Search results for: savings algorithm

Authors: Ibtissem Talbi

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During the last decade, a variety of chaos-based cryptosystems have been investigated. Most of them are based on the structure of Fridrich, which is based on the traditional confusion-diffusion architecture proposed by Shannon. Compared with traditional cryptosystems (DES, 3DES, AES, etc.), the chaos-based cryptosystems are more flexible, more modular and easier to be implemented, which make them suitable for large scale-data encyption, such as images and videos. The heart of any chaos-based cryptosystem is the chaotic generator and so, a part of the efficiency (robustness, speed) of the system depends greatly on it. In this talk, we give an overview of the state of the art of chaos-based block ciphers and we describe some of our schemes already proposed. Also we will focus on the essential characteristics of the digital chaotic generator, The needed performance of a chaos-based block cipher in terms of security level and speed of calculus depends on the considered application. There is a compromise between the security and the speed of the calculation. The security of these block block ciphers will be analyzed.

Keywords: chaos-based cryptosystems, chaotic generator, security analysis, structure of Fridrich

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Authors: T. Mohammed Chikouche, K. Hartani

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Based on the analysis of basic direct torque control, a parallel master slave for four in-wheel permanent magnet synchronous motors (PMSM) fed by two three phase inverters used in electric vehicle is proposed in this paper. A conventional system with multi-inverter and multi-machine comprises a three phase inverter for each machine to be controlled. Another approach consists in using only one three-phase inverter to supply several permanent magnet synchronous machines. A modified direct torque control (DTC) algorithm is used for the control of the bi-machine traction system. Simulation results show that the proposed control strategy is well adapted for the synchronism of this system and provide good speed tracking performance.

Keywords: electric vehicle, multi-machine single-inverter system, multi-machine multi-inverter control, in-wheel motor, master-slave control

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Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

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The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

Procedia PDF Downloads 189

Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Shahin Zanbaghi, Saeed Samet

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The internet has transformed the way we shop. Previously, most of our purchases came in the form of shopping trips to a nearby store. Now, it’s as easy as clicking a mouse. But with great convenience comes great responsibility. We have to be constantly vigilant about our personal information. In this work, our proposed approach is to encrypt the information printed on the physical packages, which include personal information in plain text, using a symmetric encryption algorithm; then, we store that encrypted information into a Blockchain network rather than storing them in companies or corporations centralized databases. We present, implement and assess a blockchain-based system using Ethereum smart contracts. We present detailed algorithms that explain the details of our smart contract. We present the security, cost, and performance analysis of the proposed method. Our work indicates that the proposed solution is economically attainable and provides data integrity, security, transparency, and data traceability.

Keywords: blockchain, Ethereum, smart contract, commit-reveal scheme

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Authors: B. M. Md-Zain, N. A. Rahman, M. A. B. Abdul-Latiff, W. M. R. Idris

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We conducted molecular research to portray phylogenetic relationships of Malaysian primates particularly in the genus of Macaca. We have sequenced cytochrome C oxidase subunit I (COI) of mitochondrial DNA of several individuals from M. fascicularis and M. arctoides. PCR amplifications were performed and COI DNA sequences were aligned using ClustalW. Phylogenetic trees were constructed using distance analyses by employing neighbor-joining algorithm (NJ). We managed to sequence 700 bp of COI DNA sequences. The tree topology showed that M. fascicularis did not clump based on phyleogeography division in Peninsular Malaysia. Individuals from Negeri Sembilan merged together with samples from Perak and Penang into one clade. In addition, phylogenetic analyses indicated that M. arctoides was classified into sinica group instead of fascicularis group supported by genetic distance data. COI gene is an effective locus to clarify phylogenetic position of M. arctoides but not in discriminating M. fascicularis population in Peninsular Malaysia.

