Artificial Intelligence - Emerging Trends and Applications最新文献_第2页

Augmenting Reality with Intelligent Interfaces 增强现实与智能接口

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-06-27 DOI: 10.5772/INTECHOPEN.75751

Dov Schafer, David Kaufman

{"title":"Augmenting Reality with Intelligent Interfaces","authors":"Dov Schafer, David Kaufman","doi":"10.5772/INTECHOPEN.75751","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.75751","url":null,"abstract":"It is clear that our daily reality will increasingly interface with virtual inputs. We already integrate the virtual into real life through constantly evolving sensor technologies embedded into our smartphones, digital assistants, and connected devices. Simultaneously, we seek more virtual input into our reality through intelligent interfaces for the applications that these devices can run in a context rich, socially connected, and personalized way. As we progress toward a future of ubiquitous Augmented Reality (AR) interfaces, it will be important to consider how this technology can best serve the various populations that can benefit most from the addition of these intelligent interfaces. This paper proposes a new terminological framework to discuss the way AR interacts with users. An intelligent interface that combines digital objects in a real-world context can be referred to as a Pose-Interfaced Presentation (PIP): Pose refers to user location and orientation in space; Interfaced means that the program responds to a user’s intention and actions in an intelligent way; and Presentation refers to the virtual object or data being layered onto the perceptive field of the user. Finally, various benefits of AR are described and examples are provided in the areas of education, worker training, and ESL learning.","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114266300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Application of AI in Chemical Engineering 人工智能在化工中的应用

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-06-27 DOI: 10.5772/INTECHOPEN.76027

Zeinab Hajjar, S. Tayyebi, Mohammad Hosein EghbalAhmadi

引用次数: 9

Biologically Inspired Intelligence with Applications on Robot Navigation 生物启发智能及其在机器人导航上的应用

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-06-27 DOI: 10.5772/INTECHOPEN.75692

C. Luo, G. E. Jan, Zhenzhong Chu, Xinde Li

{"title":"Biologically Inspired Intelligence with Applications on Robot Navigation","authors":"C. Luo, G. E. Jan, Zhenzhong Chu, Xinde Li","doi":"10.5772/INTECHOPEN.75692","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.75692","url":null,"abstract":"Biologically inspired intelligence technique, an important embranchment of series on computational intelligence, plays a crucial role for robotics. The autonomous robot and vehicle industry has had an immense impact on our economy and society and this trend will continue with biologically inspired neural network techniques. In this chapter, multiple robots cooperate to achieve a common coverage goal efficiently, which can improve the work capacity, share the coverage tasks, and reduce the completion time by a biologically inspired intelligence technique, is addressed. In many real-world applications, the coverage task has to be completed without any prior knowledge of the environment. In this chapter, a neural dynamics approach is proposed for complete area coverage by multiple robots. A bio-inspired neural network is designed to model the dynamic environment and to guide a team of robots for the coverage task. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting neural equation. Each mobile robot treats the other robots as moving obstacles. Each robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot position. The proposed model algorithm is computationally sim- ple. The feasibility is validated by four simulation studies.","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121047610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

High Performance Technology in Algorithmic Cryptography 算法密码学中的高性能技术

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-06-27 DOI: 10.5772/INTECHOPEN.75959

A. Lezama-León, J. Zárate-Corona, E. León, José Angel Montes-Olguín, Juan Ángel Rosales-Alba, Mariana Carrillo-González

引用次数: 0

A Multilevel Genetic Algorithm for the Maximum Satisfaction Problem 求解最大满足问题的多层次遗传算法

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-06-27 DOI: 10.5772/INTECHOPEN.78299

N. Bouhmala

引用次数: 0

Can Reinforcement Learning Be Applied to Surgery? 强化学习能应用于外科手术吗?

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-06-27 DOI: 10.5772/INTECHOPEN.76146

