Search results for: Google Cloud Platform

Authors: U. Yerlikaya, R. T. Balkan

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In this research, a method is developed to obtain high-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-dimensional (D) workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. The number of dimensions of the configuration space comes from the degree of freedoms of the system of interest. The method can be applied in two ways. In the first way, the point clouds of all the bodies of the system and interaction of them are used. The second way is performed via using the clearance function of simulation software where the minimum distances between surfaces of bodies are simultaneously measured. A double-turret system is held in the scope of this study. The 4-D configuration space of a double-turret system is obtained in these two ways. As a result, the difference between these two methods is around 1%, depending on the density of the point cloud. The disparity between the two forms steadily decreases as the point cloud density increases. At the end of the study, in order to verify 4-D configuration space obtained, 4-D path planning problem was realized as 2-D + 2-D and a sample path planning is carried out with using A* algorithm. Then, the accuracy of the configuration space is proved using the obtained paths on the simulation model of the double-turret system.

Keywords: A* algorithm, autonomous turrets, high-dimensional C-space, manifold C-space, point clouds

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Authors: Sendy Ghirardi, Pau Rausell Köster

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The European Commission increasingly pushes cultural policies towards social outcomes and local and regional authorities also call for culture-driven strategies for local development and prosperity and therefore, the measurement of cultural participation becomes increasingly more significant for evidence-based policy-making processes. Cultural participation involves various kinds of social and economic spillovers that combine social and economic objectives of value creation, including social sustainability and respect for human values. Traditionally, from the economic perspective, cultural consumption is measured by the value of financial transactions in purchasing, subscribing to, or renting cultural equipment and content, addressing the market value of cultural products and services. The main sources of data are the household spending survey and merchandise trade survey, among others. However, what characterizes the cultural consumption is that it is linked with the hedonistic and affective dimension rather than the utilitarian one. In fact, nowadays, more and more attention is being paid to the social and psychological dimensions of culture. The aim of this work is to present a comprehensive approach to measure the impacts of cultural participation and cultural users’ behaviour, combining both socio-psychological and economic approaches. The model combines contingent evaluation techniques with the individual characteristic and perception analysis of the cultural experiences to evaluate the cognitive, aesthetic, emotive and social impacts of cultural participation. To investigate the comprehensive approach to measure the impact of the cultural events on individuals, the research has been designed on the basis of prior theoretical development. A deep literature methodology has been done to develop the theoretical model applied to the web platform to measure the impacts of cultural experience on individuals. The developed framework aims to become a democratic tool for evaluating the services that cultural or policy institutions can adopt through the use of an interacting platform that produces big data benefiting academia, cultural management and policies. The Au Culture is a prototype based on an application that can be used on mobile phones or any other digital platform. The development of the AU Culture Platform has been funded by the Valencian Innovation Agency (Government of the Region of Valencia) and it is part of the Horizon 2020 project MESOC.

Keywords: comprehensive approach, cultural participation, economic dimension, socio-psychological dimension

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Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

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Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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Authors: Audrey Hudson

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In 2020, educational field trips went virtual for all students. At the Art Gallery of Ontario (AGO) in Canada, our solution was to create a virtual school program that addressed three pillars of access—economic, geographic and cultural—with art at the center. Now, at the close of three years, we have reached 1.6 million students! Exponentially more than we have ever welcomed for onsite school visits. In 2022, we partnered with the Museum of Modern Art (MoMA), the Hong Kong University Museum and the National Gallery of Singapore, which has pushed the boundaries of art education into the expanse of the global community. Looking forward to our fourth year of the program, we are using the platform of technology to expand our program of art, access and learning to a global platform. In 2023/24, we intend to connect across more borders to expand the pedagogical benefits of art education for a global community. We invite you to listen to how you can join this journey.

