Search results for: xylem filter

Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Lamees Nasser, Yago Diez, Robert Martí, Joan Martí, Ibrahim Sadek

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Automated 3D breast ultrasound (ABUS) screening is a novel modality in medical imaging because of its common characteristics shared with other ultrasound modalities in addition to the three orthogonal planes (i.e., axial, sagittal, and coronal) that are useful in analysis of tumors. In the literature, few automatic approaches exist for typical tasks such as segmentation or registration. In this work, we deal with two problems concerning ABUS images: nipple and rib detection. Nipple and ribs are the most visible and salient features in ABUS images. Determining the nipple position plays a key role in some applications for example evaluation of registration results or lesion follow-up. We present a nipple detection algorithm based on color and shape of the nipple, besides an automatic approach to detect the ribs. In point of fact, rib detection is considered as one of the main stages in chest wall segmentation. This approach consists of four steps. First, images are normalized in order to minimize the intensity variability for a given set of regions within the same image or a set of images. Second, the normalized images are smoothed by using anisotropic diffusion filter. Next, the ribs are detected in each slice by analyzing the eigenvalues of the 3D Hessian matrix. Finally, a breast mask and a probability map of regions detected as ribs are used to remove false positives (FP). Qualitative and quantitative evaluation obtained from a total of 22 cases is performed. For all cases, the average and standard deviation of the root mean square error (RMSE) between manually annotated points placed on the rib surface and detected points on rib borders are 15.1188 mm and 14.7184 mm respectively.

Keywords: Automated 3D Breast Ultrasound, Eigenvalues of Hessian matrix, Nipple detection, Rib detection

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Authors: Farhana Arefeen Mila, Luis Emilio Morales, Nam Hoang, Sujana Adapa, Garry Griffith

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This study investigates the existence of price transmission asymmetries and imperfections among the coastal and freshwater fish species in Bangladesh. Using a Structural Vector Autoregression (SVAR) model, we explore how price changes in one fish species impact the prices of others in the retail market. Monthly data from the Department of Agricultural Marketing (DAM) covering the period from 2012 to 2023 was analyzed. Price series were detrended using the Hodrick-Prescott filter, and unit root tests confirmed stationarity after detrending. The findings indicate that there are significant interdependencies and asymmetries in price transmission, particularly the strong influence of Hilsha on the broader fish market. Hilsha’s price shocks generate immediate responses across other species, reflecting its cultural and economic importance. Silver Pomfret demonstrates some independence but is still affected by broader market fluctuations, particularly those involving Hilsha. Meanwhile, Rohu and Catla exhibit high interdependence, where price changes in one species closely impact the other, underscoring their substitutable nature in consumer preferences. These findings emphasize the need for joint interventions and market monitoring to stabilize prices effectively. Stakeholders are encouraged to monitor Hilsha’s market, consider coordinated interventions for Rohu and Catla, and establish data-sharing partnerships to enhance market stability. Additionally, promoting consumer awareness of price trends and sustainable practices can further support market resilience and long-term sustainability in the fisheries sector.

Keywords: price transmission, cross commodity, fish, Bangladesh, CCF, SVAR, IRF

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Authors: Saeed Yazdani, Sima Mohamadi Amidabadi, Amir Mohamadi Nejad, Farahnaz Nekoofar

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As a result of uncertainty and doubts about the quantity of agricultural products, greater significance has been attached to risk management in the agricultural sector. Normally, farmers seek to minimize risks, and crop diversity has always been a means to reduce risk. The study at hand seeks to explore the long-term impact of crop diversity on income risk reduction. The timeframe of the study is 1998 to 2018. Initially, the Herfindahl index was used to estimate crop diversity in different periods, and next, the Hodrick-Prescott filter was applied to estimate income risk both in nominal and real terms. Finally, using the Vector Error Correction Model (VECM), the long-term impact of crop diversity on two modes of risk for the farmer's income has been estimated. Given the long-term pattern’s results, it is evident that in the long-run, crop diversity can reduce income fluctuations in two nominal and real terms. Moreover, results showed that in case the fluctuation shock affects the agricultural income in the short run, to balance out the shock in nominal and real terms, 4 and 3 cycles are needed respectively. In other words, in each cycle, 25% and 33% of the shock impact can be removed, respectively. Thus, as the results of the error correction coefficient showed, policies need to be put in place to prevent income shocks. In case of a shock, they need to be balanced out in a four-year period, taking inflation into account, and in a three-year period irrespective of the inflation and reparative policies such as insurance services should be developed.

