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.

We introduce the Hexagonal Convolutional Neural Network (HCNN), a modified version of CNN that is robust against rotation. HCNN utilizes a hexagonal kernel and a multi-block structure that enjoys more degrees of rotation information sharing than standard convolution layers. Our structure is easy to use and does not affect the original tissue structure of the network. We achieve the complete rotational invariance on the recognition task of simple pattern images and demonstrate better performance on the recognition task of the rotated MNIST images, synthetic biomarker images and microscopic cell images than past methods, where the robustness to rotation matters.

Device-to-device (D2D) communication allows user terminals to directly communicate with each other without the need for any base stations (BSs). Since the D2D communication underlaying a cellular system shares frequency channels with BSs, co-channel interference may occur. Successive interference cancellation (SIC), which is also called the serial interference canceler, detects and subtracts user signals from received signals in descending order of received power, can cope with the above interference and has already been applied to fog nodes that manage communications among machine-to-machine (M2M) devices besides direct communications with BSs. When differences among received power levels of user signals are negligible, however, SIC cannot work well and thus causes degradation in bit error rate (BER) performance. To solve such a problem, this paper proposes to apply parallel interference cancellation (PIC), which can simultaneously detect both desired and interfering signals under the maximum likelihood criterion and can maintain good BER performance even when power level differences among users are small. When channel coding is employed, however, SIC can be superior to PIC in terms of BER under some channel conditions. Considering the superiority, this paper also proposes to select the proper cancellation scheme and modulation and coding scheme (MCS) that can maximize the throughput of D2D under a constraint of BER, in which the canceler selection is referred to as adaptive interference cancellation. Computer simulations show that PIC outperforms SIC under almost all channel conditions and thus the adaptive selection from PIC and SIC can achieve a marginal gain over PIC, while PIC can achieve 10% higher average system throughput than that of SIC. As for transmission delay time, it is demonstrated that the adaptive selection and PIC can shorten the delay time more than any other schemes, although the fog node causes the delay time of 1ms at least.

Studies on intrinsic Josephson junctions (IJJs) of cuprate superconductors are reviewed. A system consisting of a few IJJs provides phenomena to test the Josephson phase dynamics and its interaction between adjacent IJJs within a nanometer scale, which is unique to cuprate superconductors. Quasiparticle density of states, which provides direct information on the Cooper-pair formation, is also revealed in the system. In contrast, Josephson plasma emission, which is an electromagnetic wave radiation in the sub-terahertz frequency range from an IJJ stack, arises from the synchronous phase dynamics of hundreds of IJJs coupled globally. This review summarizes a wide range of physical phenomena in IJJ systems having capacitive and inductive couplings with different nanometer and micrometer length scales, respectively.

The Dynamic Spectrum Sharing (DSS) system, which uses the frequency band allocated to incumbent systems (i.e., primary users) has attracted attention to expand the available bandwidth of the fifth-generation mobile communication (5G) systems in the sub-6GHz band. In Japan, a DSS system in the 2.3GHz band, in which the ARIB STD-B57-based Field Pickup Unit (FPU) is assigned as an incumbent system, has been studied for the secondary use of 5G systems. In this case, the incumbent FPU is a mobile system, and thus, the DSS system needs to use not only a spectrum sharing database but also radio sensors to detect primary signals with high accuracy, protect the primary system from interference, and achieve more secure spectrum sharing. This paper proposes highly efficient sensing methods for detecting the ARIB STD-B57-based FPU signals in the 2.3GHz band. The proposed methods can be applied to two types of the FPU signal; those that apply the Continuous Pilot (CP) mode pilot and the Scattered Pilot (SP) mode pilot. Moreover, we apply a sample addition method and a symbol addition method for improving the detection performance. Even in the 3GPP EVA channel environment, the proposed method can, with a probability of more than 99%, detect the FPU signal with an SNR of -10dB. In addition, we propose a quantized reference signal for reducing the implementation complexity of the complex cross-correlation circuit. The proposed reference signal can reduce the number of quantization bits of the reference signal to 2 bits for in-phase and 3 bits for orthogonal components.

