Search results for: giftedness cloud model

Authors: Jyoti Sharma

Abstract:

Although notion of giftedness is a reality, yet it swings along the pendulum of equality and excellence. At times, nurturance of gifted abilities becomes a struggle of better catchment of resources and facilities. Those from affluent setup are blessed with better support system whereas gifted children from disadvantaged group suffer from submissive upbringing. In developing countries like India, with diverse demographic profiles, socio-cultural diversity and economic disparity, the very concept of equality in education face severe challenge. The present paper presents the dichotomy of ideology of equality and excellence in education practices. It highlights the need of wider vision, better policy making and decentralized implementation services to allow gifted children to enjoy what they are; dream what they can be; and promote what they will be.

Keywords: gifted, disadvantaged, education safety net, India

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Authors: S. Bae, J. Shin, S. Lee

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As the development of smart devices such as Smart TV, Smartphone, Tablet PC, Laptop, the interest in N-Screen Services that can be cross-linked with heterogeneous devices is increasing. N-Screen means User-centric services that can share and constantly watch multimedia contents anytime and anywhere. However, the existing N-Screen system has the limitation that N-Screen system has to implement the application for each platform and device to provide multimedia service. To overcome this limitation, Multimedia N-Screen Service System is proposed through the web, and it is independent of different environments. The combination of Web and cloud computing technologies from this study results in increasing efficiency and reduction in costs.

Keywords: N-screen, web, cloud, multimedia

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Authors: Koyangbo Guere Monguia Michel Alex Emmanuel

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In e-government and especially recruitment, many researches have been conducted to build a trustworthy and reliable online or application system capable to process users or job applicant files. In this research (Government Recruitment Agency), cloud computing, identity management and public key encryption have been used to management domains, access control authorization mechanism and to secure data exchange between entities for reliable procedure of processing files.

Keywords: cloud computing network, identity management systems, public key encryption, access control and authorization

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Authors: Daniel Gonzales, Zev Winkelman, Trung Tran, Ricardo Sanchez, Dulani Woods, John Hollywood

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We have developed a distributed computing capability, Digital Forensics Compute Cluster (DFORC2) to speed up the ingestion and processing of digital evidence that is resident on computer hard drives. DFORC2 parallelizes evidence ingestion and file processing steps. It can be run on a standalone computer cluster or in the Amazon Web Services (AWS) cloud. When running in a virtualized computing environment, its cluster resources can be dynamically scaled up or down using Kubernetes. DFORC2 is an open source project that uses Autopsy, Apache Spark and Kafka, and other open source software packages. It extends the proven open source digital forensics capabilities of Autopsy to compute clusters and cloud architectures, so digital forensics tasks can be accomplished efficiently by a scalable array of cluster compute nodes. In this paper, we describe DFORC2 and compare it with a standalone version of Autopsy when both are used to process evidence from hard drives of different sizes.

Keywords: digital forensics, cloud computing, cyber security, spark, Kubernetes, Kafka

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Authors: Joel Vilca Tarazona, Igor Aguilar-Alonso

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The problem of this research related to business intelligence is the lack of a tool that supports automated and efficient financial analysis for decision-making and allows an evaluation of the financial statements, which is why the availability of the information is difficult. Relevant information to managers and users as an instrument in decision making financial, and administrative. For them, a business intelligence solution is proposed that will reduce information access time, personnel costs, and process automation, proposing a 4-layer architecture based on what was reviewed by the research methodology.

Keywords: decision making, business intelligence, Google Cloud, Microsoft Power BI

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Authors: Md Habibul Ansary, Chandan Garai, Ranjan Dasgupta

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Utilization of resources is always a great challenge for any allocation problem, particularly when resource availability is dynamic in nature. In this work VM allocation mechanism has been augmented by providing resources in a combined manner. This approach has some inherent advantages in terms of reduction of wait state for the pending jobs of some users and better utilization of unused resources from the service providers’ point of view. Moreover the algorithm takes care of released resources from the finished jobs as soon as those become available. The proposed algorithm has been explained by suitable example to make the work complete.