Keywords: cercopithecine, long-tailed macaque, Macaca fascicularis, Macaca arctoides

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Authors: A. Benmerkhi, A. Bounouioua, M. Bouchemat, T. Bouchemat

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In this paper, we present a numerical optical properties of a triangular periodic lattice of elliptical air holes. We report the influence of the ratio (semi-major axis length of elliptical hole to the filling ratio) on the photonic band gap. Then by using the finite difference time domain (FDTD) algorithm, the resonant wavelength of the point defect microcavities in a two-dimensional photonic crystal (PC) shifts towards the low wavelengths with significantly increased filing ratio. It can be noted that the Q factor is gradually changed to higher when the filling ratio increases. It is due to an increase in reflectivity of the PC mirror. Also we theoretically investigate the H1 cavity, where the value of semi-major axis (Rx) of the six holes surrounding the cavity are fixed at 0.5a and the Rx of the two edge air holes are fixed at the optimum value of 0.52a. The highest Q factor of 4.1359 × 10⁶ is achieved at the resonant mode located at λ = 1.4970 µm.

Keywords: photonic crystal, microcavity, filling ratio, elliptical holes

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Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

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We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

Procedia PDF Downloads 297

Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Stephane Maingard, Babu Paturi, Maura Daly, Finnola Armstrong

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Background: Perinatal optimization involves the implementation of twelve intervention bundles of care at Our Lady of Lourdes Hospital, reliably delivering evidence-based interventions in the antenatal, intrapartum, and neonatal period to improve preterm outcomes. These key interventions (e.g. Antenatal steroids, Antenatal counselling, Optimal cord management, Respiratory management etc.) are based on WHO (World Health Organization, BAPM (British Association of Perinatal Medicine), and the latest 2022 European Consensus guidelines recommendations. Methodology: In February 2023, a quality improvement project team (pediatricians, neonatologists, obstetricians, clinical skills managers) was established, and a project implementation plan was developed. The Program Study Act implemented the following: 1. Antenatal consultation pathway, 2. Creation and implementation of a perinatal checklist for preterm births less than 34 weeks of gestation, 3. Process changes to ensure the checklist is completed, 4. Completion of parent and staff surveys, 5. Ongoing training. We collected and compared a range of data before and after implementation. Results: Preliminary analysis so far at 1 month demonstrates improvement in the following areas: 50% increase in antenatal counselling. Right place of birth increased from 85% to 100%. Magnesium sulphate increased from 56% to 100%. No change was observed in buccal colostrum administration (28%), delayed cord clamping (75%), caffeine administration (100%), blood glucose level at one hour of life > 2,6mmol (85%). There was also no change noted in respiratory support at resuscitation, CPAP only (47%), IPPV with CPAP (45%), IPPV with intubation (20%), and surfactant administration (28%). A slight decrease in figures was noted in the following: steroid administration from 80% to 75% and thermal care obtaining optimal temperature on admission (65% to 50%). Discussion: Even though the findings are preliminary, the directional improvement shows promise. Improved communication has been achieved between all stakeholders, including our patients, who are key team members. Adherence to the bundles of care will help to improve survival and neurodevelopmental outcomes as well as reduce the length of stay, thereby overall reducing the financial cost, considering the lifetime cost of cerebral palsy is estimated at €800,000 and reducing the length of stay can result in savings of up to €206,000. Conclusion: Preliminary results demonstrate improvements across a range of patient, process, staff, and financial outcomes. Our future goal is a seamless pathway of patient centered care for babies and their families. This project is an interdisciplinary collaboration to implement best practices for a vulnerable patient cohort. Our two main challenges are changing our organization’s culture as well as ensuring the sustainability of the project.

Keywords: perinatal, optimization, antenatal, counselling, IPPV

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Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

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This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. The material character of cone paper and the loudspeaker edge were the design parameters, and the vibration displacement of the cone paper was the objective function. The results of the analysis showed that the design had high accuracy as compared to the predicted value. These results suggested that although the parameter design is difficult, with experience and intuition, the design can be performed easily using the optimized design found with the acoustic analysis software.

