Search results for: fusion models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6858

Search results for: fusion models

6828 Theoretical Investigation of Proton-Bore Fusion in Hot Spots

Authors: Morteza Habibi

Abstract:

As an alternative to D–T fuel, one can consider advanced fuels like D3-He and p-11B fuels, which have potential advantages concerning availability and/or environmental impact. Hot spots are micron-sized magnetically self-contained sources observed in pinched plasma devices. In hot spots, fusion power for 120 keV < Ti < 800 keV and 32 keV < Te < 129 keV exceeds bremsstrahlung loss and fraction of fusion power to bremsstrahlung loss reaches to 1.9. In this case, gain factor for a 150 kJ typical pulsed generator as a hot spot source will be 7.8 which is considerable for a commercial pinched plasma device.

Keywords: P-B fuel, hot spot, bremmsstrahlung loss, ion temperature

Procedia PDF Downloads 496
6827 Implementation and Comparative Analysis of PET and CT Image Fusion Algorithms

Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma

Abstract:

Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.

Keywords: image fusion, pyramid, wavelets, principal component analysis

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6826 Fusion of MOLA-based DEMs and HiRISE Images for Large-Scale Mars Mapping

Authors: Ahmed F. Elaksher, Islam Omar

Abstract:

In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

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6825 Construction of a Fusion Gene Carrying E10A and K5 with 2A Peptide-Linked by Using Overlap Extension PCR

Authors: Tiancheng Lan

Abstract:

E10A is a kind of replication-defective adenovirus which carries the human endostatin gene to inhibit the growth of tumors. Kringle 5(K5) has almost the same function as angiostatin to also inhibit the growth of tumors since they are all the byproduct of the proteolytic cleavage of plasminogen. Tumor size increasing can be suppressed because both of the endostatin and K5 can restrain the angiogenesis process. Therefore, in order to improve the treatment effect on tumor, 2A peptide is used to construct a fusion gene carrying both E10A and K5. Using 2A peptide is an ideal strategy when a fusion gene is expressed because it can avoid many problems during the expression of more than one kind of protein. The overlap extension PCR is also used to connect 2A peptide with E10A and K5. The final construction of fusion gene E10A-2A-K5 can provide a possible new method of the anti-angiogenesis treatment with a better expression performance.

Keywords: E10A, Kringle 5, 2A peptide, overlap extension PCR

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6824 Simulation for the Magnetized Plasma Compression Study

Authors: Victor V. Kuzenov, Sergei V. Ryzhkov

Abstract:

Ongoing experimental and theoretical studies on magneto-inertial confinement fusion (Angara, C-2, CJS-100, General Fusion, MagLIF, MAGPIE, MC-1, YG-1, Omega) and new constructing facilities (Baikal, C-2W, Z300 and Z800) require adequate modeling and description of the physical processes occurring in high-temperature dense plasma in a strong magnetic field. This paper presents a mathematical model, numerical method, and results of the computer analysis of the compression process and the energy transfer in the target plasma, used in magneto-inertial fusion (MIF). The computer simulation of the compression process of the magnetized target by the high-power laser pulse and the high-speed plasma jets is presented. The characteristic patterns of the two methods of the target compression are being analysed.

Keywords: magnetized target, magneto-inertial fusion, mathematical model, plasma and laser beams

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6823 Characterization of Inertial Confinement Fusion Targets Based on Transmission Holographic Mach-Zehnder Interferometer

Authors: B. Zare-Farsani, M. Valieghbal, M. Tarkashvand, A. H. Farahbod

Abstract:

To provide the conditions for nuclear fusion by high energy and powerful laser beams, it is required to have a high degree of symmetry and surface uniformity of the spherical capsules to reduce the Rayleigh-Taylor hydrodynamic instabilities. In this paper, we have used the digital microscopic holography based on Mach-Zehnder interferometer to study the quality of targets for inertial fusion. The interferometric pattern of the target has been registered by a CCD camera and analyzed by Holovision software. The uniformity of the surface and shell thickness are investigated and measured in reconstructed image. We measured shell thickness in different zone where obtained non uniformity 22.82 percent.  

