广义城市形象识别系统研究——城市形象识别系统中的“形”与“势”

随着中国城市建设的高速发展,城市形象识别越来越受到重视,以往分散在不同领域与层次的研究亟待整合。城市形象识别系统是从新的视角对城市形象问题的研究探讨,是对已有的相关理论的一种综合、补充和延展。本文借用我国传统文化中的"形势说",从"形"与"势"的概念入手,分析了城市形象识别系统的空间尺度和设计方法,将城市规划、城市景观、城市品牌等多学科的研究统一到一个广义的城市形象系统内。     

衡阳市视觉形象设计与运用研究

本文通过对衡阳市地理特征、自然景观、历史人文的总结和分析,提出了形象鲜明的衡阳城市形象定位。在此基础上,总结出对于衡阳城市形象视觉识别系统的建设方法和系统化、规范化的设计方案,以凸显城市的特色和魅力,推动衡阳城市的总体发展。     

设计管理在城市形象设计中的应用——以江西新余市孔目江两岸夜景照明设计为例

优美的滨水绿地夜景为市民提供一个舒适,宜人的夜环境,也为城市带来潜在的效益。它不仅仅属于技术的范畴,还涉及艺术、管理等多方面的内容。城市形象设计需要进行综合的考虑与研究。本文以江西新余市孔目江两岸夜景照明设计为例,从设计管理的角度探索城市视觉识别系统的设计原则,分析城市夜景照明应该注意的问题,对城市形象的设计具有重要的意义。     

从天津国庆彩车看城市形象和城市视觉设计

城市形象是城市综合实力的重要组成,城市视觉设计是对城市形象的全面提升和塑造。文章以天津国庆彩车设计为例,分析了城市形象与城市视觉设计的关系,总结了城市视觉设计的关键因素是:准确性定位、实效性沟通、象征性表达和多元兼容性。     

安徽城市形象的提升与视觉应用研究

在城市化快速发展的今天,良好的城市形象对于城市的发展有着非常重要的作用,良好的城市形象是一个城市无形的资产,不断提升城市的形象可以为城市建设带来更多的发展机遇。文章从安徽省城市形象的提升与视觉应用研究为例,分别从提升安徽城市形象与视觉应用的意义、以及如何提升安徽城市形象三个方面,对该问题做了深入的探讨和分析。     

浅议城市色彩规划设计的意义及措施

由于对城市形象与建筑色彩的规划认识不够、新材料的滥用和色彩的普遍模仿,导致城市形象混乱,与城市的地域文化特色和社会生活相脱节。文章通过对城市形象与色彩之间的关系进行重新审视,就其两者关系的发展意义进行简要分析,引出城市色彩概念内涵的同时梳理提出城市色彩规划对未来城市发展的影响,更全面有效地对城市色彩规划、管理展开系统研究,以便很好地纳入城市规划设计,成为有机组成部分。     

融入中国传统元素的城市形象塑造研究

城市形象作为城市“软实力”的重要象征,是城市文化、精神面貌的重要体现。随着中国国际地位的不断飙升与外来文化的冲击,城市间的竞争日趋激烈,塑造良好的城市形象不仅可以扩大城市的知名度和美誉度,还可以带动一个区域全方位发展。随着旅游经济全球化的推进和传统文化复兴战略的推广,城市形象塑造研究被推入一个新的征程。本文将对融入中国传统元素的城市形象塑造进行研究分析,为构建融入中国传统元素的城市形象塑造寻求新的途径和策略。     

城市文化定位和塑造城市形象的思考

准确的城市文化定位是塑造、树立和传播城市形象的基础和核心.城市文化是一个城市的历史底蕴、审美情趣、道德价值以及体现于城市内涵外质中的人文精神,它积淀城市最深层的精神追求和行为准则.城市文化定位要以城市的物质文化、精神文化和行为文化为定位依据,城市文化定位对城市形象塑造产生巨大影响,传承城市历史文脉是继承城市形象;营造城市文化环境是传播城市形象;整体规划城市文化是创新城市形象;打造城市文化魅力是提升城市形象.以城市文化定位塑造城市形象,必须通过城市文化定位,赋予城市形象美好的品质;树立城市形象给予城市形象深刻的内涵;传播城市形象予以城市形象无穷的魅力.     

