Search results for: software transactional memory

Authors: B. Pavan Kumar Reddy, P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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In this work, the fabrication and characterization of copper-doped zinc oxide (Cu:ZnO) based memristor devices with aluminum (Al) and indium tin oxide (ITO) metal electrodes are reported. The thin films of Cu:ZnO was synthesized using low-cost and low-temperature chemical process. The Cu:ZnO was then deposited onto ITO bottom electrodes using spin-coater technique, whereas the top electrode Al was deposited utilizing physical vapor evaporation technique. Ellipsometer was employed in order to measure the Cu:ZnO thickness and it was found to be 50 nm. Several surface and materials characterization techniques were used to study the thin-film properties of Cu:ZnO. To ascertain the efficacy of Cu:ZnO for memristor applications, electrical characterizations such as current-voltage (I-V), data retention and endurance were obtained, all being the critical parameters for next-generation memory. The I-V characteristic exhibits switching behavior with asymmetrical hysteresis loops. This work imputes the resistance switching to the positional drift of oxygen vacancies associated with respect to the Al/Cu:ZnO junction. Further, a non-linear curve fitting regression techniques were utilized to determine the equivalent circuit for the fabricated Cu:ZnO memristors. Efforts were also devoted in order to establish its potentiality for different electronic applications.

Keywords: copper doped, metal-oxides, oxygen vacancies, resistive switching

Procedia PDF Downloads 162

Authors: Velimir Monty Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

Procedia PDF Downloads 53

Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

Procedia PDF Downloads 169

Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 195

Authors: Erfan Asghari Fesaghandis, Reza Ghaffari Adli, Abbas Kianvash, Hossein Aghajani, Homa Homaie

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NiTi alloys possess magnificent superelastic, shape memory, high strength and biocompatible properties. For improving mechanical properties, foremost, superelasticity behavior, heat treatment process is carried out. In this paper, two different heat treatment methods were undertaken: (1) solid solution, and (2) aging. The effect of each treatment in a constant time is investigated. Five samples were prepared to study the structure and optimize mechanical properties under different time and temperature. For measuring the upper plateau stress, lower plateau stress and residual strain, tensile test is carried out. The samples were aged at two different temperatures to see difference between aging temperatures. The sample aged at 500 °C has a bigger crystallite size and lower amount of Ni which causes the mentioned sample to possess poor pseudo elasticity behaviour than the other aged sample. The sample aged at 460 °C has shown remarkable superelastic properties. The mentioned sample’s higher plateau is 580 MPa with the lowest residual strain (0.17%) while other samples have possessed higher residual strains. X-ray diffraction was used to investigate the produced phases.

Keywords: heat treatment, phase transformation, superelasticity, NiTi alloy

Procedia PDF Downloads 130

Authors: R. Tudugala, B. M. A. I. Balasooriya, W. M. Ediri Arachchi, R. W. M. W. K. Rathnayake, T. D. Premaratna

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Brachytherapy involves placing a source of radiation near the cancer site which gives promising prognosis for cervical cancer treatments. The purpose of this study was to evaluate the effect of random variation of treated volumes in between fractions in the 2D image based fractionated high dose rate brachytherapy for cervical cancer at National Cancer Institute Maharagama, Sri Lanka. Dose plans were analyzed for 150 cervical cancer patients with orthogonal radiographs (2D) based brachytherapy. ICRU treated volumes was modeled by translating the applicators with the help of “Multisource HDR plus software”. The difference of treated volumes with respect to the applicator geometry was analyzed by using SPSS 18 software; to derived patient population based estimates of delivered treated volumes relative to ideally treated volumes. Packing was evaluated according to bladder dose, rectum dose and geometry of the dose distribution by three consultant radiation oncologist. The difference of treated volumes depends on types of the applicators, which was used in fractionated brachytherapy. The means of the “Difference of Treated Volume” (DTV) for “Evenly activated tandem (ET)” length” group was ((X_1)) -0.48 cm3 and ((X_2)) 11.85 cm3 for “Unevenly activated tandem length (UET) group. The range of the DTV for ET group was 35.80 cm3 whereas UET group 104.80 cm3. One sample T test was performed to compare the DTV with “Ideal treatment volume difference (0.00cm3)”. It is evident that P value was 0.732 for ET group and for UET it was 0.00 moreover independent two sample T test was performed to compare ET and UET groups and calculated P value was 0.005. Packing was evaluated under three categories 59.38% used “Convenient Packing Technique”, 33.33% used “Fairly Packing Technique” and 7.29% used “Not Convenient Packing” in their fractionated brachytherapy treatments. Random variation of treated volume in ET group is much lower than UET group and there is a significant difference (p<0.05) in between ET and UET groups which affects the dose distribution of the treatment. Furthermore, it can be concluded nearly 92.71% patient’s packing were used acceptable packing technique at NCIM, Sri Lanka.

