We present an interactive modeling system for Japanese castles. We develop an user interface that can generate the fundamental structure of the castle tower consisting of stone walls, turrets, and roofs. By clicking on the screen displaying the 3D space with the mouse, relevant parameters are calculated automatically to generate 3D models of Japanese-style castles. We use characteristic curves that often appear in ancient Japanese architecture for the realistic modeling of the castles. We evaluate the effectiveness of our method by comparing the castle generated by our method with a commercially-available 3D mode of a castle.

We investigate an interactive evolutionary computation (IEC) using multiple users' gaze information when users partially participate in each design evaluation. Many previous IEC systems have a problem that user evaluation loads are too large. Hence, we proposed to employ user gaze information for evaluating designs generated by IEC systems in order to solve this problem. In this proposed system, users just view the presented designs, not assess, then the system automatically creates users' favorite designs. With the user's gaze information, the proposed system generates coordination that can satisfy many users. In our previous study, we verified the effectiveness of the proposed system from a real system operation viewpoint. However, we did not consider the fluctuation of the users during a solution candidate evaluation. In the actual operation of the proposed system, users may change during the process due to the user interchange. Therefore, in this study, we verify the effectiveness of the proposed system when varying the users participating in each evaluation for each generation. In the experiment, we employ two types of situations as assumed in real environments. The first situation changes the number of users evaluating the designs for each generation. The second situation employs various users from the predefined population to evaluate the designs for each generation. From the experimental results in the first situation, we confirm that, despite the change in the number of users during the solution candidate evaluation, the proposed system can generate coordination to satisfy many users. Also, from the results in the second situation, we verify that the proposed system can also generate coordination which both users who participate in the coordination evaluation can more satisfy.

In the context of Web 2.0, the interaction between users and resources is more and more frequent in the process of resource sharing and consumption. However, the current research on resource pricing mainly focuses on the attributes of the resource itself, and does not weigh the interests of the resource sharing participants. In order to deal with these problems, the pricing mechanism of resource-user interaction evaluation based on multi-agent game theory is established in this paper. Moreover, the user similarity, the evaluation bias based on link analysis and punishment of academic group cheating are also included in the model. Based on the data of 181 scholars and 509 articles from the Wanfang database, this paper conducts 5483 pricing experiments for 13 months, and the results show that this model is more effective than other pricing models - the pricing accuracy of resource resources is 94.2%, and the accuracy of user value evaluation is 96.4%. Besides, this model can intuitively show the relationship within users and within resources. The case study also exhibits that the user's knowledge level is not positively correlated with his or her authority. Discovering and punishing academic group cheating is conducive to objectively evaluating researchers and resources. The pricing mechanism of scientific and technological resources and the users proposed in this paper is the premise of fair trade of scientific and technological resources.

Connected services have been under development in the automotive industry. Meanwhile, the volume of predictive notifications that utilize travel-related data is increasing, and there are concerns that drivers cannot process such an amount of information or do not accept and follow such predictive instructions straightforwardly because the information provided is predicted. In this work, an interactive voice system using two agents is proposed to realize notifications that can easily be accepted by drivers and enhance the reliability of the system by adding contextual information. An experiment was performed using a driving simulator to compare the following three forms of notifications: (1) notification with no contextual information, (2) notification with contextual information using one agent, and (3) notification with contextual information using two agents. The notification content was limited to probable near-miss incidents. The results of the experiment indicate that the driver may decelerate more with the one- and two-agent notification methods than with the conventional notification method. The degree of deceleration depended the number of times the notification was provided and whether there were cars parked on the streets.