Keywords: air viscosity, design parameters, loudspeaker, optimization

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Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Adam Szurlej

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Currently, in automotive transport to power vehicles, almost exclusively hydrocarbon based fuels are used. Due to increase of hydrocarbon fuels consumption, quality parameters are tightend for clean environment. At the same time efforts are undertaken for development of alternative fuels. The reasons why looking for alternative fuels for petroleum and diesel are: to increase vehicle efficiency and to reduce the environmental impact, reduction of greenhouse gases emissions and savings in consumption of limited oil resources. Significant progress was performed on development of alternative fuels such as methanol, ethanol, natural gas (CNG / LNG), LPG, dimethyl ether (DME) and biodiesel. In addition, biggest vehicle manufacturers work on fuel cell vehicles and its introduction to the market. Alcohols such as methanol and ethanol create the perfect fuel for spark-ignition engines. Their advantages are high-value antiknock which determines their application as additive (10%) to unleaded petrol and relative purity of produced exhaust gasses. Ethanol is produced in distillation process of plant products, which value as a food can be irrational. Ethanol production can be costly also for the entire economy of the country, because it requires a large complex distillation plants, large amounts of biomass and finally a significant amount of fuel to sustain the process. At the same time, the fermentation process of plants releases into the atmosphere large quantities of carbon dioxide. Natural gas cannot be directly converted into liquid fuels, although such arrangements have been proposed in the literature. Going through stage of intermediates is inevitable yet. Most popular one is conversion to methanol, which can be processed further to dimethyl ether (DME) or olefin (ethylene and propylene) for the petrochemical sector. Methanol uses natural gas as a raw material, however, requires expensive and advanced production processes. In relation to pollution emissions, the optimal vehicle fuel is LPG which is used in many countries as an engine fuel. Production of LPG is inextricably linked with production and processing of oil and gas, and which represents a small percentage. Its potential as an alternative for traditional fuels is therefore proportionately reduced. Excellent engine fuel may be biogas, however, follows to the same limitations as ethanol - the same production process is used and raw materials. Most essential fuel in the campaign of environment protection against pollution is natural gas. Natural gas as fuel may be either compressed (CNG) or liquefied (LNG). Natural gas can also be used for hydrogen production in steam reforming. Hydrogen can be used as a basic starting material for the chemical industry, an important raw material in the refinery processes, as well as a fuel vehicle transportation. Natural gas can be used as CNG which represents an excellent compromise between the availability of the technology that is proven and relatively cheap to use in many areas of the automotive industry. Natural gas can also be seen as an important bridge to other alternative sources of energy derived from fuel and harmless to the environment. For these reasons CNG as a fuel stimulates considerable interest in the worldwide.

Keywords: alternative fuels, CNG (Compressed Natural Gas), LNG (Liquefied Natural Gas), NGVs (Natural Gas Vehicles)

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Dechrit Maneetham

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The aim of this paper was to design a smart electric power wheelchair (SEPW) with a novel control system for quadriplegics with head and neck mobility. Head movement has been used as a control interface for people with motor impairments in a range of applications. Acquiring measurements from the module is simplified through a synchronous a motor. Axis measures the two directions namely X ,Y and Z. The model of a DC motor is considered as a speed control by selection of a PID parameters using genetic algorithm. An experimental set-up constructed, which consists of micro controller Arduino ATmega32u4 as controllers, a DC motor driven SEPW and feedback elements. And this paper is tuning methods of parameter for a pulse width modulation (PWM) control system. A speed controller has been designed successfully for closed loop of the DC motor so that the motor runs very closed to the reference speed and angle. SEPW controller can be used to ensure the person’s head is attending the direction of travel asserted by a conventional, direction and speed control.