Keywords: inertial confinement fusion, mach-zehnder interferometer, digital holographic microscopy, image reconstruction, holovision

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6822 Design and in Slico Study of the Truncated Spike-M-N SARS-CoV-2 as a Novel Effective Vaccine Candidate

Authors: Aghasadeghi MR., Bahramali G., Sadat SM., Sadeghi SA., Yousefi M., Khodaei K., Ghorbani M., Sadat Larijani M.

Abstract:

Background:The emerging COVID-19 pandemic is a serious concernfor the public health worldwide. Despite the many mutations in the virus genome, it is important to find an effective vaccine against viral mutations. Therefore, in current study, we aimed at immunoinformatic evaluation of the virus proteins immunogenicity to design a preventive vaccine candidate, which could elicit humoral and cellular immune responses as well. Methods:Three antigenic regions are included;Spike, Membrane, and Nucleocapsid amino acid sequences were obtained, and possible fusion proteins were assessed andcompared by immunogenicity, structural features, and population coverage. The best fusion protein was also evaluated for MHC-I and MHC-II T-cell epitopes and the linear and conformational B-cell epitopes. Results: Among the four predicted models, the truncated Spike protein in fusion with M and N proteins is composed of 24 highly immunogenic human MHC class I and 29 MHC class II, along with 14 B-cell linear and 61 discontinues epitopes. Also, the selected protein has high antigenicity and acceptable population coverage of 82.95% in Iran and 92.51% in Europe. Conclusion: The data indicate that the truncated Spike-M-N SARS-CoV-2form which could be potential targets of neutralizing antibodies. The protein also has the ability to stimulate humoral and cellular immunity. The in silico study provided the fusion protein as a potential preventive vaccine candidate for further in vivo evaluation.

Keywords: SARS-CoV-2, immunoinformatic, protein, vaccine

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6821 Clinical Outcomes and Surgical Complications in Patients with Cervical Disk Degeneration

Authors: Mirzashahi Babak, Mansouri Pejman, Najafi Arvin, Farzan Mahmoud

Abstract:

Introduction: There are several surgical treatment choices for cervical spondylotic myelopathy (CSM). The aim of this study is to evaluate clinical outcomes and surgical complications in patients with cervical disk degeneration (CDD) undergoing either anterior cervical discectomy with or without fusion or cervical laminectomy and fusion. Methods: This prospective case series study included 45 consecutive patients with cervical spondylotic myelopathy between January 2010 and November 2014. There were 28 males and 17 females, with a mean age of 47 (range 37-68) years. The mean clinical follow-up was 14 months (range 3-24 months). The Neck Disability Index (NDI), visual analog scale (VAS) neck and arm pain, Short Form-36 (SF-36) were used as the functional outcome measurements. All of the complications in our patients were recorded. Results: In our study group, 26 patients underwent only one or two level anterior cervical discectomy. Ten patients underwent anterior cervical discectomy and fusion (ACDF) and nine cases underwent posterior laminectomy and fusion. We have found a statistically significant improvement between mean preoperative (29, range 19-43) and postoperative (7, range 0-12) NDI scores following surgery (P < 0.05). Also, there was a statistically significant difference between pre and post-operative VAS and SF-36 score (p < 0.05). There was a 7% overall complication rate (n = 3). The only complication in our patients was surgical site cellulitis which has been managed with oral antibiotic therapy. Conclusion: Both anterior cervical discectomy with or without fusion or posterior laminectomy and fusion are safe and efficacious treatment options for the management of CSM. The clinical outcomes seem to be fairly reproducible.

Keywords: cervical, myelopathy, discectomy, fusion, laminectomy

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6820 Multi-Source Data Fusion for Urban Comprehensive Management

Authors: Bolin Hua

Abstract:

In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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6819 A Hybrid Image Fusion Model for Generating High Spatial-Temporal-Spectral Resolution Data Using OLI-MODIS-Hyperion Satellite Imagery

Authors: Yongquan Zhao, Bo Huang

Abstract:

Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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6818 Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with Evaluation on a Ground Truth

Authors: Hatem Hajri, Mohamed-Cherif Rahal

Abstract:

Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter

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6817 Morphological Features Fusion for Identifying INBREAST-Database Masses Using Neural Networks and Support Vector Machines

Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

Abstract:

In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

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6816 Environmental and Safety Studies for Advanced Fuel Cycle Fusion Energy Systems: The ESSENTIAL Approach

Authors: Massimo Zucchetti

Abstract:

In the US, the SPARC-ARC projects of compact tokamaks are being developed: both are aimed at the technological demonstration of fusion power reactors with cutting-edge technology but following different design approaches. However, they show more similarities than differences in the fuel cycle, safety, radiation protection, environmental, waste and decommissioning aspects: all reactors, either experimental or demonstration ones, have to fulfill certain "essential" requirements to pass from virtual to real machines, to be built in the real world. The paper will discuss these "essential" requirements. Some of the relevant activities in these fields, carried out by our research group (ESSENTIAL group), will be briefly reported, with the aim of showing some methodology aspects that have been developed and might be of wider interest. Also, a non-competitive comparison between our results for different projects will be included when useful. The question of advanced D-He3 fuel cycles to be used for those machines will be addressed briefly. In the past, the IGNITOR project of a compact high-magnetic field D-T ignition experiment was found to be able to sustain limited D-He3 plasmas, while the Candor project was a more decisive step toward D-He3 fusion reactors. The following topics will be treated: Waste management and radioactive safety studies for advanced fusion power plants; development of compact high-field advanced fusion reactors; behavior of nuclear materials under irradiation: neutron-induced radioactivity due to side DT reactions, radiation damage; accident analysis; reactor siting.

Keywords: advanced fuel fusion reactors, deuterium-helium3, high-field tokamaks, fusion safety

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6815 Cross Attention Fusion for Dual-Stream Speech Emotion Recognition

Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

Abstract:

Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

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6814 Entry Inhibitors Are Less Effective at Preventing Cell-Associated HIV-2 Infection than HIV-1

Authors: A. R. Diniz, P. Borrego, I. Bártolo, N. Taveira

Abstract:

Cell-to-cell transmission plays a critical role in the spread of HIV-1 infection in vitro and in vivo. Inhibition of HIV-1 cell-associated infection by antiretroviral drugs and neutralizing antibodies (NAbs) is more difficult compared to cell-free infection. Limited data exists on cell-associated infection by HIV-2 and its inhibition. In this work, we determined the ability of entry inhibitors to inhibit HIV-1 and HIV-2 cell-to cell fusion as a proxy to cell-associated infection. We developed a method in which Hela-CD4-cells are first transfected with a Tat expressing plasmid (pcDNA3.1+/Tat101) and infected with recombinant vaccinia viruses expressing either the HIV-1 (vPE16: from isolate HTLV-IIIB, clone BH8, X4 tropism) or HIV-2 (vSC50: from HIV-2SBL/ISY, R5 and X4 tropism) envelope glycoproteins (M.O.I.=1 PFU/cell).These cells are added to TZM-bl cells. When cell-to-cell fusion (syncytia) occurs the Tat protein diffuses to the TZM-bl cells activating the expression of a reporter gene (luciferase). We tested several entry inhibitors including the fusion inhibitors T1249, T20 and P3, the CCR5 antagonists MVC and TAK-779, the CXCR4 antagonist AMD3100 and several HIV-2 neutralizing antibodies (Nabs). All compounds inhibited HIV-1 and HIV-2 cell fusion albeit to different levels. Maximum percentage of HIV-2 inhibition (MPI) was higher for fusion inhibitors (T1249- 99.8%; P3- 95%, T20-90%) followed by co-receptor antagonists (MVC- 63%; TAK-779- 55%; AMD3100- 45%). NAbs from HIV-2 infected patients did not prevent cell fusion up to the tested concentration of 4μg/ml. As for HIV-1, MPI reached 100% with TAK-779 and T1249. For the other antivirals, MPIs were: P3-79%; T20-75%; AMD3100-61%; MVC-65%.These results are consistent with published data. Maraviroc had the lowest IC50 both for HIV-2 and HIV-1 (IC50 HIV-2= 0.06 μM; HIV-1=0.0076μM). Highest IC50 were observed with T20 for HIV-2 (3.86μM) and with TAK-779 for HIV-1 (12.64μM). Overall, our results show that entry inhibitors in clinical use are less effective at preventing Env mediated cell-to-cell-fusion in HIV-2 than in HIV-1 which suggests that cell-associated HIV-2 infection will be more difficult to inhibit compared to HIV-1. The method described here will be useful to screen for new HIV entry inhibitors.

