Multi-static Primary Surveillance Radar (MSPSR) has recently attracted attention as a new surveillance technology for civil aviation. Using multiple receivers, Primary Surveillance Radar (PSR) detection performance can be improved by synthesizing the reflection characteristics which change due to the aircraft's position. In this paper, we report experimental results from our proposed optical-fiber-connected passive PSR system with transmit signal installed at the Sendai Airport in Japan. The signal-to noise ratio of experimental data is evaluated to verify moving target detection. In addition, we confirm the operation of the proposed system using a two-receiver setup, to resemble a conventional multi-static radar. Finally, after applying time correction, the delay of the reflected signal from a stationary target remains within the expected range.

It is well known that the power transfer efficiency (PTE) of a wireless power transfer (WPT) system is maximized at a specific coupling coefficient under the fixed system parameters. For an adaptive WPT system, various attempts have been made to achieve the maximum PTE by changing the system parameters. Applying the input matching networks to the WPT system is one of the most popular implementation methods to change the source impedance and improve the PTE. In this paper, we derive the optimum source condition for the given load and the achievable maximum PTE under the optimum source condition in a closed-form. Furthermore, we propose a method to estimate the input impedance, without feedback information, and an input matching network structure that transforms the source impedance into the optimum source obtained from the estimated input impedance. The proposed technique is successfully implemented at a resonant frequency of 13.56MHz. The experimental results are in close agreement with the theoretical achievable maximum PTE and show that the use of only a single matching network can sufficiently achieve a PTE close to the ideal maximum PTE.

This paper proposes optimal beam patterns of analog beamforming for SU (Single User) massive MIMO (Multi-Input Multi-Output) transmission systems. For hybrid beamforming in SU massive MIMO systems, there are several design parameters such as beam patterns, the number of beams (streams), the shape of array antennas, and so on. In conventional hybrid beamforming, rectangular patch array antennas implemented on a planar surface with linear phase shift beam patterns have been used widely. However, it remains unclear whether existing configurations are optimal or not. Therefore, we propose a method using OBPB (Optimal Beam Projection Beamforming) for designing configuration parameters of the hybrid beamforming. By using the method, the optimal beam patterns are derived first, and are projected on the assumed surface to calculate the achievable number of streams and the resulting channel capacity. The results indicate OBPB with a spherical surface yields at least 3.5 times higher channel capacity than conventional configurations.

This paper presents a design for the perpendicular-corporate feed in a four-layer circularly-polarized parallel-plate slot array antenna. We place a dielectric layer with adequate permittivity in the region between the coupling-aperture and the radiating-slot layers to remove x-shaped cavity walls completely in the radiating part of a conventional planar corporate-feed waveguide slot array antenna. To address fabrication constraints, the dielectric layer consists of PTFE and air. It excites a strong standing wave in the region and so provides 2×2-element subarrays with uniform excitation. None of the slot layers are in electrical contact due to air gaps between the slot layers. The four-layer structure with apertures for circular polarization contributes to wideband design for axial ratios because of the eigenmodes in the desired band. We realize an 11.9% bandwidth for axial ratios of less than 3.0dB as confirmed by measurements in the 60GHz band. At the design frequency, the measured realized gain is 32.7dBi with an antenna efficiency of 75.5%.

We introduce a notion of watermarking for cryptographic functions and propose a concrete scheme for watermarking cryptographic functions. Informally speaking, a digital watermarking scheme for cryptographic functions embeds information, called a mark, into functions such as one-way functions and decryption functions of public-key encryption. There are two basic requirements for watermarking schemes. A mark-embedded function must be functionally equivalent to the original function. It must be difficult for adversaries to remove the embedded mark without damaging the original functionality. In spite of its importance and usefulness, there have only been a few theoretical works on watermarking for functions (or programs). Furthermore, we do not have rigorous definitions of watermarking for cryptographic functions and concrete constructions. To solve the problem above, we introduce a notion of watermarking for cryptographic functions and define its security. Furthermore, we present a lossy trapdoor function (LTF) based on the decisional bilinear Diffie-Hellman problem problem and a watermarking scheme for the LTF. Our watermarking scheme is secure under the symmetric external Diffie-Hellman assumption in the standard model. We use techniques of dual system encryption and dual pairing vector spaces (DPVS) to construct our watermarking scheme. This is a new application of DPVS.