Keywords: technology, museums, art education, pedagogy

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Authors: Arwa Alnowaiser, Hala Shoukri

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The ‘FreeAITherapist’ is an artificial intelligence application that uses the power of AI to offer advice and mental health counseling to its users through its chatbot services. The AI therapist is designed to understand users' issues, concerns, and problems and respond appropriately; it provides empathy and guidance and uses evidence-based therapeutic techniques. With its user-friendly platform, it ensures accessibility for individuals in need, regardless of their geographical location. This website was created in direct response to the growing demand for mental health support, aiming to provide a cost-effective and confidential solution. Through promising confidentiality, it considers user privacy and data security. The ‘FreeAITherapist’ strives to bridge the gap in mental health services, offering a reliable resource for individuals seeking guidance and counseling to improve their overall well-being.

Keywords: artificial intelligence, mental health, AI therapist, website, counseling

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Authors: Chia-Yu Yao

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This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: pulse-shaping filters, FIR filters, jittering, QAM

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Authors: Ridwan Dewayanto Rusli

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We show how prisoner's dilemma-type competition problems can be mitigated through rapid platform diversification and ecosystem expansion. We analyze a ride-hailing company in Southeast Asia, Gojek, whose network grew to more than 170 million users comprising consumers, partner drivers, merchants, and complementors within a few years and has already achieved higher contribution margins than ride-hailing peers Uber and Lyft. Its ecosystem integrates ride-hailing, food delivery and logistics, merchant solutions, e-commerce, marketplace and advertising, payments, and fintech offerings. The company continues growing its network of complementors and App developers, expanding content and gaining critical mass in consumer data analytics and advertising. We compare the company's growth and diversification trajectory with those of its main international rivals and peers. The company's rapid growth and future potential are analyzed using Cusumano's (2012) Staying Power and Six Principles, Hax and Wilde's (2003) and Hax's (2010) The Delta Model as well as Santos' (2016) home-market advantages frameworks. The recently announced multi-billion-dollar merger with one of Southeast Asia's largest e-commerce majors lends additional support to the above arguments.

Keywords: ride-hailing, prisoner's dilemma, platform and ecosystem strategy, digital applications, diversification, home market advantages, e-commerce

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Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu

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This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.

Keywords: distributed model, flexible manipulator, observer, robot control

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Authors: Marat Kozhomberdiev

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The research will investigate the modern corporate finance management technologies currently used in the era of digitalization of the global economy and the degree to which financial institutions are utilizing these new technologies in the field of corporate finance management in Kyrgyzstan. The main purpose of the research is to reveal the role of financial management technologies as joint service centers, intercompany banks, specialized payment centers in the third-world country. Particularly, the analysis of the implacability of automated corporate finance management systems such as enterprise resource planning system (ERP) and treasury management system (TMS) will be carried out. Moreover, the research will investigate the role of cloud accounting systems in corporate finance management in Kyrgyz banks and whether it has any impact on the field of improving corporate finance management. The study will utilize a data collection process via surveying 3 banks in Kyrgyzstan, namely Mol-Bulak, RSK, and KICB. The banks were chosen based on their ownerships, such as state banks, private banks with local authorized capital, and private bank with international capital. The regression analysis will be utilized to reveal the correlation between the ownership of the bank and the use of new financial management technologies. The research will provide policy recommendations to both private and state banks on developing strategies for switching and utilizing modern corporate finance management technologies in their daily operations.

Keywords: digital economy, corporate finance, digital environment, digital technologies, cloud technologies, financial management

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Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

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Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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Authors: Shayma Mohammed, Adel Trabelsi