In this paper, for the purpose of clarifying the desired ITS information and communication systems considering both safety and social feasibility to prevention overengineering, using a microscopic traffic flow simulator, we discuss the required information acquisition rate of three types of safety driving support systems, that is, the sensor type and the communication type, the sensor and communication fusion type. Performances are evaluated from the viewpoint of preventing overengineering performance using the “TsRm evaluation method” that considers a vehicle approaching within the range of R meters within T seconds as the vehicle with a high possibility of collision, and that evaluates only those vehicles. The results show that regarding the communication radius and the sensing range, overengineering performance may be estimated when all vehicles in the evaluation area are used for evaluations without considering each vehicle's location, velocity and acceleration as in conventional evaluations. In addition, it is clarified that the sensor and communication fusion type system is advantageous by effectively complementing the defects of the sensor type systems and the communication type systems.

The Topics over Time (TOT) model allows users to be aware of changes in certain topics over time. The proposed method inputs the divided dataset of security blog posts based on a fixed period using an overlap period to the TOT. The results suggest the extraction of topics that include malware and attack campaign names that are appropriate for the multi-labeling of cyber threat intelligence reports.

In this paper, we propose an accurate calibration method for glassless stereoscopic systems. The method uses a lenticular lens on a general display. Glassless stereoscopic displays are currently used in many fields; however, accurately adjusting their physical display position is difficult because an accuracy of several microns or one hundredth of a degree is required, particularly given their larger display area. The proposed method enables a dynamic adjustment of the positions of images on the display to match various physical conditions in three-dimensional (3D) displays. In particular, compared with existing approaches, this avoids degradation of the image quality due to the image location on the screen while improving the image quality by local mapping. Moreover, it is shown to decrease the calibration time by performing simultaneous processing for each local area. As a result of the calibration, the offset jitter representing the crosstalk reduces from 14.946 to 8.645 mm. It is shown that high-quality 3D videos can be generated. Finally, we construct a stereoscopic viewing system using a high-resolution display and lenticular lens and produce high-quality 3D images with automatic calibration.

This paper investigates the performance of interleave division multiple access (IDMA)-based random access with various interference canceller structures in order to support massive machine-type communications (mMTC) in the fifth generation (5G) mobile communication system. To support massive connectivity in the uplink, a grant-free and contention-based multiple access scheme is essential to reduce the control signaling overhead and transmission latency. To suppress the packet loss due to collision and to achieve multi-packet reception, non-orthogonal multiple access (NOMA) with interference cancellation at the base station receiver is essential. We use IDMA and compare various interference canceller structures such as the parallel interference canceller (PIC), successive interference canceller (SIC), and their hybrid from the viewpoints of the error rate and decoding delay time. Based on extensive computer simulations, we show that IDMA-based random access is a promising scheme for supporting mMTC and the PIC-SIC hybrid achieves a good tradeoff between the error rate and decoding delay time.

A method for estimating circuit performance variation caused by packaging-induced mechanical stress is proposed. The developed method is based on the stress distribution chart for the target integrated circuit (IC) and the stress sensitivity characteristics of individual devices. This information is experimentally obtained using a specially designed test chip and a cantilever bending calibration system. A post-packaging analysis and simulation tool, called Stress Netlist Generator (SNG), is developed for conducting the proposed method. Based on the stress distribution chart and the stress sensitivity characteristics, SNG modifies the SPICE model parameters in the target netlist according to the impact of the packaging-induced stress. The netlist generated by SNG is used to estimate packaging-induced performance variation with high accuracy. The developed method is remarkably effective even for small-scale ICs with chip sizes of roughly 1 mm2, such as power management ICs, which require higher precision.