Keywords: cell-to-cell fusion, entry inhibitors, HIV, NAbs, vaccinia virus

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6813 Cognitive Fusion and Obstacles to Valued Living: Beyond Pain-Specific Events in Chronic Pain

Authors: Sergio A. Carvalho, Jose Pinto-Gouveia, David Gillanders, Paula Castilho

Abstract:

The role of psychological processes has long been recognized as crucial factors in depressive symptoms in chronic pain (CP). Although some studies have explored the negative impact of being entangled with internal experiences (e.g., thoughts, emotions, physical sensations) – cognitive fusion, it is not extensively explored 1) whether these are pain-related or rather general difficult experiences, and 2) how they relate to experiencing obstacles in committing to valued actions. The current study followed a cross-sectional design in a sample of 231 participants with CP, in which a mediational model was tested through path analyses in AMOS software. The model presented a very good model fit (Χ²/DF = 1.161; CFI = .999; TLI = .996; RMSEA = .026, PCLOSE = .550.), and results showed that pain intensity was not directly related to depressive symptoms (β = .055; p = .239) but was mediated by cognitive fusion with both general and pain-related internal experiences (β = .181, 95%CI [.097; .271]; p = .015). Additionally, results showed that only general cognitive fusion (but not pain-specific fusion) was associated with experiencing obstacles to living a meaningful life, which mediated its impact on depressive symptoms (β = .197, 95%CI [.102; .307]; p = .001). Overall, this study adds on current literature by suggesting that psychological interventions to pain management should not be focused only on management of pain-related experiences, but also on developing more effective ways of relating to overall internal experiences.

Keywords: cognitive fusion, chronic pain, depressive symptoms, valued living

Procedia PDF Downloads 179
6812 Track Initiation Method Based on Multi-Algorithm Fusion Learning of 1DCNN And Bi-LSTM

Authors: Zhe Li, Aihua Cai

Abstract:

Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

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6811 Diagonal Vector Autoregressive Models and Their Properties

Authors: Usoro Anthony E., Udoh Emediong

Abstract:

Diagonal Vector Autoregressive Models are special classes of the general vector autoregressive models identified under certain conditions, where parameters are restricted to the diagonal elements in the coefficient matrices. Variance, autocovariance, and autocorrelation properties of the upper and lower diagonal VAR models are derived. The new set of VAR models is verified with empirical data and is found to perform favourably with the general VAR models. The advantage of the diagonal models over the existing models is that the new models are parsimonious, given the reduction in the interactive coefficients of the general VAR models.

Keywords: VAR models, diagonal VAR models, variance, autocovariance, autocorrelations

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6810 TMIF: Transformer-Based Multi-Modal Interactive Fusion for Rumor Detection

Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

Abstract:

The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

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6809 Epileptic Seizure Onset Detection via Energy and Neural Synchronization Decision Fusion

Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

Abstract:

This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

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6808 The Optimum Operating Conditions for the Synthesis of Zeolite from Waste Incineration Fly Ash by Alkali Fusion and Hydrothermal Methods

Authors: Yi-Jie Lin, Jyh-Cherng Chen

Abstract:

The fly ash of waste incineration processes is usually hazardous and the disposal or reuse of waste incineration fly ash is difficult. In this study, the waste incineration fly ash was converted to useful zeolites by the alkali fusion and hydrothermal synthesis method. The influence of different operating conditions (the ratio of Si/Al, the ratio of hydrolysis liquid to solid, and hydrothermal time) was investigated to seek the optimum operating conditions for the synthesis of zeolite from waste incineration fly ash. The results showed that concentrations of heavy metals in the leachate of Toxicity Characteristic Leaching Procedure (TCLP) were all lower than the regulatory limits except lead. The optimum operating conditions for the synthesis of zeolite from waste incineration fly ash by the alkali fusion and hydrothermal synthesis method were Si/Al=40, NaOH/ash=1.5, alkali fusion at 400 oC for 40 min, hydrolysis with Liquid to Solid ratio (L/S)= 200 at 105 oC for 24 h, and hydrothermal synthesis at 105 oC for 24 h. The specific surface area of fly ash could be significantly increased from 8.59 m2/g to 651.51 m2/g (synthesized zeolite). The influence of different operating conditions on the synthesis of zeolite from waste incineration fly ash followed the sequence of Si/Al ratio > hydrothermal time > hydrolysis L/S ratio. The synthesized zeolites can be reused as good adsorbents to control the air or wastewater pollutants. The purpose of fly ash detoxification, reduction and waste recycling/reuse is achieved successfully.