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Radiopharmacy is the art of preparing high-quality, radioactive, medicinal products for use in diagnosis and therapy. Radiopharmaceuticals unlike normal medicines, this dual aspect (radioactive, medical) makes their management highly critical. One of the most convincing applications of modern technologies is the ability to delegate the execution of repetitive tasks to programming scripts. Automation has found its way to the most skilled jobs, to improve the company's overall performance by allowing human workers to focus on more important tasks than document filling. This project aims to contribute to implement a comprehensive system to insure rigorous management of radiopharmaceuticals through the use of a platform that links the Nuclear Medicine Service Management System to the Nuclear Radio-pharmacy Management System in accordance with the recommendations of World Health Organization (WHO) and International Atomic Energy Agency (IAEA). In this project we attempt to build a web application that targets radiopharmacies, the platform is built atop the inherently compatible web stack which allows it to work in virtually any environment. Different technologies are used in this project (PHP, Symfony, MySQL Workbench, Bootstrap, Angular 7, Visual Studio Code and TypeScript). The operating principle of the platform is mainly based on two parts: Radiopharmaceutical Backoffice for the Radiopharmacian, who is responsible for the realization of radiopharmaceutical preparations and their delivery and Medical Backoffice for the Doctor, who holds the authorization for the possession and use of radionuclides and he/she is responsible for ordering radioactive products. The application consists of sven modules: Production, Quality Control/Quality Assurance, Release, General Management, References, Transport and Stock Management. It allows 8 classes of users: The Production Manager (PM), Quality Control Manager (QCM), Stock Manager (SM), General Manager (GM), Client (Doctor), Parking and Transport Manager (PTM), Qualified Person (QP) and Technical and Production Staff. Digital platform bringing together all players involved in the use of radiopharmaceuticals and integrating the stages of preparation, production and distribution, Web technologies, in particular, promise to offer all the benefits of automation while requiring no more than a web browser to act as a user client, which is a strength because the web stack is by nature multi-platform. This platform will provide a traceability system for radiopharmaceuticals products to ensure the safety and radioprotection of actors and of patients. The new integrated platform is an alternative to write all the boilerplate paperwork manually, which is a tedious and error-prone task. It would minimize manual human manipulation, which has proven to be the main source of error in nuclear medicine. A codified electronic transfer of information from radiopharmaceutical preparation to delivery will further reduce the risk of maladministration.

Keywords: automated system, management, radiopharmacy, technical papers

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Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

Procedia PDF Downloads 357

Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana, Andres F. Ruiz-Olaya, Juan C. Alvarez

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Motion capture (MC) is the construction of a precise and accurate digital representation of a real motion. Systems have been used in the last years in a wide range of applications, from films special effects and animation, interactive entertainment, medicine, to high competitive sport where a maximum performance and low injury risk during training and competition is seeking. This paper presents an inertial and magnetic sensor based technological platform, intended for particular amplitude monitoring and telerehabilitation processes considering an efficient cost/technical considerations compromise. Our platform particularities offer high social impact possibilities by making telerehabilitation accessible to large population sectors in marginal socio-economic sector, especially in underdeveloped countries that in opposition to developed countries specialist are scarce, and high technology is not available or inexistent. This platform integrates high-resolution low-cost inertial and magnetic sensors with adequate user interfaces and communication protocols to perform a web or other communication networks available diagnosis service. The amplitude information is generated by sensors then transferred to a computing device with adequate interfaces to make it accessible to inexperienced personnel, providing a high social value. Amplitude measurements of the platform virtual system presented a good fit to its respective reference system. Analyzing the robotic arm results (estimation error RMSE 1=2.12° and estimation error RMSE 2=2.28°), it can be observed that during arm motion in any sense, the estimation error is negligible; in fact, error appears only during sense inversion what can easily be explained by the nature of inertial sensors and its relation to acceleration. Inertial sensors present a time constant delay which acts as a first order filter attenuating signals at large acceleration values as is the case for a change of sense in motion. It can be seen a damped response of platform virtual in other images where error analysis show that at maximum amplitude an underestimation of amplitude is present whereas at minimum amplitude estimations an overestimation of amplitude is observed. This work presents and describes the platform virtual as a motion capture system suitable for telerehabilitation with the cost - quality and precision - accessibility relations optimized. These particular characteristics achieved by efficiently using the state of the art of accessible generic technology in sensors and hardware, and adequate software for capture, transmission analysis and visualization, provides the capacity to offer good telerehabilitation services, reaching large more or less marginal populations where technologies and specialists are not available but accessible with basic communication networks.

