Search results for: power network

Authors: Ilgin Gökaşar, Saman Ghaffarian

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The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

Procedia PDF Downloads 467

Authors: J. R. Wang, J. H. Yang, Y. Chiang, H. C. Chen, C. Shih, S. W. Chen, S. C. Chiang, T. Y. Yu

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In this study of ultimate response guideline (URG), Kuosheng BWR/6 nuclear power plant (NPP) TRACE model was established. The reactor depressurization, low pressure water injection, and containment venting are the main actions of URG. This research focuses to evaluate the efficiency of URG under Fukushima-like conditions. Additionally, the sensitivity study of URG was also performed in this research. The analysis results of TRACE present that URG can keep the peak cladding temperature (PCT) below 1088.7 K (the failure criteria) under Fukushima-like conditions. It implied that Kuosheng NPP was at the safe situation.

Keywords: BWR, TRACE, safety analysis, ultimate response guideline (URG)

Procedia PDF Downloads 562

Authors: K. W. Nam, B. J. Kim, S. J. Lee

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Along with the development of network infrastructures, such as high-speed Internet and mobile environment, the explosion of multimedia data is expanding the range of multimedia services beyond voice and data services. Amid this flow, research is actively being done on the creation, management, and transmission of metadata on digital content to provide different services to users. This paper proposes a system for the insertion, storage, and retrieval of metadata about digital content. The metadata server with Binary XML was implemented for efficient storage space and retrieval speeds, and the transport data size required for metadata retrieval was simplified. With the proposed system, the metadata could be inserted into the moving objects in the video, and the unnecessary overlap could be minimized by improving the storage structure of the metadata. The proposed system can assemble metadata into one relevant topic, even if it is expressed in different media or in different forms. It is expected that the proposed system will handle complex network types of data.

Keywords: video, multimedia, metadata, editing tool, XML

Procedia PDF Downloads 171

Authors: Michał Gęca, Konrad Pietrykowski, Grzegorz Barański

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The water pump in the compression-ignition internal combustion engine transports a hot coolant along a system of ducts from the engine block to the radiator where coolant temperature is lowered. This part needs to maintain a constant volumetric flow rate. Its power should be regulated to avoid a significant drop in pressure if a coolant flow decreases. The internal combustion engine cooling system uses centrifugal pumps for suction. The paper investigates 4 constructions of engine pumps. The pumps are from diesel engine of a maximum power of 75 kW. Each of them has a different rotor shape, diameter and width. The test stand was created and the geometry inside the all 4 engine blocks was mapped. For a given pump speed on the inverter of the electric engine motor, the valve position was changed and volumetric flow rate, pressure, and power were recorded. Pump speed was regulated from 1200 RPM to 7000 RPM every 300 RPM. The volumetric flow rates and pressure drops for the pump speeds and efficiencies were specified. Accordingly, the operations of each pump were mapped. Our research was to select a pump for the aircraft compression-ignition engine. There was calculated a pressure drop at a given flow on the block and radiator of the designed aircraft engine. The water pump should be lightweight and have a low power demand. This fact shall affect the shape of a rotor and bearings. The pump volumetric flow rate was assumed as 3 kg/s (previous AVL BOOST research model) where the temperature difference was 5°C between the inlet (90°C) and outlet (95°C). Increasing pump speed above the boundary flow power defined by pressure and volumetric flow rate does not increase it but pump efficiency decreases. The maximum total pump efficiency (PCC) is 45-50%. When the pump is driven by low speeds with a 90% closed valve, its overall efficiency drops to 15-20%. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft engine, diesel engine, flow, water pump