西北城市形象研究的知识图谱（1998～2022年）——以西安市为例

西安作为我国西北具有代表性的城市，其城市形象的构建不仅关乎城市自身的发展，还对西北城市形象的建构与传播起到重要作用。本文通过选取1998～2022年中国知网国内新闻传播学领域中关于西安城市形象研究共343篇论文作为研究对象，利用CiteSpace文献计量软件绘制知识图谱进行可视化分析，总结得出过去20多年对于西安城市形象研究的一些特点，从而对今后西安的城市建设以及城市形象的提升提供依据。     

浅析汉字设计对电影海报设计的影响

在海报设计中,文字起着信息传递视觉化作用,是传递信息的重要载体。它以独特意味的"形"作为媒介传递信息,人们凭借对文字"形"的理解而转化为"义",完成信息内涵的传达与接收。不仅要学会"造字",更要懂得如何"用字"。一个优秀的设计师会恰如其分地"用字"准确而有效地传递信息。因此,在电影海报设计中,字体的设计是设计师必须认真研究和把握的问题。     

Comparing the effects of text size and format on the readibility of computer-displayed Times New Roman and Arial text

Times New Roman and Arial typefaces in 10- and 12-point, dot-matrix and anti-aliased format conditions were compared for readability (accuracy, reading speed, and accuracy/reading speed), as well as perceptions of typeface legibility, sharpness, ease of reading, and general preference. In assessing readability, the 10-point anti-aliased Arial typeface was read slower than the other type conditions. Examining perceptions of typeface legibility, sharpness, and ease of reading detected significant effects for typeface, size, and format. Overall, the 12-point dot-matrix Arial typeface was preferred to the other typefaces. Recommendations for appropriate typeface combinations for computer-displayed text are discussed.     

从Arial到Times New Roman——浅谈当今设计中的英文字体使用

在设计中,字体的选用是一个相当重要的部分。但设计师们往往不愿意在此投入太多的精力。在字体选取上固用几种字体,英文字体尤其明显,本文从两种被使用最多的英文字体Arial和TimeNewRoman着手,分析了当前设计中普遍存在的字体使用的问题。     

Examining children's reading performance and preference for different computer-displayed text

This study investigated how common online text affects reading performance of elementary school-age children by examining the actual and perceived readability of four computer-displayed typefaces at 12- and 14-point sizes. Twenty-seven children, ages 9 to 11, were asked to read eight children's passages and identify erroneous/substituted words while reading. Comic Sans MS, Arial and Times New Roman typefaces, regardless of size, were found to be more readable (as measured by a reading efficiency score) than Courier New. No differences in reading speed were found for any of the typeface combinations. In general, the 14-point size and the examined sans serif typefaces were perceived as being the easiest to read, fastest, most attractive, and most desirable for school-related material. In addition, participants significantly preferred Comic Sans MS and 14-point Arial to 12-point Courier. Recommendations for appropriate typeface combinations for children reading on computers are discussed.     

Light for patient safety: Impact of light on reading errors of medication labels

BackgroundIn in-patient care facilities, 1 in 5 medication doses is administered incorrectly. A hospital environment which supports the performance of the health-care staff will positively impact patient safety.ObjectivesDetermine which lighting leads to the least reading mistakes of medication labels.DesignExperimental study with repeated measures.SettingStudy was performed under controlled conditions in the Netherlands.ParticipantsIn total the data of 37 participants are analyzed and described. Inclusion criteria were: female, aged between either 18–30 years old (M = 26.0, SD = 3.1) or between 55 and 67 years old (M = 57.9, SD = 2.7) years old, with normal vision. Eligible participants were personally invited to participate.MethodsPer participant, the readability of three different labels (Blister, Baxter and Orange) and four different font sizes (4.5 pt, 3.5 pt, 3.0 pt, and 2.5 pt Arial Capital) were assessed under nine different light conditions (three illuminances (E),100lx, 500lx, and 1000lx and three correlated color temperatures (T_cp): 3000 K, 4000 K, and 6500 K). The participants had to read out loud text sequences of 10 letters per medication label. The numbers of errors were counted and analyzed.ResultsThe results show a significant difference between numbers of errors related to: 1. Light condition, 2. Age, 3. Label material, 4. Font size. The impact of the light condition is not identical for the different types of label and the font sizes. The impact of the light conditions is the strongest for the smallest font size (2.5 pt) and participants with Visual Acuity < 1.ConclusionLighting has an impact on the number of errors. Older people make more errors than younger people. The type of label has an impact on the number of errors made. The font size has an impact on number of errors made. For font sizes <4.5 pt (Arial), reading medication labels (Blister, Baxter and Orange) under illuminance levels of 100lx, will lead to significantly more errors than E ≥ 500lx. The light condition that generates the least errors for the total test population, all font sizes, and all different materials was the one with an E of 1000lx and a T_cp of 4000 K. People with an insufficient Visual Acuity (VA) benefit most from a higher illuminance level, especially for the Orange labels. When the VA is well-adjusted (sufficient to good) and the font size is as recommended for medication labels (Arial Capital ≥ 4.5 pt) the impact of the lighting on number of errors is limited for all of the age groups.     

