Searchable encryption with advanced query function is an important technique in today's cloud environment. To date, in the public key setting, the best query function supported by the previous schemes are conjunctive or disjunctive keyword search, which are elementary but not enough to satisfy the user's query requirements. In this paper, we make a progress for constructing a searchable public key encryption scheme with advanced query function called simple Boolean keyword search. To create our scheme, we proposed a keywords conversion method that projects the index and query keywords into a group of vectors. Based on a combination of these obtained vectors and an adaptively secure inner product encryption scheme, a public key encryption with simple Boolean keyword search scheme is proposed. We also present both theoretical and experimental analysis to show the effectiveness of this scheme. To the best of our knowledge, it is the first time to give a searchable public key encryption scheme supporting queries like q1op1q2op2…opi-1qiopi…opn-1qn, where opi is a logical operator which can be and(∨) or or(∧) and qi is a keyword.

The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffic signal control system. The proposed architecture comprises a data storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffic signal control strategy. Consequently, traffic congestion in urban areas can be alleviated by adopting ACTAM.

Testing the radio frequency compatibility between Cn-band Satellite Navigation and Microwave Landing System (MLS) has included establishing a specific interference model and reporting the effect of such interference. This paper considers two interference scenarios according to the interfered system. By calculating the Power Flux Density (PFD) values, the interference for Cn-band satellite navigation downlink signal from several visible space stations on MLS service is evaluated. Simulation analysis of the interference for MLS DPSK-data word signal and scanning signal on Cn-band satellite navigation signal is based on the Spectral Separation Coefficient (SSC) and equivalent Carrier-to-Noise Ratio methodologies. Ground tests at a particular military airfield equipped with MLS ground stations were successfully carried out, and some measured data verified the theoretical and numerical results. This study will certainly benefit the design of Cn-band satellite navigation signals and guide the interoperability and compatibility research of Cn-band satellite navigation and MLS.

We introduce a new type of Montgomery-like square root formulae in GF(2m) defined by an arbitrary irreducible trinomial, which is more efficient compared with classic square root operation. By choosing proper Montgomery factors for different kind of trinomials, the space and time complexities of such square root computations match or outperform the best results. A practical application of the Montgomery-like square root in inversion computation is also presented.

The PCHS (Park-Chang-Hong-Seo) algorithm is a varied Karatsuba algorithm (KA) that utilizes a different splitting strategy with no overlap module. Such an algorithm has been applied to develop efficient hybrid GF(2m) multipliers for irreducible trinomials and pentanomials. However, compared with KA-based hybrid multipliers, these multipliers usually match space complexity but require more gates delay. In this paper, we proposed a new design of hybrid multiplier using PCHS algorithm for irreducible all-one polynomial. The proposed scheme skillfully utilizes redundant representation to combine and simplify the subexpressions computation, which result in a significant speedup of the implementation. As a main contribution, the proposed multiplier has exactly the same space and time complexities compared with the KA-based scheme. It is the first time to show that different splitting strategy for KA also can develop the same efficient multiplier.

Surface integrity of 3D medical data is crucial for surgery simulation or virtual diagnoses. However, undesirable holes often exist due to external damage on bodies or accessibility limitation on scanners. To bridge the gap, hole-filling for medical imaging is a popular research topic in recent years [1]-[3]. Considering that a medical image, e.g. CT or MRI, has the natural form of a tensor, we recognize the problem of medical hole-filling as the extension of Principal Component Pursuit (PCP) problem from matrix case to tensor case. Since the new problem in the tensor case is much more difficult than the matrix case, an efficient algorithm for the extension is presented by relaxation technique. The most significant feature of our algorithm is that unlike traditional methods which follow a strictly local approach, our method fixes the hole by the global structure in the specific medical data. Another important difference from the previous algorithm [4] is that our algorithm is able to automatically separate the completed data from the hole in an implicit manner. Our experiments demonstrate that the proposed method can lead to satisfactory results.

