This paper presents a prototype group modem for a hyper-multipoint data gathering satellite communication system. It can handle arbitrarily and dynamically assigned FDMA signals by employing a novel FFT-type block demultiplexer/multiplexer. We clarify its configuration and operational principle. Experiments show that the developed modem offers excellent performance.

In the modern day, MPEG-4 image compression technique have been commonly applied in various indoor wireless communication systems. The efficient system design mostly relies on the joint source channel coding algorithms, which aim to reduce the complexity of channel coding process, while maintaining the quality of the receiving images. In this paper, we design the MAP source-controlled channel decoders with both random and semirandom interleavers for Rician slow flat block-fading channels. The MAP-Viterbi decoder employs the residual redundancy from zerotree symbol sequences of MPEG-4 HFS packets. The interleaving processes are done after the overall channel coding process to combat the block-fading effects. The computer simulations summarize the system performance in terms of average WER and PSNR (dB). With the interleavers, the significant improvement in PSNR of about 15-17 dB is obtained for both ML and MAP decoding. Also in many cases, we obtain more improvement of about 0.2-0.4 dB for using MAP decoding with the interleavers.

Scanning packet payload at a high speed has become a crucial task in modern network management due to its wide variety applications on network security and application-specific services. Traditionally, Deterministic finite automatons (DFAs) are used to perform this operation in linear time. However, the memory requirements of DFAs are prohibitively high for patterns used in practical packet scanning, especially when many patterns are compiled into a single DFA. Existing solutions for memory blow-up are making a trade-off between memory requirement and memory access of processing per input character. In this paper we proposed a novel method to drastically reduce the memory requirements of DFAs while still maintain the high matching speed and provide worst-case guarantees. We removed the duplicate transitions between states by dividing all the DFA states into a number of groups and making each group of states share a merged transition table. We also proposed an efficient algorithm for transition sharing between states. The high efficiency in time and space made our approach adapted to frequently updated DFAs. We performed several experiments on real world rule sets. Overall, for all rule sets and approach evaluated, our approach offers the best memory versus run-time trade-offs.

Model-Driven Engineering and Domain-Specific Modeling Languages are encouraging an increased used of metamodels for the definition of languages and tools. Although the Meta Object Facility language is the standard for metamodeling, there are alternative metamodeling languages that are aimed at satisfying specific requirements. In this context, sharing information throughout different domains and tools requires not only being able to translate models between modeling languages defined with the same metamodeling language, but also between different metamodeling languages. This paper addresses this latter need describing a general technique to define transformations that perform this translation. In this work, two case studies illustrate the application of this process.

In this letter we show that the dynamic optimal PCID allocation problem in LTE systems is NP-complete. Subsequently we provide a near-optimal solution using SON which models the problem using new merge operations and explores the search space using a suitable randomized algorithmic approach. Two feasible options for dynamic auto-configuration of the system are also discussed. Simulation results point out that the approach provides near-optimal auto-configuration of PCIDs in computationally feasible time.

Mobile Ad Hoc Networks (MANETs) have inherently dynamic topologies. Due to the distributed, multi-hop nature of these networks, random mobility of nodes not only affects the availability of radio links between particular node pairs, but also threatens the reliability of communication paths, service discovery, even quality of service of MANETs. In this paper, a novel Markov chain model is presented to predict link availability for MANETs. Based on a rough estimation of the initial distance between two nodes, the proposed approach is able to accurately estimate link availability in a random mobility environment. Furthermore, the proposed link availability estimation approach is integrated into Max-Min d-clustering heuristic. The enhanced clustering heuristic, called M4C, takes node mobility into account when it groups mobile nodes into clusters. Simulation results are given to verify the approach and the performance improvement of clustering algorithm. It also demonstrates the adaptability of M4C, and shows that M4C is able to achieve a tradeoff between the effectiveness of topology aggregation and cluster stabilities. The proposed algorithm can also be used to improve the availability and quality of services for MANETs.

Content sharing mechanisms in current DRM systems are based on a domain where multiple devices have the same domain key. This can lead to a security weakness as failure of one device means revocation of a domain itself. Furthermore, if a device leaves the domain, all the other devices should update their domain key. This also leads to efficiency problem. This paper proposes the new content sharing scheme based on the user binding DRM without the use of domain key. The proposed scheme improves the previous domain technology in terms of security and efficiency as it removes the use of domain key and only allows content sharing for multiple devices owned by the same user.

A basic and inevitable problem in estimating flow duration distribution arises from "censoring" (i.e., cutting off) the observed flow duration because of a finite measurement period. We extended the Kaplan-Meier method, which is used in the survival analysis field, and applied it to recover information on the flow duration distribution that was lost due to censoring. We show that the flow duration distribution from a short period of actual traffic data with censoring that was estimated using a Kaplan-Meier-based method can approximate well the flow duration distribution calculated from a sufficiently long period of actual traffic data.

The novel SCR-based (silicon controlled rectifier) device for ESD power clamp is presented in this paper. The proposed device has a high holding voltage and a high triggering current characteristic. These characteristics enable latch-up immune normal operation as well as superior full chip ESD protection. The device has a small area in requirement robustness in comparison to ggNMOS (gate grounded NMOS). The proposed ESD protection device is designed in 0.25 µm and 0.5 µm CMOS Technology. In the experimental result, the proposed ESD clamp has a double trigger characteristic, a high holding voltage of 4 V and a high trigger current of above 350 mA. The robustness has measured to HBM 8 kV (HBM: Human Body Model) and MM 400 V (MM: Machine Model). The proposed device has a high level It2 of 52 mA/ µm approximately.