Keywords: risk, long-term model, Herfindahl index, time series model, vector error correction model

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Authors: Kai-Jui Kou, Tzu-Ling Shen, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the different working type in 3D printing room and the stack flue during 3D printing process. The studied laboratory (10.5 m× 7.2 m × 3.2 m) with a ventilation rate of 500 m³/H is installed a 3D metal printing machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L/min, respectively. The concentrations of background, printing process, clearing operation, and screening operation were performed in the laboratory. On the other hand, we also conducted nanoparticle measurement on the 3D printing machine's stack flue to understand its emission characteristics. Results show that the nanoparticles emitted from the different operation process were the same distribution in the form of the uni-modal with number median diameter (NMD) as approximately 28.3 nm to 29.6 nm. The number concentrations of nanoparticles were 2.55×10³ count/cm³ in laboratory background, 2.19×10³ count/cm³ during printing process, 2.29×10³ count/cm³ during clearing process, 3.05×10³ count/cm³ during screening process, 2.69×10³ count/cm³ in laboratory background after printing process, and 6.75×10³ outside laboratory, respectively. We found that there are no emission nanoparticles during the printing process. However, the number concentration of stack flue nanoparticles in the ongoing print is 1.13×10⁶ count/cm³, and that of the non-printing is 1.63×10⁴ count/cm³, with a NMD of 458 nm and 29.4 nm, respectively. It can be confirmed that the measured particle size belongs to easily penetrate the filter in theory during the printing process, even though the 3D printer has a high-efficiency filtration device. Therefore, it is recommended that the stack flue of the 3D printer would be equipped with an appropriate dust collection device to prevent the operators from exposing these hazardous particles.

Keywords: nanoparticle, particle emission, 3D printing, number concentration

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Authors: Z. Abdollahi Biron, P. Pisu

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Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Keywords: fault diagnostics, communication network, connected vehicles, packet drop out, platoon

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Authors: Enyia James Diwa, Dodeye Ina Igbong, Archibong Archibong Eso

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Gas turbine operators have been faced with the dramatic financial setback resulting from compressor fouling. In a highly deregulated power industry where there is stiffness in the market competition, has made it imperative to improvise means of reducing maintenance cost in other to yield maximum profit. Compressor fouling results from the deposition of contaminants in the presence of oil and moisture on the compressor blade or annulus surfaces, which leads to a loss in flow capacity and compressor efficiency. These combined effects reduce power output, increase heat rate and cause creep life reduction. This paper also contains a model of two gas turbine engines via Cranfield University software known as TURBOMATCH, which is simulation software for detecting engine fouling rate. The model engines are of different configurations and capacities, and are operating in two different modes of constant output power and turbine inlet temperature for a two and three stage filter system. The idea is to investigate the more economically viable filtration systems by gas turbine users based on performance only. It has been demonstrated in the results that the two spool engine is a little more beneficial compared to the single spool. This is as a result of a higher pressure ratio of the two spools as well as the deceleration of the high-pressure compressor and high-pressure turbine speed in a constant TET. Meanwhile, the inlet filtration system was properly designed and balanced with a well-timed and economical compressor washing regime/scheme to control compressor fouling. The different technologies of inlet air filtration and compressor washing are considered and an attempt at optimization with respect to the cost of a combination of both control measures are made.

Keywords: inlet filtration, pressure loss, single spool, two spool

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Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Andrea Tonoli, Nicola Amati, Maria Cavatorta, Reza Mirsanei, Behzad Mozaffari, Hamed Ahani, Akbar Karamihafshejani, Mohammad Ghazivakili, Mohammad Abuabiah

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The vibrations transmitted to the drivers and passengers through vehicle seat seriously effect on the level of their attention, fatigue and physical health and reduce the comfort and efficiency of the occupants. Recently, some researchers have focused on vibrations at low excitation frequency(0.5-5 Hz) which are considered to be the main risk factors for lumbar part of the backbone but they were not applicable to A and B-segment cars regarding to the size and weight. A semi-active system with two symmetric negative stiffness structures (NSS) in parallel to a positive stiffness structure and actuators has been proposed to attenuate low frequency excitation and makes system flexible regarding to different weight of passengers which is applicable for A and B-Segment cars. Here, the 3 degree of freedom system is considered, dynamic equation clearly is presented, then simulated in MATLAB in order to analysis of performance of the system. The design procedure is derived so that the resonance peak of frequency–response curve shift to the left, the isolating range is increased and especially, the peak of the frequency–response curve is minimized. According to ISO standard different class of road profile as an input is applied to the system to evaluate the performance of the system. To evaluate comfort issues, we extract the RMS value of the vertical acceleration acting on the passenger's body. Then apply the band-pass filter, which takes into account the human sensitivity to acceleration. According to ISO, this weighted acceleration is lower than 0.315 m/s^2, so the ride is considered as comfortable.

