Search results for: edge computing module

Authors: Mehdi Ameur, Ahmed Essakdi, Tamou Nasser

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The purpose of this paper is the analysis and modeling of the photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturb and observe (P&O), incremental conductance (INC) and fuzzy logic controller(FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: photovoltaic array, maximum power point tracking, MPPT, perturb and observe, P&O, incremental conductance, INC, hill climbing, HC, fuzzy logic controller, FLC

Procedia PDF Downloads 429

Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

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In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

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Authors: Xiaoqing Wang, Jianjian Zong, Li Li, Yanxing Zheng, Jinrong Tong, Mao Zhan

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With the rapid development of network and communication technology, a great deal of data has been generated in different domains of a network. These data show a trend of increasing scale and more complex structure. Therefore, an effective and flexible cross-domain data-sharing system is needed. The Cross-domain Data Sharing System(CDSS) in a net-centric environment is composed of three sub-systems. The data distribution sub-system provides data exchange service through publish-subscribe technology that supports asynchronism and multi-to-multi communication, which adapts to the needs of the dynamic and large-scale distributed computing environment. The access control sub-system adopts Attribute-Based Access Control(ABAC) technology to uniformly model various data attributes such as subject, object, permission and environment, which effectively monitors the activities of users accessing resources and ensures that legitimate users get effective access control rights within a legal time. The cross-domain access security negotiation subsystem automatically determines the access rights between different security domains in the process of interactive disclosure of digital certificates and access control policies through trust policy management and negotiation algorithms, which provides an effective means for cross-domain trust relationship establishment and access control in a distributed environment. The CDSS’s asynchronous,multi-to-multi and loosely-coupled communication features can adapt well to data exchange and sharing in dynamic, distributed and large-scale network environments. Next, we will give CDSS new features to support the mobile computing environment.

Keywords: data sharing, cross-domain, data exchange, publish-subscribe

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Authors: A. D. Rao, Sachiko Mohanty, R. Gayathri, V. Ranga Rao

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Modeling on coupled physical and biogeochemical processes of coastal waters is vital to identify the primary production status under different natural and anthropogenic conditions. About 7, 500 km length of Indian coastline is occupied with number of semi enclosed coastal bodies such as estuaries, inlets, bays, lagoons, and other near shore, offshore shelf waters, etc. This coastline is also rich in wide varieties of ecosystem flora and fauna. Directly/indirectly extensive domestic and industrial sewage enter into these coastal water bodies affecting the ecosystem character and create environment problems such as water quality degradation, hypoxia, anoxia, harmful algal blooms, etc. lead to decline in fishery and other related biological production. The present study is focused on the southeast coast of India, starting from Pulicat to Gulf of Mannar, which is rich in marine diversity such as lagoon, mangrove and coral ecosystem. Three dimensional Massachusetts Institute of Technology general circulation model (MITgcm) along with Darwin biogeochemical module is configured for the western Bay of Bengal (BoB) to study the biogeochemistry over this region. The biogeochemical module resolves the cycling of carbon, phosphorous, nitrogen, silica, iron and oxygen through inorganic, living, dissolved and particulate organic phases. The model domain extends from 4°N-16.5°N and 77°E-86°E with a horizontal resolution of 1 km. The bathymetry is derived from General Bathymetric Chart of the Oceans (GEBCO), which has a resolution of 30 sec. The model is initialized by using the temperature, salinity filed from the World Ocean Atlas (WOA2013) of National Oceanographic Data Centre with a resolution of 0.25°. The model is forced by the surface wind stress from ASCAT and the photosynthetically active radiation from the MODIS-Aqua satellite. Seasonal climatology of nutrients (phosphate, nitrate and silicate) for the southwest BoB region are prepared using available National Institute of Oceanography (NIO) in-situ data sets and compared with the WOA2013 seasonal climatology data. The model simulations with the two different initial conditions viz., WOA2013 and the generated NIO climatology, showed evident changes in the concentration and the evolution of the nutrients in the study region. It is observed that the availability of nutrients is more in NIO data compared to WOA in the model domain. The model simulated primary productivity is compared with the spatially distributed satellite derived chlorophyll data and at various locations with the in-situ data. The seasonal variability of the model simulated primary productivity is also studied.