Keywords: Bid ratio, cloud service, virtualization, VM allocation problem

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Authors: Chingwen Yeh, Yu Ru Chen

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This paper aims to explore the growth and development of children in the creative dance class of Cloud Gate Dance School in Taichung Taiwan. Professor Chingwen Yeh’s qualitative research method was applied in this study. First of all, application of Dalcroze Eurhythmic teaching materials such as music, teaching aids, speaking language through classroom situation was collected and exam. Second, the in-class observation on the participation of the young children's learning situation was recorded both by words and on video screen as the research data. Finally, data analysis was categorized into the following aspects: children's body movement coordination, children’s mind concentration and imagination and children’s verbal expression. Through the in-depth interviews with the in-class teachers, parents of participating children and other in class observers were conducted from time to time; this research found the children's body rhythm, language skills, and social learning growth were improved in certain degree through the creative dance training. These authors hope the study can contribute as the further research reference on the related topic.

Keywords: Cloud Gate Dance School, creative dance, Dalcroze, Eurhythmic

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Authors: Ivan Stanev, Maria Koleva

Abstract:

Automated software development issues are addressed in this paper. Layers and packages of a Common Platform for Automated Programming (CPAP) are defined based on Service Oriented Architecture, Cloud computing, Knowledge based automated software engineering (KBASE) and Method of automated programming. Tools of seven leading companies (AWS of Amazon, Azure of Microsoft, App Engine of Google, vCloud of VMWare, Bluemix of IBM, Helion of HP, OCPaaS of Oracle) are analyzed in the context of CPAP. Based on the results of the analysis CPAP requirements are formulated

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

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Authors: Sai Shruthi Sridhar, A. Madhumidha, Kreethika Guru, Priyanka Sekar, Ananthi Malayappan

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Numerous changes in technology and its recent development are structuring long withstanding effect to our world, one among them is the emergence of “Internet of Things” (IoT). Similar to Technology world, one industry stands out in everyday life–healthcare. Attention to “quality of health care” is an increasingly important issue in a global economy and for every individual. As per WHO (World Health Organization) it is estimated to be less than 50% adhere to the medication provided and only about 20% get their medicine on time. Medication adherence is one of the top problems in healthcare which is fixable by use of technology. In recent past, there were minor provisions for elderly and specially-skilled to get motivated and to adhere medicines prescribed. This paper proposes a novel solution that uses IOT based RFID Medication Reminder Solution to provide personal health care services. This employs real time tracking which offer quick counter measures. The proposed solution builds on the recent digital advances in sensor technologies, smart phones and cloud services. This novel solution is easily adoptable and can benefit millions of people with a direct impact on the nation’s health care expenditure with innovative scenarios and pervasive connectivity.

Keywords: cloud services, IoT, RFID, sensors

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Authors: Kais Manai

Abstract:

The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Kirubasankar, Sanjeevkumar, Aravindh Nagappan

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This paper addresses a system for monitoring patients using biomedical sensors and displaying it in a remote place. The main challenges in present health monitoring devices are lack of remote monitoring and logging for future evaluation. Typical instruments used for health parameter measurement provide basic information regarding health status. This paper identifies a set of design principles to address these challenges. This system includes continuous measurement of health parameters such as Heart rate, electrocardiogram, SpO2 level and Body temperature. The accumulated sensor data is relayed to a processing device using a transceiver and viewed by the implementation of cloud services.

Keywords: bio-medical sensors, monitoring, logging, cloud service

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: Henrique Fernandes, Sofia Catalucci, Richard Leach, Kapil Sugand

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Background: Holograms are 3D images formed by the interference of light beams from a laser or other coherent light source. Pepper’s ghost is a form of hologram conceptualised in the 18th century. This Holographic visualisation with metrology measuring techniques by displaying measurements taken in real-time in holographic form can assist in research and education. New structural designs such as the Plexiglass Stand and the Hologram Box can optimise the holographic experience. Method: The equipment used included: (i) Zeiss’s ATOS Core 300 optical coordinate measuring instrument that scanned real-world objects; (ii) Cloud Compare, open-source software used for point cloud processing; and (iii) Hologram Box, designed and manufactured during this research to provide the blackout environment needed to display 3D point clouds in real-time measurements in holographic format, in addition to a portability aspect to holograms. The equipment was tailored to realise the goal of displaying measurements in an innovative technique and to improve on conventional methods. Three test scans were completed before doing a holographic conversion. Results: The outcome was a precise recreation of the original object in the holographic form presented with dense point clouds and surface density features in a colour map. Conclusion: This work establishes a way to visualise data in a point cloud system. To our understanding, this is a work that has never been attempted. This achievement provides an advancement in holographic visualisation. The Hologram Box could be used as a feedback tool for measurement quality control and verification in future smart factories.

