Search results for: parallel job shop scheduling problem

Authors: Ihsan Ullah Khan, Asim Kareem, Naveed Saif

Abstract:

This research study examined the application of innovative strategies for improving writing skills of Secondary level students. It also examined the steps taken by Secondary level teachers for the improvement of writing skills of their students. Effective written communication is the problem faced by all the ESL students at secondary level. The objective of the study was to help the secondary level students to overcome this problem. More specifically, this research study aimed to guide the teachers, teaching at secondary level, to bring innovation in their teaching by showing the results of innovative strategies. In order to know about the practices of the teachers, inside the classroom, data was calculated through rating scale questionnaire. After that experimental study was carried out. For the experimental study a 10th grade class was selected. Results were drawn by analyzing the pre and post-tests of the students with the help of independent sample t-test. The results showed that a significant change occurred in the writing skills of the students, belonging to Treatment group. No improvement was observed in the writing skills of the students, belonging to Control group. Thus this research study proved to be a great contribution by guiding the teachers to bring a significant change in the writing skills of the students.

Keywords: writing skills, innovative strategies, teachers, students, treatment group, control group

Procedia PDF Downloads 435

Authors: Kevin Brochard, Herve Le Sourne, Guillaume Barras

Abstract:

The design of a submarine’s hull is crucial for its operability and crew’s safety, but also complex. Indeed, engineers need to balance lightness, acoustic discretion and resistance to both immersion pressure and environmental attacks. Submarine explosions represent a first-rate threat for the integrity of the hull, whose behavior needs to be properly analyzed. The presented work is focused on the development of a simplified analytical method to study the structural response of a deeply immersed cylinder submitted to an underwater explosion. This method aims to provide engineers a quick estimation of the resulting damage, allowing them to simulate a large number of explosion scenarios. The present research relies on the so-called plastic string on plastic foundation model. A two-dimensional boundary value problem for a cylindrical shell is converted to an equivalent one-dimensional problem of a plastic string resting on a non-linear plastic foundation. For this purpose, equivalence parameters are defined and evaluated by making assumptions on the shape of the displacement and velocity field in the cross-sectional plane of the cylinder. Closed-form solutions for the deformation and velocity profile of the shell are obtained for explosive loading, and compare well with numerical and experimental results. However, the plastic-string model has not yet been adapted for a cylinder in immersion subjected to an explosive loading. In fact, the effects of fluid-structure interaction have to be taken into account. Moreover, when an underwater explosion occurs, several pressure waves are emitted by the gas bubble pulsations, called secondary waves. The corresponding loads, which may produce significant damages to the cylinder, must also be accounted for. The analytical developments carried out to solve the above problem of a shock wave impacting a cylinder, considering fluid-structure interaction will be presented for an unstiffened cylinder. The resulting deformations are compared to experimental and numerical results for different shock factors and different standoff distances.

Keywords: immersed cylinder, rigid plastic material, shock loading, underwater explosion

Procedia PDF Downloads 313

Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

Abstract:

There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

Procedia PDF Downloads 397

Authors: Astha Sinha, Anjali Kanagali

Abstract:

The United Kingdom’s withdrawal from the European Union, also termed as “Brexit,” took place on June 23, 2016 and immediately had global repercussions on the stock markets of the world. It is however expected to have a greater impact on the Banking sector in the UK. There is a two-fold effect on the earnings of banks which is being expected. First is of the trading activity and investment banking businesses being hit due to global weakness in financial markets. Second is that the banks having a large presence in the European Union will have to restructure their operations in order to cover other European countries as well increase their operating costs. As per the analysis, banks are expected to face rate cuts, bad loans, and tight liquidity. The directives in the Brexit negotiations on the Markets in Financial Instruments Directive (MiFID) will be a major decision to be taken for the Banking sector. New regulations will be required since most of the regulations governing the financial services industry allowing for the cross-border transactions were at the EU level. This paper aims to analyze the effect of Brexit on the UK Banking sector and changes in regulations that are expected due to the same. It shall also lay down the lessons learnt from the 2008 financial crisis and draw a parallel in terms of potential areas to be focused on for revival of the financial sector of Britain.

