Search results for: spatiotemporal fusion

Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: M. L. Anitha, K. A. Radhakrishna Rao

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With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, Valencia Pérez, Héctor Fernando, Lamadrid A. Alberto, Vivanco V. Martín

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Cosmology is a discipline commonly linked to philosophy. In this work, we show cosmology, from a perspective that can provide some proposals to help develop SMB in Mexico. We start from the belief that, in a complex world, the solutions to problems must nurture from different approaches. In order to be able to do this, we need to change our point of reference and use theoretical proposals and methodologies that came from other disciplines; in this case, we will try to show that between philosophy and administration exist dialogs that need to be incentivized. The work is structured in three parts. In the first one, we create a description of cosmology and how it could be applied to business. In the second, we show some of the most common problems that the SMB suffer from and in the third, we present a proposal of how cosmology can help improve the development. Finally, we concluded that better understanding of real needs, integration of knowledge at large scale and using information technologies within the cosmology framework presentment could make a difference.

Keywords: harmonic fusion, national sustainability, financial management, triple helix

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Authors: Lourdes Yareth Herrera-Chavez, Alberto Ruiz, Victor H. Lopez

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Superalloys are used in components that operate at high temperatures such as pressure vessels and heat exchanger tubing. Design standards for these components must consider creep resistance among other criteria. Fusion welding processes are commonly used in the industry to join such components. Fusion processes commonly generate three distinctive zones, i.e. heat affected zone (HAZ), namely weld metal (WM) and base metal (BM). In nickel-based superalloy, the microstructure developed during fusion welding dictates the mechanical response of the welded component and it is very important to establish these effects in the mechanical response of the component. In this work, two plates of Inconel 600 superalloy were Gas Metal Arc Welded (GMAW). Creep samples were cut and milled to specifications and creep tested at a temperature (650 °C) using stress level of 350, 300, 275, 250 and 200 MPa. Microstructural analysis results showed a progressive creep damage evolution that depends on the stress levels with a preferential accumulation of creep damage at the heat affected zone where the creep rupture preferentially occurs owing to an austenitic matrix with grain boundary precipitated of the type Cr23C6. The fractured surfaces showed dimple patterns of cavity and voids. Results indicated that the damage mechanism is due to cavity growth by the combined effect of the power law and diffusion creep.

Keywords: austenitic microstructure, creep damage evolution, heat affected zone, vickers microhardness

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Authors: Rio Hirakawa, Christian Gundlach, Sven Hartwig

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Aluminium has been used in a wide range of industrial applications due to its numerous advantages, including excellent specific strength, thermal conductivity, corrosion resistance, workability and recyclability. The automotive industry is increasingly adopting multi-materials, including aluminium in structures and components to improve the mechanical usability and performance of individual components. A common method for assembling dissimilar materials is mechanical joining, but mechanical joining requires multiple manufacturing steps, affects the mechanical properties of the base material and increases the weight due to additional metal parts. Fusion bonding is being used in more and more industries as a way of avoiding the above drawbacks. Infusion bonding, and surface pre-treatment of the base material is essential to ensure the long-life durability of the joint. Laser surface treatment of aluminium has been shown to improve the durability of the joint by forming a passive oxide film and roughening the substrate surface. Infusion bonding, the polymer bonds directly to the metal instead of the adhesive, but the sensitivity to interfacial contamination is higher due to the chemical activity and molecular size of the polymer. Laser-treated surfaces are expected to absorb impurities from the storage atmosphere over time, but the effect of such changes in the treated surface over time on the durability of fusion-bonded joints has not yet been fully investigated. In this paper, the effect of the ageing of laser-treated surfaces of aluminum alloys on the corrosion resistance of fusion-bonded joints is therefore investigated. AlMg3 of 1.5 mm thickness was cut using a water-jet cutting machine, cleaned and degreased with isopropanol and surface pre-treated with a pulsed fiber laser at a wavelength of 1060 nm, maximum power of 70 W and repetition rate of 55 kHz. The aluminum surfaces were then stored in air for various periods of time and their corrosion resistance was assessed by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). For the aluminum joints, induction heating was employed as the fusion bonding method and single-lap shear specimens were prepared. The corrosion resistance of the joints was assessed by measuring the lap shear strength before and after neutral salt spray. Cross-sectional observations by scanning electron microscopy (SEM) were also carried out to investigate changes in the microstructure of the bonded interface. Finally, the corrosion resistance of the surface and the joint were compared and the differences in the mechanisms of corrosion resistance enhancement between the two were discussed.

