Search results for: grid-interactive efficient buildings (GEB)

Authors: Wael I. Alnahhal

Abstract:

It is a major challenge to build a bridge superstructure that has long-term durability and low maintenance requirements. A solution to this challenge may be to use new materials or to implement new structural systems. Fiber reinforced polymer (FRP) composites have continued to play an important role in solving some of persistent problems in infrastructure applications because of its high specific strength, light weight, and durability. In this study, the concept of the hybrid FRP-concrete structural systems is applied to a bridge superstructure. The hybrid FRP-concrete bridge superstructure is intended to have durable, structurally sound, and cost effective hybrid system that will take full advantage of the inherent properties of both FRP materials and concrete. In this study, two hybrid FRP-concrete bridge systems were investigated. The first system consists of trapezoidal cell units forming a bridge superstructure. The second one is formed by arch cells. The two systems rely on using cellular components to form the core of the bridge superstructure, and an outer shell to warp around those cells to form the integral unit of the bridge. Both systems were investigated analytically by using finite element (FE) analysis. From the rigorous FE studies, it was concluded that first system is more efficient than the second.

Keywords: bridge superstructure, hybrid system, fiber reinforced polymer, finite element analysis

Procedia PDF Downloads 336

Authors: Yang Li, Mingkai Liu, Qiong Rao, Zhongrui Gai, Ying Pan, Hongguang Jin

Abstract:

Hydrogen is an ideal and potential energy carrier due to its high energy efficiency and low pollution. An alternative and promising approach to hydrogen generation is the chemical looping steam reforming of methane (CL-SRM) over iron-based oxygen carriers. However, the process faces challenges such as high reaction temperature (>850 ℃) and low methane conversion. We demonstrate that Ni-mixed Fe-based oxygen carrier particles have significantly improved the methane conversion and hydrogen production rate in the range of 450-600 ℃ under atmospheric pressure. The effect on the reaction reactivity of oxygen carrier particles mixed with different Ni-based particle mass ratios has been determined in the continuous unit. More than 85% of methane conversion has been achieved at 600 ℃, and hydrogen can be produced in both reduction and oxidation steps. Moreover, the iron-based oxygen carrier particles exhibited good cyclic performance during 150 consecutive redox cycles at 600 ℃. The mid-temperature iron-based oxygen carrier particles, integrated with a moving-bed chemical looping system, might provide a powerful approach toward more efficient and scalable hydrogen production.

Keywords: chemical looping, hydrogen production, mid-temperature, oxygen carrier particles

Procedia PDF Downloads 147

Authors: M. Nagaraja, H. M. Mahesh, K. Rajanna, M. Z. Kurian, J. Manjanna

Abstract:

In recent years, composites of conjugated polymers with fullerenes (C60) has attracted considerable scientific and technological attention in the field of organic electronics because they possess a novel combination of electrical, optical, ferromagnetic, mechanical and sensor properties. These properties represent major advances in the design of organic electronic devices. With the addition of C60 in the conjugated polymer matrix, the primary photo-excitation of the conjugated polymer undergoes an ultrafast electron transfer, and it has been demonstrated that fullerene molecules may serve as efficient electron acceptors in polymeric solar cells. The present paper includes the systematic studies on the effect of electrical, structural and sensor properties of polyaniline (PANI) matrix by the presence of C60. Polyaniline-fullerene (PANI/C60) composite is prepared by the introduction of fullerene during polymerization of aniline with ammonium persulfate and dodechyl benzene sulfonic acid as oxidant and dopant respectively. FTIR spectroscopy indicated the interaction between PANI and C60. X-ray diffraction proved the formation of a PANI/C60 complex. SEM image shows the highly branched chain structure of the PANI in the presence of C60. The conductivity of the PANI/C60 was found to be more than ten orders of magnitude over the pure PANI.