Keywords: brachytherapy, cervical cancer, high dose rate, tandem, treated volumes

Procedia PDF Downloads 201

Authors: Pedram Saadati, Zahra Nazari

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Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

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Authors: Swathi M. Vanniarajan

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Reading research suggests that online contextual vocabulary comprehension while reading is an interactive and integrative process. One’s success in it depends on a variety of factors including the amount and the nature of available linguistic and nonlinguistic cues, his/her analytical and integrative skills, schema memory (content familiarity), and processing speed characterized along the continuum of controlled to automatic processing. The experiment reported here, conducted with 30 native speakers as one group and 30 nonnative speakers as another group (all graduate students), hypothesized that while working on (24) tasks which required them to comprehend an unfamiliar word in real time without backtracking, due to the differences in the nature of their respective reading processes, the nonnative subjects would be less able to construct the meanings of the unknown words by integrating the multiple but sufficient contextual cues provided in the text but the native subjects would be able to. The results indicated that there were significant inter-group as well as intra-group differences in terms of the quality of definitions given. However, when given additional time, while the nonnative speakers could significantly improve the quality of their definitions, the native speakers in general would not, suggesting that all things being equal, time is a significant factor for success in nonnative vocabulary and reading comprehension processes and that accuracy precedes automaticity in the development of nonnative reading processes also.

Keywords: reading, second language processing, vocabulary comprehension

Procedia PDF Downloads 166

Authors: Francesco Angelucci, Katerina Veverova, Alžbeta Katonová, Lydia Piendel, Martin Vyhnalek, Jakub Hort

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Alzheimer's disease (AD) is a central nervous system (CNS) disease characterized by loss of memory, cognitive functions and neurodegeneration. Plasmin is an enzyme degrading many plasma proteins. In the CNS, plasmin may reduce the accumulation of A, and have other actions relevant to AD pathophysiology. Brain plasmin synthesis is regulated by two enzymes: one activating, the tissue plasminogen activator (tPA), and the other inhibiting, the plasminogen activator inhibitor-1 (PAI-1). We investigated whether tPA and PAI-1 serum levels in AD and amnestic mild cognitive impairment (aMCI) patients are altered compared to cognitively healthy controls. Moreover, we examined the PAI-1/tPA ratio in these patient groups. 40 AD, 40 aMCI and 10 healthy controls were recruited. Venous blood was collected and PAI-1 and tPA serum concentrations were quantified by sandwich ELISAs. The results showed that PAI-1 levels increased in AD and aMCI patients. This increase negatively correlated with cognitive deficit measured by MMSE. Similarly, the ratio between tPA and PAI-1 gradually increases in aMCI and AD patients. This study demonstrates that AD and aMCI patients have altered PAI-1 serum levels and PAI-1/tPA ratio. Since these enzymes are CNS regulators of plasmin, PAI-1 serum levels could be a marker reflecting a cognitive decline in AD.

Keywords: Alzheimer disease, amnestic mild cognitive impairment, plasmin, tissue-type plasminogen activator

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Authors: Phan Nghiem Vu, Le Tuan Vu, Ta Quang Tai

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The optimal construction design used during the execution of a construction project is a key factor in determining high productivity and customer satisfaction, however, this management process sometimes is carried out without care and the systematic method that it deserves, bringing negative consequences. This study proposes a knowledge management (KM) approach that will enable the intelligent use of experienced and acknowledged engineers to improve the management of construction design works for a project. Then a knowledge-based application to support this decision-making process is proposed and described. To define and design the system for the application, semi-structured interviews were conducted within five construction consulting organizations with the purpose of studying the way that the method’ optimizing process is implemented in practice and the knowledge supported with it. A system of an optimizing construction design works (OCDW) based on knowledge was developed then validated with construction experts. The OCDW was liked as a valuable tool for construction design works’ optimization, by supporting organizations to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The benefits are described as provided by the performance support system, reducing costs and time, improving product design quality, satisfying customer requirements, expanding the brand organization.

