Search results for: automated power system

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

Procedia PDF Downloads 82

Authors: Naci Kalkan, Ihsan Dagtekin

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This research presents the design and analysis of solar air-conditioning systems particularly solar chimney which is a passive strategy for natural ventilation, and demonstrates the structures of these systems’ using Computational Fluid Dynamic (CFD) and finally compares the results with several examples, which have been studied experimentally and carried out previously. In order to improve the performance of solar chimney system, highly efficient sub-system components are considered for the design. The general purpose of the research is to understand how efficiently solar chimney systems generate cooling, and is to improve the efficient of such systems for integration with existing and future domestic buildings.

Keywords: active and passive solar technologies, solar cooling system, solar chimney, natural ventilation, cavity depth, CFD models for solar chimney

Procedia PDF Downloads 557

Authors: Gizachew Belay Adugna

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Perovskite solar cells (PSCs) shows rapid development as an emerging photovoltaic material; however, the fast device degradation due to the organic nature, mainly hole transporting material (HTM) and lack of robust and reliable upscaling process for photovoltaic module hindered its commercialization. Herein, HTM molecules with/without fluorine-substituted cyclopenta[2,1-b;3,4-b’]dithiophene derivatives (HYC-oF, HYC-mF, and HYC-H) were developed for PSCs application. The fluorinated HTM molecules exhibited better hole mobility and overall charge extraction in the devices mainly due to strong molecular interaction and packing in the film. Thus, the highest power conversion efficiency (PCE) of 19.64% with improved long stability was achieved for PSCs based on HYC-oF HTM. Moreover, the fluorinated HYC-oF demonstrated excellent film processability in a larger-area substrate (10 cm×10 cm) prepared sequentially with the absorption perovskite underlayer via a scalable bar coating process in ambient air and owned a higher PCE of 18.49% compared to the conventional spiro-OMeTAD (17.51%). The result demonstrates a facile development of HTM towards stable and efficient PSCs for future industrial-scale PV modules.

Keywords: perovskite solar cells, upscaling film coating, power conversion efficiency, solution processing

Procedia PDF Downloads 55

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

Procedia PDF Downloads 150

Authors: Zheming Cao

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Control loops are the most important components in the wind turbine system. Product quality, operation safety, and the economic performance are directly or indirectly connected to the performance of control systems. This paper proposed a performance evaluation method based on minimum-variance for wind turbine control system. This method can be applied on PID controller for pitch control system in the wind turbine. The good performance result demonstrated in the paper was achieved by retuning and optimizing the controller settings based on the evaluation result. The concepts presented in this paper are illustrated with the actual data of the industrial wind farm.

Keywords: control performance, evaluation, minimum-variance, wind turbine

Procedia PDF Downloads 350

Authors: Chakshu Baweja, Ishaan Prakash, Deepak Giri, Prithwish Mukherjee, Herambraj Ashok Nalawade

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The need to prevent and control rampant and indiscriminate usage of energy in present-day realm on earth has motivated active research efforts aimed at understanding of controlling mechanisms leading to sustained energy. Although much has been done but complexity of the problem has prevented a complete understanding due to nonlinear interaction between flow, heat and mass transfer in terrestrial environment. Therefore, there is need for a systematic study to clearly understand mechanisms controlling energy-spreading phenomena to increase a system’s efficiency. The present work addresses the issue of sustaining energy and proposes a devoted technique of optimizing energy in the automotive domain. The proposed method focus on utilization of the mechanical and thermal energy of an automobile IC engine by converting and storing energy due to motion of a piston in form of electrical energy. The suggested technique utilizes piston motion of the engine to generate high potential difference capable of working as a secondary power source. This is achieved by the use of a gear mechanism and a flywheel.

