Search results for: axial flux induction machine

Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Ming-Yeh Lu, Shiao-Shing Chen, Saikat Sinha Ray, Hung-Te Hsu

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Recently, anaerobic membrane bioreactors (AnMBRs) has been widely utilized, which combines anaerobic biological treatment process and membrane filtration, that can be present an attractive option for wastewater treatment and water reuse. Conventional AnMBR is having several advantages, such as improving effluent quality, compact space usage, lower sludge yield, without aeration and production of energy. However, the removal of nitrogen and phosphorus in the AnMBR permeate was negligible which become the biggest disadvantage. In recent years, forward osmosis (FO) is an emerging technology that utilizes osmotic pressure as driving force to extract clean water without additional external pressure. The pore size of FO membrane is kindly mentioned the pore size, so nitrogen or phosphorus could effectively improve removal of nitrogen or phosphorus. Anaerobic bioreactor with FO membrane (AnOMBR) can retain the concentrate organic matters and nutrients. However, phosphorus is a non-renewable resource. Due to the high rejection property of FO membrane, the high amount of phosphorus could be recovered from the combination of AnMBR and FO. In this study, development of novel submerged anaerobic osmotic membrane bioreactor integrated with periodic microfiltration (MF) extraction for simultaneous phosphorus and clean water recovery from wastewater was evaluated. A laboratory-scale AnOMBR utilizes cellulose triacetate (CTA) membranes with effective membrane area of 130 cm² was fully submerged into a 5.5 L bioreactor at 30-35℃. Active layer-facing feed stream orientation was utilized, for minimizing fouling and scaling. Additionally, a peristaltic pump was used to circulate draw solution (DS) at a cross flow velocity of 0.7 cm/s. Magnesium sulphate (MgSO₄) solution was used as DS. Microfiltration membrane periodically extracted about 1 L solution when the TDS reaches to 5 g/L to recover phosphorus and simultaneous control the salt accumulation in the bioreactor. During experiment progressed, the average water flux was achieved around 1.6 LMH. The AnOMBR process show greater than 95% removal of soluble chemical oxygen demand (sCOD), nearly 100% of total phosphorous whereas only partial removal of ammonia, and finally average methane production of 0.22 L/g sCOD was obtained. Therefore, AnOMBR system periodically utilizes MF membrane extracted for phosphorus recovery with simultaneous pH adjustment. The overall performance demonstrates that a novel submerged AnOMBR system is having potential for simultaneous wastewater treatment and resource recovery from wastewater, and hence, the new concept of this system can be used to replace for conventional AnMBR in the future.

Keywords: anaerobic treatment, forward osmosis, phosphorus recovery, membrane bioreactor

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Malika Imoula, Rachid Saci, Renee Gatignol

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A numerical investigation is carried out to analyze vortex flows in a free surface cylinder, driven by the independent rotation and differentially heated boundaries. As a basic uncontrolled isothermal flow, we consider configurations which exhibit steady axisymmetric toroidal type vortices which occur at the free surface; under given rates of the bottom disk uniform rotation and for selected aspect ratios of the enclosure. In the isothermal case, we show that sidewall differential rotation constitutes an effective kinematic means of flow control: the reverse flow regions may be suppressed under very weak co-rotation rates, while an enhancement of the vortex patterns is remarked under weak counter-rotation. However, in this latter case, high rates of counter-rotation reduce considerably the strength of the meridian flow and cause its confinement to a narrow layer on the bottom disk, while the remaining bulk flow is diffusion dominated and controlled by the sidewall rotation. The main control parameters in this case are the rotational Reynolds number, the cavity aspect ratio and the rotation rate ratio defined. Then, the study proceeded to consider the sensitivity of the vortex pattern, within the Boussinesq approximation, to a small temperature gradient set between the ambient fluid and an axial thin rod mounted on the cavity axis. Two additional parameters are introduced; namely, the Richardson number Ri and the Marangoni number Ma (or the thermocapillary Reynolds number). Results revealed that reducing the rod length induces the formation of on-axis bubbles instead of toroidal structures. Besides, the stagnation characteristics are significantly altered under the combined effects of buoyant-thermocapillary convection. Buoyancy, induced under sufficiently high Ri, was shown to predominate over the thermocapillay motion; causing the enhancement (suppression) of breakdown when the rod is warmer (cooler) than the ambient fluid. However, over small ranges of Ri, the sensitivity of the flow to surface tension gradients was clearly evidenced and results showed its full control over the occurrence and location of breakdown. In particular, detailed timewise evolution of the flow indicated that weak thermocapillary motion was sufficient to prevent the formation of toroidal patterns. These latter detach from the surface and undergo considerable size reduction while moving towards the bulk flow before vanishing. Further calculations revealed that the pattern reappears with increasing time as steady bubble type on the rod. However, in the absence of the central rod and also in the case of small rod length l, the flow evolved into steady state without any breakdown.

