Search results for: video time

Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Pieter van den Berg, Retief Broodryk, Bert Moolman

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Firstly, this study aimed to identify which performance indicators (PIs) discriminate between winning and losing university-level Rugby Union (RU) teams and, secondly, to compare the significant PIs in RU and Rugby Union Sevens (RS) at university level. Understanding the importance of PIs and their effect on match outcomes could assist coaching staff to prioritise specific game aspects during training to increase performance. Twenty randomly selected round-robin matches of the 2018 Varsity Cup (n=20), and Varsity Sports sevens (n=20) tournaments were analysed. A linear mixed model was used to determine statistical significant differences set at p≤0.05 while effect size was reported according to Cohen's d value. Results revealed that various PIs discriminated between winning and losing RU teams and that specific PIs could be observed as significant in both RU and RS. Therefore, specific identified tactical aspects of RU and RS should be prioritised to optimise performance

Keywords: match success, notational analysis, performance analysis, rugby, video analysis

Procedia PDF Downloads 56

Authors: Sruthi Kannan

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The ongoing covid pandemic has accelerated digital transformation like never before. The physical barriers brought in as a result of the pandemic are being bridged by digital alternatives. While basic collaborative activities like voice, video calling, screen sharing have been replicated in these alternatives, there are several others that require a more intimate setup. Pitching, showcasing, and providing demonstrations are an integral part of selling strategies for startups. Traditionally these have been in-person engagements, enabling a depth of understanding of the startups’ offerings. In the new normal scenario of virtual-only connects, startups are feeling the brunt of the lack of in-person connections with potential customers and investors. This poster demonstrates how a virtual reality platform has been conceptualized and custom-built for startups to engage with their stakeholders and redefine their selling strategies. This virtual reality platform is intended to provide an immersive experience for startup showcases and offers the nearest possible alternative to physical meetings for the startup ecosystem, thereby opening newer frontiers for entrepreneurial collaborations.

Keywords: collaboration, sales, startups, strategy, virtual reality

Procedia PDF Downloads 291

Authors: Komal Ghafoor, Tauqir Ahmad, Murtaza Hanif, Hira Zaheer

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Assistive technology has been developed to support visually impaired people in their social interactions. Conversation assistive technology is designed to enhance communication skills, facilitate social interaction, and improve the quality of life of visually impaired individuals. This technology includes speech recognition, text-to-speech features, and other communication devices that enable users to communicate with others in real time. The technology uses natural language processing and machine learning algorithms to analyze spoken language and provide appropriate responses. It also includes features such as voice commands and audio feedback to provide users with a more immersive experience. These technologies have been shown to increase the confidence and independence of visually impaired individuals in social situations and have the potential to improve their social skills and relationships with others. Overall, conversation-assistive technology is a promising tool for empowering visually impaired people and improving their social interactions. One of the key benefits of conversation-assistive technology is that it allows visually impaired individuals to overcome communication barriers that they may face in social situations. It can help them to communicate more effectively with friends, family, and colleagues, as well as strangers in public spaces. By providing a more seamless and natural way to communicate, this technology can help to reduce feelings of isolation and improve overall quality of life. The main objective of this research is to give blind users the capability to move around in unfamiliar environments through a user-friendly device by face, object, and activity recognition system. This model evaluates the accuracy of activity recognition. This device captures the front view of the blind, detects the objects, recognizes the activities, and answers the blind query. It is implemented using the front view of the camera. The local dataset is collected that includes different 1st-person human activities. The results obtained are the identification of the activities that the VGG-16 model was trained on, where Hugging, Shaking Hands, Talking, Walking, Waving video, etc.

