Search results for: filter banks

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: Janne Engblom, Elias Oikarinen

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The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

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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: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

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Authors: Emiru Birhane, Tesfay Gidey, Haftu Abrha, Abrha Brhan, Amanuel Zenebe, Girmay Gebresamuel, Florent Noulèkoun

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Dracaena ombet and Dobera glabra are two of the most rare and endangered tree species in dryland areas. Unfortunately, their sustainability is being compromised by different anthropogenic and natural factors. However, the impacts of ongoing land use and climate change on the population structure and distribution of the species are less explored. This study was carried out in the grazing lands and hillside areas of the Desa'a dry Afromontane forest, northern Ethiopia, to characterize the population structure of the species and predict the impact of climate change on their potential distributions. In each land-use type, abundance, diameter at breast height, and height of the trees were collected using 70 sampling plots distributed over seven transects spaced one km apart. The geographic coordinates of each individual tree were also recorded. The results showed that the species populations were characterized by low abundance and unstable population structure. The latter was evinced by a lack of seedlings and mature trees. The study also revealed that the total abundance and dendrometric traits of the trees were significantly different between the two land uses. The hillside areas had a denser abundance of bigger and taller trees than the grazing lands. Climate change predictions using the MaxEnt model highlighted that future temperature increases coupled with reduced precipitation would lead to significant reductions in the suitable habitats of the species in northern Ethiopia. The species' suitable habitats were predicted to decline by 48–83% for D. ombet and 35–87% for D. glabra. Hence, to sustain the species populations, different strategies should be adopted, namely the introduction of alternative livelihoods (e.g., gathering NTFP) to reduce the overexploitation of the species for subsistence income and the protection of the current habitats that will remain suitable in the future using community-based exclosures. Additionally, the preservation of the species' seeds in gene banks is crucial to ensure their long-term conservation.

Keywords: grazing lands, hillside areas, land-use change, MaxEnt, range limitation, rare and endangered tree species

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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: Pedro Esteban

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Most installations nowadays are exposed to many power quality problems, and they also face numerous challenges to comply with grid code and energy efficiency requirements. The reason behind this is that they are not designed to support nonlinear, non-balanced, and variable loads and generators that make up a large percentage of modern electric power systems. These problems and challenges become especially critical when designing green buildings and smart cities. These problems and challenges are caused by equipment that can be typically found in these installations like variable speed drives (VSD), transformers, lighting, battery chargers, double-conversion UPS (uninterruptible power supply) systems, highly dynamic loads, single-phase loads, fossil fuel generators and renewable generation sources, to name a few. Moreover, events like capacitor switching (from existing capacitor banks or passive harmonic filters), auto-reclose operations of transmission and distribution lines, or the starting of large motors also contribute to these problems and challenges. Active power filters (APF) are one of the fastest-growing power electronics technologies for solving power quality problems and meeting grid code and energy efficiency requirements for a wide range of segments and applications. They are a high performance, flexible, compact, modular, and cost-effective type of power electronics solutions that provide an instantaneous and effective response in low or high voltage electric power systems. They enable longer equipment lifetime, higher process reliability, improved power system capacity and stability, and reduced energy losses, complying with most demanding power quality and energy efficiency standards and grid codes. There can be found several types of active power filters, including active harmonic filters (AHF), static var generators (SVG), active load balancers (ALB), hybrid var compensators (HVC), and low harmonic drives (LHD) nowadays. All these devices can be used in applications in Smart Cities bringing several technical and economic benefits.

Keywords: power quality improvement, energy efficiency, grid code compliance, green buildings, smart cities

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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: Mirjana Dokmanovic

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The paper will introduce main findings of the research of the responses of the Central European and South Eastern European (CEE/SEE) countries to the global economic and financial crisis in 2008 from human rights and gender perspectives. The research methodology included desk research and qualitative analysis of the available data, studies, statistics, and reports produced by the governments, the UN agencies, international financial institutions (IFIs) and international network of civil society organizations. The main conclusion of the study is that the governments in the region missed to assess the impacts of their anti-crisis policies both ex ante and ex post from the standpoint of human rights and gender equality. Majority of the countries have focused their efforts solely on prompting up the banking and financial sectors, and construction business sectors. The tremendous debt which the states have accumulated for the rescue of banks and industries lead to further cuts in social expenses and reduction of public services. Decreasing state support to health care and social protection and declining family incomes made social services unaffordable for many families. Thus, the economic and financial crisis stirred up the care crisis that was absorbed by women’s intensifying unpaid work within a family and household to manage household survival strategy. On the other hand, increased burden of the care work weakened the position of women in the labour market and their opportunities to find a job. The study indicates that the artificial separation of the real economy and the sphere of social reproduction still persist. This has created additional burden of unpaid work of women within a family. The aim of this paper is to introduce the lessons learnt for future: (a) human rights may not be derogated in the times of crisis; (b) the obligation of states to mitigate negative impacts of economic policies to population, particularly to vulnerable groups, must be prioritized; (c) IFIs and business sector must be liable as duty bearers with respect to human rights commitments.

