Program comprehension using dynamic information is one of key tasks of software maintenance. Software visualization with sequence diagrams is a promising technique to help developer comprehend the behavior of object-oriented systems effectively. There are many tools that can support automatic generation of a sequence diagram from execution traces. However it is still difficult to understand the behavior because the size of automatically generated sequence diagrams from the massive amounts of execution traces tends to be beyond developer's capacity. In this paper, we propose an execution trace slicing and visualization method. Our proposed method is capable of slice calculation based on a behavior model which can treat dependencies based on static and dynamic analysis and supports for various programs including exceptions and multi-threading. We also introduce our tool that perform our proposed slice calculation on the Eclipse platform. We show the applicability of our proposed method by applying the tool to two Java programs as case studies. As a result, we confirm effectiveness of our proposed method for understanding the behavior of object-oriented systems.

We study the correspondence between problem descriptions and requirements specification documents derived from them. Based on the results of this investigation, a model that integrates the problem space and the requirements specification space is developed. This integration is based on a semantic network representation. We also propose a model of the requirements elicitation process that is consistent with our empirical studies of traceability in requirements documents. In this process, analysts derived requirements specifications from incomplete and ambiguous problem descriptions given by customers, identify missing information, completed it, and then decide the system boundaries that define which part of the problem descriptions to implement as the target system. The model can be used to complete problem descriptions given by customers and determine the system boundaries.

Inductive Logic Programming (ILP) is a study of machine learning systems that use clausal theories in first-order logic as a representation language. In this paper, we survey theoretical foundations of ILP from the viewpoints of Logic of Discovery and Machine Learning, and try to unify these two views with the support of the modern theory of Logic Programming. Firstly, we define several hypothesis construction methods in ILP and give their proof-theoretic foundations by treating them as a procedure which complets incomplete proofs. Next, we discuss the design of individual learning algorithms using these hypothesis construction methods. We review known results on learning logic programs in computational learning theory, and show that these algorithms are instances of a generic learning strategy with proof completion methods.

We describe an index for estimating the level of interest in Web pages. This "time-based interest" (TBI) index combinates an equation reflecting page accesses and an equation reflecting the decrease in interest over time. These equations work simultaneously by using a parameter that is based on the time since the last access. We experimentally estimated the decrease ratio of the TBI index and evaluated the characteristics of the TBI equation. We found that the index follows Zipf's distribution, indicating that reflects the change in popularity. We also introduce an access-log analysis system called CyberRanking that includes TBI analysis. CyberRanking analyzes the access logs of Web servers and presents the results in 2-D or 3-D graph on a Web browser.

In this paper, we propose two methods of digital watermark for image signals based on the wavelet transform. We classify wavelet coefficients as insignificant or significant by using zerotree which is defined in the embedded zerotree wavelet (EZW) algorithm . In the first method, information data are embedded as watermark in the location of insignificant coefficients. In the second method, information data can be embedded by thresholding and modifying significant coefficients at the coarser scales in perceptually important spectral components of image signals. Information data are detected by using the position of zerotree's root and the threshold value after the wavelet decomposition of an image in which data hide. It is shown from the numerical experiments that the proposed methods can extract the watermark from images that have degraded through several common signal and geometric processing procedures.

This paper proposes a traffic-adaptive dynamic routing method, which we have named RAG, for connectionless packet networks. Conventional traffic control methods discard the packets which cause congestion. Furthermore, conventional routing methods propagate control messages all over the network for gathering global topology information, and this causes more congestion. In contrast, RAG estimates traffic conditions all over a network without any communication between nodes and makes the best use of free links so that packets make detours to avoid congestive sites. RAG adopts distributed control based on game theory (non-communication, non-zero-sum, two-person). With RAG, nodes play a packet-forwarding game without any communication with each other, and each node controls ordering and routing of the forwarding packets based on the node's individual payoff table which is dynamically reconstructed by observation of surrounding nodes. Nodes cooperate with each other, except for punishment for disloyalty. Repetition of these local operations in nodes aims at the emergence of the gradual network-global traffic balancing. The results of experiments in comparison with the conventional shortest path first (SPF) routing method show that the throughput is about 1.58 times higher with the new method.