Keywords: optimizing construction design work, construction consultant organization, knowledge management, knowledge-based application

Procedia PDF Downloads 129

Authors: Sunny Deo, Eve Barnes, Peter Arnold-Smith

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Introduction: Healthcare technology is a rapidly expanding field in healthcare, with enthusiasts suggesting a revolution in the quality and efficiency of healthcare delivery based on the utilisation of better e-healthcare, including the move to paperless healthcare. The role and use of computers and programmes for healthcare have been increasing over the past 50 years. Despite this, there is no standardised method of assessing the quality of hardware and software utilised by frontline healthcare workers. Methods and subjects: Based on standard Patient Related Outcome Measures, a questionnaire was devised with the aim of providing quantitative and qualitative data on clinicians’ perspectives of their hospital’s Information Technology (IT). The survey was distributed via the Institution’s Intranet to all contracted doctors, and the survey's qualitative results were analysed. Qualitative opinions were grouped as positive, neutral, or negative and further sub-grouped into speed/usability, software/hardware, integration, IT staffing, clinical risk, and wellbeing. Analysis was undertaken on the basis of doctor seniority and by specialty. Results: There were 196 responses, with 51% from senior doctors (consultant grades) and the rest from junior grades, with the largest group of respondents 52% coming from medicine specialties. Differences in the proportion of principle and sub-groups were noted by seniority and specialty. Negative themes were by far the commonest stated opinion type, occurring in almost 2/3’s of responses (63%), while positive comments occurred less than 1 in 10 (8%). Conclusions: This survey confirms strongly negative attitudes to the current state of electronic documentation and IT in a large single-centre cohort of hospital-based frontline physicians after two decades of so-called progress to a paperless healthcare system. Greater use would provide further insights and potentially optimise the focus of development and delivery to improve the quality and effectiveness of IT for clinicians and their patients.

Keywords: information technology, electronic patient records, digitisation, paperless healthcare

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Authors: Nizar Jawad Hadi, Sajad Abd Alabbas

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Because of their ability to encapsulate and release drugs in a controlled manner, microspheres fabricated from polymer emulsions using microfluidic devices have shown promise for drug delivery applications. In this study, the effects of velocity, density, viscosity, and surface tension, as well as channel diameter, on microsphere generation were investigated using Fluent Ansys software. The software was programmed with the physical properties of the polymer emulsion such as density, viscosity and surface tension. Simulation will then be performed to predict fluid flow and microsphere production and improve the design of drug delivery applications based on changes in these parameters. The effects of capillary and Weber numbers are also studied. The results of the study showed that the size of the microspheres can be controlled by adjusting the speed and diameter of the channel. Narrower microspheres resulted from narrower channel widths and higher flow rates, which could improve drug delivery efficiency, while smaller microspheres resulted from lower interfacial surface tension. The viscosity and density of the polymer emulsion significantly affected the size of the microspheres, ith higher viscosities and densities producing smaller microspheres. The loading and drug release properties of the microspheres created with the microfluidic technique were also predicted. The results showed that the microspheres can efficiently encapsulate drugs and release them in a controlled manner over a period of time. This is due to the high surface area to volume ratio of the microspheres, which allows for efficient drug diffusion. The ability to tune the manufacturing process using factors such as speed, density, viscosity, channel diameter, and surface tension offers a potential opportunity to design drug delivery systems with greater efficiency and fewer side effects.

Keywords: polymer emulsion, microspheres, numerical simulation, microfluidic device

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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Authors: Valeria M. Bastos, Myrian A. Costa, Matheus Ambrozio, Nelson F. F. Ebecken

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In this paper a very simple and effective user administration view of computing clusters systems is implemented in order of friendly provide the configuration and monitoring of distributed application executions. The user view, the administrator view, and an internal control module create an illusionary management environment for better system usability. The architecture, properties, performance, and the comparison with others software for cluster management are briefly commented.