Procedia PDF Downloads 252

Authors: Seada Hussen, Frie Ayalew

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Integrating different energy resources, like solar PV and hydro, is used to ensure reliable power to rural communities like Hara village in Ethiopia. Hybrid power system offers power supply for rural villages by providing an alternative supply for the intermittent nature of renewable energy resources. The intermittent nature of renewable energy resources is a challenge to electrifying rural communities in a sustainable manner with solar resources. Major rural villages in Ethiopia are suffering from a lack of electrification, that cause our people to suffer deforestation, travel for long distance to fetch water, and lack good services like clinic and school sufficiently. The main objective of this project is to provide a balanced, stable, reliable supply for Hara village, Ethiopia using solar power with a pumped hydro energy storage system. The design of this project starts by collecting data from villages and taking solar irradiance data from NASA. In addition to this, geographical arrangement and location are also taken into consideration. After collecting this, all data analysis and cost estimation or optimal sizing of the system and comparison of solar with pumped hydro and solar with battery storage system is done using Homer Software. And since solar power only works in the daytime and pumped hydro works at night time and also at night and morning, both load will share to cover the load demand; this need controller designed to control multiple switch and scheduling in this project fuzzy logic controller is used to control this scenario. The result of the simulation shows that solar with pumped hydro energy storage system achieves good results than with a battery storage system since the comparison is done considering storage reliability, cost, storage capacity, life span, and efficiency.

Keywords: pumped hydro storage, solar energy, solar PV, battery energy storage, fuzzy logic controller

Procedia PDF Downloads 78

Authors: Yogi Sirodz Gaos, Irvan Wiradinata

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In the 500 kW Organic Rankine Cycle (ORC) power plant in Indonesia, an AFT (according to the Tubular Exchanger Manufacturers Association – TEMA) type shell and tube heat exchanger device is used as a pre-heating system for the ORC’s hot water circulation system. The pre-heating source is a waste heat recovery of the brine water, which is tapped from a geothermal power plant. The brine water itself has 5 MWₜₕ capacities, with average temperature of 170ᵒC, and 7 barg working pressure. The aim of this research is to examine the performance of the heat exchanger in the ORC system in a 500 kW ORC power plant. The data for this research were collected during the commissioning on the middle of December 2016. During the commissioning, the inlet temperature and working pressure of the brine water to the shell and tube type heat exchanger was 149ᵒC, and 4.4 barg respectively. Furthermore, the ΔT for the hot water circulation of the ORC system to the heat exchanger was 27ᵒC, with the inlet temperature of 140ᵒC. The pressure in the hot circulation system was dropped slightly from 7.4ᵒC to 7.1ᵒC. The flow rate of the hot water circulation was 80.5 m³/h. The presentation and discussion of a case study on the performance of the heat exchanger on the 500 kW ORC system is presented as follows: (1) the heat exchange duty is 2,572 kW; (2) log mean temperature of the heat exchanger is 13.2ᵒC; (3) the actual overall thermal conductivity is 1,020.6 W/m².K (4) the required overall thermal conductivity is 316.76 W/m².K; and (5) the over design for this heat exchange performance is 222.2%. An analysis of the heat exchanger detailed engineering design (DED) is briefly discussed. To sum up, this research concludes that the shell and tube heat exchangers technology demonstrated a good performance as pre-heating system for the ORC’s hot water circulation system. Further research need to be conducted to examine the performance of heat exchanger system on the ORC’s hot water circulation system.

Keywords: shell and tube, heat exchanger, organic Rankine cycle, performance, commissioning

Procedia PDF Downloads 143

Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

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Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

Procedia PDF Downloads 338

Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

Procedia PDF Downloads 201

Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua

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Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.

Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability

Procedia PDF Downloads 323

Authors: Ligang Wang, Theodoros Damartzis, Stefan Diethelm, Jan Van Herle, François Marechal