In this paper, an evaluation method for electromagnetic wave absorber with anisotropic reflection properties is discussed. Anisotropic absorber panels have an axis of anisotropy (principal axis). In order to specify the principal axis, the evaluation method based on the diagonalization of reflection coefficient matrix is used. Also, the permittivity of absorber materials is considered.

The traceability of data flow diagrams against structure charts is very important for large software development. Specifying if there is a relationship between a data flow diagram and a structure chart is a time consuming task. Existing CASE tools provide a way to maintain traceability. If we can extract the input-output relationship of a system from a structure chart, the corresponding data flow diagram can be automatically generated from the relationship. For example, Benedusi et al. proposed a reverse engineering methodology to reconstruct a data flow diagram from existing code. The methodology develops a hierarchical data flow diagram from dependency relationships between the program variables. The methodology, however, transforms each module in structure charts into a process in data flow diagrams. The reconstructed diagrams may have different processes with the same name. This paper proposes a transformation algorithm that solves these problems. It analyzes the structure charts and extracts the input and ouput relationships, then determines how the set of outputs depends on the set of inputs for the data flow diagram process. After that, it produces a data flow diagram based on the include operation between the sets of output items. The major characteristics of the algorithm are that it is simple, because it only uses the basic operations of sets, it generates data flow diagrams with deterministic steps, and it can generate minimal data flow diagrams. This process will reduce the cost of traceability between data flow diagrams and structure charts.

We present a privacy preserving method based on inserting dummy data into original data on the data structure called Zero-suppressed BDDs (ZDDs). Our task is distributed itemset mining, which is frequent itemset mining from horizontally partitioned databases stored in distributed places called sites. We focus on the fundamental case in which there are two sites and each site has a database managed by its owner. By dividing the process of distributed itemset mining into the set union and the set intersection, we show how to make the operations secure in the sense of undistinguishability of data, which is our criterion for privacy preserving based on the already proposed criterion, p-indistinguishability. Our method conceals the original data in each operation by inserting dummy data, where ZDDs, BDD-based directed acyclic graphs, are adopted to represent sets of itemsets compactly and to implement the set operations in constructing the distributed itemset mining process. As far as we know, this is the first technique which gives a concrete representation of sets of itemsets and an implementation of set operations for privacy preserving in distributed itemset mining. Our experiments show that the proposed method provides undistinguishability of dummy data. Furthermore, we compare our method with Secure Multiparty Computation (SMC), which is one of the well-known techniques of secure computation.

It is important to collect and spread accurate information quickly during disasters. Therefore, utilizing Twitter at the time of accidents has been gaining attention in recent year. In this paper, we propose a real-time information sharing system during disaster based on the utilization of Twitter. The proposed system consists of two sub-systems, a disaster information tweeting system that automatically attaches user's current geo-location information (address) and the hashtag of the form “#(municipality name) disaster,” and a disaster information mapping system that displays neighboring disaster-related tweets on a map.

There is increasing demand for corporate information systems that have a simple human interface and are easy to access via WWW browsers. This paper proposes WebBASE, which integrates the WWW and relational databases. Experimental evaluation shows that WebBASE offers superior performance compared to existing products. Field studies of actual WebBASE applications show that it can improve the productivity of software developers for intranet application development.

We propose requirement validation criteria and a method based on the interaction between actors in an information system. We focus on the cyclical transitions of one actor's situation against another and clarify observable stimuli and responses based on these transitions. Both actors' situations can be listed in a state transition table, which describes the observable stimuli or responses they send or receive. Examination of the interaction between both actors in the state transition tables enables us to detect missing or defective observable stimuli or responses. Typically, this method can be applied to the examination of the interaction between a resource managed by the information system and its user. As a case study, we analyzed 332 requirement defect reports of an actual system development project in Japan. We found that there were a certain amount of defects regarding missing or defective stimuli and responses, which can be detected using our proposed method if this method is used in the requirement definition phase. This means that we can reach a more complete requirement definition with our proposed method.

In this paper we investigate the learnability of relations in Inductive Logic Programming, by using equality theories as background knowledge. We assume that a hypothesis and an observation are respectively a definite program and a set of ground literals. The targets of our learning algorithm are relations. By using equality theories as background knowledge we introduce tree structure into definite programs. The structure enable us to narrow the search space of hypothesis. We give pairs of a hypothesis language and a knowledge language in order to discuss the learnability of relations from the view point of inductive inference and PAC learning.

