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| 2. |
- Zhao, C., et al.
(author)
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First performance results of the ALICE TPC Readout Control Unit 2
- 2016
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In: Journal of Instrumentation. - 1748-0221. ; 11:1
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Journal article (peer-reviewed)abstract
- This paper presents the first performance results of the ALICE TPC Readout Control Unit 2 (RCU2). With the upgraded hardware typology and the new readout scheme in FPGA design, the RCU2 is designed to achieve twice the readout speed of the present Readout Control Unit. Design choices such as using the flash-based Microsemi Smartfusion2 FPGA and applying mitigation techniques in interfaces and FPGA design ensure a high degree of radiation tolerance. This paper presents the system level irradiation test results as well as the first commissioning results of the RCU2. Furthermore, it will be concluded with a discussion of the planned updates in firmware.
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| 3. |
- Abelev, Betty, et al.
(author)
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Long-range angular correlations on the near and away side in p-Pb collisions at root S-NN=5.02 TeV
- 2013
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In: Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. - : Elsevier BV. - 0370-2693. ; 719:1-3, s. 29-41
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Journal article (peer-reviewed)abstract
- Angular correlations between charged trigger and associated particles are measured by the ALICE detector in p-Pb collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV for transverse momentum ranges within 0.5 < P-T,P-assoc < P-T,P-trig < 4 GeV/c. The correlations are measured over two units of pseudorapidity and full azimuthal angle in different intervals of event multiplicity, and expressed as associated yield per trigger particle. Two long-range ridge-like structures, one on the near side and one on the away side, are observed when the per-trigger yield obtained in low-multiplicity events is subtracted from the one in high-multiplicity events. The excess on the near-side is qualitatively similar to that recently reported by the CMS Collaboration, while the excess on the away-side is reported for the first time. The two-ridge structure projected onto azimuthal angle is quantified with the second and third Fourier coefficients as well as by near-side and away-side yields and widths. The yields on the near side and on the away side are equal within the uncertainties for all studied event multiplicity and p(T) bins, and the widths show no significant evolution with event multiplicity or p(T). These findings suggest that the near-side ridge is accompanied by an essentially identical away-side ridge. (c) 2013 CERN. Published by Elsevier B.V. All rights reserved.
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| 4. |
- Alme, J., et al.
(author)
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RCU2-The ALICE TPC readout electronics consolidation for Run2
- 2013
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In: Journal of Instrumentation. - 1748-0221. ; 8
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Journal article (peer-reviewed)abstract
- This paper presents the solution for optimization of the ALICE TPC readout for running at full energy in the Run2 period after 2014. For the data taking with heavy ion beams an event readout rate of 400 Hz with a low dead time is envisaged for the ALICE central barrel detectors during these three years. A new component, the Readout Control Unit 2 (RCU2), is being designed to increase the present readout rate by a factor of up to 2.6. The immunity to radiation induced errors will also be significantly improved by the new design.
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| 5. |
- Bhatti, A., et al.
(author)
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Recognition and Classification of Handwritten Urdu Numerals Using Deep Learning Techniques
- 2023
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In: Applied Sciences. - : MDPI. - 2076-3417. ; 13:3
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Journal article (peer-reviewed)abstract
- Urdu is a complex language as it is an amalgam of many South Asian and East Asian languages; hence, its character recognition is a huge and difficult task. It is a bidirectional language with its numerals written from left to right while script is written in opposite direction which induces complexities in the recognition process. This paper presents the recognition and classification of a novel Urdu numeral dataset using convolutional neural network (CNN) and its variants. We propose custom CNN model to extract features which are used by Softmax activation function and support vector machine (SVM) classifier. We compare it with GoogLeNet and the residual network (ResNet) in terms of performance. Our proposed CNN gives an accuracy of 98.41% with the Softmax classifier and 99.0% with the SVM classifier. For GoogLeNet, we achieve an accuracy of 95.61% and 96.4% on ResNet. Moreover, we develop datasets for handwritten Urdu numbers and numbers of Pakistani currency to incorporate real-life problems. Our models achieve best accuracies as compared to previous models in the literature for optical character recognition (OCR).
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| 7. |
- Gadallah, Adel S., et al.
(author)
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Anti-Inflammatory Principles from Tamarix aphylla L. : A Bioassay-Guided Fractionation Study
- 2020
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In: Molecules. - : MDPI AG. - 1431-5157 .- 1420-3049. ; 25:13
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Journal article (peer-reviewed)abstract
- Natural products have served as primary remedies since ancient times due to their cultural acceptance and outstanding biodiversity. To investigate whether Tamarix aphylla L. modulates an inflammatory process, we carried out bioassay-guided isolation where the extracts and isolated compounds were tested for their modulatory effects on several inflammatory indicators, such as nitric oxide (NO), reactive oxygen species (ROS), proinflammatory cytokine; tumour necrosis factor (TNF-alpha), as well as the proliferation of the lymphocyte T-cells. The aqueous ethanolic extract of the plant inhibited the intracellular ROS production, NO generation, and T-cell proliferation. The aqueous ethanolic crude extract was partitioned by liquid-liquid fractionation using n-hexane (n-C6H6), dichloromethane (DCM), ethyl acetate (EtOAc),n-butanol (n-BuOH), and water (H2O). The DCM and n-BuOH extracts showed the highest activity against most inflammatory indicators and were further purified to obtain compounds 1-4. The structures of 3,5-dihydroxy-4',7-dimethoxyflavone (1) and 3,5-dihydroxy-4-methoxybenzoic acid methyl ester (2) from the DCM extracts; and kaempferol (3), and 3-hydroxy-4-methoxy-(E)-cinnamic acid (4) from then-BuOH extract were elucidated by different spectroscopic tools, including MS, NMR, UV, and IR. Compound 2 inhibited the production of ROS and TNF-alpha, whereas compound 3 showed inhibitory activity against all the tested mediators. A better understanding of the potential aspect of Tamarix aphylla L. derivatives as anti-inflammatory agents could open the door for the development of advanced anti-inflammatory entities.
