Search results for: high resolution synthetic imagery
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21617

Search results for: high resolution synthetic imagery

21347 Materialisation of Good Governance Concept by Effective Investment Dispute Resolution in the European Union

Authors: Jagna Mucha, Anna Kańciak

Abstract:

The concept of good governance constitutes a wide perspective for academic discussion, because it provides a substantial theoretical background for settling many practical problems faced contemporarily by the EU. The basic assumptions of good governance have basically remained unchanged since the 90’s, when the concept was introduced by the World Bank, although the scholarly discussions reveal new facets of the said concept, when related to specific domains. The paper discusses the application of the specific elements of the concept of good governance in the field of the international investment law. Specifically, it seeks to demonstrate that the concept of good governance regulates the issue of international investments in that, among others, it requires the application of the alternative dispute resolution in order to make the investment law enforceable in the best possible way.

Keywords: dispute resolution, european union, investments, good governance

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21346 Hollowfiber Poly Lactid Co-Glycolic Acid (PLGA)-Collagen Coated by Chitosan as a Candidate of Small Diameter Vascular Graft

Authors: Dita Mayasari, Zahrina Mardina, Riki Siswanto, Agresta Ifada, Ova Oktavina, Prihartini Widiyanti

Abstract:

Heart failure is a serious major health problem with high number of mortality per year. Bypass is one of the solutions that has often been taken. Natural vascular graft (xenograft) as the substitute in bypass is inconvenient due to ethic problems and the risk of infection transmission caused by the usage of another species transgenic vascular. Nowadays, synthetic materials have been fabricated from polymers. The aim of this research is to make a synthetic vascular graft with great physical strength, high biocompatibility, and good affordability. The method of this research was mixing PLGA and collagen by magnetic stirrer. This composite were shaped by spinneret with water as coagulant. Then it was coated by chitosan with 3 variations of weight (1 gram, 2 grams, and 3 grams) to increase hemo and cytocompatibility, proliferation, and cell attachment in order for the vascular graft candidates to be more biocompatible. Mechanical strength for each variation was 5,306 MPa (chitosan 1 gram), 3,433 MPa (chitosan 2 grams) and 3,745 MPa (chitosan 3 grams). All the tensile values were higher than human vascular tensile strength. Toxicity test showed that the living cells in all variations were more than 60% in number, thus the vascular graft is not toxic.

Keywords: chitosan, collagen, PLGA, spinneret

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21345 Rapid Building Detection in Population-Dense Regions with Overfitted Machine Learning Models

Authors: V. Mantey, N. Findlay, I. Maddox

Abstract:

The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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21344 Heterogeneous-Resolution and Multi-Source Terrain Builder for CesiumJS WebGL Virtual Globe

Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

Abstract:

The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain Builder, WebGL, Virtual Globe, CesiumJS, Tiled Map Service, TMS, Height-Map, Regular Grid, Geovisual Analytics, DTM

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21343 An ANOVA-based Sequential Forward Channel Selection Framework for Brain-Computer Interface Application based on EEG Signals Driven by Motor Imagery

Authors: Forouzan Salehi Fergeni

Abstract:

Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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21342 Experimental Chevreul’s Salt Production Methods on Copper Recovery

Authors: Turan Çalban, Oral Laçin, Abdüsselam Kurtbaş

Abstract:

The experimental production methods Chevreul’s salt being a intermediate stage product for copper recovery were investigated by dealing with the articles written on this topic. Chevreul’s salt, Cu2SO3.CuSO3.2H2O, being a mixed valence copper sulphite compound has been obtained by using different methods and reagents. Chevreul’s salt has a intense brick-red color. It is a highly stable and expensive salt. The production of Chevreul’s salt plays a key role in hiydrometallurgy. In recent years, researchs on this compound have been intensified. Silva et al. reported that this salt is thermally stable up to 200oC. Çolak et al. precipitated the Chevreul’s salt by using ammonia and sulphur dioxide. Çalban et al. obtained at the optimum conditions by passing SO2 from leach solutions with NH3-(NH4)2SO4. Yeşiryurt and Çalban investigated the optimum precipitation conditions of Chevreul’s salt from synthetic CuSO4 solutions including Na2SO3. Çalban et al. achieved the precipitation of Chevreul’s salt at the optimum conditions by passing SO2 from synthetic CuSO4 solutions. Çalban et al. examined the precipitation conditions of Chevreul’s salt using (NH4)2SO3 from synthetic aqueous CuSO4 solutions. In light of these studies, it can be said that Chevreul’s salt can be produced practically from both a leach solutions including copper and synthetic CuSO4 solutions.