Keywords: Bay of Bengal, Massachusetts Institute of Technology general circulation model, MITgcm, biogeochemistry, primary productivity

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Lila A. Alkhattaby, Norah A. Alsayegh, Mohammad S. Ansari, Mohammad O. Ansari

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In this work, we doped zinc oxide ZnO with potassium K we have synthesized using the sol-gel method. Structural properties were depicted by X-ray diffractometer (XRD) and energy distribution spectroscopy, X-ray diffraction studies confirm the nanosized of the particles and favored orientations along the (100), (002), (101), (102), (110), (103), (200), and (112) planes confirm the hexagonal wurtzite structure of ZnO NPs. The optical properties study using the UV-Vis spectroscopy. The band gap decreases from 4.05 eV to 3.88 eV, the lowest band gap at 10% doped concentration. The photoluminescence (PL) spectroscopy results show two main peaks, a sharp peak at ≈ 384 nm in the UV region and a broad peak around 479 nm in the visible region. The highest intensity of the band-edge luminescence was for 2% doped concentration because of the combined effect of the decreased probability of nonradiative recombination and has better crystallinity.

Keywords: K doped ZnO, photoluminescence spectroscopy, UV-Vis spectroscopy, x-ray spectroscopy

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Authors: Tabassum Husain, Shen Peng Li, Zhaolin Chen

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This paper evaluates the usability of 3D Guided Image Filtering to enhance the quality of short-time binned dynamic PET images by using MRI images. Guided image filtering is an edge-preserving filter proposed to enhance 2D images. The 3D filter is applied on 1 and 5-minute binned images. The results are compared with 15-minute binned images and the Gaussian filtering. The guided image filter enhances the quality of dynamic PET images while also preserving important information of the voxels.

Keywords: dynamic PET images, guided image filter, image enhancement, information preservation filtering

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Nevruz Zogu, Shpetim Rezniqi

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It is very important that a new environment where work shall be constructed in such a strong record to be creative and eligible for workers, can not have success in the workplace. But, is it possible to design the inner-inspire to create and collaborate? By watching and analyzing examples of creativity in business, construction managers can learn ways on how to encourage their imagination inside buildings. We struggle to find and retain talented employees and skilled labor environment is becoming more and always an important tool for recruiting and retaining employees. Managers who recognize the importance are gaining an edge over their competitors. The physical work environment is as important as its quality is often used as a recruiting tool and even to companies with The relationship between the company and the employees between strategy and behavior, between the product and the customer can reincorporated under the light of symbolic mediation of space, as instrument and interpreter of the core values and identity of the organization.

Keywords: strategy, business, quality, productivity, space, offices, assets

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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Authors: G. Rajapakse, S. Jayasinghe, A. Fleming

