为了探讨交通运输部门的低碳发展方向,基于LEAP(longrange energy alternatives planning system)模型建立西安市道路交通运输部门运输能源与环境模型,模拟2021—2050年不同情景下交通运输部门的能源需求、CO_(2)和污染物排放变化趋势...为了探讨交通运输部门的低碳发展方向,基于LEAP(longrange energy alternatives planning system)模型建立西安市道路交通运输部门运输能源与环境模型,模拟2021—2050年不同情景下交通运输部门的能源需求、CO_(2)和污染物排放变化趋势以及减排潜力。结果表明,低碳情景(LC)下能源消耗和CO_(2)排放在2031年左右达到峰值,2050年相对基准情景(BAU)的削减率分别为32.62%、30.21%,对CO、NO_(x)、PM_(10)减排效果较好,相对BAU削减率分别为33.88%、36.27%、40.33%;各子情景中,运输结构调整情景(TSA)节能减排贡献最大,其次为绿色汽车情景(GC)和技术性节能情景(TES);要实现交通运输部门碳减排和污染物的排放控制,需调整交通结构,淘汰老旧车型和大力发展公共交通,并不断完善相应的基础设施,提高新能源汽车的市占率。展开更多
县域是我国资源禀赋最丰富的区域,也是新型城镇化和农业现代化的耦合点。在推进碳达峰碳中和的过程中,县域的生态功能举足轻重。县域兴衰关系着我国发展全局,推动县域经济高质量发展是时代赋予的使命。本文以某县为研究区,利用长期能源...县域是我国资源禀赋最丰富的区域,也是新型城镇化和农业现代化的耦合点。在推进碳达峰碳中和的过程中,县域的生态功能举足轻重。县域兴衰关系着我国发展全局,推动县域经济高质量发展是时代赋予的使命。本文以某县为研究区,利用长期能源替代规划系统(Long-range Energy Alternatives Planning system,LEAP)构建适用于县域的碳达峰预测模型,分析县域碳达峰情景,对重点领域进行碳达峰预测。未来,县域要因地制宜,多措并举,以高质量发展推进碳达峰碳中和,以降碳为抓手,实现绿色低碳发展。展开更多
Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, f...Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.展开更多
文摘为了探讨交通运输部门的低碳发展方向,基于LEAP(longrange energy alternatives planning system)模型建立西安市道路交通运输部门运输能源与环境模型,模拟2021—2050年不同情景下交通运输部门的能源需求、CO_(2)和污染物排放变化趋势以及减排潜力。结果表明,低碳情景(LC)下能源消耗和CO_(2)排放在2031年左右达到峰值,2050年相对基准情景(BAU)的削减率分别为32.62%、30.21%,对CO、NO_(x)、PM_(10)减排效果较好,相对BAU削减率分别为33.88%、36.27%、40.33%;各子情景中,运输结构调整情景(TSA)节能减排贡献最大,其次为绿色汽车情景(GC)和技术性节能情景(TES);要实现交通运输部门碳减排和污染物的排放控制,需调整交通结构,淘汰老旧车型和大力发展公共交通,并不断完善相应的基础设施,提高新能源汽车的市占率。
文摘县域是我国资源禀赋最丰富的区域,也是新型城镇化和农业现代化的耦合点。在推进碳达峰碳中和的过程中,县域的生态功能举足轻重。县域兴衰关系着我国发展全局,推动县域经济高质量发展是时代赋予的使命。本文以某县为研究区,利用长期能源替代规划系统(Long-range Energy Alternatives Planning system,LEAP)构建适用于县域的碳达峰预测模型,分析县域碳达峰情景,对重点领域进行碳达峰预测。未来,县域要因地制宜,多措并举,以高质量发展推进碳达峰碳中和,以降碳为抓手,实现绿色低碳发展。
基金the Competitive Research Fund of the University of Aizu,Japan.
文摘Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.