Keywords: Chevreul’s salt, ammonia, copper sulpfite, sodium sülfite, optimum conditions

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21341 Microbial Bioproduction with Design of Metabolism and Enzyme Engineering

Authors: Tomokazu Shirai, Akihiko Kondo

Abstract:

Technologies of metabolic engineering or synthetic biology are essential for effective microbial bioproduction. It is especially important to develop an in silico tool for designing a metabolic pathway producing an unnatural and valuable chemical such as fossil materials of fuel or plastics. We here demonstrated two in silico tools for designing novel metabolic pathways: BioProV and HyMeP. Furthermore, we succeeded in creating an artificial metabolic pathway by enzyme engineering.

Keywords: bioinformatics, metabolic engineering, synthetic biology, genome scale model

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21340 Building Information Modelling (BIM) and Unmanned Aerial Vehicles (UAV) Technologies in Road Construction Project Monitoring and Management: Case Study of a Project in Cyprus

Authors: Yiannis Vacanas, Kyriacos Themistocleous, Athos Agapiou, Diofantos Hadjimitsis

Abstract:

Building Information Modelling (BIM) technology is considered by construction professionals as a very valuable process in modern design, procurement and project management. Construction professionals of all disciplines can use a single 3D model which BIM technology provides, to design a project accurately and furthermore monitor the progress of construction works effectively and efficiently. Unmanned Aerial Vehicles (UAVs), a technology initially developed for military applications, is now without any difficulty accessible and has already been used by commercial industries, including the construction industry. UAV technology has mainly been used for collection of images that allow visual monitoring of building and civil engineering projects conditions in various circumstances. UAVs, nevertheless, have undergone significant advances in equipment capabilities and now have the capacity to acquire high-resolution imagery from many angles in a cost effective manner, and by using photogrammetry methods, someone can determine characteristics such as distances, angles, areas, volumes and elevations of an area within overlapping images. In order to examine the potential of using a combination of BIM and UAV technologies in construction project management, this paper presents the results of a case study of a typical road construction project where the combined use of the two technologies was used in order to achieve efficient and accurate as-built data collection of the works progress, with outcomes such as volumes, and production of sections and 3D models, information necessary in project progress monitoring and efficient project management.

Keywords: BIM, project management, project monitoring, UAV

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21339 Text Localization in Fixed-Layout Documents Using Convolutional Networks in a Coarse-to-Fine Manner

Authors: Beier Zhu, Rui Zhang, Qi Song

Abstract:

Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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21338 Reduced Tillage and Bio-stimulant Application Can Improve Soil Microbial Enzyme Activity in a Dryland Cropping System

Authors: Flackson Tshuma, James Bennett, Pieter Andreas Swanepoel, Johan Labuschagne, Stephan van der Westhuizen, Francis Rayns

Abstract:

Amongst other things, tillage and synthetic agrochemicals can be effective methods of seedbed preparation and pest control. Nonetheless, frequent and intensive tillage and excessive application of synthetic agrochemicals, such as herbicides and insecticides, can reduce soil microbial enzyme activity. A decline in soil microbial enzyme activity can negatively affect nutrient cycling and crop productivity. In this study, the effects of four tillage treatments; continuous mouldboard plough; shallow tine-tillage to a depth of about 75 mm; no-tillage; and tillage rotation (involving shallow tine-tillage once every four years in rotation with three years of no-tillage), and two rates of synthetic agrochemicals (standard: with regular application of synthetic agrochemicals; and reduced: fewer synthetic agrochemicals in combination with bio-chemicals/ or bio-stimulants) on soil microbial enzyme activity were investigated between 2018 and 2020 in a typical Mediterranean climate zone in South Africa. Four different bio-stimulants applied contained: Trichoderma asperellum, fulvic acid, silicic acid, and Nereocystis luetkeana extracts, respectively. The study was laid out as a complete randomised block design with four replicated blocks. Each block had 14 plots, and each plot measured 50 m x 6 m. The study aimed to assess the combined impact of tillage practices and reduced rates of synthetic agrochemical application on soil microbial enzyme activity in a dryland cropping system. It was hypothesised that the application of bio-stimulants in combination with minimum soil disturbance will lead to a greater increase in microbial enzyme activity than the effect of applying either in isolation. Six soil cores were randomly and aseptically collected from each plot for microbial enzyme activity analysis from the 0-150 mm layer of a field trial under a dryland crop rotation system in the Swartland region. The activities of four microbial enzymes, β-glucosidase, acid phosphatase, alkaline phosphatase and urease, were assessed. The enzymes are essential for the cycling of glucose, phosphorus, and nitrogen, respectively. Microbial enzyme activity generally increased with a reduction of both tillage intensity and synthetic agrochemical application. The use of the mouldboard plough led to the least (P<0.05) microbial enzyme activity relative to the reduced tillage treatments, whereas the system with bio-stimulants (reduced synthetic agrochemicals) led to the highest (P<0.05) microbial enzyme activity relative to the standard systems. The application of bio-stimulants in combination with reduced tillage, particularly no-tillage, could be beneficial for enzyme activity in a dryland farming system.