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This paper aims to experimentally validate the control strategy used for electrical power converters in grid integrated oscillating water column (OWC) wave energy converter (WEC). The particular OWC’s unidirectional air turbine-generator output power results in discrete large power pulses. Therefore, the system requires power conditioning prior to integrating to the grid. This is achieved by using a back to back power converter with an energy storage system. A Li-Ion battery energy storage is connected to the dc-link of the back-to-back converter using a bidirectional dc-dc converter. This arrangement decouples the system dynamics and mitigates the mismatch between supply and demand powers. All three electrical power converters used in the arrangement are controlled using finite control set-model predictive control (FCS-MPC) strategy. The rectifier controller is to regulate the speed of the turbine at a set rotational speed to uphold the air turbine at a desirable speed range under varying wave conditions. The inverter controller is to maintain the output power to the grid adhering to grid codes. The dc-dc bidirectional converter controller is to set the dc-link voltage at its reference value. The software modeling of the OWC system and FCS-MPC is carried out in the MATLAB/Simulink software using actual data and parameters obtained from a prototype unidirectional air-turbine OWC developed at Australian Maritime College (AMC). The hardware development and experimental validations are being carried out at AMC Electronic laboratory. The designed FCS-MPC for the power converters are separately coded in Code Composer Studio V8 and downloaded into separate Texas Instrument’s TIVA C Series EK-TM4C123GXL Launchpad Evaluation Boards with TM4C123GH6PMI microcontrollers (real-time control processors). Each microcontroller is used to drive 2kW 3-phase STEVAL-IHM028V2 evaluation board with an intelligent power module (STGIPS20C60). The power module consists of a 3-phase inverter bridge with 600V insulated gate bipolar transistors. Delta standard (ASDA-B2 series) servo drive/motor coupled to a 2kW permanent magnet synchronous generator is served as the turbine-generator. This lab-scale setup is used to obtain experimental results. The validation of the FCS-MPC is done by comparing these experimental results to the results obtained by MATLAB/Simulink software results in similar scenarios. The results show that under the proposed control scheme, the regulated variables follow their references accurately. This research confirms that FCS-MPC fits well into the power converter control of the OWC-WEC system with a Li-Ion battery energy storage.

Keywords: dc-dc bidirectional converter, finite control set-model predictive control, Li-ion battery energy storage, oscillating water column, wave energy converter

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Authors: Sandy Bao, Yankang Bao

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The understanding of information that is being processed in the brain, especially in the lateral geniculate nucleus (LGN), has been proven challenging for modern neuroscience and for researchers with a focus on how neurons process signals and images. In this paper, we are proposing a method to image process different colors within different layers of LGN, that is, green information in layers 4 & 6 and red & blue in layers 3 & 5 based on the surface dimension of layers. We take into consideration the images in LGN and visual cortex, and that the edge detected information from the visual cortex needs to be considered in order to return back to the layers of LGN, along with the image in LGN to form the new image, which will provide an improved image that is clearer, sharper, and making it easier to identify objects in the image. Matrix Laboratory (MATLAB) simulation is performed, and results show that the clarity of the output image has significant improvement.

Keywords: lateral geniculate nucleus, matrix laboratory, neuroscience, visual cortex

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Authors: Arshleen Kaur, Sarang Barbarwar, Madhusudan Hamirwasia

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Sustainable architecture is going to be the soul of construction in the near future, with building material as a vital link connecting sustainability to construction. The priority in Architecture has shifted from having a lesser negative footprint to having a positive footprint on Earth. The design has to be eco-centric as well as anthro-centric so as to attain its true purpose. Brick holds the same importance like a cell holds in one’s body. The study focuses on this basic building block with an experimental material and technique known as Module Assembled Specially to Conserve (MASC). The study explores the usage and construction of these modules in the construction of buildings. It also shows the impact assessment of the modules on the environment and its significance in reducing the carbon footprint of the construction industry. The aspects like cost-effectiveness, ease of working and reusability of MASC have been studied as well.

Keywords: anthro-centric, carbon footprint, eco-centric, sustainable

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Authors: Prakash Persad, Kelvin Loutan, Trichelle Seepersad

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The Finite Element Method is commonly used in the analysis of flexible manipulators to predict elastic displacements and develop joint control schemes for reducing positioning error. In order to preserve simplicity, regular geometries, ideal joints and connections are assumed. This paper presents the dynamic FE analysis of a 4- degrees of freedom open chain manipulator, intended for striking a curved 3D surface percussion musical instrument. This was done utilizing the new MultiBody Dynamics Module in COMSOL, capable of modeling the elastic behavior of a body undergoing rigid body type motion.