Keywords: holography, 3D scans, hologram box, metrology, point cloud

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Authors: Ivan Stanev, Maria Koleva

Abstract:

A common platform for automated programming (CPAP) is defined in details. Two versions of CPAP are described: Cloud-based (including the set of components for classic programming, and the set of components for combined programming) and KBASE based (including the set of components for automated programming, and the set of components for ontology programming). Four KBASE products (module for automated programming of robots, intelligent product manual, intelligent document display, and intelligent form generator) are analyzed and CPAP contributions to automated programming are presented.

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

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Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

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Authors: Mojtaba Valinejadshoubi, Azin Shakibabarough, Ashutosh Bagchi

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Facilities such as residential buildings, office buildings, and hospitals house large density of occupants. Therefore, a low-cost facility management program (FMP) should be used to provide a satisfactory built environment for these occupants. Facility management (FM) has been recently used in building projects as a critical task. It has been effective in reducing operation and maintenance cost of these facilities. Issues of information integration and visualization capabilities are critical for reducing the complexity and cost of FM. Building information modeling (BIM) can be used as a strong visual modeling tool and database in FM. The main objective of this study is to examine the applicability of BIM in the FM process during a building’s operational phase. For this purpose, a seven-storey office building is modeled Autodesk Revit software. Authors integrated the cloud-based environment using a visual programming tool, Dynamo, for the purpose of having a real-time cloud-based communication between the facility managers and the participants involved in the project. An appropriate and effective integrated data source and visual model such as BIM can reduce a building’s operational and maintenance costs by managing the building life cycle properly.

Keywords: building information modeling, facility management, operational phase, building life cycle

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Authors: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

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In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

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Authors: Chao Wang, Zuxue Xia, Wenhai Xia, Rui Wang, Jiayuan Hu, Rui Cheng

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Aiming at the application of indoor personnel positioning under smog conditions, this paper proposes a 3D positioning method based on the IWR1443 millimeter wave radar sensor. The problem that millimeter-wave radar cannot effectively form contours in 3D point cloud imaging is solved. The results show that the method can effectively achieve indoor positioning and scene construction, and the maximum positioning error of the system is 0.130m.

Keywords: indoor positioning, millimeter wave radar, IWR1443 sensor, point cloud imaging

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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Knowledge management is essential ingredient of successful coordination in globally distributed software engineering. Various frameworks, KMSs, and tools have been proposed to foster coordination and communication between virtual teams but practical implementation of these solutions has not been found. Organizations have to face challenges to implement knowledge management system. For this purpose at first, a literature review is arranged to investigate about challenges that restrict organizations to implement KMS and then by taking in account these challenges a problem of need of integrated solution in the form of standardized KMS that can easily store tacit and explicit knowledge, has traced down to facilitate coordination and collaboration among virtual teams. Literature review has been already shown that knowledge is a complex perception with profound meanings, and one of the most important resources that contributes to the competitive advantage of an organization. In order to meet the different challenges caused by not properly managing knowledge related to projects among virtual teams in GSE, we suggest making use of the cloud computing model. In this research a distributed architecture to support KM storage is proposed called conceptual framework of KM as a service in cloud. Framework presented is enhanced and conceptual framework of KM is embedded into that framework to store projects related knowledge for future use.

Keywords: management, Globsl software development, global software engineering

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Authors: Wasmi Woishi

Abstract:

Smart card technology is a secure and safe technology that is expanding its capabilities day by day in terms of holding important information without alteration. It is readily available, and its ease of portability makes it more efficient in terms of its usage. The smart card is in use by many industries such as financial, insurance, governmental industries, personal identification, to name a few. Smart card technology is popular for its wide familiarity, adaptability, accessibility, benefits, and portability. This research aims to find out the perception toward the application of a cloud-based healthcare system through a smart card in KSA. The research has compiled the countries using a smart card or smart healthcare card and indicated the potential benefits of implementing smart healthcare cards. 120 participants from Riyadh city were surveyed by the means of a closed-ended questionnaire. Data were analyzed through SPSS. This research extends the research body in the healthcare system. Empirical evidence regarding smart healthcare cards is scarce and hence undertaken in this study. The study provides a useful insight into collecting, storing, analyzing, manipulating, and accessibility of medical information regarding smart healthcare cards. Research findings can help achieve KSA's Vision 2030 goals in terms of the digitalization of healthcare systems in improving its efficiency and effectiveness in storing and accessing healthcare data.

