19 results on '"Vinh Dinh"'
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2. Investigating the Anti-Inflammatory Activity of Curcumin-Loaded Silica-Containing Redox Nanoparticles
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Nhu-Thuy Trinh, Khoa Minh Le, Toi Van Vo, Vinh Dinh-Xuan Nguyen, Tien-Dat Van Nguyen, Dai-Nghiep Ngo, Tuan Quoc Tran, Long Binh Vong, and Thu-Ha Thi Nguyen
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Materials science ,Antioxidant ,Article Subject ,medicine.drug_class ,medicine.medical_treatment ,02 engineering and technology ,Pharmacology ,Anti-inflammatory ,03 medical and health sciences ,chemistry.chemical_compound ,In vivo ,Oral administration ,medicine ,T1-995 ,General Materials Science ,Technology (General) ,030304 developmental biology ,chemistry.chemical_classification ,0303 health sciences ,Reactive oxygen species ,021001 nanoscience & nanotechnology ,Bioavailability ,chemistry ,Drug delivery ,Curcumin ,0210 nano-technology - Abstract
Chronic inflammation is considered as one of the challenging diseases, and overproduction of reactive oxygen species (ROS) is strongly related to the onset of chronic inflammation. Therefore, antioxidant and anti-inflammatory approaches are particularly becoming suitable treatment and prevention of inflammation. Curcumin (CUR), a main component of turmeric extract, is well known as an effective agent in both antioxidant and anti-inflammatory activities; however, there are still some limitations of its use including poor water solubility, low bioavailability, and oxidation by ROS. Nanotechnology has been used as a drug delivery system, which is a promising approach in overcoming the aforementioned drawbacks of CUR; hence, it improves the antioxidant and anti-inflammatory effects of conventional medications. In this research, silica-containing redox nanoparticles (siRNP) were designed with the size of several tens of nanometers, prepared by self-assembly of an amphiphilic block copolymer consisting of drug absorptive silica moiety and ROS-scavenging nitroxide radical moiety in the hydrophobic segment. CUR was simply encapsulated into siRNP through the dialysis method, creating CUR-loaded siRNP (CUR@siRNP), which significantly improved the water solubility of CUR. The efficient antioxidant activity and anti-inflammatory effect of CUR@siRNP in vitro were also improved via 2,2-diphenyl-1-picrylhydrazyl assay and lipopolysaccharide-induced macrophage cell line activation, respectively. Oral administration of CUR@siRNP showed improvement in pharmacokinetic profile in vivo including AUC and Cmax values as compared to free CUR. Furthermore, the anti-inflammatory effect of nanoformulation was investigated in the colitis mouse model induced by dextran sodium sulfate.
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- 2021
3. Robust and Real-Time Obstacle Region Detection Based on Depth Feature for Vehicle Detection
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Narayan C. Debnath, Tam Minh Duong, Vinh Dinh Nguyen, and Anh Quoc Le
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0209 industrial biotechnology ,Pixel ,Computer science ,business.industry ,Deep learning ,Pattern recognition ,02 engineering and technology ,Object detection ,020901 industrial engineering & automation ,Feature (computer vision) ,Vehicle detection ,Obstacle ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Artificial intelligence ,Noise (video) ,business - Abstract
Obstacle region detection has been one of the most important tasks for detecting and classifying preceding vehicles moving along the road. Traditional U-V disparity-based obstacle detection methods consider only single disparity pixels to extract obstacle regions. They might fail to produce accurate obstacle regions when noise is encountered in the original disparity map. Recently, local patterns have been successfully applied to handle noise in many systems, such as texture classification and vehicle detection. Therefore, this paper introduces a new approach to compute U and V disparity using maximum local density encoding and ternary pattern features. Our method produced better performance than the existing U-V disparity methods in terms of detection rate and accuracy. In addition, we also evaluated the performance of the proposed method with the Faster RCNN-based object detection. Experimental results show that our method improved the detection rate of Faster RCNN by 1.65% on the KITTI dataset, and by 2.28% on the CCD dataset. In addition, the proposed method also improved the running time of Faster RCNN by 47% on the KITTI dataset.