Keywords: Brexit, Brexit impact on UK, impact of Brexit on banking, impact of Brexit on financial services

Procedia PDF Downloads 395

Authors: Saeed Dehnavi, Marjan Pooee

Abstract:

Background - Psychodrama, as a form of art therapy, helps people to enact and use role-plays for a specific problem, rather than just talking about it, in an effort to review the problem, gain feedback from group members, find appropriate solutions, and practice them for their life. This paper evaluated the effectiveness of psychodrama on enhancing anxiety of young adolescent boys. Methodology - This is aquasi-experimental research study, using a pre-post testing plan with control group. From four secondary schools in Kermanshah - Iran, 210 adolescent boys (aged 13 and 14 years) were asked to complete Koper Smith's self-esteem measure scale. Given the low self-esteem scores (less than the cut-off of 23), a number of 20 individuals were selected and randomly placed into two control and experimental groups. The experimental group participated in a twelve-session psychodrama therapy plan for 6 weeks, while the control group received no intervention. Data analysis was carried out by the analysis of covariance (ANCOVA). Results - The results of ANCOVA analysis showed an increase in the post-test scores for anxiety, and such increase was statistically significant. Conclusion - The findings indicated the effectiveness of psychodrama on anxiety enhancement of young boys. During psychodrama sessions, the adolescents learned to take the initiative, communicate with others in an excited state, and improve their anxiety with positive and constructive experiences.

Keywords: anxiety, art therapy, psychodrama, young adolescents

Procedia PDF Downloads 532

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

Abstract:

Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

Procedia PDF Downloads 96

Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

Abstract:

This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

Procedia PDF Downloads 290

Authors: Víctor Martínez del Rey, Kourosh Nasr Esfahani, Amir Masoud Samani Majd

Abstract:

In this experimental study, the behaviors of Mixed Oxidant solution components (MOS) and sodium hypochlorite (HYPO) as the most commonly applied surface disinfectant were compared through the effectiveness of chlorine disinfection as a function of the contact time and residual chlorine. In this regard, the variation of pH, free available chlorine (FAC) concentration, and electric conductivity (EC) of disinfection solutions in different concentrations were monitored over 48 h contact time. In parallel, the plant stress activated by chlorine-based disinfectants was assessed by comparing MOS and HYPO. The elements of pH and EC in the plant-soil and their environmental impacts, spread by disinfection solutions were analyzed through several concentrations of FAC including 500 mg/L, 1000 mg/L, and 5000 mg/L in irrigated water. All the experiments were carried out at the service station of Sant Cugat, Spain. The outcomes indicated lower pH and higher durability of MOS than HYPO at the same concentration of FAC which resulted in promising stability of FAC within MOS. Furthermore, the pH and EC value of plant-soil irrigated by NaOCl solution were higher than that of MOS solution at the same FAC concentration. On-site generation of MOS as a safe chlorination option might be considered an imaginary future of smart cities.

Keywords: disinfection, free available chlorine, on-site generation, sodium hypochlorite

Procedia PDF Downloads 108

Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

Abstract:

The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

Procedia PDF Downloads 55

Authors: Deepak Loura

Abstract:

The most contemporary method of producing horticulture crops both qualitatively and quantitatively is protected cultivation, or greenhouse cultivation, which has gained widespread acceptance in recent decades. Protected farming, commonly referred to as controlled environment agriculture (CEA), is extremely productive, land- and water-wise, as well as environmentally friendly. The technology entails growing horticulture crops in a controlled environment where variables such as temperature, humidity, light, soil, water, fertilizer, etc. are adjusted to achieve optimal output and enable a consistent supply of them even during the off-season. Over the past ten years, protected cultivation of high-value crops and cut flowers has demonstrated remarkable potential. More and more agricultural and horticultural crop production systems are moving to protected environments as a result of the growing demand for high-quality products by global markets. By covering the crop, it is possible to control the macro- and microenvironments, enhancing plant performance and allowing for longer production times, earlier harvests, and higher yields of higher quality. These shielding features alter the environment of the plant while also offering protection from wind, rain, and insects. Protected farming opens up hitherto unexplored opportunities in agriculture as the liberalised economy and improved agricultural technologies advance. Typically, the revenues from fruit, vegetable, and flower crops are 4 to 8 times higher than those from other crops. If any of these high-value crops are cultivated in protected environments like greenhouses, net houses, tunnels, etc., this profit can be multiplied. Vegetable and cut flower post-harvest losses are extremely high (20–0%), however sheltered growing techniques and year-round cropping can greatly minimize post-harvest losses and enhance yield by 5–10 times. Seasonality and weather have a big impact on the production of vegetables and flowers. The variety of their products results in significant price and quality changes for vegetables. For the application of current technology in crop production, achieving a balance between year-round availability of vegetables and flowers with minimal environmental impact and remaining competitive is a significant problem. The future of agriculture will be protected since population growth is reducing the amount of land that may be held. Protected agriculture is a particularly profitable endeavor for tiny landholdings. Small greenhouses, net houses, nurseries, and low tunnel greenhouses can all be built by farmers to increase their income. Protected agriculture is also aided by the rise in biotic and abiotic stress factors. As a result of the greater productivity levels, these technologies are not only opening up opportunities for producers with larger landholdings, but also for those with smaller holdings. Protected cultivation can be thought of as a kind of precise, forward-thinking, parallel agriculture that covers almost all aspects of farming and is rather subject to additional inspection for technical applicability to circumstances, farmer economics, and market economics.

Keywords: protected cultivation, horticulture, greenhouse, vegetable, controlled environment agriculture

Procedia PDF Downloads 68

Authors: Jae-Ho Kim, Ryosuke Yokochi, Miho Fuzihashi, Susumu Yonezawa

Abstract:

The use of silver nanoparticles in conductive inks and their printing by injecting technology has been known for years. However, the very high cost of silver limits wide industrial applications. Since copper is much cheaper but possesses a very high conductivity (only 6% less than that of Ag), Cu nanoparticles can be considered as a replacement for silver nanoparticles. However, a major problem in utilizing their copper nanoparticles is their inherent tendency to oxidize in ambient conditions. In conductive printing applications, the presence of copper oxide on the surface of nanoparticles has two negative consequences: it increases the required sintering temperature and reduces the electrical conductivity. Only a limited number of reports have attempted to address the oxidation problem, which in general is based on minimizing the exposure of the copper nanoparticles to oxygen by a protective layer composed of a second material at the surface of the particles. To form the protective layer on the surface, carbon-based materials, surfactants, metals, and so on. In this study, we tried to modify the oxide on Cu particles using fluorine gas. And the creation effects of oxyfluorides or fluorides on the oxidation resistance of Cu particles were investigated. Compared with untreated sample (a), the fluorinated samples can restrain the weight increase even at 200℃ from the TG-DTA results. It might be considered that the substantial oxyfluorides on the surface play a role in protecting metal oxidation.

Keywords: copper metal, electrical conductivity, oxidation resistance, surface fluorination

Procedia PDF Downloads 101

Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

Abstract:

High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: hybrid meta-heuristic methods, substation construction, resource allocation, time-cost efficiency

Procedia PDF Downloads 143

Authors: Omer Cahana, Ofer Levi, Maya Herman

Abstract:

Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

Procedia PDF Downloads 80

Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

Abstract:

Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

Procedia PDF Downloads 222

Authors: Maxutova I. O., Bulatbayeva A. A.