Keywords: laser surface treatment, pre-treatment, bonding, corrosion, durability, interface, automotive, aluminium alloys, joint, fusion bonding

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Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

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In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

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Authors: Rim Frikha, Nouha Bouayed Abdelmoula, Afifa Sellami, Salima Daoud, Tarek Rebai

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Klippel-Feil Syndrome (KFS) is characterized by congenital vertebral fusion of the cervical spine resulting from faulty segmentation along the embryo's developing axis. A wide spectrum of associated anomalies may be present. This heterogeneity has complicated elucidation of the genetic etiology and management of the syndrome. We report a case of an isolated Klippel-Feil Syndrome with C5-C6 fusion on the cervical spine. It‘s the rarest form of congenital fused cervical vertebrae which is predisposed to the risk of spinal cord injury and neurologic problems. The aim of this paper was to review clinical heterogeneity; radiographic abnormalities and genetic etiology in Klippel-Feil Syndrome. We insist in comprehensive evaluation and delineation of diagnostic and prognostic classes.

Keywords: Klippel–Feil anomaly, genetic, clinical heterogeneity, radiographic abnormalities

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Authors: D. R. Ambika, K. R. Radhika, D. Seshachalam

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Unconstrained authentication is an important component for personal automated systems and human-computer interfaces. Existing solutions mostly use face as the primary object of analysis. The performance of face-based systems is largely determined by the extent of deformation caused in the facial region and amount of useful information available in occluded face images. Periocular region is a useful portion of face with discriminative ability coupled with resistance to deformation. A reliable portion of periocular area is available for occluded images. The present work demonstrates that joint representation of periocular texture and periocular structure provides an effective expression and poses invariant representation. The proposed methodology provides an effective and compact description of periocular texture and shape. The method is tested over four benchmark datasets exhibiting varied acquisition conditions.

Keywords: periocular authentication, Zernike moments, LBP variance, shape and texture fusion

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Sundaresan Soundararajan, George Ezekiel Silvananthan, Chor Ngee Tan

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Introduction: Transforaminal Interbody Fusion (TLIF) has been adopted for many decades now, however, XLIF, still in relative infancy, has grown to be accepted as a new Minimally Invasive Surgery (MIS) option. There is a paucity of reports directly comparing lateral approach surgery to other MIS options such as TLIF in the treatment of lumbar degenerative disc diseases. Aims/Objectives: The objective of this study was to compare the efficacy and clinical outcomes between Minimally Invasive Transforaminal Interbody Fusion (TLIF) and Minimally Invasive Lateral Interbody Fusion (XLIF) in the treatment of patients with degenerative disc disease of the lumbar spine. Methods: A single center, retrospective cohort study involving a total of 38 patients undergoing surgical intervention between 2010 and 2013 for degenerative disc disease of lumbar spine at single L4/L5 level. 18 patients were treated with MIS TLIF, and 20 patients were treated with XLIF. Results: The XLIF group showed shorter duration of surgery compared to the TLIF group (176 mins vs. 208.3 mins, P = 0.03). Length of hospital stay was also significantly shorter in XLIF group (5.9 days vs. 9 days, p = 0.03). Intraoperative blood loss was favouring XLIF as 85% patients had blood loss less than 100cc compared to 58% in the TLIF group (P = 0.03). Radiologically, disc height was significantly improved post operatively in the XLIF group compared to the TLIF group (0.56mm vs. 0.39mm, P = 0.01). Foraminal height increment was also higher in the XLIF group (0.58mm vs. 0.45mm , P = 0.06). Clinically, back pain and leg pain improved in 85% of patients in the XLIF group and 78% in the TLIF group. Post op hip flexion weakness was more common in the XLIF group (40%) than in the TLIF group (0%). However, this weakness resolved within 6 months post operatively. There was one case of dural tear and surgical site infection in the TLIF group respectively and none in the XLIF group. Visual Analog Scale (VAS) score 6 months post operatively showed comparable reduction in both groups. TLIF group had Owsterty Disability Index (ODI) improvement on 67% while XLIF group showed improvement of 70% of its patients. Conclusions: Lateral approach surgery shows comparable clinical outcomes in resolution of back pain and radiculopathy to conventional MIS techniques such as TLIF. With significantly shorter duration of surgical time, minimal blood loss and shorter hospital stay, XLIF seems to be a reasonable MIS option compared to other MIS techniques in treating degenerative lumbar disc diseases.

