Search results for: greener cloud

Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

Procedia PDF Downloads 126

Authors: Joshua Buli, David Pietrowski, Samuel Britton

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Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.

Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization

Procedia PDF Downloads 85

Authors: M. Roberts Masillamani

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There is a phenomenal difference, as regard to the teaching methodology adopted at the urban and the rural area colleges. However, bright and talented student may be from rural back ground even. But there is huge dearth of the digitization in the rural areas and lesser developed countries. Today’s students need new skills to compete and successful in the future. Education should be combination of practical, intellectual, and social skills. What does this mean for rural classrooms and how can it be achieved. Rural colleges are not able to hire the best resources, since the best teacher’s aim is to move towards the city. If city is provided everywhere, then there will be no rural area. This is possible by forming university clusters (UC). The University cluster is a group of renowned and accredited universities coming together to bridge this dearth. The UC will deliver the live lectures and allow the students’ from remote areas to actively participate in the classroom. This paper tries to present a plan of action of providing a better live classroom teaching and learning system from the city to the rural and the lesser developed countries. This paper titled “University Clusters using ICT for teaching and learning” provides a true concept of opening live digital classroom windows for rural colleges, where resources are not available, thus reducing the digital divide. This is different from pod casting a lecture or distance learning and eLearning. The live lecture can be streamed through digital equipment to another classroom. The rural students can collaborate with their peers and critiques, be assessed, collect information, acquire different techniques in assessment and learning process. This system will benefit rural students and teachers and develop socio economic status. This will also will increase the degree of confidence of the Rural students and teachers. Thus bringing about the concept of ‘Train the Trainee’ in reality. An educational university cloud for each cluster will be built remote infrastructure facilities (RIF) for the above program. The users may be informed, about the available lecture schedules, through the RIF service. RIF with an educational cloud can be set by the universities under one cluster. This paper talks a little more about University clusters and the methodology to be adopted as well as some extended features like, tutorial classes, library grids, remote laboratory login, research and development.

Keywords: lesser developed countries, digital divide, digital learning, education, e-learning, ICT, library grids, live classroom windows, RIF, rural, university clusters and urban

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

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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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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

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Authors: Keyur Raval, Steffen Krohn, Bruno Moerschbacher

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Chitin, the biopolymer of the N-acetylglucosamine, is the most abundant biopolymer on the planet after cellulose. Industrially, chitin is isolated and purified from the shell residues of shrimps. A deacetylated derivative of chitin i.e. chitosan has more market value and applications owing to it solubility and overall cationic charge compared to the parent polymer. This deacetylation on an industrial scale is performed chemically using alkalis like sodium hydroxide. This reaction not only is hazardous to the environment owing to negative impact on the marine ecosystem. A greener option to this process is the enzymatic process. In nature, the naïve chitin is converted to chitosan by chitin deacetylase (CDA). This enzymatic conversion on the industrial scale is however hampered by the crystallinity of chitin. Thus, this enzymatic action requires the substrate i.e. chitin to be soluble which is technically difficult and an energy consuming process. We in this project wanted to address this shortcoming of CDA. In lieu of this, we have modeled a fusion protein with CDA and an auxiliary protein. The main interest being to increase the accessibility of the enzyme towards crystalline chitin. A similar fusion work with chitinases had improved the catalytic ability towards insoluble chitin. In the first step, suitable partners were searched through the protein data bank (PDB) wherein the domain architecture were sought. The next step was to create the models of the fused product using various in silico techniques. The models were created by MODELLER and evaluated for properties such as the energy or the impairment of the binding sites. A fusion PCR has been designed based on the linker sequences generated by MODELLER and would be tested for its activity towards insoluble chitin.