Abstract:

In modern conditions, the competitiveness of the military, a special educational institution in the educational market, is determined by the quality of the provision of educational services and the economic efficiency of activities. Improving the quality of educational services of the military, the special educational institution is an urgent socially and economically significant problem. The article shows a possible system for the formation of the competitiveness of military, the special educational institution through an assessment of the quality of the educational process, the problem of the transition of the military, special educational institution to digital support of indicative monitoring of the quality of services provided is raised. Quality monitoring is presented in the form of a program or information system, the work of which is carried out in a military, the special educational institution through highlighted interrelated elements. A result-oriented model of management and assessment of the quality of work of the military, the special educational institution is proposed. The indicative indicators for assessing the quality of the teaching and methodological activity of the teacher are considered and described. The publication was prepared as part of an applied grant study for 2020-2022 commissioned by the Ministry of Education and Science of the Republic of Kazakhstan on the topic "Development of a comprehensive methodology for assessing the quality of education of graduates of military special educational institutions" IRN 00029/GF-20.

Keywords: quality assessment, indicative indicators, monitoring program, educational and methodological activities, professional activities, result

Procedia PDF Downloads 139

Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

Abstract:

Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

Procedia PDF Downloads 136

Authors: I. Alhassan, A. M. Saddiq, A. G. Gashua, K. K. Gwio-Kura

Abstract:

The main objective of any irrigation program is the development of an efficient water management system to sustain crop growth and development and avoid physiological water stress in the growing plants. Field experiment to evaluate the effects of some soil moisture conservation practices on yield and water use efficiency (WUE) of maize was carried out in three locations (i.e. Mubi and Yola in the northern Guinea Savannah and Ganye in the southern Guinea Savannah of Adamawa State, Nigeria) during the dry seasons of 2013 and 2014. The experiment consisted of three different irrigation levels (7, 10 and 12 day irrigation intervals), two levels of mulch (mulch and un-mulched) and two tillage practices (no tillage and minimum tillage) arranged in a randomized complete block design with split-split plot arrangement and replicated three times. The Blaney-Criddle method was used for measuring crop evapotranspiration. The results indicated that seven-day irrigation intervals and mulched treatment were found to have significant effect (P>0.05) on grain yield and water use efficiency in all the locations. The main effect of tillage was non-significant (P<0.05) on grain yield and WUE. The interaction effects of irrigation and mulch were significant (P>0.05) on grain yield and WUE at Mubi and Yola. Generally, higher grain yield and WUE were recorded on mulched and seven-day irrigation intervals, whereas lower values were recorded on un-mulched with 12-day irrigation intervals. Tillage exerts little influence on the yield and WUE. Results from Ganye were found to be generally higher than those recorded in Mubi and Yola; it also showed that an irrigation interval of 10 days with mulching could be adopted for the Ganye area, while seven days interval is more appropriate for Mubi and Yola.

Keywords: irrigation, maize, mulching, tillage, savanna

Procedia PDF Downloads 200

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 60

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

Procedia PDF Downloads 431

Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

Procedia PDF Downloads 144

Authors: Fines Fatimah, SH. MH.

Abstract:

Indonesia is one of the countries that has ratified the UNCRPD (United Nations Convention on the Rights of Persons with Disabilities). The ratification of this convention brings consequences on the adjustment of national legislation with the UNCRPD convention, where this ratification at the same time is a measure in the eyes of the international community that a state party could be consistent with the issues and problems of disability. Persons with disabilities often have little access to justice when they are forced to deal with the criminal justice system. Pursuit of justice through litigation are often not in their favor, therefore without any awareness of law enforcement/awareness of disability will further complicate access to justice for persons with disabilities. Under Article 13 of the UNCRPD, it appeared that the convention requires ratifying states to guarantee equal opportunity and treatment in justice for persons with disabilities. The States should also ensure that any judicial rules must be adapted to the circumstances of persons with disabilities so that people with disabilities can fully participate in all stages of the trial court and, for example, as a witness. Finally, the state must provide training to understand these persons with disabilities (for those who work in the judiciary institution such as police or prison officials). Further, this paper aims to describe problem faced by persons with intellectual disabilities to access justice in Indonesian Criminal Justice System. This paper tries to find and propose the alternative solutions to promote the quality of law enforcement in Indonesia, especially for persons with intellectual disabilities.