Collecting and analyzing personal data is important in modern information applications. Though the privacy of data providers should be protected, the need to track certain data providers often arises, such as tracing specific patients or adversarial users. Thus, tracking only specific persons without revealing normal users' identities is quite important for operating information systems using personal data. It is difficult to know in advance the rules for specifying the necessity of tracking since the rules are derived by the analysis of collected data. Thus, it would be useful to provide a general way that can employ any data analysis method regardless of the type of data and the nature of the rules. In this paper, we propose a privacy-preserving data analysis construction that allows an authority to detect specific users while other honest users are kept anonymous. By using the cryptographic techniques of group signatures with message-dependent opening (GS-MDO) and public key encryption with non-interactive opening (PKENO), we provide a correspondence table that links a user and data in a secure way, and we can employ any anonymization technique and data analysis method. It is particularly worth noting that no “big brother” exists, meaning that no single entity can identify users who do not provide anomaly data, while bad behaviors are always traceable. We show the result of implementing our construction. Briefly, the overhead of our construction is on the order of 10 ms for a single thread. We also confirm the efficiency of our construction by using a real-world dataset.

Goal modeling is a method that describes requirements structurally. Goal modeling mainly consists of two tasks: extraction of goals and organization of the extracted goals. Generally, the process of the goal modeling requires intensive manual intervention and higher modeling skills than the process of the usual requirements description. In order to mitigate this problem, we propose a method that provides systematic supports for constructing goal models. In the method, the requirement analyst answers questions and a goal model is semi-automatically constructed based on the answers made. We develop a prototype tool that implements the proposed method and apply it to two systems. The results demonstrate the feasibility of the method.

This paper proposes a visual analytics (VA) interface for time-series data so that it can solve the problems arising from the property of time-series data: a collision between interaction and animation on the temporal aspect, collision of interaction between the temporal and spatial aspects, and the trade-off of exploration accuracy, efficiency, and scalability between different visualization methods. To solve these problems, this paper proposes a VA interface that can handle temporal and spatial changes uniformly. Trajectories can show temporal changes spatially, of which direct manipulation enables to examine the relationship among objects either at a certain time point or throughout the entire time range. The usefulness of the proposed interface is demonstrated through experiments.

In a large-scale information-sharing platform, such as a cloud storage, it is often required to not only securely protect sensitive information but also recover it in a reliable manner. Public-key encryption with non-interactive opening (PKENO) is considered as a suitable cryptographic tool for this requirement. This primitive is an extension of public-key encryption which enables a receiver to provide a non-interactive proof which confirms that a given ciphertext is decrypted to some public plaintext. In this paper, we present a Tag-KEM/DEM framework for PKENO. In particular, we define a new cryptographic primitive called a Tag-KEM with non-interactive opening (Tag-KEMNO), and prove the KEM/DEM composition theorem for this primitives, which ensures a key encapsulation mechanism (KEM) and a data encapsulation mechanism (DEM) can be, under certain conditions, combined to form a secure PKENO scheme. This theorem provides a secure way of combining a Tag-KEMNO scheme with a DEM scheme to construct a secure PKENO scheme. Using this framework, we explain the essence of existing constructions of PKENO. Furthermore, we present four constructions of Tag-KEMNO, which yields four PKENO constructions. These PKENO constructions coincide with the existing constructions, thereby we explain the essence of these existing constructions. In addition, our Tag-KEMNO framework enables us to expand the plaintext space of a PKENO scheme. Some of the previous PKENO schemes are only able to encrypt a plaintext of restricted length, and there has been no known way to expand this restricted plaintext space to the space of arbitrary-length plaintexts. Using our framework, we can obtain a PKENO scheme with the unbounded-length plaintext space by modifying and adapting such a PKENO scheme with a bounded-length plaintext space.

This paper proposes a classification method of second-language-learner utterances for interactive computer-assisted language learning systems. This classification method uses three types of bilingual evaluation understudy (BLEU) scores as features for a classifier. The three BLEU scores are calculated in accordance with three subsets of a learner corpus divided according to the quality of utterances. For the purpose of overcoming the data-sparseness problem, this classification method uses the BLEU scores calculated using a mixture of word and part-of-speech (POS)-tag sequences converted from word sequences based on a POS-replacement rule according to which words are replaced with POS tags in n-grams. Experiments of classifying English utterances by Japanese demonstrated that the proposed classification method achieved classification accuracy of 78.2% which was 12.3 points higher than a baseline with one BLEU score.