A novel resonant eight-way divider/combiner based on a double-layer finline is presented and studied. Experiments on the compact eight-way passive divider/combiner demonstrate a minimum overall insertion loss of 1 dB at 35.3 GHz, and the inserting loss across 34-36 GHz is less than 1.9 dB.

A novel resonant four-way divider/combiner based on finline is presented and studied. This divider/combiner designed in 34-36 GHz is composed of new probe coupling units between finline to microstrip lines. The measured power-combining efficiency of this circuit at 34.85 GHz is 83%.

A novel ratio-oriented definition based on 2T2R (Two transistors & two phase change resistors) phase change memory (PCM) cell structure is proposed to gain a high density by multilevel storage. In this novel solution, no reference is needed and good robustness remains still as conventional 2T2R, which is crucial when feature size scales to nanometer technology node. A behavioral SPICE model together with a preliminary simulation proves the idea to be feasible, and further optimization has been carried out. In addition, based on the ratio-oriented definition, a simpler and faster Error Control Coding (ECC) can be realized with n-Error-detection feasible.

In this paper, an efficient multi-modal medical image fusion approach is proposed based on local features contrast and bilateral sharpness criterion in nonsubsampled contourlet transform (NSCT) domain. Compared with other multiscale decomposition analysis tools, the nonsubsampled contourlet transform not only can eliminate the “block-effect” and the “pseudo-effect”, but also can represent the source image in multiple direction and capture the geometric structure of source image in transform domain. These advantages of NSCT can, when used in fusion algorithm, help to attain more visual information in fused image and improve the fusion quality. At the same time, in order to improve the robustness of fusion algorithm and to improve the quality of the fused image, two selection rules should be considered. Firstly, a new bilateral sharpness criterion is proposed to select the lowpass coefficient, which exploits both strength and phase coherence. Secondly, a modified SML (sum modified Laplacian) is introduced into the local contrast measurements, which is suitable for human vision system and can extract more useful detailed information from source images. Experimental results demonstrate that the proposed method performs better than the conventional fusion algorithm in terms of both visual quality and objective evaluation criteria.

In this letter, a novel wideband traveling wave power divider/combiner based on the finline with irises is presented and studied. Experiments on the four-way passive divider/combiner demonstrate a minimum overall insertion loss of 1.5 dB at 35.8 GHz, and the insertion loss across 32-38 GHz is less than 2.5 dB.

A novel 3D RRAM concept using a stackable multi-layer 1TXR memory cell structure is proposed. The access transistor is fabricated in silicon, which has excellent affinity to the standard CMOS process. Using an 8-layer metal of stacked 1TXR (X=64) as an example, the density is over 260% higher than that of the conventional single layer 1T1R structure. Further, a corresponding operation algorithm is put forward, which can inhibit effectively mis-write and mis-read caused by sneaking current and reduce power consumption.

A novel method for single image super resolution without any training samples is presented in the paper. By sparse representation, the method attempts to recover at each pixel its best possible resolution increase based on the self similarity of the image patches across different scale and rotation transforms. The experiments indicate that the proposed method can produce robust and competitive results.

In recent years, the applications of deep learning have facilitated the development of green intelligent transportation system (ITS), and carbon dioxide estimation has been one of important issues in green ITS. Furthermore, the carbon dioxide estimation could be modelled as the fuel consumption estimation. Therefore, a clustering-based neural network is proposed to analyze clusters in accordance with fuel consumption behaviors and obtains the estimated fuel consumption and the estimated carbon dioxide. In experiments, the mean absolute percentage error (MAPE) of the proposed method is only 5.61%, and the performance of the proposed method is higher than other methods.

We introduce a new type of exponentiation algorithm in GF(2m) using Euclidean inversion. Our approach is based on the fact that Euclidean inversion cost much less logic gates than ordinary multiplication in GF(2m). By applying signed binary form of the exponent instead of classic binary form, the proposed algorithm can reduce the number of operations further compared with the classic algorithms.