A New Speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road.Traffic Sign Recognition System(TSRS)is one of themost important components ofADAS.Among the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time.Accordingly,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules.Firstly,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured frames.Secondly,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise recognition.In addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting technique.Through rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,respectively.Furthermore,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.

Research on the Identification of Core Technologies of China’s Pharmaceutical Cold Chain Based on Patent Analysis

Objective To study the identification method that aims at the research and development target and makes the limited resources be optimized.With the frequent occurrence of potential drug safety hazards and the vigorous development of biomedicine,China’s pharmaceutical cold chain is facing huge opportunities and challenges.Under this background,it’s vital to promote the research and development of Chinese pharmaceutical cold chain technology.Methods First,China’s pharmaceutical cold chain patents were sorted out through the literature research method and patent analysis method,de-noises and cleans the data,uses the international patent classification(IPC)numbers as the pharmaceutical cold chain technology.Then,the IPC number co-occurrence matrix was constructed.Third,UCINET was used to visualize,draw the IPC number co-occurrence network.After that,K-cores analysis was applied to initially screen the core technology so as to build a comprehensive evaluation index system to evaluate the core technologies.Finally,Condorcet voting method was used to integrate the evaluation results to identify the core technologies.Results and Conclusion Based on this method,it can provide theoretical guidance for the development and decision-making of Chinese pharmaceutical cold chain enterprises,helping them break through technical barriers and improving the efficiency of Chinese pharmaceutical cold chain logistics.

Identification and Prediction of Core Technologies in China’s Vaccine Field Based on Patent Dimension

Objective To study the core technology in the field of vaccines from the perspective of patents,so as to provide reference for China’s vaccine research and development(R&D)enterprises when formulating development strategies.Methods Social network analysis combined with various central indicators was used to identify the core technologies in the vaccine field and the market value of the identified core technologies was evaluated through recency-frequency-monetary(RFM)customer market value assessment model.Finally,the Condorcet voting method was applied for prediction.Results and Conclusion At present,the core technology of the vaccine field is concentrated in A61P31,which has both technical and market value with great potentials.Based on this,this paper proposes that China’s vaccine industry should shift the focus of R&D from the disease treatment to prevention.R&D enterprises should also follow the overall development trend to carry out vaccine R&D activities.