Keywords: inertial sensors, joint amplitude measurement, MEMS, telerehabilitation

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Authors: Cagri Baris Kasap

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In this study, how interface designers can be viewed as producers of culture in the current era will be interrogated from a critical theory perspective. Walter Benjamin was a German Jewish literary critical theorist who, during 1930s, was engaged in opposing and criticizing the Nazi use of art and media. ‘The Author as Producer’ is an essay that Benjamin has read at the Communist Institute for the Study of Fascism in Paris. In this article, Benjamin relates directly to the dialectics between base and superstructure and argues that authors, normally placed within the superstructure should consider how writing and publishing is production and directly related to the base. Through it, he discusses what it could mean to see author as producer of his own text, as a producer of writing, understood as an ideological construct that rests on the apparatus of production and distribution. So Benjamin concludes that the author must write in ways that relate to the conditions of production, he must do so in order to prepare his readers to become writers and even make this possible for them by engineering an ‘improved apparatus’ and must work toward turning consumers to producers and collaborators. In today’s world, it has become a leading business model within Web 2.0 services of multinational Internet technologies and culture industries like Amazon, Apple and Google, to transform readers, spectators, consumers or users into collaborators and co-producers through platforms such as Facebook, YouTube and Amazon’s CreateSpace Kindle Direct Publishing print-on-demand, e-book and publishing platforms. However, the way this transformation happens is tightly controlled and monitored by combinations of software and hardware. In these global-market monopolies, it has become increasingly difficult to get insight into how one’s writing and collaboration is used, captured, and capitalized as a user of Facebook or Google. In the lens of this study, it could be argued that this criticism could very well be considered by digital producers or even by the mass of collaborators in contemporary social networking software. How do software and design incorporate users and their collaboration? Are they truly empowered, are they put in a position where they are able to understand the apparatus and how their collaboration is part of it? Or has the apparatus become a means against the producers? Thus, when using corporate systems like Google and Facebook, iPhone and Kindle without any control over the means of production, which is closed off by opaque interfaces and licenses that limit our rights of use and ownership, we are already the collaborators that Benjamin calls for. For example, the iPhone and the Kindle combine a specific use of technology to distribute the relations between the ‘authors’ and the ‘prodUsers’ in ways that secure their monopolistic business models by limiting the potential of the technology.

Keywords: interface designer, cultural producer, Walter Benjamin, materialist aesthetics, dialectical thinking

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Authors: Ching-Ju Hsiao, Mao-Chen Huang, Pei-Fan Chen, Ruo-Yun Chung, Jiun-Hua Chou, Chih-Hui Yang, Keng-Shiang Huang, Jei-Fu Shaw

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Chlorophyll has many benefits for human body. It is known to improve the health of the circulatory, digestive, immune and detoxification systems of the body. However, Chl can’t be preserved at the environment of high temperature and light exposure for a long time due to it is chemical structure is easily degradable. This characteristic causes that human body is difficult to absorb Chl effective components. In order to solve this problem, we utilize polycaprolactone (PCL) polymer encapsulation technology to increase the stability of Chl. In particular, we also established a microfluidic platform provide the control of composite beads diameter. The new composite beads is potential to be a health food. Result show that Chl effective components via the microfludic platform can be encapsulated effectively and still preserve its effective components.

Keywords: chlorophyll, PCL, PVA, microfluidic

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Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: K. Chethana, A. S. Guru Prasad, S. N. Omkar, B. Vadiraj, S. Asokan

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This paper describes an ab-initio design, development and calibration results of an Optical Sensor Ground Reaction Force Measurement Platform (OSGRFP) for gait and geriatric studies. The developed system employs an array of FBG sensors to measure the respective ground reaction forces from all three axes (X, Y and Z), which are perpendicular to each other. The novelty of this work is two folded. One is in its uniqueness to resolve the tri axial resultant forces during the stance in to the respective pure axis loads and the other is the applicability of inherently advantageous FBG sensors which are most suitable for biomechanical instrumentation. To validate the response of the FBG sensors installed in OSGRFP and to measure the cross sensitivity of the force applied in other directions, load sensors with indicators are used. Further in this work, relevant mathematical formulations are presented for extracting respective ground reaction forces from wavelength shifts/strain of FBG sensors on the OSGRFP. The result of this device has implications in understanding the foot function, identifying issues in gait cycle and measuring discrepancies between left and right foot. The device also provides a method to quantify and compare relative postural stability of different subjects under test, which has implications in post surgical rehabilitation, geriatrics and optimizing training protocols for sports personnel.