As a modulation scheme for optical wireless communication, there is MPolSK (multilevel polarization shift keying) that modulates a state of polarization of light. MPolSK has a problem that it is severely affected by mismatched polarization axes. Although MDPolSK (multilevel differential PolSK) can overcome the problem, it is susceptible to noise, and its SER (symbol error rate) degrades as compared to MPolSK. In this paper, we propose one kind of MDPolSK that estimates the mismatched polarization axes in the receiver. We analyzed SER of the proposed scheme by computer simulations. The result shows that the proposed scheme is not affected by the mismatched polarization axes, and it provides a good SER as compared to the conventional MDPolSK. In addition, we modified the constellation used in the proposed scheme to improve SER.

Topological inference is the foundation of network performance analysis and optimization. Due to the difficulty of obtaining prior topology information of wireless sensor networks, we propose routing topology inference, RTI, which reconstructs the routing topology from source nodes to sink based on marking packets and probing locally. RTI is not limited to any specific routing protocol and can adapt to a dynamic and lossy networks. We select topological distance and reconstruction time to evaluate the correctness and effectiveness of RTI and then compare it with PathZip and iPath. Simulation results indicate that RTI maintains adequate reconstruction performance in dynamic and packet loss environments and provides a global routing topology view for wireless sensor networks at a lower reconstruction cost.

Bilinear-type conversion is to translate a cryptographic scheme designed over symmetric bilinear groups into one that works over asymmetric bilinear groups with small overhead regarding the size of objects concerned in the target scheme. In this paper, we address scalability for converting complex cryptographic schemes. Our contribution is threefold. Investigating complexity of bilinear-type conversion. We show that there exists no polynomial-time algorithm for worst-case inputs under standard complexity assumption. It means that bilinear-type conversion in general is an inherently difficult problem. Presenting a new scalable conversion method. Nevertheless, we show that large-scale conversion is indeed possible in practice when the target schemes are built from smaller building blocks with some structure. We present a novel conversion method, called IPConv, that uses 0-1 Integer Programming instantiated with a widely available IP solver. It instantly converts schemes containing more than a thousand of variables and hundreds of pairings. Application to computer-aided design. Our conversion method is also useful in modular design of middle to large scale cryptographic applications; first construct over simpler symmetric bilinear groups and run over efficient asymmetric groups. Thus one can avoid complication of manually allocating variables over asymmetric bilinear groups. We demonstrate its usefulness by somewhat counter-intuitive examples where converted DLIN-based Groth-Sahai proofs are more compact than manually built SXDH-based proofs. Though the early purpose of bilinear-type conversion is to save existing schemes from attacks against symmetric bilinear groups, our new scalable conversion method will find more applications beyond the original goal. Indeed, the above computer-aided design can be seen as a step toward automated modular design of cryptographic schemes.

Kirchhoff approximation (KA) method has been applied for ray-mode conversion to analyze the plane wave scattering by conducting thick slits. The scattering fields can be considered as field radiations from equivalent magnetic current sources assumed by closing the aperture of the slit. The obtained results are compared with those of other methods to validate the accuracy of the proposed formulation in different conditions of slit dimension.

We propose new key recovery attacks on the two-round single-key n-bit Even-Mansour ciphers (2SEM) that are secure up to 22n/3 queries against distinguishing attacks proved by Chen et al. Our attacks are based on the meet-in-the-middle technique which can significantly reduce the data complexity. In particular, we introduce novel matching techniques which enable us to compute one of the two permutations without knowing a part of the key information. Moreover, we present two improvements of the proposed attack: one significantly reduces the data complexity and the other reduces the time complexity. Compared with the previously known attacks, our attack first breaks the birthday barrier on the data complexity although it requires chosen plaintexts. When the block size is 64 bits, our attack reduces the required data from 245 known plaintexts to 226 chosen plaintexts with keeping the time complexity required by the previous attacks. Furthermore, by increasing the time complexity up to 262, the required data is further reduced to 28, and DT=270, where DT is the product of data and time complexities. We show that our data-optimized attack requires DT=2n+6 in general cases. Since the proved lower bound on DT for the single-key one-round n-bit Even-Mansour ciphers is 2n, our results imply that adding one round to one-round constructions does not sufficiently improve the security against key recovery attacks. Finally, we propose a time-optimized attacks on 2SEM in which, we aim to minimize the number of the invocations of internal permutations.