Keywords: wheelchair, quadriplegia, rehabilitation, medical devices, speed control

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Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

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Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Mihai Duguleana, Florin Girbacia, Cristian Postelnicu, Raffaello Brodi, Marcello Carrozzino

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Augmented Reality (AR) has taken a big leap with the introduction of mobile applications which co-locate bi-dimensional (e.g. photo, video, text) and tridimensional information with the location of the user enriching his/her experience. This study presents the advantages of using Mobile Augmented Reality (MAR) technologies in traveling applications, improving cultural heritage exploration. We propose a location-based AR application which combines co-location with the augmented visual information about Pisa monuments to establish a friendly navigation in this historic city. AR was used to render contextual visual information in the outdoor environment. The developed Android-based application offers two different options: it provides the ability to identify the monuments positioned close to the user’s position and it offers location information for getting near the key touristic objectives. We present the process of creating the monuments’ 3D map database and the navigation algorithm.

Keywords: augmented reality, electronic compass, GPS, location-based service

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Authors: H. Nikzad, S. Yoshitomi

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This paper presents the design application and reinforcement detailing of 15 storied reinforced concrete shear wall-frame structure based on linear static analysis. Databases are generated for section sizes based on automated structural optimization method utilizing Active-set Algorithm in MATLAB platform. The design constraints of allowable section sizes, capacity criteria and seismic provisions for static loads, combination of gravity and lateral loads are checked and determined based on ASCE 7-10 documents and ACI 318-14 design provision. The result of this study illustrates the efficiency of proposed method, and is expected to provide a useful reference in designing of RC shear wall-frame structures.

Keywords: design constraints, ETABS, linear static analysis, MATLAB, RC shear wall-frame structures, structural optimization

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Authors: Farnaz Alborzi, Angelika Schmitz, Rainer Stamminger

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Reducing water temperatures in the wash phase of a washing programme and increasing the overall cycle durations are the latest trends in decreasing energy consumption of washing programmes. Since the implementation of the new energy efficiency classes in 2010, manufacturers seem to apply the aforementioned washing strategy with lower temperatures combined with longer programme durations extensively to realise energy-savings needed to meet the requirements of the highest energy efficiency class possible. A semi-representative on-line survey in eleven European countries (Czech Republic, Finland, France, Germany, Hungary, Italy, Poland, Romania, Spain, Sweden and the United Kingdom) was conducted by Bonn University in 2015 to shed light on consumer opinion and behaviour regarding the effects of the lower washing temperature and longer cycle duration in laundry washing on consumers’ acceptance of the programme. The risk of the long wash cycle is that consumers might not use the energy efficient Standard programmes and will think of this option as inconvenient and therefore switch to shorter, but more energy consuming programmes. Furthermore, washing in a lower temperature may lead to the problem of cross-contamination. Washing behaviour of over 5,000 households was studied in this survey to provide support and guidance for manufacturers and policy designers. Qualified households were chosen following a predefined quota: -Involvement in laundry washing: substantial, -Distribution of gender: more than 50 % female , -Selected age groups: -20–39 years, -40–59 years, -60–74 years, -Household size: 1, 2, 3, 4 and more than 4 people. Furthermore, Eurostat data for each country were used to calculate the population distribution in the respective age class and household size as quotas for the consumer survey distribution in each country. Before starting the analyses, the validity of each dataset was controlled with the aid of control questions. After excluding the outlier data, the number of the panel diminished from 5,100 to 4,843. The primary outcome of the study is European consumers are willing to save water and energy in a laundry washing but reluctant to use long programme cycles since they don’t believe that the long cycles could be energy-saving. However, the results of our survey don’t confirm that there is a relation between frequency of using Standard cotton (Eco) or Energy-saving programmes and the duration of the programmes. It might be explained by the fact that the majority of washing programmes used by consumers do not take so long, perhaps consumers just choose some additional time reduction option when selecting those programmes and this finding might be changed if the Energy-saving programmes take longer. Therefore, it may be assumed that introducing the programme duration as a new measure on a revised energy label would strongly influence the consumer at the point of sale. Furthermore, results of the survey confirm that consumers are more willing to use lower temperature programmes in order to save energy than accepting longer programme cycles and majority of them accept deviation from the nominal temperature of the programme as long as the results are good.