Picross 3D is a popular single-player puzzle video game for the Nintendo DS. It presents a rectangular parallelepiped (i.e., rectangular box) made of unit cubes, some of which must be removed to construct an object in three dimensions. Each row or column has at most one integer on it, and the integer indicates how many cubes in the corresponding 1D slice remain when the object is complete. Kusano et al. showed that Picross 3D is NP-complete and Kimura et al. showed that the counting version, the another solution problem, and the fewest clues problem of Picross 3D are #P-complete, NP-complete, and Σ2P-complete, respectively, where those results are shown for the restricted input that the rectangular parallelepiped is of height four. On the other hand, Igarashi showed that Picross 3D is NP-complete even if the height of the input rectangular parallelepiped is one. Extending the result by Igarashi, we in this paper show that the counting version, the another solution problem, and the fewest clues problem of Picross 3D are #P-complete, NP-complete, and Σ2P-complete, respectively, even if the height of the input rectangular parallelepiped is one. Since the height of the rectangular parallelepiped of any instance of Picross 3D is at least one, our hardness results are best in terms of height.

Here, we present a novel spectroscopic imaging method based on the boundary-extraction scheme for wide-beam terahertz (THz) three-dimensional imaging. Optical-lens-focusing systems for THz subsurface imaging generally require the depth of the object from the surface to be input beforehand to achieve the desired azimuth resolution. This limitation can be alleviated by incorporating a wide-beam THz transmitter into the synthetic aperture to automatically change the focusing depth in the post-signal processing. The range point migration (RPM) method has been demonstrated to have significant advantages in terms of imaging accuracy over the synthetic-aperture method. Moreover, in the RPM scheme, spectroscopic information can be easily associated with each scattering center. Thus, we propose an RPM-based terahertz spectroscopic imaging method. The finite-difference time-domain-based numerical analysis shows that the proposed algorithm provides accurate target boundary imaging associated with each frequency-dependent characteristic.

Liquid crystal director distributions between strong and weak polar anchoring surfaces in hybrid aligned cells are numerically analyzed. When the anchoring is a critical one, homogeneously or homeotropicly liquid crystal alignment can be obtained. Such cells have no threshold voltage and a driving voltage can be reduced less than 0.5 volt.

Mining software artifacts is a useful way to understand the source code of software projects. Topic modeling in particular has been widely used to discover meaningful information from software artifacts. However, software artifacts are unstructured and contain a mix of textual types within the natural text. These software artifact characteristics worsen the performance of topic modeling. Among several natural language pre-processing tasks, removing stop words to reduce meaningless and uninteresting terms is an efficient way to improve the quality of topic models. Although many approaches are used to generate effective stop words, the lists are outdated or too general to apply to mining software artifacts. In addition, the performance of the topic model is sensitive to the datasets used in the training for each approach. To resolve these problems, we propose an automatic stop word generation approach for topic models of software artifacts. By measuring topic coherence among words in the topic using Pointwise Mutual Information (PMI), we added words with a low PMI score to our stop words list for every topic modeling loop. Through our experiment, we proved that our stop words list results in a higher performance of the topic model than lists from other approaches.

Hadoop, a distributed processing framework for big-data, is now widely used for multimedia processing. However, when processing video data from a Hadoop distributed file system (HDFS), unnecessary network traffic is generated due to an inefficient HDFS block slice policy for picture frames in video files. We propose a new block replication policy to solve this problem and compare the newly proposed HDFS with the original HDFS via extensive experiments. The proposed HDFS reduces network traffic, and increases locality between processing cores and file locations.

This paper introduces recent trends in video streaming and four methods proposed by the authors for video streaming. Video traffic dominates the Internet as seen in current trends, and new visual contents such as UHD and 360-degree movies are being delivered. MPEG-DASH has become popular for adaptive video streaming, and machine learning techniques are being introduced in several parts of video streaming. Along with these research trends, the authors also tried four methods: route navigation, throughput prediction, image quality assessment, and perceptual video streaming. These methods contribute to improving QoS/QoE performance and reducing power consumption and storage size.