Keywords: chitin deacetylase, modeling, chitin binding domain, chitinases

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Authors: Hassan Bohra, Mingfeng Wang

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Conjugated porous polymers (CPPs) are amorphous, insoluble and highly robust organic semiconductors that have been largely synthesized by traditional transition-metal catalyzed reactions. The distinguishing feature of CPP materials is that they combine microporosity and high surface areas with extended conjugation, making them ideal for versatile applications such as separation, catalysis and energy storage. By applying a modular approach to synthesis, chemical and electronic properties of CPPs can be tailored for specific applications making these materials economical alternatives to inorganic semiconductors. Direct arylation - an environmentally benign alternative to traditional polymerization reactions – is one such reaction that extensively over the last decade for the synthesis of linear p-conjugated polymers. In this report, we present the synthesis and characterization of a new series of robust conjugated porous polymers synthesized by facile direct arylation polymerization of thiophene-flanked acceptor building blocks with multi-brominated aryls with different geometries. We observed that the porosities and morphologies of the polymers are determined by the chemical structure of the aryl bromide used. Moreover, good control of the optical bandgap in the range 2.53 - 1.3 eV could be obtained by using different building blocks. Structure-property relationships demonstrated in this study suggest that direct arylation polymerization is an attractive synthetic tool for the rational design of porous organic materials with tunable photo-physical properties for applications in photocatalysis, energy storage and conversion.

Keywords: direct arylation, conjugated porous polymers, triazine, photocatalysis

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

Procedia PDF Downloads 87

Authors: Jiankang Wang, Hongyang Yu

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This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects.

Keywords: 3D reconstruction, bundlefusion, lossless compression, depth image

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Authors: Pin Xiu Chen, Shang Liang Chen

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A virtualized software controller is developed in this research to replace traditional hardware control units. This virtualized software controller transfers motion interpolation calculations from the motion control units of end devices to edge computing platforms, thereby reducing the end devices' computational load and hardware requirements and making maintenance and updates easier. The study also applies the concept of microservices, dividing the control system into several small functional modules and then deploy into a cloud data server. This reduces the interdependency among modules and enhances the overall system's flexibility and scalability. Finally, with containerization technology, the system can be deployed and started in a matter of seconds, which is more efficient than traditional virtual machine deployment methods. Furthermore, this virtualized software controller communicates with end control devices via wireless networks, making the placement of production equipment or the redesign of processes more flexible and no longer limited by physical wiring. To handle the large data flow and maintain low-latency transmission, this study integrates 5G technology, fully utilizing its high speed, wide bandwidth, and low latency features to achieve rapid and stable remote machine control. An experimental setup is designed to verify the feasibility and test the performance of this framework. This study designs a smart manufacturing site with a 5G communication architecture, serving as a field for experimental data collection and performance testing. The smart manufacturing site includes one robotic arm, three Computer Numerical Control machine tools, several Input/Output ports, and an edge computing architecture. All machinery information is uploaded to edge computing servers and cloud servers via 5G communication and the Internet of Things framework. After analysis and computation, this information is converted into motion control commands, which are transmitted back to the relevant machinery for motion control through 5G communication. The communication time intervals at each stage are calculated using the C++ chrono library to measure the time difference for each command transmission. The relevant test results will be organized and displayed in the full-text.

Keywords: 5G, MEC, microservices, virtualized software controller, smart manufacturing

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Sarada Nivedita Bhuyan

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Earthquake is the sudden, rapid movement of the earth’s crust and is the natural means of releasing stress. Tectonic plates play a major role for earthquakes as tectonic plates are the crust of the planet. The boundary lines of tectonic plates are usually known as fault lines. To understand an earthquake before its occurrence, different types of earthquake precursors are studied by different researchers. Surface temperature, strange cloud cover, earth’s electric field, geomagnetic phenomena, ground water level, active faults, ionospheric anomalies, tectonic movements are taken as parameters for earthquake study by different researchers. In this paper we tried to gather complete and helpful information of earthquake precursors which have been studied until now.

Keywords: earthquake precursors, earthquake, tectonic plates, fault

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Authors: Mandeep Kaur, Jitendra K. Bera

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The search for atom-economical and green synthetic methods for the synthesis of functionalized molecules has attracted much attention. Metal ligand cooperation (MLC) plays a pivotal role in organometallic catalysis to activate C−H, H−H, O−H, N−H and B−H bonds through reversible bond breaking and bond making process. Towards this goal, a bifunctional N─heterocyclic carbene (NHC) based pyridyl-functionalized amide ligand precursor, and corresponding dearomatized iridium complex was synthesized. The NMR and UV/Vis acid titration study have been done to prove the proton response nature of the iridium complex. Further, the dearomatized iridium complex explored as a catalyst on the platform of MLC via dearomatzation/aromatization mode of action towards atom economical α and β─alkylation of ketones and secondary alcohols by using primary alcohols through hydrogen borrowing methodology. The key features of the catalysis are high turnover frequency (TOF) values, low catalyst loading, low base loading and no waste product. The greener syntheses of quinoline, lactone derivatives and selective alkylation of drug molecules like pregnenolone and testosterone were also achieved successfully. Another structurally similar iridium complex was also synthesized with modified ligand precursor where a pendant amide unit was absent. The inactivity of this analogue iridium complex towards catalysis authenticated the participation of proton responsive imido sidearm of the ligand to accelerate the catalytic reaction. The mechanistic investigation through control experiments, NMR and deuterated labeling study, authenticate the borrowing hydrogen strategy.

