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WoS SCOPUS Document Type Document Title Abstract Authors Affiliation ResearcherID (WoS) AuthorsID (SCOPUS) Author Email(s) Journal Name JCR Abbreviation ISSN eISSN Volume Issue WoS Edition WoS Category JCR Year IF JCR (%) FWCI FWCI Update Date WoS Citation SCOPUS Citation Keywords (WoS) KeywordsPlus (WoS) Keywords (SCOPUS) KeywordsPlus (SCOPUS) Language Publication Stage Publication Year Publication Date DOI JCR Link DOI Link WOS Link SCOPUS Link
Article Galinstan-based flexible microfluidic device for wireless human-sensor applications Liquid-metal-based wearable technologies are one of the promising ways to realize soft-skin flexible electronics. Here, we report a flexible microfluidic device that injects Galinstan liquid-metal alloy through the microchannels of a polydimethylsiloxane (PDMS) substrate, targeting an inductor-capacitor (LC) resonant circuit for wireless power transmission and sensing. The surface inside PDMS microchannels is chemically modified using sulfuric acid (H2SO4) solution, making it easier for the liquid metal to flow through the microfluidic channel. Electromechanical characteristics of the capacitive pressure sensors were evaluated by loading and unloading the external pressure continuously in the range of 0-200 mmHg for 300 cycles. After that, the characterization of Galinstan-based flexible microfluidic sensors consisting of the LC circuit conducted in a strain range of up to 30 %. Finally, monitoring of various human motion (e.g., wrist flexion and finger motion) was demonstrated using a wireless sensing platform with an external antenna. Electrical and mechanical performances confirm that the Galinstan-based sensors are reliable, reproducible, repeatable, and flexible with a sensitivity of 5 kHz/mmHg. The proposed flexible microfluidic device has the potential to become an exceptionally reliable candidate for wireless human-machine applications. (C) 2020 Elsevier B.V. All rights reserved. Munirathinam, Karthikeyan; Park, Jongsung; Jeong, Yun-Jin; Lee, Dong-Weon Chonnam Natl Univ, Sch Mech Syst Engn, MEMS & Nanotechnol Lab, Gwangju 61186, South Korea; Kyungpook Natl Univ, Dept Precis Mech Engn, Sangju 37224, South Korea; Chonnam Natl Univ, Ctr Next Generat Sensor Res & Dev, Gwangju 61186, South Korea 57219625153; 57189583605; 56261982700; 34875377700 mems@jnu.ac.kr; SENSORS AND ACTUATORS A-PHYSICAL SENSOR ACTUAT A-PHYS 0924-4247 1873-3069 315 SCIE ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2020 3.407 25.8 1.32 2025-06-25 29 29 Galinstan; Flexible microfluidic device; PDMS microchannel surface modification; Wireless capacitive sensor; Human-motion monitoring LIQUID; POWER Flexible microfluidic device; Galinstan; Human-motion monitoring; PDMS microchannel surface modification; Wireless capacitive sensor Antennas; Capacitive sensors; Flexible electronics; Fluidic devices; Inductive power transmission; Liquid metals; Microchannels; Polydimethylsiloxane; Resonant circuits; Silicones; Unloading; Wearable technology; Capacitive pressure sensors; Chemically modified; Electromechanical characteristics; Flexible microfluidics; Loading and unloading; Mechanical performance; Microfluidic channel; Polydimethylsiloxane (PDMS) substrates; Microfluidics English 2020 2020-11-01 10.1016/j.sna.2020.112344 바로가기 바로가기 바로가기 바로가기
Article Highly sensitive and flexible wearable pressure sensor with dielectric elastomer and carbon nanotube electrodes Wearable sensors for tracking human body motion are being increasingly applied in medical systems and are considered important components of human-machine interfaces. This study proposes a flexible sandwich-like capacitive pressure sensor that consists of carbon nanotube-polydimethylsiloxane (CNT-PDMS) composite electrodes and a porous polymer dielectric layer. CNT yarn and polymer materials help fabricate a pressure sensor without complex patterns, easily and quickly. The dielectric layer is made of a porous polymer to improve the sensor sensitivity. The high porosity of the dielectric layer increases its deformation under pressure and enhances the sensitivity (to approximately 5.6 kPa(-1) (%)) even under low pressures (< 5 kPa). The sensitivity of the sensor varies according to the density of porosity and dielectric permittivity of the dielectric layer. Owing to the high porosity of the dielectric layer and flexibility of the CNT yarn, the capacitive pressure sensor proposed in this study exhibits good performance in detecting even a slight change in stimulus. The proposed pressure sensor can be applied in wearable applications such as human-friendly interfaces and sensitive electronic skins. (C) 2020 Published by Elsevier B.V. Han, Maeum; Lee, Junyeop; Kim, Jae Keon; An, Hee Kyung; Kang, Shin-Won; Jung, Daewoong Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu 41566, South Korea; Korea Inst Ind Technol KITECH, Mechatron Technol Convergence R&D Grp, Daegu 42994, South Korea; Kyungpook Natl Univ, Dept Sensor & Display Engn, Daegu 41566, South Korea; Korea Inst Ind Technol KITECH, AI Syst Engn Grp, Daegu 42994, South Korea 55931924500; 57203736115; 57194519849; 56647468900; 7405682695; 36019307900 swkang@knu.ac.kr;dwjung@kitech.re.kr; SENSORS AND ACTUATORS A-PHYSICAL SENSOR ACTUAT A-PHYS 0924-4247 1873-3069 305 SCIE ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2020 3.407 25.8 3.55 2025-06-25 66 72 Carbon nanotube yarn; Pressure sensor; Capacitive type; Dielectric layer; Porous polymer; Deformation CAPACITIVE PRESSURE; TACTILE SENSOR; TRANSPARENT; STRAIN; FABRICATION; CONDUCTORS Capacitive type; Carbon nanotube yarn; Deformation; Dielectric layer; Porous polymer; Pressure sensor Capacitive sensors; Carbon nanotubes; Deformation; Electrodes; Machine components; Motion sensors; Motion tracking; Partial pressure sensors; Permittivity; Porosity; Porous carbon; Pressure sensors; Silicones; Wool; Yarn; Capacitive pressure sensors; Capacitive type; Carbon nanotube electrodes; Carbon nanotube yarns; Dielectric layer; Dielectric permittivities; Human-friendly interfaces; Porous polymers; Wearable sensors English 2020 2020-04-15 10.1016/j.sna.2020.111941 바로가기 바로가기 바로가기 바로가기
