Design of an automatic landscape design system in smart cities based on vision computing.

With rampant urbanization and industrialization, the quest to become a Smart City is in vogue. Elaborate designs, ideas, and solutions to existing problems are being devised. However, in this race, city planners often neglect the most critical factor related to one’s existence on the Earth, i.e., Sustainability. Designing smart and sustainable cities is a challenge whose solutions are not easy. Also, developing a proposed smart city is a time-consuming process as it involves its foundations, analyzing the needs, latest technology, infrastructure, and topography. This paper aims to analyze the patterns followed by cities worldwide in the quest to make smart cities. This shall also show how newer cities can become innovative based on the work already done by the existing cities through the concept of Inheritance. In order to do this, a dataset comprising 102 cities is analyzed based on six metrics. A combination of the Principal Component Analysis and K-means Clustering technique is used to assist with the analysis of this unlabeled dataset. It is thereby shown that these 102 cities can be identified as belonging to 4 clusters and the cluster properties can then be inherited by any new city poised to become a future smart city.

Systems thinking for developing sustainable complex smart cities based on self-regulated agent systems and fog computing

Computer-aided design (CAD) tools throughout a design automation (DA) system, from low level physical design to high level resource allocation and scheduling tools, require information about the fabrication technology in order to make design decisions. Technology dependent information is maintained in technology files. As fabrication technologies evolve, these files must be updated to reflect the capabilities of the current fabrication process technology. Currently, the task of updating technology files is performed manually and often prone to error and inconsistencies. A system for the automatic updating of technology dependent information in a design automation system is presented. The technology information required by the CAD tools throughout a design automation system are consistent since they are all derived from a common source. >

The articles in this special section focus on Big Data as it impacts future smart cities. The world is experiencing a period of extreme urbanization. Moreover, this process will continue, and the global urban population is expected to double by 2050. Smart city has been proposed to improve the efficiency of services and meet residents’ needs for better quality of life. Essentially, smart city integrates the Internet of Things and emerging communication technologies such as fifth generation (5G) solutions to manage the citys’ assets, including transportation systems, hospitals, water supply networks, waste management, and so on. Therefore, smart city is driving innovation and new technologies, especially big data technologies for the big data era. In the future smart city, there is an urgent need to address the following issues: how to design algorithms to process mass data and how to utilize big data to improve the quality of service (QoS) for future smart cities.

This study explored whether benzodiazepines selectively affect aspects of attention and/or visual information processing, as they do memory. A cued visual-search paradigm was employed, using normal volunteers and a single dose of triazolam. This paradigm provided for a detailed examination of two aspects of visual attention and information processing: 1) controlled versus automatic attention allocation (via central and peripheral cues), and 2) the extent to which processing an item in a non-cued location affects performance (via cue-validity). Triazolam, compared to placebo, significantly increased response time, and Drug Condition interacted with Cue-Validity but not Cue-Type. Based on these data, we argue that triazolam does not affect attention allocation but does affect attentional disengagement and/or attention switching mechanisms.

This paper presents five industrial cases where design automation (DA) systems supported by design optimization has been developed, and aims to summarize the lesson learned and identify needs for future development of such projects. By mapping the challenges during development and deployment of the systems, common issues were found in technical areas such as model integration and organizational areas such as knowledge transfer. The latter can be seen as a two-layered design paradox; one for the product that the DA system is developed for, and one for the development of the DA system.

South Korea has a long history of the planning, development, and management of smart cities to integrate emerging technological advances into complex physical infrastructure. This article explores lessons learned from smart city programs in South Korea to better understand the challenges and opportunities of future sustainable smart city innovation and development. This article conducted a comprehensive review and analysis of South Korea's smart city programs and conceptualized a sustainable smart city framework that will assist policymakers, planners, citizens, and other key stakeholders. This research proposed Governance, Policy, and Services (GPS) as the three pillars of a successful smart city framework, in addition to integrating physical and cyber infrastructures. This article argues that a smart city should function as a service platform that incubates and delivers long-term services to citizens and society. This article also emphasizes that a strong groundwork of the GPS framework will lead to the successful adaptation of innovative technologies and ideas for future smart city programs.

This paper deals with the automation of morphological design. The system proposed here is a part of a complete automatic design system that considers the divergent and convergent stages of the design process through evolutionary procedures. The system provides a way to introduce aesthetics in the decision process. This is a difficult problem within an automatic design system, as aesthetics are subjective, depend on the opinions of humans and humans do not usually agree. The objective here is to be able to obtain the best possible aesthetic solutions for a given set of humans. This is achieved through the introduction of a set of man machine interfaces that allow the system to extract information on their relative opinions without explicitly asking them, and combines them with the engineering information provided by other simulators that participate in the design process.

