Search results for: real time acquisition

Authors: Sudip Subedi, Nipesh Pradhananga

Abstract:

The musculoskeletal disorders, also known as MSDs, are common in construction workers. MSDs include lower back injuries, knee injuries, spinal injuries, and joint injuries, among others. Since most construction tasks are still manual, construction workers often need to perform repetitive, labor-intensive tasks. And they need to stay in the same or an awkward posture for an extended time while performing such tasks. It induces significant stress to the joints and spines, increasing the risk of getting into MSDs. Manual monitoring of such tasks is virtually impossible with the handful of safety managers in a construction site. This paper proposes a methodology for performing kinetic analysis of the working postures while performing such tasks in real-time. Skeletal of different workers will be tracked using a depth-sensing camera while performing the task to create training data for identifying the best posture. For this, the kinetic analysis will be performed using a human musculoskeletal model in an open-source software system (OpenSim) to visualize the stress induced by essential joints. The “safe posture” inducing lowest stress on essential joints will be computed for different actions involved in the task. The identified “safe posture” will serve as a basis for real-time monitoring and identification of awkward and unsafe postural behaviors of construction workers. Besides, the temporal simulation will be carried out to find the associated long-term effect of repetitive exposure to such observed postures. This will help to create awareness in workers about potential future health hazards and encourage them to work safely. Furthermore, the collected individual data can then be used to provide need-based personalized training to the construction workers.

Keywords: construction workers’ safety, depth sensing camera, human body kinetics, musculoskeletal disorders, real time monitoring, repetitive labor-intensive tasks

Procedia PDF Downloads 130

Authors: Alireza Ansariyar, Mansoureh Jeihani

Abstract:

Light Detection and Ranging (LiDAR) sensors are capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore City. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By using an innovative image-processing algorithm, a new safety Measure of Effectiveness (MOE) was proposed to recognize the critical zones for bicyclists entering each zone. Considering the trajectory of conflicts, the results of the analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.

Keywords: LiDAR sensor, post encroachment time threshold (PET), vehicle-bike conflicts, a measure of effectiveness (MOE), weather condition

Procedia PDF Downloads 236

Authors: Emmanuel U. Oleka, Anil Khanal, Gary L. Lebby, Ali R. Osareh

Abstract:

Synchrophasor technology is fast being deployed in electric power grids all over the world and is fast changing the way the grids are managed. This trend is to continue until the entire power grids are fully connected so they can be monitored and controlled in real-time. Much achievement has been made in the synchrophasor technology development and deployment, and much more are yet to be achieved. Real-time power grid control and protection potentials of synchrophasor are yet to be explored. It is of necessity that researchers keep in view the various challenges that still need to be overcome in expanding the frontiers of synchrophasor technology. This paper outlines the major challenges that should be dealt with in order to achieve the goal of total power grid visualization, monitoring and control using synchrophasor technology.

Keywords: electric power grid, grid visualization, phasor measurement unit, synchrophasor

Procedia PDF Downloads 556

Authors: Andrey Matyukhin

Abstract:

Russian official statistics have been showing a steady decline in residential real estate prices for several consecutive years. Price risk in real estate markets is thus affecting various groups of economic agents, namely, individuals, construction companies and financial institutions. Potential use of property derivatives might help mitigate adverse consequences of negative price dynamics. Unless a sustainable price indicator is developed, settlement of such instruments imposes constraints on counterparties involved while imposing restrictions on real estate market development. The study addresses geographical and classification heterogeneity in real estate prices by means of variance analysis in various groups of real estate properties. In conclusion, we determine optimal sample structure of representative real estate assets with sufficient level of price homogeneity. The composite price indicator based on the sample would have a higher level of robustness and reliability and hence improving liquidity in the market for property derivatives through underlying standardization. Unlike the majority of existing real estate price indices, calculated on country-wide basis, the optimal indices for Russian market shall be constructed on the city-level.

