, and Hybrid Project Management in Museum Conservation Practice: A Qualitative Evaluation of the Morris Collection Conservation Project at the Sainsbury Centre for Visual Arts

Authors: Maria Ledinskaya

Abstract:

This paper is part case study and part literature review. It seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation by looking at their practical application on a recent conservation project at the Sainsbury Centre for Visual Arts. The author outlines the advantages of leaner and more agile conservation practices in today’s faster, less certain, and more budget-conscious museum climate where traditional project structures are no longer as relevant or effective. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre by private collectors Michael and Joyce Morris. It was a medium-sized conservation project of moderate complexity, planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown conditions and materials, unconfirmed budget. The project was later impacted by the COVID-19 pandemic, introducing indeterminate lockdowns, budget cuts, staff changes, and the need to accommodate social distancing and remote communications. The author, then a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. The paper examines the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, including the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics. Although not intentionally planned as such, the Morris Project had a number of Agile and Lean features which were instrumental to its successful delivery. These key features are identified as distributed decision-making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point in favour of a hybrid model, which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: agile project management, conservation, hybrid project management, lean project management, waterfall project management

Procedia PDF Downloads 57
3547 Numerical Simulation of Phase Transfer during Cryosurgery for an Irregular Tumor Using Hybrid Approach

Authors: Rama Bhargava, Surabhi Nishad

Abstract:

The infusion of nanofluids has dramatically enhanced the heat-carrying capacity of the fluids, applicable to many engineering and medical process where the temperature below freezing is required. Cryosurgery is an efficient therapy for the treatment of cancer, but sometimes the excessive cooling may harm the nearby healthy cells. Efforts are therefore done to develop a model which can cause to generate the low temperature as required. In the present study, a mathematical model is developed based on the bioheat transfer equation to simulate the heat transfer from the probe on a tumor (with irregular domain) using the hybrid technique consisting of element free Galerkin method with αα-family of approximation. The probe is loaded will nano-particles. The effects of different nanoparticles, namely Al₂O₃, Fe₃O₄, Au on the heat-producing rate, is obtained. It is observed that the temperature can be brought to (60°C)-(-30°C) at a faster freezing rate on the infusion of different nanoparticles. Besides increasing the freezing rate, the volume of the nanoparticle can also control the size and growth of ice crystals formed during the freezing process. The study is also made to find the time required to achieve the desired temperature. The problem is further extended for multi tumors of different shapes and sizes. The irregular shape of the frozen domain and the direction of ice growth are very sensitive issues, posing a challenge for simulation. The Meshfree method has been one of the accurate methods in such problems as a domain is naturally irregular. The discretization is done using the nodes only. MLS approximation is taken in order to generate the shape functions. Sufficiently accurate results are obtained.

Keywords: cryosurgery, EFGM, hybrid, nanoparticles

Procedia PDF Downloads 109
3546 Evaluation of Genetic Resistance to Haemonchus Contortus in Teddy and Beetal Goat Breeds of Punjab, Pakistan

Authors: Muhammad S. Sajid, Asim Shamim, Muhammad Nisar Khan, Ashfaq A. Chatta, Muhammad Saqib

Abstract:

Goats (Capra hircus) are a valued asset for resource poor farmers globally. But the parasitic infection especially Haemonchus contortus (Trichostrongylid), impact the health and production of goats globally. The present study intended to evaluate resilient and resistance to Haemonchus contortus in indigenous goat breeds (Teddy and Beetal) of Punjab, Pakistan. Out of 60, 30 goats of each breed were divided into 6 groups and each group contain five goats. Two group of each breed received challenged infection with 12000 and 18000 L3 (third stage) larvae of Haemonchus contortus under two infection protocol that is early and trickle and remaining two group of each breed was kept as control. Resilient and resistance of each breed was then measured on the basis of their phenotypic markers like: faecal egg counts, packed cell volume, FAMACHA score system, body weight, total protein, albumin and worm count on 2nd, 4th, 6th, and 8th week of post infection. Variation in response of each goat breeds to Haemonchus contortus was observed. Teddy breed showed significant (P < 0.05)resistance as compared to Beetal. It is probably first attempt to report an evaluation of goat breed response towards Haemonchus contortus in Pakistan. It was concluded that Teddy goats have a greater genetic tendency to resist against to the Haemonchus contortus infection and this breed could be kept and bred from the economic point of view. Evaluation of genetic markers are like: gene, protein expression, Immunoglobulin, Histamines and interleukins determination are recommended for future studies which can be helpful to be fined resistant breed of goats.