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- 2020
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4. Pedestrian Detection Based on Deep Learning
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Vinh Dinh Nguyen, Hyung-Min Jeon, and Jae Wook Jeon
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Artificial neural network ,Computer science ,business.industry ,Pedestrian detection ,Deep learning ,Feature extraction ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,020207 software engineering ,02 engineering and technology ,010501 environmental sciences ,01 natural sciences ,Histogram ,0202 electrical engineering, electronic engineering, information engineering ,Key (cryptography) ,RGB color model ,Computer vision ,Artificial intelligence ,business ,ComputingMethodologies_COMPUTERGRAPHICS ,0105 earth and related environmental sciences - Abstract
While it is a hot issue whether cars could drive by themselves in emergent situations without any kind of human interference, pedestrian detection is the key technology in autonomous driving cars. Though current pedestrian detection technologies have come to a point in which they are accurate in normal conditions and surroundings, existent systems are inaccurate in harsh situations, such as when there are too many pedestrians, when there is too much light or when it is too dark, or when it is raining or snowing heavily. This problem may be solved by integrating deep learning and combining a new type of local pattern with the RGB raw image as input, instead of using just the RGB image as input. We will introduce a new type of local pattern called Triangular Patterns, which is effective in extracting more detailed and stable features from local regions. Here in this paper, we propose a pedestrian detection system in which deep learning is used, along with combining the RGB raw image with Triangular Patterns for input.
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- 2019
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5. Robust Stereo Data Cost With a Learning Strategy
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Hau Van Nguyen, Vinh Dinh Nguyen, and Jae Wook Jeon
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050210 logistics & transportation ,Matching (statistics) ,Stereo cameras ,Computer science ,Active learning (machine learning) ,business.industry ,Mechanical Engineering ,Deep learning ,05 social sciences ,Online machine learning ,Pattern recognition ,02 engineering and technology ,Semi-supervised learning ,Computer Science Applications ,0502 economics and business ,Automotive Engineering ,0202 electrical engineering, electronic engineering, information engineering ,Unsupervised learning ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business ,Computer stereo vision - Abstract
The performance of stereo matching algorithms strongly depends on the quality of the stereo data/matching cost. Most state-of-the-art data costs require expert knowledge for the design of a transformation function, such as census for handling gray-level changes monotonically, adaptive normalized cross correlation for handling Lambertian cases, guided filtering for preserving edge information, and local density encoding for handling illumination differences. However, it is difficult to design a complex transformation function to handle unknown factors that often occur in driving conditions such as snow, rain, and sun. Therefore, this paper has investigated the deep learning strategy to develop a novel stereo matching cost model without using much expert knowledge. Experimental results show that the proposed deep learning model obtains better results than the state-of-the-art stereo matching cost as judged by the standard KITTI benchmark, Middlebury, and HCI datasets.
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- 2017
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6. High-Speed Car Detection Using ResNet-Based Recurrent Rolling Convolution
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Hyung-Joon Jeon, Jae Wook Jeon, Vinh Dinh Nguyen, and Cuong Cao Pham
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050210 logistics & transportation ,Computer science ,0502 economics and business ,05 social sciences ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,02 engineering and technology ,Algorithm ,Residual neural network ,Convolution - Abstract
Car detection is a crucial issue in self-driving cars. Numerous in-traffic car detection models have been proposed, each of which exhibits its own strengths and weaknesses; the high detection speeds of some models are not accompanied by high precision, while the precision of other models is shadowed by insufficient speeds. Our main goal in this paper is to introduce a model that utilizes the Recurrent Rolling Convolution (RRC). The model gives promising results on detection speed and precision, thereby mitigating the weaknesses of previously proposed models, which is exhibited in our extensive experiment.