Smart cities are becoming more and more popular. Currently, there is no unified and interoperable system which could be reused and redeployed in future smart cities. Having an interoperable: (1) system, (2) architecture, (3) workflow to process IoT data, (4) interoperable applications and services, and (5) secure access to data is becoming essential to reduce development cost in smart cities and ensure interoperability among vertical IoT applications (i.e., domain-specific). Firstly, we survey existing work integrating semantic web technologies to Internet of Things, also called 'Semantic Web of Things' and applying it to smart cities. Secondly, we share in this paper, our vision of Semantic Web of Things applied to smart cities and highlight main research challenges. Finally, the main contribution of this work is the semantic engine applied to IoT and smart cities. Moreover, the proposed semantic engine is applied to three use cases: Machine-to-Machine Measurement (M3) framework, FIESTA-IOT EU project and VITAL EU project.

Artificial Intelligence (AI) is one of the science fields with huge potential to create a cognitive and tech-leaping type of future smart city design/development. However, extant studies lag behind recent applications, potential growth areas, and the challenges associated with AI implementation. This study examines AI’s current role, trend, and future potential impacts in enhancing smart city drivers. The methodology entails conducting a Systematic Literature Review (SLR) of publications from 2022 onwards. The approach involves qualitative deductive coding methods, descriptive statistical analysis, and thematic analysis. The findings revealed the impacts of AI in (i) public services and connectivity, (ii) improving accessibility and efficiency, (iii) quality healthcare, (iv) education, and (v) public safety. Likewise, strategies, such as collaborative ecosystems, digital infrastructure, capacity building, and clear guidelines and ethical framework, were proposed for fostering the integration of AI in potential future smart cities. This research fills a notable gap in the current understanding of AI’s specific contributions to smart cities, offering insights for stakeholders in urban planning, computer science, sociology, economics, environmental science, and smart city initiatives. It serves as a strategic guideline and scholarly research output for enhancing smart city design. It also underscores the potential of AI in creating dynamic, sustainable, and efficient urban environments.

Smart cities leverage advanced technologies such as the Internet of Things (IoT) to enhance the quality of life for residents, improve city infrastructure, and foster sustainability. The role of connectivity in urban development is central to the functioning of smart cities, as IoT-enabled devices provide real-time data and automated systems that optimize city operations, from traffic management to waste disposal. This article explores the role of IoT in smart cities, highlighting how connectivity and integrated technologies contribute to efficient urban living. The paper examines key applications of IoT in smart cities, including transportation, energy management, and public services, while also addressing challenges such as data privacy, security, and system interoperability. The future of smart cities and the growing influence of IoT technologies are also discussed in the context of urbanization and sustainable development.

RETRACTED: Smart city image landscape design based on wireless sensors

Automation is the key to the design of future embedded systems as it permits application-specific customization while keeping design costs low. A key problem faced by automatic design systems is evaluating the performance of the vast number of alternative designs in a timely manner. For this paper, we focus on an embedded system consisting of the following components: a VLIW processor, instruction cache, data cache, and second-level unified cache. A hierarchical approach of partitioning the system into its constituent components and evaluating each component individually is utilized. The performance of each processor is evaluated independent of its memory hierarchy, and each of the caches is simulated using the traces from a single reference processor. Since the changes in the processor architecture do indeed affect the address traces and thus the performance of the memory hierarchy, the overall performance is inaccurate. To overcome this error, the changes in the processor architecture are modeled as a dilation of the reference processor's address trace, where each instruction block in the trace is conceptually stretched out by the dilation coefficient. This approach provides a projected cache performance that more accurately accounts for changes in the processor architecture. In order to understand the accuracy of the dilation model, we separate the possible errors that the model introduces and quantify these errors on a set of benchmarks. The results show that the dilation model is effective for most of the design space and facilitates efficient automatic design.

Automatic design of stochastic local search algorithms has been shown to be very effective in generating algorithms for the permutation flowshop problem for the most studied objectives including makespan, flowtime and total tardiness. The automatic design system uses a configuration tool to combine algorithmic components following a set of rules defined as a context-free grammar. In this paper we use the same system to tackle two of the most studied additional constraints for these objectives: sequence dependent setup times and no-idle constraint. Additional components have been added to adapt the system to the new problems while keeping intact the grammar structure and the experimental setup. The experiments show that the generated algorithms outperform the state of the art in each case.

BackgroundClassical galactosemia (CG) is due to a severe deficiency of the galactose-1-phosphate uridyl-transferase (GALT), the main enzyme of galactose metabolism. Even early introduction of galactose-restricted diet fails to prevent long-term complications, including cognitive impairment, neurological and psychiatric problems, osteoporosis, premature ovarian failure and infertility. Detailed neuropsychological phenotyping is needed in order to better understand the relevant neurodevelopmental deficiencies and to develop effective treatment strategies.AimTo define specifically and significantly impaired neuropsychological traits in adult CG patients of the Swiss cohort.MethodsProspective cohort study. 22 CG patients, with confirmed genotype and low GALT activity, and 15 controls completed a computer-based neuropsychological test battery (CANTAB). Additionally, broad IQ evaluation was made for the CG patients.ResultsIn most outcome measures of the CANTAB tasks, CG patients performed significantly worse than controls. The deficits in CG patients were most prominent in tasks that involve rapid visual information processing and facial emotion recognition.ConclusionCG patients have specific cognitive problems such as impaired visual information processing and facial emotion recognition. The deficits in facial emotion recognition have not been described before and could help explain difficulties in social interactions often experienced by patients with CG.