Keywords: internal combustion engine, energy, electromagnetic induction, efficiency, gear ratio, hybrid vehicle, engine shaft

Procedia PDF Downloads 456

Authors: Amil Daraz, Suheel Abdullah Malik, Tahir Saleem, Sajid Ali Bhati

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In this paper, Integral Proportional (I-P) controller is employed for superheated steam temperature control system. The Ziegler-Nichols (Z-N) method is used for the tuning of I-P controller. The performance analysis of Z-N based I-P controller is assessed on superheated steam system of 500-MW boiler. The comparison of transient response parameters such as rise time, settling time, and overshoot is made with Z-N based Proportional Integral (PI) controller. It is observed from the results that Z-N based I-P controller completely eliminates the overshoot in the output response.

Keywords: superheated steam, process reaction curve, PI and I-P controller, Ziegler-Nichols Tuning

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Authors: A. Sgobba, C. Meskell

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The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.

Keywords: demand, energy system integration, load, manufacturing, national grid, renewable energy sources

Procedia PDF Downloads 119

Authors: L. Wei Sheng, M. T. Noor Syazwanee, C. J. Carolyna, M. Amiruddin, M. Pauziah

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This paper exhibits the alternatives towards active suspension systems revised based on the classical passive suspension system to improve comfort and handling performance. An active Magneto rheological (MR) suspension system is proposed as to explore the active based suspension system to enhance performance given its freedom to independently specify the characteristics of load carrying, handling, and ride quality. Malaysian quarter car with two degrees of freedom (2DOF) system is designed and constructed to simulate the actions of an active vehicle suspension system. The structure of a conventional twin-tube shock absorber is modified both internally and externally to comprehend with the active suspension system. The shock absorber peripheral structure is altered to enable the assembling and disassembling of the damper through a non-permanent joint whereby the stress analysis of the designed joint is simulated using Finite Element Analysis. Simulation on the internal part where an electrified copper coil of 24AWG is winded is done using Finite Element Method Magnetics to measure the magnetic flux density inside the MR damper. The primary purpose of this approach is to reduce the vibration transmitted from the effects of road surface irregularities while maintaining solid manoeuvrability. The aim of this research is to develop an intelligent control system of a consecutive damping automotive suspension system. The ride quality is improved by means of the reduction of the vertical body acceleration caused by the car body when it experiences disturbances from speed bump and random road roughness. Findings from this research are expected to enhance the quality of ride which in return can prevent the deteriorating effect of vibration on the vehicle condition as well as the passengers’ well-being.

Keywords: active suspension, FEA, magneto rheological damper, Malaysian quarter car model, vibration control

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Authors: Kazuyoshi Mori, Keisuke Hashimoto

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In this paper, we consider the two-stage compensator designs of SISO plants. As an investigation of the characteristics of the two-stage compensator designs, which is not well investigated yet, of SISO plants, we implement three dimensional visualization systems of output signals and optimization system for SISO plants by the parametrization of stabilizing controllers based on the two-stage compensator design. The system runs on Mathematica by using “Three Dimensional Surface Plots,” so that the visualization can be interactively manipulated by users. In this paper, we use the discrete-time LTI system model. Even so, our approach is the factorization approach, so that the result can be applied to many linear models.

Keywords: linear systems, visualization, optimization, Mathematica

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

Procedia PDF Downloads 270

Authors: Saghir Ahmad, Abid Hussain Ch, Misbah Malik, Ayesha Batool

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Terrorism is the marvel in which dreadful circumstance is made by a gathering of individuals who view themselves as abused by society. Terrorism is the unlawful utilization of power or viciousness by a man or a sorted out gathering by the general population or property with the aim of intimidation or compulsion of social orders or governments frequently for ideological or political reasons. Terrorism is as old as people. The main aim of the study was to find out the causes of terrorism through the perceptions of the universities students of teacher training institutions. This study was quantitative in nature. Survey method was used to collect data. A sample of two hundred and sixty seven students was selected from public universities. A five point Likert scale was used to collect data. Mean, Standard deviation, independent sample t-test, and One Way ANOVA were applied to analyze the data. The major findings of the study indicated that students perceived the main causes of terrorism are poverty, foreign interference, wrong concept of Islamization, and social injustice. It is also concluded that mostly, students think that drone attacks are promoting the terrorist activities. The education is key to eliminate the terrorism. There is need to educate the people and specially youngsters to bring the peace in the world.