Article Liquid metal embedded real time microfluidic flow pressure monitoring sensor Precise monitoring of the fluidic pressure is one of the key factors that are required for microfluidics-based devices to be successfully utilized in various biomedical applications. Although conventional methods based on electrical and optical measurement are widely used, these technologies are unstable due to their complicated fabrication process as well as difficulties in integration with other components. Here, we developed a novel liquid metal embedded microfluidic flow pressure sensor that can be used to monitor the flow pressure changes within the microfluidic channels in real time for an elongated time and with high stability. The developed pressure sensor employed high aspect ratio membranes between a main flow channel and liquid metal filled sensing channels. When the input flow pressure changes, the high aspect ratio membrane deflects and affects dimensions/morphology of the liquid metal in the sensing channel, resulting in the variation of the electrical resistance. The electrical resistance of the liquid metal corresponding to different pressure levels (0-1200 mbar) were characterized, and their long-term reliability was tested as well. The variation electrical resistance in accordance to the pressure changes showed linear correlation with high repeatability and the developed sensor have been validated to work consistently even after 3 weeks. (C) 2020 Elsevier B.V. All rights reserved. Peng, Kelu; Yao, Junyi; Cho, Sunghyun; Cho, Younghak; Kim, Hyun Soo; Park, Jaewon Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen 518055, Peoples R China; Korea Institue Machinery & Mat, Daegu Res Ctr Med Devices & Rehabil, Daegu, South Korea; Seoul Natl Univ Technol, Sch Mech Design & Automat Engn, Seoul, South Korea; Kyungpook Natl Univ, Sch Mech Engn, Daegu, South Korea Cho, Younghak/HDN-7234-2022; Park, Jaewon/I-3453-2013; Park, Jaewon/G-7432-2018 57215214073; 57207303704; 57215221736; 12769723300; 59863929300; 58766298900 hyunsookim@kimm.re.kr;jwpark@sustech.edu.cn; SENSORS AND ACTUATORS A-PHYSICAL SENSOR ACTUAT A-PHYS 0924-4247 1873-3069 305 SCIE ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2020 3.407 25.8 0.5 2025-06-25 12 11 Liquid metal; Flow pressure sensor; Real time monitoring Flow pressure sensor; Liquid metal; Real time monitoring Aspect ratio; Channel flow; Electric resistance; Liquid metals; Medical applications; Metals; Optical data processing; Pressure sensors; Biomedical applications; Conventional methods; Different pressures; Electrical resistances; Fabrication process; Microfluidic channel; Optical measurement; Real time monitoring; Microfluidics English 2020 2020-04-15 10.1016/j.sna.2020.111909 바로가기 바로가기 바로가기 바로가기
Article Optimization and characterization of a wideband multimode Tonpilz transducer for underwater acoustical arrays A multimode underwater acoustical transducer is well-known for providing wider bandwidth than a conventional single-mode transducer. However, the design of a low-frequency multimode transducer to achieve the desired wideband characteristics for an underwater array is challenging when considering the array's size and weight limitations. Therefore, this study focused on the development of a multimode transducer structure for superior wideband characteristics. The effect of various structural parameters on the performance of the multimode Tonpilz transducer was first analyzed with emphasis on its bandwidth using the finite element method (FEM). Then, the structure of the transducer was improved by analyzing the effect of the side acoustic window and incorporating realistic design considerations. Finally, the improved transducer structure was optimized to have the widest possible bandwidth while maintaining its transmitting voltage response (TVR) level over a typical power requirement. The final design was validated by fabricating a prototype transducer and evaluating its acoustical performance. (C) 2020 Elsevier B.V. All rights reserved. Afzal, Muhammad Shakeel; Lim, Youngsub; Lee, Seungjin; Yoon, Hongwoo; Roh, Yongrae Kyungpook Natl Univ, Sch Mech Engn, Daegu 41556, South Korea; LIG Nex1 Co Ltd, Maritime Integrated Secur Syst, Seongnam 13488, South Korea 57200092141; 56244666300; 57216561427; 57204548453; 7102361870 yryong@knu.ac.kr; SENSORS AND ACTUATORS A-PHYSICAL SENSOR ACTUAT A-PHYS 0924-4247 307 SCIE ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2020 3.407 25.8 0.99 2025-06-25 17 16 Tonpilz transducer; acoustic window; boundary conditions; optimization LOW-FREQUENCY; DESIGN acoustic window; boundary conditions; optimization; Tonpilz transducer Bandwidth; Ultrasonic transducers; Underwater acoustics; Acoustical performance; Design considerations; Structural parameter; Tonpilz transducer; Transducer structure; Transmitting voltage response; Weight limitations; Wideband characteristics; Transducers English 2020 2020-06-01 10.1016/j.sna.2020.112001 바로가기 바로가기 바로가기 바로가기
Article Sensitive and reliable thermal micro-flow sensor for a drug infusion system We developed a sensitive and reliable thermal micro-flow sensor (T mu FS) to measure extremely low flow rates for a drug infusion system. The T mu FS exploits a calorimetric principle. Various temperature differences upstream and downstream of a heated area were monitored by three temperature sensors to enable measurement of both cooling and heating effects at the multiple temperature-sensing areas. The flow rate was measured by subtraction or summation of the temperature differences between selected locations upstream and downstream. The temperature differences between heat loss and diffusion increased sensitivity of flow rate detection in range of 0-100 mL/h. The T mu FS takes non-invasive and non-intrusive measurements by monitoring thermal variations on the outer surface of a silicone IV tube. The T mu FS could detect flow rates as low as similar to 0.1 mL/h, with uncertainty <5%. The micro-flow sensor was accurate at a range of flow rates, initial liquid temperature, and tube inner diameters. In addition, temperatures variations in the T mu FS for flow rates agreed with numerical simulation. (C) 2020 Elsevier B.V. All rights reserved. Lee, Dongkyu; Kim, Jiae; Park, Yangkyu; Lee, Kang-Ho; Kim, Changwon; Kwon, Ohwon; Kim, Seonghwan; Lee, Sang-Ryong Korea Inst Machinery & Mat KIMM, Dept Med Devices, Daegu 42994, South Korea; Kyungpook Natl Univ, Dept Mech Engn, Daegu 702701, South Korea; Univ Calgary, Dept Mech & Mfg Engn, Calgary, AB T2N 1N4, Canada Kim, Seonghwan (Sam)/J-6884-2012; Kim, Seonghwan/P-8007-2019 8673376500; 57216742281; 55485625500; 56697620500; 57199972728; 57026875700; 55718948100; 35766722100 dongkyu@kimm.re.kr;owkwon@kimm.re.kr; SENSORS AND ACTUATORS A-PHYSICAL SENSOR ACTUAT A-PHYS 0924-4247 309 SCIE ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2020 3.407 25.8 0.91 2025-06-25 24 24 Thermal flow sensor; Flow rate detection; Noninvasive flow detection; Drug infusion system Drug infusion system; Flow rate detection; Noninvasive flow detection; Thermal flow sensor Drug infusion; Silicones; Temperature sensors; Infusion systems; Inner diameters; Liquid temperature; Micro flow sensors; Non-intrusive measurements; Temperature differences; Temperature sensing; Thermal variation; Flow rate English 2020 2020-07-01 10.1016/j.sna.2020.112033 바로가기 바로가기 바로가기 바로가기