This paper proposes a painterly morphing algorithm for mobile smart devices, where each frame in the morphing sequence looks like an oil-painted picture with brush strokes. It can be presented, for example, during the transition between the main screen and a specific application screen. For this, a novel dissimilarity function and acceleration data structures are developed. The experimental results show that the algorithm produces visually stunning effects at an interactive time.

This paper presents an interactive locomotion controller using motion capture data and an inverted pendulum model (IPM). The motion data of a character is decomposed into those of upper and lower bodies, which are then dimension-reduced via what we call hierarchical Gaussian process dynamical model (H-GPDM). The locomotion controller receives the desired walking direction from the user. It is integrated into the IPM to determine the pose of the center of mass and the stance-foot position of the character. They are input to the H-GPDM, which interpolates the low-dimensional data to synthesise a redirected motion sequence on an uneven surface. The locomotion controller allows the upper and lower bodies to be independently controlled and helps us generate natural locomotion. It can be used in various real-time applications such as games.

We developed a system called DELTA that supports the students' use of backward chaining (BC) to prove the congruence of two triangles. DELTA is designed as an interactive learning environment and supports the use of BC by providing hints and a function to automatically check the proofs inputted by the students. DELTA also has coloring, marking, and highlighting functions to support students' attempts to prove the congruence of two triangles. We evaluated the efficacy of DELTA with 36 students in the second grade of a junior high school in Japan. We found that (1) the mean number of problems, which the experimental group (EG) completely solved, was statistically higher than that of the control group on the post-test; (2) the EG effectively used the BC strategy to solve problems; and (3) the students' attempt to use both the forward chaining strategy and the BC strategy led to solving the problems completely.

Group signatures are a class of digital signatures with enhanced privacy. By using this type of signature, a user can sign a message on behalf of a specific group without revealing his identity, but in the case of a dispute, an authority can expose the identity of the signer. However, it is not always the case that we need to know the specific identity of a signature. In this paper, we propose the notion of deniable group signatures, where the authority can issue a proof showing that the specified user is NOT the signer of a signature, without revealing the actual signer. We point out that existing efficient non-interactive zero-knowledge proof systems cannot be straightforwardly applied to prove such a statement. We circumvent this problem by giving a fairly practical construction through extending the Groth group signature scheme (ASIACRYPT 2007). In particular, a denial proof in our scheme consists of 96 group elements, which is about twice the size of a signature in the Groth scheme. The proposed scheme is provably secure under the same assumptions as those of the Groth scheme.

Non-Interactive Key Exchange (NIKE) is a cryptographic primitive that allows two users to compute a shared key without any interaction. The Diffie-Hellman key exchange scheme is probably the most well-known example of a NIKE scheme. Freire et al. (PKC 2013) defined four security notions for NIKE schemes, and showed implications among them. In these notions, we consider an adversary that is challenged to distinguish a shared key of a new pair of users from a random value, using only its knowledge of keys shared between other pairs of users. To take into account side-channel attacks such as tampering and fault-injection attacks, Bellare and Kohno (Eurocrypt 2003) formalized related-key attacks (RKA), where stronger adversaries are considered. In this paper, we introduce four RKA security notions for NIKE schemes. In these notions, we consider an adversary that can also manipulate the secret keys of users and obtain shared keys computed under the modified secret keys. We also show implications and separations among the security notions, and prove that one of the NIKE schemes proposed by Freire et al. is secure in the strongest RKA sense in the random oracle model under the Double Strong Diffie-Hellman (DSDH) assumption over the group of signed quadratic residues, which is implied by the factoring assumption.

A method of color scheme is proposed considering contrast of luminance between adjacent regions and design property. This method aims at setting the contrast of luminance high, in order to make the image understandable to visually handicapped people. This method also realizes preferable color design for visually normal people by assigning color components from color combination samples. Interactive evolutionary computing is adopted to design the luminance and the color, so that the luminance and color components are assigned to each region appropriately on the basis of human subjective criteria. Here, the luminance is designed first, and then color components are assigned, keeping the luminance unchanged. Since samples of fine color combinations are applied, the obtained color design is also fine and harmonic. Computer simulations verify the high performance of this system.

