Search results for: dates nodes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 866

Search results for: dates nodes

266 Reconstruction Paleogeomorphological Map of the Nile River in Upper Egypt by Using Some Geomorphological and Geoarchaeological Indicators

Authors: Magdy Torab

Abstract:

Ancient Egyptians built their temples purposefully close to the River Nile to use it for transporting construction stones from far away quarries to building sites in river-boats. Most temples, therefore, have river-harbors associated with their geometric designs. The paleoriver channel remapped by using this idea, besides other geomorphological and geoarchaeological indicators/evidence located between Aswan and Luxor cities. In this sense, this paper defines the characteristics of this ancient course and its associated landforms using paleochannel morphology, paleomeandering, and ancient river dynamics during historic and prehistoric times. Both geomorphological and geoarchaeological approaches used to reconstruct the paleomorphology of the river course. It helps to investigate the ancient river morphology by using the following techniques: comparison and interpretation of multi dates satellite images and historical maps between 1943 and 2004. The results illustrated on maps using GIS (ARC GIS V.10 software) and the field data collected from the western bank of The Nile River at Luxor area and Karnak, Edfu, Esna and Kom Ombo temples. Created both current and paleogeomorphological maps depending upon the results of geoarchaeological surveying and soil analysis and dating, for surface and subsurface soil sampling by handle auger, laser diffraction analysis for 7 soil samples collected from some mounds and Malkata channel in the western bank of The Nile River near Luxor. Paleo-current directions were determined by using standard Brunton compass to use it as an indicator is evidence for the direction of flow of The Nile River during deposition of some accumulated mounds on the western part of the floodplain near Luxor city. C-14 dating was used for two samples collected from these mounds as well as geographical information system (GIS) technique for mapping. The geomorphological and geoarchaeological evidence shows that the Nile River course in Luxor area was around 4.5 km wide and contained many islands and sandbars which separated inside the river channel, now appearing as scattered mounds inside the floodplain. Upper Egypt has migrated during the historic times to the east up to five kilometers and become far away from the ancient temples, quarries, and harbors. It has also become as well as become more meandering and narrower than before.

Keywords: Nile River, ancient harbours, Luxor, paleogeomorphology, geoarchaeology

Procedia PDF Downloads 147
265 Method for Improving ICESAT-2 ATL13 Altimetry Data Utility on Rivers

Authors: Yun Chen, Qihang Liu, Catherine Ticehurst, Chandrama Sarker, Fazlul Karim, Dave Penton, Ashmita Sengupta

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The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect with water. The ICESAT-2 track generates multiple VSs as it crosses the different water bodies. The difficulties are particularly pronounced in large river basins where there are many tributaries and meanders often adjacent to each other. One challenge is to split photon segments along a beam to accurately partition them to extract only the true representative water height for individual elements. As far as we can establish, there is no automated procedure to make this distinction. Earlier studies have relied on human intervention or river masks. Both approaches are unsatisfactory solutions where the number of intersections is large, and river width/extent changes over time. We describe here an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparison with river water level observations at 10 different stations on 37 different dates along the Lower Murray River, Australia. The congruence is very high and without detectable bias. In addition, we compared different outlier removal methods on the mean WSE calculation at VSs post the auto-segmentation process. All four outlier removal methods perform almost equally well with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189m) and MAE (0.130–0.142m). Overall, the auto-segmentation method developed here is an effective and efficient approach to deriving accurate mean WSE at river VSs. It provides a much better way of facilitating the application of ICESAT-2 ATL13 altimetry to rivers compared to previously reported studies. Therefore, the findings of our study will make a significant contribution towards the retrieval of hydraulic parameters, such as water surface slope along the river, water depth at cross sections, and river channel bathymetry for calculating flow velocity and discharge from remotely sensed imagery at large spatial scales.