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- 2018
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7. Learning Framework for Robust Obstacle Detection, Recognition, and Tracking
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Sang Jun Lee, Hau Van Nguyen, Jae Wook Jeon, Vinh Dinh Nguyen, and Dinh T. Tran
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050210 logistics & transportation ,Engineering ,Artificial neural network ,business.industry ,Mechanical Engineering ,Pedestrian recognition ,Deep learning ,Pedestrian detection ,05 social sciences ,Advanced driver assistance systems ,02 engineering and technology ,Pedestrian ,Computer Science Applications ,Robustness (computer science) ,Obstacle ,0502 economics and business ,Automotive Engineering ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business - Abstract
This paper introduces a general framework for detection, recognition, and tracking preceding vehicles and pedestrians based on a deep learning approach. The proposed framework combines a novel deep learning approach with the use of multiple sources of local patterns and depth information to yield robust on-road vehicle and pedestrian detection, recognition, and tracking. The proposed system is first based on robust obstacle detection to identify obstacles appearing along the road that are likely to be vehicles and pedestrians, implemented as an efficient adaptive U-V disparity algorithm. Second, the results from the obstacle detection stage are input into a novel vehicle and pedestrian recognition system based on a deep learning model that processes multiple sources of depth information and local patterns. Finally, the results from the recognition stage are used to track detected vehicles or pedestrians in the next frame by means of a proposed tracking and validation model. The proposed framework has been thoroughly evaluated by inputting several vehicle and pedestrian data sets that were collected under various driving conditions. Experimental results show that this framework provides robust vehicle and pedestrian detection, recognition, and tracking with high accuracy, and also satisfies the real-time requirements of driver assistance systems.
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- 2016
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8. Real-Time Multi-Digit Recognition System Using Deep Learning on an Embedded System
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Hyung-Min Jeon, Jae Wook Jeon, and Vinh Dinh Nguyen
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Computer science ,Machine vision ,business.industry ,Deep learning ,Speech recognition ,05 social sciences ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,ComputingMethodologies_PATTERNRECOGNITION ,0502 economics and business ,ComputingMethodologies_DOCUMENTANDTEXTPROCESSING ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Digit recognition ,Artificial intelligence ,business ,050203 business & management - Abstract
In the machine learning technology, making computers read letters, characters and digits have been a hot issue in many areas of research. Among them, the recognition of handwritten numbers has still a long way to go, unlike the recognition of printed digits or the recognition of handwritten English sentences. In this paper we will introduce to you a multiple handwritten digit recognition system using deep learning.
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- 2018
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9. Bonding-Wire-Geometric-Profile-Dependent Model for Mutual Coupling Between Two Bonding Wires on a Glass Substrate
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Pierre Nicole, Dominique Lesenechal, Thanh Vinh Dinh, Philippe Descamps, Julien Pagazani, Gaelle Lissorgues, Daniel Pasquet, Laboratoire de Microélectronique et de Physique des Semiconducteurs (LaMIPS), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-NXP Semiconductors [France]-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), Electronique, Systèmes de communication et Microsystèmes (ESYCOM), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, Laboratoire de cristallographie et sciences des matériaux (CRISMAT), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU), Institut de Recherche en Systèmes Electroniques Embarqués (IRSEEM), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-École Supérieure d’Ingénieurs en Génie Électrique (ESIGELEC), THALES Airborne Systems [Elancourt], THALES, Normandie Université (NU)-NXP Semiconductors [France], École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC), École Supérieure d’Ingénieurs en Génie Électrique (ESIGELEC), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), THALES [France], Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, and Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)
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[SPI.OTHER]Engineering Sciences [physics]/Other ,Wire bonding ,Materials science ,02 engineering and technology ,Substrate (electronics) ,Electromagnetic simulation ,Industrial and Manufacturing Engineering ,Kinetic inductance ,[SPI.MAT]Engineering Sciences [physics]/Materials ,Chip scale packaging ,Bonding wire (BW) ,Dependent model ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Bonding processes ,[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics ,Electrical and Electronic Engineering ,Inductance ,[SDV.IB.BIO]Life Sciences [q-bio]/Bioengineering/Biomaterials ,ComputingMilieux_MISCELLANEOUS ,glass ,Coupling ,Bonding ,Wire (electric) ,Substrates ,Condensed matter physics ,mutual coupling ,020208 electrical & electronic engineering ,020206 networking & telecommunications ,Wires ,electromagnetic (EM) modeling ,[SPI.TRON]Engineering Sciences [physics]/Electronics ,Electronic, Optical and Magnetic Materials ,inductance formula ,[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism ,Integrated circuit modeling ,Mutual coupling - Abstract
International audience; The dependence of self-inductance and mutual inductance on bonding wire (BW) geometric profile has been studied in several papers. This paper will present a method using a BW-geometric-profile-dependent term to include this dependence in a simple model of BWs. The model element values will be calculated only from geometric dimensions. An experimental structure of two BWs in parallel planes has been fabricated based upon glass substrate technique for verification. A good agreement was obtained up to 8 GHz in comparison to electromagnetic simulation and measurement.