Keywords: alkali fusion, hydrothermal, fly ash, zeolite

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6807 Oxidative Stress Related Alteration of Mitochondrial Dynamics in Cellular Models

Authors: Orsolya Horvath, Laszlo Deres, Krisztian Eros, Katalin Ordog, Tamas Habon, Balazs Sumegi, Kalman Toth, Robert Halmosi

Abstract:

Introduction: Oxidative stress induces an imbalance in mitochondrial fusion and fission processes, finally leading to cell death. The two antioxidant molecules, BGP-15 and L2286 have beneficial effects on mitochondrial functions and on cellular oxidative stress response. In this work, we studied the effects of these compounds on the processes of mitochondrial quality control. Methods: We used H9c2 cardiomyoblast and isolated neonatal rat cardiomyocytes (NRCM) for the experiments. The concentration of stressors and antioxidants was beforehand determined with MTT test. We applied 1-Methyl-3-nitro-1-nitrosoguanidine (MNNG) in 125 µM, 400 µM and 800 µM concentrations for 4 and 8 hours on H9c2 cells. H₂O₂ was applied in 150 µM and 300 µM concentration for 0.5 and 4 hours on both models. L2286 was administered in 10 µM, while BGP-15 in 50 µM doses. Cellular levels of the key proteins playing role in mitochondrial dynamics were measured in Western blot samples. For the analysis of mitochondrial network dynamics, we applied electron microscopy and immunocytochemistry. Results: Due to MNNG treatment the level of fusion proteins (OPA1, MFN2) decreased, while the level of fission protein DRP1 elevated markedly. The levels of fusion proteins OPA1 and MNF2 increased in the L2286 and BGP-15 treated groups. During the 8 hour treatment period, the level of DRP1 also increased in the treated cells (p < 0.05). In the H₂O₂ stressed cells, administration of L2286 increased the level of OPA1 in both H9c2 and NRCM models. MFN2 levels in isolated neonatal rat cardiomyocytes raised considerably due to BGP-15 treatment (p < 0.05). L2286 administration decreased the DRP1 level in H9c2 cells (p < 0.05). We observed that the H₂O₂-induced mitochondrial fragmentation could be decreased by L2286 treatment. Conclusion: Our results indicated that the PARP-inhibitor L2286 has beneficial effect on mitochondrial dynamics during oxidative stress scenario, and also in the case of directly induced DNA damage. We could make the similar conclusions in case of BGP-15 administration, which, via reducing ROS accumulation, propagates fusion processes, this way aids preserving cellular viability. Funding: GINOP-2.3.2-15-2016-00049; GINOP-2.3.2-15-2016-00048; GINOP-2.3.3-15-2016-00025; EFOP-3.6.1-16-2016-00004; ÚNKP-17-4-I-PTE-209

Keywords: H9c2, mitochondrial dynamics, neonatal rat cardiomyocytes, oxidative stress

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6806 Investigation of Fusion Zone Microstructures in Plasma Arc Welding of Austenitic Stainless Steel (SS-304L) with Low Carbon Steel (A-36) with or without Filler Alloy

Authors: Shan-e-Fatima, Mushtaq Khan, Syed Imran Hussian

Abstract:

Plasma arc welding technology is used for welding SS-304L with A-36. Two different optimize butt welded joints were produced by using austenitic filler alloy E-309L and with direct fusion at 45 A, 2mm/sec by keeping plasma gas flow rate at 0.5LPM. Microstructure analysis of the weld bead was carried out. The results reveal complex heterogeneous microstructure in austenitic base filler alloy sample where as full martensite was found in directly fused sample.

