Search results for: edge computing module

Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Maria Venus G. Solares

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The ancient Filipinos had their own spelling or alphabet that differed from the modern Roman alphabet brought by the Spaniards. It consists of seventeen letters, three vowels, and fourteen consonants and is called Baybayin. The word Baybayin is a Tagalog word that refers to all the letters used in writing a language, an alphabet; however, it is also a syllable. The House Bill 4395, first proposed by Rep. Leopoldo Bataoil of the second district of Pangasinan in 2011, which later became House Bill 1022 of what he called The Declaration of the Baybayin as the National Writing System of the Philippines, prompted the researcher to conduct a study on the topic. The main objective of this study was to develop and assess the proposed module for enhancing the reading and writing skills in Baybayin of the students. The researchers wanted to ensure the acceptability of the Baybayin using the proposed module and meet the needs of students in developing their ability to read and write Baybayin through the module. The researchers used quasi-experimental research in this study. The data was collected through the initial and final analysis of the students of Adamson University's ABM 1102 using convenient sampling techniques. Based on statistical analysis of data using weighted mean, standard deviation, and paired t-tests, the proposed module helped improve the students' literacy skills, and the response exercises in the proposed module changed the acceptability of the Baybayin in their minds. The study showed that there was an important difference in the scores of students before and after the use of the module. The student's response to the assessment of their reading and writing skills on Baybayin was highly acceptable. This study will help develop the reading and writing skills of the students in Baybayin and teach Baybayin in response to the revival of a part of Philippine culture that has been long forgotten.

Keywords: Baybayin, proposed module, skill, acceptability

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Ofri Earon

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This article is about a growing focus in the city of Copenhagen – the edge zone between the private space inside the residential building and the public space out at the residential street. A slow transition between the private living room and the public urban space creates a mutual benefit. The urban space benefits from an insertion of a homey atmosphere by the extended performance of living rooms to the exterior. The dwelling benefits from belonging to a liveable neighborliness, which means an extension of the private home to a collective home (= the neighborhood). Grounded by this reciprocal value of the edge zone, through the article, it is argued that a wide generosity of the edge zones is of interest among both planners and residents. The article introduces the idea of the edge zone and its possible implications in the development of the liveable residential city. Three examples of ongoing projects at Arkitema Architects are bought to illustrate the challenges and potentials of a generous edge zone. Every example represents a specific dwelling typology in a particular urban context: (1) multi-family residential building in a previous industrial area in the city (2) new courtyard building in the city’s outskirt (3) low and dense residential area out in the suburbia. Throughout these examples, the article seeks to discuss the significance of the edge zone in forthcoming residential areas in Denmark. The analysis of the Danish examples raises the question of why a social behavior that happens spontaneously in the south of Europe has to be carefully implemented in the architecture of north of Europe. In this light, the article ends with a discussion on how to create edge zones that are not designed for a particular usage, but rather as an architectural invitation for varied social behaviors that spontaneously occur in different moments of time by different people. Finally, the article ends with a list of recommendations for the development of the generous edge zone as an open invitation for diverse usage over time.

Keywords: dwelling, edge zone, generosity, livability, urban space

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: Gang Liu, Huimin Song, Can Wang, Runnan Zhang, Lu Fang

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Currently, resource sharing and system security are critical issues. This paper proposes a POL module composed of PRIV ILEGE attribute (PA), obligation and log which improves attribute based access control (ABAC) model in dynamically granting authorizations and revoking authorizations. The following describes the new model termed PABAC in terms of the POL module structure, attribute definitions, policy formulation and authorization architecture, which demonstrate the advantages of it. The POL module addresses the problems which are not predicted before and not described by access control policy. It can be one of the subject attributes or resource attributes according to the practical application, which enhances the flexibility of the model compared with ABAC. A scenario that illustrates how this model is applied to the real world is provided.

Keywords: access control, attribute based access control, granting authorizations, privilege, revoking authorizations, system security

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Authors: Farzaneh Yazdani, Nastaran Yazdani, Laya Nobakht

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The aim of this study was to explore the changes that may happen in students attitudes regarding disability after attending the module ‘Disability: theories, nature and experiences’ designed around reflective self-awareness exercises. Literature indicates enhanced knowledge does not automatically lead to changes in attitude. Health care professionals are the most significant people to instil hope in their clients to pursue a happy life. As an advocate for people with disability, health care professionals need to believe themselves in people with disability being able to pursue a happy life as an abled body does. Researchers aimed to explore the impact of the ‘Disability’ module using discussion and reflective exercises, on students’ way of thinking and possible changes in attitude towards disability. Students were asked to write stories from the beginning and after completing the module. A thematic analysis was applied to identify the students’ way of communicating their thoughts and feelings about disable-bodied /disability before and after the module. Three major themes were identified to represent the differences before and after attending the module as: problem /solution oriented approach towards perceived problems, separating/ integrating disable/able-bodied, passive/ active role of disable-bodied and society.