Keywords: access to justice, Indonesian criminal justice system, intellectual disability, ratifying states

Procedia PDF Downloads 505

Authors: Benalia Kouini, Aicha Serier

Abstract:

This work aims to investigate the structure–property relationship in ternary nanocomposites consisting of polypropylene as the matrix, polyamide 66 as the minor phase and treated nanoclay DELLITE 67G as the reinforcement. All PP/PA66/Nanoclay systems with polypropylene grafted maleic anhydride PP-g-MAH as a compatibilizer were prepared via melt compounding and characterized in terms of nanoclay content. Morphological structure was investigated by scanning electron microscopy. The rheological behavior of the nanocomposites was determined by various methods, viz melt flow index (MFI) and parallel plate rheological measurements. The PP/PP-g-MAH/PA66 nanocomposites showed a homogeneous morphology supporting the compatibility improvement between PP, PA66 and nanoclay. SEM results revealed the formation of nanocomposites as the nanoclay was intercalated and exfoliated. In the ternary nanocomposites, the rheological behavior showed that, the complex viscosity is increased with increasing the nanoclay content; however, at low frequencies this increase is governed by the content of nanofiller while at high frequencies it is mainly determined by talc content. A similar trend was also observed for the variations of storage modulus (G′) and loss modulus (G″) with frequency. The results showed that the use of nanoclay considerably affects the melt elasticity.

Keywords: nanocomposites, polypropylene, polyamide66, modified nanoclay, rheology

Procedia PDF Downloads 371

Authors: A. Rana, M. Badri, D. Lopez Behar, O. Yee, H. Al Bqaei

Abstract:

The building sector is one of the largest emitters of greenhouse gases. However, as operation energy demands of this sector decrease with more effective energy policies and strategies, there is an urgent need to parallel focus on the growing proportion of embodied carbons. In this regard, benchmarks on embodied carbon of buildings can provide a point of reference to compare and improve the environmental performance of buildings for the stakeholders. Therefore, embodied carbon benchmarks can serve as a useful tool to address climate change challenges. This research utilizes the method to provide a knowledge roadmap of embodied carbon benchmarks development and implementation trends. Two main databases, Web of Science and Engineering Village, are considered for the study. The mapping was conducted with the help of VosViewer tool to provide information regarding: the critical research areas; most cited authors and publications; and countries with the highest publications. It is revealed that the role of benchmarks in energy policies is an emerging trend. In addition, the research highlighted that in policies, embodied carbon benchmarks are gaining importance at the material, whole building, and building portfolio levels. This research reveals direction for improvement and future research and of relevance to building industry professionals, policymakers, and researchers.

Keywords: buildings embodied carbon benchmark, methods, policy

Procedia PDF Downloads 162

Authors: Didem Aslantaş

Abstract:

In this study, the reforms carried out by the Justice and Development Party, which came to power in 2002, and how the foreign policy understanding it transformed reflected on the relations with Syria will be analyzed from the social constructivist theory. Contrary to the increasing security concerns of the states after the September 11 attacks, the main problem of the research is how the relations between Syria and Turkey developed and how they progressed in non-security dimensions. In order to find an answer to this question, the basic assumptions of the constructivist theory will be used. Since there is a limited number of studies in the literature, a comparative analysis of the Adana Consensus and the Cooperation Agreement between the Republic of Turkey and the Syrian Arab Republic, and the Joint Cooperation Agreement Against Terrorism and Terrorist Organizations will be included. In order to answer the main problem of the research and to support the arguments, document and archive scanning methods from qualitative research methods will be used. In the first part of the study, what the social constructivist theory is and its basic assumptions are explained, while in the second part, Turkey-Syria relations between 2002-2011 are included. In the third and last part, the relations between the two countries will be tried to be read through social constructivism by referring to the foreign policy features of the Ak Party period.