Article VOC gas sensor based on hollow cubic assembled nanocrystal Zn2SnO4 for breath analysis Hollow cubic assembled nanocrystal Zn2SnO4 was synthesized via one-step hydrothermal method for VOC gas sensing applications. The obtained Zn2SnO4 materials had a uniformly hollow cubic structure with an average size of approximately 1 mu m and a wall thickness of about 150 nm formed from nanocrystals of around 14 nm. The X-ray absorption near-edge structure results showed no structural disorder and/or lattice damage around the Zn-absorbing atoms and the Zn oxidation state of 2+ in the host lattice of the hollow cubic Zn2SnO4. The gas sensing characteristics of the prepared Zn2SnO4 material were tested to C3H6O, C2H5OH, CH3OH, NH3, H-2, and CO at 350 degrees C-450 degrees C and results showed that the sensors exhibited a good response to acetone and ethanol gases. The highest response values were 47.80 for 125 ppm of acetone and 7.52 for 10 ppm of ethanol at 450 degrees C. The Zn2SnO4 hollow cubic sensor demonstrated high sensitivity and selectivity to acetone with good stability and a detection limit of 175 ppb. The VOC sensing mechanism of the hollow cubic Zn2SnO4-based sensor was also discussed. The findings indicated that hollow cubic Zn2SnO4 is a promising material for use in excellent VOC gas sensing application towards breath analysis. (C) 2020 Elsevier B.V. All rights reserved. Nguyen Hong Hanh; Lai Van Duy; Chu Manh Hung; Nguyen Van Duy; Heo, Young-Woo; Nguyen Van Hieu; Nguyen Duc Hoa HUST, ITIMS, 1 Dai Co Viet St, Hanoi, Vietnam; Inst Engn Phys, 17 Hoang Sam St, Hanoi 122108, Vietnam; Kyungpook Natl Univ, Sch Mat Sci & Engn, Daegu 41566, South Korea; Phenikaa Univ, Fac Elect & Elect Engn, Hanoi 10000, Vietnam; Phenikaa Univ, Phenikaa Inst Adv Study, Hanoi 10000, Vietnam Hoa, Nguyen/K-3544-2012; Vân-Anh, Nguyen/ITT-3241-2023; Hung, Chu/Z-3690-2019; NGUYEN, Viet/Y-7372-2019; Van Hieu, Nguyen/C-7172-2011 57217402147; 57212019712; 57190213388; 16053717800; 7004298542; 37063946700; 13105338900 hung.chumanh@hust.edu.vn;ndhoa@itims.edu.vn; SENSORS AND ACTUATORS A-PHYSICAL SENSOR ACTUAT A-PHYS 0924-4247 1873-3069 302 SCIE ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2020 3.407 25.8 3.89 2025-06-25 56 58 VOC gas sensor; Hollow cubic Zn2SnO4; High-performance; Sub-ppm level; Gas-sensing mechanism METAL-OXIDE NANOSTRUCTURES; SENSING PROPERTIES; ZINC STANNATE; H2S GAS; PERFORMANCE; ACETONE; NANOFIBERS; DIAGNOSIS; NANOWIRES; SPHERES Gas-sensing mechanism; High-performance; Hollow cubic Zn<sub>2</sub>SnO<sub>4</sub> ; Sub-ppm level; VOC gas sensor Acetone; Ammonia; Catalyst selectivity; Chemical detection; Chemical sensors; Ethanol; Gas detectors; Gases; Nanocrystals; Tin compounds; X ray absorption; X ray absorption near edge structure spectroscopy; Gas sensing applications; Gas sensing characteristics; Gas sensing mechanism; High-performance; Structural disorders; Sub-ppm level; X ray absorption near edge structure; Zn2SnO4; Zinc compounds English 2020 2020-02-01 10.1016/j.sna.2020.111834 바로가기 바로가기 바로가기 바로가기
Article A multi-dimensional search for new heavy resonances decaying to boosted WW, WZ, or ZZ boson pairs in the dijet final state at 13TeV A search in an all-jet final state for new massive resonances decaying to WW, WZ, or ZZ boson pairs using a novel analysis method is presented. The analysis is performed on data corresponding to an integrated luminosity of 77.3 fb(-1) recorded with the CMS experiment at the LHC at a centre-of-mass energy of 13TeV. The search is focussed on potential narrow-width resonances with masses above 1.2TeV, where the decay products of each W or Z boson are expected to be collimated into a single, large-radius jet. The signal is extracted using a three-dimensional maximum likelihood fit of the two jet masses and the dijet invariant mass, yielding an improvement in sensitivity of up to 30% relative to previous search methods. No excess is observed above the estimated standard model background. In a heavy vector triplet model, spin-1 Z' and W' resonances with masses below 3.5 and 3.8TeV, respectively, are excluded at 95% confidence level. In a bulk graviton model, upper limits on cross sections are set between 27 and 0.2 fb for resonance masses between 1.2 and 5.2TeV, respectively. The limits presented in this paper are the best to date in the dijet final state. Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Dragicevic, M.; Eroe, J.; Del Valle, A. Escalante; Flechl, M.; Fruehwirth, R.; Ghete, V. M.; Hrubec, J.; Jeitler, M.; Krammer, N.; Kraetschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Rad, N.; Rohringer, H.; Schieck, J.; Schoefbeck, R.; Spanring, M.; Spitzbart, D.; Taurok, A.; Waltenberger, W.; Wittmann, J.; Wulz, C. -E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Gonzalez, J. Suarez; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Pieters, M.; Van De Klundert, M.; Janssen, X.; Lauwers, J.; Pieters, M.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Bilin, B.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Kalsi, A. K.; Lenzi, T.; Luetic, J.; Postiau, N.; Starling, E.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Wang, Q.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Trocino, D.; Tytgat, M.; Verbeke, W.; Vermassen, B.; Vit, M.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; David, P.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Saggio, A.; Marono, M. Vidal; Wertz, S.; Zobec, J.; Alves, F. L.; Alves, G. A.; Martins Junior, M. Correa; Correia Silva, G.