Masakazu Sato, K. Koga, T. Fujii, Y. Osuga

{"title":"Can Reinforcement Learning Be Applied to Surgery?","authors":"Masakazu Sato, K. Koga, T. Fujii, Y. Osuga","doi":"10.5772/INTECHOPEN.76146","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.76146","url":null,"abstract":"Background : Remarkable progress has recently been made in the field of artificial intelligence (AI). Objective : We sought to investigate whether reinforcement learning could be used in sur gery in the future . Methods : We created simple 2D tasks (Tasks 1–3) that mimicked surgery. We used a neu ral network library, Keras, for reinforcement learning. In Task 1, a Mac OS X with an 8 GB memory (MacBook Pro, Apple, USA) was used. In Tasks 2 and 3, a Ubuntu 14. 04LTS with a 26 GB memory (Google Compute Engine, Google, USA) was used . Results : In the task with a relatively small task area (Task 1), the simulated knife finally passed through all the target areas, and thus, the expected task was learned by AI. In con trast, in the task with a large task area (Task 2), a drastically increased amount of time was required, suggesting that learning was not achieved. Some improvement was observed when the CPU memory was expanded and inhibitory task areas were added (Task 3) . Conclusions : We propose the combination of reinforcement learning and surgery. Appli cation of reinforcement learning to surgery may become possible by setting rules, such as appropriate rewards and playable (operable) areas, in simulated tasks.","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129594688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Virtual Reality for Urban Sound Design: A Tool for Architects and Urban Planners 城市声音设计的虚拟现实技术：建筑师和城市规划师的工具

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-04-12 DOI: 10.5772/INTECHOPEN.75957

Josep Llorca

{"title":"Virtual Reality for Urban Sound Design: A Tool for Architects and Urban Planners","authors":"Josep Llorca","doi":"10.5772/INTECHOPEN.75957","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.75957","url":null,"abstract":"Urban sound is one of the main concerns of architects and urban planners in contempo- rary cities: how to control it, what to do about noise pollution, where silent areas should be situated, or which urban decisions must be made. These questions, among others, are based on spatial sound. Virtual reality is a powerful technology that can serve as a design tool to find some answers to these questions. Due to its power to generate realistic images of the environments that are studied, it is easy to see that virtual reality could contribute to the visualization and auralization of spaces before their construction. This task is one of architects’ responsibilities, and such a tool could be very useful to them. This chapter highlights the principles and some applications of virtual reality in urban sound design. Two big differences separate the experience of illuminating and sonic phenomena. The first consists of the fact that most visual objects are not sources of light, but simply objects, in the usual sense of the word, with light shining on them. Physicists are therefore quite accustomed to distinguishing light from the objects that reflect it. If the object itself gives out light, then we say it is a light “source”. With sound there is nothing like this. In the overwhelming majority of sonic phenomena, sound as origi-nating from “sources” is emphasized. However, the classic distinction in optics between sources and objects has not been imposed in acoustics. Attention has been given to the sound (as we say the light) considered as an emanation from a source, its paths and deformations, without the appreciation of the shapes and contours of this sound apart from the reference to its source [2] .","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129158961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Application of Biomedical Text Mining 生物医学文本挖掘的应用

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-04-04 DOI: 10.5772/INTECHOPEN.75924

Lejun Gong

引用次数: 10

Advanced Content and Interface Personalization through Conversational Behavior and Affective Embodied Conversational Agents 通过会话行为和情感具体化会话代理实现高级内容和界面个性化

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-03-30 DOI: 10.5772/INTECHOPEN.75599

M. Rojc, Z. Kacic, I. Mlakar

引用次数: 2

Human-AI Synergy in Creativity and Innovation 人类与人工智能在创造和创新方面的协同作用

Artificial Intelligence - Emerging Trends and Applications Pub Date : 2018-03-11 DOI: 10.5772/INTECHOPEN.75310

T. McCaffrey

{"title":"Human-AI Synergy in Creativity and Innovation","authors":"T. McCaffrey","doi":"10.5772/INTECHOPEN.75310","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.75310","url":null,"abstract":"In order to maximize creative behavior, humans and computers need to collaborate in a manner that will leverage the strengths of both. A 2017 mathematical proof shows two limits to how innovative a computer can be. Humans can help counteract these demonstrated limits. Humans possess many mental blind spots to innovating (e.g., functional fixedness, design fixation, analogy blindness, etc.), and particular algorithms can help counteract these shortcomings. Further, since humans produce the corpora used by AI technology, human blind spots to innovation are implicit within the text processed by AI technology. Known algorithms that query humans in particular ways can effectively counter these text-based blind spots. Working together, a human-computer partnership can achieve higher degrees of innovation than either working alone. To become an effective partnership, however, a special interface is needed that is both humanand computer-friendly. This interface called BrainSwarming possesses a linguistic component, which is a formal grammar that is also natural for humans to use and a visual component that is easily represented by standard data structures. Further, the interface breaks down innovative problem solving into its essential components: a goal, sub-goals, resources, features, interactions, and effects. The resulting human-AI synergy has the potential to achieve innovative breakthroughs that either partner working alone may never achieve.","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125118597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2