Keywords: qualitative study, reflection, rehabilitation, thematic analysis

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

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Authors: S. Khan, A. Khan, Abdul R. Soomrani, Raja F. Zafar, A. Waqas, G. Akbar

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This paper proposes a low-complexity image interpolation method. Image interpolation is used to convert a low dimension video/image to high dimension video/image. The objective of a good interpolation method is to upscale an image in such a way that it provides better edge preservation at the cost of very low complexity so that real-time processing of video frames can be made possible. However, low complexity methods tend to provide real-time interpolation at the cost of blurring, jagging and other artifacts due to errors in slope calculation. Non-linear methods, on the other hand, provide better edge preservation, but at the cost of high complexity and hence they can be considered very far from having real-time interpolation. The proposed method is a linear method that uses gradient orientation for slope calculation, unlike conventional linear methods that uses the contrast of nearby pixels. Prewitt edge detection is applied to separate uniform regions and edges. Simple line averaging is applied to unknown uniform regions, whereas unknown edge pixels are interpolated after calculation of slopes using gradient orientations of neighboring known edge pixels. As a post-processing step, bilateral filter is applied to interpolated edge regions in order to enhance the interpolated edges.

Keywords: edge detection, gradient orientation, image upscaling, linear interpolation, slope tracing

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Authors: Keshek M.H, Mohamed M.A, El-Shafey M.A

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The aim of this research was increasing the productivity of solar distillation. In order to reach this aim, a solar distiller was created with three glass sides sloping 30o at the horizontal level, and the experiments were carried out on the solar distillation unit during the period from 24th August, 2016 till 24th May, 2017 at the Agricultural Engineering and Bio Systems Department, Faculty of Agriculture, Menoufia University. Three gap lengths were used between the water level and the inner glass cover, those were 3, 6, and 9 cm. As the result of change the gap length between the water level and the inner glass cover the total volume of basins were changed from 15.5, 13, and 11 L, respectively. The total basin volume was divided to three sections, to investigate the effect of water volume. The three water volumes were 100%, 75%, and 50%. Every section was supplied with one, two, or three heaters. The one heater power was 15 W. The results showed that, by increasing the distance between the basins edge and the inner edge of the glass cover, an increase occurs in the percentage of temperature difference with maximum value was 52% at distance 9 cm from each edge, an increase occurs in the productivity with maximum productivity was 3.3 L/m2 at distance 9 cm from each edge and an increase occurs in the efficiency with maximum efficiency was 70% at distance 9 cm from each edge.

Keywords: distillation, solar energy, still productivity, efficiency

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Authors: Saw Thiha, Jay Rajasekera

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A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Mannan Ahmad Rasheed, Sawera Kanwal, Mansoor Ahmad Rasheed

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The Internet of Things (IoT) has revolutionized the way we collect and process information, making it possible to gather data from a wide range of connected devices and sensors. This has led to the development of IoT-based information processing and computing systems that are capable of handling large amounts of data in real time. This paper provides a comprehensive overview of the current state of IoT-based information processing and computing, as well as the key challenges and gaps that need to be addressed. This paper discusses the potential benefits of IoT-based information processing and computing, such as improved efficiency, enhanced decision-making, and cost savings. Despite the numerous benefits of IoT-based information processing and computing, several challenges need to be addressed to realize the full potential of these systems. These challenges include security and privacy concerns, interoperability issues, scalability and reliability of IoT devices, and the need for standardization and regulation of IoT technologies. Moreover, this paper identifies several gaps in the current research related to IoT-based information processing and computing. One major gap is the lack of a comprehensive framework for designing and implementing IoT-based information processing and computing systems.

Keywords: IoT, computing, information processing, Iot computing

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Authors: Ezil Sam Leni, Shalen S.

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Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.

Keywords: federated Learning, pothole detection, distributed framework, federated averaging

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Authors: Aabiah Nayeem, Fariha Shafiq, Mustabshra Aftab, Rabia Saman Pirzada, Samia Ghazala

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In this modern era of technology, the concept of Internet of Things is very popular in every domain. It is a widely distributed system of things in which the data collected from sensory devices is transmitted, analyzed locally/collectively then broadcasted to network where action can be taken remotely via mobile/web apps. Today’s mobile computing is also gaining importance as the services are provided during mobility. Through mobile computing, data are transmitted via computer without physically connected to a fixed point. The challenge is to provide services with high speed and security. Also, the data gathered from the mobiles must be processed in a secured way. Mobile computing is strongly influenced by internet of things. In this paper, we have discussed security issues and challenges of internet of things and mobile computing and we have compared both of them on the basis of similarities and dissimilarities.