Keywords: lidar sensor, virtual station, cross section, mean water surface elevation, beam/track segmentation

Procedia PDF Downloads 56
264 A Comparative Study between FEM and Meshless Methods

Authors: Jay N. Vyas, Sachin Daxini

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Numerical simulation techniques are widely used now in product development and testing instead of expensive, time-consuming and sometimes dangerous laboratory experiments. Numerous numerical methods are available for performing simulation of physical problems of different engineering fields. Grid based methods, like Finite Element Method, are extensively used in performing various kinds of static, dynamic, structural and non-structural analysis during product development phase. Drawbacks of grid based methods in terms of discontinuous secondary field variable, dealing fracture mechanics and large deformation problems led to development of a relatively a new class of numerical simulation techniques in last few years, which are popular as Meshless methods or Meshfree Methods. Meshless Methods are expected to be more adaptive and flexible than Finite Element Method because domain descretization in Meshless Method requires only nodes. Present paper introduces Meshless Methods and differentiates it with Finite Element Method in terms of following aspects: Shape functions used, role of weight function, techniques to impose essential boundary conditions, integration techniques for discrete system equations, convergence rate, accuracy of solution and computational effort. Capabilities, benefits and limitations of Meshless Methods are discussed and concluded at the end of paper.

Keywords: numerical simulation, Grid-based methods, Finite Element Method, Meshless Methods

Procedia PDF Downloads 384
263 Enhancement of Environmental Security by the Application of Wireless Sensor Network in Nigeria

Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

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Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: application, environment, insecurity, sensor, wireless sensor network

Procedia PDF Downloads 255
262 Blockchain for Transport: Performance Simulations of Blockchain Network for Emission Monitoring Scenario

Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

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With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

Procedia PDF Downloads 169
261 Clinicopathological Findings of Partuberclosis in Camels: Possible Steps for Control Strategy

Authors: A. M. Almujalli, G. M. Al-Ghamdi

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Mycobacterium avium subspecies paratuberculosis causes paratuberculosis, a chronic debilitating granulomatous enteritis, in camels as well as domestic and wild ruminants. The clinical manifestation of the disease in camel is not well characterized, therefore this study was aimed to investigate the clinical and pathological pictures of camels that are suffering from partuberculosis. Twelve young camels that were presented to the Veterinary Teaching Hospital, King Faisal University were investigated. Clinical and pathological examination were performed. The results revealed highly significant increase in creatinine, blood urea nitrogen, magnesium, AST and ALT in diseased camels, while glucose, total protein and albumin were highly significantly decreased in diseased camels when compared to healthy ones. Post-mortem testing indicated thickening, corrugation of the intestinal wall, folded mucosa, enlarged and oedemated ileocaecal and mesenteric lymph nodes. The microscopic findings detected short, blunt and distorted intestinal villi with hyperactive goblet cells of the villi and the crypts of lieberkuhn contained mucin droplets. The lamina propria was heavily infiltrated with mononuclear cells mostly macrophages. This clinical picture of paratuberculosis may be used to initiate control strategy to limit the spread of the disease in camel herds.

Keywords: camel, partuberclosis, control, Saudi Arabia

Procedia PDF Downloads 190
260 MhAGCN: Multi-Head Attention Graph Convolutional Network for Web Services Classification

Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

Procedia PDF Downloads 132
259 Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment

Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

Procedia PDF Downloads 204
258 Advancing Phenological Understanding of Plants/Trees Through Phenocam Digital Time-lapse Images

Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

Procedia PDF Downloads 51
257 Investigating Message Timing Side Channel Attacks on Networks on Chip with Ring Topology

Authors: Mark Davey

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Communications on a Network on Chip (NoC) produce timing information, i.e., network injection delays, packet traversal times, throughput metrics, and other attributes relating to the traffic being sent across the chip. The security requirements of a platform encompass each node to operate with confidentiality, integrity, and availability (ISO 27001). Inherently, a shared NoC interconnect is exposed to analysis of timing patterns created by contention for the network components, i.e., links and switches/routers. This phenomenon is defined as information leakage, which represents a ‘side channel’ of sensitive information that can be correlated to platform activity. The key algorithm presented in this paper evaluates how an adversary can control two platform neighbouring nodes of a target node to obtain sensitive information about communication with the target node. The actual information obtained is the period value of a periodic task communication. This enacts a breach of the expected confidentiality of a node operating in a multiprocessor platform. An experimental investigation of the side channel is undertaken to judge the level and significance of inferred information produced by access times to the NoC. Results are presented with a series of expanding task set scenarios to evaluate the efficacy of the side channel detection algorithm as the network load increases.