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Biogas production from anaerobic digestion of organic sludge from wastewater treatment as well as various urban and agricultural organic wastes is of great significance to achieve a sustainable society. Two upgrading approaches for cleaned biogas can be considered: (1) direct H₂ injection for catalytic CO₂ methanation and (2) CO₂ separation from biogas. The first approach usually employs electrolysis technologies to generate hydrogen and increases the biogas production rate; while the second one usually applies commercially-available highly-selective membrane technologies to efficiently extract CO₂ from the biogas with the latter being then sent afterward for compression and storage for further use. A straightforward way of utilizing the captured CO₂ is on-site catalytic CO₂ methanation. From the perspective of system complexity, the second approach may be questioned, since it introduces an additional expensive membrane component for producing the same amount of methane. However, given the circumstance that the sustainability of the produced biogas should be retained after biogas upgrading, renewable electricity should be supplied to drive the electrolyzer. Therefore, considering the intermittent nature and seasonal variation of renewable electricity supply, the second approach offers high operational flexibility. This indicates that these two approaches should be compared based on the availability and scale of the local renewable power supply and not only the technical systems themselves. Solid-oxide electrolysis generally offers high overall system efficiency, and more importantly, it can achieve simultaneous electrolysis of CO₂ and H₂O (namely, co-electrolysis), which may bring significant benefits for the case of CO₂ separation from the produced biogas. When taking co-electrolysis into account, two additional upgrading approaches can be proposed: (1) direct steam injection into the biogas with the mixture going through the SOE, and (2) CO₂ separation from biogas which can be used later for co-electrolysis. The case study of integrating SOE to a wastewater treatment plant is investigated with wind power as the renewable power. The dynamic production of biogas is provided on an hourly basis with the corresponding oxygen and heating requirements. All four approaches mentioned above are investigated and compared thermo-economically: (a) steam-electrolysis with grid power, as the base case for steam electrolysis, (b) CO₂ separation and co-electrolysis with grid power, as the base case for co-electrolysis, (c) steam-electrolysis and CO₂ separation (and storage) with wind power, and (d) co-electrolysis and CO₂ separation (and storage) with wind power. The influence of the scale of wind power supply is investigated by a sensitivity analysis. The results derived provide general understanding on the economic competitiveness of SOE for sustainable biogas upgrading, thus assisting the decision making for biogas production sites. The research leading to the presented work is funded by European Union’s Horizon 2020 under grant agreements n° 699892 (ECo, topic H2020-JTI-FCH-2015-1) and SCCER BIOSWEET.

Keywords: biogas upgrading, solid-oxide electrolyzer, co-electrolysis, CO₂ utilization, energy storage

Procedia PDF Downloads 155

Authors: M. Radunovic

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Region of Southeastern Europe has a substantial energy resource potential and is witnessing an increasing rate of power and energy project investments. This comes as a result of countries harmonizing their legal framework and market regulations to conform the ones of European Union, enabling direct private investments. Funding in the power and energy market in this region originates from various resources and investment entities, including commercial and institutional ones. Risk anticipation and assessment is crucial to project success, especially given the long exploitation period of project in power and energy domain, as well as the wide range of stakeholders involved. This paper analyzes the possibility of combined application of tools used in total quality management and international financing institutions for project planning, execution and evaluation, with the goal of anticipating, assessing and minimizing the risks that might occur in the development and execution phase of a power and energy project in the market of southeastern Europe. History of successful project management and investments both in the industry and institutional sector provides sufficient experience, guidance and internationally adopted tools to provide proper project assessment for investments in power and energy. Business environment of southeastern Europe provides immense potential for developing power and engineering projects of various magnitudes, depending on stakeholders’ interest. Diversification on investment sources provides assurance that there is interest and commitment to invest in this market. Global economic and political developments will be intensifying the pace of investments in the upcoming period. The proposed approach accounts for key parameters that contribute to the sustainability and profitability of a project which include technological, educational, social and economic gaps between the southeastern European region and western Europe, market trends in equipment design and production on a global level, environment friendly approach to renewable energy sources as well as conventional power generation systems, and finally the effect of the One Belt One Road Initiative led by People’s Republic of China to the power and energy market of this region in the upcoming period on a long term scale. Analysis will outline the key benefits of the approach as well as the accompanying constraints. Parallel to this it will provide an overview of dominant threats and opportunities in present and future business environment and their influence to the proposed application. Through concrete examples, full potential of this approach will be presented along with necessary improvements that need to be implemented. Number of power and engineering projects being developed in southeastern Europe will be increasing in the upcoming period. Proper risk analysis will lead to minimizing project failures. The proposed successful combination of reliable project planning tools from different investment areas can prove to be beneficial in the future power and engineering investments, and guarantee their sustainability and profitability.

Keywords: capital investments, lean six sigma, logical framework approach, logical framework matrix, one belt one road initiative, project management tools, quality function deployment, Southeastern Europe, total quality management

Procedia PDF Downloads 109

Authors: Khaled Selatnia

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Nowadays, the traffic congestion becomes increasingly a chronic problem. Sometimes, the cause is attributed to the recurrent road works that create barriers to the efficient movement. But congestion, which usually occurs in cities, can take diverse forms and magnitudes. The case study of Biskra city in Algeria and the diagnosis of its road network show that throughout all the micro regional system, the road network seems at first quite dense. However, this density although it is important, does not cover all areas. A major flow is concentrated in the axis Sidi Okba – Biskra – Tolga. The largest movement of people in the Wilaya (prefecture) revolves around these three centers and their areas of influence. Centers farthest from the trio are very poorly served. This fact leads us to ask questions about the extent of congestion in Biskra city and its relationship to the imbalance of the urban framework. The objective of this paper is to highlight the impact of the urban fact on the traffic congestion.