Keywords: CEE/SEE region, global financial and economic crisis, international financial institutions, human rights commitments, principle of non-derogability of human rights

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Authors: Mojtaba Eshraghi Arani

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According to the international conventions for the carriage of goods by sea, the consignee is the person who is entitled to take delivery of the cargo from the carrier. Such a person is usually named in the relevant box of the bill of lading unless the latter is issued “To Order” or “To Bearer”. However, there are some cases in which the apparent consignee, as above, was not intended to take delivery of cargo, like the L/C issuing bank or the freight forwarder who are named as consignee only for the purpose of security or acceleration of transit process. In such cases as well as the BL which is issued “To Order”, the so-called “real consignee” can be found out in the “Notify Party” box. The dispute revolves around the choice between apparent consignee and real consignee for being entitled not only to take delivery of the cargo but also to sue the carrier for any damages or loss. While it is a generally accepted rule that only the apparent consignee shall be vested with such rights, some courts like France’s Cour de Cassation have declared that the “Notify Party”, as the real consignee, was entitled to sue the carrier and in some cases, the same court went far beyond and permitted the real consignee to take suit even where he was not mentioned on the BL as a “Notify Party”. The main argument behind such reasoning is that the real consignee is the person who suffered the loss and thus had a legitimate interest in bringing action; of course, the real consignee must prove that he incurred a loss. It is undeniable that the above-mentioned approach is contrary to the position of the international conventions on the express definition of consignee. However, international practice has permitted the use of BL in a different way to meet the business requirements of banks, freight forwarders, etc. Thus, the issue is one of striking a balance between the international conventions on the one hand and existing practices on the other hand. While the latest convention applicable for sea transportation, i.e., the Rotterdam Rules, dealt with the comparable issue of “shipper” and “documentary shipper”, it failed to cope with the matter being discussed. So a new study is required to propose the best solution for amending the current conventions for carriage of goods by sea. A qualitative method with the concept of interpretation of data collection has been used in this article. The source of the data is the analysis of domestic and international regulations and cases. It is argued in this manuscript that the judge is not allowed to recognize any one as real consignee, other than the person who is mentioned in the “Consingee” box unless the BL is issued “To Order” or “To Bearer”. Moreover, the contract of carriage is independent of the sale contract and thus, the consignee must be determined solely based on the facts of the BL itself, like “Notify Party” and not any other contract or document.

Keywords: real consignee, cargo, delivery, to order, notify the party

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Authors: Harneet Walia, Morteza Zihayat

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Customer acquisition has become one of the critical issues of any business in the 21st century; having a healthy customer base is the essential asset of the bank business. Term deposits act as a major source of cheap funds for the banks to invest and benefit from interest rate arbitrage. To attract customers, the marketing campaigns at most financial institutions consist of multiple outbound telephonic calls with more than one contact to a customer which is a very time-consuming process. Therefore, customized direct marketing has become more critical than ever for attracting new clients. As customer acquisition is becoming more difficult to archive, having an intelligent and redefined list is necessary to sell a product smartly. Our aim of this research is to increase the effectiveness of campaigns by predicting customers who will most likely subscribe to the fixed deposit and suggest the most suitable month to reach out to customers. We design a Time Aware Upsell Prediction Framework (TAUPF) using two different approaches, with an aim to find the best approach and technique to build the prediction model. TAUPF is implemented using Upsell Prediction Approach (UPA) and Clustered Upsell Prediction Approach (CUPA). We also address the data imbalance problem by examining and comparing different methods of sampling (Up-sampling and down-sampling). Our results have shown building such a model is quite feasible and profitable for the financial institutions. The Time Aware Upsell Prediction Framework (TAUPF) can be easily used in any industry such as telecom, automobile, tourism, etc. where the TAUPF (Clustered Upsell Prediction Approach (CUPA) or Upsell Prediction Approach (UPA)) holds valid. In our case, CUPA books more reliable. As proven in our research, one of the most important challenges is to define measures which have enough predictive power as the subscription to a fixed deposit depends on highly ambiguous situations and cannot be easily isolated. While we have shown the practicality of time-aware upsell prediction model where financial institutions can benefit from contacting the customers at the specified month, further research needs to be done to understand the specific time of the day. In addition, a further empirical/pilot study on real live customer needs to be conducted to prove the effectiveness of the model in the real world.