Keywords: embedded systems, multiprocessor, network on chip, side channel

Procedia PDF Downloads 65
256 An Enhanced Hybrid Backoff Technique for Minimizing the Occurrence of Collision in Mobile Ad Hoc Networks

Authors: N. Sabiyath Fatima, R. K. Shanmugasundaram

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In Mobile Ad-hoc Networks (MANETS), every node performs both as transmitter and receiver. The existing backoff models do not exactly forecast the performance of the wireless network. Also, the existing models experience elevated packet collisions. Every time a collision happens, the station’s contention window (CW) is doubled till it arrives at the utmost value. The main objective of this paper is to diminish collision by means of contention window Multiplicative Increase Decrease Backoff (CWMIDB) scheme. The intention of rising CW is to shrink the collision possibility by distributing the traffic into an outsized point in time. Within wireless Ad hoc networks, the CWMIDB algorithm dynamically controls the contention window of the nodes experiencing collisions. During packet communication, the backoff counter is evenly selected from the given choice of [0, CW-1]. At this point, CW is recognized as contention window and its significance lies on the amount of unsuccessful transmission that had happened for the packet. On the initial transmission endeavour, CW is put to least amount value (C min), if transmission effort fails, subsequently the value gets doubled, and once more the value is set to least amount on victorious broadcast. CWMIDB is simulated inside NS2 environment and its performance is compared with Binary Exponential Backoff Algorithm. The simulation results show improvement in transmission probability compared to that of the existing backoff algorithm.

Keywords: backoff, contention window, CWMIDB, MANET

Procedia PDF Downloads 274
255 Blockchain-Based Approach on Security Enhancement of Distributed System in Healthcare Sector

Authors: Loong Qing Zhe, Foo Jing Heng

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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

Procedia PDF Downloads 183
254 Revitalization Strategy of Beijing-Tianjin-Hebei Rural Areas Organized by Production-Living-Ecology Spatial Network at Township Level

Authors: Liuhui Zhu, Peng Zeng

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The rural revitalization strategy means to take the country and the city on the same level, and achieve urban-rural integration and comprehensive development of rural areas. Beijing-Tianjin-Hebei rural areas have always been the weak links in the region, with prominently uneven development between urban and rural areas. The rural areas need to join the overall regional synergy. Based on the analysis of the characteristics and problems of rural development in the region from the perspective of production-living-ecology space, the paper proposes the township as the basic unit for rural revitalization according to the overall requirements of the rural revitalization strategy. The basic unit helps to realize resource arrangement, functional organization, and collaborative governance organized by the production-living-ecology spatial network. The paper summarizes the planning strategies for the basic unit. Through spatial cognition and spatial reconstruction, the three space is networked through the base, nodes, and connections to improve the comprehensive value of rural areas and achieve the multiple goals of rural revitalization.

Keywords: rural revitalization, Beijing-Tianjin-Hebei region, township level, production-living-ecology spatial network

Procedia PDF Downloads 189
253 Last ca 2500 Yr History of the Harmful Algal Blooms in South China Reconstructed on Organic-Walled Dinoflagellate Cysts

Authors: Anastasia Poliakova

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Harmful algal bloom (HAB) is a known negative phenomenon that is caused both by natural factors and anthropogenic influence. HABs can result in a series of deleterious effects, such as beach fouling, paralytic shellfish poisoning, mass mortality of marine species, and a threat to human health, especially if toxins pollute drinking water or occur nearby public resorts. In South China, the problem of HABs has an ultimately important meaning. For this study, we used a 1.5 m sediment core LAX-2018-2 collected in 2018 from the Zhanjiang Mangrove National Nature Reserve (109°03´E, 20°30´N), Guangdong Province, South China. High-resolution coastal environment reconstruction with a specific focus on the HABs history during the last ca 2500 yrs was attempted. Age control was performed with five radiocarbon dates obtained from benthic foraminifera. A total number of 71 dinoflagellate cyst types was recorded. The most common types found consistently throughout the sediment sequence were autotrophic Spiniferites spp., Spiniferites hyperacanthus and S. mirabilis, S. ramosus, Operculodinium centrocarpum sensu Wall and Dale 1966, Polysphaeridium zoharyi, and heterotrophic Brigantedinium ssp., cyst of Gymnodinium catenatum and cysts mixture of Protoperidinium. Three local dinoflagellate zones LAX-1 to LAX-3 were established based on the results of the constrained cluster analysis and data ordination; additionally, the middle zone LAX-2 was derived into two subzones, LAX-2a and LAX-2b based on the dynamics of toxic and heterotrophic cysts as well as on the significant changes (probability, P=0.89) in percentages of eutrophic indicators. The total cyst count varied from 106 to 410 dinocysts per slide, with 177 cyst types on average. Dinocyst assemblages are characterized by high values of the dost-depositional degradation index (kt) that varies between 3.6 and 7.6 (averaging 5.4), which is relatively high and is very typical for the areas with selective dinoflagellate cyst preservation that is related to bottom-water oxygen concentrations.