Keywords: bio-stimulants, soil microbial enzymes, synthetic agrochemicals, tillage

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21337 Pectin Degrading Enzyme: Entrapment of Pectinase Using Different Synthetic and Non-Synthetic Polymers for Continuous Degradation of Pectin Polymer

Authors: Haneef Ur Rehman, Afsheen Aman, Abdul Hameed Baloch, Shah Ali Ul Qader

Abstract:

Pectinase is a heterogeneous group of enzymes that catalyze the hydrolysis of pectin substances and widely has been used in food and textile industries. In current study, pectinase from B. licheniformis KIBGE-IB21 was immobilized within different polymers (calcium alginate beads, polyacrylamide gel and agar-agar matrix) to enhance its catalytic properties. Polyacrylamide gel was found to be most promising one and gave maximum (89%) immobilization yield. While less immobilization yield was observed in case of calcium alginate beads that only retained 46 % activity. The reaction time for maximum pectinolytic activity was increased from 5.0 to 10 minutes after immobilization. The temperature of pectinase for maximum enzyme activity was increased from 45 °C to 50 °C and 55 °C when it was immobilized within agar-agar and calcium alginate beads, respectively. The optimum pH of pectinase didn’t alter when it was immobilized within polyacrylamide gel and calcium alginate beads, but in case of agar-agar it was changed from pH 10 to pH 9.0. Thermal stability of pectinase was improved after immobilization and immobilized pectinase showed higher toleration against different temperatures as compared to free enzyme. It can be concluded that the entrapment is a simple, single step and promising procedure to immobilized pectinase within different synthetic and non-synthetic polymers and enhanced its catalytic properties.

Keywords: pectinase, characterization immobilization, polyacrylamide, agar-agar, calcium alginate beads

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21336 Predicting OpenStreetMap Coverage by Means of Remote Sensing: The Case of Haiti

Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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21335 Poly-ε-Caprolactone Nanofibers with Synthetic Growth Factor Enriched Liposomes as Controlled Drug Delivery System

Authors: Vera Sovkova, Andrea Mickova, Matej Buzgo, Karolina Vocetkova, Eva Filova, Evzen Amler

Abstract:

PCL (poly-ε-caprolactone) nanofibrous scaffolds with adhered liposomes were prepared and tested as a possible drug delivery system for various synthetic growth factors. TGFβ, bFGF, and IGF-I have been shown to increase hMSC (human mesenchymal stem cells) proliferation and to induce hMSC differentiation. Functionalized PCL nanofibers were prepared with synthetic growth factors encapsulated in liposomes adhered to them in three different concentrations. Other samples contained PCL nanofibers with adhered, free synthetic growth factors. The synthetic growth factors free medium served as a control. The interaction of liposomes with the PCL nanofibers was visualized by SEM, and the release kinetics were determined by ELISA testing. The potential of liposomes, immobilized on the biodegradable scaffolds, as a delivery system for synthetic growth factors, and as a suitable system for MSCs adhesion, proliferation and differentiation in vitro was evaluated by MTS assay, dsDNA amount determination, confocal microscopy, flow cytometry and real-time PCR. The results showed that the growth factors adhered to the PCL nanofibers stimulated cell proliferation mainly up to day 11 and that subsequently their effect was lower. By contrast, the release of the lowest concentration of growth factors from liposomes resulted in gradual proliferation of MSCs throughout the experiment. Moreover, liposomes, as well as free growth factors, stimulated type II collagen production, which was confirmed by immunohistochemical staining using monoclonal antibody against type II collagen. The results of this study indicate that growth factors enriched liposomes adhered to surface of PCL nanofibers could be useful as a drug delivery instrument for application in short timescales, be combined with nanofiber scaffolds to promote local and persistent delivery while mimicking the local microenvironment. This work was supported by project LO1508 from the Ministry of Education, Youth and Sports of the Czech Republic

Keywords: drug delivery, growth factors, hMSC, liposomes, nanofibres

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21334 Bias Minimization in Construction Project Dispute Resolution

Authors: Keyao Li, Sai On Cheung

Abstract:

Incorporation of alternative dispute resolution (ADR) mechanism has been the main feature of current trend of construction project dispute resolution (CPDR). ADR approaches have been identified as efficient mechanisms and are suitable alternatives to litigation and arbitration. Moreover, the use of ADR in this multi-tiered dispute resolution process often leads to repeated evaluations of a same dispute. Multi-tiered CPDR may become a breeding ground for cognitive biases. When completed knowledge is not available at the early tier of construction dispute resolution, disputing parties may form preconception of the dispute matter or the counterpart. This preconception would influence their information processing in the subsequent tier. Disputing parties tend to search and interpret further information in a self-defensive way to confirm their early positions. Their imbalanced information collection would boost their confidence in the held assessments. Their attitudes would be hardened and difficult to compromise. The occurrence of cognitive bias, therefore, impedes efficient dispute settlement. This study aims to explore ways to minimize bias in CPDR. Based on a comprehensive literature review, three types of bias minimizing approaches were collected: strategy-based, attitude-based and process-based. These approaches were further operationalized into bias minimizing measures. To verify the usefulness and practicability of these bias minimizing measures, semi-structured interviews were conducted with ten CPDR third party neutral professionals. All of the interviewees have at least twenty years of experience in facilitating settlement of construction dispute. The usefulness, as well as the implications of the bias minimizing measures, were validated and suggested by these experts. There are few studies on cognitive bias in construction management in general and in CPDR in particular. This study would be the first of its type to enhance the efficiency of construction dispute resolution by highlighting strategies to minimize the biases therein.

Keywords: bias, construction project dispute resolution, minimization, multi-tiered, semi-structured interview

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21333 The Social Process of Alternative Dispute Resolution and Collective Conciliation: Unveiling the Theoretical Framework

Authors: Adejoke Yemisi Ige

Abstract:

This study presents a conceptual analysis and investigation into the development of a systematic framework required for better understanding of the social process of Alternative Dispute Resolution (ADR) and collective conciliation. The critical examination presented in this study is significant because; it draws on insight from ADR, negotiation and collective bargaining literature and applies it in our advancement of a methodical outline which gives an insight into the influence of the key actors and other stakeholder strategies and behaviours during dispute resolution in relation to the outcomes which is novel. This study is qualitative and essentially inductive in nature. One of the findings of the study confirms the need to consider ADR and collective conciliation within the context of the characteristic conditions; which focus on the need for some agreement to be reached. Another finding of the study shows the extent which information-sharing, willingness of the parties to negotiate and make concession assist both parties to attain resolution. This paper recommends that in order to overcome deadlock and attain acceptable outcomes at the end of ADR and collective conciliation, the importance of information exchange and sustenance of trade union and management relationship cannot be understated. The need for trade unions and management, the representatives to achieve their expectations in order to build the confidence and assurance of their respective constituents is essential. In conclusion, the analysis presented in this study points towards a set of factors that together can be called the social process of collective conciliation nevertheless; it acknowledges that its application to collective conciliation is new.

Keywords: alternative dispute resolution, collective conciliation, social process, theoretical framework, unveiling

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21332 Adsorption Kinetics and Equilibria at an Air-Liquid Interface of Biosurfactant and Synthetic Surfactant

Authors: Sagheer A. Onaizi

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The adsorption of anionic biosurfactant (surfactin) and anionic synthetic surfactant (sodium dodecylbenzenesulphonate, abbreviated as SDOBS) from phosphate buffer containing high concentrations of co- and counter-ions to the air-buffer interface has been investigated. The self-assembly of the two surfactants at the interface has been monitored through dynamic surface tension measurements. The equilibrium surface pressure-surfactant concentration data in the premicellar region were regressed using Gibbs adsorption equation. The predicted surface saturations for SDOBS and surfactin are and, respectively. The occupied area per an SDOBS molecule at the interface saturation condition is while that occupied by a surfactin molecule is. The surface saturations reported in this work for both surfactants are in a very good agreement with those obtained using expensive techniques such as neutron reflectometry, suggesting that the surface tension measurements coupled with appropriate theoretical analysis could provide useful information comparable to those obtained using highly sophisticated techniques.