Keywords: buoyancy, cylinder, surface tension, toroidal vortex

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Authors: Ramin Hosseinnezhad, Iurii Vozniak, Andrzej Galeski

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Shear-induced crystallization, originated from orientation of chains along the flow direction, is an inevitable part of most polymer processing technologies. It plays a dominant role in determining the final product properties and is affected by many factors such as shear rate, cooling rate, total strain, etc. Investigation of the shear-induced crystallization process become of great importance for preparation of nanocomposite, which requires crystallization of nanofibrous sheared inclusions at higher temperatures. Thus, the effects of shear time, shear rate, and also thermal condition of cooling on crystallization of two aliphatic-aromatic copolyesters have been investigated. This was performed using Linkam optical shearing system (CSS450) for both Ecoflex® F Blend C1200 produced by BASF and synthesized copolyester of butylene terephthalate and a mixture of butylene esters: adipate, succinate, and glutarate, (PBASGT), containing 60% of aromatic comonomer. Crystallization kinetics of these biodegradable copolyesters was studied at two different conditions of shearing. First, sample with a thickness of 60µm was heated to 60˚C above its melting point and subsequently subjected to different shear rates (100–800 sec-1) while cooling with specific rates. Second, the same type of sample was cooled down when shearing at constant temperature was finished. The intensity of transmitted depolarized light, recorded by a camera attached to the optical microscope, was used as a measure to follow the crystallization. Temperature dependencies of conversion degree of samples during cooling were collected and used to determine the half-temperature (Th), at which 50% conversion degree was reached. Shearing ecoflex films for 45 seconds with a shear rate of 100 sec-1 resulted in significant increase of Th from 56˚C to 70˚C. Moreover, the temperature range for the transition of molten samples to crystallized state decreased from 42˚C to 20˚C. Comparatively low shift of 10˚C in Th towards higher temperature was observed for PBASGT films at shear rate of 600 sec-1 for 45 seconds. However, insufficient melt flow strength and non-laminar flow due to Taylor vortices was a hindrance to reach more elevated Th at very high shear rates (600–800 sec-1). The shift in Th was smaller for the samples sheared at a constant temperature and subsequently cooled down. This may be attributed to the longer time gap between cessation of shearing and the onset of crystallization. The longer this time gap, the more possibility for crystal nucleus to re-melt at temperatures above Tm and for polymer chains to recoil and relax. It is found that the crystallization temperature, crystallization induction time and spherulite growth of aliphatic-aromatic copolyesters are dramatically influenced by both the cooling rate and the shear imposed during the process.

Keywords: induced crystallization, shear rate, aliphatic-aromatic copolyester, ecoflex

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Authors: Chunying Fang, Haifeng Li, Lin Ma, Mancai Zhang

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Speech intelligibility assessment is an important measure to evaluate the functional outcomes of surgical and non-surgical treatment, speech therapy and rehabilitation. The assessment of pathological speech plays an important role in assisting the experts. Pathological speech usually is non-stationary and mutational, in this paper, we describe a multi-granularity combined feature schemes, and which is optimized by hierarchical visual method. First of all, the difference granularity level pathological features are extracted which are BAFS (Basic acoustics feature set), local spectral characteristics MSCC (Mel s-transform cepstrum coefficients) and nonlinear dynamic characteristics based on chaotic analysis. Latterly, radar chart and F-score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96-dimensions.The experimental results denote that new features by support vector machine (SVM) has the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.