Keywords: big data, computing clusters, administration view, user view

Procedia PDF Downloads 331

Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems, and issues of this new era have been found and are being found like no other time in history. Brain-computer interface so-called BCI has opened the door to several new research areas and have been able to provide solutions to critical and important issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair or even a car and neurotechnology enabled the rehabilitation of the lost memory, etc. This review work presents state-of-the-art methods and improvements of canonical correlation analyses (CCA), which is an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said in a different way, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers to understand the most state-of-the-art methods available in this field with their pros and cons, along with their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the prominent methods used in this field in a hierarchical way (2) explaining pros and cons of each method and their performance (3) presenting the gaps that exist at the end of each method that can open the understanding and doors to new research and/or improvements.

Keywords: BCI, CCA, SSVEP, EEG

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Authors: Prince Mugoya, Collins Oduor Ondiek, Patrick Kanyi Wamuyu

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Refugee Job Board Website is a web-based application that provides a platform for organizations to post jobs specifically for refugees. Organizations upload job opportunities and refugees can view them on the website. The website also allows refugees to input their skills and qualifications. The methodology used to develop this system is a waterfall (traditional) methodology. Software development tools include Brackets which will be used to code the website and PhpMyAdmin to store all the data in a database.

Keywords: information technology, refugee, skills, utilization, economy, jobs

Procedia PDF Downloads 165

Authors: Haroon Jan Khan, Xian-Feng Xu, Syed Nasir Shah, Anooshay Niazi

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CNC machines are not only used on a large scale but also now become a prominent necessity among households and smaller businesses. Printed Circuit Boards manufactured by the chemical process are not only risky and unsafe but also expensive and time-consuming. A 3-axis precise CNC machine has been developed, which not only fabricates PCB but has also been used for multi-tasks just by changing the materials used and tools, making it versatile. The advanced CNC machine takes data from CAM software. The TB-6560 controller is used in the CNC machine to adjust variation in the X, Y, and Z axes. The advanced machine is efficient in automatic drilling, engraving, and cutting.

Keywords: CNC, G-code, CAD, CAM, Proteus, FLATCAM, Easel

Procedia PDF Downloads 160

Authors: Soukat Kumar Das

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Rapid industrialization and increase in population has resulted in the scarcity of suitable ground conditions. It has driven the need of ground improvement by means of reinforcement with geosynthetics with the minimum possible settlement and with maximum possible safety. Prestressing the geosynthetics offers an economical yet safe method of gaining the goal. Commercially available software PLAXIS 3D has made the analysis of prestressed geosynthetics simpler with much practical simulations of the ground. Attempts have been made so far to analyse the effect of prestressing geosynthetics and the effect of interference of footing on Unreinforced (UR), Geogrid Reinforced (GR) and Prestressed Geogrid Reinforced (PGR) soil on the load bearing capacity and the settlement characteristics of prestressed geogrid reinforced soil using the numerical analysis by using the software PLAXIS 3D. The results of the numerical analysis have been validated and compared with those given in the referred paper. The results have been found to be in very good agreement with those of the actual field values with very small variation. The GR soil has been found to be improve the bearing pressure 240 % whereas the PGR soil improves it by almost 500 % for 1mm settlement. In fact, the PGR soil has enhanced the bearing pressure of the GR soil by almost 200 %. The settlement reduction has also been found to be very significant as for 100 kPa bearing pressure the settlement reduction of the PGR soil has been found to be about 88 % with respect to UR soil and it reduced to up to 67 % with respect to GR soil. The prestressing force has resulted in enhanced reinforcement mechanism, resulting in the increased bearing pressure. The deformation at the geogrid layer has been found to be 13.62 mm for GR soil whereas it decreased down to mere 3.5 mm for PGR soil which certainly ensures the effect of prestressing on the geogrid layer. The parameter Improvement factor or conventionally known as Bearing Capacity Ratio for different settlements and which depicts the improvement of the PGR with respect to UR and GR soil and the improvement of GR soil with respect to UR soil has been found to vary in the range of 1.66-2.40 in the present analysis for GR soil and was found to be vary between 3.58 and 5.12 for PGR soil with respect to UR soil. The effect of prestressing was also observed in case of two interfering square footings. The centre to centre distance between the two footings (SFD) was taken to be B, 1.5B, 2B, 2.5B and 3B where B is the width of the footing. It was found that for UR soil the improvement of the bearing pressure was up to 1.5B after which it remained almost same. But for GR soil the zone of influence rose up to 2B and for PGR it further went up to 2.5B. So the zone of interference for PGR soil has increased by 67% than Unreinforced (UR) soil and almost 25 % with respect to GR soil.