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- 2015
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10. Real-time pedestrian detection using a support vector machine and stixel information
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Jae Wook Jeon, Mi Thi-Tra Nguyen, and Vinh Dinh Nguyen
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0209 industrial biotechnology ,business.industry ,Computer science ,Pedestrian detection ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Robotics ,Tracking system ,02 engineering and technology ,Support vector machine ,Set (abstract data type) ,020901 industrial engineering & automation ,Histogram of oriented gradients ,Feature (computer vision) ,Region of interest ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business - Abstract
Pedestrian detection systems have become a crucial topic due to their contribution to numerous applications, such as surveillance, self-driving cars, tracking systems, and robotics. Therefore, we have developed an efficient pedestrian detection algorithm using a support vector machine (SVM) and a histogram of oriented gradients (HOG) feature. This paper introduces a system that is capable of reducing the set of candidate detection regions and classifying pedestrians and non-pedestrians in urban traffic by using the stixel world and HOG + SVM, respectively. The stixel world computation in this proposal is used to compute the region of interest of the input image. We also introduce our new human dataset, including more than 3100 human images, and a method used for classifying the dataset. By implementing on a CPU only, we reach high-quality detection at 56 fps in urban traffic scenarios. Our experimental results demonstrate the effectiveness of reducing the set of detection regions to improve the processing time of our system.
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- 2017
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11. Analysis of broadband power combiners and coupled antennas with stochastic load matching in a random field for mm-wave applications
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Peter Russer, Damienne Bajon, Johannes A. Russer, Thanh Vinh Dinh, Paul Mattheijssen, Dominique Lesenechal, and Sidina Wane
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Random field ,Computer science ,020208 electrical & electronic engineering ,MIMO ,020206 networking & telecommunications ,02 engineering and technology ,Function (mathematics) ,Broadband ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Equivalent circuit ,Power dividers and directional couplers ,Antenna (radio) ,Energy harvesting - Abstract
In this paper, we present design and experimental verification of integrated power combiners and closely coupled antennas. Several design variants are proposed for assessing effects of stochastic matching on antenna correlations as function of frequency up to 110GHz. Broadband equivalent circuit models accounting for radiation effects are extracted for proper random EM-Fields-Circuit Co-Design and Co-Analysis. Perspectives for Cognitive Built-In-Self-Test implementing real-time tuning of stochastic matching with EM-Thermal energy harvesting are drawn for mm-Wave MIMO and Phased-Array applications.
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- 2017
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12. Characterization of anisotropic substrates from RF, mm-Wave to THz: Design of 3D conformal antenna for connected objects
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Damienne Bajon, Tanh Vinh Dinh, Audrey Cayron, Dominique Lesenechal, Sidina Wane, Laurent Leyssenne, Philippe Descamps, Sebastien Massenot, and Bernadette Domengès
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Materials science ,business.industry ,Terahertz radiation ,Wearable computer ,020206 networking & telecommunications ,02 engineering and technology ,021001 nanoscience & nanotechnology ,Laser ,Refraction ,Characterization (materials science) ,law.invention ,Optics ,law ,0202 electrical engineering, electronic engineering, information engineering ,Optoelectronics ,Antenna (radio) ,0210 nano-technology ,business ,Anisotropy ,Absorption (electromagnetic radiation) ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
Anisotropic Liquid Crystal Polymer (LCP) substrates are used to design 3D conformal antenna elements and filtering structures in Laser Direct Structuring technology (LDS) for applications including 5G connected objects and massive Internet of Things (IoT): e.g., wearable (smart watches/rings), mobile (smartphones/tablets), home (appliances/lighting) devices. Based on the experimentally extracted optical absorption and refraction properties, identification of chemical and/or morphologic composition of the characterized samples (solid and liquid materials) are targeted. Perspectives for macro-modeling of composite materials and nano-Particles using homogeneization techniques are drawn.