Keywords: pathological speech, multi-granularity feature, MSCC (Mel s-transform cepstrum coefficients), F-score, radar chart

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Authors: Ravi Raj, Louis Chiu, Deepak Marla, Aijun Huang

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Hybridization of the directed laser deposition (DLD) process using an in-situ micro-roller to impart a vertical compressive load on the deposited bead at elevated temperatures can relieve tensile residual stresses incurred in the process. To investigate this stress relief mechanism and its relationship with the in-situ rolling parameters, a fully coupled dynamic thermo-mechanical model is presented in this study. A single bead deposition of Ti-6Al-4V alloy with an in-situ roller made of mild steel moving at a constant speed with a fixed nominal bead reduction is simulated using the explicit solver of the finite element software, Abaqus. The thermal model includes laser heating during the deposition process and the heat transfer between the roller and the deposited bead. The laser heating is modeled using a moving heat source with a Gaussian distribution, applied along the pre-formed bead’s surface using the VDFLUX Fortran subroutine. The bead’s cross-section is assumed to be semi-elliptical. The interfacial heat transfer between the roller and the bead is considered in the model. Besides, the roller is cooled internally using axial water flow, considered in the model using convective heat transfer. The mechanical model for the bead and substrate includes the effects of rolling along with the deposition process, and their elastoplastic material behavior is captured using the J2 plasticity theory. The model accounts for strain, strain rate, and temperature effects on the yield stress based on Johnson-Cook’s theory. Various aspects of this material behavior are captured in the FE software using the subroutines -VUMAT for elastoplastic behavior, VUHARD for yield stress, and VUEXPAN for thermal strain. The roller is assumed to be elastic and does not undergo any plastic deformation. Also, contact friction at the roller-bead interface is considered in the model. Based on the thermal results of the bead, the distance between the roller and the deposition nozzle (roller o set) can be determined to ensure rolling occurs around the beta-transus temperature for the Ti-6Al-4V alloy. It is identified that roller offset and the nominal bead height reduction are crucial parameters that influence the residual stresses in the hybrid process. The results obtained from a simulation at roller offset of 20 mm and nominal bead height reduction of 7% reveal that the tensile residual stresses decrease to about 52% due to in-situ rolling throughout the deposited bead. This model can be used to optimize the rolling parameters to minimize the residual stresses in the hybrid DLD process with in-situ micro-rolling.

Keywords: directed laser deposition, finite element analysis, hybrid in-situ rolling, thermo-mechanical model

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Authors: Ahmed Ashit

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Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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Authors: Hongliang Zhang

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The use of chance procedures and randomizers in poetry-writing can be traced back to surrealist works, which, by appealing to Sigmund Freud's theories, were still logocentrism. In the 1960s, random permutation and combination were extensively used by the Oulipo, John Cage and Jackson Mac Low, which further deconstructed the metaphysical presence of writing. Today, the randomly-generated digital poetry has emerged as a genre of cybertext which should be co-authored by readers. At the same time, the classical theories have now been updated by cybernetics and media theories. N· Katherine Hayles put forward the concept of ‘the floating signifiers’ by Jacques Lacan to be the ‘the flickering signifiers’ , arguing that the technology per se has become a part of the textual production. This paper makes a historical review of the computer-generated poetry in the perspective of semiotics, emphasizing that the randomly-generated digital poetry which hands over the dual tasks of both interpretation and writing to the readers demonstrates the intervention of media technology in literature. With the participation of computerized algorithm and programming languages, poems randomly generated by computers have not only blurred the boundary between encoder and decoder, but also raises the issue of human-machine. It is also a significant feature of the cybertext that the productive process of the text is full of randomness.