Keywords: dynamic modeling, entertainment robots, finite element method, flexible robot manipulators, multibody dynamics, musical robots

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Authors: Vishal V. Choudhari, Gaurao A. Dongre, S. P. Diwan

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A number of reference current generation have been developed for analysis of shunt active power filter to mitigate the load compensation. Depending upon the type of load the technique has to be chosen. In this paper, six reference current generation techniques viz. instantaneous reactive power theory(IRP), Synchronous reference frame theory(SRF), Perfect harmonic cancellation(PHC), Unity power factor method(UPF), Self-tuning filter method(STF), Predictive filtering method(PFM) are compared for different operating conditions. The harmonics are introduced because of non-linear loads in the system. These harmonics are eliminated using above techniques. The results and performance of system simulated on MATLAB/Simulink platform. The system is experimentally implemented using DS1104 card of dSPACE system.

Keywords: SAPF, power quality, THD, IRP, SRF, dSPACE module DS1104

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Authors: Rolla Monib, Chris Ian Goodier, Alistair Gibb

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This paper aims to investigate decision support strategies in the EC sector to determine the most appropriate degree of modularization. This is achieved through three oil and gas (O&G) and two power plant case studies via semi-structured interviews (n=59 and n=27, respectively), analysis of project documents, and case study-specific semi-structured validation interviews (n=12 and n=8). New terminology to distinguish degrees of modularization is proposed, along with a decision-making support checklist and a diagrammatic decision-making support figure. Results indicate that the EC sub-sectors were substantially more satisfied with the application of component, structural, or traditional modularization compared with system modularization for some types of modules. Key drivers for decisions on the degree of modularization vary across module types. This paper can help the EC sector determine the most suitable degree of modularization via a decision-making support strategy.

Keywords: modularization, engineering construction, case study, decision support

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Authors: Priya Sharma

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As one think of fashion, the only things that come to mind are feminine activities such as acquiring high-end bags, clothing, and shoes. A person's personal style is defined by their clothing. Fashion been more feminine over the centuries, but the masculine identity has also dwindled. Fashion has an impact on social status, trends, and the socio-economic and political environment. The major focus of this study is on how the most prominent fast fashion businesses establish their gender identities in order to achieve industry legitimacy. A questionnaire survey was conducted to understand the people prospection. It also helps in understanding the different driving factors which contribute collectively from the Doman from social and economic norms across the different reign in India. A conceptual module was made which help to understand the future scope of fashion with respect to gender identity in India. The ways there feel to create their own personal style and their feelings and how fashion can make more confident and authentic in their minds.

Keywords: fashion, gender, identity, feminism, environment

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Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: T. A. Khan, A. B. Khan, M. Babar, T. A. Taj, Imran Ijaz Imran

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Smart Meter is a key element in the evolving concept of Smart Grid, which plays an important role in interaction between the consumer and the supplier. In general, the smart meter is an intelligent digital energy meter that measures the consumption of electrical energy and provides other additional services as compared to the conventional energy meters. One of the important element that makes a meter smart and different is its communication module. Smart meters usually have two way and real-time communication between the consumer and the supplier through which its transfer data and information. In this paper, Ultra Wide Band (UWB) is recommended as communication platform because of its high data-rate and presents the physical layer, which could be easily incorporated in existing Smart Meters. The physical layer is simulated in MATLAB Simulink and the results are provided.

Keywords: Ultra Wide Band (UWB), Smart Meter, MATLAB, transfer data

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Authors: Hazem Bunkheila

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Ghadames is an oasis on the edge of the Sahara Desert in southwestern Libya at the border with Algeria and Tunisia. It is the oldest oasis in the world that provides a fascinating example of traditional urban in the desert environment. The urban of the small city is considered a genuine adaptation to the harsh desert climate. The historic city of Ghadames remained unaffected by the rapid after oil changes. That makes it a good field to study sustainable, vernacular, earth architecture and urban design. The aim of this paper is to investigate the urban structure, concept, and fabric of the old oasis. The research also surveys the environmental considerations in the city that shades the sustainable features in this traditional residential area. In addition, the paper addresses the modern applications in the new city of Ghadams and sides of success and failure compared to the traditional urban fabric.