Keywords: extreme lateral interbody fusion, lateral approach, minimally invasive, XLIF

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Authors: Chantal Hendriks, Harry Gibson, Anna Trett, Penny Hancock, Catherine Moyes

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The use of modern inputs for crop protection, such as insecticides, is strongly underestimated in Sub-Saharan Africa. Several studies measured toxic concentrations of insecticides in fruits, vegetables and fish that were cultivated in Sub-Saharan Africa. The use of agricultural insecticides has impact on human and environmental health, but it also has the potential to impact on insecticide resistance in malaria transmitting mosquitos. To analyse associations between historic use of agricultural insecticides and the distribution of insecticide resistance through space and time, the use and environmental fate of agricultural insecticides needs to be mapped through the same time period. However, data on the use and environmental fate of agricultural insecticides in Africa are limited and therefore risk maps on the spatiotemporal occurrence of agricultural insecticides are created using environmental data. Environmental data on crop density and crop type were used to select the areas that most likely receive insecticides. These areas were verified by a literature review and expert knowledge. Pesticide fate models were compared to select most dominant processes that are involved in the environmental fate of insecticides and that can be mapped at a continental scale. The selected processes include: surface runoff, erosion, infiltration, volatilization and the storing and filtering capacity of soils. The processes indicate the risk for insecticide accumulation in soil, water, sediment and air. A compilation of all available data for traces of insecticides in the environment was used to validate the maps. The risk maps can result in space and time specific measures that reduce the risk of insecticide exposure to non-target organisms.

Keywords: crop protection, pesticide fate, tropics, insecticide resistance

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Authors: N. Ghatwary, A. Ahmed, H. Jalab

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In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

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Authors: Tianhao Zhang, Cen Chen, Dawei Cheng, Yuqi Liang, Yuanyuan Liang

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Dealing with anomalies is a crucial preprocessing step for multivariate time series prediction. However, existing methods that separate anomaly preprocessing and model training into two stages have certain limitations. Specifically, these methods fail to leverage auxiliary information necessary to distinguish latent anomalies related to spatiotemporal factors during the preprocessing stage. Instead, they solely rely on data distribution for detection which may lead to incorrect processing of many samples that are beneficial for training. To address this, we propose STTS-EAD, an end-to-end method that seamlessly integrates anomaly detection into the training process of multivariate time series forecasting and aims to improve Spatio-Temporal learning based Time Series prediction via Embedded Anomaly Detection. Our proposed STTS-EAD leverages spatio-temporal information for forecasting and anomaly detection, with the two parts alternately executed and optimized for each other. To the best of our knowledge, STTS-EAD is the first to integrate anomaly detection and forecasting tasks in the training phase for improving the accuracy of multivariate time series forecasting. Extensive experiments on a public stock dataset and two real-world sales datasets from a renowned coffee chain enterprise show that our proposed method can effectively process detected anomalies in the training stage to improve forecasting performance in the inference stage and significantly outperform baselines.

Keywords: multivariate time series, anomaly detection, time series forecasting, spatiotemporal feature learning

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Authors: Gargi Phadke, Mugdha Joshi, Shamal Salunkhe

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Facial sketches are used as a crucial clue by criminal investigators for identification of suspects when the description of eyewitness or victims are only available as evidence. A forensic artist develops a sketch as per the verbal description is given by an eyewitness that shows the facial look of the culprit. In this paper, the fusion of Scale Invariant Feature Transform (SIFT) and multiscale local binary patterns (MLBP) are proposed as a feature to recognize a forensic face sketch images from a gallery of mugshot photos. This work focuses on comparative analysis of proposed scheme with existing algorithms in different challenges like illumination change and rotation condition. Experimental results show that proposed scheme can lead to better performance for the defined problem.