There is currently much interest in the development of Optic Wireless and Visible Light Communication (VLC) systems in the ITS field. Research in VLC and boomerang systems in particular often remain at a theoretical or computer-simulated level. This paper reports the 3-stage development of a boomerang prototype communication and ranging system using visible light V2V communication via LEDs and photodiodes, with direct-sequence spread spectrum techniques. The system uses simple and widely available components aiming for a low-cost frugal innovation approach. Results show that while we have to improve the prototype distance measurement unit due to a margin of error, simultaneous communication and ranging is possible with our newly designed prototype. The benefits of further research and development of boomerang technology prototypes are confirmed.

In this paper, we present a method of analyzing relationships between items in specific health examination data, as one of the basic researches to address increases of lifestyle-related diseases. We use self-organizing maps, and pick up the data from the examination dataset according to the condition specified by some item values. We then focus on twelve items such as hemoglobin A1c (HbA1c), aspartate transaminase (AST), alanine transaminase (ALT), gamma-glutamyl transpeptidase (γ-GTP), and triglyceride (TG). We generate training data presented to a map by calculating the difference between item values associated with successive two years and normalizing the values of this calculation. We label neurons in the map on condition that one of the item values of training data is employed as a parameter. We finally examine the relationships between items by comparing results of labeling (clusters formed in the map) to each other. From experimental results, we separately reveal the relationships among HbA1c, AST, ALT, γ-GTP and TG in the unfavorable case of HbA1c value increasing and those in the favorable case of HbA1c value decreasing.

Recently, broadband wireless communication has been significantly enhanced; thus, frequency spectrum scarcity has become an extremely serious problem. Spatial frequency reuse based on spectrum databases has attracted significant attention. The spectrum database collects wireless environment information, such as the radio signal strength indicator (RSSI), estimates the propagation coefficient for the propagation loss and shadow effect, and finds a vacant area where the secondary system uses the frequency spectrum without harmful interference to the primary system. Wireless sensor networks are required to collect the RSSI from a radio environmental monitor. However, a large number of RSSI values should be gathered because numerous sensors are spread over the wireless environment. In this study, a data compression technique based on spatial features, such as buildings and houses, is proposed. Using computer simulation and experimental evaluation, we confirm that the proposed compression method successfully reduces the size of the RSSI and restores the original RSSI in the recovery process.

Effects of field edge steps on characteristics of MOSFETs with tungsten polycide stacked gate electrodes patterned by KrF excimer laser lithography was studied through an electrical gate length measurement technique. Sheet resistance of the gate electrodes on the field oxide, on the active region and across the field edge steps was determined from the relationship between gate conductance and designed gate linewidth. The sheet resistance of the gate electrode across the field edge steps was larger than that on the flat regions. Effects of field edge steps on gate linewidth variation were evaluated by SEM observations and electrical measurements. Distribution of gate linewidth in a wafer was measured by the MOSFET test structures with the linewidth down to sub-quarter micron. Gate linewidth variation near the field edge steps was found to influence the short channel MOSFET characteristics.

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.

We propose a fully automatic method for detecting the carotid artery from volumetric ultrasound images as a preprocessing stage for building three-dimensional images of the structure of the carotid artery. The proposed detector utilizes support vector machine classifiers to discriminate between carotid artery images and non-carotid artery images using two kinds of LBP-based features. The detector switches between these features depending on the anatomical position along the carotid artery. We evaluate our proposed method using actual clinical cases. Accuracies of detection are 100%, 87.5% and 68.8% for the common carotid artery, internal carotid artery, and external carotid artery sections, respectively.

Normally, flow field is described with governing equations, such as the Navier-Stokes equations. However, for complex flow including multiphase and reactive flow such as combustion, this approach may not be suitable. As an alternative approach, Lattice Gas Automata (LGA) has been used to simulate fluid with mesoscopic particles by assuming that space and time are discrete, and the physical quantities take only a finite set of values. In this study, the model for combustion simulation is proposed, with the reaction probability depending on the local temperature to simplify the chemical reaction. Here, counter-flow twin flames are simulated. In order to validate this approach, some results of non-reactive flow are presented, compared with those by solving Navier-Stokes equations.