Keywords: balance and stability, gait analysis, FBG applications, optical sensor ground reaction force platform

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Hassan Gomar, Shahin Bagheri, Nader Keyvan, Mozhdeh Shirinzadeh

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Air-Cooled Condenser (ACC) platform structures are the most complicated and principal structures in power plants and other industrial parts which need to condense the low-pressure steam in the cycle. Providing large spans for this structure has great merit as there would be more space for other subordinate buildings and pertinent equipment. Moreover, applying methods to reduce the overall cost of construction while maintaining its strength against severe seismic loading is of high significance. Tabular spatial structures and composite frames have been widely used in recent years to satisfy the need for higher strength at a reasonable price. In this research program, three different structural systems have been regarded for ACC steel platform using Special Concentrate Braced Frames (SCBF), which is the most common system (first scheme), modular spatial frames (second scheme) and finally, a modified method applying Concrete Filled Steel Tabular (CFST) columns (third scheme). The finite element method using Sap2000 and Etabs software was conducted to investigate the behavior of the structures and make a precise comparison between the models. According to the results, the total weight of the steel structure in the second scheme decreases by 13% compared to the first scheme and applying CFST columns in the third scheme causes a 3% reduction in the total weight of the structure in comparison with the second scheme while all the lateral displacements and P-M interaction ratios are in the admissible limit.

Keywords: ACC, SCBF frames, spatial structures, CFST frames

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Authors: Saman Mostafazadeh-Fard, Zohrab Samani, Kenneth Suazo

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Agricultural ditch liners are used to prevent soil erosion and reduce seepage losses. This paper introduced an approach to validate a computational fluid dynamics (CFD) platform FLOW-3D code and its use to design a flow-regulating corrugated agricultural ditch liner system (Smart Ditch (SM)). Hydrodynamic and sediment transport analyses were performed on the proposed liner flow using the CFD platform FLOW-3D code. The code's hydrodynamic and scour and sediment transport models were calibrated and validated using lab data with an accuracy of 94 % and 95%, respectively. The code was then used to measure hydrodynamic parameters of sublayer turbulent intensity, kinetic energy, dissipation, and packed sediment mass normalized with respect to sublayer flow velocity. Sublayer turbulent intensity, kinetic energy, and dissipation in the SM flow were significantly higher than CR flow. An alternative corrugated liner was also designed, and sediment transport was measured and compared to SM and CR flows. Normalized packed sediment mass with respect to average sublayer flow velocity was 27.8 % lower in alternative flow compared to SM flow. CFD platform FLOW-3D code could effectively be used to design corrugated ditch liner systems and perform hydrodynamic and sediment transport analysis under various corrugation designs.

Keywords: CFD, hydrodynamic, sediment transport, ditch, liner design

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Authors: Martin Pumera

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Graphene materials are being widely used in electrochemistry due to their versatility and excellent properties as platforms for biosensing. Here we present current trends in the electrochemical biosensing of pesticides and other toxic compounds. We explore two fundamentally different designs, (i) using graphene and other 2-D nanomaterials as an electrochemical platform and (ii) using these nanomaterials in the laboratory on chip design, together with paramagnetic beads. More specifically: (i) We explore graphene as transducer platform with very good conductivity, large surface area, and fast heterogeneous electron transfer for the biosensing. We will present the comparison of these materials and of the immobilization techniques. (ii) We present use of the graphene in the laboratory on chip systems. Laboratory on the chip had a huge advantage due to small footprint, fast analysis times and sample handling. We will show the application of these systems for pesticide detection and detection of other toxic compounds.