Keywords: C-C bond formation, hydrogen borrowing, metal ligand cooperation (MLC), n-heterocyclic carbene

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Authors: Sartaj Singh, Amar Singh, Ashok Sharma, Sandeep Kaur

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With upcoming threats in a digital world, we need to work continuously in the area of security in all aspects, from hardware to software as well as data modelling. The rise in social media activities and hunger for data by various entities leads to cybercrime and more attack on the privacy and security of persons. Cryptography has always been employed to avoid access to important data by using many processes. Symmetric key and asymmetric key cryptography have been used for keeping data secrets at rest as well in transmission mode. Various cryptosystems have evolved from time to time to make the data more secure. In this research article, we are studying various cryptosystems in asymmetric cryptography and their application with usefulness, and much emphasis is given to Elliptic curve cryptography involving algebraic mathematics.

Keywords: cryptography, symmetric key cryptography, asymmetric key cryptography

Procedia PDF Downloads 124

Authors: I Putu Deny Arthawan Sugih Prabowo, Eko Nugroho, Rudy Hartanto

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Known, Green IT is a concept about how to use the technology (IT) wisely, efficiently, and environmentally. However, it exists as the consequence of the rapid-growth of the technology (especially IT) currently. Not only for the environments, the usage of Green IT applications, e.g. Cloud Computing (Cloud Storage) and E-Money (E-Cash), also gives its benefits for the organizational business strategy (especially the organizational product/service strategy) in order to gain the organizational competitive advantage (to be the market leader). This paper takes the case at E-Money as a Value-Added Services (VAS) of a telecommunication firm (company) in Indonesia which it also competes with the competitors’ similar product (service). Although it has been a popular telecommunication firm’s product/service, but its strategic values for the organization (firm) is still unknown, and therefore, the aim of this paper is for analyzing its strategic values for gaining the organizational competitive advantage. However, in this paper, its strategic value analysis is viewed by how to assess (consider) its strategic benefits and also manage the challenges or risks of its implementation at the organization as an organizational product/service. Then the paper uses a research model for investigating the influences of both perceived risks and the organizational cultures to the usage of Green IT Application at the organization and also both the usage of Green IT Application at the organization and the threats-challenges of the organizational products/services to the competitive advantage of the organizational products/services. However, the paper uses the quantitative research method (collecting the information from the field respondents by using the research questionnaires) and then, the primary data is analyzed by both descriptive and inferential statistics. Also in this paper, SmartPLS is used for analyzing the primary data by the quantitative research method. Besides using the quantitative research method, the paper also uses the qualitative research method, such as interviewing the field respondent and/or directly field observation, for deeply confirming the quantitative research method’s analysis results at the certain domain, e.g. both organizational cultures and internal processes that support the usage of Green IT applications for the organizational product/service (E-Money in this paper case). However, the paper is still at an infant stage of in-progress research. Then the paper’s results may be used as a reference for the organization (firm or company) in developing the organizational business strategies, especially about the organizational product/service that relates to Green IT applications. Besides it, the paper may also be the future study, e.g. the influence of knowledge transfer about E-Money and/or other Green IT application-based products/services to the organizational service performance that relates to the product (service) in order to gain the competitive advantage.

Keywords: Green IT, competitive advantage, strategic value, organization (firm or company), organizational product (service)

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Authors: Zhang Lei, Zhan Haiyang, Gu Miao

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A universal software platform is developed for improving the defects in the practical one. This software platform has distinct advantages in modularization, information management, and the interfaces. Several technologies such as computer technology, virtualization technology, network technology, etc. are combined together in this software platform, and four working modes are introduced in this article including single mode, distributed mode, cloud mode, and the centralized mode. The application area of the software platform is extended through the switch between these working modes. The software platform can arrange the thermal vacuum test process automatically. This function can improve the reliability of thermal vacuum test.