In cloud computing environments, data processing systems with strong and stochastic stream data processing capabilities are highly desired by multi-service oriented computing-intensive applications. The independeny of different business data streams makes these services very suitable for parallel processing with the aid of multicore processors. Furthermore, for the random crossing of data streams between different services, data synchronization is required. Aiming at the stochastic cross service stream, we propose a hardware synchronization mechanism based on index tables. By using a specifically designed hardware synchronization circuit, we can record the business index number (BIN) of the input and output data flow of the processing unit. By doing so, we can not only obtain the flow control of the job package accessing the processing units, but also guarantee that the work of the processing units is single and continuous. This approach overcomes the high complexity and low reliability of the programming in the software synchronization. As demonstrated by numerical experiment results, the proposed scheme can ensure the validity of the cross service stream, and its processing speed is better than that of the lock-based synchronization scheme. This scheme is applied to a cryptographic server and accelerates the processing speed of the cryptographic service.

An ASIC crypto processor optimized for the 254-bit prime-field optimal-ate pairing over Barreto-Naehrig (BN) curve is proposed. The data path of the proposed crypto processor is designed to compute five Fp2 operations, a multiplication, three addition/subtractions, and an inversion, simultaneously. We further propose a design methodology to automate the instruction scheduling by using a combinatorial optimization solver, with which the total cycle count is reduced to 1/2 compared with ever reported. The proposed crypto processor is designed and fabricated by using a 65nm silicon-on-thin-box (SOTB) CMOS process. The chip measurement result shows that the fabricated chip successfully computes a pairing in 0.185ms when a typical operating voltage of 1.20V is applied, which corresponds to 2.8× speed up compared to the current state-of-the-art pairing implementation on ASIC platform.

Malware has become a growing threat as malware writers have learned that signature-based detectors can be easily evaded by packing the malware. Packing is a major challenge to malware analysis. The generic unpacking approach is the major solution to the threat of packed malware, and it is based on the intrinsic nature of the execution of packed executables. That is, the original code should be extracted in memory and get executed at run-time. The existing generic unpacking approaches need a simulated environment to monitor the executing of the packed executables. Unfortunately, the simulated environment is easily detected by the environment-sensitive packers. It makes the existing generic unpacking approaches easily evaded by the packer. In this paper, we propose a novel unpacking approach, BareUnpack, to monitor the execution of the packed executables on the bare-metal operating system, and then extracts the hidden code of the executable. BareUnpack does not need any simulated environment (debugger, emulator or VM), and it works on the bare-metal operating system directly. Our experimental results show that BareUnpack can resist the environment-sensitive packers, and improve the unpacking effectiveness, which outperforms other existing unpacking approaches.

In this paper, we investigate how to obtain binary locally repairable codes (LRCs) with good locality and availability from binary Simplex codes. We first propose a Combination code having the generator matrix with all the columns of positive weights less than or equal to a given value. Such a code can be also obtained by puncturing all the columns of weights larger than a given value from a binary Simplex Code. We call by block-puncturing such puncturing method. Furthermore, we suggest a heuristic puncturing method, called subblock-puncturing, that punctures a few more columns of the largest weight from the Combination code. We determine the minimum distance, locality, availability, joint information locality, joint information availability of Combination codes in closed-form. We also demonstrate the optimality of the proposed codes with certain choices of parameters in terms of some well-known bounds.

In this paper, we propose a novel method to extrinsically calibrate a camera to a 3D reference object that is not directly visible from the camera. We use a human cornea as a spherical mirror and calibrate the extrinsic parameters from the reflections of the reference points. The main contribution of this paper is to present a cornea-reflection-based calibration algorithm with a simple configuration: five reference points on a single plane and one mirror pose. In this paper, we derive a linear equation and obtain a closed-form solution of extrinsic calibration by introducing two ideas. The first is to model the cornea as a virtual sphere, which enables us to estimate the center of the cornea sphere from its projection. The second is to use basis vectors to represent the position of the reference points, which enables us to deal with 3D information of reference points compactly. We demonstrate the performance of the proposed method with qualitative and quantitative evaluations using synthesized and real data.

The Infrastructure as a Service (IaaS) Clouds are emerging as a promising platform for the execution of resource demanding and computation intensive workflow applications. Scheduling the execution of scientific applications expressed as workflows on IaaS Clouds involves many uncertainties due to the variable and unpredictable performance of Cloud resources. These uncertainties are modeled by probability distribution functions in past researches or totally ignored in some cases. In this paper, we propose a novel robust deadline constrained workflow scheduling algorithm which handles the uncertainties in scheduling workflows in the IaaS Cloud environment. Our proposal is a static scheduling algorithm aimed at addressing the uncertainties related to: the estimation of task execution times; and, the delay in provisioning computational Cloud resources. The workflow scheduling problem was considered as a cost-optimized, deadline-constrained optimization problem. Our uncertainty handling strategy was based on the consideration of knowledge of the interval of uncertainty, which we used to modeling the execution times rather than using a known probability distribution function or precise estimations which are known to be very sensitive to variations. Experimental evaluations using CloudSim with synthetic workflows of various sizes show that our proposal is robust to fluctuations in estimates of task runtimes and is able to produce high quality schedules that have deadline guarantees with minimal penalty cost trade-off depending on the length of the interval of uncertainty. Scheduling solutions for varying degrees of uncertainty resisted against deadline violations at runtime as against the static IC-PCP algorithm which could not guarantee deadline constraints in the face of uncertainty.