Keywords: dreadful circumstance, governments, power, students, terrorism

Procedia PDF Downloads 530

Authors: K. Adu Michael, K. Alese Boniface

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Developing a reliable and sustainable software products is today a big challenge among up–coming software developers in Nigeria. The inability to develop a comprehensive problem statement needed to execute proper requirements engineering process is missing. The need to describe the ‘what’ of a system in one document, written in a natural language is a major step in the overall process of Software Engineering. Requirements Engineering is a process use to discover, analyze and validate system requirements. This process is needed in reducing software errors at the early stage of the development of software. The importance of each of the steps in Requirements Engineering is clearly explained in the context of using detailed problem statement from client/customer to get an overview of an existing system along with expectations from the new system. This paper elicits inadequate Requirements Engineering principle as the major cause of poor software development in developing nations using a case study of final year computer science students of a tertiary-education institution in Nigeria.

Keywords: client/customer, problem statement, requirements engineering, software developers

Procedia PDF Downloads 389

Authors: Pankaj Pathak, Susmita Sharma

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Incessant industrial growth fulfill the energy demand of present day society, at the same time it produces huge amount of waste which could be hazardous or non-hazardous in nature. These wastes are coming out from different sources viz, nuclear power, thermal power, coal mines which contain different types of contaminants and one of the emergent contaminant is strontium, used in the present study. The isotope of strontium (Sr90) is radioactive in nature with half-life of 28.8 years and permissible limit of strontium in drinking water is 1.5 ppm. Above the permissible limit causes several types of diseases in human being. Therefore, safe disposal of strontium into ground becomes a biggest challenge for the researchers. In this context, bentonite is being used as an efficient material to retain strontium onto ground due to its specific physical, chemical and mineralogical properties which exhibits higher cation exchange capacity and specific surface area. These properties influence the interaction between strontium and bentonite, which is quantified by employing a parameter known as distribution coefficient. Batch test was conducted, and sorption isotherms were modelled at different interaction time. The pseudo first-order and pseudo second order kinetic models have been used to fit experimental data, which helps to determine the sorption rate and mechanism.

Keywords: bentonite, interaction time, sorption, strontium

Procedia PDF Downloads 285

Authors: Kumaresh Selvakumar, Man Young Kim

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A wet scrubber is an air pollution control device that removes particulate matter and acid gases from waste gas streams found in marine engine exhaust. If the flue gases in the exhaust is employed for CFD simulation, it makes the problem complicate due to the involvement of emissions. Owing to the fact, the scrubber system in this paper is handled with appropriate approach by designing with the flow properties of hot air and water droplet injections to evaluate the flow behavior inside the system. Since the wet scrubber has the capability of operating over wide range of mixture compositions, the current scrubber model with the designing approach doesn’t deviate from the actual behavior of the system. The scrubber design is constructed with engine exhaust pipe with the purpose of measuring the flow properties inside the scrubber by the influence of exhaust pipe characteristics. The flow properties are computed by the thermodynamic variables such as temperature and pressure with the flow velocity. In this work, numerical analyses have been conducted for the flow of fluid in the scrubber system through CFD technique.

Keywords: wet scrubber, water droplet injections, thermodynamic variables, CFD technique

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Authors: Temsiri Sapsaman, Anocha Bhocarattanahkul

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The maintenance of work rolls in hot strip processing has been lengthy and difficult tasks for hot strip manufacturer because heavy work rolls have to be taken out of the production line, which could take hours. One way to increase the time between maintenance is to improve the effectiveness of the work roll cooling system such that the wear and tear more slowly occurs, while the operation cost is kept low. Therefore, this study aims to improve the work roll cooling system by providing the manufacturer the relationship between the work-roll temperature reduced by cooling and the water flow that can help manufacturer determining the more effective water flow of the cooling system. The relationship is found using simulation with a systematic process adjustment so that the satisfying quality of product is achieved. Results suggest that the manufacturer could reduce the water flow by 9% with roughly the same performance. With the same process adjustment, the feasibility of finishing-mill-stand reduction is also investigated. Results suggest its possibility.