Keywords: SIFT feature, MLBP, PCA, face sketch

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Authors: Rodrigo Antunes, Olga Borisevich, David Demange

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In future nuclear fusion reactors, tritium self-sufficiency will be ensured by tritium (3H) production via reactions between the fusion neutrons and lithium. To favor tritium breeding, a neutron multiplier must also be used. Both tritium breeder and neutron multiplier will be placed in the so-called Breeding Blanket (BB). For the European Helium-Cooled Pebble Bed (HCPB) BB concept, the tritium production and neutron multiplication will be ensured by neutron bombardment of Li4SiO4 and Be pebbles, respectively. The produced tritium is extracted from the pebbles by purging them with large flows of He (~ 104 Nm3h-1), doped with small amounts of H2 (~ 0.1 vol%) to promote tritium extraction via isotopic exchange (producing HT). Due to the presence of oxygen in the pebbles, production of tritiated water is unavoidable. Therefore, the purging gas downstream of the BB will be composed by Q2/Q2O/He (Q = 1H, 2H, 3H), with Q2/Q2O down to ppm levels, which must be further processed for tritium recovery. A two-stage continuous approach, where zeolite membranes (ZMs) are followed by a catalytic membrane reactor (CMR), has been recently proposed to fulfil this task. The tritium recovery from Q2/Q2O/He is ensured by the CMR, that requires a reduction of the gas flow coming from the BB and a pre-concentration of Q2 and Q2O to be efficient. For this reason, and to keep this stage with reasonable dimensions, ZMs are required upfront to reduce as much as possible the He flows and concentrate the Q2/Q2O species. Therefore, experimental activities have been carried out at the Tritium Laboratory Karlsruhe (TLK) to test the separation performances of different zeolite membranes for H2/H2O/He. First experiments have been performed with binary mixtures of H2/He and H2O/He with commercial MFI-ZSM5 and NaA zeolite-type membranes. Only the MFI-ZSM5 demonstrated selectivity towards H2, with a separation factor around 1.5, and H2 permeances around 0.72 µmolm-2s-1Pa-1, rather independent for feed concentrations in the range 0.1 vol%-10 vol% H2/He. The experiments with H2O/He have demonstrated that the separation factor towards H2O is highly dependent on the feed concentration and temperature. For instance, at 0.2 vol% H2O/He the separation factor with NaA is below 2 and around 1000 at 5 vol% H2O/He, at 30°C. Overall, both membranes demonstrated complementary results at equivalent temperatures. In fact, at low feed concentrations ( ≤ 1 vol% H2O/He) MFI-ZSM5 separates better than NaA, whereas the latter has higher separation factors for higher inlet water content ( ≥ 5 vol% H2O/He). In this contribution, the results obtained with both MFI-ZSM5 and NaA membranes for H2/He and H2O/H2 mixtures at different concentrations and temperatures are compared and discussed.

Keywords: nuclear fusion, gas separation, tritium processes, zeolite membranes

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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Authors: Robnier Reyes, Andrew J. P. Marques, Joel Ramjist, Chris R. Pasarikovski, Victor X. D. Yang

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Over the past three decades, surgical robotic systems have demonstrated their ability to improve surgical outcomes. The LBR Med is a collaborative robotic arm that is meant to work with a surgeon to streamline surgical workflow. It has 7 degrees of freedom and thus can be easily oriented. Position and torque sensors at each joint allow it to maintain a position accuracy of 150 µm with real-time force and torque feedback, making it ideal for complex surgical procedures. Spinal fusion procedures involve the placement of as many as 20 pedicle screws, requiring a great deal of accuracy due to proximity to the spinal canal and surrounding vessels. Any deviation from intended path can lead to major surgical complications. Assistive surgical robotic systems are meant to serve as collaborative devices easing the workload of the surgeon, thereby improving pedicle screw placement by mitigating fatigue related inaccuracies. Moreover, robotic spinal systems have shown marked improvements over conventional freehanded techniques in both screw placement accuracy and fusion quality and have greatly reduced the need for screw revision, intraoperatively and post-operatively. However, current assistive spinal fusion robots, such as the ROSA Spine, are limited in functionality to positioning surgical instruments. While they offer a small degree of improvement in pedicle screw placement accuracy, they do not alleviate surgeon fatigue, nor do they provide real-time force and torque feedback during screw insertion. We propose a semi-autonomous surgical robot workflow for spinal fusion where the surgeon guides the robot to its initial position and orientation, and the robot drives the pedicle screw accurately into the vertebra. Here, we demonstrate feasibility by inserting pedicle screws into ex-vivo bovine rib bone. The robot monitors position, force and torque with respect to predefined values selected by the surgeon to ensure the highest possible spinal fusion quality. The workflow alleviates the strain on the surgeon by having the robot perform the screw placement while the ability to monitor the process in real-time keeps the surgeon in the system loop. The approach we have taken in terms of level autonomy for the robot reflects its ability to safely collaborate with the surgeon in the operating room without external navigation systems.