Keywords: graphene, 2D nanomaterials, biosensing, chip design

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

Procedia PDF Downloads 168

Authors: Alex Maina, Mwenda Makathimo, Adwek George, Charles Opiyo

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This research entails the simulation of three possible power scenarios for Kenya from 2015 to 2035 using the Low Emissions Analysis Platform (LEAP). These scenarios represent the unfolding future electricity generation that will fully satisfy the demand while considering the following: energy security, power generation cost and impacts on the environment. These scenarios are Reference Scenario (RS), Nuclear Scenario (NS) and More Renewable Scenario (MRS). The findings obtained reveals that the most sustainable scenario while comparing the costs was found to be the coal scenario with a Net Present Value (NPV) of $30,052.67 million though it has the highest Green House Gases (GHGs) emissions. However, the More Renewable Scenario (MRS) had the least GHGs emissions but was found to be a most expensive scenario to implement with an NPV of $30,733.07 million.

Keywords: energy security, Kenya, low emissions analysis platform, net-present value, greenhouse gases

Procedia PDF Downloads 80

Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

Procedia PDF Downloads 169

Authors: Chandan Kundu, Sankar Bhattacharya

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A significant disadvantage of fossil fuel energy production is the considerable amount of carbon dioxide (CO₂) released, which is one of the contributors to climate change. Apart from environmental concerns, changing fossil fuel prices have pushed society gradually towards renewable energy sources in recent years. Biomass is a plentiful and renewable resource and a source of carbon. Recent years have seen increased research interest in generating fuels and chemicals from biomass. Unlike fossil-based resources, biomass is composed of lignocellulosic material, which does not contribute to the increase in atmospheric CO₂ over a longer term. These considerations contribute to the current move of the chemical industry from non-renewable feedstock to renewable biomass. This presentation focuses on generating bio-oil and two major platform chemicals that can potentially improve the environment. Thermochemical processes such as pyrolysis are considered viable methods for producing bio-oil and biomass-based platform chemicals. Fluidized bed reactors, on the other hand, are known to boost bio-oil yields during pyrolysis due to their superior mixing and heat transfer features, as well as their scalability. This review and the associated experimental work are focused on the thermochemical conversion of biomass to bio-oil and two high-value platform chemicals, Levoglucosenone (LGO) and 5-Chloromethyl furfural (5-CMF), in a fluidized bed reactor. These two active molecules with distinct features can potentially be useful monomers in the chemical and pharmaceutical industries since they are well adapted to the manufacture of biologically active products. This process took several meticulous steps. To begin, the biomass was delignified using a peracetic acid pretreatment to remove lignin. Because of its complicated structure, biomass must be pretreated to remove the lignin, increasing access to the carbohydrate components and converting them to platform chemicals. The biomass was then characterized by Thermogravimetric analysis, Synchrotron-based THz spectroscopy, and in-situ DRIFTS in the laboratory. Based on the results, a continuous-feeding fluidized bed reactor system was constructed to generate platform chemicals from pretreated biomass using hydrogen chloride acid-gas as a catalyst. The procedure also yields biochar, which has a number of potential applications, including soil remediation, wastewater treatment, electrode production, and energy resource utilization. Consequently, this research also includes a preliminary experimental evaluation of the biochar's prospective applications. The biochar obtained was evaluated for its CO₂ and steam reactivity. The outline of the presentation will comprise the following: Biomass pretreatment for effective delignification Mechanistic study of the thermal and thermochemical conversion of biomass Thermochemical conversion of untreated and pretreated biomass in the presence of an acid catalyst to produce LGO and CMF A thermo-catalytic process for the production of LGO and 5-CMF in a continuously-fed fluidized bed reactor and efficient separation of chemicals Use of biochar generated from the platform chemicals production through gasification

Keywords: biomass, pretreatment, pyrolysis, levoglucosenone

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Authors: Remus Pravalie, Georgeta Bandoc

