We address the problem of entity identification on a microblog with special attention to indirect reference cases in which entities are not referred to by their names. Most studies on identifying entities referred to them by their full/partial name or abbreviation, while there are many indirectly mentioned entities in microblogs, which are difficult to identify in short text such as microblogs. We therefore tackled indirect reference cases by developing features that are particularly important for certain types of indirect references and modeling dependency among referred entities by a Conditional Random Field (CRF) model. In addition, we model non-sequential order dependency while keeping the inference tractable by dynamically building dependency among entities. The experimental results suggest that our features were effective for indirect references, and our CRF model with adaptive dependency was robust even when there were multiple mentions in a microblog and achieved the same high performance as that with the fully connected CRF model.

A distributive serial multi-bit parallel test scheme for large capacity DRAMs has been developed. The scheme, distributively and serially, extracts and compares the data from cells on a main word-line. This test scheme features a high parallel test bit number, little restriction on test patterns, and, with regard to cells and sense-amplifiers, the same operational margin as normal mode. In an experimental 256-Mb DRAM, the scheme successfully has achieved a 512-bit parallel test.

Assurance cases are documents for arguing that systems satisfy required properties such as safety and security in the given environment based on sufficient evidence. As systems become complex and networked, the importance of assurance cases has become significant. However, we observe that creating assurance cases has some essential difficulties, and unfortunately it seems that assurance cases have not been widely used in industries. For this problem, we have been developing assurance cases creation methods and opening workshops based on the creation methods. This paper presents an assurance cases creation method called “D-Case Steps” which is based on d* framework[1], an agent-based assurance case method, and reports the results of workshops. The results indicate that our workshops have been improved and our activities on assurance cases facilitates use of them in Japan. This paper is an extended version of [2]. We add detailed background and related works, workshops results and evaluation, and lessons learned from our a decade experiences.

An experimental latch circuit is fabricated by using a 0.35µm MT-CMOS technology. This latch circuit has a volume smaller by 30%, a delay time shorter by 10%, and has an active power consumption smaller by 10% over those of a conventional MT-CMOS circuit. Furthermore, at a operation frequency of 100 MHz, an SRAM employing this IPS scheme has a standby current which is 0.4% of SRAM's without using IPS scheme.

This letter describes the architecture and ASIC implementation of the FSP-3 (Flexible Servo motor control Processor-3) chip. The FSP-3 is a special purpose 32 bit microprocessor dedicated to the Flexible Servo Control System (FSC), which is able to manipulate various kinds of servo motors efficiently. FSP-3 chip is one of the largest scale system ASICs entirely designed in Japanese universities.

Recent IDEs have become more extensible tool platforms but do not concern themselves with how other tools running on them collaborate with each other. They compel developers to use proprietary representations or the classical abstract syntax tree (AST) to build source code tools. Although these representations contain sufficient information, they are neither portable nor extensible. This paper proposes a tool platform that manages commonly used, fined-grained, information about Java source code by using an XML representation. Our representation is suitable for developing tools which browse and manipulate actual source code, since the original code is annotated with tags based on its structure and retained within the tags. Additionally, it exposes information resulting from global semantic analysis, which is never provided by the typical AST. Our proposed platform allows the developers to extend the representation for the purpose of sharing or exchanging various kinds of information about the source code, and also enables them to build new tools by using existing XML utilities.

A new shielding evaluation setup for conductive O-rings is proposed. This setup consists of the holder with a groove to fix the O-ring position. There are two ways to apply O-rings in narrow gaps, cylinder-fixing and plane-fixing. With this holder shielding effects of the O-rings can be evaluated from 10 kHz to 1 GHz for both fixing types.

In this study, we generate dialogue contents in which two systems discuss their distress with each other. The user inputs sentences that include environment and feelings of distress. The system generates the dialogue content from the input. In this study, we created dialogue data about distress in order to generate them using deep learning. The generative model fine-tunes the GPT of the pre-trained model using the TransferTransfo method. The contribution of this study is the creation of a conversational dataset using publicly available data. This study used EmpatheticDialogues, an existing empathetic dialogue dataset, and Reddit r/offmychest, a public data set of distress. The models fine-tuned with each data were evaluated both automatically (such as by the BLEU and ROUGE scores) and manually (such as by relevance and empathy) by human assessors.