Keywords: embedded computing, internet of things, mobile computing, wireless technologies

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: Adnan Alhathal Alanezi

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The performance of vacuum membrane distillation (VMD) process for water desalination was investigated utilizing a new design membrane module using two commercial polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) flat sheet hydrophobic membranes. The membrane module's design demonstrated its suitability for achieving a high heat transfer coefficient of the order of 103 (W/m2K) and a high Reynolds number (Re). The heat and mass transport coefficients within the membrane module were measured using VMD experiments. The permeate flux has been examined in relation to process parameters such as feed temperature, feed flow rate, vacuum degree, and feed concentration. Because the feed temperature, feed flow rate, and vacuum degree all play a role in improving the performance of the VMD process, optimizing all of these parameters is the best method to achieve a high permeate flux. In VMD desalination, the PTFE membrane outperformed the PVDF membrane. When compared to previous studies, the obtained water flux is relatively high, reaching 43.8 and 52.6 (kg/m2h) for PVDF and PTFE, respectively. For both membranes, the salt rejection of NaCl was greater than 99%.

Keywords: desalination, vacuum membrane distillation, PTFE and PVDF, hydrophobic membranes, O-ring membrane module

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

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Authors: J. Joy, T. H. New, I. H. Ibrahim

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A computational study on bio-inspired NACA634-021 hydrofoils with leading-edge protuberances has been carried out to investigate their hydrodynamic flow control characteristics at a Reynolds number of 14,000 and different angles-of-attack. The numerical simulations were performed using ANSYS FLUENT and based on Reynolds-Averaged Navier-Stokes (RANS) solver mode incorporated with k-ω Shear Stress Transport (SST) turbulence model. The results obtained indicate varying flow phenomenon along the peaks and troughs over the span of the hydrofoils. Compared to the baseline hydrofoil with no leading-edge protuberances, the leading-edge modified hydrofoils tend to reduce flow separation extents along the peak regions. In contrast, there are increased flow separations in the trough regions of the hydrofoil with leading-edge protuberances. Interestingly, it was observed that dissimilar flow separation behaviour is produced along different peak- or trough-planes along the hydrofoil span, even though the troughs or peaks are physically similar at each interval for a particular hydrofoil. Significant interactions between adjacent flow structures produced by the leading-edge protuberances have also been observed. These flow interactions are believed to be responsible for the dissimilar flow separation behaviour along physically similar peak- or trough-planes.

Keywords: computational fluid dynamics, flow separation control, hydrofoils, leading-edge protuberances

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Authors: K. K. Saijaand, K. Prabhakaran Nair

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This study aims to determine change in optimal lo-cations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multi-objective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization results shows that the inboard flap location at low Ct/σ ratio move farther from the baseline value and at high Ct/σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: helicopter rotor, trailing-edge flap, thrust coefficient to solidity (Ct /σ) ratio, optimization

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Authors: Branci Sarra, Branci Saadia

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Because of the multiplied data growth, many computer science tools have been developed to process and analyze these Big Data. High-performance computing architectures have been designed to meet the treatment needs of Big Data (view transaction processing standpoint, strategic, and tactical analytics). The purpose of this article is to provide a historical and global perspective on the recent trend of high-performance computing architectures especially what has a relation with Analytics and Data Mining.

Keywords: high performance computing, HPC, big data, data analysis

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Authors: Abdullah Aljumah, Tariq Ahamad

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The simplest possible human-computer interaction is mobile cloud computing as it emerges and makes the use of all modern-day human-oriented technology. The main aim of this idea is the QoS (quality of service) by using user-friendly and reliable software over the global network in order to make it economical by reducing cost, reliable, and increase the main storage. Since we studied and went through almost all the existing related work in this area and we came up with some challenges that will rise or might be rising for some basic areas in mobile cloud computing and mostly stogie and security area. In this research article, we suggest some recommendation for mobile cloud computing and for its security that will help in building more powerful tools to handle all this pressure.