Keywords: reconstruction of palaeoenvironment, harmful algal blooms, anthropogenic influence on coastal zones, South China Sea

Procedia PDF Downloads 82
252 Turbulent Channel Flow Synthesis using Generative Adversarial Networks

Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

Procedia PDF Downloads 201
251 Study of the Facilities in the Cultural and Ecotourism Route in the Area of Om Nont Canal, Nonthaburi Provice, Thailand

Authors: Supattra Suanlim

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Nonthaburi province is one of the provinces in the central region of Thailand. There is the Chao Phraya River, which is a large and important river of Thailand passing through the province. With the way of life and social changes since the past. There is a digging canal called Lat canal or Om canal, communities along the canal have dense settlements. Important in life and culture. This research has 3 objectives as follows. 1.To explore cultural and ecotourism attractions in the Om Nont canal area. 2.To explore the facilities in the Om Nont canal tourist attraction. To suggest facilities for tourist attractions in the Om Nont canal, Nonthaburi, Thailand. This research is a qualitative research, using research methods by collecting data and surveying tourist attractions by water traffic. The results of the research can be concluded that There are 21 tourist attractions that have the potential to welcome tourists who want to travel cultural. 16 temples or places of worship, 2 government offices, 1 market, 2 landmarks. Each should be improved to increase the potential of the paths. There should be improvements in the road landscape that is a connection to water traffic. Districts should have signage and signage installation within tourist sites and have guidelines for architectural improvements. And the Nodes should improve the public space of the community. Such as the Nonthaburi pier area to have the idea of designing a tourist center Provide information in both Thai and English.

Keywords: Community, Cultural, Ecotourism, Facility

Procedia PDF Downloads 127
250 The Effect of the Variety and Harvesting Date on Polyphenol Composition of Haskap (Lonicera caerulea L.) and Anti-diabetic Properties of Haskap Polyphenols

Authors: Aruma Baduge Kithma De Silva

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Haskap (Lonicera caerulea L.), also known as blue honeysuckle, is a newly commercialized berry crop in Canada. Haskap berries are rich in polyphenols, including, anthocyanins, which are known for potential health-promoting properties. Cyanidin-3-O-glucoside (C3G) is the most abundant anthocyanin of haskap berries. The compound C3G has the ability to reduce the risk of type 2 diabetes (T2D), which has become an increasingly common health issue around the world. The T2D is characterized as a metabolic disorder of hyperglycemia and insulin resistance. It has been demonstrated that C3G has anti-diabetic effects through several ways, including inhibition of dipeptidyl peptidase-4 (DPP-4), reduction of gluconeogenesis, improvement in insulin sensitivity, and inhibition of activities of carbohydrate hydrolyzing enzymes, including α-amylase and α-glucosidase. The goal of this study was to investigate the influence of variety and harvests maturity of haskap on C3G, other fruit quality characteristics and anti-diabetic activities of haskap berries using in vitro studies. The polyphenols present in four commercially grown haskap cultivars, Aurora, Rebecca, Larissa, and Evie harvested at five harvesting dates (H1-H5) apart from 2-3 days, were extracted separately. High-performance liquid chromatography electrospray ionization mass spectrometry (HPLC-ESI-MS) analyzes of polyphenols revealed that haskap berries contain predominantly anthocyanins, flavonols, flavan-3-ols, and phenolic acids. The compound C3G was the most prominent anthocyanin, which is available in approximately 79% of total anthocyanin in four cultivars. The Larissa at H5 contained the highest C3G content. The antioxidant capacity of Evie at H5 was greater than other cultivars. Furthermore, Larissa H5 showed the greatest inhibition of carbohydrate hydrolyzing enzymes including alpha-glucosidase and alpha-amylase. In conclusion, the haskap variety and harvesting date influenced the polyphenol composition and biological properties. The variety Larissa, at H5 harvesting date, contained the highest polyphenol content and the ability of inhibition of the carbohydrate hydrolyzing enzyme as well as DPP4 enzyme in order to reduce type 2 diabetes.

