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In Shamir’s (k,n) secret sharing scheme, the distributor splits a secret into n shares(shadows), and sends the shares to n participants. Each participant has a different share. In the phase of secret reconstruction, only K or more participants with their shares can reconstruct the secret together, less than K participants can’t reconstruct the secret, and know nothing about the secret. Shamir’s scheme is unconditionally secure in theory. However, this scheme can’t prevent adversaries from cheating. In asynchronous communication, a dishonest participant or a foreign adversary sends a fake share to the honest participants after he gets the shares from other participants and will reconstruct the secret alone while the other honest participants cannot reconstruct the secret. This scheme does not verify the share and identify the participants. In this paper, an efficient share verification method based on Merkel tree will be discussed, in which the root and authentication paths of a Merkel tree are used to verify shares between the participants, so that they can reconstruct secrets correctly after verifying and eliminating the fake shares. This method does not need complex algorithms and estimating the number of cheaters in advance, and will not increase the size of each share.

Energy-efficient scheduling problem in wireless communication system is investigated in this paper. We propose two near-optimal schedulers which have simple structures for the general hard delay constraint scenario. Both single-user and multiuser cases are considered. The first scheduler invokes Gaussian approximation while the second one is inspired by the inverse water-filling (IWF) approach. The scheduling policies consist of a channel-awareness term and a delay-awareness term. Numerical results show that the proposed policies achieve near optimal performance when the total required transmit bits, R, is large. For the multiuser scenario, our scheduling strategy consists of an initial resource (number of time slots) allocation and a slot-by-slot user selection and bit loading algorithm. The former depends on the rate requirement and a priori knowledge of user-dependent channel statistic while the latter use an order statistic based approach designed to minimize the expected total energy consumption.

The IEEE 802.16 standard for broadband wireless access, known as Worldwide Interoperability for Microwave Access (WiMAX), provides high throughput over long-range transmission. The key developments in the physical (PHY) layer include Orthogonal Frequency-Division Multiple Access (OFDMA) and the Multiple-Input-Multiple-Output (MIMO) antenna technology, which enhance transmission quality and throughput.

Intelligent control based on fuzzy model reference learning control (FMRLC) is being applied to hydraulic power sets, which are characterized by their nonlinearity, time variability and non-minimum phase free property, after having first studied principles of and methods used by FMRLC, and analyzed its capability of adjusting and correcting fuzzy rules. A FMRLC controller for a hydraulic power set was subsequently designed, which is capable of adjusting its fuzzy rules according to the controlled object's output deviations compared with the ideal reference model's output. Herewith, the hydro power set's output is made to follow that of the reference model on a real time basis. Simulation results show that this method of control not only suits to hydraulic power sets in cases of minor vacillation of operating conditions, but also for large ones. Nevertheless, further exploring work is required for practical application purposes.

A novel trend emerged in music exploration is to organize and search songs according to their emotions. However, research on automatic playlist generation (APG) primarily focuses on metadata and audio similarity. Mainstream solutions view APG as a static problem. This paper argues that the APG problem is better modeled as a continuous optimization problem, and proposes an adaptive preference model for personalized APG based on emotions. The main idea is to collect a user’s behavior in music playing, e.g., rating, skipping and replaying, as immediate feedback in learning the user’s preferences for music emotion within a playlist. Reinforcement learning is adopted to learn the user’s current preferences, which are used to generate personalized playlists. Learning parameters are tuned by simulation of two hypothetical users. A two-month user study is conducted to evaluate the APG solutions. The results show that the proposed approach reduces the Miss Ratio by 10% in comparison with the baseline approach.

In this work, a novel architecture with stacked-type CMOS device is presented. The reformed CMOS switch was implemented by the TSMC 0.18 um 1P6M standard CMOS process. In order to improve power handling capability and strengthen the isolation, the proposed circuit is inserted with an excess transistor adjacent to the receiver side. The insertion loss of the designed CMOS T/R switch is about 1.9plusmn0.3 dB. The isolation is greater than 25 dB and the power handling is capable of 28 dBm at 5.8 GHz.

Nano-powders of p-type transparent conductive copper aluminum oxide (CAO) have been successfully synthesized by co-precipitation method. By adding sodium hydroxide into the mixed solution of copper chloride and aluminum chloride, co-precipitate precursors of CAO with particle size around 50-60 nm were produced After washing, filtering, and drying of the co-precipitates, nano-powders of CuAlO2 were produced when the dried co-precipitate precursors were calcined at temperature above 1100degC. By aging at pH = 3.5 for six hours and co-precipitating at pH = 8.0, the atomic ratio of Cu/Al of the nano-powders can be maintained throughout the synthesis. After calcining at 12000 in air for 4 hours, the CAO co-precipitate precursors totally transformed into nano-powders of CuAlO2 with crystal size around 64 nm. Continued calcining at 1200degC above 4 hours led to the decomposition of CuAlO2 into nano-powders of CuAl2O4 and volatile CuO with no significant change in crystal size. Finally, it was found that by calcining under inert atmosphere, the decomposition of CuAlO2 could be suppressed at the expense of decreasing its crystallinity.

Nano-sized powders of transparent conductive aluminum-doped zinc oxide (AZO) have been successfully prepared by electrolysis-modified co-precipitation method. By adding ammonium hydroxide into the precursor solution prepared by electrolytic dissolution of zinc metal in a buffered electrolyte solution of nitric acid and ammonium nitrate with adequate addition of aluminum nitrate, co-precipitate precursors of AZO with particle size between 30 to 60 nm were produced. After washing, filtering, and drying of the co-precipitates, nano-powders of AZO with wurtzite structure were produced when the dried co-precipitate precursors were calcined at temperature above 800degC. By aging at pH = 5 and co-precipitating at pH = 8.0, the atomic ratio of Al/Zn of the nano-powders could be maintained throughout the synthesis. After calcining at 1000degC in air for 2 hours, nano-sized powders of AZO with ZnO wurtzite structure and particle size between 200 to 500 nm were synthesized. Finally, it was found that both the particle sizes of co-precipitate precursors and calcined nano-powders of AZO could be decreased by increasing the pH of the electrolyte solution for electrolytic dissolution.

Wireless sensor networks are emerging as a popular research issue and tool for many applications. However, nodes in a sensor network are severely constrained by energy, storage capacity and computing power. In this paper, we propose an integrated network environment (sensor and ad hoc network) with IEEE 802.15.4a, ultra-wideband (UWB) and two-tier data dissemination (TTDD) routing protocol. We wish that sensor network could support fast dynamic location-tracking, information gathering and response. And base station use theses information to compute an optimal path for ad hoc mobile devices to offer good QoS level and reliable data transmission according to different requests

The third generation (3G) wireless networks are characterized by connectivity in anytime, anywhere, enhanced data services, and higher data rates to mobile users. It is an important and to be worthy of research issue which elucidates that how to provide mobile users for roaming among different access technology networks through seamless handoff mechanism. IPv6 plays an important role in wireless access networks. To integrate with heterogeneous wireless networks, adopting IP backbone is the best solution. Moreover, it supports that the mobile users roam seamlessly by mobile IP technology. The major objective of this paper is to propose an integrated architecture for UMTS network and IEEE 802.11 WLAN. We also propose a mobile IPv6 based seamless handoff strategy for heterogeneous wireless networks to provide mobility management between UMTS and IEEE 802.11 WLAN for the mobile users.