Keywords: work-roll cooling system, hot strip process adjustment, feasibility study, stand reduction

Procedia PDF Downloads 355

Authors: J. Ierache, N. A. Mangiarua, S. A. Bevacqua, N. N. Verdicchio, M. E. Becerra, D. R. Sanz, M. E. Sena, F. M. Ortiz, N. D. Duarte, S. Igarza

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Augmented Reality is a technology that involves the overlay of virtual content, which is context or environment sensitive, on images of the physical world in real time. This paper presents the development of a catalog system that facilitates and allows the creation, publishing, management and exploitation of augmented multimedia contents and Augmented Reality applications, creating an own space for anyone that wants to provide information to real objects in order to edit and share it then online with others. These spaces would be built for different domains without the initial need of expert users. Its operation focuses on the context of Web 2.0 or Social Web, with its various applications, developing contents to enrich the real context in which human beings act permitting the evolution of catalog’s contents in an emerging way.

Keywords: augmented reality, catalog system, computer graphics, mobile application

Procedia PDF Downloads 337

Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

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An efficient and well-planned ultrafiltration process is becoming a necessity for monetary returns in the industrial settings. The aim of the present study was to develop a mathematical model for an accurate prediction of ultrafiltration membrane fouling of latex effluent applied to homogeneous and heterogeneous membranes with uniform and non-uniform pore sizes, respectively. The models were also developed for an accurate prediction of power consumption that can handle the large-scale purposes. The model incorporated the fouling attachments as well as chemical and physical factors in membrane fouling for accurate prediction and scale-up application. Both Polycarbonate and Polysulfone flat membranes, with pore sizes of 0.05 µm and a molecular weight cut-off of 60,000, respectively, were used under a constant feed flow rate and a cross-flow mode in ultrafiltration of the simulated paint effluent. Furthermore, hydrophilic ultrafilic and hydrophobic PVDF membranes with MWCO of 100,000 were used to test the reliability of the models. Monodisperse particles of 50 nm and 100 nm in diameter, and a latex effluent with a wide range of particle size distributions were utilized to validate the models. The aggregation and the sphericity of the particles indicated a significant effect on membrane fouling.

Keywords: membrane fouling, mathematical modeling, power consumption, attachments, ultrafiltration

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Authors: Bhaumik Tyagi, Mandeep Kaur, Kanika Singla

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The advancement of blockchain has facilitated scholars to remodel e-voting systems for future generations. Server-side attacks like SQL injection attacks and DOS attacks are the most common attacks nowadays, where malicious codes are injected into the system through user input fields by illicit users, which leads to data leakage in the worst scenarios. Besides, quantum attacks are also there which manipulate the transactional data. In order to deal with all the above-mentioned attacks, integration of blockchain, convolutional neural network (CNN), and Quantum Key Distribution is done in this very research. The utilization of blockchain technology in e-voting applications is not a novel concept. But privacy and security issues are still there in a public and private blockchains. To solve this, the use of a hybrid blockchain is done in this research. This research proposed cryptographic signatures and blockchain algorithms to validate the origin and integrity of the votes. The convolutional neural network (CNN), a normalized version of the multilayer perceptron, is also applied in the system to analyze visual descriptions upon registration in a direction to enhance the privacy of voters and the e-voting system. Quantum Key Distribution is being implemented in order to secure a blockchain-based e-voting system from quantum attacks using quantum algorithms. Implementation of e-voting blockchain D-app and providing a proposed solution for the privacy of voters in e-voting using Blockchain, CNN, and Quantum Key Distribution is done.