Keywords: conductivity, fullerene, nanocomposite, polyaniline

Procedia PDF Downloads 218

Authors: Ritu Ahuja

Abstract:

Globally the built environment sector is striving to be highly efficient, quality-centred and socially-responsible. Built environment sector is an integral part of the economy and plays an important role in urbanization, industrialization and improved quality of living. The inherent challenges such as excessive material and process waste, over reliance on resources, energy usage, and carbon footprint need to be addressed in order to meet the needs of the economy. It is envisioned that these challenges can be resolved by integration of Lean-Green-Building Information Modelling (BIM) paradigms. Ipso facto, with BIM as a catalyst, this research identifies the operational and tactical connections of lean and green philosophies by providing a conceptual integration framework and underpinning theories. The research has developed a framework for BIM-based organizational capabilities for enhanced adoption and effective use of BIM within architectural organizations. The study was conducted through a sequential mixed method approach focusing on collecting and analyzing both qualitative and quantitative data. The framework developed as part of this study will enable architectural organizations to successfully embrace BIM on projects and gain lean and green benefits.

Keywords: BIM, lean, green, AEC organizations

Procedia PDF Downloads 191

Authors: Ridoy Das, Myriam Neaimeh, Yue Wang, Ghanim Putrus

Abstract:

Electric vehicles are a popular transportation medium renowned for potential environmental benefits. However, large and uncontrolled charging volumes can impact distribution networks negatively. Smart charging is widely recognized as an efficient solution to achieve both improved renewable energy integration and grid relief. Nevertheless, different decision-makers may pursue diverse and conflicting objectives. In this context, this paper proposes a multi-objective optimization framework to control electric vehicle charging to achieve both energy cost reduction and peak shaving. A weighted-sum method is developed due to its intuitiveness and efficiency. Monte Carlo simulations are implemented to investigate the impact of uncertain electric vehicle driving patterns and provide decision-makers with a robust outcome in terms of prospective cost and network loading. The results demonstrate that there is a conflict between energy cost efficiency and peak shaving, with the decision-makers needing to make a collaborative decision.

Keywords: electric vehicles, multi-objective optimization, uncertainty, mixed integer linear programming

Procedia PDF Downloads 180

Authors: Münüre Tanur Erkoyuncu, Mustafa Yorgancılar

Abstract:

Crop improvement through genetic engineering depends on effective and reproducible plant regeneration systems. Immature embryos are the most widely used explant source for in vitro regeneration in barley (Hordeum vulgare L.). However, immature embryos require the continuous growth of donor plants and the suitable stage for their culture is also certainly limited. On the other hand, mature embryos can be procured and stored easily; they can be studied throughout the year. In this study, an effective callus induction and plant regeneration were aimed to develop from mature embryos of different barley genotypes. The effect of medium (MS₁ and MS₂), auxin type (2,4-D, dicamba, picloram and 2,4,5-T) and concentrations (2, 4, 6 mg/l) on callus formation and effect of cytokinin type (TDZ, BAP) and concentrations (0.2, 0.5, 1.0 mg/l) on green plant regeneration were evaluated in mature embryo culture of barley. Callus and shoot formation was successful for all genotypes. By depending on genotype, MS₁ is the best medium, 4 mg/l dicamba is the best growth regulator in the callus induction and MS₁ is the best medium, 1 mg/l BAP is the best growth regulator in the shoot formation were determined.

Keywords: barley, callus, embryo culture, mature embryo

Procedia PDF Downloads 328

Authors: Kashika P. H.

Abstract:

The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

Procedia PDF Downloads 108

Authors: Derssie Mebratu

Abstract:

As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

Procedia PDF Downloads 97

Authors: Anu Paul, Varghese Paul

Abstract:

The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model

Procedia PDF Downloads 524

Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

Abstract:

In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

Procedia PDF Downloads 238

Authors: Amar Danial Abd Azis, Shipun Anuar Hamzah, Mohd Noh Dalimin, Khairun Nidzam Ramli, Mohd Sani Yahya, Fauziahanim Che Seman

Abstract:

This paper discusses the design, simulation results, and testing of a compact dual-band printed dipole antenna operating at frequencies of 916 MHz and 1.57 GHz for LoRa and GPS applications, respectively. The basic design of this antenna uses a linear dipole that operates at 916 MHz and 2.7 GHz. A small triangular-shaped linear balun has been developed as the matching network. Parasitic elements are employed to tune the second frequency to 1.57 GHz through a parametric study. Meanwhile, a stub is used to suppress the undesired 2.6 GHz frequency. This antenna is capable of operating on dual-frequency bands simultaneously with high efficiency in suppressing the unwanted frequency. The antenna exhibits the following parameters: return loss of -18.5 dB at 916 MHz and -14 dB at 1.57 GHz, VSWR of 1.25 at 868 MHz and 1.5 at 1.57 GHz, and gain of 2 dBi at 916 MHz and 2.75 dBi at 1.57 GHz. The radiation pattern of the antenna shows a directional E-plane and an omnidirectional H-plane at both frequencies. With its compact size and dual-band capability, this antenna demonstrates great potential for use in IoT applications that require both LoRa and GPS communication, particularly in applications where a small yet efficient form factor is essential.