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Calligaris, L.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Marinov, A.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Levin, A.; Li, J.; Li, L.; Li, Q.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Wang, Y.; Avila, C.; Cabrera, A.; Carrillo Montoya, C. A.; Chaparro Sierra, L. F.; Florez, C.; Gonzalez Hernandez, C. F.; Segura Delgado, M. A.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Kolosova, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M., Jr.; Ayala, E.; Jarrin, E. Carrera; Assran, Y.; Elgammal, S.; Mohammed, Y.; Bhowmik, S.; De Oliveira, A. Carvalho Antunes; Dewanjee, R. K.; Ehataht, K.; Kadastik, M.; Raidal, M.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkila, J. K.; Jarvinen, T.; Karimaki, V.; Kinnunen, R.; Lampen, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Linden, T.; Luukka, P.; Maenpaa, T.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; de Monchenault, G. Hamel; Jarry, P.; Leloup, C.; Locci, E.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. O.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Beaudette, F.; Busson, P.; Charlot, C.; de Cassagnac, R. Granier; Kucher, I.; Lobanov, A.; Blanco, J. Martin; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Leiton, A. G. Stahl; Zabi, A.; Zghiche, A.; Agram, J. -L.; Andrea, J.; Bloch, D.; Brom, J. -M.; Chabert, E. C.; Cherepanov, V.; Collard, C.; Conte, E.; Fontaine, J. -C.; Gele, D.; Goerlach, U.; Jansova, M.; Le Bihan, A. -C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chanon, N.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lattaud, H.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Zhang, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Rauch, M. P.; Schomakers, C.; Schulz, J.; Teroerde, M.; Wittmer, B.; Zhukov, V.; Albert, A.; Duchardt, D.; Endres, M.; Erdmann, M.; Esch, T.; Fischer, R.; Ghosh, S.; Gueth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Keller, H.; Knutzen, S.; Mastrolorenzo, L.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Schmidt, A.; Teyssier, D.; Fluegge, G.; Hlushchenko, O.; Kress, T.; Kuensken, A.; Muller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Roy, D.; Sert, H.; Stahl, A.; Martin, M. Aldaya; Arndt, T.; Asawatangtrakuldee, C.; Babounikau, I.; Beernaert, K.; Behnke, O.; Behrens, U.; Martinez, A. Bermudez; Bertsche, D.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Danilov, V.; De Wit, A.; Defranchis, M. M.; Pardos, C. Diez; Damiani, D. Dominguez; Eckerlin, G.; Eichhorn, T.; Elwood, A.; Eren, E.; Gallo, E.; Geiser, A.; Luyando, J. M. Grados; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Haranko, M.; Harb, A.; Hauk, J.; Jung, H.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Knolle, J.; Kruecker, D.; Lange, W.; Lelek, A.; Lenz, T.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I. -A.; Meyer, A. B.; Meyer, M.; Missiroli, M.; Mittag, G.; Mnich, J.; Myronenko, V.; Pflitsch, S. K.; Pitzl, D.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Schuetze, P.; Schwanenberger, C.; Shevchenko, R.; Singh, A.; Tholen, H.; Turkot, O.; Vagnerini, A.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Benato, L.; Benecke, A.; Blobel, V.; Vignali, M. Centis; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Karavdina, A.; Kasieczka, G.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Kutzner, V.; Lange, J.; Marconi, D.; Multhaup, J.; Niedziela, M.; Nowatschin, D.; Perieanu, A.; Reimers, A.; Rieger, O.; Scharf, C.; Schleper, P.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrueck, G.; Stober, F. M.; Stoever, M.; Troendle, D.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baselga, M.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; El Morabit, K.; Faltermann, N.; Freund, B.; Giffels, M.; Harrendorf, M. A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Katkov, I.; Kudella, S.; Mildner, H.; Mitra, S.; Mozer, M. U.; Mueller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schroder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. 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Inst Nucl Res, Moscow, Russia; Natl Res Nucl Univ, Moscow Engn Phys Inst MEPhI, Moscow, Russia; St Petersburg State Polytech Univ, St Petersburg, Russia; Univ Florida, Gainesville, FL USA; PN Lebedev Phys Inst, Moscow, Russia; CALTECH, Pasadena, CA 91125 USA; Budker Inst Nucl Phys, Novosibirsk, Russia; Univ Belgrade, Fac Phys, Belgrade, Serbia; Univ Pavia, INFN, Sez Pavia, Pavia, Italy; Univ Belgrade, Fac Phys, Belgrade, Serbia; Vinca Inst Nucl Sci, Belgrade, Serbia; INFN, Scuola Normale & Sez, Pisa, Italy; Natl & Kapodistrian Univ Athens, Athens, Greece; Riga Tech Univ, Riga, Latvia; Univ Zurich, Zurich, Switzerland; Stefan Meyer Inst Subat Phys SMI, Vienna, Austria; Adiyaman Univ, Adiyaman, Turkey; Istanbul Aydin Univ, Istanbul, Turkey; Mersin Univ, Mersin, Turkey; Piri Reis Univ, Istanbul, Turkey; Gaziosmanpasa Univ, Tokat, Turkey; Ozyegin Univ, Istanbul, Turkey; Izmir Inst Technol, Izmir, Turkey; Marmara Univ, Istanbul, Turkey; Kafkas Univ, Kars, Turkey; Istanbul Univ, Fac Sci, Istanbul, Turkey; Istanbul Bilgi Univ, Istanbul, Turkey; Hacettepe Univ, Ankara, Turkey; Rutherford Appleton Lab, Didcot, Oxon, England; Univ Southampton, Sch Phys & Astron, Southampton, Hants, England; Monash Univ, Fac Sci, Clayton, Vic, Australia; Bethel Univ, St Paul, MN USA; Karamanoglu Mehmetbey Univ, Karaman, Turkey; Utah Valley Univ, Orem, UT USA; Purdue Univ, W Lafayette, IN 47907 USA; Beykent Univ, Istanbul, Turkey; Bingol Univ, Bingol, Turkey; Sinop Univ, Sinop, Turkey; Mimar Sinan Univ, Istanbul, Turkey; Texas A&M Univ Qatar, Doha, Qatar; Kyungpook Natl Univ, Daegu, South Korea; Univ Hyderabad, Hyderabad, India ; Cardini, Andrea/KUF-0984-2024; Mignerey, Alice/D-6623-2011; Belyaev, Alexander/F-6637-2015; Cepeda, María/HNO-9314-2023; Polikarpov, Sergey/C-8939-2016; Verma, Rahul/W-7692-2019; cartiglia, nicolo/ABF-1008-2021; Aimè, Chiara/GXG-4131-2022; BAT, Ayse/GOK-2363-2022; Janssen, Xavier/E-1915-2013; Morovic, Srecko/T-9019-2019; Gonzalez, Jesus David/IAN-5526-2023; Akgun, Bora/AAM-8311-2021; 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57199996532; 57193995091; 56681761900; 57199995207; 35226976800; 57201355284; 57201326914; 57202855809; 57202859632; 57204081939; 57202277169; 35227298700; 36660861400; 57207902314; 57203665352; 55210767800; 57203667105; 57202852316; 