Keywords: adsorption, air-liquid interface, biosurfactant, surface tension

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21331 Comparative Performance Analysis of Fiber Delay Line Based Buffer Architectures for Contention Resolution in Optical WDM Networks

Authors: Manoj Kumar Dutta

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Wavelength division multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating fiber delay lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput

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21330 Regional Changes under Extreme Meteorological Events

Authors: Renalda El Samra, Elie Bou-Zeid, Hamza Kunhu Bangalath, Georgiy Stenchikov, Mutasem El Fadel

Abstract:

The regional-scale impact of climate change over complex terrain was examined through high-resolution dynamic downscaling conducted using the Weather Research and Forecasting (WRF) model, with initial and boundary conditions from a High-Resolution Atmospheric Model (HiRAM). The analysis was conducted over the eastern Mediterranean, with a focus on the country of Lebanon, which is characterized by a challenging complex topography that magnifies the effect of orographic precipitation. Four year-long WRF simulations, selected based on HiRAM time series, were performed to generate future climate projections of extreme temperature and precipitation over the study area under the conditions of the Representative Concentration Pathway (RCP) 4.5. One past WRF simulation year, 2008, was selected as a baseline to capture dry extremes of the system. The results indicate that the study area might be exposed to a temperature increase between 1.0 and 3ºC in summer mean values by 2050, in comparison to 2008. For extreme years, the decrease in average annual precipitation may exceed 50% at certain locations in comparison to 2008.

Keywords: HiRAM, regional climate modeling, WRF, Representative Concentration Pathway (RCP)

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21329 Carbon Nitride Growth on ZnO Architectures for Enhanced Photoelectrochemical Water Splitting Application

Authors: Špela Hajduk, Sean P. Berglund, Matejka Podlogar, Goran Dražić, Fatwa F. Abdi, Zorica C. Orel, Menny Shalom

Abstract:

Graphitic carbon nitride materials (g-CN) have emerged as an attractive photocatalyst and electrocatalyst for photo and electrochemical water splitting reaction, due to their environmental benignity nature and suitable band gap. Many approaches were introduced to enhance the photoactivity and electronic properties of g-CN and resulted in significant changes in the electronic and catalytic properties. Here we demonstrate the synthesis of thin and homogenous g-CN layer on highly ordered ZnO nanowire (NW) substrate by growing a seeding layer of small supramolecular assemblies on the nanowires. The new synthetic approach leads to the formation of thin g-CN layer (~3 nm) without blocking all structure. Two different deposition methods of carbon nitride were investigated and will be presented. The amount of loaded carbon nitride significantly influences the PEC activity of hybrid material and all the ZnO/g-CNx electrodes show great improvement in photoactivity. The chemical structure, morphology and optical properties of the deposited g-CN were fully characterized by various techniques as X-ray powder spectroscopy (XRD), scanning electron microscopy (SEM), focused ion beam scanning electron microscopy (FIB-SEM), high-resolution scanning microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS).

Keywords: carbon nitride, photoanode, solar water splitting, zinc oxide

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21328 Landslide Hazard Assessment Using Physically Based Mathematical Models in Agricultural Terraces at Douro Valley in North of Portugal

Authors: C. Bateira, J. Fernandes, A. Costa

Abstract:

The Douro Demarked Region (DDR) is a production Porto wine region. On the NE of Portugal, the strong incision of the Douro valley developed very steep slopes, organized with agriculture terraces, have experienced an intense and deep transformation in order to implement the mechanization of the work. The old terrace system, based on stone vertical wall support structure, replaced by terraces with earth embankments experienced a huge terrace instability. This terrace instability has important economic and financial consequences on the agriculture enterprises. This paper presents and develops cartographic tools to access the embankment instability and identify the area prone to instability. The priority on this evaluation is related to the use of physically based mathematical models and develop a validation process based on an inventory of the past embankment instability. We used the shallow landslide stability model (SHALSTAB) based on physical parameters such us cohesion (c’), friction angle(ф), hydraulic conductivity, soil depth, soil specific weight (ϱ), slope angle (α) and contributing areas by Multiple Flow Direction Method (MFD). A terraced area can be analysed by this models unless we have very detailed information representative of the terrain morphology. The slope angle and the contributing areas depend on that. We can achieve that propose using digital elevation models (DEM) with great resolution (pixel with 40cm side), resulting from a set of photographs taken by a flight at 100m high with pixel resolution of 12cm. The slope angle results from this DEM. In the other hand, the MFD contributing area models the internal flow and is an important element to define the spatial variation of the soil saturation. That internal flow is based on the DEM. That is supported by the statement that the interflow, although not coincident with the superficial flow, have important similitude with it. Electrical resistivity monitoring values which related with the MFD contributing areas build from a DEM of 1m resolution and revealed a consistent correlation. That analysis, performed on the area, showed a good correlation with R2 of 0,72 and 0,76 at 1,5m and 2m depth, respectively. Considering that, a DEM with 1m resolution was the base to model the real internal flow. Thus, we assumed that the contributing area of 1m resolution modelled by MFD is representative of the internal flow of the area. In order to solve this problem we used a set of generalized DEMs to build the contributing areas used in the SHALSTAB. Those DEMs, with several resolutions (1m and 5m), were built from a set of photographs with 50cm resolution taken by a flight with 5km high. Using this maps combination, we modelled several final maps of terrace instability and performed a validation process with the contingency matrix. The best final instability map resembles the slope map from a DEM of 40cm resolution and a MFD map from a DEM of 1m resolution with a True Positive Rate (TPR) of 0,97, a False Positive Rate of 0,47, Accuracy (ACC) of 0,53, Precision (PVC) of 0,0004 and a TPR/FPR ratio of 2,06.