Keywords: dual band, dipole antenna, parasitic elements, harmonic suppression, LoRa and Gps

Procedia PDF Downloads 16

Authors: Serge B. Provost

Abstract:

Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

Procedia PDF Downloads 166

Authors: Lamia Hammadi, Abdellah Ait Ouhman, Aomar Ibourk

Abstract:

It is widely assumed that the case of Customs Supply Chain is classified as a complex system, due to not only the variety and large number of actors, but also their complex structural links, and the interactions between these actors, that’s why this system is subject to various types of Risks. The economic, political and social impacts of those risks are highly detrimental to countries, businesses and the public, for this reason, Risk management in the customs supply chain is becoming a crucial issue to ensure the sustainability, security and safety. The main characteristic of customs risk management approach is determining which goods and means of transport should be examined? To what extend? And where future compliance resources should be directed? The purposes of this article are, firstly to deal with the concept of customs supply chain, secondly present our risk management approach based on Cross Activity Based Costing (ABC) Method as an interactive tool to support decision making in customs risk management. Finally, analysis of case study of Moroccan customs to putting theory into practice and will thus draw together the various elements of a structured and efficient risk management approach.

Keywords: cross ABC method, customs supply chain, risk, risk management

Procedia PDF Downloads 381

Authors: Elham Ahmadi, Roshaali Khaturia, Pardis Sahraei, Mohammad Niyayesh, Omid Fatahi Valilai

Abstract:

Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.

Keywords: vendor managed inventory, VMI, blockchain technology, supply chain planning, sustainability

Procedia PDF Downloads 228

Authors: Romisaa Ali

Abstract:

This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

Procedia PDF Downloads 107

Authors: Vanaja Rao

Abstract:

In the recent times, the need for the integration of Renewable Energy Sources (RES) in a Smart Grid is on the rise. As a result of this, associated energy storage systems are known to play important roles in sustaining the efficient operation of such RES like wind power and solar power. This paper investigates the importance of location selection of Energy Storage Systems (ESSs) in a Smart Grid. Three scenarios of ESS location is studied and analyzed in a Smart Grid, which are – 1. Near the generation/source, 2. In the middle of the Grid and, 3. Near the demand/consumption. This is explained with the aim of assisting any Distribution Network Operator (DNO) in deploying the ESSs in a power network, which will significantly help reduce the costs and time of planning and avoid any damages incurred as a result of installing them at an incorrect location of a Smart Grid. To do this, the outlined scenarios mentioned above are modelled and analyzed with the National Grid’s datasets of energy generation and consumption in the UK power network. As a result, the outcome of this analysis aims to provide a better overview for the location selection of the ESSs in a Smart Grid. This ensures power system stability and security along with the optimum usage of the ESSs.

Keywords: distribution networks, energy storage system, energy security, location planning, power stability, smart grid

Procedia PDF Downloads 301

Authors: Daniele Losanno, Giorgio Serino

Abstract:

This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete frames

Procedia PDF Downloads 294

Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai

Abstract:

An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.

Keywords: safety, highway geometry, optimization, alignment

Procedia PDF Downloads 412

Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

Abstract:

Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

Procedia PDF Downloads 197

Authors: Tripti Watwe

Abstract:

Music or art of any country is its national heritage and represents the cultural personality of that region. Noble Laureate Rabindranath Tagore through his international educational endeavour called ‘Visva-Bharati’ established this concept that music can very much be a part of the mainstream education of a country because the purpose of both music and education is to bring in transformation in an individual. An individual with musical veins is more focused and meditative towards his or her goal in life. That is why in Tagore’s Visva-Bharati, one can observe even the brightest brains from various fields of economics, science, social sciences or literature equally verbal and efficient in Rabindra songs which the poet created under his own name.Tagore established this phenomenon that music if made a part of education and life, brings in profound transformation in the character and over-all personality of a person giving better and responsible citizens to a nation. It is expected that this hypothesis that music and education can be a nectarine combination can be established and proved with the help of various recorded observations containing Tagore’s educational philosophy, his experiments in his own institution ‘Visva-Bharati’ and through recorded research materials which have been gathered during the author’s field work in Visva-Bharati.