Keywords: low frequency excitation, negative stiffness, seat vehicle, vibration isolation

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Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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Authors: Kyosuke Kamada, Christoph Kapeller, Michael Jordan, Mostafa Mohammadpour, Christy Li, Christoph Guger

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Cortico-cortical evoked potentials (CCEP) refer to responses generated by cortical electrical stimulation at distant brain sites. These responses provide insights into the functional networks associated with language or motor functions, and in the context of epilepsy, they can reveal pathological networks. Locating the origin and spread of seizures within the cortex is crucial for pre-surgical planning. This process can be enhanced by employing cortical stimulation at the seizure onset zone (SOZ), leading to the generation of CCEPs in remote brain regions that may be targeted for disconnection. In the case of a 24-year-old male patient suffering from intractable epilepsy, corpus callosotomy was performed as part of the treatment. DTI-MRI imaging, conducted using a 3T MRI scanner for fiber tracking, along with CCEP, is used as part of an assessment for surgical planning. Stimulation of the SOZ, with alternating monophasic pulses of 300µs duration and 15mA current intensity, resulted in CCEPs on the contralateral frontal cortex, reaching a peak amplitude of 206µV with a latency of 31ms, specifically in the left pars triangularis. The related fiber tracts were identified with a two-tensor unscented Kalman filter (UKF) technique, showing transversal fibers through the corpus callosum. The CCEPs were monitored through the progress of the surgery. Notably, the SOZ-associated CCEPs exhibited a reduction following the resection of the anterior portion of the corpus callosum, reaching the identified connecting fibers. This intervention demonstrated a potential strategy for mitigating the impact of intractable epilepsy through targeted disconnection of identified cortical regions.

Keywords: CCEP, SOZ, Corpus callosotomy, DTI

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Authors: T. Obateru, Samuel Olaniran

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In an era when the new media is affording easy access to packaging and dissemination of information, the social media have become a popular avenue for sharing information for good or ill. It is evident that the traditional role of journalists as ‘news breakers’ is fast being eroded. People now share information on happenings via the social media like Facebook, Twitter and the rest, such that journalists themselves now get leads on happenings from such sources. Beyond the access to information provided by the new media is the erosion of the gatekeeping role of journalists who by their training and calling, are supposed to handle information with responsibility. Thus, sensitive information that journalists would normally filter is randomly shared by social media activists. This was the experience of journalists in Jos, Plateau State in January 2010 when another of the recurring ethnoreligious crisis that engulfed the state resulted in another widespread killing, vandalism, looting, and displacements. Considered as one of the high points of crises in the state, journalists who had the duty of covering the crisis also relied on some of these sources to get their bearing on the violence. This paper examined the role of Facebook in the work of journalists who covered the 2010 crisis. Taking the gatekeeping perspective, it interrogated the extent to which Facebook impacted their professional duty positively or negatively vis-à-vis the peace journalism model. It employed survey to elicit information from 50 journalists who covered the crisis using questionnaire as instrument. The paper revealed that the dissemination of hate information via mobile phones and social media, especially Facebook, aggravated the crisis situation. Journalists became news followers rather than news breakers because a lot of them were put on their toes by information (many of which were inaccurate or false) circulated on Facebook. It recommended that journalists must remain true to their calling by upholding their ‘gatekeeping’ role of disseminating only accurate and responsible information if they would remain the main source of credible information on which their audience rely.

Keywords: crisis, ethnoreligious, Facebook, journalists

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Lidija Trandafilovic, Kirsten Leistner, Marie Stenfeldt, Louise Olsson

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Ammonia Selective Catalytic Reduction (NH3 SCR), is one of the most efficient post combustion abatement technologies for removing NOx from diesel engines. In order to remove soot, diesel particulate filters (DPF) are used. Recently, SCR coated filters have been introduced, which captures soot and simultaneously is active for ammonia SCR. There are large advantages with using SCR coated filters, such as decreased volume and also better light off characteristics, since both the SCR function as well as filter function is close to the engine. The objective of this work was to examine the effect of soot, produced using an engine bench, on Cu/SSZ-13 catalysts. The impact of soot on Cu/SSZ-13 in standard SCR, NH3 oxidation, NH3 temperature programmed desorption (TPD), as well as soot oxidation (with and without water) was examined using flow reactor measurements. In all experiments, prior to the soot loading, the fresh activity of Cu/SSZ-13 was recorded with stepwise increasing the temperature from 100°C till 600°C. Thereafter, the sample was loaded with soot and the experiment was repeated in the temperature range from 100°C till 700°C. The amount of CO and CO2 produced in each experiment is used to calculate the soot oxidized at each steady state temperature. The soot oxidized during the heating to next temperature step is included, e.g. the CO+CO2 produced when increasing the temperature to 600°C is added to the 600°C step. The influence of the two factors seem to be of the most importance to soot oxidation: ammonia and water. The influence of water on soot oxidation shift the maximum of CO2 and CO production towards lower temperatures, thus water increases the soot oxidation. Moreover, when adding ammonia to the system it is clear that the soot oxidation is lowered in the presence of ammonia, resulting in larger integrated COx at 500°C for O2+H2O, while opposite results at 600 °C was received where more was oxidised for O2+H2O+NH3 case. To conclude the presence of ammonia reduces the soot oxidation, which is in line with the ammonia TPD results where we found ammonia storage on the soot. Interestingly, during ammonia SCR conditions the activity for soot oxidation is regained at 500°C. At this high temperature the SCR zone is very short, thus the majority of the catalyst is not exposed to ammonia and therefore the inhibition effect of ammonia is not observed.

