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 propose an augmented-reality-based method for arranging furniture using natural markers extracted from the edges of the walls of rooms. The proposed method extracts natural markers and estimates the camera parameters from single images of rooms using deep neural networks. Experimental results show that in all the measurements, the superimposition error of the proposed method was lower than that of general marker-based methods that use practical-sized markers.

For insertion and deletion channels, there are many coding schemes based on low-density parity-check (LDPC) codes, such as spatially coupled (SC) LDPC codes and concatenated codes of irregular LDPC codes and markers. However, most of the previous works have problems, such as poor finite-length performance and unrealistic settings for codeword lengths and decoding iterations. Moreover, when using markers, the decoder receives log-likelihood (LLR) messages with different statistics depending on code bit position. In this paper, we propose a novel concatenation scheme using protograph-based LDPC code and markers that offers excellent asymptotic/finite-length performance and a structure that controls the irregularity of LLR messages. We also present a density evolution analysis and a simple optimization procedure for the proposed concatenated coding scheme. For two decoding scenarios involving decoding complexity, both asymptotic decoding thresholds and finite-length performance demonstrate that the newly designed concatenated coding scheme outperforms the existing counterparts: the irregular LDPC code with markers, the SC-LDPC code, and the protograph LDPC code, which is optimized for an additive white Gaussian noise channel, with markers.

In this paper, we propose a method of embedding and detecting data in printed images with several formats, such as different resolutions and numbers of blocks, using the camera of a tablet device. To specify the resolution of an image and the number of blocks, invisible markers that are embedded in the amplitude domain of the discrete Fourier transform of the target image are used. The proposed method can increase the variety of images suitable for data embedding.

We present a novel method to enable users to experience mobile interaction with digital content on external displays by embedding markers imperceptibly on the screen. Our method consists of two parts: marker embedding on external displays and marker detection. To embed markers, similar to previous work, we display complementary colors in alternating frames, which are selected by considering L*a*b color space in order to make the markers harder for humans to detect. Our marker detection process does not require mobile devices to be synchronized with the display, while certain constraints for the relation between camera and display update rate need to be fulfilled. In this paper, we have conducted three experiments. The results show 1) selecting complementary colors in the a*b* color plane maximizes imperceptibility, 2) our method is extremely robust when used with static contents and can handle animated contents up to certain optical flow levels, and 3) our method was proved to work well in case of small movements, but large movements can lead to loss of tracking.

In this paper, we propose improved methods of liquid-phase detection of biological targets utilizing magnetic markers and a high-critical-temperature superconducting quantum interference device (SQUID). For liquid-phase detection, the bound and unbound (free) markers are magnetically distinguished by using Brownian relaxation of free markers. Although a signal from the free markers is zero in an ideal case, it exists in a real sample on account of the aggregation and precipitation of free markers. This signal is called a blank signal, and it degrades the sensitivity of target detection. To solve this problem, we propose improved detection methods. First, we introduce a reaction field, Bre, during the binding reaction between the markers and targets. We additionally introduce a dispersion process after magnetization of the bound markers. Using these methods, we can obtain a strong signal from the bound markers without increasing the aggregation of the free markers. Next, we introduce a field-reversal method in the measurement procedure to differentiate the signal from the markers in suspension from that of the precipitated markers. Using this procedure, we can eliminate the signal from the precipitated markers. Then, we detect biotin molecules by using these methods. In an experiment, the biotins were immobilized on the surfaces of large polymer beads with diameters of 3.3 µm. They were detected with streptavidin-conjugated magnetic markers. The minimum detectable molecular number concentration was 1.8×10-19 mol/ml, which indicates the high sensitivity of the proposed method.

This paper proposes an adaptive marker coding (AMC) for correction of insertion/deletion/substitution errors. Unlike the conventional marker codings which select marker-bit values deterministically, the AMC adaptively reverses the first and last bits of each marker as well as bits surrounding the marker. Decoding is based on a forward-backward algorithm which takes into account the dependency of bit-values around the marker. Evaluation shows that, for a channel with insertion/deletion error probability 1.8×10-2, the decoded BER of existing marker coding of rate 9/16 is 4.25×10-3, while that of the proposed coding with the same code rate is 1.73×10-3.