Keywords: customer acquisition, predictive analysis, targeted marketing, time-aware analysis

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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 215

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 257

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

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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

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Authors: Minjuan Sun

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Ever since the late 1990s, China has experienced explosive growth in consumer lending, especially in short-term consumer loans, among which, the growth rate of non-bank lending has surpassed bank lending due to the development in financial technology. On the other hand, China does not have a universal credit scoring and registration system that can guide lenders during the processes of credit evaluation and risk control, for example, an individual’s bank credit records are not available for online lenders to see and vice versa. Given this context, the purpose of this paper is three-fold. First, we explore if and how alternative digital footprint data can be utilized to assess borrower’s creditworthiness. Then, we perform a comparative analysis of machine learning methods for the canonical problem of credit default prediction. Finally, we analyze, from an institutional point of view, the necessity of establishing a viable and nationally universal credit registration and scoring system utilizing online digital footprints, so that more people in China can have better access to the consumption loan market. Two different types of digital footprint data are utilized to match with bank’s loan default records. Each separately captures distinct dimensions of a person’s characteristics, such as his shopping patterns and certain aspects of his personality or inferred demographics revealed by social media features like profile image and nickname. We find both datasets can generate either acceptable or excellent prediction results, and different types of data tend to complement each other to get better performances. Typically, the traditional types of data banks normally use like income, occupation, and credit history, update over longer cycles, hence they can’t reflect more immediate changes, like the financial status changes caused by the business crisis; whereas digital footprints can update daily, weekly, or monthly, thus capable of providing a more comprehensive profile of the borrower’s credit capabilities and risks. From the empirical and quantitative examination, we believe digital footprints can become an alternative information source for creditworthiness assessment, because of their near-universal data coverage, and because they can by and large resolve the "thin-file" issue, due to the fact that digital footprints come in much larger volume and higher frequency.

Keywords: credit score, digital footprint, Fintech, machine learning

Procedia PDF Downloads 134

Authors: Ali Kadivar, Kaveh Niayesh

Abstract:

This report summarizes a simulation-based approach to estimate the current interruption behavior of a fuse element utilized in a DC network protecting battery banks under different stresses. Due to internal resistance of the battries, the short circuit current in very close to the nominal current, and it makes the fuse designation tricky. The base configuration considered in this report consists of five fuse units in parallel. The simulations are performed using a multi-physics software package, COMSOL® 5.6, and the necessary material parameters have been calculated using two other software packages.The first phase of the simulation starts with the heating of the fuse elements resulted from the current flow through the fusing element. In this phase, the heat transfer between the metallic strip and the adjacent materials results in melting and evaporation of the filler and housing before the aluminum strip is evaporated and the current flow in the evaporated strip is cut-off, or an arc is eventually initiated. The initiated arc starts to expand, so the entire metallic strip is ablated, and a long arc of around 20 mm is created within the first 3 milliseconds after arc initiation (v_elongation = 6.6 m/s. The final stage of the simulation is related to the arc simulation and its interaction with the external circuitry. Because of the strong ablation of the filler material and venting of the arc caused by the melting and evaporation of the filler and housing before an arc initiates, the arc is assumed to burn in almost pure ablated material. To be able to precisely model this arc, one more step related to the derivation of the transport coefficients of the plasma in ablated urethane was necessary. The results indicate that an arc current interruption, in this case, will not be achieved within the first tens of milliseconds. In a further study, considering two series elements, the arc was interrupted within few milliseconds. A very important aspect in this context is the potential impact of many broken strips parallel to the one where the arc occurs. The generated arcing voltage is also applied to the other broken strips connected in parallel with arcing path. As the gap between the other strips is very small, a large voltage of a few hundred volts generated during the current interruption may eventually lead to a breakdown of another gap. As two arcs in parallel are not stable, one of the arcs will extinguish, and the total current will be carried by one single arc again. This process may be repeated several times if the generated voltage is very large. The ultimate result would be that the current interruption may be delayed.

Keywords: DC network, high current / low SC fuses, FEM simulation, paralle fuses

Procedia PDF Downloads 44