Keywords: NH3-SCR, Cu/SSZ-13, soot, zeolite

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Authors: Othman Maklouf, Abdunnaser Tresh

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Land vehicle navigation is subject of great interest today. Global Positioning System (GPS) is the main navigation system for positioning in such systems. GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation (INS) is the implementation of inertial sensors to determine the position and orientation of a vehicle. The availability of low-cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop INS using an inertial measurement unit (IMU). INS has unbounded error growth since the error accumulates at each step. Usually, GPS and INS are integrated with a loosely coupled scheme. With the development of low-cost, MEMS inertial sensors and GPS technology, integrated INS/GPS systems are beginning to meet the growing demands of lower cost, smaller size, and seamless navigation solutions for land vehicles. Although MEMS inertial sensors are very inexpensive compared to conventional sensors, their cost (especially MEMS gyros) is still not acceptable for many low-end civilian applications (for example, commercial car navigation or personal location systems). An efficient way to reduce the expense of these systems is to reduce the number of gyros and accelerometers, therefore, to use a partial IMU (ParIMU) configuration. For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a field experiment for a low-cost strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach, we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of our low-cost IMU (Inertial Measurement Unit) and because of the relatively small area of the trajectory.

Keywords: GPS, IMU, Kalman filter, materials engineering

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Authors: A. Aljohani, D. Burke, D. Clarke, M. Gormally, M. Byrne, G. Fleming

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Introduction: House Dust Mites (HDMs) are a source of allergen particles embedded in textiles and furnishings. Vacuum sampling is commonly used to recover and determine the abundance of HDMs but the efficiency of this method is less than standardized. Here, the efficiency of recovery of HDMs was evaluated from home-associated textiles using vacuum sampling protocols.Methods/Approach: Living Mites (LMs) or dead Mites (DMs) House Dust Mites (Dermatophagoides pteronyssinus: FERA, UK) were separately seeded onto the surfaces of Smooth Cotton, Denim and Fleece (25 mites/10x10cm2 squares) and left for 10 minutes before vacuuming. Fabrics were vacuumed (SKC Flite 2 pump) at a flow rate of 14 L/min for 60, 90 or 120 seconds and the number of mites retained by the filter (0.4μm x 37mm) unit was determined. Vacuuming was carried out in a linear direction (Protocol 1) or in a multidirectional pattern (Protocol 2). Additional fabrics with LMs were also frozen and then thawed, thereby euthanizing live mites (now termed EMs). Results/Findings: While there was significantly greater (p=0.000) recovery of mites (76% greater) in fabrics seeded with DMs than LMs irrespective of vacuuming protocol or fabric type, the efficiency of recovery of DMs (72%-76%) did not vary significantly between fabrics. For fabrics containing EMs, recovery was greatest for Smooth Cotton and Denim (65-73% recovered) and least for Fleece (15% recovered). There was no significant difference (p=0.99) between the recovery of mites across all three mite categories from Smooth Cotton and Denim but significantly fewer (p=0.000) mites were recovered from Fleece. Scanning Electron Microscopy images of HMD-seeded fabrics showed that live mites burrowed deeply into the Fleece weave which reduced their efficiency of recovery by vacuuming. Research Implications: Results presented here have implications for the recovery of HDMs by vacuuming and the choice of fabric to ameliorate HDM-dust sensitization.