Keywords: dessert climate design, Ghadames, sustainable urban design, traditional urban design

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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This employee productivity and work well-being effective system aims to maximise the work performance of personnel and boost well-being in offices. Affective computing, decision support, and knowledge-based systems were used in our research. The basis of this effective system is our European Patent application (No: EP 4 020 134 A1) and two Lithuanian patents (LT 6841, LT 6866). Our study examines ways to support efficient employee productivity and well-being by employing mass-customised, personalised office environment. Efficient employee performance and well-being are managed by changing mass-customised office environment factors such as air pollution levels, humidity, temperature, data, information, knowledge, activities, lighting colours and intensity, scents, media, games, videos, music, and vibrations. These aspects of management generate a customised, adaptive environment for users taking into account their emotional, affective, and physiological (MAP) states measured and fed into the system. This research aims to develop an innovative method and system which would analyse, customise and manage a personalised office environment according to a specific user’s MAP states in a cohesive manner. Various values of work spaces (e.g., employee utilitarian, hedonic, perceived values) are also established throughout this process, based on the measurements that describe MAP states and other aspects related to the office environment. The main contribution of our research is the development of a real-time mass-customised office environment to boost employee performance and well-being. Acknowledgment: This work was supported by Project No. 2020-1-LT01-KA203-078100 “Minimizing the influence of coronavirus in a built environment” (MICROBE) from the European Union’s Erasmus + program.

Keywords: effective decision support and a knowledge-based system, human resource management, employee productivity and work well-being, affective computing

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Authors: T. Teruzzi, S. Antonietti, C. Mosca, C. Paglia

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This paper discusses the causes of the structural failure in a tower crane. The structural collapse occurred at the upper joints of the extension element used to increase the height of the crane. The extension element consists of a steel lattice structure made with angular profiles and plates joined to the tower element by arc welding. Macroscopic inspection of the sections showed that the break was always observed on the angular profiles at the weld bead edge. The case study shows how, using mechanical characterization, chemical analysis of the steel and macroscopic and microscopic metallographic examinations, it was possible to obtain significant evidence that identified the mechanism causing the breakage. The analyses identified the causes of the structural failure as the use of materials that were not suitable for welding and poor performance in the welding joints.

Keywords: failure, metals, weld, microstructure

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Authors: Naime Boudemagh

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In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

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Authors: Gaurav Prabhudesai, Shaurya Kaushal, Pulkit Dubey, B. D. Pant

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The current race of miniaturization of circuits, systems, modules and networks has resulted in portable and mobile wireless systems having tremendous capabilities with small volume and weight. The power drivers or the power pack, electrically driving these modules have also reduced in proportion. Normally, the power packs in these mobile or fixed systems are batteries, rechargeable or non-rechargeable, which need regular replacement or recharging. Another approach to power these modules is to utilize the ambient energy available for electrical driving to make the system self-sustained. The current paper presents an overview of the different MEMS (Micro-Electro-Mechanical Systems) based techniques used for the harvesting of vibration energy to electrically drive a WSN (wireless sensor network) or a mobile module. This kind of system would have enormous applications, the most significant one, may be in cell phones.

Keywords: energy harvesting, WSN, MEMS, piezoelectrics

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Authors: Maibigue Nanglet, Arafat Ousman Béchir, Mahamat Hassan Béchir

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The economy of Central African countries is growing very fast, and the demand for energy is increasing every day. As a result, insufficient power generation is one of the major problems slowing down development. This paper explores the factors of degradation of the I-V curve of the PV Generator (GPV) in harsh environments, taking the case of two locals: Mongo and Abeche. Its objective is to quantify the voltage leaks due to the different GPV installation areas; after using the Newton-Raphson numerical method of the solar cell, a survey of several experimental measurement points was made. The results of the simulation in MATLAB/Simulink show a relative power loss factor of 11.8765% on the GPVs installed in Mongo and 8.5463% on those installed in Abeche; these results allow us to say that the supports on which the modules are installed have an average impact of 10.2114% on their efficiency.