Keywords: price homogeneity, property derivatives, real estate price index, real estate price risk

Procedia PDF Downloads 307

Authors: Radek Malinský, Ivan Jelínek

Abstract:

The current web has become a modern encyclopedia, where people share their thoughts and ideas on various topics around them. Such kind of encyclopedia is very useful for other people who are looking for answers to their questions. However, with the growing popularity of social networking and blogging and ever expanding network services, there has also been a growing diversity of technologies along with different structure of individual websites. It is, therefore, difficult to directly find a relevant answer for a common Internet user. This paper presents a web application for the real-time end-to-end analysis of selected Internet trends; where the trend can be whatever the people post online. The application integrates fully configurable tools for data collection and analysis using selected webometric algorithms, and for its chronological visualization to user. It can be assumed that the application facilitates the users to evaluate the quality of various products that are mentioned online.

Keywords: Trend, visualizer, web analysis, web 2.0.

Procedia PDF Downloads 264

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

Abstract:

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 352

Authors: Jonas P. Reges, Jessyca A. Bessa, Auzuir R. Alexandria

Abstract:

The research came up with the need of monitoring them of temperature and relative moisture in past work that enveloped the study of a greenhouse located in the Research and Extension Unit(UEPE). This research brought several unknowns that were resolved from bibliographical research. Based on the studies performed were found some monitoring methods, including the serial communication between the arduino and matlab which showed a great option due to the low cost. The project was conducted in two stages, the first, an algorithm was developed to the Arduino and Matlab, and second, the circuits were assembled and performed the monitoring tests the following variables: moisture, temperature, and distance. During testing it was possible to momentarily observe the change in the levels of monitored variables. The project showed satisfactory results, such as: real-time verification of the change of state variables, the low cost of acquisition of the prototype, possibility of easy change of programming for the execution of monitoring of other variables. Therefore, the project showed the possibility of monitoring through software and hardware that have easy programming and can be used in several areas. However, it is observed also the possibility of improving the project from a remote monitoring via Bluetooth or web server and through the control of monitored variables.

Keywords: automation, monitoring, programming, arduino, matlab

Procedia PDF Downloads 515

Authors: E. Calil, L. A. Pereira

Abstract:

The acquisition of orthography is a complex process, involving both lexical and grammatical questions. This learning occurs simultaneously with the domain of multiple textual aspects (e.g.: graphs, punctuation, etc.). However, most of the research on orthographic acquisition focus on this acquisition from an autonomous point of view, separated from the process of textual production. This means that their object of analysis is the production of words selected by the researcher or the requested sentences in an experimental and controlled setting. In addition, the analysis of the Spelling Problems (SP) are identified by the researcher on the sheet of paper. Considering the perspective of Textual Genetics, from an enunciative approach, this study will discuss the SPs recognized by dyads of newly literate students, while they are writing a text collaboratively. Six proposals of textual production were registered, requested by a 2nd year teacher of a Portuguese Primary School between January and March 2015. In our case study we discuss the SPs recognized by the dyad B and L (7 years old). We adopted as a methodological tool the Ramos System audiovisual record. This system allows real-time capture of the text in process and of the face-to-face dialogue between both students and their teacher, and also captures the body movements and facial expressions of the participants during textual production proposals in the classroom. In these ecological conditions of multimodal registration of collaborative writing, we could identify the emergence of SP in two dimensions: i. In the product (finished text): SP identification without recursive graphic marks (without erasures) and the identification of SPs with erasures, indicating the recognition of SP by the student; ii. In the process (text in progress): identification of comments made by students about recognized SPs. Given this, we’ve analyzed the comments on identified SPs during the text in progress. These comments characterize a type of reformulation referred to as Commented Oral Erasure (COE). The COE has two enunciative forms: Simple Comment (SC) such as ' 'X' is written with 'Y' '; or Unfolded Comment (UC), such as ' 'X' is written with 'Y' because...'. The spelling COE may also occur before or during the SP (Early Spelling Recognition - ESR) or after the SP has been entered (Later Spelling Recognition - LSR). There were 631 words entered in the 6 stories written by the B-L dyad, 145 of them containing some type of SP. During the text in progress, the students recognized orally 174 SP, 46 of which were identified in advance (ESRs) and 128 were identified later (LSPs). If we consider that the 88 erasure SPs in the product indicate some form of SP recognition, we can observe that there were twice as many SPs recognized orally. The ESR was characterized by SC when students asked their colleague or teacher how to spell a given word. The LSR presented predominantly UC, verbalizing meta-orthographic arguments, mostly made by L. These results indicate that writing in dyad is an important didactic strategy for the promotion of metalinguistic reflection, favoring the learning of spelling.