Keywords: Rabindranath Tagore, Visva-Bharati, education, music, philosophy

Procedia PDF Downloads 300

Authors: Felix Givois, Nicolas R. Gauger, Matthias Kabel

Abstract:

The efficient digital material characterization is of great interest to many fields of application. It consists of the following three steps. First, a 3D reconstruction of 2D scans must be performed. Then, the resulting gray-value image of the material sample is enhanced by image processing methods. Finally, partial differential equations (PDE) are solved on the segmented image, and by averaging the resulting solutions fields, effective properties like stiffness or conductivity can be computed. Due to the high resolution of current CT images, the latter is typically performed with matrix-free solvers. Among them, a solver that uses the explicit formula of the Green-Eshelby operator in Fourier space has been proposed by Moulinec and Suquet. Its algorithmic, most complex part is the Fast Fourier Transformation (FFT). In our talk, we will discuss the potential quantum advantage that can be obtained by replacing the FFT with the Quantum Fourier Transformation (QFT). We will especially show that the data transfer for noisy intermediate-scale quantum (NISQ) devices can be improved by using appropriate boundary conditions for the PDE, which also allows using semi-classical versions of the QFT. In the end, we will compare the results of the QFT-based algorithm for simple geometries with the results of the FFT-based homogenization method.

Keywords: most likelihood amplitude estimation (MLQAE), numerical homogenization, quantum Fourier transformation (QFT), NISQ devises

Procedia PDF Downloads 81

Authors: Stefan K. Behfar

Abstract:

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

Procedia PDF Downloads 78

Authors: Gizachew Belay Adugna

Abstract:

Perovskite solar cells (PSCs) shows rapid development as an emerging photovoltaic material; however, the fast device degradation due to the organic nature, mainly hole transporting material (HTM) and lack of robust and reliable upscaling process for photovoltaic module hindered its commercialization. Herein, HTM molecules with/without fluorine-substituted cyclopenta[2,1-b;3,4-b’]dithiophene derivatives (HYC-oF, HYC-mF, and HYC-H) were developed for PSCs application. The fluorinated HTM molecules exhibited better hole mobility and overall charge extraction in the devices mainly due to strong molecular interaction and packing in the film. Thus, the highest power conversion efficiency (PCE) of 19.64% with improved long stability was achieved for PSCs based on HYC-oF HTM. Moreover, the fluorinated HYC-oF demonstrated excellent film processability in a larger-area substrate (10 cm×10 cm) prepared sequentially with the absorption perovskite underlayer via a scalable bar coating process in ambient air and owned a higher PCE of 18.49% compared to the conventional spiro-OMeTAD (17.51%). The result demonstrates a facile development of HTM towards stable and efficient PSCs for future industrial-scale PV modules.

Keywords: perovskite solar cells, upscaling film coating, power conversion efficiency, solution processing

Procedia PDF Downloads 76

Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

Abstract:

Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

Procedia PDF Downloads 186

Authors: Abdelhadi Adel, Kadri Ouahab

Abstract:

This paper proposes a hybrid algorithm for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

Procedia PDF Downloads 339

Authors: Chih Hung Shih

Abstract:

Eyewitness identification is one of the efficient information to identify suspects during criminal investigation. However eyewitness identification is improved frequently, inaccurate and plays vital roles in wrongful convictions. Most eyewitness misidentifications are made during police criminal investigation stage and then accepted by juries. Four failure investigation case studies in Taiwan are conduct to demonstrate how misidentifications are caused during the police investigation context. The result shows that there are several common grounds among these cases: (1) investigators lacked for knowledge about eyewitness memory so that they couldn’t evaluate the validity of the eyewitnesses’ accounts and identifications, (2) eyewitnesses were always asked to filter out several suspects during the investigation, and received investigation information which contaminated the eyewitnesses’ memory, (3) one to one live individual identifications were made in most of cases, (4) eyewitness identifications were always used to support the hypotheses of investigators, and exaggerated theirs powers when conform with the investigation lines, (5) the eyewitnesses’ confidence didn’t t reflect the validity of their identifications , but always influence the investigators’ beliefs for the identifications, (6) the investigators overestimated the power of the eyewitness identifications and ignore the inconsistency with other evidence. Recommendations have been proposed for future academic research and police practice of eyewitness identification in Taiwan.