We propose a method of spread spectrum digital watermarking with quantization index modulation (QIM) and evaluate the method on the basis of IHC evaluation criteria. The spread spectrum technique can make watermarks robust by using spread codes. Since watermarks can have redundancy, messages can be decoded from a degraded stego-image. Under IHC evaluation criteria, it is necessary to decode the messages without the original image. To do so, we propose a method in which watermarks are generated by using the spread spectrum technique and are embedded by QIM. QIM is an embedding method that can decode without an original image. The IHC evaluation criteria include JPEG compression and cropping as attacks. JPEG compression is lossy compression. Therefore, errors occur in watermarks. Since watermarks in stego-images are out of synchronization due to cropping, the position of embedded watermarks may be unclear. Detecting this position is needed while decoding. Therefore, both error correction and synchronization are required for digital watermarking methods. As countermeasures against cropping, the original image is divided into segments to embed watermarks. Moreover, each segment is divided into 8×8 pixel blocks. A watermark is embedded into a DCT coefficient in a block by QIM. To synchronize in decoding, the proposed method uses the correlation between watermarks and spread codes. After synchronization, watermarks are extracted by QIM, and then, messages are estimated from the watermarks. The proposed method was evaluated on the basis of the IHC evaluation criteria. The PSNR had to be higher than 30 dB. Ten 1920×1080 rectangular regions were cropped from each stego-image, and 200-bit messages were decoded from these regions. Their BERs were calculated to assess the tolerance. As a result, the BERs were less than 1.0%, and the average PSNR was 46.70 dB. Therefore, our method achieved a high image quality when using the IHC evaluation criteria. In addition, the proposed method was also evaluated by using StirMark 4.0. As a result, we found that our method has robustness for not only JPEG compression and cropping but also additional noise and Gaussian filtering. Moreover, the method has an advantage in that detection time is small since the synchronization is processed in 8×8 pixel blocks.

In this paper, we propose a fully automatic method for extracting carotid artery contours from ultrasound images based on an active contour approach. Several contour extraction techniques have been proposed to measure carotid artery walls for early detection of atherosclerotic disease. However, the majority of these techniques require a certain degree of user interaction that demands time and effort. Our proposal automatically detects the position of the carotid artery by identifying blood flow information related to the carotid artery, and an active contour model is employed that uses initial contours placed in the detected position. Our method also applies a global energy minimization scheme to the active contour model. Experiments on clinical cases show that the proposed method automatically extracts the carotid artery contours at an accuracy close to that achieved by manual extraction.

A reduction in the intensity deviation of a nine-channel optical frequency comb block (OFCB) is demonstrated, by adopting an asymmetric differential drive method for an InP-based dual drive Mach-Zehnder modulator. The generation of a tailored OFCB with an intensity deviation of less than 0.8dB is confirmed by using the modulator.

Approximate computing is considered as a promising approach to design of power- or area-efficient digital circuits. This paper proposes a systematic methodology for design and worst-case accuracy analysis of approximate array multipliers. Our methodology systematically designs a series of approximate array multipliers with different area, delay, power and accuracy characteristics so that an LSI designer can select the one which best fits to the requirements of her/his applications. Our experiments explore the trade-offs among area, delay, power and accuracy of the approximate multipliers.

The elementary formal system (EFS, for short) is a kind of logic program which directly manipulates character strings. This paper outlines in brief the authors' studies on algorithmic learning theory developed in the framework of EFS's. We define two important classes of EFS's and a new hierarchy of various language classes. Then we discuss EFS's as logic programs. We show that EFS's form a good framework for inductive inference of languages by presenting model inference system for EFS's in Shapiro's sense. Using the framework we also show that inductive inference from positive data and PAC-learning are both much more powerful than they have been believed. We illustrate an application of our theoretical results to Molecular Biology.

