Search results for: CMOS image sensors

Authors: Tarcisio F. Leao, Bruno Utiyama, Jeison Fonseca, Eduardo Bock, Aron Andrade

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This work presents a blood flow estimator based in Look-Up-Table (LUT) for control of Left Ventricular Assist Device (LVAD). This device has been used as bridge to transplantation or as destination therapy to treat patients with heart failure (HF). Destination Therapy application requires a high performance LVAD; thus, a stable control is important to keep adequate interaction between heart and device. LVAD control provides an adequate cardiac output while sustaining an appropriate flow and pressure blood perfusion, also described as physiologic control. Because thrombus formation and system reliability reduction, sensors are not desirable to measure these variables (flow and pressure blood). To achieve this, control systems have been researched to estimate blood flow. LVAD used in the study is composed by blood centrifugal pump, control, and power supply. This technique used pump and actuator (motor) parameters of LVAD, such as speed and electric current. Estimator relates electromechanical torque (motor or actuator) and hydraulic power (blood pump) via LUT. An in vitro Mock Loop was used to evaluate deviations between blood flow estimated and actual. A solution with glycerin (50%) and water was used to simulate the blood viscosity with hematocrit 45%. Tests were carried out with variation hematocrit: 25%, 45% and 58% of hematocrit, or 40%, 50% and 60% of glycerin in water solution, respectively. Test with bovine blood was carried out (42% hematocrit). Mock Loop is composed: reservoir, tubes, pressure and flow sensors, and fluid (or blood), beyond LVAD. Estimator based in LUT is patented, number BR1020160068363, in Brazil. Mean deviation is 0.23 ± 0.07 L/min for mean flow estimated. Larger mean deviation was 0.5 L/min considering hematocrit variation. This estimator achieved deviation adequate for physiologic control implementation. Future works will evaluate flow estimation performance in control system of LVAD.

Keywords: blood pump, flow estimator, left ventricular assist device, look-up-table

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Authors: A. Harrouz, O. Harrouz, A. Benatiallah

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This paper is to review the essential definitions, roles, and characteristics of communication of metering system. We discuss measurement, data acquisition, and metrological control of a signal sensor from dynamic metering system. After that, we present control of instruments of metering system of fluid with more detailed discussions to the reference standards.

Keywords: data acquisition, dynamic metering system, reference standards, metrological control

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Authors: Huidan Yu, Anurag Deb, Rou Chen, I-Wen Wang

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The use of left ventricle assist devices (LVADs) in patients with heart failure has been a proven and effective therapy for patients with severe end-stage heart failure. Due to the limited availability of suitable donor hearts, LVADs will probably become the alternative solution for patient with heart failure in the near future. While the LVAD is being continuously improved toward enhanced performance, increased device durability, reduced size, a better understanding of implantation management becomes critical in order to achieve better long-term blood supplies and less post-surgical complications such as thrombi generation. Important issues related to the LVAD implantation include the location of outflow grafting (OG), the angle of the OG, the combination between LVAD and native heart pumping, uniform or pulsatile flow at OG, etc. We have hypothesized that an optimal implantation of LVAD is patient specific. To test this hypothesis, we employ a novel in-house computational modeling technique, named InVascular, to conduct a systematic evaluation of cardiac output at aortic arch together with other pertinent hemodynamic quantities for each patient under various implantation scenarios aiming to get an optimal implantation strategy. InVacular is a powerful computational modeling technique that integrates unified mesoscale modeling for both image segmentation and fluid dynamics with the cutting-edge GPU parallel computing. It first segments the aortic artery from patient’s CT image, then seamlessly feeds extracted morphology, together with the velocity wave from Echo Ultrasound image of the same patient, to the computation model to quantify 4-D (time+space) velocity and pressure fields. Using one NVIDIA Tesla K40 GPU card, InVascular completes a computation from CT image to 4-D hemodynamics within 30 minutes. Thus it has the great potential to conduct massive numerical simulation and analysis. The systematic evaluation for one patient includes three OG anastomosis (ascending aorta, descending thoracic aorta, and subclavian artery), three combinations of LVAD and native heart pumping (1:1, 1:2, and 1:3), three angles of OG anastomosis (inclined upward, perpendicular, and inclined downward), and two LVAD inflow conditions (uniform and pulsatile). The optimal LVAD implantation is suggested through a comprehensive analysis of the cardiac output and related hemodynamics from the simulations over the fifty-four scenarios. To confirm the hypothesis, 5 random patient cases will be evaluated.