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Forests are crucial for humanity and biodiversity, through the various ecosystem services and functions they provide all over the world. Forest ecosystems are vital in Romania as well, through their various benefits, known as provisioning (food, wood, or fresh water), regulating (water purification, soil protection, carbon sequestration or control of climate change, floods, and other hazards), cultural (aesthetic, spiritual, inspirational, recreational or educational benefits) and supporting (primary production, nutrient cycling, and soil formation processes, with direct or indirect importance for human well-being) ecosystem services. These ecological benefits are of great importance in Romania, especially given the fact that forests cover extensive areas countrywide, i.e. ~6.5 million ha or ~27.5% of the national territory. However, the diversity and functionality of these ecosystem services fundamentally depend on certain key attributes of forests, such as biomass, which has so far not been studied nationally in terms of potential changes due to climate change and other driving forces. This study investigates, for the first time, changes in forest biomass in Romania in recent decades, based on a high volume of satellite data (Landsat images at high spatial resolutions), downloaded from the Google Earth Engine platform and processed (using specialized software and methods) across Romanian forestland boundaries from 1987 to 2018. A complex climate database was also investigated across Romanian forests over the same 32-year period, in order to detect potential similarities and statistical relationships between the dynamics of biomass and climate data. The results obtained indicated considerable changes in forest biomass in Romania in recent decades, largely triggered by the climate change that affected the country after 1987. Findings on the complex pattern of recent forest changes in Romania, which will be presented in detail in this study, can be useful to national policymakers in the fields of forestry, climate, and sustainable development.

Keywords: forests, biomass, climate change, trends, romania

Procedia PDF Downloads 144

Authors: Jeong Ju Kim, Hee Yoon Chung, Dong Ho Rhee, Hyung Hee Cho

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There is a gap at combustor-turbine interface where leakage flow comes out to prevent hot gas ingestion into the gas turbine nozzle platform. The leakage flow protects the nozzle endwall surface from the hot gas coming from combustor exit. For controlling flow’s stream, the gap’s geometry is transformed by changing fillet radius size. During the operation, step configuration is occurred that was unintended between combustor-turbine platform interface caused by thermal expansion or mismatched assembly. In this study, CFD simulations were performed to investigate the effect of the fillet and step on heat transfer and film cooling effectiveness on the nozzle platform. The Reynolds-averaged Navier-stokes equation was solved with turbulence model, SST k-omega. With the fillet configuration, predicted film cooling effectiveness results indicated that fillet radius size influences to enhance film cooling effectiveness. Predicted film cooling effectiveness results at forward facing step configuration indicated that step height influences to enhance film cooling effectiveness. We suggested that designer change a combustor-turbine interface configuration which was varied by fillet radius size near endwall gap when there was a step at combustor-turbine interface. Gap shape was modified by increasing fillet radius size near nozzle endwall. Also, fillet radius and step height were interacted with the film cooling effectiveness and heat transfer on endwall surface.

Keywords: gas turbine, film cooling effectiveness, endwall, fillet

Procedia PDF Downloads 353

Authors: Shui Lien Chen, Yi-Fen Tsai, Jim Shih-Chiao Chin

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—In this study, using Chunghwa Telecom as a case. The company accounted for the highest proportion of the telecommunications company in Taiwan. First, this paper would like to understand the effect of convenience performance on perceived ease of use and perceived usefulness. Further, the perceived ease of use and perceived usefulness of Technology Acceptance Model (TAM) are adopted as the factors on the company's brand perception. Afterward, the brand perception influence on customer satisfaction, and finally whether producing a good reputation and recommendation are tested. The study participants are people who have used electronic platform service of Chunghwa Telecom. A total of 478 valid questionnaires were used and AMOS 20.0 statistical software programs were adopted to analyze.

Keywords: technology acceptance model, brand association, brand awareness, brand attachment, customer satisfaction, word-of-mouth (WOM)

Procedia PDF Downloads 268