Keywords: software platform, thermal vacuum test, control and measurement, work mode

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Authors: Sudeshna Mukherjee, Leena Fageria, R. Venkataramana Dilip, Rajdeep Chowdhury, Jitendra Panwar

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Metal nanoparticles in recent years have gained importance in cancer therapy due to their enhanced permeability retention effect. Among various nanomaterials, silver nanoparticles (AgNPs) have received considerable attention due to their unique properties like conductivity, chemical stability, relative lower toxicity and outstanding therapeutic potential, such as anti-inflammatory, antimicrobial and anti-cancerous activities. In this study, we took a greener approach to synthesize silver nanoparticle from fungus and analyze its effects on both epithelial and mesenchymal derived cancer cells. Much research has been done on nanoparticle-induced apoptosis, but little is known about its role in autophagy. In our study, the silver nanoparticles were seen to induce autophagy which was analyzed by studying the expression of several autophagy markers like, LC3B-II and ATG genes. Monodansylcadaverine (MDC) assay also revealed the induction of autophagy upon treatment with AgNPs. Inhibition of autophagy by chloroquine resulted in increased cell death suggesting autophagy as a survival strategy adopted by the cells. In parallel to autophagy induction, silver nanoparticles induced ROS accumulation. Interestingly, autophagy inhibition by chloroquine increased ROS level, resulting in enhanced cell death. We further analyzed MAPK signaling upon AgNP treatment. It was observed that along with autophagy, activation of JNK signaling served as pro-survival while ERK signaling served as a pro-death signal. Our results provide valuable insights into the role of autophagy upon AgNP exposure and provide cues to probabilistic strategies to effectively sensitize cancer cells.

Keywords: autophagy, JNK signalling, reactive oxygen species, silver nanoparticles

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Authors: Rock-Hyun Choi, Won-Seok Kang, Chang-Sik Son

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Physical activity is important for healthy living. Recently wearable devices which motivate physical activity are quickly developing, and become cheaper and more comfortable. In particular, fitness trackers provide a variety of information and need to provide well-analyzed, and user-friendly results. In this study, frequency analysis was performed to classify various data sets of Fitbit into simple activity status. The data from Fitbit cloud server consists of 263 subjects who were healthy factory and office workers in Korea from March 7th to April 30th, 2016. In the results, we found assumptions of activity state classification seem to be sufficient and reasonable.

Keywords: activity status, fitness tracker, heart rate, steps

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Authors: Lilian Noronha Nassif

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Cybercrime investigation demands an appropriated evidence collection mechanism. If the investigator does not acquire digital proofs in a forensic sound, some important information can be lost, and judges can discard case evidence because the acquisition was inadequate. The correct digital forensic seizing involves preparation of professionals from fields of law, police, and computer science. This paper presents important challenges faced during evidence collection in different perspectives of places. The crime scene can be virtual or real, and technical obstacles and privacy concerns must be considered. All pointed challenges here highlight the precautions to be taken in the digital evidence collection and the suggested procedures contribute to the best practices in the digital forensics field.

Keywords: digital evidence, digital forensics process and procedures, mobile forensics, cloud forensics

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Authors: Sanaa I. Abu Alasal, Madleen M. Esbeih, Eman R. Fayyad, Rami S. Gharaibeh, Mostafa Z. Ali, Ahmed A. Freewan, Monther M. Jamhawi

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This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: meshes, point clouds, surface reconstruction protocols, 3D reconstruction

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Authors: Shreya Bokare, Sanjay Pawar, Shika Nema

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Growth in cloud applications is generating the tremendous amount of data, building load on traditional storage management systems. Software Defined Storage (SDS) is a new storage management concept becoming popular to handle this large amount of data. CoprHD is one of the open source SDS controller, available for experimentation and development in the storage industry. In this paper, the storage management techniques provided by CoprHD to manage heterogeneous storage platforms are experimented and analyzed. Various storage management parameters such as time to provision, storage capacity measurement, and heterogeneity are experimentally evaluated along with the theoretical expression to prove the completeness of CoprHD controller for storage management.