57204001272; 59140364000; 57219189942; 35313280300; 59140361600; 35227272400; 57188680295; 35227373700; 56437208100; 57189270386; 57204004071; 58632485800; 36170749800; 56446433400; 56437697200; 56448208700; 59395369400; 57764686200; 56501784000; 59395375000; 35356052000; 58632153800; 55286440200; 57219190462; 55286336800; 56893518800; 56681811000; 35227973900; 57220521234; 57205536163; 55350384900; 15755021800; 56973389300; 55225629800; 35227159700; 37048454000; 57043822800; 35227367700; 57202847289; 56800717400; 56681723400; 57204005081; 55795646500; 55203009000; 56352741400; 12758816400; 57217797874; 35221473300; 35227512400; 56681986300; 57205307086; 57199997802; 55095942200; 56682022400; 9276392600; 36171331300; 7101904491; 24376473600; 56682068800; 55134092500; 7005485775; 36170873500; 56924477700; 55603522400; 55496142400; 7102931559; 37051309800; 57220064097; 7004188390; 6701436560; 35274582500; 57202522373; 57219648360; 57220064080; 57220064314; 35227503800; 57220064375; 57220064223; 57220064351; 57220064259; 57220064396; 57203514331; 57199996011; 35222476000; 57206353679; 57194775056; 16226119300; 55951354400; 35356070900; 35227050000; 56681988200; 56414432900; 35271695700; 55868435500; 47960970300; 35308730700; 8984617000; 57189693933; 7006404363; 57210312265; 7201657574; 7003879901; 57210321748; 56681978600; 36123824900; 35227990900; 57193206437; 56648200300; 56181581800 EUROPEAN PHYSICAL JOURNAL C EUR PHYS J C 1434-6044 1434-6052 80 3 SCIE PHYSICS, PARTICLES & FIELDS 2020 4.59 25.9 3.15 2025-06-25 31 37 PROTON-PROTON COLLISIONS; PP COLLISIONS; HIGGS-BOSON; ROOT-S=8 TEV; ALGORITHMS; LEPTONS CMS; Diboson resonances; Physics; Substructure Gravitation; Maximum likelihood; A-center; Analysis method; Center-of-mass energies; Centre-of-mass energies; CMS; Diboson resonance; Final state; Integrated luminosity; Multi dimensional; Substructure; Bosons English 2020 2020-03-12 10.1140/epjc/s10052-020-7773-5 바로가기 바로가기 바로가기 바로가기
Article Approach to Transparent Photovoltaics Based on Wide Band Gap Sb2S3 Absorber Layers and Optics-Based Device Optimization Numerous methods have been employed for utilizing inorganic thin films to improve the stability of transparent photovoltaics (TPVs). However, the use of these methods was restricted due to limitations involving restricted physical dimensions, complex fabrication processes, visible transparency, and photovoltaic performance. In this study, a novel approach to novel TPVs based on wide band gap inorganic thin-film solar cell devices was first proposed. This approach was based on an Sb2S3 thin-film absorber and the optical optimization of a planar-type solar cell device structure. High-quality and uniformly thick Sb2S3 thin films were deposited via atomic layer deposition (ALD) to produce a high-quality transparent absorber layer for a planar-type transparent thin-film solar cell. To maintain the light transmittance of ALD-Sb2S3 solar cell devices, a flat indium tin oxide (ITO) substrate, a low-temperature-processed ALD TiO2 electron-transport layer (ETL), and an ultrathin Au top electrode were systematically combined with the transparent ALD-Sb2S3 absorber layer. The transparent ALD-Sb2S3 solar cell device showed a power conversion efficiency of 3.44% and an average light transmittance of 13%. These results proposed the technological possibility of using novel inorganic transparent Sb2S3 solar cell devices for transparent applications, such as self-powered transparent displays, high-efficiency tandem solar cells, robust bifacial solar cells, and so on. Lee, Sang-Ju; Sung, Shi-Joon; Yang, Kee-Jeong; Kang, Jin-Kyu; Kim, Jun Yong; Do, Yun Seon; Kim, Dae-Hwan DGIST, Div Energy Technol, Daegu 42988, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea ; Kim, Jihyun/F-6940-2013; Kim, Dae/AAJ-7518-2021; Jin-Kyu, Kang/AAR-9096-2021; Sung, Shi-Joon/AAU-2464-2021 57207064878; 7202731923; 15763941100; 35096377300; 57209837877; 24338060500; 57778048600 yuns.da@knu.ac.kr;monolith@dgist.ac.kr;yuns.do@knu.ac.kr; ACS APPLIED ENERGY MATERIALS ACS APPL ENERG MATER 2574-0962 3 12 SCIE CHEMISTRY, PHYSICAL;ENERGY & FUELS;MATERIALS SCIENCE, MULTIDISCIPLINARY 2020 6.024 25.9 1.29 2025-06-25 35 29 transparent photovoltaics; antimony sulfide; ALD; thin films; optical properties ALD; antimony sulfide; optical properties; thin films; transparent photovoltaics Antimony compounds; Atomic layer deposition; Conversion efficiency; Display devices; Efficiency; Electron transport properties; Energy gap; Light; Oxide minerals; Sulfide minerals; Temperature; Thin film circuits; Thin films; Tin oxides; Titanium dioxide; Electron transport layers; Indium tin oxide substrates; Inorganic thin films; Photovoltaic performance; Power conversion efficiencies; Transparent displays; Transparent thin film; Visible transparencies; Thin film solar cells English 2020 2020-12-28 10.1021/acsaem.0c02552 바로가기 바로가기 바로가기 바로가기
Article Automatic reconstruction of deleted AVI video files composed of scattered and corrupted fragments Video files of surveillance cameras frequently play a role of major evidence for criminals or accidents. But, if the video file containing the evidence is deleted, we need to recover it if possible. In this paper, we propose a recovery scheme for deleted video files with AVI format on FAT32 file system. The proposed scheme first recovers deleted video files from unallocated storage space exploiting both signatures of video frames and behaviours of file systems. The scheme finds fragments of deleted video files based on the start indicator of video frames or the file header signature, and connects the found fragments based on the file allocation patterns of FAT32 file system. Next, if a recovered video file is partially corrupted, the scheme automatically reconstructs the corrupted AVI video file so that the video file can be played back. The lost file header of the corrupted video file is reconstructed based on the file header of a reference video file, and the lost data multimedia data is filled with zero. Through practical implementation, we show that the proposed scheme recovers deleted video files from unallocated storage space and reconstructs corrupted AVI video files. Lee, Wan Yeon; Kim, Kyong Hoon; Yang, Hyeim; Ko, Young Woong Dongduk Womens Univ, Dept Comp Sci, Seoul 02748, South Korea; Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea; Hallym Univ, Dept Comp Sci & Engn, Chunchon 24252, South Korea Kim, Honghyok/LDF-5356-2024 14024347300; 15065463500; 57218329017; 16233663600 wanlee@dongduk.ac.kr; MULTIMEDIA TOOLS AND APPLICATIONS MULTIMED TOOLS APPL 1380-7501 1573-7721 79 37-38 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, SOFTWARE ENGINEERING;COMPUTER SCIENCE, THEORY & METHODS;ENGINEERING, ELECTRICAL & ELECTRONIC 2020 2.757 25.9 0.13 2025-06-25 2 2 Automatic reconstruction; Scattered video fragments; Corrupted video; AVI format; FAT32 LINUX FAT32 ALLOCATOR Automatic reconstruction; AVI format; Corrupted video; FAT32; Scattered video fragments Digital storage; File organization; Recovery; Security systems; Automatic reconstruction; FAT32 file systems; File allocation; File systems; Multimedia data; Recovery scheme; Storage spaces; Surveillance cameras; Image reconstruction English 2020 2020-10 10.1007/s11042-020-09404-5 바로가기 바로가기 바로가기 바로가기