Keywords: graphic processing unit (GPU) parallel computing, left ventricle assist device (LVAD), lumped-parameter model, patient-specific computational hemodynamics

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Authors: Zahra Mehrabbeygi

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This research is opted to analyze and survey discourse variety and news image-making in western media regarding the news coverage of the Russian army intrusion into Ukraine. This research will be done on the news coverage of Ukraine in a period from February 2022 to May 2022 in five western media, "BBC, CBS, NBC, Al Jazeera, and Telegraph." This research attempts to discover some facts about the news policies of the five western news agencies during the circumstances of the Ukraine-Russia war. Critical theories in the news, such as Framing, Media Imperialism of News, Image Making, Discourse, and Ideology, were applied to achieve this goal. The research methodology uses Van Dijk's discourse exploration method based on discourse analysis. The research's statistical population is related to all the news about racial discrimination during the mentioned period. After a statistical population survey with Targeted Sampling, the researcher randomly selected ten news cases for exploration. The research findings show that the western media have similarities in their texts via lexical items, polarization, citations, persons, and institutions. The research findings also imply pre-suppositions, connotations, and components of consensus agreement and underlying predicates in the outset, middle, and end events. The reaction of some western media not only shows their bewilderment but also exposes their prejudices rooted in racism.

Keywords: news discourse analysis, western media, racial discrimination, Ukraine-Russia war

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Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: S. Dalvi, N. Sane, V. Patil, D. Bansode, A. Tharakan, V. Mathur

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Measurement of routine clinical electrolyte tests is common in labs worldwide for screening of illness or diseases. All the analyzers for the measurement of electrolyte parameters have sensors, reagents, sampler, pump tubing, valve, other tubing’s separate that are either expensive, require heavy maintenance and have a short shelf-life. Moreover, the costs required to maintain such Lab instrumentation is high and this limits the use of the device to only highly specialized personnel and sophisticated labs. In order to provide Healthcare Diagnostics to ALL at affordable costs, there is a need for an All-in-one Universal Modular Cartridge that contains sensors, reagents, sampler, valve, pump tubing, and other tubing’s in one single integrated module-in-module cartridge that is affordable, reliable, easy-to-use, requires very low sample volume and is truly modular and maintenance-free. DiaSys India has developed a World’s first, Patent Pending, Versatile All-in-one Universal Module-in-Module Cartridge based Electrolyte Analyzer (QDx InstaLyte) that can perform sodium, potassium, chloride, calcium, pH, lithium tests. QDx InstaLyte incorporates High Performance, Inexpensive All-in-one Universal Cartridge for rapid quantitative measurement of electrolytes in body fluids. Our proposed methodology utilizes Advanced & Improved long life ISE sensors to provide a sensitive and accurate result in 120 sec with just 100 µl of sample volume. The All-in-One Universal Cartridge has a very low reagent consumption capable of maximum of 1000 tests with a Use-life of 3-4 months and a long Shelf life of 12-18 months at 4-25°C making it very cost-effective. Methods: QDx InstaLyte analyzers with All-in-one Universal Modular Cartridges were independently evaluated with three R&D lots for Method Performance (Linearity, Precision, Method Comparison, Cartridge Stability) to measure Sodium, Potassium, Chloride. Method Comparison was done against Medica EasyLyte Plus Na/K/Cl Electrolyte Analyzer, a mid-size lab based clinical chemistry analyzer with N = 100 samples run over 10 days. Within-run precision study was done using modified CLSI guidelines with N = 20 samples and day-to-day precision study was done for 7 consecutive days using Trulab N & P Quality Control Samples. Accelerated stability testing was done at 45oC for 4 weeks with Production Lots. Results: Data analysis indicates that the CV for within-run precision for Na is ≤ 1%, for K is ≤2%, and for Cl is ≤2% and with R2 ≥ 0.95 for Method Comparison. Further, the All-in-One Universal Cartridge is stable up to 12-18 months at 4-25oC storage temperature based on preliminary extrapolated data. Conclusion: The Developed Technology Platform of All-in-One Universal Module-in-Module Cartridge based QDx InstaLyte is Reliable and meets all the performance specifications of the lab and is Truly Modular and Maintenance-Free. Hence, it can be easily adapted for low cost, sensitive and rapid measurement of electrolyte tests in low resource settings such as in urban, semi-urban and rural areas in the developing countries and can be used as a Point-of-care testing system for worldwide applications.