Keywords: hybrid blockchain, secure e-voting system, convolutional neural networks, quantum key distribution, one-time pad

Procedia PDF Downloads 75

Authors: R. V. Dahibhate, A. B. Deoghare, P. M. Padole

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Maintaining natural integrity of biosystem is paramount significant for orthopedic surgeon while performing surgery. Restoration is challenging task to rehabilitate trauma patient. Drilling is an inevitable procedure to fix implants. The task leads to rise in temperature at the contact site which intends to thermal necrosis. A precise monitoring can avoid thermal necrosis. To accomplish it, data acquiring instrument is integrated with the drill bit. To contemplate it, electronic feedback system is developed. It not only measures temperature without any physical contact in between measuring device and target but also visualizes the site and monitors correct movement of tool path. In the current research work an infrared thermometer data acquisition system is used which monitors variation in temperature at the drilling site and a camera captured movement of drill bit advancement. The result is presented in graphical form which represents variations in temperature, drill rotation and time. A feedback system helps in keeping drill speed in threshold limit.

Keywords: thermal necrosis, infrared thermometer, drilling tool, feedback system

Procedia PDF Downloads 219

Authors: Eliud Kiprop, Kenichi Matsui, Joseph Karanja, Hesborn Ondiba

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To double the share of renewable energy in the global energy mix by 2030 as part of actions for the Paris Agreement, policymakers in each ratifying country must accelerate their efforts within the next few years by implementing their own renewable energy strategies. Kenya has increased its funding for research and development in renewable energy sources largely because it intends to reduce greenhouse gas GHG emissions by 30% from business as usual (BAU) levels (143 MtCO₂eq) by 2030. In 2013, the Kenyan government launched an ambitious plan to increase the installed power generation capacity from 1,768MW to more than 5,000MW by the end of 2017. This paper examines the formulation and implementation process of this plan and shows how this plan will affect Kenya’s renewable energy industry and national policy implementation in general. Results demonstrate that, despite having a well- documented policy in place, the Kenyan government cannot meet its target of 5000MW by the end of 2017. Among other factors, we find that the main reason is attributable to the failure in adhering to the main principles of the policy plan. We also find that the government has failed to consider the future energy demand. Had the policy been implemented on time, we argue that there would have been excess power.

Keywords: policy implementation, policy plan, renewable energy, sustainable development

Procedia PDF Downloads 205

Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Svetlana Missina, Anatoliy Shipilov, Alexandr Vavaev

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The purpose of the present study was to investigate the relationship between sprint and vertical jump performance in elite female football players. Twenty four professional female football players (age, 18.6±3.1 years; height, 168.3±6.3 cm, body mass 61.6±7.4 kg; mean±SD) were tested for 30-m sprint time, 10-m sprint time and vertical countermovement (CMJ) and squat (SJ) jumps height. Participants performed three countermovement jumps and three squat jumps for maximal height on a force platform. Mean values of three trials were used in statistical analysis. The displacement of center of mass (COM) during flight phase (e.g. jump height) was calculated using the vertical velocity of the COM at the moment of take-off. 30-m and 10-m sprint time were measured using OptoGait optical system. The best of three trials were used for analysis. A significant negative correlation was found between 30-m sprint time and CMJ, SJ height (r = -0.85, r = -0.79 respectively), between 10-m sprint time and CMJ, SJ height (r = -0.73, r = -0.8 respectively), and step frequency was significantly related to CMJ peak power (r = -0.57). Our study indicates that there is strong correlation between sprint and jump performance in elite female football players, thus vertical jump test can be considered as a good sprint and agility predictor in female football.

Keywords: agility, female football players, sprint performance, vertical jump height

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Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

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Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome

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Authors: Vijaya Chandra Tenneti

Abstract:

The juvenile justice delivery system in India suffers from many lacunae at the operational level and ignores many dimensions of human rights guaranteed to the juvenile delinquents. The present study begins with the hypothesis that the existing justice delivery system seemingly ignores the basic tenets of the fair trial and systemic support to the delinquent juveniles in integrating them into the mainstream of society. As per the designed methodology, data has been collected from the unit of the present study, and other stakeholders, namely, Juvenile Justice Board, Observation Homes etc., of Warangal district of Telangana state, India. The study shows that there is the overemphasis on procedural laws. The juvenile integration programs are not effective. The administrators lack training. Juveniles lack formal education. The study indicates the incidents of juvenile crimes is on the rise and that the majority of the juvenile delinquents hold a low socio-economic profile. Another significant observation of the study is that the juvenile justice system lacks a holistic and human rights-centric approach.