Keywords: duration, energy-saving, standard programmes, washing temperature

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Authors: B. Siva Kumar Reddy, B. Lakshmi

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WiMAX has adopted an Adaptive Modulation and Coding (AMC) in OFDM to endure higher data rates and error free transmission. AMC schemes employ the Channel State Information (CSI) to efficiently utilize the channel and maximize the throughput and for better spectral efficiency. This CSI has given to the transmitter by the channel estimators. In this paper, LSE (Least Square Error) and MMSE (Minimum Mean square Error) estimators are suggested and BER (Bit Error Rate) performance has been analyzed. Channel equalization is also integrated with with AMC-OFDM system and presented with Constant Modulus Algorithm (CMA) and Least Mean Square (LMS) algorithms with convergence rates analysis. Simulation results proved that increment in modulation scheme size causes to improvement in throughput along with BER value. There is a trade-off among modulation size, throughput, BER value and spectral efficiency. Results also reported the requirement of channel estimation and equalization in high data rate systems.

Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX

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Authors: Alan Crowle, Philpp Thies

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As the floating offshore wind turbine industry continues to develop and grow, the capabilities of established port facilities need to be assessed as to their ability to support the expanding construction and installation requirements. This paper assesses current infrastructure requirements and projected changes to port facilities that may be required to support the floating offshore wind industry. Understanding the infrastructure needs of the floating offshore renewable industry will help to identify the port-related requirements. Floating Offshore Wind Turbines can be installed further out to sea and in deeper waters than traditional fixed offshore wind arrays, meaning that it can take advantage of stronger winds. Separate ports are required for substructure construction, fit-out of the turbines, moorings, subsea cables and maintenance. Large areas are required for the laydown of mooring equipment; inter-array cables, turbine blades and nacelles. The capabilities of established port facilities to support floating wind farms are assessed by evaluation of the size of substructures, the height of wind turbine with regards to the cranes for fitting of blades, distance to offshore site and offshore installation vessel characteristics. The paper will discuss the advantages and disadvantages of using large land-based cranes, inshore floating crane vessels or offshore crane vessels at the fit-out port for the installation of the turbine. Water depths requirements for import of materials and export of the completed structures will be considered. There are additional costs associated with any emerging technology. However part of the popularity of Floating Offshore Wind Turbines stems from the cost savings against permanent structures like fixed wind turbines. Floating Offshore Wind Turbine developers can benefit from lighter, more cost-effective equipment which can be assembled in port and towed to the site rather than relying on large, expensive installation vessels to transport and erect fixed bottom turbines. The ability to assemble Floating Offshore Wind Turbines equipment onshore means minimizing highly weather-dependent operations like offshore heavy lifts and assembly, saving time and costs and reducing safety risks for offshore workers. Maintenance might take place in safer onshore conditions for barges and semi-submersibles. Offshore renewables, such as floating wind, can take advantage of this wealth of experience, while oil and gas operators can deploy this experience at the same time as entering the renewables space The floating offshore wind industry is in the early stages of development and port facilities are required for substructure fabrication, turbine manufacture, turbine construction and maintenance support. The paper discusses the potential floating wind substructures as this provides a snapshot of the requirements at the present time, and potential technological developments required for commercial development. Scaling effects of demonstration-scale projects will be addressed, however, the primary focus will be on commercial-scale (30+ units) device floating wind energy farms.

Keywords: floating wind, port, marine construction, offshore renewables

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Authors: Yassir AbdelRazig

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Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.

Keywords: ant colony, construction site layout, optimization, genetic algorithms

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Authors: Mohammad Javad Maghsoudi, Z. Mohamed, A. R. Husain

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Input shaping has been utilized for vibration reduction of many oscillatory systems. This paper presents an optimal closed-loop input shaping scheme for control of a three dimensional (3D) gantry crane system including. This includes a PID controller and Zero Vibration shaper which consider two control objectives concurrently. The control objectives are minimum sway of a payload and fast and accurate positioning of a trolley. A complete mathematical model of a lab-scaled 3D gantry crane is simulated in Simulink. Moreover, by utilizing PSO algorithm and a proposed scheme the controller is designed to cater both control objectives concurrently. Simulation studies on a 3D gantry crane show that the proposed optimal controller has an acceptable performance. The controller provides good position response with satisfactory payload sway in both rail and trolley responses.

