In this letter, we present a class of binary sequences with optimal autocorrelation magnitude. Compared with Krengel-Ivanov sequences, some proposed sequences have different autocorrelation distribution. This indicates those sequences would be new. As an application of constructed binary sequences, we derive a class of quaternary sequences of length 4p with autocorrelation magnitude equal to $2sqrt{2}$, which is lower than the autocorrelation magnitude equal to 4 of Chung-Han-Yang sequences given in 2011.

This letter investigates the physical layer security for a buffer-aided underlay cooperative cognitive radio network in the presence of an eavesdropper, wherein, the relay is equipped with a buffer so that it can store packets received from the secondary source. To improve the secure performance of cognitive radio networks, we propose a novel cognitive secure link selection scheme which incorporates the instantaneous strength of the wireless links as well as the status of relay's buffer, the proposed scheme adapts the link selection decision on the strongest available link by dynamically switching between relay reception and transmission. Closed-form expressions of secrecy outage probability (SOP) for cognitive radio network is obtained based on the Markov chain. Numerical results demonstrate that the proposed scheme can significantly enhance the secure performance compared to the conventional relay selection scheme.

Constant weight codes have mathematical interest and practical applications such as coding for bandwidth-efficient channels and construction of spherical codes for modulation. In this letter, by using difference balanced functions with d-form property, we constructed a class of constant composition code with new parameters, which achieves the equal sign of generalized Johnson bound.

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.

A new type of compact one dimension (1-D) microstrip photonic bandgap (PBG) structure for filter is presented. A miniature semiconductor-based structure band-stop filter with four cells is simulated, fabricated, and measured. Agreement between the experimental and simulation results has been achieved. The filter with four proposed PBG structure exhibits deep (about -60 dB) and steep (about 40 dB/GHz) stop-band characteristics. It also has less loss and ripples in the pass-band. The period of the PBG lattice is about 0.2 λe (λe, guiding wavelength at the center frequency of stop-band), or 0.068 λ0 (λ0 wavelength in air), and the filter is very compact and much easier for fabrication and realization in MIC and MMIC.

Counting the number of differentially active S-boxes is of great importance in evaluating the security of a block cipher against differential attack. Mouha et al. proposed a technique based on Mixed-Integer Linear Programming (MILP) to automatically calculate a lower bound of the number of differentially active S-boxes for word-oriented block ciphers, and applied it to symmetric ciphers AES and Enocoro-128v2. Later Sun et al. extended the method by introducing bit-level representations for S-boxes and new constraints in the MILP problem, and applied the extended method to PRESENT-80 and LBlock. This kind of methods greatly depends on the constraints in the MILP problem describing the differential propagation of the block cipher. A more accurate description of the differential propagation leads to a tighter bound on the number of differentially active S-boxes. In this paper, we refine the constraints in the MILP problem describing XOR operations, and apply the refined MILP modeling to determine a lower bound of the number of active S-boxes for the Lai-Massey type block cipher FOX in the model of single-key differential attack, and obtain a tighter bound in FOX64 than existing results. Experimental results show that 6, instead of currently known 8, rounds of FOX64 is strong enough to resist against basic single-key differential attack since the differential characteristic probability is upper bounded by 2-64, and thus the maximum differential characteristic probability of 12-round FOX64 is upper bounded by 2-128, where 128 is the key-length of FOX64. We also get the lower bound of the number of differentially active S-boxes for 5-round FOX128, and proved the security of the full-round FOX128 with respect to single-key differential attack.

A novel dynamic element matching (DEM) method, called binary-tree random DEM (BTR-DEM), is presented for a Nyquist-rate current-steering digital-to-analog converter (DAC). By increasing or decreasing the number of unit current sources randomly at the same time, the BTR-DEM encoding reduces switch transition glitches. A 5-bit current-steering DAC with the BTR-DEM technique is implemented in a 65-nm CMOS technology. The measured spurious free dynamic range (SFDR) attains 42 dB for a sample rate of 100 MHz and shows little dependence on signal frequency.

In this paper, we present two classes of zero difference balanced (ZDB) functions, which are derived by difference balanced functions, and a class of perfect ternary sequences respectively. The proposed functions have parameters not covered in the literature, and can be used to design optimal constant composition codes, and perfect difference systems of sets.

Heterogeneous distributed computing environments are well suited to meet the fast increasing computational demands. Task scheduling is very important for a heterogeneous distributed system to satisfy the large computational demands of applications. The performance of a scheduler in a heterogeneous distributed system normally has something to do with the dynamic task flow, that is, the scheduler always suffers from the heterogeneity of task sizes and the variety of task arrivals. From the long-term viewpoint it is necessary and possible to improve the performance of the scheduler serving the dynamic task flow. In this paper we propose a task scheduling method including a scheduling strategy which adapts to the dynamic task flow and a genetic algorithm which can achieve the short completion time of a batch of tasks. The strategy and the genetic algorithm work with each other to enhance the scheduler's efficiency and performance. We simulated a task flow with enough tasks, the scheduler with our strategy and algorithm, and the schedulers with other strategies and algorithms. We also simulated a complex scenario including the variant arrival rate of tasks and the heterogeneous computational nodes. The simulation results show that our scheduler achieves much better scheduling results than the others, in terms of the average waiting time, the average response time, and the finish time of all tasks.

A compact open-loop resonator bandpass filter is presented to suppress the spurious passband using compensated compact microstrip resonant cell (C-CMRC) feeding structure. Based on the inherently compact and stopband characteristics of the C-CMRC feeding, the proposed filters shows a better spurious rejection performance than the only open-loop resonator filter. The suppression is -57.4 dB, -49.5 dB, and -43.9 dB at the 2nd, 3rd and 4th harmonic signal separately. All the performance of proposed filters have been verified by the measured results.