Keywords: agricultural terraces, cartography, landslides, SHALSTAB, vineyards

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21327 Review of Comparison of Subgrade Soil Stabilised with Natural, Synthetic, and Waste Fibers

Authors: Jacqueline Michella Anak Nathen

Abstract:

Subgrade soil is an essential component in the design of road structures as it provides lateral support to the pavement. One of the main reasons for the failure of the pavement is the settlement of the subgrade and the high susceptibility to moisture, which leads to a loss of strength of the subgrade. Construction over weak or soft subgrade affects the performance of the pavement and causes instability of the pavement. If the mechanical properties of the subgrade soils are lower than those required, the soil stabilisation method can be an option to improve the soil properties of the weak subgrade. Soil stabilisation is one of the most popular techniques for improving poor subgrade soils, resulting in a significant improvement in the subgrade soil’s tensile strength, shear strength, and bearing capacity. Soil stabilisation encompasses the various methods used to alter the properties of soil to improve its engineering properties. Soil stabilisation can be broadly divided into four types: thermal, electrical, mechanical, and chemical. The most common method of improving the physical and mechanical properties of soils is stabilisation using binders such as cement and lime. However, soil stabilisation with conventional methods using cement and lime has become uneconomical in recent years, so there is a need to look for an alternative, such as fiber. Although not a new technique, adding fiber is a very practical alternative to soil stabilisation. Various types of fibers, such as natural, synthetic, and waste fibers, have been used as stabilising agents to improve the strength and durability of subgrade soils. This review provides a comprehensive comparison of the effectiveness of natural, synthetic, and waste fibers in stabilising subgrade soils.

Keywords: subgrade, soil stabilisation, pavement, fiber, stabiliser

Procedia PDF Downloads 98
21326 Simple and Effective Method of Lubrication and Wear Protection

Authors: Buddha Ratna Shrestha, Jimmy Faivre, Xavier Banquy

Abstract:

By precisely controlling the molecular interactions between anti-wear macromolecules and bottle-brush lubricating molecules in the solution state, we obtained a fluid with excellent lubricating and wear protection capabilities. The reason for this synergistic behavior relies on the subtle interaction forces between the fluid components which allow the confined macromolecules to sustain high loads under shear without rupture. Our results provide rational guides to design such fluids for virtually any type of surfaces. The lowest friction coefficient and the maximum pressure that it can sustain is 5*10-3 and 2.5 MPa which is close to the physiological pressure. Lubricating and protecting surfaces against wear using liquid lubricants is a great technological challenge. Until now, wear protection was usually imparted by surface coatings involving complex chemical modifications of the surface while lubrication was provided by a lubricating fluid. Hence, we here research for a simple, effective and applicable solution to the above problem using surface force apparatus (SFA). SFA is a powerful technique with sub-angstrom resolution in distance and 10 nN/m resolution in interaction force while performing friction experiment. Thus, SFA is used to have the direct insight into interaction force, material and friction at interface. Also, we always know the exact contact area. From our experiments, we found that by precisely controlling the molecular interactions between anti-wear macromolecules and lubricating molecules, we obtained a fluid with excellent lubricating and wear protection capabilities. The reason for this synergistic behavior relies on the subtle interaction forces between the fluid components which allow the confined macromolecules to sustain high loads under shear without rupture. The lowest friction coefficient and the maximum pressure that it can sustain in our system is 5*10-3 and 2.5 GPA which is well above the physiological pressure. Our results provide rational guides to design such fluids for virtually any type of surfaces. Most importantly this process is simple, effective and applicable method of lubrication and protection as until now wear protection was usually imparted by surface coatings involving complex chemical modifications of the surface. Currently, the frictional data that are obtained while sliding the flat mica surfaces are compared and confirmed that a particular mixture of solution was found to surpass all other combination. So, further we would like to confirm that the lubricating and antiwear protection remains the same by performing the friction experiments in synthetic cartilages.

