In this paper, we propose an error-correction low-pass filter (EC-LPF) algorithm for estimating the wireless distance between devices. To measure this distance, the received signal strength indication (RSSI) is a popularly used method because the RSSI of a wireless signal, such as Wi-Fi and Bluetooth, can be measured easily without the need for additional hardware. However, estimating the wireless distance using an RSSI is known to be difficult owing to the occurrence of inaccuracies. To examine the inaccuracy characteristics of Bluetooth RSSI, we conduct a preliminary test to discover the relationship between the actual distance and Bluetooth RSSI under several different environments. The test results verify that the main reason for inaccuracy is the existence of measurement errors in the raw Bluetooth RSSI data. In this paper, the EC-LPF algorithm is proposed to reduce measurement errors by alleviating fluctuations in a Bluetooth signal with responsiveness for real-time applications. To evaluate the effectiveness of the EC-LPF algorithm, distance accuracies of different filtering algorithms are compared, namely, a low-pass filer (LPF), a Kalman filter, a particle filter, and the EC-LPF algorithm under two different environments: an electromagnetic compatibility (EMC) chamber and an indoor hall. The EC-LPF algorithm achieves the best performance in both environments in terms of the coefficient of determination, standard deviation, measurement range, and response time. In addition, we also implemented a meeting room application to verify the feasibility of the EC-LPF algorithm. The results prove that the EC-LPF algorithm distinguishes the inside and outside areas of a meeting room without error.

Recently, the growing concepts that information communication technologies apply to social infrastructures have caused deep interests with wireless sensor networks (WSNs). WSNs can be used for various application areas such as home, health, factory and so on. For the different application areas, there are different technical issues (e.g., security, reliability, real time gathering, long life time, scalability). Efficient information gathering can be potentially obtained if we take a suitable information gathering method with considering the requirements of each WSN application. Thus, we have not persisted all information gathering perfectly and have proposed one of simple information gathering methods in response to the requirements of WSN applications in this paper. In the proposed method, the information is converted to physical-layer parameters of wireless communications, such as frequency and time. Also, simulations are performed to validate the effectiveness of the proposed method in real time gathering and estimating with high precision.

In recent years, hybrid typestate analysis has been proposed to eliminate unnecessary monitoring instrumentations for runtime monitors at compile-time. Nop-shadows Analysis (NSA) is one of these hybrid typestate analyses. Before generating residual monitors, NSA performs the data-flow analysis which is intra-procedural flow-sensitive and partially context-sensitive to improve runtime performance. Although NSA is precise, there are some cases on which it has little effects. In this paper, we propose three optimizations to further improve the precision of NSA. The first two optimizations try to filter interferential states of objects when determining whether a monitoring instrumentation is necessary. The third optimization refines the inter-procedural data-flow analysis induced by method invocations. We have integrated our optimizations into Clara and conducted extensive experiments on the DaCapo benchmark. The experimental results demonstrate that our first two optimizations can further remove unnecessary instrumentations after the original NSA in more than half of the cases, without a significant overhead. In addition, all the instrumentations can be removed for two cases, which implies the program satisfy the typestate property and is free of runtime monitoring. It comes as a surprise to us that the third optimization can only be effective on 8.7% cases. Finally, we analyze the experimental results and discuss the reasons why our optimizations fail to further eliminate unnecessary instrumentations in some special situations.

Optimizing embedded software is a problem having scientific and practical signification. Optimizing embedded software can be done in different phases of the software life cycle under different optimal conditions. Most studies of embedded software optimization are done in forward engineering and these studies have not given an overall model for the optimization problem of embedded software in both forward engineering and reverse engineering. Therefore, in this paper, we propose a new approach to embedded software optimization based on reverse engineering. First, we construct an overall model for the embedded software optimization in both forward engineering and reverse engineering and present a process of embedded software optimization in reverse engineering. The main idea of this approach is that decompiling executable code to source code, converting the source code to models and optimizing embedded software under different levels such as source code and model. Then, the optimal source code is recompiled. To develop this approach, we present two optimization techniques such as optimizing power consumption of assembly programs based on instruction schedule and optimizing performance based on alternating equivalent expressions.

