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Construction of CeO2/ZnTCPP heterojunction with enhanced photocatalytic hydrogen production performance
No full textIn this work, a two-step solvothermal method was used to design CeO2/ZnTCPP composites for photocatalytic hydrogen evolution. Systematic characterization including morphological, structural, optical and electrochemical measurements revealed a correlation between the sample structure and photocatalytic activity. Compared with pure CeO2 and ZnTCPP, the optimized CeO2/ZnTCPP photocatalyst has good hydrogen production performance (1314.6 μmol g-1h-1). At the same time, the catalyst can still maintain a high hydrogen production rate (1162.7 µmol g-1h-1) under visible light. The experimental results showed that the CeO2/ZnTCPP composites have high carrier separation efficiency, which is attributed to the formation of a type-II heterojunction in the structure between the CeO2 and ZnTCPP.journal articl
All in How You Ask for It: Simple Black-Box Method for Jailbreak Attacks
Get PDFLarge Language Models (LLMs), such as ChatGPT, encounter ‘jailbreak’ challenges, wherein safeguards are circumvented to generate ethically harmful prompts. This study introduces a straightforward black-box method for efficiently crafting jailbreak prompts that bypass LLM defenses. Our technique iteratively transforms harmful prompts into benign expressions directly utilizing the target LLM, predicated on the hypothesis that LLMs can autonomously generate expressions that evade safeguards. Through experiments conducted with ChatGPT (GPT-3.5 and GPT-4) and Gemini-Pro, our method consistently achieved an attack success rate exceeding 80% within an average of five iterations for forbidden questions and proved to be robust against model updates. The jailbreak prompts generated were not only naturally worded and succinct, but also challenging to defend against. These findings suggest that the creation of effective jailbreak prompts is less complex than previously believed, underscoring the heightened risk posed by black-box jailbreak attacks.journal articl
Self-Assessment of Exploratory Report Assignment in Writing Course
Get PDF本研究では，大学でのライティング科目における最終レポート課題に対して学生の自己評価を実施し，その特徴について明らかにすることを目的とした．ライティング科目の受講生33名を対象に，ルーブリックによる自己評価を実施し，各項目の平均値や項目間の相関係数を算出した．その結果，文の体裁・文法表現に関する自己評価が他の項目に比べて低い傾向にあり，当該授業においてはこれらに関する練習の機会をより多く設ける必要性があることが示唆された．journal articl
水中音響通信におけるパワー変調により通信量を2倍にする二次元OFDMシステム
Get PDF九州工業大学九州工業大学博士学位論文（要旨）学位記番号:生工博甲第485号 学位授与年月日:令和6年3月25日thesi
色素増感太陽電池の光電変換性能に及ぼすスクアリン酸色素の中心置換の影響に関する研究
Get PDF九州工業大学九州工業大学博士学位論文（要旨）学位記番号:生工博甲第491号 学位授与年月日:令和6年3月25日thesi
Evaluating Learning Potential with Internal States in Deep Neural Networks
Get PDFDeploying deep learning models on small-scale computing devices necessitates considering computational resources. However, reducing the model size to accommodate these resources often results in a trade-off with accuracy. The iterative process of training and validating to optimize model size and accuracy can be inefficient. A potential solution to this dilemma is the extrapolation of learning curves, which evaluates a model’s potential based on initial learning curves. As a result, it is possible to efficiently search for a network that achieves a balance between accuracy and model size. Nonetheless, we posit that a more effective approach to analyzing the latent potential of training models is to focus on the internal state, rather than merely relying on the validation scores. In this vein, we propose a module dedicated to scrutinizing the network’s internal state, with the goal of automating the optimization of both accuracy and network size. Specifically, this paper delves into analyzing the latent potential of the network by leveraging the internal state of the Long Short-Term Memory (LSTM) in a traffic accident prediction network.19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, February 27-29, 2024, Rome, Italyjournal articl
Effective training method using transmission matrix for optoelectronic deep neural network
Get PDF5th International Symposium on Neuromorphic AI Hardware, March 1-2, 2024, Kyushu Institute of Technologyconference pape