Visual inpainting is an interpolation problem that restores an image or a frame with missing or damaged parts. Over the past decades, a number of computable models of visual inpainting have been developed, but most of these models are based on the pixel domain. Little theoretical and computational work of visual inpainting is based on the compressed domain. In this paper, a visual inpainting model in the discrete cosine transform (DCT) domain is proposed. DCT coefficients of the non-inpainting blocks are utilized to get block features, and those block features are propagated to the inpainting region iteratively. The experimental results with I frames of MPEG4 are presented to demonstrate the efficiency and accuracy of the proposed algorithm.

The Clonal Selection Algorithm (CSA) is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus. In the immune response, according to Burnet's clonal selection principle, the antigen imposes a selective pressure on the antibody population by allowing only those cells which specifically recognize the antigen to be selected for proliferation and differentiation. However ongoing investigations indicate that receptor editing, which refers to the process whereby antigen receptor engagement leads to a secondary somatic gene rearrangement event and alteration of the receptor specificity, is occasionally found in affinity maturation process. In this paper, we extend the traditional CSA approach by incorporating the receptor editing method, named RECSA, and applying it to the Traveling Salesman Problem. Thus, both somatic hypermutation (HM) of clonal selection theory and receptor editing (RE) are utilized to improve antibody affinity. Simulation results and comparisons with other general algorithms show that the RECSA algorithm can effectively enhance the searching efficiency and greatly improve the searching quality within reasonable number of generations.

This paper proposes a metric for example matching under the example-based machine translation. Our metric served as similarity measure is employed to retrieve the most similar examples to a given query. Basically it makes use of simple information such as lemma and part-of-speech information of typographically mismatched words. In addition, it uses the contiguity information of matched word units to catch the full context. Finally we show the results for the correctness of the proposed metric.

We propose a tool to manage several sorts of relationships among RDF (Resource Description Framework) and RDFS (RDF Schema). Our tool consists of three main functions: graphical editing of RDF descriptions, graphical editing of RDFS descriptions, and meta-model management facilities. In this paper, we focus on the meta-model management, a key concept which is defined as the appropriate management of the correspondence between a model and its meta-model: especially, the class and property in the meta-model, and the type of RDF resource and property in the model. The above facilities are implemented based on the plug-in system. We provide basic plug-in modules for checking the consistency of RDFS classes and properties. The prototyping tool, called MR3 (Meta-Model Management based on RDFs Revision Reflection), is implemented by Java language. Through an experiment using MR3, we show how MR3 contributes to the Semantic Web paradigm from the standpoint of RDFs description management.

In this paper, we are concerned with a structural ambiguity problem of tree adjoining grammars (TAGs), which is an essential problem when we try to model consensus structures of given set of ribonucleic acid (RNA) secondary structures by TAGs. RNA secondary structures can be represented as strings with structural information, and TAGs have a descriptive capability of this kind of strings, what we call structure-annotated strings. Thus, we can model RNA secondary structures by TAGs. It is sufficient to use existing alignment methods for just computing the optimal alignment between RNA secondary structures. However, when we also want to model the resulting alignment by grammars, if we adopt these existing methods, then we may fail in modeling the alignment result by grammars. Therefore, it is important to introduce a new alignment method whose alignment results can be appropriately modeled by grammars. In this paper, we will propose an alignment method based on TAG's derivations each corresponding to a given RNA secondary structure. For an RNA secondary structure, there exist a number of derivations of TAGs which correspond to the structure. From the grammatical point of view, the property of TAGs drives us to the question how we should choose a derivation from these candidates in order to obtain an optimal alignment. This is the structural ambiguity problem of TAGs, which will be mainly discussed in this paper. For dealing with this problem appropriately, we will propose an edit distance between two structure-annotated strings, and then present an algorithm which computes an optimal alignment based on the edit distance.

In order to boost the translation quality of corpus-based MT systems for speech translation, the technique of splitting an input utterance appears promising. In previous research, many methods used word-sequence characteristics like N-gram clues among splitting positions. In this paper, to supplement splitting methods based on word-sequence characteristics, we introduce another clue using similarity based on edit-distance. In our splitting method, we generate candidates for utterance splitting based on N-grams, and select the best one by measuring the utterance similarity against a corpus. This selection is founded on the assumption that a corpus-based MT system can correctly translate an utterance that is similar to an utterance in its training corpus. We conducted experiments using three MT systems: two EBMT systems, one of which uses a phrase as a translation unit and the other of which uses an utterance, and an SMT system. The translation results under various conditions were evaluated by objective measures and a subjective measure. The experimental results demonstrate that the proposed method is valuable for the three systems. Using utterance similarity can improve the translation quality.

One of the key issues in the next generation Internet is end-to-end Quality of Service (QoS) provisioning for real-time applications. The Differentiated Services (DiffServ) architecture offers a scalable alternative to provide QoS in the Internet. However, within this architecture, an efficient scheduling mechanism is still needed to ensure such QoS guarantees. In this paper, scheduling mechanism for supporting QoS differentiation among multiple traffic classes in IP differentiated services networks is studied. A scheduling algorithm called Multiclass Efficient Packet Fair Queueing (MEPFQ) is proposed that enables fair bandwidth sharing while supporting better bounds on end-to-end network delay for QoS-sensitive applications such as voice over IP (VoIP) within the DiffServ framework. The mechanism allows to create service classes and assign proportional weights to such classes efficiently according to their resource requirements. Besides, MEPFQ tries to ensure that packets from low priority class will not be starved even under extreme congestion cases. The results from the simulation studies show that the mechanism is able to ensure both the required end-to-end network delay bounds and bandwidth fairness for QoS-sensitive applications based on the specified service weights under various traffic and network conditions. Another important aspect of the MEPFQ algorithm is that the scheme has lower implementation complexity, along with scalability to accommodate the growing traffic flows at the core routers of high-speed Internet backbone.