We study the problem of transforming one list (vertex) coloring of a graph into another list coloring by changing only one vertex color assignment at a time, while at all times maintaining a list coloring, given a list of allowed colors for each vertex. This problem is known to be PSPACE-complete for bipartite planar graphs. In this paper, we first show that the problem remains PSPACE-complete even for bipartite series-parallel graphs, which form a proper subclass of bipartite planar graphs. We note that our reduction indeed shows the PSPACE-completeness for graphs with pathwidth two, and it can be extended for threshold graphs. In contrast, we give a polynomial-time algorithm to solve the problem for graphs with pathwidth one. Thus, this paper gives sharp analyses of the problem with respect to pathwidth.

In recent years, researchers have tried to create unhindered human-computer interaction by giving virtual agents human-like conversational skills. Predicting backchannel feedback for agent listeners has become a novel research hot-spot. The main goal of this paper is to identify appropriate features and methods for backchannel prediction in Mandarin conversations. Firstly, multimodal Mandarin conversations are recorded for the analysis of backchannel behaviors. In order to eliminate individual difference in the original face-to-face conversations, more backchannels from different listeners are gathered together. These data confirm that backchannels occurring in the speakers' pauses form a vast majority in Mandarin conversations. Both prosodic and visual features are used in backchannel prediction. Four types of models based on the speakers' pauses are built by using support vector machine classifiers. An evaluation of the pause-based prediction model has shown relatively high accuracy in consideration of the optional nature of backchannel feedback. Finally, the results of the subjective evaluation validate that the conversations performed between humans and virtual listeners using backchannels predicted by the proposed models is more unhindered compared to other backchannel prediction methods.

In recent years, the time variation of Internet traffic has increased due to the growth of streaming and cloud services. Backbone networks must accommodate such traffic without congestion. Traffic engineering with traffic prediction is one approach to stably accommodating time-varying traffic. In this approach, routes are calculated from predicted traffic to avoid congestion, but predictions may include errors that cause congestion. We propose prediction-based traffic engineering that is robust against prediction errors. To achieve robust control, our method uses model predictive control, a process control method based on prediction of system dynamics. Routes are calculated so that future congestion is avoided without sudden route changes. We apply calculated routes for the next time slot, and observe traffic. Using the newly observed traffic, we again predict traffic and re-calculate the routes. Repeating these steps mitigates the impact of prediction errors, because traffic predictions are corrected in each time slot. Through simulations using backbone network traffic traces, we demonstrate that our method can avoid the congestion that the other methods cannot.

Multi-hop cooperative communication has been investigated in order to overcome disadvantages such as fading, obstruction and low power. In addition, with the goal of increasing access capacity, the orthogonal frequency division multiplexing (OFDM) modulation is being advanced as a solution. In this paper, we propose the approach of relay ordering in a Decode-and-Forward OFDM scheme. Combining techniques such as maximal ratio combining and selection combining are employed at receivers and approximate outage capacity probabilities are derived for evaluating system performance over frequency selective Rayleigh fading channels. Final, the expressions are validated by Monte-Carlo simulations, and are used to compare with the same scheme based relay selection.

Controlling interference from the secondary system (SS) to the receiver of the primary system (PS) is an important issue when the SS uses the same frequency band as the television broadcast system. The reason includes that the SS is unaware of the interference imposed on the primary receiver (PS-Rx), which does not have a transmitter. In this paper, we propose an interference control method between PS-Rx and SS, where a load modulation scheme is introduced to the PS-Rx. In this method, the signal from the PS transmitting station is scattered by switching its load impedance. The SS observes the scattered channel and calculates the interference suppression weights for transmitting, and controls interference by transmit beamforming. A simulation shows that the Signal-to-Interference Ratio (SIR) with interference control is improved by up to 41.5dB compared to that without interference control at short distances; the results confirm that the proposed method is effective in controlling interference between PS-Rx and SS. Furthermore, we evaluate the Signal-to-Noise Ratio (SNR) and channel capacity at SS.