Keywords: cybertext, digital poetry, poetry generator, semiotics

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Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

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Authors: Chia-Ju Peng, Shih-Jui Chen

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This paper proposes a method to discriminate electroencephalogram (EEG) signals between different concentration states using empirical mode decomposition (EMD). Brain-computer interface (BCI), also called brain-machine interface, is a direct communication pathway between the brain and an external device without the inherent pathway such as the peripheral nervous system or skeletal muscles. Attention level is a common index as a control signal of BCI systems. The EEG signals acquired from people paying attention or in relaxation, respectively, are decomposed into a set of intrinsic mode functions (IMF) by EMD. Fast Fourier transform (FFT) analysis is then applied to each IMF to obtain the frequency spectrums. By observing power spectrums of IMFs, the proposed method has the better identification of EEG attention level than the original EEG signals between different concentration states. The band power of IMF3 is the most obvious especially in β wave, which corresponds to fully awake and generally alert. The signal processing method and results of this experiment paves a new way for BCI robotic system using the attention-level control strategy. The integrated signal processing method reveals appropriate information for discrimination of the attention and relaxation, contributing to a more enhanced BCI performance.

Keywords: biomedical engineering, brain computer interface, electroencephalography, rehabilitation

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Authors: Juan Pablo Botero Torres, Alba Avila, Luis Felipe Giraldo

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Independent navigation and mobility through unknown spaces pose a challenge for the autonomy of visually impaired people (VIP), who have relied on the use of traditional assistive tools like the white cane and trained dogs. However, emerging visually assistive technologies (VAT) have proposed several human-machine interfaces (HMIs) that could improve VIP’s ability for self-guidance. Hereby, we introduce the design and implementation of a visually assistive device, Anajaa – Visual Substitution System (AVSS). This system integrates ultrasonic sensors with custom electronics, and computer vision models (convolutional neural networks), in order to achieve a robust system that acquires information of the surrounding space and transmits it to the user in an intuitive and efficient manner. AVSS consists of two modules: the sensing and the actuation module, which are fitted to a chest mount and belt that communicate via Bluetooth. The sensing module was designed for the acquisition and processing of proximity signals provided by an array of ultrasonic sensors. The distribution of these within the chest mount allows an accurate representation of the surrounding space, discretized in three different levels of proximity, ranging from 0 to 6 meters. Additionally, this module is fitted with an RGB-D camera used to detect potentially threatening obstacles, like staircases, using a convolutional neural network specifically trained for this purpose. Posteriorly, the depth data is used to estimate the distance between the stairs and the user. The information gathered from this module is then sent to the actuation module that creates an HMI, by the means of a 3x2 array of vibration motors that make up the tactile display and allow the system to deliver haptic feedback. The actuation module uses vibrational messages (tactones); changing both in amplitude and frequency to deliver different awareness levels according to the proximity of the obstacle. This enables the system to deliver an intuitive interface. Both modules were tested under lab conditions, and the HMI was additionally tested with a focal group of VIP. The lab testing was conducted in order to establish the processing speed of the computer vision algorithms. This experimentation determined that the model can process 0.59 frames per second (FPS); this is considered as an adequate processing speed taking into account that the walking speed of VIP is 1.439 m/s. In order to test the HMI, we conducted a focal group composed of two females and two males between the ages of 35-65 years. The subject selection was aided by the Colombian Cooperative of Work and Services for the Sightless (COOTRASIN). We analyzed the learning process of the haptic messages throughout five experimentation sessions using two metrics: message discrimination and localization success. These correspond to the ability of the subjects to recognize different tactones and locate them within the tactile display. Both were calculated as the mean across all subjects. Results show that the focal group achieved message discrimination of 70% and a localization success of 80%, demonstrating how the proposed HMI leads to the appropriation and understanding of the feedback messages, enabling the user’s awareness of its surrounding space.

Keywords: computer vision on embedded systems, electronic trave aids, human-machine interface, haptic feedback, visual assistive technologies, vision substitution systems

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Authors: Roya Yumul, Ofelia Loani Elvir-Lazo, Sevan Komshian, Ruby Wang, Jun Tang

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BACKGROUND: An objective means for monitoring the anti-nociceptive effects of perioperative medications has long been desired as a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively. To this end, electroencephalogram (EEG) based tools including BIS and qCON were designed to provide information about the depth of sedation while qNOX was produced to inform on the degree of antinociception. The goal of this study was to compare the reliability of qCON/qNOX to BIS as specific indicators of response to nociceptive stimulation. METHODS: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board (IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to the endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed on all patients prior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. RESULTS: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from 74 ±13 mm Hg at baseline to 84 ± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76 ± 12 BPM at baseline to 80 ± 13 BPM during noxious stimuli [p=0.078] respectively). CONCLUSION: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices

Keywords: antinociception, BIS, general anesthesia, LMA, qCON/qNOX

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

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Authors: Harun Aydilek, Asiye Aydilek, Ali Allahverdi

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The total tardiness is a widely used performance measure in the scheduling literature. This performance measure is particularly important in situations where there is a cost to complete a job beyond its due date. The cost of scheduling increases as the gap between a job's due date and its completion time increases. Such costs may also be penalty costs in contracts, loss of goodwill. This performance measure is important as the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. The problem is addressed in the literature, however, it has been assumed zero setup times. Even though this assumption may be valid for some environments, it is not valid for some other scheduling environments. When setup times are treated as separate from processing times, it is possible to increase machine utilization and to reduce total tardiness. Therefore, non-zero setup times need to be considered as separate. A dominance relation is developed and several algorithms are proposed. The developed dominance relation is utilized in the proposed algorithms. Extensive computational experiments are conducted for the evaluation of the algorithms. The experiments indicated that the developed algorithms perform much better than the existing algorithms in the literature. More specifically, one of the newly proposed algorithms reduces the error of the best existing algorithm in the literature by 40 percent.

Keywords: algorithm, assembly flowshop, dominance relation, total tardiness

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Authors: Xia Huo

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The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu and 34 children from Haojiang. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and both the alpha diversity index and specific metabolites in single-element models. The study found that the Bayesian kernel machine regression (BKMR) model showed a negative correlation between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the Chao 1 index, particularly beyond the 55th percentile. Furthermore, the EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our research suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the gut microbiota and its metabolites. These alterations may be associated with neurodevelopmental abnormalities in children.

Keywords: gut microbiota, 6PPDQ, PBDEs, PCBs, metal(loid)s, BKMR

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Authors: Morgan Kuligowski, Marientina Gotsis

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Extended reality (XR) technologies share an intertwined history with spaceflight and innovation. New advancements in XR technologies offer expanding possibilities to advance the future of human space exploration with increased crew autonomy. This paper seeks to identify implementation gaps between existing and proposed XR space applications to inform future mission planning. A review of virtual reality, augmented reality, and mixed reality technologies implemented aboard the International Space Station revealed a total of 16 flown investigations. A secondary set of ground-tested XR human spaceflight applications were systematically retrieved from literature sources. The two sets of XR technologies, those flown and those existing in the literature were analyzed to characterize application domains and device types. Comparisons between these groups revealed untapped application areas for XR to support crew psychological health, in-flight training, and extravehicular operations on future flights. To fill these roles, integrating XR technologies with advancements in biometric sensors and machine learning tools is expected to transform crew capabilities.

Keywords: augmented reality, extended reality, international space station, mixed reality, virtual reality

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Authors: Sean Goltz, Michael Mayo

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The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.

Keywords: taxation, law, multinational, corporation

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Authors: Feng Xu, Zhaozhi Liu, Junhua Xu, Xiaolong Tang, Dunwen Zuo

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Chemical vapor deposition (CVD) diamond coated cutting tool has excellent cutting performance, it is the most ideal tool for the processing of nonferrous metals and alloys, composites, nonmetallic materials and other difficult-to-machine materials efficiently and accurately. Depositing CVD diamond coating on the cemented carbide with high cobalt content can improve its toughness and strength, therefore, it is very important to research on the preparation technology and cutting properties of CVD diamond coated cemented carbide cutting tool with high cobalt content. The preparation technology of boron-doped diamond (BDD) coating has been studied and the coated drills were prepared. BDD coating were deposited on the drills by using the optimized parameters and the SEM results show that there are no cracks or collapses in the coating. Cutting tests with the prepared drills against the silumin and aluminum base printed circuit board (PCB) have been studied. The results show that the wear amount of the coated drill is small and the machined surface has a better precision. The coating does not come off during the test, which shows good adhesion and cutting performance of the drill.