We propose waveguide to microstrip line transitions for automotive millimeter wave radar modules. The transitions perpendicularly connect one waveguide and one or two microstrip lines. The configuration is simple because it consists of a waveguide and a dielectric substrate with copper foils. Additionally the transitions do not need via holes on the substrate. It leads to lower costs and improved reliability. We have already proposed a via-less transition by using multi-stage impedance transformers. The impedance transformers are used for suppressing undesirable radiation from the transition as well as impedance matching. In this paper, we propose a new transition with the microstrip lines on the long axis of the waveguide while most transitions place the microstrip lines on the minor axis (electric field direction) of the waveguide. Though our transition uses bend structures of microstrip lines, which basically cause radiation, our optimized configuration can keep small radiation. We also design a transition with a single microstrip line. The proposed transition with 2 microstrip lines can be modified to the 1 microstrip line version with minimum radiation loss. Electromagnetic simulations confirm the small radiation levels expected. Additionally we fabricate the transitions with back to back structure and determine the transmission and radiation performance. We also fabricates the transition for a patch array antenna. We confirm that the undesirable radiation from the proposed transition is small and the radiation pattern of the array antenna is not worsen by the transition.

For voice-enabled car navigation systems that use a multi-purpose cloud speech recognition service (cloud ASR), utterance classification that is robust against speech recognition errors is needed to realize a user-friendly voice interface. The purpose of this study is to improve the accuracy of utterance classification for voice-enabled car navigation systems when inputs to a classifier are error-prone speech recognition results obtained from a cloud ASR. The role of utterance classification is to predict which car navigation function a user wants to execute from a spontaneous utterance. A cloud ASR causes speech recognition errors due to the noises that occur when traveling in a car, and the errors degrade the accuracy of utterance classification. There are many methods for reducing the number of speech recognition errors by modifying the inside of a speech recognizer. However, application developers cannot apply these methods to cloud ASRs because they cannot customize the ASRs. In this paper, we propose a system for improving the accuracy of utterance classification by modifying both speech-signal inputs to a cloud ASR and recognized-sentence outputs from an ASR. First, our system performs speech enhancement on a user's utterance and then sends both enhanced and non-enhanced speech signals to a cloud ASR. Speech recognition results from both speech signals are merged to reduce the number of recognition errors. Second, to reduce that of utterance classification errors, we propose a data augmentation method, which we call “optimal doping,” where not only accurate transcriptions but also error-prone recognized sentences are added to training data. An evaluation with real user utterances spoken to car navigation products showed that our system reduces the number of utterance classification errors by 54% from a baseline condition. Finally, we propose a semi-automatic upgrading approach for classifiers to benefit from the improved performance of cloud ASRs.

Lasso regression based on the L1 regularization is one of the most popular sparse estimation methods. It is often required to set appropriately in advance the regularization parameter that determines the degree of regularization. Although the empirical Bayes approach provides an effective method to estimate the regularization parameter, its solution has yet to be fully investigated in the lasso regression model. In this study, we analyze the empirical Bayes estimator of the one-parameter model of lasso regression and show its uniqueness and its properties. Furthermore, we compare this estimator with that of the variational approximation, and its accuracy is evaluated.

Locally repairable codes, which can repair erased symbols from other symbols, have attracted a good deal of attention in recent years because its local repair property is effective on distributed storage systems. (ru, δu)u∈[s]-locally repairable codes with multiple localities, which are an extension of ordinary locally repairable codes, can repair δu-1 erased symbols simultaneously from a set consisting of at most ru symbols. An upper bound on the minimum distance of these codes and a construction method of optimal codes, attaining this bound with equality, were given by Chen, Hao, and Xia. In this paper, we discuss the parameter restrictions of the existing construction, and we propose explicit constructions of optimal codes with multiple localities with relaxed restrictions based on the encoding polynomial introduced by Tamo and Barg. The proposed construction can design a code whose minimum distance is unrealizable by the existing construction.