Keywords: anthocyanin, Haskap, type 2 diabetes, polyphenol

Procedia PDF Downloads 138
249 Flood Hazards, Vulnerability and Adaptations in Upper Imo River Basin of South Eastern Nigera Introduction

Authors: Christian N. Chibo

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Imo River Basin is located in South Eastern Nigeria comprising of 11 states of Imo, Abia, Anambra, Ebonyi, Enugu, Edo, Rivers, Cross river, AkwaIbom, Bayelsa, Delta, and Bayelsa states. The basin has a fluvial erosional system dominated by powerful rivers coming down from steep slopes in the area. This research investigated various hazards associated with flood, the vulnerable areas, elements at risk of flood and various adaptation strategies adopted by local inhabitants to cope with the hazards. The research aim is to identify, examine and assess flood hazards, vulnerability and adaptations in the Upper Imo River Basin. The study identified the role of elevation in cause of flood, elements at risk of flood as well as examine the effectiveness or otherwise of the adaptation strategies for coping with the hazards. Data for this research is grouped as primary and secondary. Their various methods of generation are field measurement, questionnaire, library websites etc. Other types of data were generated from topographical, geological, and Digital Elevation model (DEM) maps, while the hydro meteorological data was sourced from Nigeria Meteorological Agency (NIMET), Meteorological stations of Geography and Environmental Management Departments of Imo State University and Alvan Ikoku Federal College of Education. 800 copies of questionnaire were distributed using systematic sampling to 8 locations used for the pilot survey. About 96% of the questionnaire were retrieved and used for the study. 13 flood events were identified in the study area. Their causes, years and dates of events were documented in the text, and the damages they caused were evaluated. The study established that for each flood event, there is over 200mm of rain observed on the day of the flood and the day before the flood. The study also observed that the areas that situate at higher elevation (See DEM) are less prone to flood hazards while areas at low elevations are more prone to flood hazards. Elements identified to be at risk of flood are agricultural land, residential dwellings, retail trading and related services, public buildings and community services. The study thereby recommends non settlement at flood plains and flood prone areas and rearrangement of land use activities in the upper Imo River Basin among others

Keywords: flood hazard, flood plain, geomorphology, Imo River Basin

Procedia PDF Downloads 293
248 Graph Cuts Segmentation Approach Using a Patch-Based Similarity Measure Applied for Interactive CT Lung Image Segmentation

Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

Procedia PDF Downloads 164
247 An Approach of Node Model TCnNet: Trellis Coded Nanonetworks on Graphene Composite Substrate

Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

Procedia PDF Downloads 99
246 Marital Expectations, Marital Infidelity and Neuroticism as Predictors of Marital Conflict: Case Study of Igbo Spouses in Imo State, Nigeria

Authors: Ann Ukachi Madukwe, Juliana Chinwendu Njoku

Abstract:

Marital conflict, conceptualized in this study as the ongoing lack of peace and satisfaction in a marital union which threatens marital stability, has become quite prevalent in modern Igbo communities. The frequent incidences of spousal battery, spousal sexual abuse, domestic violence, long term separation and in some cases outright divorce are worrisome indicators of the endemic challenge marital conflict poses in most Igbo communities. This study examined marital expectations, marital infidelity (self and spouse), and neuroticism as predictors of marital conflict. Marital expectation was described as a married person’s appraisal of how well their pre-marital desires were being met by their spouses and within the marriage relationship. It assessed different aspects of personal and interpersonal positive outcomes in a marital union. Marital infidelity referred to the likelihood that married individuals or their spouses could have indulged in intimate activities like passionate kisses and romantic dates with someone other than their spouses. Participants reported on themselves as well as their spouses. The last predictor variable neuroticism was measured as a personality trait that addresses issues of emotional instability especially as it relates to a person’s interactions. Neurotic persons were considered to have high emotional reactivity; they would have strong emotional response to issues that emotionally stable persons might overlook. Participants comprised of Igbo male and female spouses selected from Imo state using randomized cluster sampling method. The study utilized the cross sectional survey design and Stepwise linear multiple regression for data analyses. Findings showed that though marital infidelity by spouse was generally below average and spouses marital expectations were being fulfilled; marital expectations followed by marital infidelity – spouse proved to be significant predictors of marital conflict. Marital conflict reduced as marital expectations got fulfilled and increased as the level of likelihood of marital infidelity by the spouse increased. Spouses in this study also reported an increased level of neuroticism, with males being more neurotic than females. Neuroticism was found to be the least significant predictor of marital conflict compared to marital expectations and marital infidelity – spouse. Finally, the article made recommendations to spouses and marital counsellors regarding especially the need to manage the neurotic tendencies of Igbo spouses.