Keywords: cemented carbide with high cobalt content, CVD boron-doped diamond, cutting test, drill

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Authors: Anastasios Georgoulas, Manolia Andredaki, Marco Marengo

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The present paper investigates the hydrodynamics and heat transfer characteristics of slug-plug flows under saturated flow boiling conditions within circular micro-channels. Numerical simulations are carried out, using an enhanced version of the open-source CFD-based solver ‘interFoam’ of OpenFOAM CFD Toolbox. The proposed user-defined solver is based in the Volume Of Fluid (VOF) method for interface advection, and the mentioned enhancements include the implementation of a smoothing process for spurious current reduction, the coupling with heat transfer and phase change as well as the incorporation of conjugate heat transfer to account for transient solid conduction. In all of the considered cases in the present paper, a single phase simulation is initially conducted until a quasi-steady state is reached with respect to the hydrodynamic and thermal boundary layer development. Then, a predefined and constant frequency of successive vapour bubbles is patched upstream at a certain distance from the channel inlet. The proposed numerical simulation set-up can capture the main hydrodynamic and heat transfer characteristics of slug-plug flow regimes within circular micro-channels. In more detail, the present investigation is focused on exploring the interaction between subsequent vapour slugs with respect to their generation frequency, the hydrodynamic characteristics of the liquid film between the generated vapour slugs and the channel wall as well as of the liquid plug between two subsequent vapour slugs. The proposed investigation is carried out for the 3 different working fluids and three different values of applied heat flux in the heated part of the considered microchannel. The post-processing and analysis of the results indicate that the dynamics of the evolving bubbles in each case are influenced by both the upstream and downstream bubbles in the generated sequence. In each case a slip velocity between the vapour bubbles and the liquid slugs is evident. In most cases interfacial waves appear close to the bubble tail that significantly reduce the liquid film thickness. Finally, in accordance with previous investigations vortices that are identified in the liquid slugs between two subsequent vapour bubbles can significantly enhance the convection heat transfer between the liquid regions and the heated channel walls. The overall results of the present investigation can be used to enhance the present understanding by providing better insight of the complex, underpinned heat transfer mechanisms in saturated boiling within micro-channels in the slug-plug flow regime.

Keywords: slug-plug flow regime, micro-channels, VOF method, OpenFOAM

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Authors: Ming-Jong Tsai, Y. L. Cheng, Y. L. Kuo, S. Y. Hsiao, J. W. Chen, P. H. Liu, D. H. Chen

Abstract:

The 3D printing is a combination of digital technology, material science, intelligent manufacturing and control of opto-mechatronics systems. It is called the third industrial revolution from the view of the Economist Journal. A color 3D printing machine may provide the necessary support for high value-added industrial and commercial design, architectural design, personal boutique, and 3D artist’s creation. The main goal of this paper is to develop photo-curable color 3D manufacturing technology and system implementation. The key technologies include (1) Photo-curable color 3D additive manufacturing processes development and materials research (2) Piezo type ink-jet head control and Opto-mechatronics integration technique of the photo-curable color 3D laminated manufacturing system. The proposed system is integrated with single Piezo type ink-jet head with two individual channels for two primary UV light curable color resins which can provide for future colorful 3D printing solutions. The main research results are 16 grey levels and grey resolution of 75 dpi.

Keywords: 3D printing, additive manufacturing, color, photo-curable, Piezo type ink-jet, UV Resin

Procedia PDF Downloads 562

Authors: Khalil Aryanfar, Pariya Gholipor, Elmira Hafez

Abstract:

This study examines the proportionality between the needs of industry and technical and vocational training of male and female vocational schools. The research method was descriptive that was conducted in two parts: documentary analysis and needs assessment and Delphi method was used in the need assessment. The statistical population of the study included 312 individuals from the industry sector employers and 52 of them were selected through stratified random sampling. Methods of data collection in this study, upstream documents include: document of the development of technical and vocational training, Statistical Yearbook 1393 in Tehran, the available documents in Isfahan Planning Department, the findings indicate that there is an almost proportionality between the needs of industry and Vocational training of male and female vocational schools in fields of welding, industrial electronics, electro technique, industrial drawing, auto mechanics, design, packaging, machine tool, metalworking, construction, accounting, computer graphics and the Administrative Affairs. The findings indicate that there is no proportionality between the needs of industry and Vocational training of male and female vocational schools in fields of Thermal - cooling systems, building electricity, building drawing, interior architecture, car electricity and motor repair.