Keywords: Social Constructivist Theory, foreign policy analysis, Justice and Development Party, Syria

Procedia PDF Downloads 74

Authors: Nivedhitha Venkatakrishnan

Abstract:

Walking down busy temple streets in India is an experience in lifetime. Especially the temple streets are one of the most energetic places not only because of the divinity but also because of the streets itself which provides place for people to relax, meet, shop, linger, just walk around these activities create a set of experience which results in memories that lasts longer. Thinking of any temple street in India the image that comes to anyone’s mind are the elegantly sculpted Gopurams (Gateway) that depicts the craftsmanship and the history of the place, people taking a holy dip in the water, the aroma of the agarbathi’s, flowers with the divine Vedic chants and the sound of the temple bell flock of pigeons flying from the niches of the Gopuram with the sun in the backdrop. It gives a feeling of impulse energy that brings in life to these streets. Any temple street with even any one factor missing would look dead. This will be amiss in the essence in the scene of one’s experiences. These Temple Streets traditionally cater not only for religious purpose but to a wide range of activities. A vibrant street that facilitates such activities are preferred by the public any day. The research seeks to understand and find out the definition of Vibrancy in Indian Context. What is Vibrancy? What brings in the feeling of Vibrancy/Liveliness/Energy? Is it the Built structure and the city? Or is it the people? Or is it the Activity? Or is it Built structure – city – People – Activity put together brings the sense of Vibrancy to a place? How to define Vibrancy? Is it measurable? For which a case of Car Street Udupi, Karnataka is taken. The research is carried out in two stages. ‘Stage One’ makes use of ethnographic fieldwork as a basic method, complimented by structured field observations using a behavioral mapping procedure of the streets. Stage Two’ utilizes surveys that collected. This stage seeks to understand what design characteristics and furniture arrangements are associated with stationary, social and gathering activities of people by each cultural group and all groups collectively. The main conclusion from this research is that retail activities remain the main concern of people in cultural streets. Management and higher-level planning of retail activities on the streets could encourage and motivate possible Shops to enrich the trade variety of the street that provides a means for social and cultural diversity. In addition to business activities, spatial design characteristics are found to have an influence on people’s behavior and activity. The findings of this research suggest that retail and business activities, together with the design and skillful management of the public areas, could support a wider range of static and social activities among people of various ethnic backgrounds.

Keywords: activity, liveliness, temple street, vibrancy

Procedia PDF Downloads 148

Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

Procedia PDF Downloads 105

Authors: Youngsun Moon, Yeong-Ju Go, Jong-Soo Choi

Abstract:

Most drones that currently have surveillance/reconnaissance missions are basically equipped with optical equipment, but we also need to use a microphone array to estimate the location of the acoustic source. This can provide additional information in the absence of optical equipment. The purpose of this study is to estimate Direction of Arrival (DOA) based on Time Difference of Arrival (TDOA) estimation of the acoustic source in the drone. The problem is that it is impossible to measure the clear target acoustic source because of the drone noise. To overcome this problem is to separate the drone noise and the target acoustic source using Blind Source Separation(BSS) based on Independent Component Analysis(ICA). ICA can be performed assuming that the drone noise and target acoustic source are independent and each signal has non-gaussianity. For maximized non-gaussianity each signal, we use Negentropy and Kurtosis based on probability theory. As a result, we can improve TDOA estimation and DOA estimation of the target source in the noisy environment. We simulated the performance of the DOA algorithm applying BSS algorithm, and demonstrated the simulation through experiment at the anechoic wind tunnel.