Keywords: bearing, geogrid, prestressed, reinforced

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Authors: Samar Swaid

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Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. One of the leading companies in Design-Thinking, IDEO (Innovation, Design, Engineering Organization), defines Design-Thinking as an approach to problem-solving that relies on a set of multi-layered skills, processes, and mindsets that help people generate novel solutions to problems. Design thinking may result in new ideas, narratives, objects or systems. It is about redesigning systems, organizations, infrastructures, processes, and solutions in an innovative fashion based on the users' feedback. Tim Brown, president and CEO of IDEO, sees design thinking as a human-centered approach that draws from the designer's toolkit to integrate people's needs, innovative technologies, and business requirements. The application of design thinking has been witnessed to be the road to developing innovative applications, interactive systems, scientific software, healthcare application, and even to utilizing Design-Thinking to re-think business operations, as in the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "wow" effect on consumers. The Association of Computing Machinery task force on Data Science program states that" Data scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, the Data Science program includes design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing ways of framing computational thinking. Here, describe the fundamentals of Design-Thinking and teaching modules for data science programs.

Keywords: data science, design thinking, AI, currculum, transformation

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Authors: Roberta Gentry

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The presentation will begin with a brief literature review of the use of computer simulation in teacher education programs. This information will be summarized. Additionally, based on the literature review, advantages and disadvantages of using computer simulation in higher education will be shared. Finally, a study in which computer simulations software was used with 50 initial licensure teacher candidates in both an introductory course and a behavior management course will be shared. Candidates reflected on their experiences with using computer simulation. The instructor of the course will also share lessons learned.

Keywords: simulations, teacher education, teacher preparation, educational research

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Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

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Authors: Misra Ayse Adsiz, Selim Selvi

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In today's world, technology is competing with time. In order to catch up with the world's companies and adapt quickly to the changes, it is necessary to speed up the processes and keep pace with the rate of change of the technology. The missile system design processes, which are handled with classical methods, keep behind in this race. Because customer requirements are not clear, and demands are changing again and again in the design process. Therefore, in the system design process, a methodology suitable for the missile system design dynamics has been investigated and the processes used for catching up the era are examined. When commonly used design processes are analyzed, it is seen that any one of them is dynamic enough for today’s conditions. So a hybrid design process is established. After a detailed review of the existing processes, it is decided to focus on the Scrum Framework and Agile Philosophy. Scrum is a process framework. It is focused on to develop software and handling change management with rapid methods. In addition, agile philosophy is intended to respond quickly to changes. In this study, it is aimed to integrate Scrum framework and agile philosophy, which are the most appropriate ways for rapid production and change adaptation, into the missile system design process. With this approach, it is aimed that the design team, involved in the system design processes, is in communication with the customer and provide an iterative approach in change management. These methods, which are currently being used in the software industry, have been integrated with the product design process. A team is created for system design process. The roles of Scrum Team are realized with including the customer. A scrum team consists of the product owner, development team and scrum master. Scrum events, which are short, purposeful and time-limited, are organized to serve for coordination rather than long meetings. Instead of the classic system design methods used in product development studies, a missile design is made with this blended method. With the help of this design approach, it is become easier to anticipate changing customer demands, produce quick solutions to demands and combat uncertainties in the product development process. With the feedback of the customer who included in the process, it is worked towards marketing optimization, design and financial optimization.

Keywords: agile, design, missile, scrum

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Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

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This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic non linearity parameter was obtained by amplitude-dependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic non linearity parameter and residual strength was proposed from each test result.