Liquid-phase detection of biological targets utilizing magnetic marker and superconducting quantum interference device (SQUID) magnetometer is shown. In this method, magnetic markers are coupled to the biological targets, and the binding reaction between them is detected by measuring the magnetic signal from the bound markers. Detection can be done in the liquid phase, i.e., we can detect only the bound markers even in the presence of unbound (free) markers. Since the detection principle is based on the different magnetic properties between the free and bound markers, we clarified the Brownian relaxation of the free markers and the Neel relaxation of the bound markers. Usefulness of the present method is demonstrated from the detection of the biological targets, such as biotin-coated polymer beads, IgE and Candida albicans.

Augmented reality tasks require a high-reliability tracking method. Large tracking error causes many problems during AR applications. Tracking error estimation should be integrated with them to improve the reliability of tracking methods. Although some tracking error estimation methods have been developed, they are not feasible to be integrated because of computational speed and accuracy. For this study, a tracking error estimation algorithm with screen error estimation based on the characteristic of linecode marker was applied. It can rapidly estimate tracking error. An evaluation experiment was conducted to compare the estimated tracking error and the actual measured tracking error. Results show that the algorithm is reliable and sufficiently fast to be used for real-time tracking error warning or tracking accuracy improvement methods.

Dividing a lecture speech into segments and providing those segments as learning objects are quite general and convenient way to construct e-learning resources. However it is difficult to assign an appropriate title to each object that reflects its content. Since there are various aspects of analyzing discourse segments, it is inevitable that researchers will face the diversity when describing the "meanings" of discourse segments. In this paper, we propose the assignment of discourse segment titles from the representation of their "meanings." In this assigning procedure, we focus on the speaker's evaluation for the event or the speech object. To verify the effectiveness of our idea, we examined identification of the segment boundaries from the titles that were described in our procedure. We confirmed that the result of the identification was more accurate than that of intuitive identification.

Nuclear power plants (NPPs) must be maintained periodically. Their maintenance efficiency must be improved and human error must be reduced simultaneously to improve NPPs' competitive capability in electricity markets. Although Augmented Reality (AR) offers great possibilities to support NPP maintenance work, some difficulties exist for application of AR to actual work support because current AR systems cannot be implemented in NPP environments without technical improvement. There are several kinds of problems such as recognition distance, tracking accuracy, and a complex working environment when applying AR to NPP field work support. Considerable extension of tracking distance and improvement of accuracy are particularly desired because NPPs are large-scale indoor environments. This study designed a linecode marker, a new type of paper-based marker, along with recognition and tracking algorithms for it to resolve these problems. In contrast to conventional paper-based markers, such as square markers and circle markers, the linecode marker is not merely easier to set up in complex industrial environments: it also enables the use of AR in industrial plants because of its considerable tracking-performance improvement. To evaluate tracking accuracy, the trackable distance, and the tracking speed of the proposed tracking method, an evaluation experiment was conducted in a large room. The experiment results show that the tracking distance is extended extremely over that of the traditional marker-based tracking method: tracking accuracy improved to 20 cm over a 10 m distance. The running speed of the tracking can be as fast as 15 frames per second using a laptop PC.

Traffic markers differentiate among packets from senders based on their service profile in the differentiated service networks. Researchers have previously revealed that the existing marking mechanism causes the unfairness in aggregates. This study presents a new marking algorithm. Simulation results demonstrate that the fairness of the proposed scheme exceeds that of SRTCM, TRTCM, TSWTCM and ITSWTCM for medium to high network provision levels.

Magnetic immunoassays utilizing magnetic marker and high Tc superconducting quantum interference device (SQUID) have been performed. In this magnetic method, binding-reaction between an antigen and its antibody is detected by measuring the magnetic field from the magnetic marker. First, we discuss the magnetic property of the marker, and show that Fe3O4 particles with diameter of 25 nm can be used for remanence measurement. We also show a design of the SQUID for sensitive detection of the magnetic signal from the marker. Next, we developed a measurement system utilizing the SQUID and a reaction chamber with very low magnetic contamination. Finally, we conducted an experiment on the detection of the biological materials called IL8 and IgE. At present, a few atto-mol of IL8 and IgE has been detected, which shows the high sensitivity of the present method.