Keywords: allergy, asthma, dead, fabric, fleece, live mites, sampling

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Authors: Mansoor Soomro

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The evolution of power electronic equipment has been pivotal in making industrial processes productive, efficient and safe. Despite its attractive features, it has been due to nonlinear loads which make it vulnerable to power quality conditions. Harmonics is one of the power quality problem in which the harmonic frequency is integral multiple of supply frequency. Therefore, the supply voltage and supply frequency do not last within their tolerable limits. As a result, distorted current and voltage waveform may appear. Attributes of low power quality confirm that an electrical device or equipment is likely to malfunction, fail promptly or unable to operate under all applied conditions. The electrical power system is designed for delivering power reliably, namely maximizing power availability to customers. However, power quality events are largely untracked, and as a result, can take out a process as many as 20 to 30 times a year, costing utilities, customers and suppliers of load equipment, a loss of millions of dollars. The ill effects of current harmonics reduce system efficiency, cause overheating of connected equipment, result increase in electrical power and air conditioning costs. With the passage of time and the rapid growth of power electronic converters has highlighted the damages of current harmonics in the electrical power system. Therefore, it has become essential to address the bad influence of current harmonics while planning any suitable changes in the electrical installations. In this paper, an effort has been made to mitigate the effects of dominant 3rd order current harmonics. Passive filtering technique with six pulse multiplication converter has been employed to mitigate them. Since, the standards of power quality are to maintain the supply voltage and supply current within certain prescribed standard limits. For this purpose, the obtained results are validated as per specifications of IEEE 519-1992 and IEEE 519-2014 performance standards.

Keywords: current harmonics, power quality, passive filters, power electronic converters

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Authors: Tafadzwa Makonese, Harold Annegarn, Patricia Forbes

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Residential coal combustion is one of the largest sources of carbonaceous aerosols in the Highveld region of South Africa, significantly affecting the local and regional climate. In this study, we investigated single coal burning particles emitted when using different fire-ignition techniques (top-lit up-draft vs bottom-lit up-draft) and air ventilation rates (defined by the number of air holes above and below the fire grate) in selected informal braziers. Aerosol samples were collected on nucleopore filters at the SeTAR Centre Laboratory, University of Johannesburg. Individual particles (~700) were investigated using a scanning electron microscope equipped with an energy-dispersive X-ray spectroscopy (EDS). Two distinct forms of spherical organic particles (SOPs) were identified, one less oxidized than the other. The particles were further classified into "electronically" dark and bright, according to China et al. [2014]. EDS analysis showed that 70% of the dark spherical organic particles balls had higher (~60%) relative oxygen content than in the bright SOPs. We quantify the morphology of spherical organic particles and classify them into four categories: ~50% are bare single particles; ~35% particles are aggregated and form diffusion accretion chains; 10% have inclusions; and 5% are deformed due to impaction on filter material during sampling. We conclude that there are two distinct kinds of coal burning spherical organic particles and that dark SOPs are less volatile than bright SOPs. We also show that these spherical organic particles are similar in nature and characteristics to tar balls observed in biomass combustion, and that they have the potential to absorb sunlight thereby affecting the earth’s radiative budget and climate. This study provides insights on the mixing states, morphology, and possible formation mechanisms of these organic particles from residential coal combustion in informal stoves.

Keywords: spherical organic particles, residential coal combustion, fixed-bed, aerosols, morphology, stoves

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Authors: Kashif Habib, Zeeshan Ayyub

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ZnO voltage dependent resistor was widely used as components of the electrical system for over-voltage protection. It has a wide application prospect in superconducting energy-removal, generator de-excitation, overvoltage protection of electrical & electronics equipment. At present, the research for the application of ZnO voltage dependent resistor stop, it uses just in the field of its nonlinear voltage current characteristic and overvoltage protection areas. There is no further study over the over-voltage breakdown characteristics, such as the combustion phenomena and the measure of the voltage/current when it breakdown, and the affect to its surrounding equipment. It is also a blind spot in its application. So, when we do the feature test of ZnO voltage dependent resistor, we need to design a reasonable test power supply, making the terminal voltage keep for sine wave, simulating the real use of PF voltage in power supply conditions. We put forward the solutions of using inverter to generate a controllable power. The paper mainly focuses on the breakdown characteristic test power supply of nonlinear ZnO voltage dependent resistor. According to the current mature switching power supply technology, we proposed power control system using the inverter as the core. The power mainly realize the sin-voltage output on the condition of three-phase PF-AC input, and 3 control modes (RMS, Peak, Average) of the current output. We choose TMS320F2812M as the control part of the hardware platform. It is used to convert the power from three-phase to a controlled single-phase sin-voltage through a rectifier, filter, and inverter. Design controller produce SPWM, to get the controlled voltage source via appropriate multi-loop control strategy, while execute data acquisition and display, system protection, start logic control, etc. The TMS320F2812M is able to complete the multi-loop control quickly and can be a good completion of the inverter output control.