Keywords: goat, beetal, teddy, haemonchus contortus, resistance, resilience, phenotypic markers

Procedia PDF Downloads 349
3545 Optimization of Passive Vibration Damping of Space Structures

Authors: Emad Askar, Eldesoky Elsoaly, Mohamed Kamel, Hisham Kamel

Abstract:

The objective of this article is to improve the passive vibration damping of solar array (SA) used in space structures, by the effective application of numerical optimization. A case study of a SA is used for demonstration. A finite element (FE) model was created and verified by experimental testing. Optimization was then conducted by implementing the FE model with the genetic algorithm, to find the optimal placement of aluminum circular patches, to suppress the first two bending mode shapes. The results were verified using experimental testing. Finally, a parametric study was conducted using the FE model where patch locations, material type, and shape were varied one at a time, and the results were compared with the optimal ones. The results clearly show that through the proper application of FE modeling and numerical optimization, passive vibration damping of space structures has been successfully achieved.

Keywords: damping optimization, genetic algorithm optimization, passive vibration damping, solar array vibration damping

Procedia PDF Downloads 437
3544 Utilization of Developed Single Sequence Repeats Markers for Dalmatian Pyrethrum (Tanacetum cinerariifolium) in Preliminary Genetic Diversity Study on Natural Populations

Authors: F. Varga, Z. Liber, J. Jakše, A. Turudić, Z. Šatović, I. Radosavljević, N. Jeran, M. Grdiša

Abstract:

Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.; Asteraceae), a source of the commercially dominant plant insecticide pyrethrin, is a species endemic to the eastern Adriatic. Genetic diversity of T. cinerariifolium was previously studied using amplified fragment length polymorphism (AFLP) markers. However, microsatellite markers (single sequence repeats - SSRs) are more informative because they are codominant, highly polymorphic, locus-specific, and more reproducible, and thus are most often used to assess the genetic diversity of plant species. Dalmatian pyrethrum is an outcrossing diploid (2n = 18) whose large genome size and high repeatability have prevented the success of the traditional approach to SSR markers development. The advent of next-generation sequencing combined with the specifically developed method recently enabled the development of, to the author's best knowledge, the first set of SSRs for genomic characterization of Dalmatian pyrethrum, which is essential from the perspective of plant genetic resources conservation. To evaluate the effectiveness of the developed SSR markers in genetic differentiation of Dalmatian pyrethrum populations, a preliminary genetic diversity study was conducted on 30 individuals from three geographically distinct natural populations in Croatia (northern Adriatic island of Mali Lošinj, southern Adriatic island of Čiovo, and Mount Biokovo) based on 12 SSR loci. Analysis of molecular variance (AMOVA) by randomization test with 10,000 permutations was performed in Arlequin 3.5. The average number of alleles per locus, observed and expected heterozygosity, probability of deviations from Hardy-Weinberg equilibrium, and inbreeding coefficient was calculated using GENEPOP 4.4. Genetic distance based on the proportion of common alleles (DPSA) was calculated using MICROSAT. Cluster analysis using the neighbor-joining method with 1,000 bootstraps was performed with PHYLIP to generate a dendrogram. The results of the AMOVA analysis showed that the total SSR diversity was 23% within and 77% between the three populations. A slight deviation from Hardy-Weinberg equilibrium was observed in the Mali Lošinj population. Allele richness ranged from 2.92 to 3.92, with the highest number of private alleles observed in the Mali Lošinj population (17). The average observed DPSA between 30 individuals was 0.557. The highest DPSA (0.875) was observed between several pairs of Dalmatian pyrethrum individuals from the Mali Lošinj and Mt. Biokovo populations, and the lowest between two individuals from the Čiovo population. Neighbor-joining trees, based on DPSA, grouped individuals into clusters according to their population affiliation. The separation of Mt. Biokovo clade was supported (bootstrap value 58%), which is consistent with the previous study on AFLP markers, where isolated populations from Mt. Biokovo differed from the rest of the populations. The developed SSR markers are an effective tool for assessing the genetic diversity and structure of natural Dalmatian pyrethrum populations. These preliminary results are encouraging for a future comprehensive study with a larger sample size across the species' range. Combined with the biochemical data, these highly informative markers could help identify potential genotypes of interest for future development of breeding lines and cultivars that are both resistant to environmental stress and high in pyrethrins. Acknowledgment: This work has been supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.) insecticidal potential’- (PyrDiv) (IP-06-2016-9034) and by project KK.01.1.1.01.0005, Biodiversity and Molecular Plant Breeding, at the Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia.

Keywords: Asteraceae, genetic diversity, genomic SSRs, NGS, pyrethrum, Tanacetum cinerariifolium

Procedia PDF Downloads 103
3543 A User Identification Technique to Access Big Data Using Cloud Services

Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

Abstract:

Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

Procedia PDF Downloads 457