Keywords: dataset, visually impaired person, natural language process, human activity recognition

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Authors: Christina Knorr

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Analysis of the evacuation of occupants of a building plays a significant role in Fire Safety Engineering. One of the tools used for the analysis is the concept of the Required Safe Egress Time (RSET). It is generally accepted that RSET is measured from the time the fire ignites until the time that all occupants have evacuated to a safe location. Instructions on how RSET is determined can be found in both the International Fire Engineering Guidelines and, more recently, in the Australian Fire Engineering Guidelines. The guidelines also specify measures that could be applied to reduce the RSET and hence improve the performance of fire-safety measures of a building. Further, it is suggested that the delay period can be reduced through “training programs.” This study examined the overall level of fire-safety awareness among occupants of residential apartment buildings in Australia and investigated the possible effects of fire-safety training on the delay period and, hence, the RSET. A questionnaire, interviews, and an experiment were conducted to collect data about people’s fire-safety knowledge, people’s behaviour and nature, and the duration of activities people are likely to undertake in the event of a fire. The study led to an investigation into the delay and response time approximations and the development of a new equation to incorporate the impact of training into the RSET calculations for the general use of the fire engineering community. Regardless of the RSET, it can be concluded that fire-safety education and training for residents of apartment buildings have a direct impact on improving their behaviour and firefighting equipment usage in a fire incident.

Keywords: fire safety engineering, fire safety training, occupant evacuation behaviour, required safe egress time

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Authors: Preeti Panthari, Harsha Kharkwal

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Myrica nagi belongs to Myricaceae family. It is known for its therapeutic use since ancient times. The leaves were extracted with methanol and further fractioned with different solvents with increasing polarity. The n-butanol fraction of methanol extract was passed through celite, on separation through silica gel column chromatography yielded ten fractions. For the first time we report isolation of Caffeic acid from n-butanol fraction of Myrica nagi leaves in Chloroform: methanol (70:30) fraction. The mobile phase used for analysis in HPLC was Methanol: water (60:40) at the flow rate of 1 ml/min at wavelength of 280 nm. The retention time was 2.66 mins.

Keywords: Myrica nagi, column chromatography, retention time, caffeic acid

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Authors: Ali W. Alattabi, Khalid S. Hashim, Hassnen M. Jafer, Ali Alzeyadi

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This study was performed to optimise the react time (RT) and study its effects on the removal rates of nitrogen compounds in a sequencing batch reactor (SBR) treating synthetic industrial wastewater. The results showed that increasing the RT from 4 h to 10, 16 and 22 h significantly improved the nitrogen compounds’ removal efficiency, it was increased from 69.5% to 95%, 75.7 to 97% and from 54.2 to 80.1% for NH₃-N, NO₃-N and NO₂-N respectively. The results obtained from this study showed that the RT of 22 h was the optimum for nitrogen compounds removal efficiency.

Keywords: ammonia-nitrogen, retention time, nitrate, nitrite, sequencing batch reactor, sludge characteristics

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Authors: Janice Haworth, Karamoko Camara, Marie-Therèse Dramou, Kokoly Haba, Daniel Léno, Augustin Mara, Adama Noël Oulari, Silafa Tolno, Noël Zoumanigui

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The traditional rhythms of the West African country of Guinea have played a centuries-long role in defining the different people groups that make up the country. Throughout their history, before and since colonization by the French, the different ethnicities have used their traditional music as a distinct part of their historical identities. That is starting to change. Guinea is an impoverished nation created in the early twentieth-century with little regard for the history and cultures of the people who were included. The traditional rhythms of the different people groups and their heritages have remained. Fifteen individual traditional Guinean rhythms were chosen to represent popular rhythms from the four geographical regions of Guinea. Each rhythm was traced back to its native village and video recorded on-site by as many different local performing groups as could be located. The cyclical patterns rhythms were transcribed via a circular, spatial design and then copied into a box notation system where sounds happening at the same time could be studied. These rhythms were analyzed for their consistency-over-performance in a Fundamental Rhythm Pattern analysis so rhythms could be compared for how they are changing through different performances. The analysis showed that the traditional rhythm performances of the Middle and Forest Guinea regions were the most cohesive and showed the least evidence of change between performances. The role of music in each of these regions is both limited and focused. The Coastal and High Guinea regions have much in common historically through their ethnic history and modern-day trade connections, but the rhythm performances seem to be less consistent and demonstrate more changes in how they are performed today. In each of these regions the role and usage of music is much freer and wide-spread. In spite of advances being made as a country, different ethnic groups still frequently only respond and participate (dance and sing) to the music of their native ethnicity. There is some evidence that this self-imposed musical barrier is beginning to change and evolve, partially through the development of better roads, more access to electricity and technology, the nation-wide Ebola health crisis, and a growing self-identification as a unified nation.