Keywords: smart card technology, healthcare using smart cards, smart healthcare cards, KSA healthcare information system, cloud-based healthcare cards

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Authors: Milind Chaudhari, Suhail Balasinor

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Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

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Authors: Adeniyi Onasanya, Maher Elshakankiri

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In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.

Keywords: IoT, smart health care system, business analytics, (wireless) sensor network, cancer care services, cloud services

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Authors: Fabiano Amorim Vaz, Camila Gonzaga de Araujo

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With the growing number of personal devices such as smartphones, tablets, smart watches, among others, in addition to recent devices designed for IoT, it is observed that residential environment has potential to generate important information about our daily lives. Therefore, this work is focused on showing and evaluating a system that integrates all these technologies considering the context of a smart house. To achieve this, we define an architecture capable of supporting the amount of data generated and consumed at a residence and, mainly, the variety of this data presents. We organize it in a particular cloud containing information about robots, recreational vehicles, weather, in addition to data from the house, such as lighting, energy, security, among others. The proposed architecture can be extrapolated to various scenarios and applications. Through the core of this work, we can define new functionality for residences integrating them with more resources.

Keywords: cloud computing, IoT, robotics, smart house

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Authors: Nay Myo Sandar

Abstract:

With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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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: Nwadike Emmanuel Chinagoron, Achebe Chukwunonso, Ezeliora Chukwuemeka Daniel, Azaka Onyemazuwa Andrew

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In this research work, the process of biodiesel production in a pilot plant was studied using cow tallow as raw material, methanol as the solvent and potassium hydroxide as catalysts. The biodiesel quality was determined by characterization. The tallow used in the production had a molecular weight of 860g. Its oil had a density value of 0.8g/ml, iodine value of 63.45, viscosity at 300C was 9.83pas, acid value was 1.96, free fatty acid (FFA) of 0.98%, saponification value of 82.75mleq/kg, specific gravity of 0.898, flash point of 1100C, cloud point of 950C and Calorific value also called Higher Heating Value (HHV) of 38.365MJ/Kg. The produced biodiesel had a density of 0.82g/ml, iodine value of 126.9, viscosity of 4.32pas at 300C, acid value of 0.561, FFA of 0.2805%, saponification value of 137.45 mleq/kg.Flash point, cloud point and centane number of the biodiesel produced are 1390C, 980C and 57.5 respectively, with fat content, protein content, ash content, moisture content, fiber content and carbohydrate content values of 10%, 2.8%, 5%, 5%, 20%, and 37.2% respectively. The biodiesel higher heating values (calorific values) when estimated from viscosity, density and flash points were 41.4MJ/Kg, 63.8MJ/Kg, and 34.6MJ/Kg respectively. The biodiesel was blended with conventional diesel. The blend B-10 had values of 1320C and 960C for flash and cloud points, with Calorific value (or HHV) of 34.6 MJ/Kg (when estimated from its Flash point) and fat content, protein content, ash content, moisture content, fiber content and carbohydrate content values of 5%, 2.1%,10%, 5%, 15%, and 62.9% respectively.

Keywords: biodiesel, characterization, cow-tallow, cetane rating

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Authors: J. Zhang, K. Agyapong-Kodua

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Digital factory based on visual design and simulation has emerged as a mainstream to reduce digital development life cycle. Some basic industrial systems are being integrated via semantic modelling, and products (P) matching process (P)-resource (R) requirements are designed to fulfill current customer demands. Nevertheless, product design is still limited to fixed product models and known knowledge of product engineers. Therefore, this paper presents a rapid reconfiguration method based on semantic technologies with PPR ontologies to reuse known and unknown knowledge. In order to avoid the influence of big data, our system uses a cloud manufactory and distributed database to improve the efficiency of querying meeting PPR requirements.

Keywords: semantic technologies, factory system, digital factory, cloud manufactory

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Authors: Hsien-Tsen Wang

Abstract:

Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

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Authors: Nima Mahmoudi, Hamzeh Khazaei

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Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

Procedia PDF Downloads 153