Keywords: congestion, urban framework, regional, urban and regional studies

Procedia PDF Downloads 625

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

Procedia PDF Downloads 174

Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian, D. Ashouri

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In this research, the capability of neural networks in modeling and learning complicated and nonlinear relations has been used to develop a model for the prediction of changes in the diameter of bubbles in pool boiling distilled water. The input parameters used in the development of this network include element temperature, heat flux, and retention time of bubbles. The test data obtained from the experiment of the pool boiling of distilled water, and the measurement of the bubbles form on the cylindrical element. The model was developed based on training algorithm, which is typologically of back-propagation type. Considering the correlation coefficient obtained from this model is 0.9633. This shows that this model can be trusted for the simulation and modeling of the size of bubble and thermal transfer of boiling.

Keywords: bubble diameter, heat flux, neural network, training algorithm

Procedia PDF Downloads 443

Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

Procedia PDF Downloads 252

Authors: Gokhan Kilic, Pelin Celik

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Structural health monitoring (SHM) is widely used in evaluating the state and health of membrane structures. In the past, in order to collect data and send it to a data collection unit on membrane structures, wire sensors had to be put as part of the SHM process. However, this study recommends using wireless sensors instead of traditional wire ones to construct an economical, useful, and easy-to-install membrane structure health monitoring system. Every wireless sensor uses a software translation program that is connected to the monitoring server. Operational neural networks (ONNs) have recently been developed to solve the shortcomings of convolutional neural networks (CNNs), such as the network's resemblance to the linear neuron model. The results of using ONNs for monitoring to evaluate the structural health of a membrane are presented in this work.

Keywords: wireless sensor network, non-destructive testing, operational neural networks, membrane structures, dynamic monitoring

Procedia PDF Downloads 92

Authors: Jan Dahlhaus, Alejandro Cardenas Miranda, Frederik Scholer, Maximilian Leonhardt, Matthias Moullion, Frank Beutenmuller, Julia Eckhardt, Josef Wasner, Frank Nittel, Sebastian Stoll, Devin Atukalp, Daniel Folgmann, Tobias Mayer, Obrad Dordevic, Paul Riley, Jean-Marc Le Peuvedic

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Electrical and hybrid aerospace technologies pose very challenging demands on the battery pack – especially with respect to weight and power. In the Clean Sky 2 research project LiBAT (funded by the EU), the consortium is currently building an ambitious prototype with state-of-the art cells that shows the potential of an intelligent pack design with a high level of integration, especially with respect to thermal management and power electronics. For the latter, innovative multi-level-inverter technology is used to realize the required power converting functions with reduced equipment. In this talk the key approaches and methods of the LiBat project will be presented and central results shown. Special focus will be set on the simulative methods used to support the early design and development stages from an overall system perspective. The applied methods can efficiently handle multiple domains and deal with different time and length scales, thus allowing the analysis and optimization of overall- or sub-system behavior. It will be shown how these simulations provide valuable information and insights for the efficient evaluation of concepts. As a result, the construction and iteration of hardware prototypes has been reduced and development cycles shortened.

Keywords: electric aircraft, battery, Li-ion, multi-level-inverter, Novec

Procedia PDF Downloads 166

Authors: Yanrong Song, Zikai Dong, Runqin Xu, Jinrong Tian, Kexuan Li

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Nonlinear polarization rotation (NPR) technique has become one of the main techniques to achieve mode-locked fiber lasers for its compactness, implementation, and low cost. In this paper, we demonstrate a compact mode-locked Yb-doped fiber laser based on NPR technique in the all normal dispersion (ANDi) regime. In the laser cavity, there are no physical filter and polarization controller in laser cavity. Mode-locked pulse train is achieved in ANDi regime based on NPR technique. The fiber birefringence induced filtering effect is the mainly reason for mode-locking. After that, an extra 20 m long single-mode fiber is inserted in two different positions, dissipative soliton operation and noise like pulse operations are achieved correspondingly. The nonlinear effect is obviously enhanced in the noise like pulse regime and broadband spectrum generated owing to enhanced stimulated Raman scattering effect. When the pump power is 210 mW, the central wavelength is 1030 nm, and the corresponding 1st order Raman scattering stokes wave generates and locates at 1075 nm. When the pump power is 370 mW, the 1st and 2nd order Raman scattering stokes wave generate and locate at 1080 nm, 1126 nm respectively. When the pump power is 600 mW, the Raman continuum is generated with cascaded multi-order stokes waves, and the spectrum extends to 1188 nm. The total flat spectrum is from 1000nm to 1200nm. The maximum output average power and pulse energy are 18.0W and 14.75nJ, respectively.