Keywords: Igbo spouses, marital conflict, marital expectations, Nigeria

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245 Wireless Sensor Network for Forest Fire Detection and Localization

Authors: Tarek Dandashi

Abstract:

WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

Procedia PDF Downloads 258
244 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

Abstract:

The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

Procedia PDF Downloads 172
243 Multi-Scale Control Model for Network Group Behavior

Authors: Fuyuan Ma, Ying Wang, Xin Wang

Abstract:

Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.

Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior

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242 Graph Neural Networks and Rotary Position Embedding for Voice Activity Detection

Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

Procedia PDF Downloads 61
241 Bitcoin, Blockchain and Smart Contract: Attacks and Mitigations

Authors: Mohamed Rasslan, Doaa Abdelrahman, Mahmoud M. Nasreldin, Ghada Farouk, Heba K. Aslan

Abstract:

Blockchain is a distributed database that endorses transparency while bitcoin is a decentralized cryptocurrency (electronic cash) that endorses anonymity and is powered by blockchain technology. Smart contracts are programs that are stored on a blockchain. Smart contracts are executed when predetermined conditions are fulfilled. Smart contracts automate the agreement execution in order to make sure that all participants immediate-synchronism of the outcome-certainty, without any intermediary's involvement or time loss. Currently, the Bitcoin market worth billions of dollars. Bitcoin could be transferred from one purchaser to another without the need for an intermediary bank. Network nodes through cryptography verify bitcoin transactions, which are registered in a public-book called “blockchain”. Bitcoin could be replaced by other coins, merchandise, and services. Rapid growing of the bitcoin market-value, encourages its counterparts to make use of its weaknesses and exploit vulnerabilities for profit. Moreover, it motivates scientists to define known vulnerabilities, offer countermeasures, and predict future threats. In his paper, we study blockchain technology and bitcoin from the attacker’s point of view. Furthermore, mitigations for the attacks are suggested, and contemporary security solutions are discussed. Finally, research methods that achieve strict security and privacy protocol are elaborated.

Keywords: Cryptocurrencies, Blockchain, Bitcoin, Smart Contracts, Peer-to-Peer Network, Security Issues, Privacy Techniques

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240 Merging Appeal to Ignorance, Composition, and Division Argument Schemes with Bayesian Networks

Authors: Kong Ngai Pei

Abstract:

The argument scheme approach to argumentation has two components. One is to identify the recurrent patterns of inferences used in everyday discourse. The second is to devise critical questions to evaluate the inferences in these patterns. Although this approach is intuitive and contains many insightful ideas, it has been noted to be not free of problems. One is that due to its disavowing the probability calculus, it cannot give the exact strength of an inference. In order to tackle this problem, thereby paving the way to a more complete normative account of argument strength, it has been proposed, the most promising way is to combine the scheme-based approach with Bayesian networks (BNs). This paper pursues this line of thought, attempting to combine three common schemes, Appeal to Ignorance, Composition, and Division, with BNs. In the first part, it is argued that most (if not all) formulations of the critical questions corresponding to these schemes in the current argumentation literature are incomplete and not very informative. To remedy these flaws, more thorough and precise formulations of these questions are provided. In the second part, how to use graphical idioms (e.g. measurement and synthesis idioms) to translate the schemes as well as their corresponding critical questions to graphical structure of BNs, and how to define probability tables of the nodes using functions of various sorts are shown. In the final part, it is argued that many misuses of these schemes, traditionally called fallacies with the same names as the schemes, can indeed be adequately accounted for by the BN models proposed in this paper.

Keywords: appeal to ignorance, argument schemes, Bayesian networks, composition, division

Procedia PDF Downloads 281
239 A Patient Passport Application for Adults with Cystic Fibrosis

Authors: Tamara Vagg, Cathy Shortt, Claire Hickey, Joseph A. Eustace, Barry J. Plant, Sabin Tabirca

Abstract:

Introduction: Paper-based patient passports have been used advantageously for older patients, patients with diabetes, and patients with learning difficulties. However, these passports can experience issues with data security, patients forgetting to bring the passport, patients being over encumbered, and uncertainty with who is responsible for entering and managing data in this passport. These issues could be resolved by transferring the paper-based system to a convenient platform such as a smartphone application (app). Background: Life expectancy for some Cystic Fibrosis (CF) patients are rising and as such new complications and procedures are predicted. Subsequently, there is a need for education and management interventions that can benefit CF adults. This research proposes a CF patient passport to record basic medical information through a smartphone app which will allow CF adults access to their basic medical information. Aim: To provide CF patients with their basic medical information via mobile multimedia so that they can receive care when traveling abroad or between CF centres. Moreover, by recording their basic medical information, CF patients may become more aware of their own condition and more active in their health care. Methods: This app is designed by a CF multidisciplinary team to be a lightweight reflection of a hospital patient file. The passport app is created using PhoneGap so that it can be deployed for both Android and iOS devices. Data entered into the app is encrypted and stored locally only. The app is password protected and includes the ability to set reminders and a graph to visualise weight and lung function over time. The app is introduced to seven participants as part of a stress test. The participants are asked to test the performance and usability of the app and report any issues identified. Results: Feedback and suggestions received via this testing include the ability to reorder the list of clinical appointments via date, an open format of recording dates (in the event specifics are unknown), and a drop down menu for data which is difficult to enter (such as bugs found in mucus). The app is found to be usable and accessible and is now being prepared for a pilot study with adult CF patients. Conclusions: It is anticipated that such an app will be beneficial to CF adult patients when travelling abroad and between CF centres.

Keywords: Cystic Fibrosis, digital patient passport, mHealth, self management

Procedia PDF Downloads 245
238 Landsat Data from Pre Crop Season to Estimate the Area to Be Planted with Summer Crops

Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

Abstract:

The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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237 Economic of Chickpea Cultivars as Influenced by Sowing Time and Seed Rate

Authors: Indu Bala Sethi, Meena Sewhag, Rakesh Kumar, Parveen Kumar

Abstract:

Field experiment was conducted at Pulse Research Area of CCS Haryana Agricultural University, Hisar during rabi 2012-13 to study the economics of chickpea cultivars as influenced by sowing time and seed rate on sandy loam soils under irrigated conditions. The factorial experiment consisting of 24 treatment combinations with two sowing time (1st fortnight of November and 1st fortnight of December.) and four cultivars (H09-23, H08-18, C-235 and HC-1) kept in main plots while three seed rates viz. 40 kg ha-1, 50 kg ha-1 and 60 kg ha-1 was laid out in split plot design with three replications. The crop was sown with common row spacing of 30 cm as per the dates of sowing. The fertilizer was applied in the form of di- ammonium phosphate. The soil of the experimental site was deep sandy loam having pH of 7.9, EC of 0.13 dS/m and low in organic carbon (0.34%), low in available N status (193.36 kg ha-1), medium in available P2O5 (32.18 kg ha-1) and high in available K2O (249.67 kg ha-1). The crop was irrigated as and when required so as to maintain adequate soil moisture in the root zone The crop was sprayed with monocrotophos (1.25 l/ha) at initiation of flowering and at pod filling stage to protect the crop from pod borer attack. The yield was measured at the time of harvest. The cost of field preparation, sowing of seeds, thinning, weeding, plant protection, harvesting and cleaning contributed to fixed cost. The experiment was laid out in a split plot design with two sowing time (1st fortnight of November and 1st fortnight of December.) and four cultivars (H09-23, H08-18, C-235 and HC-1) kept in main plots while three seed rates viz. 40 kg ha-1, 50 kg ha-1 and 60 kg ha-1 were kept in subplots and replicated thrice. Results revealed that 1st fortnight of November sowing recorded significantly higher gross (Rs.1, 01,254 ha-1), net returns (Rs. 68,504 ha-1) and BC (3.09) ratio as compared to delayed crop of chickpea. Highest gross (Rs.91826 ha-1), net returns (Rs. 59076ha-1) and BC ratio (2.81) was recorded with H08-18. Higher value of cost of cultivation of chickpea was observed in higher seed rate than the lower ones. However no significant variation in net and gross returns was observed due to seed rates. Highest BC (2.72) ratio was recorded with 50 kg ha-1 which differs significantly from 60 kg ha-1 but was at par with 40 kg ha-1. This is because of higher grain yield obtained with 50 kg ha-1 seed rate. Net profit for farmers growing chickpea with seed rate of 50 kg ha-1 was higher than the farmers growing chickpea with seed rate of 40 and 60 kg ha.

Keywords: chickpea, cultivars, seed rate, sowing time

Procedia PDF Downloads 441