Keywords: all-in-one modular catridge, electrolytes, maintenance free, QDx instalyte

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Authors: Andres Gonzalez, Adam Boies, Jacob Swanson, David Kittelson

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The concern of the indoor air quality (IAQ) has been increasing due to its risk to human health. The smoking, sweeping, and stove and stovetop use are the activities that have a major contribution to the indoor air pollution. Outdoor air pollution also affects IAQ. The most important factors over IAQ from cooking activities are the materials, fuels, foods, and ventilation. The low-cost, mobile air quality monitoring (LCMAQM) sensors, is reachable technology to assess the IAQ. This is because of the lower cost of LCMAQM compared to conventional instruments. The IAQ was assessed, using LCMAQM, during cooking activities in a University of Minnesota graduate-housing evaluating different ventilation systems. The gases measured are carbon monoxide (CO) and carbon dioxide (CO₂). The particles measured are particle matter (PM) _2.5 micrometer (µm) and lung deposited surface area (LDSA). The measurements are being conducted during April 2019 in Como Student Community Cooperative (CSCC) that is a graduate housing at the University of Minnesota. The measurements are conducted using an electric stove for cooking. The amount and type of food and oil using for cooking are the same for each measurement. There are six measurements: two experiments measure air quality without any ventilation, two using an extractor as mechanical ventilation, and two using the extractor and windows open as mechanical and natural ventilation. 3The results of experiments show that natural ventilation is most efficient system to control particles and CO₂. The natural ventilation reduces the concentration in 79% for LDSA and 55% for PM_2.5, compared to the no ventilation. In the same way, CO₂ reduces its concentration in 35%. A well-mixed vessel model was implemented to assess particle the formation and decay rates. Removal rates by the extractor were significantly higher for LDSA, which is dominated by smaller particles, than for PM_2.5, but in both cases much lower compared to the natural ventilation. There was significant day to day variation in particle concentrations under nominally identical conditions. This may be related to the fat content of the food. Further research is needed to assess the impact of the fat in food on particle generations.

Keywords: cooking, indoor air quality, low-cost sensor, ventilation

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Authors: Satyam Raikwar, Thomas Herlitzius, Jens Fehrmann

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In recent years, the autonomous navigation of orchard and field robots is an emerging technology of the mobile robotics in agriculture. One of the core aspects of autonomous navigation builds upon path planning, which is still a crucial issue. Generally, for simple representation, the path planning for a mobile robot is performed in a two-dimensional space, which creates a path between the start and goal point. This paper presents the automatic path planning approach for robots used in orchards and vineyards using occupancy grid maps with field consideration. The orchards and vineyards are usually structured environment and their topology is assumed to be constant over time; therefore, in this approach, an RGB image of a field is used as a working environment. These images undergone different image processing operations and then discretized into two-dimensional grid matrices. The individual grid or cell of these grid matrices represents the occupancy of the space, whether it is free or occupied. The grid matrix represents the robot workspace for motion and path planning. After the grid matrix is described, a probabilistic roadmap (PRM) path algorithm is used to create the obstacle-free path over these occupancy grids. The path created by this method was successfully verified in the test area. Furthermore, this approach is used in the navigation of the orchard robot.

Keywords: orchard robots, automatic path planning, occupancy grid, probabilistic roadmap

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Authors: Pranee Pathomchaiwat

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This research aims to study tourism data and behavior of foreign tourists visited Wat Phrachetuponwimolmangkalaram (Wat Po) Sample groups are tourists who visited inside the temple, during February, March, April and May 2013. Tools used in the research are questionnaires constructed by the researcher, and samples are dawn by Convenience sampling. There are 207 foreign tourists who are willing to be respondents. Statistics used are percentage, average mean and standard deviation. The results of the research reveal that: A. General Data of Respondents: The foreign tourists who visited the temple are mostly female (57.5 %), most respondents are aged between 20-29 years (37.2%). Most respondents live in Europe (62.3%), most of them got the Bachelor’s degree (40.1%), British are mostly found (16.4%), respondents who are students are also found (23.2%), and Christian are mostly found (60.9%). B. Tourists’ Behavior While Visiting the Temple Compound: The result shows that the respondents came with family (46.4%), have never visited the temples (40.6%), and visited once (42 %). It is found that the foreign tourists’ inappropriate behavior are wearing revealing attires (58.9%), touching or getting closed to the monks (55.1%), and speaking loudly (46.9%) respectively. The respondents’ outstanding objectives are to visit inside the temple (57.5%), to pay respect to the Reclining Buddha Image in the Viharn (44.4%) and to worship the Buddha image in the Phra Ubosod (37.7%) respectively. C. The Respondents’ Self-evaluation of Performance: It is found that over all tourists evaluated themselves in the highest level averaged 4.40. When focusing on each item, it is shown that they evaluated themselves in the highest level on obeying the temple staff averaged 4.57, and cleanness concern of the temple averaged 4.52, well-behaved performance during the temple visit averaged 4.47 respectively.