Keywords: collaborative writing, erasure, learning, metalinguistic awareness, spelling, text production

Procedia PDF Downloads 163

Authors: Nadeem Qaiser, Sherjeel Munsif Khan, Muhammad Mustafa Hussian, Vincent Tung

Abstract:

One of the emerging fields in the detection of chronic diseases is based on the point-of-care (POC) early monitoring of the symptoms and thus provides a state-of-the-art personalized healthcare system. Nowadays, wearable and flexible sensors are being used for analyzing sweat, glucose, blood pressure, and other skin conditions. However, localized jaw-bone swelling called parotid-swelling caused by some viruses has never been tracked before. To track physical motion or deformations, strain sensors, especially piezoresistive ones, are widely used. This work, for the first time, reports carbon nanotubes (CNTs)-based piezoresistive sensing patch that is highly flexible and stretchable and can record muscle deformations in real-time. The developed patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. To calibrate the volumetric muscle expansion, we fabricated the pneumatic actuator that experienced volumetric expansion and thus redefined the gauge factor. Moreover, we employ a Bluetooth-low-energy system that can send information about muscle activity in real-time to a smartphone app. We utilized COMSOL calculations to reveal the mechanical robustness of the patch. The experiments showed the sensing patch's greater cyclability, making it a patch for personal healthcare and an excellent choice for monitoring the real-time POC monitoring of the human muscle swelling.

Keywords: piezoresistive strain sensor, FEM simulations, CNTs sensor, flexible

Procedia PDF Downloads 88

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

Procedia PDF Downloads 156

Authors: Rui Chen, Shu-min Zhou, Xiong-jie Zhang, Ren-bo Wang, Fan Huang, Bin Tang

Abstract:

During the temperature changes in reactor core, the nuclide cross section in reactor can vary with temperature, which eventually causes the changes of reactivity. To simulate the interaction between incident neutron and various materials at different temperatures on the nose, it is necessary to generate all the relevant reaction temperature-dependent cross section. Traditionally, the real time cross section generation method is used to avoid storing huge data but contains severe problems of low efficiency and adaptability for narrow energy region. Focused on the research on multi-temperature cross sections generation in real time during in neutron transport, this paper investigated the on-the-fly cross section generation method for resolved resonance region, thermal region and unresolved resonance region, and proposed the real time multi-temperature cross sections generation method based on double-exponential formula for resolved resonance region, as well as the Neville interpolation for thermal and unresolved resonance region. To prove the correctness and validity of multi-temperature cross sections generation based on wide energy region of incident neutron, the proposed method was applied in critical safety benchmark tests, which showed the capability for application in reactor multi-physical coupling simulation.

Keywords: cross section, neutron transport, numerical simulation, on-the-fly

Procedia PDF Downloads 197

Authors: Linda Dusman, Linda Baker

Abstract:

The Bearman Study of Audience Engagement examined the potential for real-time music education during online symphony orchestra concerts. It follows on the promising results of a preliminary study of STEAM (Science, Technology, Engineering, Arts, and Mathematics) education during live concerts, funded by the National Science Foundation with the Baltimore Symphony Orchestra. For the Bearman Study, audience groups were recruited to attend two previously recorded concerts of the National Orchestral Institute (NOI) in 2020 or the Utah Symphony in 2021. They used a smartphone app called EnCue to present real-time program notes about the music being performed. Short notes along with visual information (photos and score fragments) were designed to provide historical, cultural, biographical, and theoretical information at specific moments in the music where that information would be most pertinent, generally spaced 2-3 minutes apart to avoid distraction. The music performed included Dvorak Symphony No. 8 and Mahler Symphony No. 5 at NOI, and Mendelssohn Scottish Symphony and Richard Strauss Metamorphosen with the Utah Symphony, all standard repertoire for symphony orchestras. During each phase of the study (2020 and 2021), participants were randomly assigned to use the app to view program notes during the first concert or to use the app during the second concert. A total of 139 participants (67 in 2020 and 72 in 2021) completed three online questionnaires, one before attending the first concert, one immediately after the concert, and the third immediately after the second concert. Questionnaires assessed demographic background, expertise in music, engagement during the concert, learning of content about the composers and the symphonies, and interest in the future use of the app. In both phases of the study, participants demonstrated that they learned content presented on the app, evidenced by the fact that their multiple-choice test scores were significantly higher when they used the app than when they did not. In addition, most participants indicated that using the app enriched their experience of the concert. Overall, they were very positive about their experience using the app for real-time learning and they expressed interest in using it in the future at both live and streaming concerts. Results confirmed that informal real-time learning during concerts is possible and can generate enhanced engagement and interest in classical music.