Keywords: cultural identity, Guinea, traditional rhythms, west Africa

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Authors: Doga Erisik, Ahmet Karaman, Gulfem Alptekin, Ozlem Durmaz Incel

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Augmented reality (AR) is a type of virtual reality aiming to duplicate real world’s environment on a computer’s video feed. The mobile application, which is built for this project (called SARAS), enables annotating real world point of interests (POIs) that are located near mobile user. In this paper, we aim at introducing a robust and simple algorithm for placing labels in an augmented reality system. The system places labels of the POIs on the mobile device screen whose GPS coordinates are given. The proposed algorithm is compared to an existing one in terms of energy consumption and accuracy. The results show that the proposed algorithm gives better results in energy consumption and accuracy while standing still, and acceptably accurate results when driving. The technique provides benefits to AR browsers with its open access algorithm. Going forward, the algorithm will be improved to more rapidly react to position changes while driving.

Keywords: accurate tagging algorithm, augmented reality, localization, location-based AR

Procedia PDF Downloads 359

Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

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Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

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Authors: Varsha Prasad, S. Sandya

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Cosmic Ray effects in microelectronics such as single event effect (SET) and total dose ionization (TID) have been of major concern in space electronics since 1970. Advanced CMOS technologies have demonstrated reduced sensitivity to TID effect. However, charge pump Phase Locked Loop is very much vulnerable to single event transient effect. This paper presents an SET analysis model, where the SET is modeled as a double exponential pulse. The time domain analysis reveals that the settling time of the voltage controlled oscillator (VCO) depends on the SET pulse strength, setting the time constant and the damping factor. The analysis of the proposed SET analysis model is confirmed by the simulation results.

Keywords: charge pump, phase locked loop, SET, VCO

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Authors: Mohd Ishfaq Bhat, Navin Chandra Shahi, Umesh Chandra Lohani

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The present study aimed to evaluate the effect of microwave application in synergy with the conventional sodium chlorite delignification of rice straw biomass. For the study, Box-Behnken experimental design involving four independent parameters, each with three levels viz. microwave power (480-800 W), irradiation time (4-12 min), bleaching solution concentration (0.4-3.0%), and bleaching time (1-5h) was used. The response was taken in the form of delignification percentage. The optimization of process parameters was done through response surface methodology. The respective optimum parameters of microwave power, irradiation time, bleaching solution concentration, and bleaching time were obtained as 671 W, 8.66 min, 2.67%, and 1h. The delignification percentage achieved at optimum conditions was 93.51%. The spectral, morphological, and x-ray diffraction characteristics of the rice straw powder after delignification showed a complete absence of lignin peaks, deconstruction of lignocellulose complex, and an increase of crystallinity (from 39.8 to 61.6 %).

Keywords: lignocellulosic biomass, delignification, microwaves, rice straw, characterization

Procedia PDF Downloads 136

Authors: Annalisa Gaetani, Anna Nora Tassetti, Gianna Fabi

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The hydroacoustic technology is an efficient tool to study the sea environment: the most recent advancement in artificial habitat mapping involves acoustic systems to investigate fish abundance, distribution and behavior in specific areas. Along with a detailed high-coverage bathymetric mapping of the seabed, the high-frequency Multibeam Echosounder (MBES) offers the potential of detecting fine-scale distribution of fish aggregation, combining its ability to detect at the same time the seafloor and the water column. Surveying fish schools distribution around artificial structures, MBES allows to evaluate how their presence modifies the biological natural habitat overtime in terms of fish attraction and abundance. In the last years, artificial habitat mapping experiences have been carried out by CNR-ISMAR in the Adriatic sea: fish assemblages aggregating at offshore gas platforms and artificial reefs have been systematically monitored employing different kinds of methodologies. This work focuses on two case studies: a gas extraction platform founded at 80 meters of depth in the central Adriatic sea, 30 miles far from the coast of Ancona, and the concrete and steel artificial reef of Senigallia, deployed by CNR-ISMAR about 1.2 miles offshore at a depth of 11.2 m . Relating the MBES data (metrical dimensions of fish assemblages, shape, depth, density etc.) with the results coming from other methodologies, such as experimental fishing surveys and underwater video camera, it has been possible to investigate the biological assemblage attracted by artificial structures hypothesizing which species populate the investigated area and their spatial dislocation from these artificial structures. Processing MBES bathymetric and water column data, 3D virtual scenes of the artificial habitats have been created, receiving an intuitive-looking depiction of their state and allowing overtime to evaluate their change in terms of dimensional characteristics and depth fish schools’ disposition. These MBES surveys play a leading part in the general multi-year programs carried out by CNR-ISMAR with the aim to assess potential biological changes linked to human activities on.

