The Cyber Threat Intelligence (CTI) marketplace is an emerging platform for CTI service requesters to countermeasure advanced cyber attacks, where CTI service providers are employed on payment. To create a trustworthy CTI marketplace environment, consortium-blockchain-based CTI service platforms have been widely proposed, where the blockchain system becomes the third role, crucially impacting the CTI service quality. How to sustainably promote CTI service quality in this tripartite marketplace is a challenging issue, which has not been well investigated in the literature. In this study, we propose a two-stage tripartite dynamic game-model-based incentive mechanism, where the participation incentives of the three parties are promoted under the constraints of Individual Rationality (IR) and Incentive Compatibility (IC). The sustainability of CTI service is quantitatively formalized through the CTI market demand, which impacts the future profits of the three parties. The Nash equilibrium of the proposed incentive mechanism is solved, where the CTI requester offers an optimal price to achieve effective defense against cyber attacks, and the blockchain platform and CTI service providers collaboratively contribute high-quality CTI services. Empirical experimental results show that the higher the quality of CTI services provided in the marketplace, the greater the market demand for CTI, resulting in a sustainable CTI marketplace.

Theoretical studies on evolutionary algorithms have developed vigorously in recent years. Many such algorithms have theoretical guarantees in both running time and approximation ratio. Some approximation mechanism seems to be inherently embedded in many evolutionary algorithms. In this paper, we identify such a relation by proposing a unified analysis framework for a global simple multiobjective evolutionary algorithm (GSEMO) and apply it on a minimum weight general cover problem, which is general enough to subsume many important problems including the minimum submodular cover problem in which the submodular function is real-valued, and the minimum connected dominating set problem for which the potential function is nonsubmodular. We show that GSEMO yields theoretically guaranteed approximation ratios matching those achievable by a greedy algorithm in expected polynomial time when the potential function g is polynomial in the input size and the minimum gap between different g-values is a constant. History: Accepted by Erwin Pesch, Area Editor for Heuristic Search & Approximation Algorithms. Funding: This work was supported by National Natural Science Foundation of China [11771013, U20A2068]; Zhejiang Provincial Natural Science Foundation of China [LD19A010001].

In a weak energy environment, the output power of a miniature piezoelectric energy harvester is typically less than 10μW. Due to the weak diode current, the rectifier diode of traditional power management circuit in micro-power energy harvester has a high on-resistance and large power consumption, causing a low charging power. In this paper, an inductor energy storage power management circuit is proposed. Weak current is stored in a high-Q-value inductor during the storage period, and is released into the rectifier circuit when the stored current is relatively high. Hence, the on-resistance of the rectifier diode is reduced with a higher rectifier current. To improve the charging power, this paper investigates the distributed capacitance of the inductor and develops a high-Q-value honeycomb inductor coil with a small distributed capacitance. Experimental results confirm that the use of the honeycomb inductor in the proposed circuit can increase the maximum charging power by 15.6% as compared to an ordinary winding inductor. In comparison with the traditional up-conversion circuit and the standard rectifier circuit, the proposed circuit provides larger average charging power at an input power of 1-10 μW.

Chinese is a language composed of syllables with tones. Initials, finals, and tones are the three main attributes of Chinese syllables. In this paper, continuous two-character-words are segmented through syllables, and the effective segmentation of syllables is performed by using the characteristics of short-time energy and short-time zero-crossing rate of initial. It is useful to extracting the pitch frequency with the autocorrelation function and average amplitude difference function method . This paper proposes a speaker-independent two-character-words fuzzy identification method and uses the main characteristics of the pitch curve to form a fuzzy membership function. The tone recognition algorithm uses the decision function to classify the tone pattern. The method has simple, reliable, and good real-time characteristics.