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- 2016
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13. Experimental characterization of packaged switch devices for RF and millimeter-Wave applications
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Dominique Lesenechal, Philippe Descamps, Sidina Wane, Thanh Vinh Dinh, Daniel Pasquet, Laboratoire de Microélectronique et de Physique des Semiconducteurs (LaMIPS), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-NXP Semiconductors [France], Laboratoire de cristallographie et sciences des matériaux (CRISMAT), École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC), NXP Semiconductors [France], Mehta S.Lin L., Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, and Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)
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Materials science ,02 engineering and technology ,Broadband ,Chip-Package-PCB Co-Design ,0202 electrical engineering, electronic engineering, information engineering ,[CHIM.CRIS]Chemical Sciences/Cristallography ,Insertion loss ,Package/Board Deembedding ,[CHIM]Chemical Sciences ,Microelectromechanical systems ,multi-port measurement ,business.industry ,020208 electrical & electronic engineering ,Electrical engineering ,Linearity ,020206 networking & telecommunications ,[CHIM.MATE]Chemical Sciences/Material chemistry ,Plastic molding ,Characterization (materials science) ,switches ,[CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry ,MEMS ,Power consumption ,Circuit testing ,Extremely high frequency ,business - Abstract
International audience; In this paper we present experimental characterization of packaged switch devices in terms of their RF attributes isolation, insertion loss, power consumption, and linearity. Packaging and Board assembly significantly reduce their RF and mm-Wave performances. A broadband experimental setup is developed for the qualification of packaged switch devices accounting for deembedding effects both with on-board/on-package and on-chip probing. Module-based switch devices have been measured then, plastic molding, Si cap, and bonding wires have been sequentially removed to investigate their influences. Different challenges with packaged switch devices are identified and effective solutions are proposed for their qualification. © 2016 IEEE.
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- 2016
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14. A RF tunable Agile Filter: From component to system design
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Gaelle Lissorgues, G. Schropfer, A. Mehdaoui, T. Vinh-Dinh, D. Pasquet, Julien Pagazani, Pierre Nicole, Electronique, Systèmes de communication et Microsystèmes (ESYCOM), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, Groupe d'Etude de la Matière Condensée (GEMAC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Coventor, Laboratoire de Microélectronique et de Physique des Semiconducteurs (LaMIPS), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-NXP Semiconductors [France], Laboratoire de cristallographie et sciences des matériaux (CRISMAT), École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC), THALES Airborne Systems [Elancourt], THALES, Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), THALES [France], Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, and Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)
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Engineering ,Micromechanical devices ,Resonator filters ,Varactors ,Hardware design languages ,Capacitance ,02 engineering and technology ,Radiofrequency filters ,law.invention ,[SPI.MAT]Engineering Sciences [physics]/Materials ,Hardware_GENERAL ,law ,Radio frequency ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Insertion loss ,[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics ,[SDV.IB.BIO]Life Sciences [q-bio]/Bioengineering/Biomaterials ,ComputingMilieux_MISCELLANEOUS ,Microelectromechanical systems ,Multi-physics modelling ,business.industry ,020208 electrical & electronic engineering ,Electrical engineering ,RF MEMS ,021001 nanoscience & nanotechnology ,Tuneable capacitor ,[SPI.TRON]Engineering Sciences [physics]/Electronics ,Capacitor ,[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism ,Filter (video) ,System level simulation ,Systems design ,Combline filters ,Microfabrication ,Antenna (radio) ,0210 nano-technology ,business ,Varicap - Abstract
International audience; The work is related to an Agile Filter which is a specific RF block to be inserted between an antenna and a first stage of pre-amplification in future on board antenna systems or any future multi-purpose communications terminals. It will be able to process signals in the frequency range between 2 and 18 GHz with target insertion loss below 3dB. The basic idea of the demonstrator studied and developed in this project is to evaluate a SiP approach combining heterogeneous technologies and 3D integration and packaging. This paper presents the process flow used to design, fabricate and integrate in 3D a tunable RF filter which tunability is obtained by the use of MEMS varactors based on a copper on glass technology and stacked on micro-PCD for the electronic control functions. MEMS+ parameterized structures for RF MEMS varactor designs are presented with dimension constraints to be compatible with the space available at the end of each combline sub-filter. Indeed, the MEMS capacitors are composed of a mobile square membrane of 210μm by side and overall size of 600μm. In addition, these RF MEMS tunable capacitor models were automatically transferred into VerilogA for rapid system-level simulation usable further in ADS environment to verify the RF performances.
