Hang Liu Fei Wu
Keiji GOTO Toru KAWANO Ryohei NAKAMURA
Takahiro SASAKI Yukihiro KAMIYA
Xiang XIONG Wen LI Xiaohua TAN Yusheng HU
Anton WIDARTA
Hiroshi OKADA Mao FUKINAKA Yoshiki AKIRA
Shun-ichiro Ohmi
Tohgo HOSODA Kazuyuki SAITO
Shohei Matsuhara Kazuyuki Saito Tomoyuki Tajima Aditya Rakhmadi Yoshiki Watanabe Nobuyoshi Takeshita
Koji Abe Mikiya Kuzutani Satoki Furuya Jose A. Piedra-Lorenzana Takeshi Hizawa Yasuhiko Ishikawa
Yihan ZHU Takashi OHSAWA
Shengbao YU Fanze MENG Yihan SHEN Yuzhu HAO Haigen ZHOU
Ryo KUMAGAI Ryosuke SUGA Tomoki UWANO
Jun SONODA Kazusa NAKAMICHI
Kaiji Owaki Yusuke Kanda Hideaki Kimura
Takuya FUJIMOTO
Yuji Wada
Fuyuki Kihara Chihiro Matsui Ken Takeuchi
Keito YUASA Michihiro IDE Sena KATO Kenichi OKADA Atsushi SHIRANE
Tomoo Ushio Yuuki Wada Syo Yoshida
Futoshi KUROKI
Jun FURUTA Shotaro SUGITANI Ryuichi NAKAJIMA Takafumi ITO Kazutoshi KOBAYASHI
Yuya Ichikawa Ayumu Yamada Naoko Misawa Chihiro Matsui Ken Takeuchi
Ayumu Yamada Zhiyuan Huang Naoko Misawa Chihiro Matsui Ken Takeuchi
Yoshinori ITOTAGAWA Koma ATSUMI Hikaru SEBE Daisuke KANEMOTO Tetsuya HIROSE
Hikaru SEBE Daisuke KANEMOTO Tetsuya HIROSE
Zhibo CAO Pengfei HAN Hongming LYU
Takuya SAKAMOTO Itsuki IWATA Toshiki MINAMI Takuya MATSUMOTO
Koji YAMANAKA Kazuhiro IYOMASA Takumi SUGITANI Eigo KUWATA Shintaro SHINJO
Minoru MIZUTANI Takashi OHIRA
Katsumi KAWAI Naoki SHINOHARA Tomohiko MITANI
Baku TAKAHARA Tomohiko MITANI Naoki SHINOHARA
Akihiko ISHIWATA Yasumasa NAKA Masaya TAMURA
Atsushi Fukuda Hiroto Yamamoto Junya Matsudaira Sumire Aoki Yasunori Suzuki
Ting DING Jiandong ZHU Jing YANG Xingmeng JIANG Chengcheng LIU
Fan Liu Zhewang Ma Masataka Ohira Dongchun Qiao Guosheng Pu Masaru Ichikawa
Ludovico MINATI
Minoru Fujishima
Hyunuk AHN Akito IGUCHI Keita MORIMOTO Yasuhide TSUJI
Kensei ITAYA Ryosuke OZAKI Tsuneki YAMASAKI
Akira KAWAHARA Jun SHIBAYAMA Kazuhiro FUJITA Junji YAMAUCHI Hisamatsu NAKANO
Seiya Kishimoto Ryoya Ogino Kenta Arase Shinichiro Ohnuki
Yasuo OHTERA
Tomohiro Kumaki Akihiko Hirata Tubasa Saijo Yuma Kawamoto Tadao Nagatsuma Osamu Kagaya
Haonan CHEN Akito IGUCHI Yasuhide TSUJI
Keiji GOTO Toru KAWANO Munetoshi IWAKIRI Tsubasa KAWAKAMI Kazuki NAKAZAWA
Dongzhu LI Zhijie ZHAN Rei SUMIKAWA Mototsugu HAMADA Atsutake KOSUGE Tadahiro KURODA
A 0.13mJ/prediction with 68.6% accuracy wired-logic deep neural network (DNN) processor is developed in a single 16-nm field-programmable gate array (FPGA) chip. Compared with conventional von-Neumann architecture DNN processors, the energy efficiency is greatly improved by eliminating DRAM/BRAM access. A technical challenge for conventional wired-logic processors is the large amount of hardware resources required for implementing large-scale neural networks. To implement a large-scale convolutional neural network (CNN) into a single FPGA chip, two technologies are introduced: (1) a sparse neural network known as a non-linear neural network (NNN), and (2) a newly developed raster-scan wired-logic architecture. Furthermore, a novel high-level synthesis (HLS) technique for wired-logic processor is proposed. The proposed HLS technique enables the automatic generation of two key components: (1) Verilog-hardware description language (HDL) code for a raster-scan-based wired-logic processor and (2) test bench code for conducting equivalence checking. The automated process significantly mitigates the time and effort required for implementation and debugging. Compared with the state-of-the-art FPGA-based processor, 238 times better energy efficiency is achieved with only a slight decrease in accuracy on the CIFAR-100 task. In addition, 7 times better energy efficiency is achieved compared with the state-of-the-art network-optimized application-specific integrated circuit (ASIC).