Keywords: bottle brush polymer, hyaluronic acid, lubrication, tribology

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21325 Effect of Botanical and Synthetic Insecticide on Different Insect Pests and Yield of Pea (Pisum sativum)

Authors: Muhammad Saeed, Nazeer Ahmed, Mukhtar Alam, Fazli Subhan, Muhammad Adnan, Fazli Wahid, Hidayat Ullah, Rafiullah

Abstract:

The present experiment evaluated different synthetic insecticides against Jassid (Amrasca devastations) on pea crop at Agriculture Research Institute Tarnab, Peshawar Khyber Pakhtunkhwa. The field was prepared to cultivate okra crop in Randomized Complete Block (RCB) Design having six treatments with four replications. Plant to plant and row to row distance was kept at 15 cm and 30 cm, respectively. Pre and post spray data were recorded randomly from the top, middle and bottom leaves of five selected plants. Five synthetic insecticides, namely Confidor (Proponil), a neonicotinoid insecticide, Chlorpyrifos (chlorinated organophosphate (OP) insecticide), Lazer (dinitroaniline) (Pendimethaline), Imidacloprid (neonicotinoids insecticide) and Thiodan (Endosulfan, organochlorine insecticide), were used against infestation of aphids, pea pod borer, stem fly, leaf minor and pea weevil. Each synthetic insecticide showed significantly more effectiveness than control (untreated plots) but was non-significant among each other. The lowest population density was recorded in the plot treated with synthetic insecticide i.e. Confidor (0.6175 liter.ha-1) (4.24 aphids plant⁻¹) which is followed by Imidacloprid (0.6175 liter.ha⁻¹) (4.64 pea pod borer plant⁻¹), Thiodan (1.729 liter.ha⁻¹) (4.78 leaf minor plant⁻¹), Lazer (2.47 liter.ha-1) (4.91 pea weevil plant⁻¹), Chlorpyrifos (1.86 liter.ha⁻¹) (5.11 stem fly plant⁻¹), respectively while the highest population was recorded from the control plot. It is concluded from the data that the residual effect decreases with time after the application of spray, which may be less dangerous to the environment and human beings and can effectively manage this dread.

Keywords: okra crop, jassids, Confidor, imidacloprid, chlorpyrifos, laser, Thiodan

Procedia PDF Downloads 84
21324 Change Detection Method Based on Scale-Invariant Feature Transformation Keypoints and Segmentation for Synthetic Aperture Radar Image

Authors: Lan Du, Yan Wang, Hui Dai

Abstract:

Synthetic aperture radar (SAR) image change detection has recently become a challenging problem owing to the existence of speckle noises. In this paper, an unsupervised distribution-free change detection for SAR image based on scale-invariant feature transform (SIFT) keypoints and segmentation is proposed. Firstly, the noise-robust SIFT keypoints which reveal the blob-like structures in an image are extracted in the log-ratio image to reduce the detection range. Then, different from the traditional change detection which directly obtains the change-detection map from the difference image, segmentation is made around the extracted keypoints in the two original multitemporal SAR images to obtain accurate changed region. At last, the change-detection map is generated by comparing the two segmentations. Experimental results on the real SAR image dataset demonstrate the effectiveness of the proposed method.

Keywords: change detection, Synthetic Aperture Radar (SAR), Scale-Invariant Feature Transformation (SIFT), segmentation

Procedia PDF Downloads 386
21323 Exploring Selected Nigerian Fictional Work and Films as Sources of Peace Building and Conflict Resolution in the Natural Resource Extraction Regions of Nigeria: A Social Conflict Theoretical Perspective and Analysis

Authors: Joyce Onoromhenre Agofure

Abstract:

Research has shown how fictional work and films reflect the destruction of the environment due to the exploitation of oil, gas, gold, and forest products by multinational companies for profits but overlook discussions on conflict resolution and peacebuilding. However, this paper examines the manner art forms project peace and conflict resolution, thereby contributing to mediation and stability geared towards changing appalling situations in the resource extraction regions of Nigeria. This paper draws from selected Nigerian films- Blood and Oil (2019), directed by Curtis Graham, Black November (2012), directed by Jeta Amata, and a novel- Death of Eternity (2007), by Adamu Kyuka Usman. The study seeks to show that the disruptions caused in the natural resource regions of Nigeria have not only left adverse effects on the social well-being of the people but require resolutions through means of peacebuilding. By adopting the theoretical insights of Social Conflict, this paper focuses on artistic processes that enhance peacebuilding and conflict resolution in non-violent ways by using scenes, visual effects, themes, and images that can educate by shaping opinions, influencing attitudes, and changing ideas and behavioral patterns of individuals and communities. Put together; the research will open up critical perceptions brought about by the artists of study to shed light on the dire need to sustain peace and actively participate in conflict resolution in natural resource extraction spaces.