The scheduling of real-time tasks with fault-tolerant requirements has been an important problem in multiprocessor systems. The primary-backup (PB) approach is often used as a fault-tolerant technique to guarantee the deadlines of tasks despite the presence of faults. In this paper we propose a dynamic PB-based task scheduling approach, wherein an allocation parameter is used to search the available time slots for a newly arriving task, and the previously scheduled tasks can be re-scheduled when there is no available time slot for the newly arriving task. In order to improve the schedulability we also propose an overloading strategy for PB-overloading and Backup-backup (BB) overloading. Our proposed task scheduling algorithm is compared with some existing scheduling algorithms in the literature through simulation studies. The results have shown that the task rejection ratio of our real-time task scheduling algorithm is almost 50% lower than the compared algorithms.

In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e.g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

This letter presents a novel two-dimensional (2-D) defected ground array (DGA) for planar circuits, which has horizontal and vertical periodicities of defect structure. The defect unit cell of DGA is composed of a Sierpinski carpet structure to improve the effective inductance. Measurements show that the proposed DGA provides steeper cutoff characteristics, lower cutoff frequency, and higher slow-wave factors than the conventional periodic defected ground structure in the same occupied surface.

At Crypto 2019, Gohr first adopted the neural distinguisher for differential cryptanalysis, and since then, this work received increasing attention. However, most of the existing work focuses on improving and applying the neural distinguisher, the studies delving into the intrinsic principles of neural distinguishers are finite. At Eurocrypt 2021, Benamira et al. conducted a study on Gohr’s neural distinguisher. But for the neural distinguishers proposed later, such as the r-round neural distinguishers trained with k ciphertext pairs or ciphertext differences, denoted as NDcpk_r (Gohr’s neural distinguisher is the special NDcpk_r with K = 1) and NDcdk_r , such research is lacking. In this work, we devote ourselves to study the intrinsic principles and relationship between NDcdk_r and NDcpk_r. Firstly, we explore the working principle of NDcd1_r through a series of experiments and find that it strongly relies on the probability distribution of ciphertext differences. Its operational mechanism bears a strong resemblance to that of NDcp1_r given by Benamira et al.. Therefore, we further compare them from the perspective of differential cryptanalysis and sample features, demonstrating the superior performance of NDcp1_r can be attributed to the relationships between certain ciphertext bits, especially the significant bits. We then extend our investigation to NDcpk_r, and show that its ability to recognize samples heavily relies on the average differential probability of k ciphertext pairs and some relationships in the ciphertext itself, but the reliance between k ciphertext pairs is very weak. Finally, in light of the findings of our research, we introduce a strategy to enhance the accuracy of the neural distinguisher by using a fixed difference to generate the negative samples instead of the random one. Through the implementation of this approach, we manage to improve the accuracy of the neural distinguishers by approximately 2% to 8% for 7-round Speck32/64 and 9-round Simon32/64.

Based on the periodical-loaded principle, a new wider stop-band filter is presented. The design equations are provided, the validity of which is proved by the measured results. Compared with loaded stub of length 1/4λg, the improved T-shape stub can change admittance paralleled with microstrip line and widen the band width of the band-stop filter. The size of the filter loaded by one side can be reduced by 2/3. The stop-band filter loaded by one side and two sides are simulated and realized. The filter loaded by two sides can achieve very wide stop-band. In addition, the stop-band of the new type of filter is deep and steep.

In this paper, a high accuracy, high efficiency, and wide current-sensing range current-mode PWM buck converter with on-chip current-sensing technique is presented. The proposed current-sensing circuit uses simple switch technique to achieve high accuracy, high power efficiency, and high line regulation. The test chip is fabricated using TSMC 0.18 µm 1P6M 3.3 V CMOS process. The measurement results show that the buck converter with on-chip current-sensing circuit can operate from 700 kHz to 3 MHz with a supply voltage of 1.5-5 V and the output voltage of 0.5-4.5 V for lithium ion battery applications. The accuracy of the proposed current-sensing circuit is exceeds 89.8% for load current from 50 mA to 500 mA and for temperature from 0C to 100C. The peak power efficiency of the buck converter is up to 95.5%.

To make the best use of the resources in a shared grid environment, an application scheduler must make a prediction of available performance on each resource. In this paper, we examine the problem of predicting available CPU performance in time-shared grid system. We present and evaluate a new and innovative method to predict the one-step-ahead CPU load in a grid. Our prediction strategy forecasts the future CPU load based on the variety tendency in several past steps and in previous similar patterns, and uses a polynomial fitting method. Our experimental results on large load traces collected from four different kinds of machines demonstrate that this new prediction strategy achieves average prediction errors which are between 22% and 86% less than those incurred by four previous methods.

Although the classical vector median filter (VMF) has been widely used to suppress the impulse noise in the color image, many thin color curve pixels aligned in arbitrary directions are usually removed out as impulse noise. This serious problem can be solved by the proposed method that can protect the thin curves in arbitrary direction in color image and remove out the impulse noise at the same time. Firstly, samples in the 3x3 filter window are considered to preliminarily detect whether the center pixel is corrupted by impulse noise or not. Then, samples outside a 5x5 filter window are conditionally and partly considered to accurately distinguish the impulse noise and the noise-free pixel. At last, based on the previous outputs, samples on the processed positions in a 3x3 filter window are chosen as the samples of VMF operation to suppress the impulse noise. Extensive experimental results indicate that the proposed algorithm can be used to remove the impulse noise of color image while protecting the thin curves in arbitrary directions.