Smaller antenna structures for long-range radar transmitters and receivers operating in the 77-GHz band for automotive application have been achieved by using antennas with a horn, lens, and microstrip antenna. The transmitter (Tx) antenna height was reduced while keeping the antenna gain high and the antenna substrate small by developing an antenna structure composed of two differential horn and lens antennas in which the diameter and focus distance of the lenses were half those in the previous design. The microstrip antennas are directly connected to the differential outputs of a monolithic microwave integrated circuit. A Tx antenna fabricated using commercially available materials was 14mm high and had an output-aperture of 18×44mm. It achieved an antenna gain of 23.5dBi. The antenna substrate must be at least 96mm2. The antenna had a flat beam with half-power elevation and azimuth beamwidths of 4.5° and 21°, respectively. A receiver (Rx) antenna array composed of four sets of horn and lens antennas with an output-aperture of 9×22mm and a two-by-two array configuration was fabricated for application in a newly proposed small front-end module with azimuth direction of arrival (DOA) estimation. The Rx antenna array had an antenna coupling of less than -31dB in the 77-GHz band, which is small enough for DOA estimation by frequency-modulated continuous wave radar receivers even though the four antennas are arranged without any separation between their output-apertures.

This paper presents on-wafer noise figure (NF) de-embedding method of differential low noise amplifier (LNA). The characterization of NF was set up and referred as multi-stage network. The Friis law was applied to improve from the noise contributions from the subsequent stages. The correlated differential NF is accurately obtained after de-embedding the noise contribution from the interconnections and external components. Details of equations and measurement procedure are reported in this work. A 2.4GHz differential LNA was tested to demonstrate the feasibility of measurement and showed precise NF compared with other methods. The result shows an NF of 0.57dB achieved using de-embedding method and 1.06dB obtained without the de-embedding method. This is an improvement of 0.49dB of NF measurement.

This paper presents a series of secure PIN/password input methods resilient to shoulder hacking. When a person inputs a PIN or password to a smartphone, tablet, banking terminal, etc., there is a risk of shoulder hacking of the PIN or the password being stolen. To decrease the risk, we propose a method that erases key-top labels, moves them smoothly and simultaneously, and lets the user touch the target key after they stopped. The user only needs to trace a single key, but peepers have to trace the movements of all the keys at the same time. We extend the method by assigning different colors, shapes, and/or sizes to keys for enhancing distinguishability, which allows all the keys to be moved instantaneously after key-top labels are erased and the user to touch the target key. We also introduce a “move backward/forward” function that allows the user to play back the movements. This series of methods does not have the highest security, but it is easy to use and does not require any changes to the server side. Results of a performance evaluation demonstrate that this method has high resistance to shoulder hacking while providing satisfactory usability without large input errors.

Web service users are overwhelmed by the amount of information presented to them and have difficulties in finding the information that they need. Therefore, a recommendation system that predicts users' taste is an essential factor for the success of businesses. However, recommendation systems require users' personal information and can thus lead to serious privacy violations. To solve this problem, many research has been conducted about protecting personal information in recommendation systems and implementing differential privacy, a privacy protection technique that inserts noise into the original data. However, previous studies did not examine the following factors in applying differential privacy to recommendation systems. First, they did not consider the sparsity of user rating information. The total number of items is much more than the number of user-rated items. Therefore, a rating matrix created for users and items will be very sparse. This characteristic renders the identification of user patterns in rating matrixes difficult. Therefore, the sparsity issue should be considered in the application of differential privacy to recommendation systems. Second, previous studies focused on protecting user rating information but did not aim to protect the lists of user-rated items. Recommendation systems should protect these item lists because they also disclose user preferences. In this study, we propose a differentially private recommendation scheme that bases on a grouping method to solve the sparsity issue and to protect user-rated item lists and user rating information. The proposed technique shows better performance and privacy protection on actual movie rating data in comparison with an existing technique.