Keywords: natural resource, extraction, conflict resolution, peace building

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21322 A Review of the Fundamental Aspects and Dimensions of Alternative Dispute Resolution (ADR) as Important Components in the Promotion of Social Justice in Nigeria

Authors: Odoh Ben Uruchi

Abstract:

Access to Justice implies access to social and distributive Justice. Access to social justice in Nigeria remains an illusion where cases last in courts for unduly long period of time, as is currently the situation in the country. As the popular saying goes– justice delayed is justice denied. It is, however, important to underscore the point that these perspectives are not necessarily disconnected since the extent to which one can have distributive justice in any system is largely determined by the level and effectiveness of social justice in the country. Generally, Alternative Dispute Resolution (ADR) Processes are increasingly being accepted in Nigeria as appropriate mechanisms for resolving disputes. While some jurisdictions have institutionalized ADR through the concept of a Multidoor Courthouse, many other are at different stages of doing same. With these developments, it is obvious that stakeholders in the administration of justice in Nigeria, can no longer be indifferent about understanding and fully mainstreaming ADR into their various activities and professional practice. Any framework for promoting social justice in Nigeria should therefore of necessity include provision of avenues for use of ADR in the protection and enforcement of citizen’s rights. The constitutional and other legal provisions that guarantee various rights of citizens cannot of itself ensure the enjoyment of the rights in the absence of an effective framework for dispute resolution. Excessive reliance on litigation and other adversarial approaches will also fail to ensure a sound regime of social justice. There should be structured mainstreaming of alternative dispute resolution mechanisms in justice delivery if the society must provide and guarantee social justice to the citizens. This paper seeks to address some of the fundamental issues affecting the perception, knowledge and skills of ADR in the provision of social justice. In doing this, the paper proposes to unlock the full enormous potentials of Alternative Dispute Resolution (ADR) in promoting access to justice in Nigeria.

Keywords: aspects, dimensions, alternative dispute resolution, social justice

Procedia PDF Downloads 434
21321 Utilizing the Principal Component Analysis on Multispectral Aerial Imagery for Identification of Underlying Structures

Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

Abstract:

Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

Procedia PDF Downloads 178
21320 Integration of GIS with Remote Sensing and GPS for Disaster Mitigation

Authors: Sikander Nawaz Khan

Abstract:

Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information of natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provide precise and accurate locations and other related information like speed, track, direction and distance of target object to emergency responders. Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing vital role in disaster management. Early on Geographic Information System (GIS) was used to collect, arrange, and map the spatial information but now it has capability to analyze spatial data. This analytical ability of GIS is the main cause of its adaption by different emergency services providers like police and ambulance service. Full potential of these so called 3S technologies cannot be used in alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

Keywords: disaster mitigation, GIS, GPS, remote sensing

Procedia PDF Downloads 481
21319 The Climate Impact Due to Clouds and Selected Greenhouse Gases by Short Wave Upwelling Radiative Flux within Spectral Range of Space-Orbiting Argus1000 Micro-Spectrometer

Authors: Rehan Siddiqui, Brendan Quine

Abstract:

The Radiance Enhancement (RE) and integrated absorption technique is applied to develop a synthetic model to determine the enhancement in radiance due to cloud scene and Shortwave upwelling Radiances (SHupR) by O2, H2O, CO2 and CH4. This new model is used to estimate the magnitude variation for RE and SHupR over spectral range of 900 nm to 1700 nm by varying surface altitude, mixing ratios and surface reflectivity. In this work, we employ satellite real observation of space orbiting Argus 1000 especially for O2, H2O, CO2 and CH4 together with synthetic model by using line by line GENSPECT radiative transfer model. All the radiative transfer simulations have been performed by varying over a different range of percentages of water vapor contents and carbon dioxide with the fixed concentration oxygen and methane. We calculate and compare both the synthetic and real measured observed data set of different week per pass of Argus flight. Results are found to be comparable for both approaches, after allowing for the differences with the real and synthetic technique. The methodology based on RE and SHupR of the space spectral data can be promising for the instant and reliable classification of the cloud scenes.

Keywords: radiance enhancement, radiative transfer, shortwave upwelling radiative flux, cloud reflectivity, greenhouse gases

Procedia PDF Downloads 336
21318 Non-Uniform Filter Banks-based Minimum Distance to Riemannian Mean Classifition in Motor Imagery Brain-Computer Interface

Authors: Ping Tan, Xiaomeng Su, Yi Shen

Abstract:

The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

Procedia PDF Downloads 126