Keywords: delinquency, human rights, juvenile justice, rehabilitation

Procedia PDF Downloads 125

Authors: Muhammad A. Alsubaie, Mubarak K. H. Alhajri, Tarek S. Altowaim

Abstract:

A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted.

Keywords: model mismatch, repetitive control, singular values, state feedback

Procedia PDF Downloads 139

Authors: Michael Dimmer, Holger Flederer

Abstract:

The basis of realizing a construction project is a technically flawless concept which satisfies conditions regarding environment and costs, as well as static-constructional terms. The presented software system actively supports civil engineers during the setup of optimal designs, by giving advice regarding durability, life-cycle costs, sustainability and much more. A major part of the surrounding conditions of a design process is gathered and assimilated by experienced engineers subconsciously. It is a question about eligible building techniques and their practicability by considering emerging costs. Planning engineers have acquired many of this experience during their professional life and use them for their daily work. Occasionally, the planning engineer should disassociate himself from his experience to be open for new and better solutions which meet the functional demands, as well. The developed expert system gives planning engineers recommendations for preferred design options of new constructions as well as for existing bridge constructions. It is possible to analyze construction elements and techniques regarding sustainability and life-cycle costs. This way the software provides recommendations for future constructions. Furthermore, there is an option to design existing road bridges especially for heavy duty transport. This implies a route planning tool to get quick and reliable information as to whether the bridge support structures of a transport route have been measured sufficiently for a certain heavy duty transport. The use of this expert system in bridge planning companies and building authorities will save costs massively for new and existent bridge constructions. This is achieved by consequently considering parameters like life-cycle costs and sustainability for its planning recommendations.

Keywords: expert system, planning process, road bridges, software system

Procedia PDF Downloads 265

Authors: Safa Safdar

Abstract:

Breast cancer is a type of cancer which is developed by the formation of a tumor on the breast. This tumor invades and causes different electrolyte imbalance. The present study was designed to measure the serum calcium and inorganic phosphorous levels and to check the frequency of hypercalcemia and hypophosphatemia in breast cancer patients. Serum calcium and phosphorous levels of fifty breast cancer women of 18-70 years of age group and fifty healthy women of same age group were measured by using semi-automated chemistry analyzer ( Humalyzer 3000, Human, Germany ). Significant variation in these levels was observed. The mean calcium value in BC patients was higher 9.398 mg/dl as compared to controls which were 8.694 mg/dl. Whereas the mean value of inorganic phosphorus level was lower 4.060 mg/dl in BC patients as compared to controls having 4.456 mg/dl. In this study, the frequency of hypercalcemia in Breast cancer patients was 10% i.e. only 10 out of 50 Breast cancer patients were suffering from hypercalcemia. Whereas the frequency of hypophosphatemia in this study was only 2 % i.e. only 1 out of 50 patients was suffering from hypophosphatemia. Thus it is concluded that there is a significant change in serum calcium and inorganic phosphorous levels in Breast cancer patients as the disease progresses. So, this study will be helpful for the clinicians to maintain serum calcium and phosphorous levels in Breast cancer patients and also preventing them from further complications.

Keywords: serum analysis, calcium, inorganic phosphorus, hpercalcemia hypophosphatemia

Procedia PDF Downloads 276

Authors: F. Sallem, B. Dahhou, A. Kamoun

Abstract:

In this work, the main problem considered is the detection and the isolation of the actuator fault. A new formulation of the linear system is generated to obtain the conditions of the actuator fault diagnosis. The proposed method is based on the representation of the actuator as a subsystem connected with the process system in cascade manner. The designed formulation is generated to obtain the conditions of the actuator fault detection and isolation. Detectability conditions are expressed in terms of the invertibility notions. An example and a comparative analysis with the classic formulation illustrate the performances of such approach for simple actuator fault diagnosis by using the linear model of nuclear reactor.

Keywords: actuator fault, Fault detection, left invertibility, nuclear reactor, observability, parameter intervals, system inversion

Procedia PDF Downloads 384