Keywords: ZnO, multi-loop control, SPWM, non-linear load

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Authors: Andrew Hargreaves, Peter Vale, Jonathan Whelan, Carlos Constantino, Gabriela Dotro, Pablo Campo

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As a consequence of their potential to cause harm, there are strong regulatory drivers that require metals to be removed as part of the wastewater treatment process. Bioavailability-based standards have recently been specified for copper (Cu), lead (Pb), nickel (Ni) and zinc (Zn) and are expected to reduce acceptable metal concentrations. In order to comply with these standards, wastewater treatment works may require new treatment types to enhance metal removal and it is, therefore, important to examine potential treatment options. A substantial proportion of Cu, Pb, Ni and Zn in effluent is adsorbed to and/or complexed with macromolecules (eg. proteins, polysaccharides, aminosugars etc.) that are present in the colloidal size fraction. Therefore, technologies such as coagulation-flocculation (CF) that are capable of removing colloidal particles have good potential to enhance metals removal from wastewater. The present study investigated the effectiveness of CF at removing trace metals from humus effluent using the following coagulants; ferric chloride (FeCl3), the synthetic polymer polyethyleneimine (PEI), and the biopolymers chitosan and Tanfloc. Effluent samples were collected from a trickling filter treatment works operating in the UK. Using jar tests, the influence of coagulant dosage and the velocity and time of the slow mixing stage were studied. Chitosan and PEI had a limited effect on the removal of trace metals (<35%). FeCl3 removed 48% Cu, 56% Pb and 41% Zn at the recommended dose of 0.10 mg/L. At the recommended dose of 0.25 mg/L Tanfloc removed 77% Cu, 68% Pb, 18% Ni and 42% Zn. The dominant mechanism for particle removal by FeCl3 was enmeshment in the precipitates (i.e. sweep flocculation) whereas, for Tanfloc, inter-particle bridging was the dominant removal mechanism. Overall, FeCl3 and Tanfloc were found to be most effective at removing trace metals from wastewater.

Keywords: coagulation-flocculation, jar test, trace metals, wastewater

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Authors: Hussein Bizimana, Osman Sönmez

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Constructed wetlands are current the most widely recognized waste water treatment option, especially in developing countries where they have the potential for improving water quality and creating valuable wildlife habitat in ecosystem with treatment requirement relatively simple for operation and maintenance cost. Lack of grey waste water treatment facilities in Kigali İnstitute of Science and Technology in Rwanda, causes pollution in the surrounding localities of Rugunga sector, where already a problem of poor sanitation is found. In order to treat grey water produced at Kigali İnstitute of Science and Technology, with high BOD concentration, high nutrients concentration and high alkalinity; a Horizontal Sub-surface Flow pilot-scale constructed wetland was designed and can operate in Kigali İnstitute of Science and Technology. The study was carried out in a sedimentation tank of 5.5 m x 1.42 m x 1.2 m deep and a Horizontal Sub-surface constructed wetland of 4.5 m x 2.5 m x 1.42 m deep. The grey waste water flow rate of 2.5 m3/d flew through vegetated wetland and sandy pilot plant. The filter media consisted of 0.6 to 2 mm of coarse sand, 0.00003472 m/s of hydraulic conductivity and cattails (Typha latifolia spp) were used as plants species. The effluent flow rate of the plant is designed to be 1.5 m3/ day and the retention time will be 24 hrs. 72% to 79% of BOD, COD, and TSS removals are estimated to be achieved, while the nutrients (Nitrogen and Phosphate) removal is estimated to be in the range of 34% to 53%. Every effluent characteristic will meet exactly the Rwanda Utility Regulatory Agency guidelines primarily because the retention time allowed is enough to make the reduction of contaminants within effluent raw waste water. Treated water reuse system was developed where water will be used in the campus irrigation system again.

Keywords: constructed wetlands, hydraulic conductivity, grey waste water, cattails

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Authors: Genesis Julyus T. Agcaoili, Esperanza C. Cabrera