Keywords: deportment, traveler, foreign tourists, temple

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Jasim Uddin, Rod Smith, Malcolm Gillies

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Surface irrigation is the most popular irrigation method all over the world. However, two issues: low efficiency and huge labour involvement concern irrigators due to scarcity in recent years. To address these issues, a smart automated furrow is conceptualised that can be operated using digital devices like smartphone, iPad or computer and a preliminary evaluation was conducted in this study. The smart automated system is the integration of commercially available software and hardware. It includes real-time surface irrigation optimisation software (SISCO) and Rubicon Water’s surface irrigation automation hardware and software. The automated system consists of automatic water delivery system with 300 mm flexible pipes attached to both sides of a remotely controlled valve to operate the irrigation. A water level sensor to obtain the real-time inflow rate from the measured head in the channel, advance sensors to measure the advance time to particular points of an irrigated field, a solar-powered telemetry system including a base station to communicate all the field sensors with the main server. On the basis of field data, the software (SISCO) is optimised the ongoing irrigation and determine the optimum cut-off for particular irrigation and send this information to the control valve to stop the irrigation in a particular (cut-off) time. The preliminary evaluation shows that the automated surface irrigation worked reasonably well without manual intervention. The evaluation of farmers managed irrigation events show the potentials to save a significant amount of water and labour. A substantial amount of economic and social benefits are expected in rural industries by adopting this system. The future outcome of this work would be a fully tested commercial adaptive real-time furrow irrigation system able to compete with the pressurised alternative of centre pivot or lateral move machines on capital cost, water and labour savings but without the massive energy costs.

Keywords: furrow irrigation, smart automation, infiltration, SISCO, real-time irrigation, adoptive control

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Authors: Zekun Lin, Xun Li

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Silicon photonics has gained much interest and extensive research for a promising aspect for fabricating compact, high-speed and low-cost photonic devices compatible with complementary metal-oxide-semiconductor (CMOS) process. Despite the remarkable progress made on the development of silicon photonics, high-performance, cost-effective, and reliable silicon laser sources are still missing. In this work, we present a 1550 nm III-V/silicon laser design with stable single-mode lasing property and robust and high-efficiency vertical coupling. The InP cavity consists of two uniform Bragg grating sections at sides for mode selection and feedback, as well as a central second-order grating for surface emission. A grating coupler is etched on the SOI waveguide by which the light coupling between the parallel III-V and SOI is reached vertically rather than by evanescent wave coupling. Laser characteristic is simulated and optimized by the traveling-wave model (TWM) and a Green’s function analysis as well as a 2D finite difference time domain (FDTD) method for the coupling process. The simulation results show that single-mode lasing with SMSR better than 48dB is achievable, and the threshold current is less than 15mA with a slope efficiency of around 0.13W/A. The coupling efficiency is larger than 42% and possesses a high tolerance with less than 10% reduction for 10 um horizontal or 15 um vertical dislocation. The design can be realized by standard flip-chip bonding techniques without co-fabrication of III-V and silicon or precise alignment.

Keywords: III-V/silicon integration, silicon photonics, single mode laser, vertical coupling

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Zhuang Hou, Xiaolei Cao

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The general public and medical professionals recognized the importance of accurately measuring and storing blood oxygen levels and heart rate during the COVID-19 pandemic. The demand for accurate contactless devices was motivated by the need for cross-infection reduction and the shortage of conventional oximeters, partially due to the global supply chain issue. This paper evaluated a contactless mini program HealthyPai’s heart rate (HR) and oxygen saturation (SpO2) measurements compared with other wearable devices. In the HR study of 185 samples (81 in the laboratory environment, 104 in the real-life environment), the mean absolute error (MAE) ± standard deviation was 1.4827 ± 1.7452 in the lab, 6.9231 ± 5.6426 in the real-life setting. In the SpO2 study of 24 samples, the MAE ± standard deviation of the measurement was 1.0375 ± 0.7745. Our results validated that HealthyPai utilizing the Integrated Image Deep Learning Solution (IIDLS) framework, can accurately measure HR and SpO2, providing the test quality at least comparable to other FDA-approved wearable devices in the market and surpassing the consumer-grade and research-grade wearable standards.