Keywords: ex vivo bovine bone, pedicle screw, surgical robot, surgical workflow

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Authors: B. R. S. Babu, E. Prasad, P. V. Laveen, A. M. Vinodkumar

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Searching the “Island of stability” is a topic of extreme interest in theoretical as well as experimental modern physics today. This “island of stability” is spanned by superheavy elements (SHE's) that are produced in the laboratory. SHE's are believed to exist primarily due to the “magic” stabilizing effects of nuclear shell structure. SHE synthesis is extremely difficult due to their very low production cross section, often of the order of pico barns or less. Stabilizing effects of shell closures at proton number Z=82 and neutron number N=126 are predicted theoretically. Though stabilizing effects of Z=82 have been experimentally verified, no concluding observations have been made with N=126, so far. We measured and analyzed the total evaporation residue (ER) cross sections for a number of systems with neutron number around 126 to explore possible shell closure effects in ER cross sections, in this work.

Keywords: super heavy elements, fusion, evaporation residue, compund nucleus

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Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Long Wang, Yongjin Feng, Xiaofang Luo

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Tritium permeation through structural materials is a significant issue for fusion demonstration (DEMO) reactor blankets in terms of fuel cycle efficiency and radiological safety. Reduced activation ferritic (RAFM) steel CLF-1 is a prime candidate for the China’s CFETR blanket structural material, facing high permeability of hydrogen isotopes at reactor operational temperature. To confine tritium as much as possible in the reactor, surface modification of the steels including fabrication of tritium permeation barrier (TPB) attracts much attention. As a new alloy system, high entropy alloy (HEA) contains at least five principal elements, each of which ranges from 5 at% to 35 at%. This high mixing effect entitles HEA extraordinary comprehensive performance. So it is attractive to lead HEA into surface alloying for protective use. At present, studies on the hydrogen isotope permeability of HEA coatings is still insufficient and corresponding mechanism isn’t clear. In our study, we prepared three kinds of HEA coatings, including AlCrTaTiZr, (AlCrTaTiZr)N and (AlCrTaTiZr)O. After comprehensive characterization of SEM, XPS, AFM, XRD and TEM, the structure and composition of the HEA coatings were obtained. Deuterium permeation tests were conducted to evaluate the hydrogen isotope permeability of AlCrTaTiZr, (AlCrTaTiZr)N and (AlCrTaTiZr)O HEA coatings. Results proved that the (AlCrTaTiZr)N and (AlCrTaTiZr)O HEA coatings had better hydrogen isotope permeation resistance. Through analyzing and characterizing the hydrogen isotope permeation results of the corroded samples, an internal link between hydrogen isotope permeation behavior and structure of HEA coatings was established. The results provide valuable reference in engineering design of structural and TPB materials for future fusion device.

Keywords: high entropy alloy, hydrogen isotope permeability, tritium permeation barrier, fusion demonstration reactor

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Authors: I. Nyoman Mahayasa Adiputra

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Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.

Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city

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Authors: Ezzeddin Anawa, Abdol-Ghane Olabi

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The dissimilar joint between aluminum /titanium alloys (Al 6082 and Ti G2) alloys were successfully achieved by CO2 laser welding with a single pass and without filler material using the overlap joint design. Laser welding parameters ranges combinations were experimentally determined using Taguchi approach with the objective of producing welded joint with acceptable welding profile and high quality of mechanical properties. In this study a joining of dissimilar Al 6082 / Ti G2 was result in three distinct regions fusion area (FA), heat-affected zone (HAZ), and the unaffected base metal (BM) in the weldment. These regions are studied in terms of its microstructural characteristics and microhardness which are directly affecting the welding quality. The weld metal was mainly composed of martensite alpha prime. In two different metals in the two different sides of joint HAZ, grain growth was detected. The microhardness of the joint distribution also has shown microhardness increasing in the HAZ of two base metals and a varying microhardness in fusion zone.

Keywords: microharness , microstructure, laser welding and dissimilar jointed materials.