Self-Organizing Map (SOM) is a powerful tool for the exploratory of clustering methods. Clustering is the most important task in unsupervised learning and clustering validity is a major issue in cluster analysis. In this paper, a new clustering validity index is proposed to generate the clustering result of a two-level SOM. This is performed by using the separation rate of inter-cluster, the relative density of inter-cluster, and the cohesion rate of intra-cluster. The clustering validity index is proposed to find the optimal numbers of clusters and determine which two neighboring clusters can be merged in a hierarchical clustering of a two-level SOM. Experiments show that, the proposed algorithm is able to cluster data more accurately than the classical clustering algorithms which is based on a two-level SOM and is better able to find an optimal number of clusters by maximizing the clustering validity index.

Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.

In the current statistical machine translation (SMT), erroneous word reordering is one of the most serious problems. To resolve this problem, many word-reordering constraint techniques have been proposed. Inversion transduction grammar (ITG) is one of these constraints. In ITG constraints, target-side word order is obtained by rotating nodes of the source-side binary tree. In these node rotations, the source binary tree instance is not considered. Therefore, stronger constraints for word reordering can be obtained by imposing further constraints derived from the source tree on the ITG constraints. For example, for the source word sequence { a b c d }, ITG constraints allow a total of twenty-two target word orderings. However, when the source binary tree instance ((a b) (c d)) is given, our proposed "imposing source tree on ITG" (IST-ITG) constraints allow only eight word orderings. The reduction in the number of word-order permutations by our proposed stronger constraints efficiently suppresses erroneous word orderings. In our experiments with IST-ITG using the NIST MT08 English-to-Chinese translation track's data, the proposed method resulted in a 1.8-points improvement in character BLEU-4 (35.2 to 37.0) and a 6.2% lower CER (74.1 to 67.9%) compared with our baseline condition.

In this paper, a method of the signal subspace interpolation to constructing a continuous fingerprint database for radio localization is proposed. When using the fingerprint technique, enhancing the accuracy of location estimation requires very fine spatial resolution of the database, which entails much time in collecting the data to build up the database. Interpolated signal subspace is presented to achieve a fine spatial resolution of the fingerprint database. The angle of arrival (AOA) and the measured signal subspace at known locations are needed to obtain the interpolated signal subspaces. The effectiveness of this method is verified by an outdoor experiment and the estimated location using this method was compared with those using the geometrically calculated fingerprint and the measured signal subspace fingerprint techniques.

We first consider a variant of the Schmidt-Samoa-Takagi encryption scheme without losing additively homomorphic properties. We show that this variant is secure in the sense of IND-CPA under the decisional composite residuosity assumption, and of OW-CPA under the assumption on the hardness of factoring n=p2q. Second, we introduce new algebraic properties "affine" and "pre-image restriction," which are closely related to homomorphicity. Intuitively, "affine" is a tuple of functions which have a special homomorphic property, and "pre-image restriction" is a function which can restrict the receiver to having information on the encrypted message. Then, we propose an encryption scheme with primitive power roots of unity in (Z/ns+1). We show that our scheme has, in addition to the additively homomorphic property, the above algebraic properties. In addition to the properties, we also show that the encryption scheme is secure in the sense of OW-CPA and IND-CPA under new number theoretic assumptions.

The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

It is said that the lower bound of the number of iterations of Miller's algorithm for pairing calculation is log 2r/(k), where () is the Euler's function, r is the group order, and k is the embedding degree. Ate pairing reduced the number of the loops of Miller's algorithm of Tate pairing from ⌊log 2r⌋ to ⌊ log 2(t-1)⌋, where t is the Frobenius trace. Recently, it is known to systematically prepare a pairing-friendly elliptic curve whose parameters are given by a polynomial of integer variable "χ." For such a curve, this paper gives integer variable χ-based Ate (Xate) pairing that achieves the lower bound. In the case of the well-known Barreto-Naehrig pairing-friendly curve, it reduces the number of loops to ⌊log 2χ⌋. Then, this paper optimizes Xate pairing for Barreto-Naehrig curve and shows its efficiency based on some simulation results.

A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.

Shamir's (k,n)-threshold secret sharing scheme (threshold scheme) has two problems: a heavy computational cost is required to make shares and recover the secret, and a large storage capacity is needed to retain all the shares. As a solution to the heavy computational cost problem, several fast threshold schemes have been proposed. On the other hand, threshold ramp secret sharing schemes (ramp scheme) have been proposed in order to reduce each bit-size of shares in Shamir's scheme. However, there is no fast ramp scheme which has both low computational cost and low storage requirements. This paper proposes a new (k,L,n)-threshold ramp secret sharing scheme which uses just EXCLUSIVE-OR(XOR) operations to make shares and recover the secret at a low computational cost. Moreover, by proving that the fast (k,n)-threshold scheme in conjunction with a method to reduce the number of random numbers is an ideal secret sharing scheme, we show that our fast ramp scheme is able to reduce each bit-size of shares by allowing some degradation of security similar to the existing ramp schemes based on Shamir's threshold scheme.

A new type of mode converter that converts TE30 to TE10 mode is proposed. As an example of the ease of fabrication, holes can be drilled at the top of a metallic waveguide and dielectric rods inserted. This converter is useful for application as a power divider or power combiner.

In this letter, we propose a two-bit representation method for turbo decoder extrinsic information based on bit error count minimization and parameter reset. We show that the performance of the proposed system approaches that of the full precision decoder within 0.17 dB and 0.48 dB at 1 % packet error rate for packet lengths of 500 and 10,000 information bits. The idea of parameter reset we introduce can be used not only in turbo decoder but also in many other iterative algorithms.