Article Automatic segmentation of liver & lesion detection using H-minima transform and connecting component labeling Automatic segmentation of the liver and the Lesion detection can be a very challenging task due to its variability in size, shape, position and the presence of other organs with similar intensities. Manual segmentation and detection of a tumor is a time-consuming task and greatly depends upon the expertise and experience of the physician. We proposed a method which consists of automatic segmentation and detection of liver and lesion using CT scan modality. H-minima transform filter, Otsu global thresholds, Morphological opening by reconstruction and modified Connected Component Labeling algorithms are applied for liver segmentation. To keep the technique simple and effective, an appropriate range of threshold values are defined to detect different types of lesions. Performance of the proposed system is evaluated and compared with the state-of-the art algorithms. The results of the comparison show that the proposed approach is robust and efficient due to its simplicity. The dice coefficient score for the hepatic segmentation is 94% while sensitivity and specificity for hepatic lesion are 93% and 87% respectively. Khan, Nazish; Ahmed, Imran; Kiran, Mahreen; Rehman, Hamoodur; Din, Sadia; Paul, Anand; Reddy, Alavalapati Goutham Ctr Excellence Informat Technol, Inst Management Sci, Peshawar, Pakistan; Kyungpook Natl Univ, Sch Comp Sci & Engn, Korea, South Korea; Natl Inst Technol, Dept Comp Sci & Engn, Tadepalligudem, Andhra Pradesh, India Ahmed, Imran/HDL-7255-2022; Kiran, Mahreen/HGC-9076-2022; Din, Sadia/ADU-4679-2022; Paul, Anand/V-6724-2017; ALAVALAPATI, GOUTHAM REDDY/AGN-0905-2022; Alavalapati, Goutham Reddy/AGN-0905-2022 57207688029; 58776130700; 57207685107; 57207909427; 57188997144; 56650522400; 57189311304 diyanoor82@yahoo.com;imran.ahmed@imsciences.edu.pk;mehreen.kiran89@gmail.com;hamoodurrehman@imsciences.edu.pk;saadia.deen@gmail.com;paul.editor@gmail.com;goutham.ace@gmail.com; MULTIMEDIA TOOLS AND APPLICATIONS MULTIMED TOOLS APPL 1380-7501 1573-7721 79 13-14 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, SOFTWARE ENGINEERING;COMPUTER SCIENCE, THEORY & METHODS;ENGINEERING, ELECTRICAL & ELECTRONIC 2020 2.757 25.9 0.46 2025-06-25 7 7 Liver; Lesion; Segmentation; Detection; H-minima transform; CCL; Automatic; Opening by reconstruction CT; TOMOGRAPHY Automatic; CCL; Detection; H-minima transform; Lesion; Liver; Opening by reconstruction; Segmentation Error detection; Image segmentation; Liver; Automatic; Automatic segmentations; Connected component labeling algorithm; Lesion; Morphological opening; Sensitivity and specificity; State-of-the-art algorithms; Time-consuming tasks; Computerized tomography English 2020 2020-04 10.1007/s11042-019-7347-4 바로가기 바로가기 바로가기 바로가기
Article Biomechanical stability of internal bone-level implant: Dependency on hex or non-hex structure Considerable controversy surrounds the choice of the best abutment type for implant prosthetics. The two most common structures are hex and non-hex abutments. The non-hex abutment typically furnishes a larger contact area between itself and the implant than that provided by a hex structure. However, when a hex abutment is loaded, the position of its contact area may be deeper than that of a non-hex abutment. Hence, the purpose of this study is to determine the different biomechanical behaviors of an internal bone-level implant based on the abutment type-hex or non-hex-and clinical crown length under static and cyclic loadings using finite element analysis (FEA). The hex structure was found to increase the implant and abutment stability more than the non-hex structure among several criteria. The use of the hex structure resulted in a smaller volume of bone tissues being at risk of hypertrophy and fatigue failure. It also reduced micromovement (separation) between the implant components, which is significantly related to the pumping effect and possible inflammation. Both static and fatigue analyses, used to examine short- and long-term stability, demonstrated the advantages of the hex abutment over the non-hex type for the stability of the implant components. Moreover, although its impact was not as significant as that of the abutment type, a large crown-implant ratio (CIR) increased bone strain and stress in the implant components, particularly under oblique loading. Lee, Hyeonjong; Park, Si-Myung; Noh, Kwantae; Ahn, Su-Jin; Shin, Sangkyun; Noh, Gunwoo Pusan Natl Univ, Sch Dent, Dept Prosthodont, 49 Busandaehak Ro, Yangsan Si 50612, Gyeongsangnam D, South Korea; Korea Inst Sci & Technol, Ctr Med Robot, 5 Hwarang Ro,14 Gil, Seoul 02792, South Korea; Kyung Hee Univ, Dept Prosthodont, Sch Dent, 26 Kyungheedae Ro, Seoul 02447, South Korea; Kyung Hee Univ, Kyung Hee Univ Hosp Gangdong, Sch Dent, Dept Biomat & Prosthodont, 892 Dongnam Ro, Seoul 05278, South Korea; Kyungpook Natl Univ, Sch Mech Engn, 80 Daehak Ro, Daegu 41566, South Korea Noh, Kwantae/AAK-3492-2020; Lee, Hyeonjong/HDM-6492-2022 57190951278; 57192916912; 55041739400; 55145967600; 37054653900; 55010264000 gunwoo@knu.ac.kr; STRUCTURAL ENGINEERING AND MECHANICS STRUCT ENG MECH 1225-4568 1598-6217 74 4 SCIE ENGINEERING, CIVIL;ENGINEERING, MECHANICAL 2020 3.524 25.9 0.44 2025-06-25 8 8 finite element analysis; dental implant; abutment type; fatigue; micromovement FINITE-ELEMENT-ANALYSIS; STRESS-DISTRIBUTION; ABUTMENT INTERFACE; FRACTURE STRENGTH; INCLUSION; FATIGUE; TISSUE Abutment type; Dental implant; Fatigue; Finite element analysis; Micromovement Biomechanics; Fatigue of materials; Pathology; Stability criteria; Stress analysis; Abutment stability; Biomechanical behavior; Biomechanical stability; Common structures; Fatigue analysis; Fatigue failures; Implant components; Long term stability; Abutments (bridge) English 2020 2020-05-25 10.12989/sem.2020.74.4.567 바로가기 바로가기 바로가기 바로가기
