Research on Generalized Computing Systems

This paper presents a kind of artificial intelligent system-generalized computing system (GCS for short), and introduces its mathematical description, implement problem and learning problem.

A Partitioning Methodology That Optimizes the Communication Cost for Reconfigurable Computing Systems

This paper focuses on the design process for reconfigurable architecture. Our contribution focuses on introducing a new temporal partitioning algorithm. Our algorithm is based on typical mathematic flow to solve the temporal partitioning problem. This algorithm optimizes the transfer of data required between design partitions and the reconfiguration overhead. Results show that our algorithm considerably decreases the communication cost and the latency compared with other well known algorithms.

Parallel Inference for Real-Time Machine Learning Applications

Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.

Resource Reconstruction Algorithms for On-demand Allocation in Virtual Computing Resource Pool

Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.

A New Scheme to Projective Synchronization of Fractional-Order Chaotic Systems

We demonstrate that the projective synchronization can be observed in coupled fractional-order chaotic systems. A new systematic and powerful coupling scheme is developed to investigate the projective synchronization via the open-plus-closed-loop control, which allows us to arbitrarily manipulate the scaling factor of projective synchronization. The proposed scheme is proved analytically on the basis of the stability theorem of the fractional differential equations. Numerical simulations on the fraction-order chaotic Chen system are presented to justify the theoretical analysis.

Security Analysis of a Block Encryption Algorithm Based on Dynamic Sequences of Multiple Chaotic Systems

Recently, the cryptosystem based on chaos has attracted much attention. Wang and Yu （Commun. Nonlin. Sci. Numer. Simulat. 14（2009）574） proposed a block encryption algorithm based on dynamic sequences of multiple chaotic systems. We analyze the potential flaws in the algorithm. Then, a chosen-plaintext attack is presented. Some remedial measures are suggested to avoid the flaws effectively. Furthermore, an improved encryption algorithm is proposed to resist the attacks＂ and to keep all the merits of the original cryptosystem.

Stochastic Resonance in a Time-Delayed Mono-Stable System with Multiplicative and Additive Noise

The stochastic resonance （SR） in a time-delayed mono-stable system driven by multiplicative white noise, additive white noise, additive dichotomous noise as well as a periodic square-wave signal is considered from the view of the signal-to-noise ratio （SNR）. It is found that the SNR increases monotonically with the increase of the delay time. The SNR exhibits the SR behavior when it is plotted as a function of intensities of the noises, displaying the asymmetry of the dichotomous noise. The SNR varies non-monotonically with the increase of the system parameter and the amplitude of the input square-wave signal.

Entropic Stochastic Resonance Driven by Colored Noise

The phenomenon of entropic stochastic resonance （ESR） in a two-dimensional confined system driven by a transverse periodic force is investigated when the colored fluctuation is included in the system. Applying the method of unified colored noise approximation, the approximate Fokker-Planck equation can be derived in the absence of the periodic force. Through the escaping rate of the Brownian particle from one well to the other, the power spectral amplification can be obtained. It is found that increasing the values of the noise correlation time and the signal frequency can suppress the ESR of the system.

Active Mixing in a Microchannel

We investigate a minute magneto hydro-dynamic mixer with relatively rapid mixing enhancement experimentally and analytically. The mixer is fabricated with brass and polymethyl methacrylate （PMMA） layers. A secondary flow is generated by using the Lorentz force in the fluids. The efficiency of mixing is greatly improved due to the large increase of the contact area between two mixing fluids. The micro particle image velocimetry technique is employed to measure the fluid flow characteristics in the micro-channel. Numerical simulation is performed based on the theoretical model of the computational fluid dynamics and the electromagnetic field theory. The experimental results are in good agreement with the numerical results, which indicates that the mixing area is enlarged by the driving of Lorentz force and the mixing can be enhanced.

Periodic, Quasiperiodic and Chaotic q-Breathers in a Fermi-Pasta-Ulam Lattice

We study the features of a single q-breather （SQB） in a Fermi-Pasta-Ulam lattice by the numerical method, and obtain that the stability of SQB correlates to coupling constant K and nonlinear parameter β. No matter whether K or β increases, the periodic SQB can be transformed into a quasiperiodic SQB or a chaotic SQB. We also obtain the conditions of excitation of periodic, quasiperiodic and chaotic SQBs.

Condensation of Self-Driven Particles in Scale-Free Networks

A new simple model of self-driven particles in scale-free networks is introduced to understand the emergence of condensation in the natural world. In the model, at each time step, particles are driven to choose their next habitats according to the particle numbers at both the present habitats and neighbors. It is found that the hub effect results in the condensation. The present numerical results as well as the theoretical analysis of condensation transition show the criterion of condensation. Both simulations and theoretical analysis display that there are three phases for different hopping probabilities δ： non-condensation （δ〈δc）, partial condensation （δc≤ δ〈1）, and complete condensation （δ≥δc＇= 1）, and the mean occupation particle number at the stationary state is also obtained. Moreover, the noise effect on self-driven particles is studied, and it makes particle numbers at nodes tend towards being identical.

Prisoner＇s Dilemma on Co-Evolving Networks without Strategy Update

We investigate the game theory in a structured population with the assumption that the evolution of network structure is far faster than that of strategy update. We find that the degree distribution for the finM network consists of two distinct parts： the low degree part which is contributed to by defectors and a broadband in the regime with high degree which is formed by cooperators. The structure of the final network and the final strategy pattern have also been numerically proved to be independent of the game parameters.

Effect of Time Delay on Stochastic Tumor Growth

We study the dynamics of tumor cell growth with time-delayed feedback driven by multiplicative noise in an asymmetrical bistable potential well. For a small delay time, the analytical solutions of the probability distribution and the first passage time show that, with the increasing delay time, the peak of the probability distribution in a lower population state would increase, but in a higher population state it decreases. It is shown that the multiplicative noise and the time delay play opposite roles in the tumor cell growth.

Call for Papers Special Issue on Cognitive Systems and Computation

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. From 2012, the journal enters into IEEE Xplore Digital Library with the open access mode. In 2015, Tsinghua Science and Technology has been indexed in the Science Citation Index Expanded with IF 1.250.