Keywords: aeroacoustics, acoustic source detection, time difference of arrival, direction of arrival, blind source separation, independent component analysis, drone

Procedia PDF Downloads 150

Authors: Mohammad Reza Zamani Kouhpanji

Abstract:

This paper presents a MEMS/NEMS device for fatigue and fracture characterization of nanomaterials. This device can apply static loads, cyclic loads, and their combinations in nanomechanical experiments. It is based on the electromagnetic force induced between paired parallel wires carrying electrical currents. Using this concept, the actuator and sensor parts of the device were designed and analyzed while considering the practical limitations. Since the PWCC device only uses two wires for actuation part and sensing part, its fabrication process is extremely easier than the available MEMS/NEMS devices. The total gain and phase shift of the MEMS/NEMS device were calculated and investigated. Furthermore, the maximum gain and sensitivity of the MEMS/NEMS device were studied to demonstrate the capability and usability of the device for wide range of nanomaterials samples. This device can be readily integrated into SEM/TEM instruments to provide real time study of the mechanical behaviors of nanomaterials as well as their fatigue and fracture properties, softening or hardening behaviors, and initiation and propagation of nanocracks.

Keywords: sensors and actuators, MEMS/NEMS devices, fatigue and fracture nanomechanical testing device, static and cyclic nanomechanical testing device

Procedia PDF Downloads 285

Authors: Marin Senila, Oana Cadar, Thorsten Janisch, Patrick Lacroix-Desmazes

Abstract:

The study presents the analytical capability and validation of a method based on microwave-assisted acid digestion for quantitative determination of platinum and palladium in catalysts using inductively coupled plasma optical emission spectrometry (ICP-OES). In order to validate the method, the main figures of merit such as limit of detection and limit of quantification, precision and accuracy were considered and the measurement uncertainty was estimated based on the bottom-up approach according to the international guidelines of ISO/IEC 17025. Limit of detections, estimated from blank signal using 3 s criterion, were 3.0 mg/kg for Pt and respectively 3.6 mg/kg for Pd, while limits of quantification were 9.0 mg/kg for Pt and respectively 10.8 mg/kg for Pd. Precisions, evaluated as standard deviations of repeatability (n=5 parallel samples), were less than 10% for both precious metals. Accuracies of the method, verified by recovery estimation certified reference material NIST SRM 2557 - pulverized recycled monolith, were 99.4 % for Pt and 101% for Pd. The obtained limit of quantifications and accuracy were satisfactory for the intended purpose. The paper offers all the steps necessary to validate the determination method for Pt and Pd in catalysts using inductively coupled plasma optical emission spectrometry.

Keywords: catalyst analysis, ICP-OES, method validation, platinum, palladium

Procedia PDF Downloads 160

Authors: Ihn Sook Jeong, Eun Joo Lee, Jae Hyung Kim, Gun Ho Kim, Young Jun Hwang

Abstract:

This study investigated intravenous (IV) infiltration using bioelectrical impedance for 27 hospitalized patients in a long-term care hospital. Impedance parameters showed significant differences before and after infiltration as follows. First, the resistance (R) after infiltration significantly decreased compared to the initial resistance. This indicates that the IV solution flowing from the vein due to infiltration accumulates in the extracellular fluid (ECF). Second, the relative resistance at 50 kHz was 0.94 ± 0.07 in 9 subjects without infiltration and was 0.75 ± 0.12 in 18 subjects with infiltration. Third, the magnitude of the reactance (Xc) decreased after infiltration. This is because IV solution and blood components released from the vein tend to aggregate in the cell membrane (and acts analogously to the linear/parallel circuit), thereby increasing the capacitance (Cm) of the cell membrane and reducing the magnitude of reactance. Finally, the data points plotted in the R-Xc graph were distributed on the upper right before infiltration but on the lower left after infiltration. This indicates that the infiltration caused accumulation of fluid or blood components in the epidermal and subcutaneous tissues, resulting in reduced resistance and reactance, thereby lowering integrity of the cell membrane. Our findings suggest that bioelectrical impedance is an effective method for detection of infiltration in a noninvasive and quantitative manner.

Keywords: intravenous infiltration, impedance, parameters, resistance, reactance

Procedia PDF Downloads 169