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| 8. |
- Anjum, Asad Ur Rehman, et al.
(author)
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Sensitivity Analysis of Mathematical Model to Study the Effect of T Cells Infusion in Treatment of CLL
- 2020
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In: Mathematics. - : MDPI AG. - 2227-7390. ; 8:4
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Journal article (peer-reviewed)abstract
- In this paper, we considered a mathematical model concerned with the treatment of Chronic Lymphocytic Leukemia (CLL) taking into account the effect of superficially infused T cells in this particular type of tumor. The model is described thoroughly by the system of non-linear differential equations explaining the interaction of naive, infected, cancer and immune cell population. The detailed sensitivity analysis with the application is the major part of this paper. The basic objective is to provide insight to how parameters' behavior varies model results by elaborating the results obtained from the application of sensitivity analysis. The sensitivity of the model was evaluated not only theoretically, but also with the help of a numerical approach, producing graphs providing better imminent of results. We argue that the application of the sensitivity analysis method endows an insight into how and which parameters are of primary significance in controlling the spread of leukemia.
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| 9. |
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| 10. |
- Haq, M. U., et al.
(author)
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Capsule Network with Its Limitation, Modification, and Applications—A Survey
- 2023
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In: Machine Learning and Knowledge Extraction. - : Multidisciplinary Digital Publishing Institute (MDPI). - 2504-4990. ; 5:3, s. 891-921
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Journal article (peer-reviewed)abstract
- Numerous advancements in various fields, including pattern recognition and image classification, have been made thanks to modern computer vision and machine learning methods. The capsule network is one of the advanced machine learning algorithms that encodes features based on their hierarchical relationships. Basically, a capsule network is a type of neural network that performs inverse graphics to represent the object in different parts and view the existing relationship between these parts, unlike CNNs, which lose most of the evidence related to spatial location and requires lots of training data. So, we present a comparative review of various capsule network architectures used in various applications. The paper’s main contribution is that it summarizes and explains the significant current published capsule network architectures with their advantages, limitations, modifications, and applications.
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| 11. |
- Manssour, J., et al.
(author)
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Analysis and performance of network decoding strategies for cooperative network coding
- 2013
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In: Physical Communication. - : Elsevier BV. - 1874-4907 .- 1876-3219. ; 6, s. 48-61
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Journal article (peer-reviewed)abstract
- In this work, we present two new low-complexity network decoding strategies for cooperative network coding in a multiple-access relay channel scenario. For these two strategies, Selection and Soft Combining and Majority Vote Network Decoding, along with the optimal joint network decoding, we derive expressions for bit error probability performance as a function of the signal-to-noise ratio (SNR) of the different Rayleigh fading links, and show the tightness of the derived bounds through simulation results. The two proposed schemes provide a similar bit error probability (BEP) performance compared to the optimal scheme, while having significantly lower complexity. Further, we study the effect of user pairing on the error performance by considering different SNRs on the user and relay links towards the destination. It is also shown that the error performance of the different schemes follows the same trend for a given user pairing strategy.
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| 12. |
- Mo, Fan, et al.
(author)
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A maturity model for the autonomy of manufacturing systems
- 2023
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In: The International Journal of Advanced Manufacturing Technology. - : Springer Nature. - 0268-3768 .- 1433-3015. ; 126:1-2, s. 405-428
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Journal article (peer-reviewed)abstract
- Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility, and resilience. To adapt to these new requirements, manufacturers should consider investigating, investing in, and implementing system autonomy. Autonomy is being adopted in multiple industrial contexts, but divergences arise when formalizing the concept of autonomous systems. To develop an implementation of autonomous manufacturing systems, it is essential to specify what autonomy means, how autonomous manufacturing systems are different from other autonomous systems, and how autonomous manufacturing systems are identified and achieved through the main features and enabling technologies. With a comprehensive literature review, this paper provides a definition of autonomy in the manufacturing context, infers the features of autonomy from different engineering domains, and presents a five-level model of autonomy — associated with maturity levels for the features — to ensure the complete identification and evaluation of autonomous manufacturing systems. The paper also presents the evaluation of a real autonomous system that serves as a use-case and a validation of the model.
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| 13. |
- Nikpay, Majid, et al.
(author)
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A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease
- 2015
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:10, s. 1121-1121
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Journal article (peer-reviewed)abstract
- Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of similar to 185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
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