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- 2015
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15. Microwave-Assisted Synthesis of Goethite Nanoparticles Used for Removal of Cr(VI) from Aqueous Solution
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Jindrich Kynicky, Pavlina Ambrozova, Vinh Dinh Nguyen, and Vojtech Adam
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Thermogravimetric analysis ,Materials science ,Goethite ,microwave ,Analytical chemistry ,02 engineering and technology ,010501 environmental sciences ,lcsh:Technology ,01 natural sciences ,Article ,symbols.namesake ,Adsorption ,Differential thermal analysis ,goethite nanoparticles ,Cr(VI) removal ,General Materials Science ,lcsh:Microscopy ,Thermal analysis ,lcsh:QC120-168.85 ,0105 earth and related environmental sciences ,Aqueous solution ,lcsh:QH201-278.5 ,lcsh:T ,Langmuir adsorption model ,021001 nanoscience & nanotechnology ,lcsh:TA1-2040 ,visual_art ,symbols ,visual_art.visual_art_medium ,lcsh:Descriptive and experimental mechanics ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,lcsh:Engineering (General). Civil engineering (General) ,0210 nano-technology ,lcsh:TK1-9971 ,BET theory - Abstract
The microwave-assisted synthesis of goethite nanoparticles has been studied. The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential thermal analysis (DTA) and Brunauer-Emmett-Teller (BET) method. Goethite rod-like nanoparticles have been successfully synthesized in 10 min of microwave treating at 100 degrees C. Particle size is in the range from 30 to 60 nm in width and from 200 to 350 nm in length. BET analysis indicated that the surface area of the product is 158.31 m(2)g(-1). The feasibility of Cr(VI) removal fromaqueous solution depends on the pH of the solution and contact time. The maximum adsorptionis reached at pH 4.0 and 540 min of contact time. The adsorption kinetics was analyzedby the pseudo-first-and second-order models and the results reveal that the adsorption process obeys the pseudo-second-order model. The adsorption data were fitted well with the Langmuir adsorption isotherm.
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- 2017
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16. Synthesis and Modification of Clinoptilolite
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Pavlina Ambrozova, Vinh Dinh Nguyen, Jindrich Kynicky, and Tomáš Urubek
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Materials science ,clinoptilolite crystallization ,Inorganic chemistry ,HDTMA ,Pharmaceutical Science ,Review ,02 engineering and technology ,010501 environmental sciences ,01 natural sciences ,Analytical Chemistry ,law.invention ,Autoclave ,lcsh:QD241-441 ,Crystallinity ,lcsh:Organic chemistry ,law ,Drug Discovery ,Hydrothermal synthesis ,zeolite ,Organic Chemicals ,Physical and Theoretical Chemistry ,Crystallization ,Zeolite ,Alkyl ,0105 earth and related environmental sciences ,chemistry.chemical_classification ,Clinoptilolite ,Organic Chemistry ,Temperature ,Polymer ,021001 nanoscience & nanotechnology ,hydrothermal synthesis ,chemistry ,Chemistry (miscellaneous) ,Zeolites ,Molecular Medicine ,surfactant modification ,0210 nano-technology - Abstract
Clinoptilolite is a natural mineral with exceptional physical characteristics resulting from its special crystal structure, mainstreamed into a large zeolite group called heulandites. An overall view of the research related to the synthesis, modification and application of synthetic clinoptilolite is presented. A single phase of clinoptilolite can be hydrothermally synthesized for 1–10 days in an autoclave from various silica, alumina, and alkali sources with initial Si/Al ratio from 3.0 to 5.0 at a temperature range from 120 to 195 °C. Crystallization rate and crystallinity of clinoptilolite can be improved by seeding. The modification of clinoptilolite has received noticeable attention from the research community, since modified forms have specific properties and therefore their area of application has been broadening. This paper provides a review of the use of organic compounds such as quarter alkyl ammonium, polymer, amine and inorganic species used in the modification process, discusses the processes and mechanisms of clinoptilolite modification, and identifies research gaps and new perspectives.