In the classical computation theory, the language of a system features the computational behavior of the system but it does not distinguish the determinism and nondeterminism of actions. However, Milner found that the determinism and nondeterminism affect the interactional behavior of interactive systems and thus the notion of language does not features the interactional behavior. Therefore, Milner proposed the notion of (weak) bisimulation to solve this problem. With the development of internet, more and more interactive systems occur in the world, such as electronic trading system. Security is one of the most important topics for these systems. We find that different security policies can also affect the interactional behavior of a system, which exactly is the reason why a good policy can strengthen the security. In other words, two interactive systems with different security policies are not of an equivalent behavior although their functions (or business processes) are identical. However, the classic (weak) bisimulation theory draws an opposite conclusion that their behaviors are equivalent. The notion of (weak) bisimulation is not suitable for these security-oriented interactive systems since it does not consider a security policy. This paper proposes the concept of secure bisimulation in order to solve the above problem.

In interactive audio services, users can render audio objects rather freely to match their desires and the spatial audio object coding (SAOC) scheme is fairly good both in the sense of bitrate and audio quality. But rather perceptible audio quality degradation can occur when an object is suppressed or played alone. To complement this, the SAOC scheme with Two-Step Coding (SAOC-TSC) was proposed. But the bitrate of the side information increases two times compared to that of the original SAOC due to the bitrate needed for the residual coding used to enhance the audio quality. In this paper, an efficient residual coding method of the SAOC-TSC is proposed to reduce the side information bitrate without audio quality degradation or complexity increase.

Residents living in a nursing home usually have established medical histories in multiple sources, and most previous medicine management systems have only focused on the integration of prescriptions and the identification of repeated drug uses. Therefore, a comprehensive medicine management system is proposed to integrate medical information from different sources. The proposed system not only detects inappropriate drugs automatically but also allows users to input such information for any non-prescription medicines that the residents take. Every participant can fully track the residents' latest medicine use online and in real time. Pharmacists are able to issue requests for suggestions on medicine use, and residents can also have a comprehensive understanding of their medicine use. The proposed scheme has been practically implemented in a nursing home in Taiwan. The evaluation results show that the average time to detect an inappropriate drug use and complete a medicine record is reduced. With automatic and precise comparisons, the repeated drugs and drug side effects are identified effectively such that the amount of medicine cost spent on the residents is also reduced. Consequently, the proactive feedback, real-time tracking, and interactive consulting mechanisms bind all parties together to realize a comprehensive medicine management system.

The primitive called public key encryption with non-interactive opening (PKENO) is a class of public key encryption (PKE) with additional functionality. By using this, a receiver of a ciphertext can prove that the ciphertext is an encryption of a specified message in a publicly verifiable manner. In some situation that a receiver needs to claim that a ciphertext is NOT decrypted to a specified message, if he/she proves the fact by using PKENO straightforwardly, the real message of the ciphertext is revealed and a verifier checks that it is different from the specified message about which the receiver wants to prove. However, this naive solution is problematic in terms of privacy. Inspired by this problem, we propose the notion of disavowable public key encryption with non-interactive opening (disavowable PKENO) where, with respect to a ciphertext and a message, the receiver of the ciphertext can issue a proof that the plaintext of the ciphertext is NOT the message. Also, we give a concrete construction. Specifically, a disavowal proof in our scheme consists of 61 group elements. The proposed disavowable PKENO scheme is provably secure in the standard model under the decisional linear assumption and strong unforgeability of the underlying one-time signature scheme.

In this paper, the repeatable hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. The authors' had previously proposed a hybrid parallel algorithm for inverse matrix computation. It is reasonably fast for a one time computation of an inverse matrix, but it is hard to apply this algorithm repeatedly for consecutive computations since the relocation of the large matrix is required at the beginning of each iterations. In order to eliminate the relocation of the large input matrix which is the output of the inverse matrix computation from the previous time step, the computation algorithm has been redesigned so that the required portion of the input matrix becomes the same as the output portion of the previously computed matrix in each node. This makes it possible to repeatedly and efficiently apply the SMW formula to compute inverse matrix in a time-series simulation.