Keywords: fusion zone microstructure, stainless steel, low carbon steel, plasma arc welding

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6805 Image Retrieval Based on Multi-Feature Fusion for Heterogeneous Image Databases

Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: feature fusion, image retrieval, membership function, normalization

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6804 Multi Biomertric Personal Identification System Based On Hybird Intellegence Method

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

Abstract:

Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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6803 Frequency of BCR-ABL Fusion Transcript Types with Chronic Myeloid Leukemia by Multiplex Polymerase Chain Reaction in Srinagarind Hospital, Khon Kaen Thailand

Authors: Kanokon Chaicom, Chitima Sirijerachai, Kanchana Chansung, Pinsuda Klangsang, Boonpeng Palaeng, Prajuab Chaimanee, Pimjai Ananta

Abstract:

Chronic myeloid leukemia (CML) is characterized by the consistent involvement of the Philadelphia chromosome (Ph), which is derived from a reciprocal translocation between chromosome 9 and 22, the main product of the t(9;22) (q34;q11) translocation, is found in the leukemic clone of at least 95% of CML patients. There are two major forms of the BCR/ABL fusion gene, involving ABL exon 2, but including different exons of BCR gene. The transcripts b2a2 (e13a2) or b3a2 (e14a2) code for a p210 protein. Another fusion gene leads to the expression of an e1a2 transcript, which codes for a p190 protein. Other less common fusion genes are b3a3 or b2a3, which codes for a p203 protein and e19a2 (c3a2) transcript, which codes for a p230 protein. Its frequency varies in different populations. In this study, we aimed to report the frequency of BCR-ABL fusion transcript types with CML by multiplex PCR (polymerase chain reaction) in Srinagarind Hospital, Khon Kaen, Thailand. Multiplex PCR for BCR-ABL was performed on 58 patients, to detect different types of BCR-ABL transcripts of the t (9; 22). All patients examined were positive for some type of BCR/ABL rearrangement. The majority of the patients (93.10%) expressed one of the p210 BCR-ABL transcripts, b3a2 and b2a2 transcripts were detected in 53.45% and 39.65% respectively. The expression of an e1a2 transcript showed 3.75%. Co-expression of p210/p230 was detected in 3.45%. Co-expression of p210/p190 was not detected. Multiplex PCR is useful, saves time and reliable in the detection of BCR-ABL transcript types. The frequency of one or other rearrangement in CML varies in different population.

Keywords: chronic myeloid leukemia, BCR-ABL fusion transcript types, multiplex PCR, frequency of BCR-ABL fusion

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6802 An Adaptive Back-Propagation Network and Kalman Filter Based Multi-Sensor Fusion Method for Train Location System

Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

Abstract:

The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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6801 RV-YOLOX: Object Detection on Inland Waterways Based on Optimized YOLOX Through Fusion of Vision and 3+1D Millimeter Wave Radar

Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

Abstract:

Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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6800 Keypoint Detection Method Based on Multi-Scale Feature Fusion of Attention Mechanism

Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

Abstract:

Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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6799 Radiation Protection and Licensing for an Experimental Fusion Facility: The Italian and European Approaches

Authors: S. Sandri, G. M. Contessa, C. Poggi

Abstract:

An experimental nuclear fusion device could be seen as a step toward the development of the future nuclear fusion power plant. If compared with other possible solutions to the energy problem, nuclear fusion has advantages that ensure sustainability and security. In particular considering the radioactivity and the radioactive waste produced, in a nuclear fusion plant the component materials could be selected in order to limit the decay period, making it possible the recycling in a new reactor after about 100 years from the beginning of the decommissioning. To achieve this and other pertinent goals many experimental machines have been developed and operated worldwide in the last decades, underlining that radiation protection and workers exposure are critical aspects of these facilities due to the high flux, high energy neutrons produced in the fusion reactions. Direct radiation, material activation, tritium diffusion and other related issues pose a real challenge to the demonstration that these devices are safer than the nuclear fission facilities. In Italy, a limited number of fusion facilities have been constructed and operated since 30 years ago, mainly at the ENEA Frascati Center, and the radiation protection approach, addressed by the national licensing requirements, shows that it is not always easy to respect the constraints for the workers' exposure to ionizing radiation. In the current analysis, the main radiation protection issues encountered in the Italian Fusion facilities are considered and discussed, and the technical and legal requirements are described. The licensing process for these kinds of devices is outlined and compared with that of other European countries. The following aspects are considered throughout the current study: i) description of the installation, plant and systems, ii) suitability of the area, buildings, and structures, iii) radioprotection structures and organization, iv) exposure of personnel, v) accident analysis and relevant radiological consequences, vi) radioactive wastes assessment and management. In conclusion, the analysis points out the needing of a special attention to the radiological exposure of the workers in order to demonstrate at least the same level of safety as that reached at the nuclear fission facilities.

Keywords: fusion facilities, high energy neutrons, licensing process, radiation protection

Procedia PDF Downloads 329