Large-scale content transfer, especially video transfer, is now a dominant traffic component in the Internet. Originally, content transfer had a content-oriented feature, i.e., “Users do not care where content is retrieved. Users only take care of what content they obtain.” Conventional traffic engineering (TE) aims to obtain optimal routes for traffic between ingress and egress router pairs, i.e., TE has focused on a location-oriented approach that takes care of where to connect. With increased demand for content-oriented features for content traffic, TE needs to focus on content-oriented routing design. In this study, we therefore propose a novel approach to content-oriented TE, called content aware routing (CAR). In CAR, routes are designed for content and egress router pairs, i.e., content traffic toward a receiver-side router. Content demand can be flexibly distributed to multiple servers (i.e., repositories) providing the same content, meaning that content can be obtained from anywhere. CAR solves the optimization problem of minimizing maximum link utilization. If there are multiple optimal solutions, CAR selects a solution in which resource usage is minimized. Using numerical examples formulated by the linear programming problem, we evaluated CAR by comparing it with combinations of conventional content delivery networks and TE, i.e., location-oriented designs. Our numerical results showed that CAR improved maximum link utilization by up to 15%, with only a 5% increase of network resource usage.

At Indocrypt 2005, Coglianese and Goi [1] suggested a new public key cryptosystem, MaTRU, which is a variant of NTRU. MaTRU is defined over ring M of k×k matrices whose elements are in the quotient ring R = Z[X]/(Xn-1). In addition, five example parameter sets suitable for this new structure were proposed. In this paper, we prove that it is impossible to generate appropriate key pairs for four parameter sets among the five proposed in [1] according to the key generation procedure described in [1]. The only parameter set where key pair generation is possible is when p, one of the parameters of MaTRU, is 2 and df, another parameter, is odd. Even with this parameter set, however, the decryption operation defined in [1] cannot recover an original plaintext from a given ciphertext because the value of another parameter, q, has been defined too small in [1]. Therefore, we propose an alternative method for key generation and suggest corrected parameter sets. In addition, a refined analysis for the key security of MaTRU is provided, and it is demonstrated that the key security may be significantly lower than that of the original analysis.

Square-root Nyquist transmit filtering is typically used in single-carrier (SC) transmission. By changing the filter roll-off factor, the bit-error rate (BER), peak-to-average power ratio (PAPR), and spectrum efficiency (SE) changes, resulting in a tradeoff among these performance indicators. In this paper, assuming SC with frequency-domain equalization (SC-FDE), we design a new transmit filtering based on the minimum variance of instantaneous transmit power (VIP) criterion in order to reduce the PAPR of the transmit signal of SC-FDE. Performance evaluation of SC-FDE using the proposed transmit filtering is done by computer simulation, and shows that the proposed transmit filtering contributes lower transmit PAPR, while there exists only a small degradation in BER performance compared to SC-FDE using square-root Nyquist filtering.

Recommender systems, which provide users with recommendations of content suited to their needs, have received great attention in today's online business world. However, most recommendation approaches exploit only a single source of input data and suffer from the data sparsity problem and the cold start problem. To improve recommendation accuracy in this situation, additional sources of information, such as friend relationship and user-generated tags, should be incorporated in recommendation systems. In this paper, we revise the user-based collaborative filtering (CF) technique, and propose two recommendation approaches fusing user-generated tags and social relations in a novel way. In order to evaluate the performance of our approaches, we compare experimental results with two baseline methods: user-based CF and user-based CF with weighted friendship similarity using the real datasets (Last.fm and Movielens). Our experimental results show that our methods get higher accuracy. We also verify our methods in cold-start settings, and our methods achieve more precise recommendations than the compared approaches.