Article Chemical bath synthesis of NiCo 2 O 4 nanoflowers with nanorods like thin film for flexible supercapacitor application -effect of urea concentration on structural conversion Waghmode, R. B.; Maile, N. C.; Lee, D. S.; Torane, A. P. Yashavantrao Chavan Inst Sci, Dept Phys, Solid State Phys Lab, Satara, India; Kyungpook Natl Univ, Dept Environm Engn, Daegu, South Korea Maile, Nagesh/AFD-8838-2022 57140737300; 57193804539; 55568524907; 6603033209 daesung@knu.ac.kr;appasahebtorane@yahoo.in; ELECTROCHIMICA ACTA ELECTROCHIM ACTA 0013-4686 1873-3859 350 SCIE ELECTROCHEMISTRY 2020 6.901 25.9 1.8 2025-06-25 44 46 CARBON TEXTILES; NANOWIRE ARRAYS; STAINLESS-STEEL; PERFORMANCE; DEPOSITION; ELECTRODES; FOAM; NANOSTRUCTURES Nickel-cobalt oxide; Polymer gel electrolyte; Symmetric-flexible supercapacitors Capacitance; Deposition; Metabolism; Morphology; Nanorods; Polyvinyl alcohols; Potassium hydroxide; Solid electrolytes; Supercapacitor; Thin films; Urea; Chemical-bath deposition; Electronic conductivity; Gel electrolyte; Ionic diffusion; Power densities; Specific capacitance; Structural conversion; Supercapacitor application; Nanoflowers English 2020 2020-08-01 10.1016/j.electacta.2020.136413 바로가기 바로가기 바로가기 바로가기
Article Comparative analysis of segmentation techniques based on chest X-ray images The image segmentation is the basic step in the image processing involved in the processing of medical images. Over the past two decades, medical image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in research studies. This article surveys the techniques and their effect on chest X-ray images. The objective of this work is to study the key similarities and differences among the different published methods while highlighting their strengths and weaknesses on chest X-ray images. The reason is to assist the researchers in the choice of an appropriate lung segmentation methodology. We additionally give a complete portrayal of the existing few basic methods when combined with preprocessing method that can be utilized as a part of the segmentation. A discussion and fair analysis justified with experimental results along with quantitative correlation of the outcomes on 247 images of JSRT through Dice coefficient exhibited. Kiran, Mehreen; Ahmed, Imran; Khan, Nazish; Rehman, Hamood Ur; Din, Sadia; Paul, Anand; Reddy, Alavalapati Goutham Ctr Excellence Informat Technol, Inst Management Sci, Peshawar, Pakistan; Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea; Natl Inst Technol, Dept Comp Sci & Engn, Tadepalligudem, Andhra Pradesh, India Rehman, Hamood/JDC-7393-2023; Din, Sadia/ADU-4679-2022; ALAVALAPATI, GOUTHAM REDDY/AGN-0905-2022; Alavalapati, Goutham Reddy/AGN-0905-2022; Kiran, Mahreen/HGC-9076-2022; Ahmed, Imran/HDL-7255-2022; Paul, Anand/V-6724-2017 57207685107; 58776130700; 57207688029; 57205131706; 57188997144; 56650522400; 57189311304 mehreen.kiran89@gmail.com;imran.ahmed@imseiences.edu.pk;diyanoor82@yahoomail.com;hamoodurrehman@imsciences.edu.pk;saadia.deen@gmail.com;paul.editor@gmail.com;goutham.ace@gmail.com; MULTIMEDIA TOOLS AND APPLICATIONS MULTIMED TOOLS APPL 1380-7501 1573-7721 79 13-14 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, SOFTWARE ENGINEERING;COMPUTER SCIENCE, THEORY & METHODS;ENGINEERING, ELECTRICAL & ELECTRONIC 2020 2.757 25.9 0 2025-06-25 1 2 Chest radiography; Survey; Computer-aided diagnosis; Codes; executable; Commands; Lung region extraction; Segmentation MEANS CLUSTERING-ALGORITHM; CONTRAST ENHANCEMENT; K-MEANS; HISTOGRAM EQUALIZATION Chest radiography; Codes; Commands; Computer-aided diagnosis; executable; Lung region extraction; Segmentation; Survey Biological organs; Computer aided diagnosis; Image analysis; Image segmentation; Surveying; Surveys; X ray radiography; Chest radiography; Codes; Commands; executable; Lung regions; Medical image processing English 2020 2020-04 10.1007/s11042-019-7348-3 바로가기 바로가기 바로가기 바로가기
Article Convolutional neural network based early fire detection The detection of manmade disasters particularly fire is valuable because it causes many damages in terms of human lives. Research on fire detection using wireless sensor network and video-based methods is a very hot research topic. However, the WSN based detection model need fire happens and a lot of smoke and fire for detection. Similarly, video-based models also have some drawbacks because conventional algorithms need feature vectors and high rule-based models for detection. In this paper, we proposed a fire detection method which is based on powerful machine learning and deep learning algorithms. We used both sensors data as well as images data for fire prevention. Our proposed model has three main deep neural networks i.e. a hybrid model which consists of Adaboost and many MLP neural networks, Adaboost-LBP model and finally convolutional neural network. We used Adaboost-MLP model to predict the fire. After the prediction, we proposed two neural networks i.e. Adaboost-LBP model and convolutional neural network for detection of fire using the videos and images taken from the cameras installed for the surveillance. Adaboost-LBP model is to generate the ROIs from the image where emergencies exist Our proposed model results are quite good, and the accuracy is almost 99%. The false alarming rate is very low and can be reduced more using further training. Saeed, Faisal; Paul, Anand; Karthigaikumar, P.; Nayyar, Anand Kyungpook Natl Univ, 80 Daehak Ro, Daegu, South Korea; Kyungpook Natl Univ, Sch Comp Sci & Engn, 80 Daehak Ro, Daegu, South Korea; Anna Univ, Chennai 600025, Tamil Nadu, India; Duy Tan Univ, Grad Sch, Da Nang, Vietnam Nayyar, Anand/F-3732-2015; Saeed, Faisal/HNT-0710-2023; Nayyar, Dr. Anand/F-3732-2015; Paul, Anand/V-6724-2017; Palanivel, Karthigaikumar/AAR-5414-2020 58165089300; 56650522400; 16637341800; 55201442200 bscsfaisal821@gmail.com;paul.editor@gmail.com;p.karthigaikumar@gmail.com;anandnayyar@duytan.edu.vn; MULTIMEDIA TOOLS AND APPLICATIONS MULTIMED TOOLS APPL 1380-7501 1573-7721 79 13-14 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, SOFTWARE ENGINEERING;COMPUTER SCIENCE, THEORY & METHODS;ENGINEERING, ELECTRICAL & ELECTRONIC 2020 2.757 25.9 3.61 2025-06-25 76 92 Fire; Machine learning; Adaboost-MLP; Adaboost-LBP; Convolutional Neural Network FLAME DETECTION; IMAGE; ALGORITHM; COLOR Adaboost-LBP; Adaboost-MLP; Convolutional Neural Network; Fire; Machine learning Adaptive boosting; Convolution; Damage detection; Deep neural networks; Fire detectors; Fireproofing; Fires; Learning systems; Machine learning; Neural networks; Security systems; Smoke; Conventional algorithms; Convolutional neural network; Fire-detection method; Further trainings; Hot research topics; Man-made disasters; MLP neural networks; Rule-based models; Wireless sensor networks English 2020 2020-04 10.1007/s11042-019-07785-w 바로가기 바로가기 바로가기 바로가기