Keywords: remote photoplethysmography, heart rate, oxygen saturation, contactless measurement, mini program

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Authors: Moumen Abdelhafidh, Stribu Bogdan, Laboureur Delphine, Gallant Johan, Hendrick Patrick

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This study is part of an ongoing effort to improve the understanding of phenomena occurring during the intermediate ballistic phase, such as muzzle flows. A thorough comprehension of muzzle flow fields is essential for optimizing muzzle device and projectile design. This flow characterization has heretofore been almost entirely limited to local and intrusive measurement techniques such as pressure measurements using pencil probes. Consequently, the body of quantitative experimental data is limited, so is the number of numerical codes validated in this field. The objective of the work presented here is to demonstrate the applicability of the Particle Image Velocimetry (PIV) technique in the challenging environment of the propellant flow of a .300 blackout weapon to provide accurate velocity measurements. The key points of a successful PIV measurement are the selection of the particle tracer, their seeding technique, and their tracking characteristics. We have experimentally investigated the aforementioned points by evaluating the resistance, gas dispersion, laser light reflection as well as the response to a step change across the Mach disk for five different solid tracers using two seeding methods. To this end, an experimental setup has been performed and consisted of a PIV system, the combustion chamber pressure measurement, classical high-speed schlieren visualization, and an aerosol spectrometer. The latter is used to determine the particle size distribution in the muzzle flow. The experimental results demonstrated the ability of PIV to accurately resolve the salient features of the propellant flow, such as the under the expanded jet and vortex rings, as well as the instantaneous velocity field with maximum centreline velocities of more than 1000 m/s. Besides, naturally present unburned particles in the gas and solid ZrO₂ particles with a nominal size of 100 nm, when coated on the propellant powder, are suitable as tracers. However, the TiO₂ particles intended to act as a tracer, surprisingly not only melted but also functioned as a combustion accelerator and decreased the number of particles in the propellant gas.

Keywords: intermediate ballistic, muzzle flow fields, particle image velocimetry, propellant gas, particle size distribution, under expanded jet, solid particle tracers

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Authors: Si-Jie Ji, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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With the rapid development of industrialization and urbanization, air pollution poses significant global environmental challenges, contributing to acid rain, global warming, and adverse health effects. Therefore, it is necessary to monitor the concentration of toxic gases in the atmospheric environment in real-time and to deploy cost-effective gas sensors capable of detecting their emissions. In this study, we systematically investigated the sensing capabilities of the two-dimensional MoSe₂ for seven key environmental gases (NO, NO₂, CO, CO₂, SO₂, SO₃, and O₂) using density functional theory (DFT) and non-equilibrium Green’s function (NEGF) calculations. We also investigated the impact of H₂O as an interfering gas. Our results indicate that the MoSe₂ monolayer is thermodynamically stable and exhibits strong gas-sensing capabilities. The calculated adsorption energies indicate that these gases can stably adsorb on MoSe₂, with SO₃ exhibiting the strongest adsorption energy (-0.63 eV). Electronic structure analysis, including projected density of states (PDOS) and Bader charge analysis, demonstrates significant changes in the electronic properties of MoSe₂ upon gas adsorption, affecting its conductivity and sensing performance. We find that oxygen (O₂) adsorption notably influenced the deformation of MoSe₂. To comprehensively understand the potential of MoSe₂ as a gas sensor, we used the NEGF method to assess the electronic transport properties of MoSe₂ under gas adsorption, evaluating current-voltage (I-V), resistance-voltage (R-V) characteristics, and transmission spectra to determine sensitivity, selectivity, and recovery time compared to pristine MoSe₂. Sensitivity, selectivity, and recovery time are analyzed at a bias voltage of 1.7V, showing excellent performance of MoSe₂ in detecting SO₃, among other gases. The pronounced changes in electronic transport behavior induced by SO₃ adsorption confirm MoSe₂’s strong potential as a high-performance gas-sensing material. Overall, this theoretical study provides new insights into the development of high-performance gas sensors, demonstrating the potential of MoSe₂ as a gas-sensing material, particularly for gases like SO₃.