A number of network monitoring sensors such as honeypot and web crawler have been launched to observe increasingly-sophisticated cyber attacks. Based on these technologies, there have been several large scale network monitoring projects launched to fight against cyber threats on the Internet. Meanwhile, these projects are facing some problems such as Difficulty of collecting wide range darknet, Burden of honeypot operation and Blacklisting problem of honeypot address. In order to address these problems, this paper proposes a novel proactive cyber attack monitoring platform called GHOST sensor, which enables effective utilization of physical and logical resources such as hardware of sensors and monitoring IP addresses as well as improves the efficiency of attack information collection. The GHOST sensor dynamically allocates targeted IP addresses to appropriate sensors so that the sensors can flexibly monitor attacks according to profiles of each attacker. Through an evaluation in a experiment environment, this paper presents the efficiency of attack observation and resource utilization.

The ultimate purpose of a business process is to promote business values. Thus, any process that fails to enhance or promote business values should be improved or adjusted so that business values can be achieved. Therefore an organization should have the capability of confirming whether a business value is achieved; furthermore, in order to cope with the changes of business environment, it should be able to define the necessary measures on the basis of business values. This paper proposes techniques for measuring a business process based on business values, which can be used to monitor and control business activities focusing on the attainment of business values. To show the feasibility of the techniques, we compare their monitoring and controlling capabilities with those of the current fulfillment process of a company. The results show that the proposed techniques are effective in linking business values to relevant processes and integrating each measurement result in accordance with the management level.

In this short correspondence, (1+uv)-constacyclic codes over the finite non-chain ring R[v]/(v2+v) are investigated, where R=F2+uF2 with u2=0. Some structural properties of this class of constacyclic codes are studied. Further, some optimal binary linear codes are obtained from these constacyclic codes.

Content-Centric Networking (CCN) has an in-network caching mechanism, which can reduce the traffic volume along the route to the destination host. This traffic volume reduction on the transit link can decrease inter-ISP transit cost. However, the memory space for caching in CCN routers is small relative to content volume. In addition, any initial access to the content requested by a user must use the transit link, even when a nearby CCN router outside the route has the cached content. In this paper, we propose a method of cooperative cache sharing among CCN routers in multiple ISPs. It aims to attain a further reduction in the inter-ISP transit cost by improving the cache hit ratio. In the proposed method, the CCN routers share the memory space for caching of non-overlapping cache content. We evaluate the proposed method by simulation experiments using the IP-level network topology of actual ISP, and show that the inter-ISP transit traffic can be reduced by up to 28% compared with normal caching behavior of CCN.

In this letter, we present a method for automatic mura detection for display film using the efficient decision of cut-off frequency with DCT and mask filtering with wavelet transform. First, the background image including reflected light is estimated using DCT with adaptive cut-off frequency, and DWT is applied to background-removed images for generating mura mask. Then, a mura mask is generated by separating low-frequency noise in the approximation coefficients. Lastly, mura is detected by applying mura mask filtering to the detail coefficients. According to the comparison by Semu index, the results from the proposed method are superior to those from the existing methods. This indicates that the proposed method is high in reliability.

This paper describes an architectural design and related services of a new Japanese academic backbone network, called SINET5, which will be launched in April 2016. The network will cover all 47 prefectures with 100-Gigabit Ethernet technology and connect each pair of prefectures with a minimized latency. This will enable users to leverage evolving cloud-computing powers as well as draw on a high-performance platform for data-intensive applications. The transmission layer will form a fully meshed, SDN-friendly, and reliable network. The services will evolve to be more dynamic and cloud-oriented in response to user demands. Cyber-security measures for the backbone network and tools for performance acceleration and visualization are also discussed.

Most previous approaches on comparing the results for software architecture recovery are designed to handle only flat decompositions. In this paper, we propose a novel distance called Split-Jaccard Distance of Hierarchical Decompositions. It extends the Jaccard coefficient and incorporates the concept of the splits of leaves in a hierarchical decomposition. We analyze the proposed distance and derive its properties, including the lower-bound and the metric space.