Article Designing of nanoflakes anchored nanotubes-like MnCo2S4/halloysite composites for advanced battery like supercapacitor application In this study, we report a facile chemical synthesis of a novel MnCo2S4/halloysite (HNTs) nanoflakes decorated on nanotubes which coated on Ni foam via a screen-printing technique. The MnCo2S4 thin films were prepared using a coprecipitation method which demonstrate battery kind of behavior. The MnCo2S4/HNTs-based electrode shows a specific capacity of 359 mAh g(-1) at 5 mV s(-1) with excellent cycling stability. Furthermore, the symmetric system exhibits an outstanding energy density and power density of 6.98 Wh kg(-1) and 1976.0 W kg(-1), respectively. The results obtained with the MnCo2S4/HNTs composite in a symmetric system indicate that this composite material can potentially be used as an alternative electrode material for electrochemical energy storage. (C) 2020 Elsevier Ltd. All rights reserved. Shinde, S. K.; Ghodake, G. S.; Maile, N. C.; Yadav, H. M.; Jagadale, A. D.; Jalak, M. B.; Kadam, A. A.; Ramesh, Sivalingam; Bathula, C.; Kim, D-Y Dongguk Univ, Coll Life Sci & Biotechnol, Dept Biol & Environm Sci, 32 Dongguk Ro,Biomed Campus, Goyang Si 10326, Gyeonggi Do, South Korea; Kyungpook Natl Univ, Dept Environm Engn, 80 Daehak Ro, Daegu 41566, South Korea; Dongguk Univ, Dept Energy & Mat Engn, Seoul 04620, South Korea; SASTRA Deemed Univ, Sch Elect & Elect Engn, Ctr Energy Storage & Convers, Thanjavur 613401, Tamil Nadu, India; Shivaji Univ, Dept Phys, Kolhapur 416004, Maharashtra, India; Dongguk Univ, Res Inst Biotechnol & Med Converged Sci, Biomed Campus, Goyang Si 10326, Gyeonggi Do, South Korea; Dongguk Univ, Dept Mech Robot & Energy Engn, Seoul 04620, South Korea; Dongguk Univ Seoul, Div Elect & Elect Engn, Seoul 04620, South Korea Kadam, Avinash/G-5992-2016; Jagadale, Ajay/O-5253-2014; Kadam, Avinash Ashok/G-5992-2016; Maile, Nagesh/AFD-8838-2022 55776351000; 22979024500; 57193804539; 55389590800; 44161199800; 57203877390; 56267499300; 57280606300; 36993734300; 55742887400 sbpkim@dongguk.edu; ELECTROCHIMICA ACTA ELECTROCHIM ACTA 0013-4686 1873-3859 341 SCIE ELECTROCHEMISTRY 2020 6.901 25.9 2.2 2025-06-25 41 42 MnCo2S4/HNTs composite; Coprecipitation; Screen printing method; Nanotubes; Symmetric electrode HALLOYSITE NANOTUBES; ELECTROCHEMICAL PERFORMANCE; HYDROTHERMAL CARBONIZATION; EFFICIENT ELECTROCATALYST; NIS NANOPARTICLES; COUNTER ELECTRODE; NANOSTRUCTURES; MNCO2S4; NANOSHEETS; GRAPHENE Coprecipitation; MnCo<sub>2</sub>S<sub>4</sub>/HNTs composite; Nanotubes; Screen printing method; Symmetric electrode Coprecipitation; Electrochemical electrodes; Nanotubes; Screen printing; Secondary batteries; Supercapacitor; Coprecipitation method; Electrochemical energy storage; Electrode material; Screen printing methods; Screen printing technique; Specific capacities; Supercapacitor application; Symmetric systems; Manganese compounds English 2020 2020-05-01 10.1016/j.electacta.2020.135973 바로가기 바로가기 바로가기 바로가기
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WoS Web of Science. Clarivate Analytics에서 제공하는 학술 데이터베이스입니다. 해당 논문이 WoS에 수록되어 있는지 여부를 표시합니다 (○: 수록됨).
SCOPUS Elsevier에서 제공하는 세계 최대 규모의 초록 및 인용 데이터베이스입니다. 해당 논문이 SCOPUS에 수록되어 있는지 여부를 표시합니다 (○: 수록됨).
Document Type 문헌의 유형을 나타냅니다. Article(원저), Review(리뷰), Proceeding Paper(학회논문), Editorial Material(편집자료), Letter(레터) 등으로 분류됩니다.
Title 논문의 제목입니다.
Abstract 논문의 초록(요약)입니다. 연구의 목적, 방법, 결과, 결론을 간략히 요약한 내용입니다.
Authors 논문의 저자 목록입니다. 공동 저자가 여러 명인 경우 세미콜론(;)으로 구분됩니다.
Affiliation 저자들의 소속 기관 정보입니다. 대학, 연구소, 기업 등 저자가 소속된 기관명이 표시됩니다.
ResearcherID (WoS) Web of Science의 고유 연구자 식별번호입니다. 동명이인을 구분하고 연구자의 업적을 정확하게 추적할 수 있습니다.
AuthorsID (SCOPUS) SCOPUS의 고유 저자 식별번호입니다. 연구자의 모든 출판물을 추적하고 관리하는 데 사용됩니다.
Journal 논문이 게재된 학술지의 정식 명칭입니다.
JCR Abbreviation Journal Citation Reports에서 사용하는 저널의 공식 약어입니다. 저널을 간략하게 표기할 때 사용됩니다.
ISSN International Standard Serial Number. 국제표준연속간행물번호로, 인쇄본 저널에 부여되는 고유 식별번호입니다.
eISSN Electronic ISSN. 전자 버전 저널에 부여되는 고유 식별번호입니다.
Volume 저널의 권(Volume) 번호입니다. 보통 연도별로 하나의 권이 부여됩니다.
Issue 저널의 호(Issue) 번호입니다. 한 권 내에서 여러 호로 나누어 출판되는 경우가 많습니다.
WoS Edition Web of Science의 에디션입니다. SCIE(Science Citation Index Expanded), SSCI(Social Sciences Citation Index), AHCI(Arts & Humanities Citation Index) 등으로 구분됩니다.
WoS Category Web of Science의 주제 분류 카테고리입니다. 저널과 논문이 속한 학문 분야를 나타냅니다.
JCR Year 해당 저널의 JCR(Journal Citation Reports) 지표가 산출된 연도입니다.
IF (Impact Factor) 저널 영향력 지수. 최근 2년간 발표된 논문이 해당 연도에 평균적으로 인용된 횟수를 나타냅니다. 저널의 학술적 영향력을 나타내는 대표적인 지표입니다.
JCR (%) 해당 카테고리에서 저널이 위치하는 상위 백분율입니다. 값이 낮을수록 우수한 저널임을 의미합니다 (예: 5%는 상위 5%를 의미).
FWCI Field-Weighted Citation Impact. 분야별 가중 인용 영향력 지수입니다. 논문이 받은 인용을 동일 분야, 동일 연도, 동일 문헌 유형의 평균과 비교한 값입니다. 1.0이 평균이며, 1.0보다 높으면 평균 이상의 인용을 받았음을 의미합니다.
FWCI UpdateDate FWCI 값이 마지막으로 업데이트된 날짜입니다. FWCI는 인용이 누적됨에 따라 주기적으로 업데이트됩니다.
WOS Citation Web of Science에서 집계된 해당 논문의 총 인용 횟수입니다.
SCOPUS Citation SCOPUS에서 집계된 해당 논문의 총 인용 횟수입니다.
Keywords (WoS) 저자가 논문에서 직접 지정한 키워드입니다. Web of Science에 등록된 저자 키워드 목록입니다.
KeywordsPlus (WoS) Web of Science에서 자동으로 추출한 추가 키워드입니다. 논문의 참고문헌 제목에서 자주 등장하는 단어들로 생성됩니다.
Keywords (SCOPUS) 저자가 논문에서 직접 지정한 키워드입니다. SCOPUS에 등록된 저자 키워드 목록입니다.
KeywordsPlus (SCOPUS) SCOPUS에서 자동으로 추출하거나 추가한 색인 키워드입니다.
Language 논문이 작성된 언어입니다. 대부분 English이며, 그 외 다양한 언어로 작성된 논문이 포함될 수 있습니다.
Publication Year 논문이 출판된 연도입니다.
Publication Date 논문의 정확한 출판 날짜입니다 (년-월-일 형식).
DOI Digital Object Identifier. 디지털 객체 식별자로, 논문을 고유하게 식별하는 영구적인 식별번호입니다. 이를 통해 논문의 온라인 위치를 찾을 수 있습니다.