We describe the preparation of an α-phenyl-4'-(diphenylamino)stilbene (TPA) single crystal and the evaluation of its hole transport property. Based on the characterization using optical microscopy, polarizing microscopy, and X-ray diffraction, a large-scale TPA single crystal of dimensions 7.0×0.9×0.8mm is successfully synthesized using a solution method based on the solubility and supersolubility curves of the TPA. Notably, the current in the long-axis direction is larger than those in the short-axis and thickness directions (i(long) > i(short) > i(thickness)), which reveals the anisotropic charge transfer of the TPA single crystal. The observed anisotropic conductivity is well explained by the orientation of the triphenylamine unit in the TPA single crystal. Furthermore, the activation energy of the long-axis direction in the TPA single crystal is lower than that of the short-axis in TPA and all the axes in the α-phenyl-4'-[bis(4-methylphenyl)amino]stilbene single crystal reported in our previous study.

This paper presents a formal approach for generating train timetables in a mesoscopic level that is more concrete than the macroscopic level, where each station is simply expressed in a black-box, and more abstract than the microscopic level, where the infrastructure in each station-area is expressed in detail. The accuracy of generated timetable and the computational effort for the generation is a trade-off. In this paper, we design a formal mesoscopic modeling language by analyzing real railways, for example Tazawako-line as the first step of this work. Then, we define the constraint formulae for generating train timetables with the help of SMT (Satisfiability Module Theories)-Solver, and explain our tool RW-Solver that is an implementation of the constraint formulae. Finally, we demonstrate how RW-Solver with the help of SMT-Solver can be used for generating timetables in a case study of Tazawako-line.

Depth image based rendering (DIBR), which is utilized to render virtual views with a color image and the corresponding depth map, is one of the key procedures in the 2D to 3D conversion process. However, some troubling problems, such as depth edge misalignment, disocclusion occurrences and cracks at resampling, still exist in current DIBR systems. To solve these problems, in this paper, we present a robust depth image based rendering scheme for stereoscopic view synthesis. The cores of the proposed scheme are two depth map filters which share a common domain transform based filtering framework. As a first step, a filter of this framework is carried out to realize texture-depth boundary alignments and directional disocclusion reduction smoothing simultaneously. Then after depth map 3D warping, another adaptive filter is used on the warped depth maps with delivered scene gradient structures to further diminish the remaining cracks and noises. Finally, with the optimized depth map of the virtual view, backward texture warping is adopted to retrieve the final texture virtual view. The proposed scheme enables to yield visually satisfactory results for high quality 2D to 3D conversion. Experimental results demonstrate the excellent performances of the proposed approach.

Word boundary ambiguity in word segmentation has long been a fundamental challenge within Thai language processing. The Conditional Random Fields (CRF) model is among the best-known methods to have achieved remarkably accurate segmentation. Nevertheless, current advancements appear to have left the problem of compound words unaccounted for. Compound words lose their meaning or context once segmented. Hence, we introduce a dictionary-based word-merging algorithm, which merges all kinds of compound words. Our evaluation shows that the algorithm can accomplish a high-accuracy of word segmentation, with compound words being preserved. Moreover, it can also restore some incorrectly segmented words. Another problem involving a different word-chunking approach is sentence boundary ambiguity. In tackling the problem, utilizing the part of speech (POS) of a segmented word has been found previously to help boost the accuracy of CRF-based sentence segmentation. However, not all segmented words can be tagged. Thus, we propose a POS-based word-splitting algorithm, which splits words in order to increase POS tags. We found that with more identifiable POS tags, the CRF model performs better in segmenting sentences. To demonstrate the contributions of both methods, we experimented with three of their applications. With the word merging algorithm, we found that intact compound words in the product of topic extraction can help to preserve their intended meanings, offering more precise information for human interpretation. The algorithm, together with the POS-based word-splitting algorithm, can also be used to amend word-level Thai-English translations. In addition, the word-splitting algorithm improves sentence segmentation, thus enhancing text summarization.