Keywords: criminal investigation, eyewitness identification, investigative bias, investigative failures

Procedia PDF Downloads 247

Authors: William G. "Gus" Simmons

Abstract:

Municipal and industrial wastewater plants across our country utilize anaerobic digestion as either primary treatment or as a means of waste sludge treatment and reduction. The emphasis on renewable energy and clean energy over the past several years, coupled with increasing electricity costs and increasing consumer demands for efficient utility operations has led to closer examination of the potential for harvesting the energy value of the biogas produced by anaerobic digestion. Although some facilities may have already come to the belief that harvesting this energy value is not practical or a top priority as compared to other capital needs and initiatives at the wastewater plant, we see that many are seeing biogas, and an opportunity for additional revenues, go up in flames as they continue to flare. Conversely, few wastewater plants under progressive and visionary leadership have demonstrated that harvesting the energy value from anaerobic digestion is more than “smoke and hot air”. From providing thermal energy to adjacent or on-campus operations to generating electricity and/or transportation fuels, these facilities are proving that energy harvesting can not only be profitable, but sustainable. This paper explores ways in which wastewater treatment plants can increase their value and import to the communities they serve through the generation of clean, renewable energy; also presented the processes in which these facilities moved from energy and cost sinks to sparks of innovation and pride in the communities in which they operate.

Keywords: anaerobic digestion, harvesting energy, biogas, renewable energy, sustainability

Procedia PDF Downloads 320

Authors: R. M. Chandler, A. J. Stringer

Abstract:

In adults, short bursts of high-intensity exercise (intensities between 80-95% of maximum heart rates) increase cardiovascular and metabolic function without the time investment of traditional aerobic training. Similar improvements in various health indices are also becoming increasingly evident in children in countries other than the United States. In the United States, physical education programs have become shorter in length and fewer in frequency. With this in the background, it is imperative that health and physical educators delivered well-organized and focused fitness programs that can be tolerated across many different somatotypes. Perhaps the least effective lag-time in a US physical education (PE) class is the first 10 minutes, a time during which children warm up. Replacing a traditional PE warmup with a 10 min high-intensity excise protocol is a time-efficient method to impact health, leaving as much time for other PE material such as skill development, motor behavior development as possible. This supplemented 10 min high-intensity exercise increases cardiovascular function as well as induces favorable body composition changes in as little as six weeks with further enhancement throughout a semester of activity. The supplemental high-intensity exercise did not detract from the PE lesson outcomes.

Keywords: cardiovascular fitness, high intensity interval training, high intensity exercise, pediatric

Procedia PDF Downloads 138

Authors: Alyamama Alsaidi

Abstract:

This research has been conducted in order to analyse the impact of outsourcing on telecommunication industry in Oman. The research is conducted by collecting qualitative and quantitative data in order to widen the area of comprehension. The data has been collected from genuine sources which showcased that results were reliable and possess validity. The outsourcing is very important because it helps the organisation in saving the cost and efforts of the workers. In Oman, the telecommunication industry largely uses the outsourcing service which is provided by the third party. The third party is responsible for providing outsourcing to the telecommunication companies. This research gives an overall view of the outsourcing in the telecommunication companies of Oman. The IT companies of Oman give their work to the outsourcing services as this will help in reducing the cost the project. Rather employing the experts to do the projects, the organization can easily give their products to the outsourcing services in which they complete the work for a cheaper rate for the telecommunication company of Oman. It will help in reducing the work load on the staffs and management of the telecommunication companies in Oman. The IT outsourcing in Oman is very common because some of the staff are not well experienced to do the IT work. The outsourcing has positive as well as negative impact on the telecommunication industry in Oman. The research has been done while considering ethical aspect in an effective and efficient manner. Furthermore, the literature is adequately reviewed so that views of various specialists can be considered for future guidance.

Keywords: IT outsourcing, client company, services company, telecommunication

Procedia PDF Downloads 189

Authors: Xiaoyun Zhao, Rami Darwish, Anna Pernestål

Abstract:

Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.

Keywords: automated vehicle, connectivity and automation, intelligent transport system, traffic control, traffic safety

Procedia PDF Downloads 141