Keywords: density functional theory, gas sensing, MoSe₂, non-equilibrium Green’s function, SO

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Authors: Abdelrahman Elsehsah

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Land Use and Land Cover (LULC) dynamics in Riyadh over a decade were comprehensively analyzed using the Google Earth Engine (GEE) platform. By harnessing the Landsat 8 Image collection and night-time light image collection from May to August for the years 2013 and 2023, we were able to generate insightful datasets capturing the changing landscape of the region. Our approach involved a Random Forest (RF) classification model that consistently displayed commendable precision scores above 92% for both years. A notable discovery from the study was the pronounced urban expansion, particularly around Riyadh city. Within a mere ten-year span, urbanization surged noticeably, affecting the broader ecological environment of the region. Interestingly, the northeastern part of Riyadh emerged as a focal point of this growth, signaling rapid urban growth of urban sprawl and development. A comparison between the two years indicates a 21.51% increase in built-up areas, revealing the transformative pace of urban sprawl. Contrastingly, vegetation cover patterns presented a more nuanced picture. While our initial hypothesis predicted a decline in vegetation, the actual findings depicted both vegetation reduction in certain pockets and new growth in others, resulting in an overall 25.89% increase. This intricate pattern might be attributed to shifting agricultural practices, afforestation efforts, or even satellite image timings not aligning with seasonal vegetation growth. The bare soil, predominant in the desert landscape of Riyadh, saw a marginal reduction of 0.37% over the decade, challenging our initial expectations. Urban and agricultural advancements in Saudi Arabia appear to have slightly reduced the expanse of barren terrains. This study, underpinned by a rigorous methodological framework, reveals the multifaceted land cover changes in Riyadh in response to urban development and environmental factors. The precise, data-driven insights provided by our analysis serve as invaluable tools for understanding urban growth trajectories, guiding urban planning, policy formulation, and sustainable development endeavors in the region.

Keywords: remote sensing, KSA, ArcGIS, spatio-temporal

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Guanhao Tong, Li Li, Ben David

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This study aims to provide an explanatory account of how the leisure tourist experience emerges from tourists and their surroundings through a critical realist lens. This was achieved by applying Archer’s realist social theory as the underlying theoretical ground to unpack the interplays between the external (tourism system or structure) and the internal (tourists or agency). This theory argues that social phenomena can be analyzed in three domains - structure, agency, and culture (SAC), and along three phases – structure conditioning, sociocultural interactions, and structure elaboration. From the realist perspective, the world is an open system; events and discourses are irreducible to present individuals and collectivities. Therefore, identifying the processes or mechanisms is key to help researchers understand how social reality is brought about. Based on the contextual nature of the tourist experience, the research focuses on Chinese tourists (from mainland China) to London as a destination and British culture conveyed through the concept of the destination image. This study uses an intensive approach based on Archer’s M/M approach to discover the mechanisms/processes of the emergence of the tourist experience. Individual interviews were conducted to reveal the underlying causes of lived experiences of the tourists. Secondary data was also collected to understand how British destinations are portrayed to Chinese tourists.

Keywords: Chinese tourists, destination image, M/M approach, realist social theory, social mechanisms, tourist experience

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Authors: Aliyu J. Abubakar, Mazlan Hashim, Amin B. Pour

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Exploiting geothermal resources for either power, home heating, Spa, greenhouses, industrial or tourism requires an initial identification of suitable areas. This can be done cost-effectively using remote sensing satellite imagery which has synoptic capabilities of covering large areas in real time and by identifying possible areas of hydrothermal alteration and minerals related to Geothermal systems. Earth features and minerals are known to have unique diagnostic spectral reflectance characteristics that can be used to discriminate them. The focus of this paper is to investigate the applicability of mapping hydrothermal alteration in relation to geothermal systems (thermal springs) at Yankari Park Northeastern Nigeria, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data for resource exploration. The ASTER Short Wave Infrared (SWIR) bands are used to highlight and discriminate alteration areas by employing sophisticated digital image processing techniques including image transformations and spectral mapping methods. Field verifications are conducted at the Yankari Park using hand held Global Positioning System (GPS) monterra to identify locations of hydrothermal alteration and rock samples obtained at the vicinity and surrounding areas of the ‘Mawulgo’ and ‘Wikki’ thermal springs. X-Ray Diffraction (XRD) results of rock samples obtained from the field validated hydrothermal alteration by the presence of indicator minerals including; Dickite, Kaolinite, Hematite and Quart. The study indicated the applicability of mapping geothermal anomalies for resource exploration in unmapped sparsely vegetated savanna environment characterized by subtle surface manifestations such as thermal springs. The results could have implication for geothermal resource exploration especially at the prefeasibility stages by narrowing targets for comprehensive surveys and in unexplored savanna regions where expensive airborne surveys are unaffordable.