Keywords: artificial habitat mapping, fish assemblages, hydroacustic technology, multibeam echosounder

Procedia PDF Downloads 252

Authors: Rajeshwar S. Matche, Subhash V. Pawde, Suraj P, Sachin R. Chaudhari

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Time Temperature Indicator’s (TTI) are trending approach in a food packaging that will be insightful to have safe and hygienic food products. Currently, available TTI in the market are mostly a product specific and sometime even difficult to handle especially in supply chain as these are pre-activated and require specific storage conditions. In the present study, research focus is on the development of a cost-effective lactic acid based TTI that can work over a wide range of temperature and can be activated at time of packaging or on demand. The correlation between activation energies of colour change of the developed indicator and packed pasteurized milk spoilage with respect to time and temperature was established. Developed lactic acid based TTI strips have range of activation energy from 10.13 to 24.20 KJ/mol. We found that the developed TTI strip’s with activation energy 12.42, and 14.41KJ/mol can be correlated with spoilage activation energy of packed pasteurized milk which was 25.71 KJ/mol with factor of 2 at storage temperature 4°C. The implementation of these TTI on packed pasteurized milk allow us see visual colour change during the storage and can be fruitful to monitoring quality of the milk and understand its freshness especially in a cold supply chain, viz distributor and road vendor etc.

Keywords: pasteurised packed milk, time temperature indicator, spoilage, freshness

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Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough

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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.

Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport

Procedia PDF Downloads 247

Authors: Romain Ben Taleb, Aurélie Montarnal, Matthieu Lauras, Mathieu Dahan, Romain Miclo

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To be competitive and sustainable, any company has to maximize its value. However, unlike listed companies that can assess their values based on market shares, most Small and Medium Enterprises (SMEs) which are non-listed cannot have direct and live access to this critical information. Traditional accounting reports only give limited insights to SME decision-makers about the real impact of their day-to-day decisions on the company’s performance and value. Most of the time, an SME’s financial valuation is made one time a year as the associated process is time and resource-consuming, requiring several months and external expertise to be completed. To solve this issue, we propose in this paper a value-oriented metamodel that enables real-time and dynamic assessment of the SME’s value based on the large definition of their assets. These assets cover a wider scope of resources of the company and better account for immaterial assets. The proposal, which is illustrated in a case study, discusses the benefits of incorporating assets in the SME valuation.

Keywords: SME, metamodel, decision support system, financial valuation, assets

Procedia PDF Downloads 81

Authors: Dohun Kim

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Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

Procedia PDF Downloads 180

Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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The development of CPUs and of real-time systems based on them made it possible to use time at increasingly low resolutions. Together with the scheduling methods and algorithms, time organizing has been improved so as to respond positively to the need for optimization and to the way in which the CPU is used. This presentation contains both a detailed theoretical description and the results obtained from research on improving the performances of the nMPRA (Multi Pipeline Register Architecture) processor by implementing specific functions in hardware. The proposed CPU architecture has been developed, simulated and validated by using the FPGA Virtex-7 circuit, via a SoC project. Although the nMPRA processor hardware structure with five pipeline stages is very complex, the present paper presents and analyzes the tests dedicated to the implementation of the CPU and of the memory on-chip for instructions and data. In order to practically implement and test the entire SoC project, various tests have been performed. These tests have been performed in order to verify the drivers for peripherals and the boot module named Bootloader.

Keywords: hardware scheduler, nMPRA processor, real-time systems, scheduling methods

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Authors: Nicolò Vaiana, Giorgio Serino

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The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.