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Authors: Fadwa Alaskar, Fang-Chieh Chou, Carlos Flores, Xiao-Yun Lu, Alexandre M. Bayen

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This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car-following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter’s resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration tracking system. Several highway tests have been performed with two trucks. The tests show accurate and fast tracking of the target, which impacts on the gap control loop positively. The experiments also show the fulfilment of control design requirements, such as fast speed variations tracking and robust time gap following.

Keywords: object tracking, perception, sensor fusion, adaptive cruise control, cooperative adaptive cruise control

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Authors: Charbel Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Jitendar Kumar Tiwari, Ajay Mandal, N. Sathish, A. K. Srivastava

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Since the last decade, graphene achieved great attention toward the progress of multifunction metal matrix composites, which are highly demanded in industries to develop energy-efficient systems. This study covers the two advanced aspects of the latest scientific endeavor, i.e., graphene as reinforcement in metallic materials and additive manufacturing (AM) as a processing technology. Herein, high-quality graphene and AlSi10Mg powder mechanically mixed by very low energy ball milling with 0.1 wt. % and 0.2 wt. % graphene. Mixed powder directly subjected to the powder bed fusion process, i.e., an AM technique to produce composite samples along with bare counterpart. The effects of graphene on porosity, microstructure, and mechanical properties were examined in this study. The volumetric distribution of pores was observed under X-ray computed tomography (CT). On the basis of relative density measurement by X-ray CT, it was observed that porosity increases after graphene addition, and pore morphology also transformed from spherical pores to enlarged flaky pores due to improper melting of composite powder. Furthermore, the microstructure suggests the grain refinement after graphene addition. The columnar grains were able to cross the melt pool boundaries in case of the bare sample, unlike composite samples. The smaller columnar grains were formed in composites due to heterogeneous nucleation by graphene platelets during solidification. The tensile properties get affected due to induced porosity irrespective of graphene reinforcement. The optimized tensile properties were achieved at 0.1 wt. % graphene. The increment in yield strength and ultimate tensile strength was 22% and 10%, respectively, for 0.1 wt. % graphene reinforced sample in comparison to bare counterpart while elongation decreases 20% for the same sample. The hardness indentations were taken mostly on the solid region in order to avoid the collapse of the pores. The hardness of the composite was increased progressively with graphene content. Around 30% of increment in hardness was achieved after the addition of 0.2 wt. % graphene. Therefore, it can be concluded that powder bed fusion can be adopted as a suitable technique to develop graphene reinforced AlSi10Mg composite. Though, some further process modification required to avoid the induced porosity after the addition of graphene, which can be addressed in future work.

Keywords: graphene, hardness, porosity, powder bed fusion, tensile properties

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Authors: John Hardy

Abstract:

The expansion of special operations forces (SOF) in the twenty-first century is often discussed in terms of the size and disposition of SOF units. Research regarding the number SOF personnel, the equipment SOF units procure, and the variety of roles and mission that SOF fulfill in contemporary conflicts paints a fascinating picture of changing expectations for the use of force. A strong indicator of the changing nature of SOF in contemporary conflicts is the fusion of strike and intelligence functions in the SOF in many countries. What were once more distinct roles on the kind of battlefield generally associated with the concept of conventional warfare have become intermingled in the era of persistent conflict which SOF face. This study presents a historical analysis of the co-evolution of the intelligence and direct action functions carried out by SOF in counterterrorism, counterinsurgency, and training and mentoring missions between 2004 and 2016. The study focuses primarily on innovation in the US military and the diffusion of key concepts to US allies first, and then more broadly afterward. The findings show that there were three key phases of evolution throughout the period of study, each coinciding with a process of innovation and doctrinal adaptation. The first phase was characterized by the fusion of intelligence at the tactical and operational levels. The second phase was characterized by the industrial counterterrorism campaigns used by US SOF against irregular enemies in Iraq and Afghanistan. The third phase was characterized by increasing forward collection of actionable intelligence by SOF force elements in the course of direct action raids. The evolution of strike and intelligence functions in SOF operations between 2004 and 2016 was significantly influenced by reciprocity. Intelligence fusion led to more effective targeting, which then increased intelligence collection. Strike and intelligence functions were then enhanced by greater emphasis on intelligence exploitation during operations, which further increased the effectiveness of both strike and intelligence operations.

Keywords: counterinsurgency, counterterrorism, intelligence, irregular warfare, military operations, special operations forces

Procedia PDF Downloads 235