Breast cancer, which is one of the most common types of cancer among women worldwide, is responsible for claiming numerous lives annually, resulting in almost 600,000 fatalities. The key to achieving successful treatment lies in the early identification of the disease. The continuous progress in artificial intelligence has revolutionized the potential for accurately diagnosing and treating breast cancer. This research centers on the practical implementation of convolutional neural networks, a form of artificial intelligence, in recognizing breast cancer. The outcomes indicate that this particular method substantially improves the speed of detection, allowing medical professionals to render more precise judgments in a considerably reduced timeframe.

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This paper describes a method for synchronizing two chaotic systems with three-dimensional heterogeneous structures. We introduced a mathematical model and designed a new synchronous controller that can synchronize the system from different initial values. This paper analyzes the advantages and disadvantages of the synchronous controller, and also uses MATLAB software to generate the error curve of the synchronous system when the synchronous controller is activated on the response system, and shows its effectiveness.

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The new guide cap utilizes an STM32 microcontroller as its control core, enabling a range of advanced features such as obstacle avoidance, intelligent recognition, voice interaction, and GPS positioning. The system incorporates the OpenMV4 Cam H7 Plus intelligent camera to provide continuous real-time monitoring and accurate feedback on important road information such as traffic lights and zebra crossings. Additionally, an ultrasonic sensor is employed to convert electrical signals into ultrasonic output, allowing for effective measurement of obstacle distances. to enhance safety, the system utilizes a Wi-Fi module and GPS positioning to transmit the user's location information in real time to nearby vehicles and pedestrians. This real-time communication ensures the maximum level of user safety.

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This paper utilises image pre-processing techniques and deep residual neural networks to enhance the traffic sign detection system. A novel Analytic Hierarchy Process (AHP) model for performance evaluation has been proposed and utilised to determine the optimal parameter configuration of the learning models. Four evaluation metrics, namely accuracy, stability, response time, and system capability, have been defined for AHP measurements. The experiments were conducted using a comprehensive dataset, with VGG-16 and Google Net implemented for comparisons. Finally, the combination of ResNet-50 and the AHP model yielded the best results, achieving a 98.01% accuracy rate, 0.09% false alarm rate, and 1.28% undetection rate.

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In order to strengthen the development of China's elderly care industry, the project has designed an intelligent crutch based on stm32 and raspberry pie. This product adds many functions on the basis of general intelligent crutches. It is equipped with real-time GPS monitoring and uploading APP. When the elderly fall, they can immediately and automatically alarm. When they fall, they can simultaneously emit an alarm sound of about 100 decibels to the surrounding. It provides a touch screen, supports voice recognition, and can achieve multiple functions. It is equipped with a step counting function, temperature and humidity display and other functions. This product uses a 5G module to communicate with the mqtt server, and then sends it to the APP through the server.

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With the rapid development of the logistics industry, the traditional logistics transportation mode has been difficult to meet the needs of modern logistics. Intelligent ground and air multi-robot cooperative transportation system can use robot technology to achieve automated and intelligent logistics transportation, improve logistics efficiency and quality, reduce logistics costs, and meet customer needs. This paper introduces a new type of intelligent ground to air multi-robot cooperative transportation system, which is designed and integrated with a variety of technologies, such as robot technology, artificial intelligence technology, Internet of Things technology, etc., to promote technological innovation and development. This paper introduces the research status and background of intelligent ground to air multi-robot cooperative transportation system, and introduces the working principle and equipment selection of the system in detail.

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This study is aimed at capturing the impact of flaming generated through social media on content by Emotion analysis and Key Graph Analysis. The analysis and discussion clarify those three points. First, humans want to mourn the death of comic strip character, as an Artificial Life. Second, Reply tends to be relatively positive throughout the entire flaming period, thus they do not fully reflect the feelings of the recipients. Third, content that has been under flaming will not stop being criticized for a long period of time, and that being flaming experience itself will be consumed as content.

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As critical infrastructure has seen substantial growth in recent years, the security of its Cyber-Physical Systems (CPS) has gained greater significance. The rapid evolution of machine learning technology is being harnessed to detect and prevent these threats. Accordingly, this study establishes a Testbed for gathering pertinent datasets to aid machine learning needs, including model training and attack analysis.

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The multi-scroll conservative chaotic system represents a novel category of chaotic systems renowned for their complex dynamics. Due to their intricate behavior, they have garnered significant interest among researchers in the field. This study focuses on the creation of a conservative multilayer chaotic system. The design involves integrating a polygon-free sinusoidal function to generate multiple scrolls within this conservative multilayer chaotic system. By incorporating nonlinear functions, this system generates one-dimensional linear multi-roll and two-dimensional multi-roll lattice distributions.

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Blind travel has always been the core issue of social concern, and how to assist the blind to travel safely has always been an urgent problem to be solved urgently. Although some intelligent blind guide products have flooded into the market in recent years, such as guide boxes, guide battles, etc., but most of their functions only stay in the obstacle avoidance stage, lack of path planning, intelligent recognition functions, blind person positioning and are not easy to carry. Based on the above shortcomings, an intelligent mobile blind guide robot is designed in this paper. The blind guide robot is equipped with a variety of sensors and combined with the powerful computing power of the main control board to form a complete obstacle avoidance system to achieve autonomous navigation and obstacle avoidance in a complex environment. It controls GPS positioning through Jetson-Nano, plans the route, detects obstacles with the help of cameras and ultrasonic sensors, and gives users feedback through the alarm sound of the buzzer.After experiments, the GPS positioning accuracy can reach 2.5m, the positioning delay time is 3s on average, and the camera recognition accuracy can reach 83.3% on average, which can meet the guidance needs of the blind in indoor and outdoor life.

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