Keywords: fiber laser, mode-locking, nonlinear polarization rotation, Raman scattering

Procedia PDF Downloads 221

Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

Procedia PDF Downloads 294

Authors: Nikolai David Blaskow

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Nietzsche's scholarship in the main has never quite resolved its deeply divided, at times self-contradictory responses to what Friedrich Nietzsche might have actually meant by his notion of the 'will to power'. Yet, in the context of the current global pandemic and climate change crisis, never has there been a more urgent need to investigate and resolve that contradiction. This paper argues for the 'will to power' as being a potentially irrational-rational psychopathology, one that can properly be understood only by means of Nietzsche's agonistic insights into another psychopathology—that of ressentiment. The argument also makes a case for the contention that amor fati (Nietzsche’s positive affirmation of life) may prove to be ressentiment's cure. In addition, as an integral part of the case’s methodology, the lens defined as the Mimetic and Scapegoat theory of Rene Girard (1923-2015) is brought to bear on resolving the contradiction. Ressentiment and Mimetic Theory will prove to be key players in the investigation, in as much as they expose the reasons for a modernity in crisis. The major finding of this study is that when the explanatory power of the two theories is applied, an understanding of the dynamics of the crisis in which we find ourselves emerges. The keys to that insight will include: (1) how these two psychopathologies closely resemble the contemporary neurologically defined 'borderline conditions' and their implications for culture (2) how identity politics stifle exemplary leadership, and so create toxic cultures (3) a critical assessment of Achille Mbembe's (2019) re-working of Frantz Fanon's 'ethics of the passerby' and its resonances with Nietzsche's amor fati.

Keywords: agon, amor fati, borderline conditions, ethics of the passer by, exemplary leadership, identity politics, mimesis, ressentiment, scapegoat mechanism

Procedia PDF Downloads 252

Authors: Anna Crivellari, Valerio Cozzani

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Even though most of the electricity produced in the entire world still comes from fossil fuels, new policies are being implemented in order to promote a more sustainable use of energy sources. Offshore renewable resources have become increasingly attractive thanks to the huge entity of power potentially obtained. However, the intermittent nature of renewables often limits the capacity of the systems and creates mismatches between supply and demand. Hydrogen is foreseen to be a promising vector to store and transport large amounts of excess renewable power by using existing oil and gas infrastructure. In this work, an offshore hybrid energy system integrating wind energy conversion with hydrogen production was conceptually defined and applied to offshore gas platforms. A techno-economic analysis was performed by considering two different locations for the installation of the innovative power system, i.e., the North Sea and the Adriatic Sea. The water depth, the distance of the platform from the onshore gas grid, the hydrogen selling price and the green financial incentive were some of the main factors taken into account in the comparison. The results indicated that the use of well-defined indicators allows to capture specifically different cost and revenue features of the analyzed systems, as well as to evaluate their competitiveness in the actual and future energy market.

Keywords: cost analysis, energy efficiency assessment, hydrogen production, offshore wind energy

Procedia PDF Downloads 126

Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

Procedia PDF Downloads 474

Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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Authors: Dulal Bhaumik, Fei Jie, Runa Bhaumik, Bikas Sinha

Abstract:

Human brain is an amazingly complex network. Aberrant activities in this network can lead to various neurological disorders such as multiple sclerosis, Parkinson’s disease, Alzheimer’s disease and autism. fMRI has emerged as an important tool to delineate the neural networks affected by such diseases, particularly autism. In this paper, we propose mixed-effects models together with an appropriate procedure for controlling false discoveries to detect disrupted connectivities in whole brain studies. Results are illustrated with a large data set known as Autism Brain Imaging Data Exchange or ABIDE which includes 361 subjects from 8 medical centers. We believe that our findings have addressed adequately the small sample inference problem, and thus are more reliable for therapeutic target for intervention. In addition, our result can be used for early detection of subjects who are at high risk of developing neurological disorders.