Keywords: audience engagement, informal education, music technology, real-time learning

Procedia PDF Downloads 203

Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

Abstract:

Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of Supervisory Control and Data Acquisition System (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide Area Measurement System (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of MATLAB based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: GPS global positioning system, PMU phasor measurement system, WAMS wide area monitoring system, DFT, PDC

Procedia PDF Downloads 496

Authors: Omar A. A. Shaebi, Matouk M. Elamari, Salaheddin Allid

Abstract:

The Information Computing System of Monitoring (ICSM) for the Research Reactor of Tajoura Nuclear Research Centre (TNRC) stopped working since early 1991. According to the regulations, the computer is necessary to operate the reactor up to its maximum power (10 MW). The fund is secured via IAEA to develop a modern computer based data acquisition system to replace the old computer. This paper presents the development of the Labview based data acquisition system to allow automated measurements using National Instruments Hardware and its labview software. The developed system consists of SCXI 1001 chassis, the chassis house four SCXI 1100 modules each can maintain 32 variables. The chassis is interfaced with the PC using NI PCI-6023 DAQ Card. Labview, developed by National Instruments, is used to run and operate the DAQ System. Labview is graphical programming environment suited for high level design. It allows integrating different signal processing components or subsystems within a graphical framework. The results showed system capabilities in monitoring variables, acquiring and saving data. Plus the capability of the labview to control the DAQ.

Keywords: data acquisition, labview, signal conditioning, national instruments

Procedia PDF Downloads 494

Authors: Nevena Jakovčević Stor, Ivan Slapničar

Abstract:

Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

Procedia PDF Downloads 418

Authors: Zhdanova A. O., Volkov R. S., Kuznetsov G. V., Strizhak P. A.

Abstract:

Fires in different types of facilities are a serious problem worldwide.It is still an unaccomplished science and technology objective to establish the minimum number and type of sensors in automatic systems of compartment fire suppression which would turn the fire-extinguishing agent spraying on and off in real time depending on the state of the fire, minimize the amount of agent applied, delay time in fire suppression and system response, as well as the time of combustion suppression. Based on the results of experimental studies, the conclusion was made that it is reasonable to use a gas analysis system and heat sensors (in the event of their prior activation) to determine the effectiveness of fire suppression (fire-extinguishing composition interacts with the fire). Thus, the concentration of CO in the interaction of the firefighting liquid with the fire increases to 0.7–1.2%, which indicates a slowdown in the flame combustion, and heat sensors stop responding at a gas medium temperature below 80 ºC, which shows a gradual decrease in the heat release from the fire. The evidence from this study suggests that the information received from the video recording equipment (video camera) should be used in real time as an additional parameter confirming fire suppression. Research was supported by Russian Science Foundation (project No 21-19-00009, https://rscf.ru/en/project/21-19-00009/).

Keywords: compartment fires, fire suppression, continuous control of fire behavior, feedback systems

Procedia PDF Downloads 129

Authors: Semanur Savruk, Onur Akbatı

Abstract:

Integration of various communication protocols into an automation system causes a rise in setup and maintenance cost and make to control network devices in difficulty. The gateway becomes necessary for reducing complexity in network topology. In this study, Modbus RTU/Modbus TCP industrial ethernet gateway design and implementation are presented with ARM embedded system and FreeRTOS real-time operating system. The Modbus gateway can perform communication with Modbus RTU and Modbus TCP devices over itself. Moreover, the gateway can be adjustable with the user-interface application or messaging interface. Conducted experiments and the results are presented in the paper. Eventually, the proposed system is a complete, low-cost, real-time, and user-friendly design for monitoring and setting devices and useful for meeting remote control purposes.

