This paper discusses the idea that the industry can have a differentiator of program quality by encouraging the activities of the Broadcasting Ethics ＆ Program Improvement Organization （BPO） in Japan. The BPO, a wo...This paper discusses the idea that the industry can have a differentiator of program quality by encouraging the activities of the Broadcasting Ethics ＆ Program Improvement Organization （BPO） in Japan. The BPO, a worldwide independent organization, has a mission of a breakwater against state power, and thus can be regarded as a kind of media accountability system, as proposed by Claude-Jean Bertrand. We review some controversial affairs in the TV industry and discuss BPO＇s activities aimed preventing ＂yellow journalism＂ and improving the quality of programming. High-quality content may be a differentiator for viewers faced with a choice of media, and thus, we focus on BPO and its role as a differentiator of the Japanese TV industry among the other, especially, Internet media. We also propose four ideas in response of critiques of BPO. Those are to strengthen transparency of governance of BPO, to improve the conformity of the TV industry to BPO＇s assessments of it, to establish a new committee to examine the whole concept of journalism, and to introduce a new certification institution to guarantee quality.展开更多
To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduc...To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.展开更多
文摘This paper discusses the idea that the industry can have a differentiator of program quality by encouraging the activities of the Broadcasting Ethics ＆ Program Improvement Organization （BPO） in Japan. The BPO, a worldwide independent organization, has a mission of a breakwater against state power, and thus can be regarded as a kind of media accountability system, as proposed by Claude-Jean Bertrand. We review some controversial affairs in the TV industry and discuss BPO＇s activities aimed preventing ＂yellow journalism＂ and improving the quality of programming. High-quality content may be a differentiator for viewers faced with a choice of media, and thus, we focus on BPO and its role as a differentiator of the Japanese TV industry among the other, especially, Internet media. We also propose four ideas in response of critiques of BPO. Those are to strengthen transparency of governance of BPO, to improve the conformity of the TV industry to BPO＇s assessments of it, to establish a new committee to examine the whole concept of journalism, and to introduce a new certification institution to guarantee quality.
文摘To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.