Yosuke ITO Tatsuya GOTO Takuma HORI
In recent years, measuring biomagnetic fields in the Earth’s field by differential measurements of scalar-mode OPMs have been actively attempted. In this study, the sensitivity of the scalar-mode OPMs under the geomagnetic environment in the laboratory was studied by numerical simulation. Although the noise level of the scalar-mode OPM in the laboratory environment was calculated to be 104 pT/$\sqrt{\mathrm{Hz}}$, the noise levels using the first-order and the second-order differential configurations were found to be 529 fT/cm/$\sqrt{\mathrm{Hz}}$ and 17.2 fT/cm2/$\sqrt{\mathrm{Hz}}$, respectively. This result indicated that scalar-mode OPMs can measure very weak magnetic fields such as MEG without high-performance magnetic shield roomns. We also studied the operating conditions by varying repetition frequency and temperature. We found that scalar-mode OPMs have an upper limit of repetition frequency and temperature, and that the repetition frequency should be set below 4 kHz and the temperature should be set below 120°C.
The magnetic field resolution of the tunnel magneto-resistive (TMR) sensors has been improving and it reaches below 1.0 pT/Hz0.5 at low frequency. The real-time measurement of the magnetocardiography (MCG) and the measurement of the magnetoencephalography (MEG) have been demonstrated by developed TMR sensors. Although the MCG and MEG have been applied to diagnosis of diseases, the conventional MCG/MEG system using superconducting quantum interference devices (SQUIDs) cannot measure the signal by touching the body, the body must be fixed, and maintenance costs are huge. The MCG/MEG system with TMR sensors operating at room temperature have the potential to solve these problems. In addition, it has the great advantage that it does not require a special magnetic shielded room. Further developments are expected to progress to maximize these unique features of TMR sensors.
Mohd Mawardi SAARI Mohd Herwan SULAIMAN Toshihiko KIWA
In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor coupled by a flux transformer to sense the modulated magnetization signal from a sample. The magnetization signal is modulated by the lateral vibration of the sample on top of a planar differential detection coil of the flux transformer. A pair of primary and excitation coils are utilized to apply an excitation field parallel to the sensitive axis of the detection coil. Using the high-Tc SQUID magnetometer, the magnetization curve of a commercial MNP sample (Resovist) was measured in a logarithmic scale of the excitation field. The PSO inverse technique is then applied to the magnetization curve to construct the magnetic moment distribution. A multimodal normalized log-normal distribution was used in the minimization of the objective function of the PSO inversion technique, and a modification of the PSO search region is proposed to improve the exploration and exploitation of the PSO particles. As a result, a good agreement on the Resovist magnetic core size was obtained between the proposed technique and the non-negative least square (NNLS) inversion technique. The estimated core sizes of 8.0484 nm and 20.3018 nm agreed well with the values reported in the literature using the commercial low-Tc SQUID magnetometer with the SVD and NNLS inversion techniques. Compared to the NNLS inversion technique, the PSO inversion technique had merits in exploring an optimal core size distribution freely without being regularized by a parameter and facilitating an easy peak position determination owing to the smoothness of the constructed distribution. The combination of the high-Tc SQUID magnetometer and the PSO-based reconstruction technique offers a powerful approach for characterizing the MNP core size distribution, and further improvements can be expected from the recent state-of-the-art optimization algorithm to optimize further the computation time and the best objective function value.
Takako MIZOGUCHI Akihiko KANDORI Keiji ENPUKU
Simple and quick tests at medical clinics have become increasingly important. Magnetic sensing techniques have been developed to detect biomarkers using magnetic nanoparticles in liquid-phase assays. We developed a biomarker assay that involves using an alternating current (AC) susceptibility measurement system that uses functional magnetic particles and magnetic sensing technology. We also developed compact biomarker measuring equipment to enable quick testing. Our assay is a one-step homogeneous assay that involves simply mixing a sample with a reagent, shortening testing time and simplifying processing. Using our compact measuring equipment, which includes anisotropic magneto resistance (AMR) sensors, we conducted high-sensitivity measurements of extremely small amounts of two biomarkers (C-reactive protein, CRP and α-Fetoprotein, AFP) used for diagnosing arteriosclerosis and malignant tumors. The results indicate that an extremely small amount of CRP and AFP could be detected within 15 min, which demonstrated the possibility of a simple and quick high-sensitivity immunoassay that involves using an AC-susceptibility measurement system.