Keywords: ABIDE, autism spectrum disorder, fMRI, mixed-effects model

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Authors: Saifurahman Fayiz

Abstract:

Geo-strategically and geo-politically location of Afghanistan has endured the consideration of Indian government policy. Afghanistan has a durable and widespread economic, historical, military, and cultural relationship with India. Afghanistan has significant and durable bilateral relations with its neighbor India. India has enjoyed friendly relations with Afghanistan since 1947. After the collapse of the Taliban regime, India and Afghanistan started diplomatic relations. The relationship between the two countries was friendly and stable. The objective of this research is to study the India- Afghanistan relationship from 2001 to 2021 from different aspects. The research conducted a qualitative research method based on descriptive. The research findings propose that India should expand its soft power in Afghanistan, and India’s foreign policy in Afghanistan should be evaluated.

Keywords: relation, policy, soft power, sector

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Authors: Lopamudra Bakshi Basu

Abstract:

Transport is one of the most important characteristic features of Indian cities. The physical and societal requirements determine the selection of a particular transport system along with the uniqueness of road networks. Kolkata has a mixed traffic of which Paratransit system plays a crucial role. It is an indispensable transport system in Kolkata mainly because of its size and service flexibility which has led to a unique network character. The paratransit system, mainly the autorickshaws, is the most favoured mode of transport in the city. Its fast movement and comfortability make it a vital transport system of the city. Since the inception of the autorickshaws in Kolkata in 1981, this mode has gained popularity and presently serves nearly 80 to 90 percent of the total passenger trips. This employment generating mode of transport has increased its number rapidly affecting the city’s traffic. Minimal check on their growth by the authority has led to traffic snarls along many streets of Kolkata. Indiscipline behavior, violation of traffic rules and rash driving make situations even worse. The rise in the number and increasing popularity of the autorickshaws make it an interesting study area. Autorickshaws as a paratransit mode play its role as a leader or a follower. However, it is informal in its planning and operations, which makes it a problem area for the city. The entire research work deals with the growth and expansion of the number of vehicles and the routes within the city. The development of transport system has been interesting in the city, which has been studied. The growth of the paratransit modes in the city has been rapid. The network pattern of the paratransit mode within Kolkata has been analysed.

Keywords: growth, informal, network characteristics, paratransit, service flexibility

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Authors: Van Dong Phung, Igor Hawryszkiewycz, Kyeong Kang, Muhammad Hatim Binsawad

Abstract:

Knowledge sharing (KS) is the key to creativity and innovation in any organizations. Overcoming the KS barriers has created new challenges for designing in dynamic and complex environment. There may be interrelations and interdependences among the barriers. The purpose of this paper is to present a review of literature of KS barriers and impute the relative importance of them through the fuzzy analytic network process that is a generalization of the analytical hierarchy process (AHP). It helps to prioritize the barriers to find ways to remove them to facilitate KS. The study begins with a brief description of KS barriers and the most critical ones. The FANP and its role in identifying the relative importance of KS barriers are explained. The paper, then, proposes the model for research and expected outcomes. The study suggests that the use of the FANP is appropriate to impute the relative importance of KS barriers which are intertwined and interdependent. Implications and future research are also proposed.

Keywords: FANP, ANP, knowledge sharing barriers, knowledge sharing, removing barriers, knowledge management

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Authors: Daniel P. Clayton, Edward A. Ball

Abstract:

This paper describes an investigation into the isolation characteristics and bandwidth performance of RF combiners that are used as part of Chireix PA architectures, designed for use in the X-Band range of frequencies. Combiner designs investigated are the typical Chireix and Wilkinson configurations which also include simulation of the Wilkinson using manufacturer’s data for the isolation resistor. Another simulation was the less common approach of using a Branchline coupler to form the combiner, as well as simulation results from adding an additional stage. This paper presents the findings of this investigation and compares the bandwidth performance and isolation characteristics to determine suitability.

Keywords: bandwidth, Chireix, couplers, outphasing, power amplifiers, Wilkinson, X-Band

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

Abstract:

This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

Abstract:

In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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