Keywords: needs assessment, technical and vocational training, industry

Procedia PDF Downloads 455

Authors: Noushin Shokouhinejad, Hasan Razmi, Reza Fekrazad, Saeed Asgary, Ammar Neshati, Hadi Assadian, Sanam Kheirieh

Abstract:

This study compared the push-out bond strength of mineral trioxide aggregate (MTA) and a new endodontic cement (NEC) as root-end filling materials in root-end cavities prepared by ultrasonic technique (US) or Er,Cr:YSGG laser (L). Eighty single-rooted extracted human teeth were endodontically treated, apicectomised and randomly divided into four following groups (n = 20): US/MTA, US/NEC, L/MTA and L/NEC. In US/MTA and US/NEC groups, rooted cavities were prepared with ultrasonic retrotip and filled with MTA and NEC, respectively. In L/MTA and L/NEC groups, root-end cavities were prepared using Er, Cr:YSGG laser and filled with MTA and NEC, respectively. Each root was cut apically to create a 2 mm-thick root slice for measurement of bond strength using a universal testing machine. Then, all slices were examined to determine the mode of bond failure. Data were analysed using two-way ANOVA. Root-end filling materials showed significantly higher bond strength in root-end cavities prepared using the ultrasonic technique (US/MTA and US/NEC) (P < 0.001). The bond strengths of MTA and NEC did not differ significantly. The failure modes were mainly adhesive for MTA, but cohesive for NEC. In conclusion, bond strengths of MTA and NEC to root-end cavities were comparable and higher in ultrasonically prepared cavities.

Keywords: bond strength, Er, Cr:YSGG laser, MTA, NEC, root-end cavity

Procedia PDF Downloads 347

Authors: Keigo Nishitani, Kohei Mizuta Mizuta, Kazuyoshi Kurita, Yukinori Taniguchi

Abstract:

To establish mass production process of Ti capsule which has Fe powder inside as magnetic hyperthermia implant, we assumed that Ti thin sheet can be drawn into a φ1.0 mm die hole through the medium of Fe Powder and becomes outer shell of capsule. This study discusses mechanism of powder assisted deep drawing process by both of numerical simulation and experiment. Ti thin sheet blank was placed on die, and was covered by Fe powder layer without pressurizing. Then upper punch was indented on the Fe powder layer, and the blank can be drawn into die cavity as pressurized powder particles were extruded into die cavity from behind of the drawn blank. Distinct Element Method (DEM) has been used to demonstrate the process. To identify bonding parameters on Fe particles which are cohesion, tensile bond stress and inter particle friction angle, axial and diametrical compression failure test of Fe powder compact was conducted. Several density ratios of powder compacts in range of 0.70 - 0.85 were investigated and relationship between mean stress and equivalent stress was calculated with consideration of critical state line which rules failure criterion in consolidation of Fe powder. Since variation of bonding parameters with density ratio has been experimentally identified, and good agreement has been recognized between several failure tests and its simulation, demonstration of powder assisted sheet forming by using DEM becomes applicable. Results of simulation indicated that indent/drawing length of Ti thin sheet is promoted by smaller Fe particle size, larger indent punch diameter, lower friction coefficient between die surface and Ti sheet and certain degrees of die inlet taper angle. In the deep drawing test, we have made die-set with φ2.4 mm punch and φ1.0 mm die bore diameter. Pure Ti sheet with 100 μm thickness, annealed at 650 deg. C has been tested. After indentation, indented/drawn capsule has been observed by microscope, and its length was measured to discuss the feasibility of this capsulation process. Longer drawing length exists on progressive loading pass comparing with the case of single stroke loading. It is expected that progressive loading has an advantage of which extrusion of powder particle into die cavity with Ti sheet is promoted since powder particle layer can be rebuilt while the punch is withdrawn from the layer in each loading steps. This capsulation phenomenon is qualitatively demonstrated by DEM simulation. Finally, we have fabricated Ti capsule which has Fe powder inside for magnetic hyperthermia cancer care treatment. It is concluded that suggested method is possible to use the manufacturing of Ti capsule implant for magnetic hyperthermia cancer care.