Keywords: software defined storage, SDS, CoprHD, open source, SMI-S simulator, clarion, Symmetrix

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Authors: Francisco Liaño-Carrera, Jorge Enrique Baños-Illana, Arturo Gómez-Barrero, José Isaac Ramírez-Macías, Erik Omar Paredes-JuáRez, David Salas-Monreal, Mayra Lorena Riveron-Enzastiga

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Topographical changes in coastal areas are usually assessed with airborne LIDAR and conventional photogrammetry. In recent times Unmanned Aerial Vehicles (UAV) have been used several in photogrammetric applications including coastline evolution. However, its use goes further by using the points cloud associated to generate beach Digital Elevation Models (DEM). We present a methodology for monitoring coastal topographic changes along a 50 km coastline in Veracruz, Mexico using high-resolution images (less than 10 cm ground resolution) and dense points cloud captured with an UAV. This monitoring develops in the context of the port of Veracruz expansion project which construction began in 2015 and intends to characterize coast evolution and prevent and mitigate project impacts on coastal environments. The monitoring began with a historical coastline reconstruction since 1979 to 2015 using aerial photography and Landsat imagery. We could define some patterns: the northern part of the study area showed accretion while the southern part of the study area showed erosion. Since the study area is located off the port of Veracruz, a touristic and economical Mexican urban city, where coastal development structures have been built since 1979 in a continuous way, the local beaches of the touristic area are been refilled constantly. Those areas were not described as accretion since every month sand-filled trucks refill the sand beaches located in front of the hotel area. The construction of marinas and the comitial port of Veracruz, the old and the new expansion were made in the erosion part of the area. Northward from the City of Veracruz the beaches were described as accretion areas while southward from the city, the beaches were described as erosion areas. One of the problems is the expansion of the new development in the southern area of the city using the beach view as an incentive to buy front beach houses. We assessed coastal changes between seasons using high-resolution images and also points clouds during 2016 and preliminary results confirm that UAVs can be used in permanent coast monitoring programs with excellent performance and detail.

Keywords: digital elevation model, high-resolution images, topographic coast monitoring, unmanned aerial vehicle

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Authors: Do-Jin Jang, Sung-Ah Kim

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In designing a kinetic façade, it is hard for the designer to make digital models due to its complex geometry with motion. This paper aims to present a methodology of converting a point cloud of a physical model into a single digital model with a certain topology and motion. The method uses a Microsoft Kinect sensor, and color markers were defined and applied to three paper folding-inspired designs. Although the resulted digital model cannot represent the whole folding range of the physical model, the method supports the designer to conduct a performance-oriented design process with the rough physical model in the reduced folding range.

Keywords: design media, kinetic facades, tangible user interface, 3D scanning

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Authors: Kuladeep Kumar Sadevi

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The shift towards raising global urban population has intense implications on the sustainability of the urban livelihoods. Rapid urbanization has made governments, companies and civil societies recognize that they are barely equipped to deal with growing urban demands, especially water, waste and energy management. Effective management of land, water, energy and waste at a community level should be addressed well to attain greener cities. In pursuit of Green livelihoods; various norms, codes, and green rating programmes have been followed by stakeholders at various levels. While the sustainability is being adapted at smaller scale developments, greening the urban environment at community/city level is still finding its path to reality. This is due to lack of the sense of ownership in the citizens for their immediate neighborhoods and city as a whole. This phenomenon can be well connected to the theory of 'tragedy of commons' with respect to the community engagement to manage the common pool resources. The common pool resource management has been well addressed by Elinor Ostrom, who shared the Nobel Prize in Economics in 2009 for her lifetime of scholarly work investigating how communities succeed or fail at managing common pool (finite) resources. This paper examines the applicability of Elinor Ostrom's 8 Principles for Managing a Commons, to meet urban sustainability. The key objective of this paper is to come up with a model for effective urban common pool resource management, which ultimately leads to sustainability as a whole. The paper brings out a methodology to understand various parameters involved in urban sustainability, examine the synergies of all such parameters, and application of Ostrom’s principles to correlate these parameters in order to attain effective urban resource management.