(m+k,m)-functions with good cryptographic properties when 1≤k

Difference systems of sets (DSSs) introduced by Levenstein are combinatorial structures used to construct comma-free codes for synchronization. In this letter, two classes of optimal DSSs are presented. One class is obtained based on q-ary ideal sequences with d-form property and difference-balanced property. The other class of optimal and perfect DSSs is derived from perfect ternary sequences given by Ipatov in 1995. Compared with known constructions (Zhou, Tang, Optimal and perfect difference systems of sets from q-ary sequences with difference-balanced property, Des. Codes Cryptography, 57(2), 215-223, 2010), the proposed DSSs lead to comma-free codes with nonzero code rate.

This paper proposes a successive interference cancellation (SIC) of independent component analysis (ICA) aided spatial division multiple access (SDMA) for Gaussian filtered frequency shift keying (GFSK) in Bluetooth low energy (BLE) systems. The typical SDMA scheme requires estimations of channel state information (CSI) using orthogonal pilot sequences. However, the orthogonal pilot is not embedded in the BLE packet. This fact motivates us to add ICA detector into BLE systems. In this paper, focusing on the covariance matrix of ICA outputs, SIC can be applied with Cholesky decomposition. Then, in order to address the phase ambiguity problems created by the ICA process, we propose a differential detection scheme based on the MAP algorithm. In practical scenarios, it is subject to carrier frequency offset (CFO) as well as symbol timing offset (STO) induced by the hardware impairments present in the BLE peripherals. The packet error rate (PER) performance is evaluated by computer simulations when BLE peripherals simultaneously communicate in the presence of CFO and STO.

Side-channel Attack, such as simple power analysis and differential power analysis (DPA), is an efficient method to gather the key, which challenges the security of crypto chips. Side-channel Attack logs the power trace of the crypto chip and speculates the key by statistical analysis. To reduce the threat of power analysis attack, an innovative method based on random execution and register randomization is proposed in this paper. In order to enhance ability against DPA, the method disorders the correspondence between power trace and operands by scrambling the data execution sequence randomly and dynamically and randomize the data operation path to randomize the registers that store intermediate data. Experiments and verification are done on the Sakura-G FPGA platform. The results show that the key is not revealed after even 2 million power traces by adopting the proposed method and only 7.23% slices overhead and 3.4% throughput rate cost is introduced. Compared to unprotected chip, it increases more than 4000× measure to disclosure.

This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.

Safety critical systems are often modeled using Time Petri Nets (TPN) for analyzing their reliability with formal verification methods. This paper proposed an efficient verification method for TPN introducing bounded model checking based on satisfiability solving. The proposed method expresses time constraints of TPN by Difference Logic (DL) and uses SMT solvers for verification. Its effectiveness was also demonstrated with an experiment.

Differential code biases (DCBs) are important parameters that must be estimated accurately for precise positioning and Satellite Based Augmentation Systems (SBAS) ionospheric related parameter generation. In this paper, in order to solve the performance degradation problem of the traditional minimum STD searching algorithm in disturbed ionosphere status and in geomagnetic low latitudes, we propose a linear planar based minimum STD searching algorithm. Firstly, we demonstrate the linear planar trend of the local vertical TEC and introduce the linear planar model based minimum standard variance searching method. Secondly, we validate the correctness of our proposed method through theoretical analysis and propose bias detection to avoid large estimation bias. At last, we show the performance of our proposed method under different geomagnetic latitudes, different seasons and different ionosphere status. The experimental results show that for the traditional minimum STD searching algorithm based on constant model, latitude difference is the key factor affecting the performance of DCB estimation. The DCB estimation performance in geomagnetic mid latitudes is the best, followed by the high latitudes and the worst is for the low latitudes. While the algorithm proposed in this paper can effectively solve the performance degradation problem of DCB estimation in geomagnetic low latitudes by using the linear planar model which is with a higher degree of freedom to model the local ionosphere characteristics and design dJ to screen the epochs. Through the analysis of the DCB estimation results of a large number of stations, it can be found that the probability of large estimation deviation of the traditional method will increase obviously under the disturb ionosphere conditions, but the algorithm we proposed can effectively control the amplitude of the maximum deviation and alleviate the probability of large estimation deviation in disturb ionosphere status.