Keywords: metal powder compaction, metal forming, distinct element method, cancer care, magnetic hyperthermia

Procedia PDF Downloads 299

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

Procedia PDF Downloads 421

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

Abstract:

Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

Procedia PDF Downloads 176

Authors: Teja Koduru

Abstract:

Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

Procedia PDF Downloads 242

Authors: Yoji Yamato

Abstract:

In this paper, we propose an automatic verification technology of software patches for user virtual environments on IaaS Cloud to decrease verification costs of patches. In these days, IaaS services have been spread and many users can customize virtual machines on IaaS Cloud like their own private servers. Regarding to software patches of OS or middleware installed on virtual machines, users need to adopt and verify these patches by themselves. This task increases operation costs of users. Our proposed method replicates user virtual environments, extracts verification test cases for user virtual environments from test case DB, distributes patches to virtual machines on replicated environments and conducts those test cases automatically on replicated environments. We have implemented the proposed method on OpenStack using Jenkins and confirmed the feasibility. Using the implementation, we confirmed the effectiveness of test case creation efforts by our proposed idea of 2-tier abstraction of software functions and test cases. We also evaluated the automatic verification performance of environment replications, test cases extractions and test cases conductions.

Keywords: OpenStack, cloud computing, automatic verification, jenkins

Procedia PDF Downloads 491

Authors: Juanita, B. Kombaitan, Iwan Pratoyo Kusumantoro

Abstract:

The traditional mode is a non-motorized vehicle powered by human or animal power. The objective of the study was to define the strategy of using traditional modes by the framework of sustainable urban transport in support of urban tourism activities. The study of the traditional mode does not include a modified mode using the engine power as motor tricycles are often called ‘bentor ‘in Indonesia. The use of non-motorized traditional mode in Indonesia has begun to shift, and its use began to be eliminated by the change of propulsion using the machine. In an effort to push back the use of traditional mode one of them with tourism activities. Strategies for the use of traditional modes within the framework of sustainable urban transport are seen from three dimensions: social, economic and environmental. The social dimension related to accessibility and livability, an economic dimension related to traditional modes can promote products and tourist attractions, while the environmental dimension related to the needs of the users/groups with respect to safety, comfort. The traditional mode is rarely noticed by the policy makers, and public opinion in its use needs attention. The involvement of policy-making between stakeholders and the community is needed in the development of sustainable traditional mode strategies in support of urban tourism activities.

Keywords: traditional mode, sustainable, urban, transportation

Procedia PDF Downloads 267

Authors: Xueying Zhao, Ke Ma, Hui Li, Yu Cao, Fan Yang, Qingwen Xu, Wenbin Liu

Abstract:

Massively parallel sequencing (MPS) technologies allow high-throughput sequencing analyses with a relatively affordable price and have gradually been applied to forensic casework. MPS technology identifies short tandem repeat (STR) loci based on sequence so that repeat motif variation within STRs can be detected, which may help one to infer the origin of the mutation in some cases. Here, we report on one case with one three-step mismatch (D18S51) in family trios based on both capillary electrophoresis (CE) and MPS typing. The alleles of the alleged father (AF) are [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₁₅. The mother’s alleles are [AGAA]₁₉ and [AGAA]₉AGGA[AGAA]₃. The questioned child’s (QC) alleles are [AGAA]₁₉ and [AGAA]₁₂. Given that the sequence variants in repeat regions of AF and mother are not observed in QC’s alleles, the QC’s allele [AGAA]₁₂ was likely inherited from the AF’s allele [AGAA]₁₅ by loss of three repeat [AGAA]. Besides, two new alleles of D18S51 in this study, [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₉AGGA[AGAA]₃, have not been reported before. All the results in this study were verified using Sanger-type sequencing. In summary, the MPS typing method can offer valuable information for forensic genetics research and play a promising role in paternity testing.

Keywords: family trios analysis, forensic casework, ion torrent personal genome machine (PGM), massively parallel sequencing (MPS)

Procedia PDF Downloads 302