Keywords: calculation, degradation, site, GPV, severe environment

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Authors: Helen Potkin

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This paper presents a practice-based case study of a project in which the student group designed and planned the curriculum content, classroom activities and assessment briefs in collaboration with the tutor. It focuses on the co-creation of the curriculum within a history and theory module, Researching the Contemporary, which runs for BA (Hons) Fine Art and Art History and for BA (Hons) Art Design History Practice at Kingston University, London. The paper analyses the potential of collaborative approaches to engender students’ investment in their own learning and to encourage reflective and self-conscious understandings of themselves as learners. It also addresses some of the challenges of working in this way, attending to the risks involved and feelings of uncertainty produced in experimental, fluid and open situations of learning. Alongside this, it acknowledges the tensions inherent in adopting such practices within the framework of the institution and within the wider of context of the commodification of higher education in the United Kingdom. The concept underpinning the initiative was to test out co-creation as a creative process and to explore the possibilities of altering the traditional hierarchical relationship between teacher and student in a more active, participatory environment. In other words, the project asked about: what kind of learning could be imagined if we were all in it together? It considered co-creation as producing different ways of being, or becoming, as learners, involving us reconfiguring multiple relationships: to learning, to each other, to research, to the institution and to our emotions. The project provided the opportunity for students to bring their own research and wider interests into the classroom, take ownership of sessions, collaborate with each other and to define the criteria against which they would be assessed. Drawing on students’ reflections on their experience of co-creation alongside theoretical considerations engaging with the processual nature of learning, concepts of equality and the generative qualities of the interrelationships in the classroom, the paper suggests that the dynamic nature of collaborative and participatory modes of engagement have the potential to foster relevant and significant learning experiences. The findings as a result of the project could be quantified in terms of the high level of student engagement in the project, specifically investment in the assessment, alongside the ambition and high quality of the student work produced. However, reflection on the outcomes of the experiment prompts a further set of questions about the nature of positionality in connection to learning, the ways our identities as learners are formed in and through our relationships in the classroom and the potential and productive nature of creative practice in education. Overall, the paper interrogates questions of what it means to work with students to invent and assemble the curriculum and it assesses the benefits and challenges of co-creation. Underpinning it is the argument that, particularly in the current climate of higher education, it is increasingly important to ask what it means to teach and to envisage what kinds of learning can be possible.

Keywords: co-creation, collaboration, learning, participation, risk

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Authors: Siti Ruhliah Lizarose Samion, Mohamed Sukri Mat Ali

Abstract:

The effect of sawtooth plate thickness on the aerodynamic noise generated in flow at a Reynolds number of 150 is numerically investigated. Two types of plate thickness (hthick=0.2D and hthin=0.02D) are proposed. Flow simulations are carried out using Direct Numerical Simulation, whereas the calculation of aerodynamic noise radiated from the flow is solved using Curle’s equation. It is found that the flow behavior of thin sawtooth plate, consisting counter-rotating-vortices, is more complex than that of the thick plate. This then explains well the generated sound in both plates cases. Sound generated from thin plat is approximately 0.5 dB lower than the thick plate. Findings from current study provide better understanding of the flow and noise behavior in edge serrations via understanding the case of a sawtooth plate.

Keywords: aerodynamic sound, bluff body, sawtooth plate, Curle analogy

Procedia PDF Downloads 436

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

Abstract:

The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

Procedia PDF Downloads 137

Authors: Muhammad Naeem, Syed M. Moeen-ud-Din Raheel, Muhammad Arshad, Muhammad Naeem Qaisar, Muhammad Khalid, Muhammad Zubair Ahmed, Muhammad Ashraf

Abstract:

Iron, Copper, Cadmium, Zinc, Manganese, Chromium levels were estimated to study the risk of trace elements on human consumption. The area of collection was Dera Ghazi Khan, Pakistan and was evaluated by means of flame atomic absorption spectrophotometer. The standards find in favor of the six heavy metals were in accordance with the threshold edge concentrations on behalf of fish meat obligatory by European and other international normative. Regressions were achieved for both size (length and weight) and condition factor with concentrations of metal present in the fish body.

Keywords: Oreochromis mossambica, toxic analysis, body size, condition factor

Procedia PDF Downloads 584