This paper proposes a temporal domain difference based secondary background modeling algorithm for surveillance video coding. The proposed algorithm has three key technical contributions as following. Firstly, the LDBCBR (Long Distance Block Composed Background Reference) algorithm is proposed, which exploits IBBS (interval of background blocks searching) to weaken the temporal correlation of the foreground. Secondly, both BCBR (Block Composed Background Reference) and LDBCBR are exploited at the same time to generate the temporary background reference frame. The secondary modeling algorithm utilizes the temporary background blocks generated by BCBR and LDBCBR to get the final background frame. Thirdly, monitor the background reference frame after it is generated is also important. We would update the background blocks immediately when it has a big change, shorten the modeling period of the areas where foreground moves frequently and check the stable background regularly. The proposed algorithm is implemented in the platform of IEEE1857 and the experimental results demonstrate that it has significant improvement in coding efficiency. In surveillance test sequences recommended by the China AVS (Advanced Audio Video Standard) working group, our method achieve BD-Rate gain by 6.81% and 27.30% comparing with BCBR and the baseline profile.

In this paper, we propose an automatic design support system for compact acoustic devices such as microspeakers inside smartphones. The proposed design support system outputs the dimensions of compact acoustic devices with the desired acoustic characteristic. This system uses a deep neural network (DNN) to obtain the relationship between the frequency characteristic of the compact acoustic device and its dimensions. The training data are generated by the acoustic finite-difference time-domain (FDTD) method so that many training data can be easily obtained. We demonstrate the effectiveness of the proposed system through some comparisons between desired and designed frequency characteristics.

Deep neural network (NN) has been widely accepted for enabling various AI applications, however, the limitation of computational and memory resources is a major problem on mobile devices. Quantized NN with a reduced bit precision is an effective solution, which relaxes the resource requirements, but the accuracy degradation due to its numerical approximation is another problem. We propose a novel quantized NN model employing the “dithering” technique to improve the accuracy with the minimal additional hardware requirement at the view point of the hardware-algorithm co-designing. Dithering distributes the quantization error occurring at each pixel (neuron) spatially so that the total information loss of the plane would be minimized. The experiment we conducted using the software-based accuracy evaluation and FPGA-based hardware resource estimation proved the effectiveness and efficiency of the concept of an NN model with dithering.

MDS transformation plays an important role in resisting against differential cryptanalysis (DC) and linear cryptanalysis (LC). Recently, M. Sajadieh, et al.[15] designed an efficient recursive diffusion layer with Feistel-like structures. Moreover, they obtained an MDS transformation which is related to a linear function and the inverse is as lightweight as itself. Based on this work, we consider one specific form of linear functions to get the diffusion layer with low XOR gates for the hardware implementation by using temporary registers. We give two criteria to reduce the construction space and obtain six new classes of lightweight MDS transformations. Some of our constructions with one bundle-based LFSRs have as low XOR gates as previous best known results. We expect that these results may supply more choices for the design of MDS transformations in the (lightweight) block cipher algorithm.

Due to its simplicity and efficiency, differential evolution (DE) has gained the interest of researchers from various fields for solving global optimization problems. However, it is prone to premature convergence at local minima. To overcome this drawback, a novel hybrid dragonfly algorithm with differential evolution (Hybrid DA-DE) for solving global optimization problems is proposed. Firstly, a novel mutation operator is introduced based on the dragonfly algorithm (DA). Secondly, the scaling factor (F) is adjusted in a self-adaptive and individual-dependent way without extra parameters. The proposed algorithm combines the exploitation capability of DE and exploration capability of DA to achieve optimal global solutions. The effectiveness of this algorithm is evaluated using 30 classical benchmark functions with sixteen state-of-the-art meta-heuristic algorithms. A series of experimental results show that Hybrid DA-DE outperforms other algorithms significantly. Meanwhile, Hybrid DA-DE has the best adaptability to high-dimensional problems.