Keywords: gateway, industrial communication, modbus, network

Procedia PDF Downloads 141

Authors: Qiang Zhang, Xiaojian Hu

Abstract:

In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 163

Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 105

Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

Abstract:

This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

Procedia PDF Downloads 138

Authors: Ibrahim Umar, Ashiru Rajab, Sumayya Chindo, Emmanuel Olashore

Abstract:

INTRODUCTION: Kano is the most populous state in Nigeria and one of the two states with the highest TB burden in the country. The state notifies an average of 8,000+ TB cases quarterly and has the highest yearly notification of all the states in Nigeria from 2020 to 2022. The contribution of the state TB program to the National TB notification varies from 9% to 10% quarterly between the first quarter of 2022 and second quarter of 2023. The Kano State TB Situation Room is an innovative platform for timely data collection, collation and analysis for informed decision in health system. During the 2023 second National TB Testing week (NTBTW) Kano TB program aimed at early TB detection, prevention and treatment. The state TB Situation room provided avenue to the state for coordination and surveillance through real time data reporting, review, analysis and use during the NTBTW. OBJECTIVES: To assess the role of innovative information and communication technology platform for real-time TB reporting during second National TB Testing week in Nigeria 2023. To showcase the NTBTW data cascade analysis using TSR as innovative ICT platform. METHODOLOGY: The State TB deployed a real-time virtual dashboard for NTBTW reporting, analysis and feedback. A data room team was set up who received realtime data using google link. Data received was analyzed using power BI analytic tool with statistical alpha level of significance of <0.05. RESULTS: At the end of the week-long activity and using the real-time dashboard with onsite mentorship of the field workers, the state TB program was able to screen a total of 52,054 people were screened for TB from 72,112 individuals eligible for screening (72% screening rate). A total of 9,910 presumptive TB clients were identified and evaluated for TB leading to diagnosis of 445 TB patients with TB (5% yield from presumptives) and placement of 435 TB patients on treatment (98% percentage enrolment). CONCLUSION: The TB Situation Room (TBSR) has been a great asset to Kano State TB Control Program in meeting up with the growing demand for timely data reporting in TB and other global health responses. The use of real time surveillance data during the 2023 NTBTW has in no small measure improved the TB response and feedback in Kano State. Scaling up this intervention to other disease areas, states and nations is a positive step in the right direction towards global TB eradication.

Keywords: tuberculosis (tb), national tb testing week (ntbtw), tb situation rom (tsr), information communication technology (ict)

Procedia PDF Downloads 71

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 72

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

Abstract:

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

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

Procedia PDF Downloads 89

Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

Abstract:

This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

Procedia PDF Downloads 78

Authors: Andrey V. Timofeev

Abstract:

The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

Procedia PDF Downloads 470

Authors: Ates Gul Ergun, Melda Tacyildiz

Abstract:

The current study focuses on the relationship between the personality traits and starting a romantic relationship on social media. It is interested in the study whether there are any personality trait differences between individuals who started their romantic relationships on social media platforms or through circle of friends in daily life. Sixty five participants between the ages of 18-30 filled out a three-question-survey about romantic relationships and social media, with the Big Five Inventory. Four separate independent samples t tests comparing agreeableness and extraversion scores on the environment of participants first interacted (online vs. real-life) and where they fırst meet without interaction (online vs. real-life) were carried out. The results indicated that there was a statistically significant difference between people who had the first interaction with their partner online vs. real-life in terms of extraversion and agreeableness traits. The more extrovert and agreeable traits reported the more people were likely to interact with their partner through circle of friends in real-life. Furthermore, it was found that people who are less agreeable have a tendency to interact with their partners in social media for the first time. However, there was no statistically significant difference between how participants met with their partners without interaction (online vs. real-life) in terms of extraversion and agreeableness traits. This study has shown the relationships between personality traits and starting a romantic relationship on social media versus in real-life but not the reasons behind it. Further research could examine such reasons. In addition, the data only includes Turkish sample. By virtue of the cultural restriction in the present study, it is suggested that the future research should also include different cultures to investigate how people spend time with their friends and also in social media which can be changed according to individualism levels of countries. Overall, the study emphasizes the importance and the role of social media in individual’s lives, and it opens the ways associated with personal traits and social media relationships for further researches.

