Influencing Factors Analysis on Advertising Effectiveness of News feeds Ads

News feeds ads has became one of the mainstream mobile ads. However, there are also a series of problems behind the success of feeds ads: inaccurate recommendations, information security issues, and so on.This paper studies the influencing factors of advertising marketing effect of information flow, and puts forward corresponding suggestions, which has important guiding value for enterprise marketing under the age of big data. This research uses news feeds ads as the object, adopts literature research methods, questionnaire analysis methods, etc. Through combing related documents, we have selected three evaluation indicators: advertising cognition, advertising attitude and advertising sales. In terms of aspects and advertisements, there are seven factors influencing the reliability of the platform, the popularity of the platform, the familiarity of consumer brands, the degree of consumer participation, the degree of consumer rejection of advertisements, advertising creativity and performance, and the targeting of advertisements. Put forward relevant hypotheses and verify the sample data through SPSS to draw relevant con+clusions. The research shows that the reliability of the platform, the sensitivity of consumers to advertising, the familiarity of consumer brands, the degree of consumer participation, and the creative and targeted advertising all have a positive impact on the effectiveness of advertising. Based on the above conclusions, the author is the enterprise information. Streaming ads have made some targeted recommendations

Simulation and experiment of algorithm and circuit design for UPQC

Power quality issues have become one of the most important issue for researchers to concern. In this paper, simulation and experiment of algorithm and circuit design of Unified Power Quality Conditioner (UPQC) are provided. Control algorithm and topology design of one UPQC which includes active power filter (APF) and dynamic voltage restorer (DVR) are introduced. Stability condition of the filter unit is deduced and proved by Routh stability criterion. Simulation for APF and DVR is carried out in PSCAD to show the proposed control strategy. Experiments such as current tracking, harmonic detection and compensation and voltage drop compensation are provided in details. Experimental results show that the proposed control method and the designed topology are effective and practical

Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decoding

Auto-completing code enables developers to speed up coding significantly. Recent advances in transformer-based large language model (LLM) technologies have been applied to code synthesis. However, studies show that many of such synthesized codes contain vulnerabilities. We propose a novel vulnerability-constrained decoding approach to reduce the amount of vulnerable code generated by such models. Using a small dataset of labeled vulnerable lines of code, we fine-tune an LLM to include vulnerability labels when generating code, acting as an embedded classifier. Then, during decoding, we deny the model to generate these labels to avoid generating vulnerable code. To evaluate the method, we chose to automatically complete Ethereum Blockchain smart contracts (SCs) as the case study due to the strict requirements of SC security. We first fine-tuned the 6-billion-parameter GPT-J model using 186,397 Ethereum SCs after removing the duplication from 2,217,692 SCs. The fine-tuning took more than one week using ten GPUs. The results showed that our fine-tuned model could synthesize SCs with an average BLEU (BiLingual Evaluation Understudy) score of 0.557. However, many codes in the auto-completed SCs were vulnerable. Using the code before the vulnerable line of 176 SCs containing different types of vulnerabilities to auto-complete the code, we found that more than 70% of the auto-completed codes were insecure. Thus, we further fine-tuned the model on other 941 vulnerable SCs containing the same types of vulnerabilities and applied vulnerability-constrained decoding. The fine-tuning took only one hour with four GPUs. We then auto-completed the 176 SCs again and found that our approach could identify 62% of the code to be generated as vulnerable and avoid generating 67% of them, indicating the approach could efficiently and effectively avoid vulnerabilities in the auto-completed code.Comment: 12 pages, 8 figures, 2 tables, 5 listings, accepted to the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE 2023

Barriers and facilitators in providing oral health care to nursing home residents, from the perspective of care aides—a systematic review protocol

PRISMA-P checklist. The checklist is composed of recommended items to address in a systematic review protocol. (PDF 218 kb

ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queries

Existing autonomous driving pipelines separate the perception module from the prediction module. The two modules communicate via hand-picked features such as agent boxes and trajectories as interfaces. Due to this separation, the prediction module only receives partial information from the perception module. Even worse, errors from the perception modules can propagate and accumulate, adversely affecting the prediction results. In this work, we propose ViP3D, a visual trajectory prediction pipeline that leverages the rich information from raw videos to predict future trajectories of agents in a scene. ViP3D employs sparse agent queries throughout the pipeline, making it fully differentiable and interpretable. Furthermore, we propose an evaluation metric for this novel end-to-end visual trajectory prediction task. Extensive experimental results on the nuScenes dataset show the strong performance of ViP3D over traditional pipelines and previous end-to-end models.Comment: Project page is at https://tsinghua-mars-lab.github.io/ViP3