Keywords: Cloud Computing, MCC, SAAS, computer interaction

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Authors: Kelebaone Tsamaase, Rapelang Kemoabe, Japhet Sakala, Edward Rakgati, Ishmael Zibani

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Increasing demand for energy, depletion of non-renewable energy, effects of climate change, the abundance of renewable energy such as solar energy have increased the interest in investing in renewable energies, in particular solar photovoltaic (PV) energy. Solar photovoltaic energy systems as part of clean technology are considered to be environmentally friendly, freely available, offer clean production systems, long term costs benefits as opposed to conventional sources, and are the attractive power source for a wide range of applications in remote areas where there is no easy access to the national grid. To get maximum electrical power, maximum solar power should penetrate the module and be converted accordingly. However, some environmental and other geographical related factors reduce the electrical power. One of them is dust which accumulates on the surface of the module and forming a dust layer and in the process obstructing the solar power from penetrating PV module. This study intends to improve the performance of solar photovoltaic (PV) energy modules by establishing soil accumulation effects correction factor from dust characteristics and properties, and also from dust accumulation and retention pattern on PV module surface. The non-urban dry deposition flux model was adapted to determine monthly and yearly dust accumulation pattern. Consideration was done on prevailing environmental and other geographical conditions. Preliminary results showed that cumulative dust settlement increased during the months of July to October leading to a higher drop in module electrical output power.

Keywords: dust, electrical power output, PV module, soil correction factor

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Authors: Wenjun Hou, Marek Perkowski

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The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

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Authors: Sunthorn Sittisakuljaroen

Abstract:

The edge waviness in hot rolled steel is a common defect. Variables that effect for such defect include as raw material and machine. These variables are necessary to consider. This research studied the defect of edge waviness for SS 400 of metal sheet manufacture. Defect of metal sheets divided into two groups. The specimens were investigated on chemical composition and mechanical properties to find the difference. The results of investigate showed that not different to a standard significantly. Therefore the roll milled machine for sample need to adjustable rollers for press on metal sheet which was more appropriate to adjustable at both ends.

Keywords: edge waviness, hot rolling steel, metal sheet defect, SS 400, roll leveller

Procedia PDF Downloads 371

Authors: Abul Bashar

Abstract:

The recent surge in the adoption of cloud computing systems by various organizations has brought forth the challenge of evaluating their performance. One of the major issues faced by the cloud service providers and customers is to assess the ability of cloud computing systems to provide the desired services in accordance to the QoS and SLA constraints. To this end, an opportunity exists to develop means to ensure that the desired performance levels of such systems are met under simulated environments. This will eventually minimize the service disruptions and performance degradation issues during the commissioning and operational phase of cloud computing infrastructure. However, it is observed that several simulators and modelers are available for simulating the cloud computing systems. Therefore, this paper presents a critical evaluation of the state-of-the-art modeling and simulation frameworks applicable to cloud computing systems. It compares the prominent simulation frameworks in terms of the API features, programming flexibility, operating system requirements, supported services, licensing needs and popularity. Subsequently, it provides recommendations regarding the choice of the most appropriate framework for researchers, administrators and managers of cloud computing systems.

Keywords: cloud computing, modeling framework, performance evaluation, simulation tools

Procedia PDF Downloads 461

Authors: Disha Gupta

Abstract:

The aim of this research is to conduct X-ray and e-beam characterization techniques on lithium-ion battery materials for the improvement of battery performance. The key characterization techniques employed are the synchrotron X-ray Absorption Spectroscopy (XAS) combined with X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to obtain a more holistic approach to understanding material properties. This research effort provides additional battery characterization knowledge that promotes the development of new cathodes, anodes, electrolyte and separator materials for batteries, hence, leading to better and more efficient battery performance. Both ex-situ and in-situ synchrotron experiments were performed on LiFePO₄, one of the most common cathode material, from different commercial sources and their structural analysis, were conducted using Athena/Artemis software. This analysis technique was then further extended to study other cathode materials like LiMnxFe(₁₋ₓ)PO₄ and even some sulphate systems like Li₂Mn(SO₄)₂ and Li₂Co0.5Mn₀.₅ (SO₄)₂. XAS data were collected for Fe and P K-edge for LiFePO4, and Fe, Mn and P-K-edge for LiMnxFe(₁₋ₓ)PO₄ to conduct an exhaustive study of the structure. For the sulphate system, Li₂Mn(SO₄)₂, XAS data was collected at both Mn and S K-edge. Finite Difference Method for Near Edge Structure (FDMNES) simulations were also conducted for various iron, manganese and phosphate model compounds and compared with the experimental XANES data to understand mainly the pre-edge structural information of the absorbing atoms. The Fe K-edge XAS results showed a charge compensation occurring on the Fe atom for all the differently synthesized LiFePO₄ materials as well as the LiMnxFe(₁₋ₓ)PO₄ systems. However, the Mn K-edge showed a difference in results as the Mn concentration changed in the materials. For the sulphate-based system Li₂Mn(SO₄)₂, however, no change in the Mn K-edge was observed, even though electrochemical studies showed Mn redox reactions.

Keywords: li-ion batteries, electrochemistry, X-ray absorption spectroscopy, XRD

Procedia PDF Downloads 118