This paper proposes a credit-based congestion control scheme for multicast communication which employs application-specific processing at intermediate network nodes. The control scheme was designed not only to take advantage of credit-based flow control for unicast communication, but also to achieve flexibility supported by active network technology. The resultant active multicast congestion control scheme is able to meet the different requirements of various multicast applications in terms of reliability and end-to-end latency. The performance of the proposed control scheme was evaluated using both discrete-event simulations and experiments on a prototype active network implementation. The results show that the proposed scheme performs very well in terms of fairness, responsiveness, and scalability. The implementation experiences also confirmed the feasibility of the scheme in practice.

Our aim is to develop an intuitive sound designing interface for non-expert users. We propose editing sound by sound, which means using vocal mimicking as a "master" to transform the pitch and amplitude envelope. Our technique allows any user to easily and intuitively design sound because it requires no knowledge of acoustic features.

Credit-based electronic payment systems are considered to play important roles in future automated payment systems. Like most other types of payment systems, however, credit-based systems proposed so far generally involve computationally expensive cryptographic operations. Such a relatively heavy computational load is preventing credit-based systems from being used in applications which require very fast processing. A typical example is admission-fee payment at the toll gate of an expressway without stopping a vehicle that travels at a high speed. In this article, we propose a very fast credit-based electronic payment protocol for admission-fee payment. More specifically, we propose a payment system between a high-speed vehicle and a toll gate which uses only very simple and fast computations. The proposed system makes use of an optimized Key Pre-distribution System (or KPS) to obtain high resistance against collusion attacks.

For the realization of the very high-speed data transmission over wide area network, the HIPPI-ATM conversion for connecting two remote HIPPI end systems is specified by ANSI. Since the credit scheme is adopted for the flow control on the ATM part in the specification, the propagation delay influences the remarkable transfer throughput degradation with the longer distance between end systems. In this paper, two priority types of HIPPI bursts are proposed, which include the flag indicating the priority, high priority or low priority. We propose the hybrid scheme that the credit scheme is adopted only for sending the high priority HIPPI bursts and the source can send low priority HIPPI bursts without reserving buffers in the receiver. In order to confirm the effectiveness of the proposed scheme, we show the characteristics of transfer performance and low priority bursts loss ratio v. s. transmission distance by simulation. Furthermore, we introduce the implemental example of the proposed scheme in the MPEG video transmission application, and show it's good performance.

Broadband Integrated Services Digital Network (B-ISDN) is intended to provide various services in telecommunications like voice, video, and data communication. For realizing the B-ISDN network, Asynchronous Transfer Mode (ATM) is one of several data transfer technologies that are proposed and currently being developed. Several flow control methods have been proposed for data cell traffic in ATM network. One of the feedback control mechanisms is credit-based flow control that is proposed to handle an Available Bit Rate (ABR) traffic. The credit based mechanism is applied in Local Area Network (LAN) and usually uses static buffer allocation method. When the conventional credit-based algorithm is applied in the LAN system, the problems such as low utilization of node buffer and large delay of source data will occur. In this paper, we propose a new algorithm that is called stop and release credit method to make credit-based flow control more effective. According to simulation results, proposed method will make high utilization of node buffer and small delay of source data.

This paper describes a novel shared file system, whose main features are enhanced security and its concurrency control mechanism. The system is especially suitable for access from mobile hosts. Users can edit their shared files concurrently. Shared files are encrypted and decrypted only by clients, and the file server cannot know the contents. The server asynchronously receives the edited parts, which are already encrypted, and merges them into the current version, deciphering neither the stored file nor the encrypted editing data. We call the mechanism 'privacy enhanced merging'. The mechanism and the underlying encryption algorithm, shared file data structure and procedures followed by clients and the server are shown.

A method for the compression of ECG data is presented. The method is based on the edit distance algorithm developed in the file comparison problems. The edit distance between two sequences of symbols is defined as the number of edit operations required to transform a sequence of symbols into the other. We adopt the edit distance algorithm to obtain a list of edit operations, called edit script, which transforms a reference pulse into a pulse selected from ECG data. If the decoder knows the same reference, it can reproduce the original pulse, only from the edit script. The amount of the edit script is expected to be smaller than that of the original pulse when the two pulses look alike and thereby we can reduce the amount of space to store the data. Applying the proposed scheme to the raw data of ECG, we have achieved a high compression about 14: 1 without losing the significant features of signals.

Syntax-directed editors have several advantages in editing programs because programming is guided by the syntax and free from syntax errors. Nevertheless, they are less popular than text editiors. One of the reason is that they force a priori specified editing structures on the user and do not allow him to use his own structure. ACE (Algorithmically Customizable syntax-directed Editor) provides a solution for this problem by using a technique of machine learning; ACE has a special function of customizing the grammar algorithmically and interactively based on the learning method for grammars from examples and queries. The grammar used in the editor is customized through interaction with the user so that the user can edit his program in a more familiar structure. The customizing function has been implemented based on the methods for learning of context-free grammars from structural examples, for which the correctness and the efficiency are proved formally. This guarantees the soundness and the efficiency of customization. Furthermore, ACE can be used as an algorithmic and interactive tool to design grammars, which is required for several purposes such as compiler design and pretty-printer design.