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- 2017
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17. Analytical crossing lines modeling
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Pierre Nicole, Daniel Pasquet, Philippe Descamps, Thanh Vinh Dinh, Dominique Lesénéchal, Julien Pagazani, Gaelle Lissorgues, Laboratoire de Microélectronique et de Physique des Semiconducteurs (LaMIPS), Laboratoire de cristallographie et sciences des matériaux (CRISMAT), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Electronique, Systèmes de communication et Microsystèmes (ESYCOM), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, THALES Airborne Systems [Elancourt], THALES [France], Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-NXP Semiconductors [France], École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, THALES, Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, and Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)
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Crossing lines ,Integrated circuit interconnections ,Optimization ,EM simulation ,Computer science ,Circuit design ,Capacitance ,02 engineering and technology ,Discrete circuit ,01 natural sciences ,[SPI.MAT]Engineering Sciences [physics]/Materials ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics ,[SDV.IB.BIO]Life Sciences [q-bio]/Bioengineering/Biomaterials ,ComputingMilieux_MISCELLANEOUS ,Analyticals models ,010302 applied physics ,business.industry ,Electrical engineering ,020206 networking & telecommunications ,[SPI.TRON]Engineering Sciences [physics]/Electronics ,EM modeling ,[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism ,Integrated circuit modeling ,Solid modeling ,Couplings ,business - Abstract
International audience; This paper presents a model for the crossover area of two crossing lines. The model was compared to 3D full wave electromagnetic simulation with good agreement up to 20 GHz.
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- 2014
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18. Model of mutual coupling between two bonding wires on glass substrate
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Gaelle Lissorgues, Julien Pagazani, Daniel Pasquet, Dominique Lesenechal, Philippe Descamps, Thanh Vinh Dinh, Pierre Nicole, Laboratoire de Microélectronique et de Physique des Semiconducteurs (LaMIPS), Laboratoire de cristallographie et sciences des matériaux (CRISMAT), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Electronique, Systèmes de communication et Microsystèmes (ESYCOM), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, THALES Airborne Systems [Elancourt], THALES [France], Normandie Université (NU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-NXP Semiconductors [France]-Presto Engineering Europe, Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-NXP Semiconductors [France], École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut de Chimie du CNRS (INC), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris, and THALES
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Materials science ,02 engineering and technology ,Substrate (electronics) ,Electromagnetic simulation ,[SPI.MAT]Engineering Sciences [physics]/Materials ,Lead bonding ,Full wave ,Mathematical model ,0202 electrical engineering, electronic engineering, information engineering ,Electromagnetic coupling ,[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics ,Inductance ,[SDV.IB.BIO]Life Sciences [q-bio]/Bioengineering/Biomaterials ,ComputingMilieux_MISCELLANEOUS ,Coupling ,Bonding ,Condensed matter physics ,Substrates ,Electromagnetic modeling ,020206 networking & telecommunications ,021001 nanoscience & nanotechnology ,Wires ,[SPI.TRON]Engineering Sciences [physics]/Electronics ,[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism ,Anodic bonding ,Bonding wire ,Solid modeling ,Mutual coupling ,Glass ,0210 nano-technology - Abstract
International audience; This paper presents a simple model of mutual coupling between 2 bonding wires. The model has been compared to 3D full wave electromagnetic simulation up to 20 GHz. A good accordance was obtained.
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- 2013
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19. Chip-Package-PCB Co-Design of Power Combiners in SESUB and WLCSP Technology with Re-Distribution Layers
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Laurent Leyssenne, Thanh Vinh Dinh, Dominique Lesenechal, Damienne Baion, Philippe Descamps, and Sidina Wane
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020208 electrical & electronic engineering ,020206 networking & telecommunications ,Topology (electrical circuits) ,Hardware_PERFORMANCEANDRELIABILITY ,02 engineering and technology ,Inductor ,Chip ,7. Clean energy ,Chip-scale package ,Broadband ,Hardware_INTEGRATEDCIRCUITS ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,RLC circuit ,Power dividers and directional couplers ,Equivalent circuit - Abstract
We present SESUB (Semiconductor Embedded in Substrate) and WLCSP (Wafer-Level-Chip-Scale Packaging) integration of Power Combiners for WLAN and 5G applications. The proposed technology solutions offer optimized Electromagnetic-Thermal-Mechanical performances for Energy-Efficient Chip-Package-PCB distributed Co-Design. PDK-Library oriented RLC Lumped-model topologies are compared to broadband distributed Layout design. Prototype demonstrators are designed and experimentally verified for emerging 5G and IoT applications both for frequencies below 6GHz and in the mm-Wave domain (28GHz, 39GHz). Innovative broadband physics-based RLC equivalent circuit models valid from DC to mm-Wave frequencies is proposed and verified against measurement.
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