Keywords: geothermal exploration, image enhancement, minerals, spectral mapping

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Authors: Subham Ghosh, Banani Basu, Marami Das

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Background: The development of compact, low-power antenna sensors has resulted in hardware restructuring, allowing for wireless ubiquitous sensing. The antenna sensors can create wireless body-area networks (WBAN) by linking various wireless nodes across the human body. WBAN and IoT applications, such as remote health and fitness monitoring and rehabilitation, are becoming increasingly important. In particular, Parkinson’s disease (PD), a common neurodegenerative disorder, presents clinical features that can be easily misdiagnosed. As a mobility disease, it may greatly benefit from the antenna’s nearfield approach with a variety of activities that can use WBAN and IoT technologies to increase diagnosis accuracy and patient monitoring. Methodology: This study investigates the feasibility of leveraging a single patch antenna mounted (using cloth) on the wrist dorsal to differentiate actual Parkinson's disease (PD) from false PD using a small hardware platform. The semi-flexible antenna operates at the 2.4 GHz ISM band and collects reflection coefficient (Γ) data from patients performing five exercises designed for the classification of PD and other disorders such as essential tremor (ET) or those physiological disorders caused by anxiety or stress. The obtained data is normalized and converted into 2-D representations using the Gabor wavelet transform (GWT). Data augmentation is then used to expand the dataset size. A lightweight deep-learning (DL) model is developed to run on the GPU-enabled NVIDIA Jetson Nano platform. The DL model processes the 2-D images for feature extraction and classification. Findings: The DL model was trained and tested on both the original and augmented datasets, thus doubling the dataset size. To ensure robustness, a 5-fold stratified cross-validation (5-FSCV) method was used. The proposed framework, utilizing a DL model with 1.356 million parameters on the NVIDIA Jetson Nano, achieved optimal performance in terms of accuracy of 88.64%, F1-score of 88.54, and recall of 90.46%, with a latency of 33 seconds per epoch.

Keywords: antenna, deep-learning, GPU-hardware, Parkinson’s disease

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Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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Authors: Jeremy Bost, Matthew Brett, Jacob Flynn, Weihui Li

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One response during anaphylaxis is reduced blood pressure due to blood vessels relaxing and dilating. Epinephrine causes the blood vessels to constrict, which raises blood pressure to counteract the symptoms. When going through an allergic reaction, an Epinephrine injector is used to administer a shot of epinephrine intramuscularly. Epinephrine injectors have become an integral part of day-to-day life for people with allergies. Current Epinephrine injectors (EpiPen) are completely mechanical and have no sensors to monitor the vital signs of patients or give suggestions the optimal time for the shot. The EpiPens are also large and inconvenient to carry daily. The current price of an EpiPen is roughly 600$ for a pack of two. This makes carrying an EpiPen very expensive, especially when they need to be switched out when the epinephrine expires. This new design is in the form of a bracelet, which has the ability to inject epinephrine. The bracelet will be equipped with vital signs monitors that can aid the patient to sense the allergic reaction. The vital signs that would be of interest are blood pressure, heart rate and Electrodermal activity (EDA). The heart rate of the patient will be tracked by a photoplethysmograph (PPG) that is incorporated into the sensors. The heart rate is expected to increase during anaphylaxis. Blood pressure will be monitored through a radar sensor, which monitors the phase changes in electromagnetic waves as they reflect off of the blood vessel. EDA is under autonomic control. Allergen-induced anaphylaxis is caused by a release of chemical mediators from mast cells and basophils, thus changes the autonomic activity of the patient. So by measuring EDA, it will give the wearer an alert on how their autonomic nervous system is reacting. After the vital signs are collected, they will be sent to an application on a smartphone to be analyzed, which can then alert an emergency contact if the epinephrine injector on the bracelet is activated. Overall, this design creates a safer system by aiding the user in keeping track of their epinephrine injector, while making it easier to track their vital signs. Also, our design will be more affordable and more convenient to replace. Rather than replacing the entire product, only the needle and drug will be switched out and not the entire design.