Keywords: agreeableness, big five, extraversion, romantic relationships, social media

Procedia PDF Downloads 147

Authors: Wei Li, Tuo Yang

Abstract:

In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

Procedia PDF Downloads 87

Authors: Monika Szymańska-Czerwińsk, Kinga Zaręba-Marchewka, Krzysztof Niemczuk

Abstract:

Chlamydiaceae are Gram-negative bacteria distributed worldwide in animals and humans. One of them is Chlamydia gallinacea recently discovered. Available data show that C. gallinacea is dominant chlamydial agent found in poultry in European and Asian countries. The aim of the studies was screening of poultry flocks in order to evaluate frequency of C. gallinacea shedding and genetic diversity. Sampling was conducted in different regions of Poland in 2019-2020. Overall, 1466 cloacal/oral swabs were collected in duplicate from 146 apparently healthy poultry flocks including chickens, turkeys, ducks, geese and quails. Dry swabs were used for DNA extraction. DNA extracts were screened using a Chlamydiaceae 23S rRNA real-time PCR assay. To identify Chlamydia species, specific real-time PCR assays were performed. Furthermore, selected samples were used for sequencing based on ompA gene fragments and variable domains (VD1-2, VD3-4). In total, 10.3% of the tested flocks were Chlamydiaceae-positive (15/146 farms). The presence of Chlamydiaceae was confirmed mainly in chickens (13/92 farms) but also in turkey (1/19 farms) and goose (1/26 farms) flocks. Eleven flocks were identified as C. gallinacea-positive while four flocks remained unclassified. Phylogenetic analysis revealed at least 16 genetic variants of C. gallinacea. Research showed that Chlamydiaceae occur in a poultry flock in Poland. The strains of C. gallinacea as dominant species show genetic variability.

Keywords: C. gallinacea, emerging agent, poultry, real-time PCR

Procedia PDF Downloads 104

Authors: Carlos Fontanillas

Abstract:

Brazil is going through a real revolution in the logistics area. It is increasingly common to find articles and news in this context, as companies begin to become aware that a good management of the areas that make up the logistics can bring excellent results in reducing costs and increasing productivity. With this, companies are investing more emphasis on reduced spending on storage and transport of their products to ensure competitiveness. The scope of this work is the analysis of the logistics of a restaurant and materials will be presented the best way to serve the customer, avoiding the interruption of production due to lack of materials; for it will be analyzed the supply chain in terms of acquisition costs, maintenance and service demand.

Keywords: ABC curve, logistic, productivity, supply chain

Procedia PDF Downloads 313

Authors: Parampal Kaur, Deepak Aggarwal

Abstract:

In the computational Grid, fault tolerance is an imperative issue to be considered during job scheduling. Due to the widespread use of resources, systems are highly prone to errors and failures. Hence, fault tolerance plays a key role in the grid to avoid the problem of unreliability. Scheduling the task to the appropriate resource is a vital requirement in computational Grid. The fittest resource scheduling algorithm searches for the appropriate resource based on the job requirements, in contrary to the general scheduling algorithms where jobs are scheduled to the resources with best performance factor. The proposed method is to improve the fault tolerance of the fittest resource scheduling algorithm by scheduling the job in coordination with job replication when the resource has low reliability. Based on the reliability index of the resource, the resource is identified as critical. The tasks are scheduled based on the criticality of the resources. Results show that the execution time of the tasks is comparatively reduced with the proposed algorithm using real-time approach rather than a simulator.

Keywords: computational grid, fault tolerance, task replication, job scheduling

Procedia PDF Downloads 436