We propose an algorithm for finding heavy hitters in terms of cardinality (the number of distinct items in a set) in massive traffic data using a small amount of memory. Examples of such cardinality heavy-hitters are hosts that send large numbers of flows, or hosts that communicate with large numbers of other hosts. Finding these hosts is crucial to the provision of good communication quality because they significantly affect the communications of other hosts via either malicious activities such as worm scans, spam distribution, or botnet control or normal activities such as being a member of a flash crowd or performing peer-to-peer (P2P) communication. To precisely determine the cardinality of a host we need tables of previously seen items for each host (e.g., flow tables for every host) and this may infeasible for a high-speed environment with a massive amount of traffic. In this paper, we use a cardinality estimation algorithm that does not require these tables but needs only a little information called the cardinality summary. This is made possible by relaxing the goal from exact counting to estimation of cardinality. In addition, we propose an algorithm that does not need to maintain the cardinality summary for each host, but only for partitioned addresses of a host. As a result, the required number of tables can be significantly decreased. We evaluated our algorithm using actual backbone traffic data to find the heavy-hitters in the number of flows and estimate the number of these flows. We found that while the accuracy degraded when estimating for hosts with few flows, the algorithm could accurately find the top-100 hosts in terms of the number of flows using a limited-sized memory. In addition, we found that the number of tables required to achieve a pre-defined accuracy increased logarithmically with respect to the total number of hosts, which indicates that our method is applicable for large traffic data for a very large number of hosts. We also introduce an application of our algorithm to anomaly detection. With actual traffic data, our method could successfully detect a sudden network scan.

Recently, many non-traditional applications of Switched-Capacitor circuits have been popularly studied. As one of those applications, we present here a new constructing technique of a Switched-Capacitor Impedance Simulation Circuit (SC-ISC) with unity-gain buffers. Any desired impedance can be obtained by applying this SC-ISC technique. To make up a SC-ISC simply and generally, four kinds of basic constructing Units and two types of feedback circuits are introduced. Furthermore, by applying those Units, an arbitrary transfer function can be easily synthesized. In addition, some algorithms to obtain useful impedances are proposed. Several SC-ISC impedances were experimentally constructed and theoretically analyzed. In particular, some kinds of simple filters and oscillators were made and tested. They were also theoretically analyzed.

The demand for multi-application smart card platform has been increasing in various business sectors recently. When it comes to the actual implementation of the platform, however, network-based dynamic downloading in a Card Issuer-Service Provider separated environment has not made much progress. This paper introduces the smart card information sharing platform that uses licensing/policy/profile management and PKI-based technologies to enable multiple CIs and multiple SPs to reflect their own business policy flexibly via network. It makes the paradigm shift from card-oriented scheme to service-oriented scheme. By through world's first implementation of the scheme and some experiments including deployment, we confirmed that this technology is well-accepted and applicable to various business sectors and it can be of practical use.

This paper proposes a method of designing EM absorber panels under oblique incident waves. TM and TE wave reflection characteristics of the absorber panel show its anisotropy under oblique incidence. By using the wire array sheet proposed this paper, TM and TE reflection coefficients in oblique incidence can be matched at almost the same frequency range.

A light, thin and flexible applicator using a microstrip patch array for microwave heating is presented and tested in this work. The applicator is made of a flat silicone rubber bag, inside of which flows cooling water. EM coupling feeding is applied, which has no direct contact between the feed and the patch, to improve durability and reliability when it is repeatedly applied to the uneven surface of the heated portion of the human body. Simulations of SAR distribution are performed using the finite difference time domain (FD-TD) method. Simulated data are compared with the experimental ones using cubic and cylindrical phantom models with single and multielement patch applicators. Simulations of temperature distribution are also performed using the heat transfer equation. Simulated data are compared with the experimental ones using cubic and cylindrical phantom models. The simulated results agree well with the experimental ones. The results obtained here show that the multielement flexible microstrip patch applicator which operates at 430MHz can heat a relatively shallow and widespread area on the human body for hyperthermia treatments.

Object-oriented analysis methods can be grouped into data-driven and behavior-driven approaches. With data-driven approaches, object models are developed based on a list of objects and their inter-relationships, which describe a static view of the real world. With behavior-oriented approaches, a system usage scenario is analyzed before developing the object models. Although qualitative comparisons of these two types of methods have been made, there was no statistical study has evaluated them based on controlled experiments. This paper proposes the patterned object-oriented method, POOM, which is a behavior-oriented approach, and compares it to OMT, a data-driven approach, using small team experiments. The effectiveness of POOM is shown in terms of productivity and homogeneity.