Keywords: base isolation, computational efficiency, nonlinear exponential model, nonlinear time history analysis

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Khoo Shin Yee, Lian Yee Cheng, Ong Zhi Chao, Zubaidah Ismail, Siamak Noroozi

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Structural frequency response testing is accurate in identifying the dynamic characteristic of a machinery structure. In practical perspective, conventional structural frequency response testing such as experimental modal analysis with impulse technique (also known as “impulse testing”) has limitation especially on its long acquisition time. The high acquisition time is mainly due to the redundancy procedure where the engineer has to repeatedly perform the test in 3 directions, namely the axial-, horizontal- and vertical-axis, in order to comprehensively define the dynamic behavior of a 3D structure. This is unfavorable to numerous industries where the downtime cost is high. This study proposes to reduce the testing time by using oblique impact. Theoretically, a single oblique impact can induce significant vibration responses and vibration modes in all the 3 directions. Hence, the acquisition time with the implementation of the oblique impulse technique can be reduced by a factor of three (i.e. for a 3D dynamic system). This study initiates an experimental investigation of impulse testing with oblique excitation. A motor-driven test rig has been used for the testing purpose. Its dynamic characteristic has been identified using the impulse testing with the conventional normal impact and the proposed oblique impact respectively. The results show that the proposed oblique impulse testing is able to obtain all the desired natural frequencies in all 3 directions and thus providing a feasible solution for a fast and time effective way of conducting the impulse testing.

Keywords: frequency response function, impact testing, modal analysis, oblique angle, oblique impact

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Authors: Salah Menouar, Sara Hassoul

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The dynamic of time-dependent three coupled oscillators is studied through an approach based on decoupling of them using the unitary transformation method. From a first unitary transformation, the Hamiltonian of the complicated original system is transformed to an equal but a simple one associated with the three coupled oscillators of which masses are unity. Finally, we diagonalize the matrix representation of the transformed hamiltonian by using a unitary matrix. The diagonalized Hamiltonian is just the same as the Hamiltonian of three simple oscillators. Through these procedures, the coupled oscillatory subsystems are completely decoupled. From this uncouplement, we can develop complete dynamics of the whole system in an easy way by just examining each oscillator independently. Such a development of the mechanical theory can be done regardless of the complication of the parameters' variations.

Keywords: schrödinger equation, hamiltonian, time-dependent three coupled oscillators, unitary transformation

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Authors: Misook Ahn

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This study examines the Institutional Curriculum Repository (ICR) developed with MS SharePoint. The purpose of using MS SharePoint is to organize, share, and manage the curriculum data. The ICR aims to build a centralized curriculum infrastructure, preserve all curriculum materials, and provide academic service to users (faculty, students, or other agencies). The ICR collection includes core language curriculum materials developed by each language school—foreign language textbooks, language survival kits, and audio files currently in or not in use at the schools. All core curriculum materials with audio and video files have been coded, collected, and preserved at the ICR. All metadata for the collected curriculum materials have been input by language, code, year, book type, level, user, version, and current status (in use/not in use). The qualitative content analysis, including the survey data, is used to evaluate the effectiveness of using MS SharePoint for the repository system. This study explains how to manage and preserve curriculum materials with MS SharePoint, along with challenges and suggestions for further research. This study will be beneficial to other universities or organizations considering archiving or preserving educational materials.

Keywords: digital preservation, ms sharepoint, repository, curriculum materials

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Authors: Walid Fantazi

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The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 241

Authors: Alejandro Rodríguez-Molinero, Carlos Pérez-López, Jorge Hernández-Vara, Àngels Bayes-Rusiñol, Juan Carlos Martínez-Castrillo, David A. Pérez-Martínez

Abstract:

Background: Monitoring motor symptoms in Parkinson's patients is often a complex and time-consuming task for clinicians, as Hauser's diaries are often poorly completed by patients. Recently, new automatic devices (Parkinson's holter: STAT-ON®) have been developed capable of monitoring patients' motor fluctuations. The MoMoPa-EC clinical trial (NCT04176302) investigates which of the two methods produces better clinical results. In this sub-analysis, the concordance between both methods is analyzed. Methods: In the MoMoPa-EC clinical trial, 164 patients with moderate-severe Parkinson's disease and at least two hours a day of Off will be included. At the time of patient recruitment, all of them completed a seven-day motor fluctuation diary at home (Hauser’s diary) while wearing the Parkinson's holter. In this sub-analysis, 71 patients with complete data for the purpose of this comparison were included. The intraclass correlation coefficient was calculated between the patient diary entries and the Parkinson's holter data in terms of time On, Off, and time with dyskinesias. Results: The intra-class correlation coefficient of both methods was 0.57 (95% CI: 0.3-0.74) for daily time in Off (%), 0.48 (95% CI: 0.14-0.68) for daily time in On (%), and 0.37 (95% CI %: -0.04-0.62) for daily time with dyskinesias (%). Conclusions: Both methods have a moderate agreement with each other. We will have to wait for the results of the MoMoPa-EC project to estimate which of them has the greatest clinical benefits. Acknowledgment: This work is supported by AbbVie S.L.U, the Instituto de Salud Carlos III [DTS17/00195], and the European Fund for Regional Development, 'A way to make Europe'.

Keywords: Parkinson, sensor, motor fluctuations, dyskinesia

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Authors: Ersin Sener, Ibrahim Demir, Hasan Aykut Karaboga, Kadir Kilinc

Abstract:

Bayesian methods, which have very wide range of applications, are implemented to the data obtained from the production of F class fly ash-based geopolymer bricks’ experimental design. In this study, dependent variable is compressive strength, independent variables are treatment type (oven and steam), treatment time, molding time, temperature, water absorbtion ratio and density. The effect of independent variables on compressive strength is investigated. There is no difference among treatment types, but there is a correlation between independent variables. Therefore, hierarchical Bayesian path analysis is applied. In consequence of analysis we specified that treatment time, temperature and density effects on compressive strength is higher, molding time, and water absorbtion ratio is relatively low.

Keywords: experimental design, F class fly ash, geopolymer bricks, hierarchical Bayesian path analysis

Procedia PDF Downloads 372

Authors: Aswathi Thrivikraman, S. Advaith

Abstract:

The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

Procedia PDF Downloads 141

Authors: Savaş Karpuz, Sami Küçükşen

Abstract:

The aim of this study is to investigate the effectiveness of neurological rehabilitation in patients with traumatic brain injury. Participants were 45 consecutive adults with traumatic brain injury who were received the neurologic rehabilitation. Sociodemographic characteristics of the patients, the cause of the injury, the duration of the coma and posttraumatic amnesia, the length of stay in the other inpatient clinics before rehabilitation, the time between injury and admission to the rehabilitation clinic, and the length of stay in the rehabilitation clinic were recorded. The differences in functional status between admission and discharge were determined with Disability Rating Scale (DRS), Functional Independence Measure (FIM), and Functional Ambulation Scale (FAS) and levels of cognitive functioning determined with Ranchos Los Amigos Scale (RLAS). According to admission time, there was a significant improvement identified in functional status of patients who had been given the intensive in-hospital cognitive rehabilitation program. At discharge time, the statistically significant differences were obtained in DRS, FIM, FAS and RLAS scores according to admission time. Better improvement in functional status was detected in patients with lower scores in DRS, and higher scores FIM and RLAS scores at the entry time. The neurologic rehabilitation significantly affects the recovery of functional status after traumatic brain injury.

Keywords: traumatic brain injury, rehabilitation, functional status, neurological

Procedia PDF Downloads 221

Authors: Aziz Sezgin, Yuksel Hacioglu, Nurkan Yagiz

Abstract:

Sliding mode controller for a vehicle active suspension system is designed in this study. The widely used quarter car model is preferred and it is aimed to improve the ride comfort of the passengers. The effect of the actuator time delay, which may arise due to the information processing, sensors or actuator dynamics, is also taken into account during the design of the controller. A sliding mode controller was designed that has taken into account the actuator time delay by using Smith predictor. The successful performance of the designed controller is confirmed via numerical results.

Keywords: sliding mode control, active suspension system, actuator, time delay, vehicle

Procedia PDF Downloads 399