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Thirty (30) isolates of lactic acid bacteria (LAB) from traditionally-prepared fermented products specifically fermented soy-bean paste, fermented mustard and fermented rice-fish mixture were studied for their in vitro antimicrobial and cytotoxic activities. Seventeen (17) isolates were identified as Lactobacillus plantarum, while 13 isolates were identified as Enterococcus spp using 16s rDNA sequences. Disc diffusion method was used to determine the antibacterial activity of LAB against Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922), while the modified agar overlay method was used to determine the antifungal activity of LAB isolates on the yeast Candida albicans, and the dermatophytes Microsporum gypseum, Trichophyton rubrum and Epidermophyton floccosum. The filter-sterilized LAB supernatants were evaluated for their cytotoxicity to mammalian colon cancer cell lines (HT-29 and HCT116) and normal human dermal fibrolasts (HDFn) using resazurin assay (PrestoBlueTM). Colchicine was the positive control. No antimicrobial activity was observed against the bacterial test organisms and the yeast Candida albicans. On the other hand, all of the tested LAB strains were fungicidal for all the test dermatophytes. Cytotoxicity index profiles of the supernatants of the 15 randomly picked LABs and negative control (brain heart infussion broth) suggest nontoxicity to the cells when compared to colchicine, whereas all LAB supernatants were found to be cytotoxic to HT-29 and HCT116 colon cancer cell lines. Results provide strong support for the role of the lactic acid bacteria studied in antimicrobial treatment and anticancer therapy.

Keywords: antimicrobial, fermented products, fungicidal activity, lactic acid bacteria, probiotics

Procedia PDF Downloads 236

Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

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Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

Procedia PDF Downloads 288

Authors: Manasa Kalla, Narasimha Raju Chebrolu, Ashok Chatterjee

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We have studied the quantum transport properties of a single molecular transistor in the presence of an external magnetic field using the Keldysh Green function technique. We also used the Anderson-Holstein-Caldeira-Leggett Model to describe the single molecular transistor that consists of a molecular quantum dot (QD) coupled to two metallic leads and placed on a substrate that acts as a heat bath. The phonons are eliminated by the Lang-Firsov transformation and the effective Hamiltonian is used to study the effect of an external magnetic field on the spectral density function, Tunneling Current, Differential Conductance and Spin polarization. A peak in the spectral function corresponds to a possible excitation. In the presence of a magnetic field, the spin-up and spin-down states are degenerate and this degeneracy is lifted by the magnetic field leading to the splitting of the central peak of the spectral function. The tunneling current decreases with increasing magnetic field. We have observed that even the differential conductance peak in the zero magnetic field curve is split in the presence electron-phonon interaction. As the magnetic field is increased, each peak splits into two peaks. And each peak indicates the existence of an energy level. Thus the number of energy levels for transport in the bias window increases with the magnetic field. In the presence of the electron-phonon interaction, Differential Conductance in general gets reduced and decreases faster with the magnetic field. As magnetic field strength increases, the spin polarization of the current is increasing. Our results show that a strongly interacting QD coupled to metallic leads in the presence of external magnetic field parallel to the plane of QD acts as a spin filter at zero temperature.

Keywords: Anderson-Holstein model, Caldeira-Leggett model, spin-polarization, quantum dots

Procedia PDF Downloads 181

Authors: Ganbat Danaa, Chuluundorj Puntsag

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The steel structures of the Oyu-Tolgoi mining Concentrator plant are corroded during operation, which raises doubts about the continued use of some important structures of the plant, which is one of the problems facing the plant's regular operation. As a part of the main operation of the plant, the bottom part of the pressure vessel, which plays an important role in the reliable operation of the concentrate filter-drying unit, was heavily corroded, so it was necessary to study by engineering calculations, modeling, and simulation using modern advanced engineering programs and methods. The purpose of this research is to investigate whether the corroded part of the pressure vessel can be used normally in the future using advanced engineering software and to predetermine the remaining life of the time of the pressure vessel based on engineering calculations. When the thickness of the bottom part of the pressure vessel was thinned by 0.5mm due to corrosion detected by non-destructive testing, finite element analysis using ANSYS WorkBench software was used to determine the mechanical stress, strain and safety factor in the wall and bottom of the pressure vessel operating under 2.2 MPa working pressure, made conclusions on whether it can be used in the future. According to the recommendations, by using sand-blast cleaning and anti-corrosion paint, the normal, continuous and reliable operation of the Concentrator plant can be ensured, such as ordering new pressure vessels and reducing the installation period. By completing this research work, it will be used as a benchmark for assessing the corrosion condition of steel parts of pressure vessels and other metallic and non-metallic structures operating under severe conditions of corrosion, static and dynamic loads, and other deformed steels to make analysis of the structures and make it possible to evaluate and control the integrity and reliable operation of the structures.