As a generalization of perfect nonlinear (PN) functions, zero-difference balanced (ZDB) functions play an important role in coding theory, cryptography and communications engineering. Inspired by a foregoing work of Liu et al. [1], we present a class of ZDB functions with new parameters based on the cyclotomy in finite fields. Employing these ZDB functions, we obtain simultaneously optimal constant composition codes and perfect difference systems of sets.

Accurate estimation of the state-of-charge is a crucial need for the battery, which is the most important power source in electric vehicles. To achieve better estimation result, an accurate battery model with optimum parameters is required. In this paper, a gradient-free optimization technique, namely tree seed algorithm (TSA), is utilized to identify specific parameters of the battery model. In order to strengthen the search ability of TSA and obtain more quality results, the original algorithm is improved. On one hand, the DE/rand/2/bin mechanism is employed to maintain the colony diversity, by generating mutant individuals in each time step. On the other hand, the control parameter in the algorithm is adaptively updated during the searching process, to achieve a better balance between the exploitation and exploration capabilities. The battery state-of-charge can be estimated simultaneously by regarding it as one of the parameters. Experiments under different dynamic profiles show that the proposed method can provide reliable and accurate estimation results. The performance of conventional algorithms, such as genetic algorithm and extended Kalman filter, are also compared to demonstrate the superiority of the proposed method in terms of accuracy and robustness.

Smart-routers develop greatly in recent years as one of the representative products of IoT and Smart home. Different from traditional routers, they have storage and processing capacity. Actually, smart-routers in the same location or ISP have better link conditions and can provide high quality service to each other. Therefore, for the content required services, how to construct the overlay network and efficiently deploy replications of popular content in smart-routers' network are critical. The performance of existing centralized models is limited by the bottleneck of the single point's performance. In order to improve the stability and scalability of the system through the capability of smart-router, we propose a novel intelligent and decentralized content diffusion system in smart-router network. In the system, the content will be quickly and autonomously diffused in the network which follows the specific requirement of coverage rate in neighbors. Furthermore, we design a heuristic node selection algorithm (MIG) and a replacement algorithm (MCL) to assist the diffusion of content. Specifically, system based MIG will select neighbor with the maximum value of information gain to cache the replication. The replication with the least loss of the coverage rate gain will be replaced in the system based on MCL. Through the simulation experiments, at the same requirement of coverage rate, MIG can reduce the number of replications by at least 20.2% compared with other algorithms. Compared with other replacement algorithms, MCL achieves the best successful service rate which means how much ratio of the service can be provided by neighbors. The system based on the MIG and MCL can provide stable service with the lowest bandwidth and storage cost.

We numerically demonstrate a possibility on-off keying (OOK) type of modulation over tens gigabits per second for sub-terahertz radiation in our proposed wireless transmitter device structure towards radio over fiber (RoF) technology. The integrated device consists of an InP-based compound semiconductor resonant tunneling diode (RTD) adjacent to an InP-based photo diode (PD), a self-complementary type of bow-tie antenna (BTA), external microstrip lines. These integration structures are carefully designed to obtain robust relaxation oscillation (RO) due to the negative differential conductance (NDC) characteristic of the RTD and the nonlinearity of the NDC. Moreover, the device is designed to exhibit OOK modulation of RO due to photo current from the PD inject into the RTD. Electromagnetic simulations and nonlinear equivalent circuit model of the whole device structure are established to perform large signal analysis numerically with considerations of previously measured characteristics of the triple-barrier RTD.