This paper presents a new template matching method based on marker-controlled watershed segmentation (TMCWS). It is applied to recognize numbers on special metal plates in production lines where traditional image recognition methods do not work well. TMCWS is a shape based matching method that uses different pattern images and their corresponding marker images as probes to explore a gradient space of an unknown image to determine which pattern best matches a target object in it. Different from other matching algorithms, TMCWS firstly creates a marker image for each pattern, and then takes both the pattern image and its corresponding marker image as a template window and shifts this window across a gradient space pixel by pixel to do a search. At each position, the marker image is used to try to extract the contour of the target object with the help of marker-controlled watershed segmentation, and the pattern image is employed to evaluate the extracted shape in each trial. All of the pattern images and their corresponding marker images are tried and the pattern that best matches the target object is the recognition result. TMCWS contains shape extraction procedures and it is a high-level template matching method. Experiments are performed with this method on nearly 400 images of metal plates and the test results show its effectiveness in recognizing numbers in noisy images.

The differentiated services (DiffServ) architecture is proposed to provide a service differentiation between traffic classes or behavior aggregates in a scalable manner. A key functional element to deploy DiffServ is traffic conditioning, more specifically traffic marker. This paper proposes an adaptive and aggregated traffic marker embodying the functions: (1) inter-connect two-rate three color markers (trTCMs), (2) estimate the aggregate rate of Assured Forwarding (AF) classes, and (3) re-mark the some parts of excessive portion of assigned link-rate per AF class queue with some down-grading probability to lower AF class. Both analysis and simulations are used to evaluate the performance of the proposed aggregate-traffic marker. The analysis of the proposed marker shows its clear service differentiation among behavior aggregates (BAs) under different traffic load conditions. Also a performance evaluation is performed through network simulation with more realistic traffics as unbalanced intensities among different BAs. Shortly, our proposed aggregate-traffic marker enables to keep the priority orders in terms of loss rate and delay/jitter among BAs in spites of varying and unbalanced traffic intensities.

A high-speed context-free marker controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make high speed marker-controlled watershed possible without over-segmentation and region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of the marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detect and segment multiple objects from a complex background while reducing the over-segmentation and computation time.

A high Tc superconducting quantum interference device (SQUID) magnetometer system is developed for the application to biological immunoassay. In this application, magnetic nanoparticles are used as magnetic markers to perform immunoassay, i.e., to detect binding reaction between an antigen and its antibody. The antibody is labeled with γ-Fe2O3 nanoparticles, and the binding reaction can be magnetically detected by measuring the magnetic field from the nanoparticles. Design and set up of the system is described, and the sensitivity of the system is studied in terms of detectable number of the magnetic markers. At present, we can detect 4106 markers when the diameter of the marker is 50 nm. Total weight of the magnetic nanoparticles becomes 520 pg in this case. An experiment is also conducted to measure antigen-antibody reaction with the present system. It is shown that the sensitivity of the present system is 10 times better than that of the conventional method using an optical marker. A one order of magnitude improvement of sensitivity will be realized by the sophistication of the present system.

This paper presents an algorithm for viewpoint-based similarity discernment of linguistic concepts on Semantic Network Array Processor (SNAP). The viewpoint-based similarity discernment plays a key role in retrieving similar propositions. This is useful for advanced knowledge processing areas such as analogical reasoning and case-based reasoning. The algorithm assumes that a knowledge base is constructed for SNAP, based on information acquired from the WordNet linguistic database. The algorithm identifies paths on the knowledge base between each given concept and a given viewpoint concept, then computes a similarity degree between the two concepts based on the number of nodes shared by the paths. A small scale knowledge base was constructed and an experiment was conducted on a SNAP simulator that demonstrated the feasibility of this algorithm. Because of SNAP's scalability, the algorithm is expected to work similarly on a large scale knowledge base.

In the ITS (Intelligent Transport Systems), it is an essential condition (mixed environment) that vehicles that have communication equipment and vehicles that do not have it simultaneously run in the same road. In this paper, a vehicular driving assistant system that is applicable to the mixed environment is proposed. The proposed system uses spread spectrum techniques and consists of several new systems such as a PN code assignment system, new vehicle position systems, and a vehicle map update system. In the proposed system, the wireless broadcast CDMA is used for inter-vehicle communications. This paper also shows preexaminations of the proposed system by using an autonomous traffic flow simulator including inter-vehicle communications. It is shown that the traffic safety can be improved by using inter-vehicle communications.

This paper introduces a probabilistic rebound automaton (pra), and investigates its accepting power and closure property. We show that (1) the class of languages recognized by pra's with error probability less than 1/2, PRA, is incomparable with the class of context-free languages, (2) there is a language accepted by a two-way nondeterministic one counter automaton, but not in PRA, and (3) there is a language accepted by a deterministic one-marker rebound automaton, but not in PRA. We also show that PRA is not closed under concatenation and Kleene + .