Keywords: allergy, anaphylaxis, epinephrine, injector, vital signs monitor

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Authors: S. Haider, B. Bhushan

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Eye Gaze behaviour of individuals with and without intellectual disability are investigated in an eye tracking study in terms of sensitivity to Nonaccidental (NAPs) and Metric (MPs) shape properties. Total fixation time is used as an indirect measure of attention allocation. Studies have found Mean reaction times for non accidental properties (NAPs) to be shorter than for metric (MPs) when the MP and NAP differences were equalized. METHODS: Twenty-five individuals with intellectual disability (mild and moderate level of Mental Retardation) and twenty-seven normal individuals were compared on mean total fixation duration, accuracy level and mean reaction time for mild NAPs, extreme NAPs and metric properties of images. 2D images of cylinders were adapted and made into forced choice match-to-sample tasks. Tobii TX300 Eye Tracker was used to record total fixation duration and data obtained from the Areas of Interest (AOI). Variable trial duration (total reaction time of each participant) and fixed trail duration (data taken at each second from one to fifteen seconds) data were used for analyses. Both groups did not differ in terms of fixation times (fixed as well as variable) across any of the three image manipulations but differed in terms of reaction time and accuracy. Normal individuals had longer reaction time compared to individuals with intellectual disability across all types of images. Both the groups differed significantly on accuracy measure across all image types. Normal individuals performed better across all three types of images. Mild NAPs vs. Metric differences: There was significant difference between mild NAPs and metric properties of images in terms of reaction times. Mild NAPs images had significantly longer reaction time compared to metric for normal individuals but this difference was not found for individuals with intellectual disability. Mild NAPs images had significantly better accuracy level compared to metric for both the groups. In conclusion, type of image manipulations did not result in differences in attention allocation for individuals with and without intellectual disability. Mild Nonaccidental properties facilitate better accuracy level compared to metric in both the groups but this advantage is seen only for normal group in terms of mean reaction time.

Keywords: eye gaze fixations, eye movements, intellectual disability, stimulus properties

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Authors: A. Raj Kumar, S. Bilaloglu

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Stroke is a leading cause of adult disability worldwide. We depend on our hands for our activities of daily living(ADL). Although many patients regain the ability to walk, they continue to experience long-term hand motor impairments. As the number of individuals with young stroke is increasing, there is a critical need for effective approaches for rehabilitation of hand function post-stroke. Motor relearning for dexterity requires task-specific kinesthetic, tactile and visual feedback. However, when a stroke results in both sensory and motor impairment, it becomes difficult to ascertain when and what type of sensory substitutions can facilitate motor relearning. In an ideal situation, real-time task-specific data on the ability to learn and data-driven feedback to assist such learning will greatly assist rehabilitation for dexterity. We have found that kinesthetic and tactile information from the unaffected hand can assist patients re-learn the use of optimal fingertip forces during a grasp and lift task. Measurement of fingertip grip force (GF), load forces (LF), their corresponding rates (GFR and LFR), and other metrics can be used to gauge the impairment level and progress during learning. Currently ATI mini force-torque sensors are used in research settings to measure and compute the LF, GF, and their rates while grasping objects of different weights and textures. Use of the ATI sensor is cost prohibitive for deployment in clinical or at-home rehabilitation. A cost effective mechatronic device is developed to quantify GF, LF, and their rates for stroke rehabilitation purposes using off-the-shelf components such as load cells, flexi-force sensors, and an Arduino UNO microcontroller. A salient feature of the device is its integration with an interactive gaming environment to render a highly engaging user experience. This paper elaborates the integration of kinesthetic and tactile sensing through computation of LF, GF and their corresponding rates in real time, information processing, and interactive interfacing through augmented reality for visual feedback.

Keywords: feedback, gaming, kinesthetic, rehabilitation, tactile

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Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

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The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: electric propulsion, mass gauging, propellant, PVT, xenon

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Authors: R. Kumaravelu, S. Poornima, Sunil Kumar Kashyap

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The optimized and digitalized restoration of the information from the old and used manual jacquard punched card in textile industry is referred to as Jacquard Punch Card (JPC) reader. In this paper, we present a novel design and development of photo electronics based system for reading old and used punched cards and storing its binary information for transforming them into an effective image file format. In our textile industry the jacquard punched cards holes diameters having the sizes of 3mm, 5mm and 5.5mm pitch. Before the adaptation of computing systems in the field of textile industry those punched cards were prepared manually without digital design source, but those punched cards are having rich woven designs. Now, the idea is to retrieve binary information from the jacquard punched cards and store them in digital (Non-Graphics) format before processing it. After processing the digital format (Non-Graphics) it is converted into an effective image file format through either by Row major or Column major parsing technique.To accomplish these activities, an embedded system based device and software integration is developed. As part of the test and trial activity the device was tested and installed for industrial service at Weavers Service Centre, Kanchipuram, Tamilnadu in India.

Keywords: file system, SPI. UART, ARM controller, jacquard, punched card, photo LED, photo diode

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