Keywords: 3D gantry crane, input shaping, closed-loop control, optimal scheme, PID

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Authors: Naima Ikken, Abdelhadi Bouknadel, Nour-eddine Tariba Ahmed Haddou, Hafsa El Omari

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The operation of grid-connected inverters necessity a single-phase phase locked loop (PLL) is proposed in this article to accurately and quickly estimate and detect the grid phase angle. This article presents the improvement of a method of phase-locked loop. The novelty is to generate a method (PLL) of synchronizing the grid with a Notch filter based on adaptive fuzzy logic for inverter systems connected to the grid. The performance of the proposed method was tested under normal and abnormal operating conditions (amplitude, frequency and phase shift variations). In addition, simulation results with ISPM software are developed to verify the effectiveness of the proposed method strategy. Finally, the experimental test will be used to extract the result and discuss the validity of the proposed algorithm.

Keywords: phase locked loop, PLL, notch filter, fuzzy logic control, grid connected inverters

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: David C. Ni

Abstract:

In the previous efforts, we constructed N-Body Systems by an extended Blaschke product (EBP), which represents a non-temporal and nonlinear extension of Lorentz transformation. In this construction, we rely only on two parameters, nonlinear degree, and relative momentum to characterize the systems. We further explored root computation via iteration with an algorithm extended from Jenkins-Traub method. The solution sets demonstrate a form of σ+ i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various canonical distributions. In this paper, we correlate the convergent sets in the original domain with solution sets, which demonstrating large-deviation distributions in the codomain. We proceed to compare our approach with the formula or principles, such as Donsker-Varadhan and Wentzell-Freidlin theories. The deterministic model based on this construction allows us to explore applications in the areas of finance and statistical mechanics.

Keywords: nonlinear Lorentz transformation, Blaschke equation, iteration solutions, root computation, large deviation distribution, deterministic model

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Authors: Soltani Amir, Wang Xuan

Abstract:

The advantage of using non-linear passive damping system in vibration control of two adjacent structures is investigated under their base excitation. The base excitation is El Centro earthquake record acceleration. The damping system is considered as an optimum and effective non-linear viscous damper that is connected between two adjacent structures. A Matlab program is developed to produce the stiffness and damping matrices and to determine a time history analysis of the dynamic motion of the system. One structure is assumed to be flexible while the other has a rule as laterally supporting structure with rigid frames. The response of the structure has been calculated and the non-linear damping coefficient is determined using optimum LQR algorithm in an optimum vibration control system. The non-linear parameter of damping system is estimated and it has shown a significant advantage of application of this system device for vibration control of two adjacent tall building.

Keywords: active control, passive control, viscous dampers, structural control, vibration control, tall building

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Authors: Jiayuan Wu. Lu Hu

Abstract:

With the development of the sharing economy and mobile technology, carsharing becomes more popular. In this paper, we focus on the joint optimization of one-way station-based carsharing systems. We model the problem as an integer linear program with six elements: station locations, station capacity, fleet size, initial vehicle allocation, vehicle relocation, and demand selection. A greedy-based heuristic is proposed to address the model. Firstly, initialization based on the location variables relaxation using Gurobi solver is conducted. Then, according to the profit margin and demand satisfaction of each station, the number of stations is downsized iteratively. This method is applied to real data from Chengdu, Sichuan taxi data, and it’s efficient when dealing with a large scale of candidate stations. The result shows that with vehicle relocation and demand selection, the profit and demand satisfaction of carsharing systems are increased.

Keywords: one-way carsharing, location, vehicle relocation, demand selection, greedy algorithm

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Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

Abstract:

Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

Abstract:

Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, road network, selection method, spatial information expression, distribution pattern

Procedia PDF Downloads 410