Keywords: corrosion, non-destructive testing, finite element analysis, safety factor, structural reliability

Procedia PDF Downloads 65

Authors: Y. Zhang, J. Perez, S. Marnier

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To date, no study on goaltending butterfly motion has been completed in real conditions, during an ice hockey game or training practice, to the author's best knowledge. This motion, performed to save score, is unnatural, intense, and repeated. The target of this research activity is to identify representative biomechanical criteria for this goaltender-specific movement pattern. Determining specific physical parameters may allow to will identify the risk of hip and groin injuries sustained by goaltenders. Four professional or academic goalies were instrumented during ice hockey training practices with five inertial measurement units. These devices were inserted in dedicated pockets located on each thigh and shank, and the fifth on the lumbar spine. A camera was also installed close to the ice to observe and record the goaltenders' activities, especially the butterfly motions, in order to synchronize the captured data and the behavior of the goaltender. Each data recorded began with a calibration of the inertial units and a calibration of the fully equipped goaltender on the ice. Three butterfly motions were recorded out of the training practice to define referential individual butterfly motions. Then, a data processing algorithm based on the Madgwick filter computed hip and knee joints joint range of motion as well as angular specific angular velocities. The developed algorithm software automatically identified and analyzed all the butterfly motions executed by the four different goaltenders. To date, it is still too early to show that the analyzed criteria are representative of the trauma generated by the butterfly motion as the research is only at its beginning. However, this descriptive research activity is promising in its ecological assessment, and once the criteria are found, the tools and protocols defined will allow the prevention of as many injuries as possible. It will thus be possible to build a specific training program for each goalie.

Keywords: biomechanics, butterfly motion, human motion analysis, ice hockey, inertial measurement unit

Procedia PDF Downloads 124

Authors: Mengjie Qu, Yi Wang, Jiawei Ding, Siyu Chen, Yanan Di

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Marine ecosystem is facing intensified multiple stresses caused by environmental contaminants from human activities. Xenobiotics, such as benzo(α)pyrene (BaP) have been discharged into marine environment and cause hazardous impacts on both marine organisms and human beings. As a filter-feeder, marine mussels, Mytilus spp., has been extensively used to monitor the marine environment. However, their genomic alterations induced by such xenobiotics are still kept unknown. In the present study, gills, as the first defense barrier in mussels, were selected to evaluate the genetic instability alterations induced by the exposure to BaP both in vivo and in vitro. Both random amplified polymorphic DNA (RAPD) assay and comet assay were applied as the rapid tools to assess the environmental stresses due to their low money- and time-consumption. All mussels were identified to be the single species of Mytilus coruscus before used in BaP exposure at the concentration of 56 μg/l for 1 & 3 days (in vivo exposure) or 1 & 3 hours (in vitro). Both RAPD and comet assay results were showed significantly increased genomic instability with time-specific altering pattern. After the recovery period in 'in vivo' exposure, the genomic status was as same as control condition. However, the relative higher genomic instabilities were still observed in gill cells after the recovery from in vitro exposure condition. Different repair mechanisms or signaling pathway might be involved in the isolated gill cells in the comparison with intact tissues. The study provides the robust and rapid techniques to exam the genomic stability in marine organisms in response to marine environmental changes and provide basic information for further mechanism research in stress responses in marine organisms.

Keywords: genotoxic impacts, in vivo/vitro exposure, marine mussels, RAPD and comet assay

Procedia PDF Downloads 278

Authors: Annisa Ulfah Pristya, Andi Setiawan

Abstract:

Indonesia placed in sixth rank total Acute Respiratory Infection (ARI) patient in the world and Riau as one of the province with the highest number of people with respiratory infection in Indonesia reached 37 thousand people. Usually society using a mask as prevention action. Unfortunately the commercial mouth mask only can work maximum for 4 hours and the pores are too large to filter out microorganisms and viruses carried by infectious droplets nucleated 1-5 μm. On the other hand, Indonesia is rich with Titanium dioxide (TiO2) and purple sweet potato anthocyanin pigment. Therefore, offered Bio-nano-mask which is a antimicrobial and antiviral mouth mask with Nano-TiO2 coating and purple sweet potato anthocyanins utilization as an effective solution to high ARI patients in Riau, which has the advantage of the mask surface can’t be attached by infectious droplets, self-cleaning and have anthocyanins biosensors that give visual response can be understood easily by the general public in the form of a mask color change from blue/purple to pink when acid levels increase. Acid level is an indicator of microorganisms accumulation in the mouth and surrounding areas. Bio-nano mask making process begins with the preparation (design, Nano-TiO2 liquid preparation, anthocyanins biosensors manufacture) and then superimposing the Nano-TiO2 on the outer surface of spunbond color using a sprayer, then superimposing anthocyanins biosensors film on the Meltdown surface, making bio nano-mask and it pack. Bio-nano mask has the advantage is effectively preventing pathogenic microorganisms and infectious droplets and has accumulated indicator microorganisms that color changes which easily observed by the common people though.

Keywords: anthocyanins, ARI, nano-TiO2 liquid, self cleaning

Procedia PDF Downloads 567

Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

Procedia PDF Downloads 147