Keywords: nonlinear resonance vibration method, non linearity parameter, splitting tensile strength, micro damage, post-fire-curing, fire damaged concrete

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Nandini Mohan, Elayne Ahern

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Neurocognitive deficits, as well as psychosocial dysfunction, are typically observed in major depressive disorder (MDD). These deficits persist even after a significant reduction of symptoms and remission from MDD. These deficits have also been linked to greater relapse rates. The link between neurocognitive deficits, relapse, and psychosocial functioning in MDD, on the other hand, has received little attention. This review aimed to conduct an in-depth review of the literature on the association between neurocognitive deficits, relapse, and psychosocial functioning in MDD remission. We used search terms related to MDD, MDD remission, psychosocial functioning, neurocognitive impairments, and relapse to conduct a systematic review of English-language literature in PubMed, PsycArticles, PsycINFO, Medline, and Web of Science to identify relevant studies in the area from which 15 studies were identified for inclusion following an examination against inclusion/ exclusion criteria. Executive functioning, psychomotor speed, and memory were closely related to the psychosocial deficits in the phase of MDD remission. Similarly, Executive function, divided attention, and inhibition were closely related to the relapse in the phase of MDD remission. The limitations of the present review include limited and contradicting evidence that led to fewer studies being included. The implications of this review include an understanding of the difference between clinical and full-functional recovery. This evidence can be the basis for incorporating treatment measures that focus on neurocognitive and psychosocial deficits along with the affective symptoms of MDD.

Keywords: depression, MDD, remission, relapse, neurocognitive functioning, psychosocial deficits

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Authors: M. Sohrabi Narciss

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Urban spaces of Tehran, the capital of Iran, have witnessed many revolts, movements, and protests during the past few decades. After the Iranian Constitutional Revolution, the 1979 Revolution has had a profound impact on Tehran’s urban space. In 1979, the world watched as Iranians demonstrated en masse against the Pahlavi dynastdy which eventually led to its overthrow. Tehran’s public space is replete with images and artwork that depict the overthrow of the Pahlavi regime and the establishment of an Islamic government in Iran. The public artworks related to the 1979 Islamic Revolution reflect the riots, protests, and strikes that the Iranians underwent during the revolution. Many of these artworks try to revitalize the events that occurred in the 1970s by means of collective memory. Almost 4 decades have passed since the revolution and ever since the public artwork has been affected either directly or indirectly by the Iran-Iraq War, the Green Movement, and the rise and fall of various political forces. The present study is an attempt to investigate Tehran’s urban artwork such as urban sculptures and mural paintings organized and supervised by the government and the graffiti drawn by the critics or the opposition groups. To this end, in addition to the available documents, field research and questionnaires were used to qulaitatively analyze the data. This paper tries to address the following questions: 1) what changes have occurred in Tehran’s urban art? 2) Does the public, revolution-related artwork have an effect on people’s vitality? 3) do Iranians find these artworks appealing or not?

Keywords: public space, Tehran, public art, movement, Islamic revolution

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

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Authors: Soroush Momeni

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Excellent damping capacity and superelasticity of the bulk NiTi shape memory alloy (SMA) makes it a suitable material of choice for tools in machining process as well as tribological systems. Although thin film of NiTi SMA has a same damping capacity as NiTi bulk alloys, it has a poor mechanical properties and undesirable tribological performance. This study aims at eliminating these application limitations for NiTi SMA thin films. In order to achieve this goal, NiTi thin films were magnetron sputtered as an interlayer between reactively sputtered hard TiCN coatings and hard work tool steel substrates. The microstructure, composition, crystallographic phases, mechanical and tribological properties of the deposited thin films were analyzed by using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), nanoindentation, ball–on-disc, scratch test, and three dimensional (3D) optical microscopy. It was found that under a specific coating architecture, the superelasticity of NiTi inter-layer can be combined with high hardness and wear resistance of TiCN protective layers. The obtained results revealed that the thickness of NiTi interlayers is an important factor controlling mechanical and tribological performance of bi-layer composite coating systems.

Keywords: PVD coatings, sliding wear, hardness, tool steel

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