A Service-Oriented Middleware for Building Collaborative UAVs

For a while, Unmanned Arial Vehicles (UAVs) use was limited to military applications, however recently UAVs are also used for a wide range of civilian applications. Some of these UAV applications may involve multiple UAVs that must cooperate to achieve a common goal. This kind of applications is termed collaborative UAV applications. This paper investigates the collaborative aspects and challenges of multiple UAV systems. One of the main issues for multiple UAV systems is developing an effective framework to enable the development of software systems for collaborative UAV operations. One possible approach is to rely on service-oriented computing and service-oriented middleware technologies to simplify the development and operations of such applications. This paper discusses how the service-oriented middleware approach can help resolve some of the challenges of developing collaborative UAVs. The paper also proposes a service-oriented middleware architecture that can satisfy the development and operations of such applications.     

Text legibility and the letter superiority effect

Effects of font design and electronic display parameters upon text legibility were determined using a threshold size method. Participants' visual acuity (inverse of the minimum detection size, representing the threshold legibility for each condition) was measured using upper- and lowercase letters and lowercase words in combinations of 6 fonts, 3 font-smoothing modes, 4 font sizes, 10 pixel heights, and 4 stroke widths. Individual lowercase letters were 10% to 20% more legible than lowercase words (i.e., lowercase words must be 10%-20% larger to have the same threshold legibility). This letter superiority effect suggests that individual letters play a large role and word shape plays a smaller role, if any, in word identification at threshold. Pixel height, font, stroke width, and font smoothing had significant main effects on threshold legibility. Optimal legibility was attained at 9 pixels (10 points). Verdana and Arial were the most legible fonts; Times New Roman and Franklin were least legible. Subpixel rendering (ClearType) improved threshold legibility for some fonts and, in combination with Verdana, was the most legible condition. Increased stroke width (bold) improved threshold legibility but only at the thinnest width tested. Potential applications of this research include optimization of font design for legibility and readability.     

Desertification Detection in Makkah Region based on Aerial Images Classification

Desertification has become a global threat and caused a crisis, especially in Middle Eastern countries, such as Saudi Arabia. Makkah is one of the most important cities in Saudi Arabia that needs to be protected from desertification. The vegetation area in Makkah has been damaged because of desertification through wind, floods, overgrazing, and global climate change. The damage caused by desertification can be recovered provided urgent action is taken to prevent further degradation of the vegetation area. In this paper, we propose an automatic desertification detection system based on Deep Learning techniques. Aerial images are classified using Convolutional Neural Networks (CNN) to detect land state variation in real-time. CNNs have been widely used for computer vision applications, such as image classification, image segmentation, and quality enhancement. The proposed CNN model was trained and evaluated on the Arial Image Dataset (AID). Compared to state-of-the-art methods, the proposed model has better performance while being suitable for embedded implementation. It has achieved high efficiency with 96.47% accuracy. In light of the current research, we assert the appropriateness of the proposed CNN model in detecting desertification from aerial images.     

基于多尺度分割的遥感影像滨海湿地分类

基于多尺度的高分辨率遥感影像分类方法研究,可以为滨海湿地动态监测、规划保护提供更详尽的湿地分类信息和更快速的数据获取方法,对湿地保护具有重要意义。选取连云港青口河入海口处湿地为研究区,以高分辨率遥感影像WV\|Ⅱ和航空遥感影像为数据源,利用多尺度分割方法将影像分割成不同层次的实体对象;在不同层次,以实体对象为单元,结合光谱、形状、纹理等不同影像特征,进行滨海湿地分类研究,结果表明:利用该方法分类后,研究区各种湿地类型都达到较高精度。基于多尺度分割的影像分类方法能充分利用各种影像特征完成湿地分类,有效地减少了遥感影像中的“椒盐”现象,提高了分类精度;选择适宜的分割尺度和分割参数是基于多尺度分割的遥感影像分类方法提高精度的前提。     

Proposed features of an online examination interface design and its optimal values

User Interface Design is an essential part of any software application. Accordingly, online examination is an equally important system within eLearning. Consequently, online examination design features are a significant factor in enhancing exam efficiency as well as convenience for examinees. Nine main design features are generally applied in the online exam, namely font (i.e., type, size, colour, and style), background colour, sound alert, questions group, time counters, and number of questions per page. The values of these features are closely related to user characteristics, whether relating to the physical, cognitive, psychomotor, demographics or experience. Our experiment was conducted on 119 students to identify the commonly preferred online examination design. The results show that the students had variations in their choice of online exam interface design, where students preferred to group questions by Topic and then by Type. The most popular font type was Arial with a size of 14 or 12 and using regular font style. Moreover, white background and black text were the most preferred. Most of the students selected 5 and 3 questions/page respectively. Countdown Timer was the most preferred time counter. Regarding sound alert, the 15 and 5 min remains were the most selected by students.