Theoretical Design and FPGA-Based Implementation of Higher-Dimensional Digital Chaotic Systems

Traditionally, chaotic systems are built on the domain of infinite precision in mathematics. However, the quantization is inevitable for any digital devices, which causes dynamical degradation. To cope with this problem, many methods were proposed, such as perturbing chaotic states and cascading multiple chaotic systems. This paper aims at developing a novel methodology to design the higher-dimensional digital chaotic systems (HDDCS) in the domain of finite precision. The proposed system is based on the chaos generation strategy controlled by random sequences. It is proven to satisfy the Devaney's definition of chaos. Also, we calculate the Lyapunov exponents for HDDCS. The application of HDDCS in image encryption is demonstrated via FPGA platform. As each operation of HDDCS is executed in the same fixed precision, no quantization loss occurs. Therefore, it provides a perfect solution to the dynamical degradation of digital chaos.Comment: 12 page

A Numerical Study on the Temperature Field of a R290 Hermetic Reciprocating Compressor with Experimental Validation

A numerical model to predict the temperature field in a R290 hermetic reciprocating compressor is presented in this work. The control volume method and the lumped parameter method are used in the simulation. The compressor is divided into 6 control volumes, including the suction muffler, the cylinder, the discharge chamber, the discharge muffler, the discharge pipe and the shell. The system of non-linear equations is formed of the energy balance equations of every control column. The temperature field is derived by solving the equations. To valid the numerical model accurately, temperature experiment has been carried out in 3 same-type hermetic reciprocating compressors using R290 as working fluid. The simulation result shows a good agreement compared with the experiment

4,5-Bis(4-meth­oxy­phen­oxy)phthalonitrile

The title compound, C22H16N2O4, was obtained unintentionally as the product of an attempted synthesis of a new phthalocyanine. The dihedral angles formed by the central benzene ring with the aromatic rings of the meth­oxy­phen­oxy groups are 85.39 (5) and 64.19 (5)°

MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention

Problematic smartphone use negatively affects physical and mental health. Despite the wide range of prior research, existing persuasive techniques are not flexible enough to provide dynamic persuasion content based on users' physical contexts and mental states. We first conduct a Wizard-of-Oz study (N=12) and an interview study (N=10) to summarize the mental states behind problematic smartphone use: boredom, stress, and inertia. This informs our design of four persuasion strategies: understanding, comforting, evoking, and scaffolding habits. We leverage large language models (LLMs) to enable the automatic and dynamic generation of effective persuasion content. We develop MindShift, a novel LLM-powered problematic smartphone use intervention technique. MindShift takes users' in-the-moment physical contexts, mental states, app usage behaviors, users' goals & habits as input, and generates high-quality and flexible persuasive content with appropriate persuasion strategies. We conduct a 5-week field experiment (N=25) to compare MindShift with baseline techniques. The results show that MindShift significantly improves intervention acceptance rates by 17.8-22.5% and reduces smartphone use frequency by 12.1-14.4%. Moreover, users have a significant drop in smartphone addiction scale scores and a rise in self-efficacy. Our study sheds light on the potential of leveraging LLMs for context-aware persuasion in other behavior change domains