Keywords: common pool resources, green cities, green communities, participatory management, sustainable development, urban resource management, urban sustainability

Procedia PDF Downloads 356

Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

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This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

Procedia PDF Downloads 203

Authors: Roman Bieda

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The General Data Protection Regulation (GDPR) will come into force on 25 May 2018 which will create a new legal framework for the protection of personal data in the European Union. Article 20 of GDPR introduces a right to data portability. This right allows for data subjects to receive the personal data which they have provided to a data controller, in a structured, commonly used and machine-readable format, and to transmit this data to another data controller. The right to data portability, by facilitating transferring personal data between IT environments (e.g.: applications), will also facilitate changing the provider of services (e.g. changing a bank or a cloud computing service provider). Therefore, it will contribute to the development of competition and the digital market. The aim of this paper is to discuss the right to data portability and its influence on the development of new digital services.

Keywords: data portability, digital market, GDPR, personal data

Procedia PDF Downloads 473

Authors: Deniz Yurtoğlu

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Aerosols directly affect the radiative balance of the earth by absorbing and/or scattering the sun rays reaching the atmosphere and indirectly affect the balance by acting as a nucleus in cloud formation. The composition, physical, and chemical properties of aerosols vary depending on their sources and the time spent in the atmosphere. The Eastern Mediterranean Basin has a high aerosol load that is formed from different sources; such as anthropogenic activities, desert dust outbreaks, and the spray of sea salt; and the area is subjected to atmospheric transport from other locations on the earth. This region, which includes the deserts of Africa, the Middle East, and the Mediterranean sea, is one of the most affected areas by climate change due to its location and the chemistry of the atmosphere. This study aims to investigate the spatiotemporal deviation of aerosol load in the Eastern Mediterranean Basin between the years 2018-2022 with the help of a new pioneer satellite of ESA (European Space Agency), Sentinel-5P. The TROPOMI (The TROPOspheric Monitoring Instrument) traveling on this low-Earth orbiting satellite is a UV (Ultraviolet)-sensing spectrometer with a resolution of 5.5 km x 3.5 km, which can make measurements even in a cloud-covered atmosphere. By using Absorbing Aerosol Index data produced by this spectrometer and special scripts written in Python language that transforms this data into images, it was seen that the majority of the aerosol load in the Eastern Mediterranean Basin is sourced from desert dust and anthropogenic activities. After retrieving the daily data, which was separated from the NaN values, seasonal analyses match with the normal aerosol variations expected, which are high in warm seasons and lower in cold seasons. Monthly analyses showed that in four years, there was an increase in the amount of Absorbing Aerosol Index in spring and winter by 92.27% (2019-2021) and 39.81% (2019-2022), respectively. On the other hand, in the summer and autumn seasons, a decrease has been observed by 20.99% (2018-2021) and 0.94% (2018-2021), respectively. The overall variation of the mean absorbing aerosol index from TROPOMI between April 2018 to April 2022 reflects a decrease of 115.87% by annual mean from 0.228 to -0.036. However, when the data is analyzed by the annual mean values of the years which have the data from January to December, meaning from 2019 to 2021, there was an increase of 57.82% increase (0.108-0.171). This result can be interpreted as the effect of climate change on the aerosol load and also, more specifically, the effect of forest fires that happened in the summer months of 2021.

Keywords: aerosols, eastern mediterranean basin, sentinel-5p, tropomi, aerosol index, remote sensing

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Authors: Hardeep

Abstract:

The aim of this research work to improve the solubility and bioavailability of Simvastatin using a self nanoemulsifying drug delivery system (SNEDDS). Self emulsifying property of various oils including essential oils was evaluated with suitable surfactants and co-surfactants. Validation of a method for accuracy, repeatability, Interday and intraday precision, ruggedness, and robustness were within acceptable limits. The liquid SNEDDS was prepared and optimized using a ternary phase diagram, thermodynamic, centrifugation and cloud point studies. The globule size of optimized formulations was less than 200 nm which could be an acceptable nanoemulsion size range. The mean droplet size, drug loading, PDI and zeta potential were found to be 141.0 nm, 92.22%, 0.23 and -10.13 mV and 153.5nm, 93.89 % ,0.41 and -11.7 mV and 164.26 nm, 95.26% , 0.41 and -10.66mV respectively.

Keywords: simvastatin, self nanoemulsifying drug delivery system, solubility, bioavailability

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

Procedia PDF Downloads 121