scholarly journals An Application Deployment Approach for City IoT Applications in Resource-constrained Edge Computing Environments

2020 ◽  
Author(s):  
Jialei Liu ◽  
Quanzhen Huang
Keyword(s):  
Resource Constrained ◽  
Simulation Test ◽  
Iot Applications ◽  
High Resource ◽  
Load Imbalance ◽  
Resource Requirements ◽  
Application Deployment ◽  
Development And Utilization ◽  
The City ◽  
Execution Delay

Abstract With the development and utilization of more and more city Internet of Things (IoT) applications with high resource requirements, how to reduce the consumption of energy, processor resources and bandwidth resources in resource-constrained edge clouds while ensuring the execution delay of these applications is an urgent problem to be solved. Therefore, an optimal energy-bandwidth tradeoff deployment approach for city IoT application is proposed for resource-constrained edge clouds. In this approach, the city IoT applications are first divided into multiple collaborative tasks and offload to edge clouds. Secondly, a joint optimization model including energy consumption, resource wastage, resource load imbalance and bandwidth resource consumption is established for the task offloading scheme. Thirdly, the city IoT application deployment problem is optimized under the constraints of resource and execution delay. Finally, a comprehensive simulation test is conducted to analyze the deployment approaches from the aspects of performance and effectiveness. The experimental results show that our deployment approach is superior to other related approaches.

scholarly journals A Dynamic Information-Based Parking Guidance for Megacities considering Both Public and Private Parking

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
Jong-Ho Shin ◽  
Namhun Kim ◽  
Hong-bae Jun ◽  
Duck Young Kim
Keyword(s):  
Intelligent Transportation System ◽  
Guidance System ◽  
Simulation Test ◽  
Dynamic Information ◽  
Public And Private ◽  
Parking Management ◽  
Points Of View ◽  
Spatial Resources ◽  
The City ◽  
Infant Stage

The constantly increasing number of cars in the megacities is causing severe parking problems. To resolve this problem, many cities adopt parking guidance system as a part of intelligent transportation system (ITS). However, the current parking guidance system stays in its infant stage since the obtainable information is limited. To enhance parking management in the megacity and to provide better parking guidance to drivers, this study introduces an intelligent parking guidance system and proposes a new methodology to operate it. The introduced system considers both public parking and private parking so that it is designed to maximize the use of spatial resources of the city. The proposed methodology is based on the dynamic information related parking in the city and suggests the best parking space to each driver. To do this, two kinds of utility functions which assess parking spaces are developed. Using the proposed methodology, different types of parking management policies are tested through the simulation. According to the experimental test, it is shown that the centrally managed parking guidance can give better results than individually preferred parking guidance. The simulation test proves that both a driver’s benefits and parking management of a city from various points of view can be improved by using the proposed methodology.

The Study about the Integrated Development and Utilization of above and below Urban Ground Space in China

2011 ◽  
Vol 71-78 ◽  
pp. 1403-1410
Author(s):  
Zhi Long Chen ◽  
Cheng Zhang ◽  
Dong Jun Guo
Keyword(s):  
Urban Space ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Sustainable Urban Development ◽  
Land Resources ◽  
Space System ◽  
Development And Utilization ◽  
Different Characteristics ◽  
The City ◽  
Three Dimensional Space

As the development of the economic of China and the acceleration of urbanization, metropolises have run out of land resources. Therefore, developing and utilizing the underground space becomes the inevitable trend of sustainable urban development. The modern urban space is a three-dimensional space system which is made up of above and below parts of the space. According to the city on or under the ground, the different characteristics exist. Arranging their own appropriate functions, and avoid weaknesses, will not only make best use of their function, but also promote each to form a good system of urban functions to ensure the city’s efficient and orderly operation.

3B Rapid Transit: Yangzhou’s Ecology-Based Urban Development Research

2011 ◽  
Vol 280 ◽  
pp. 36-39
Author(s):  
Yu Jing Zhu
Keyword(s):  
Urban Transport ◽  
Pattern Language ◽  
Bus Rapid Transit ◽  
Development Research ◽  
Rapid Transit ◽  
Main Mode ◽  
Transit System ◽  
Development And Utilization ◽  
Mode Of Transport ◽  
The City

The paper considers the development and utilization of the Yangzhou’s Canal is not enough, the city's achievements in building a far cry from the once glorious, now can not meet the future transport planning has been far from development. This paper then made twenty creative pattern language to develop the city's green transport, including the characteristics of canal traffic and the bike and bus rapid transit system as the city's main mode of transport, to create a set of Boats, Buses, Bikes (3B Rapid Transit) in one of the three healthy, environmentally friendly urban transport network, reshaping the image of the city, another city of glory.

THE IMPACT OF ROAD COMPLEXITYON THE PSYCHOPHYSIOLOGICAL LOAD EXPERIENCED BY CAR DRIVERS USING ELECTROENCEPHALOGRAPHY (EEG) MEASUREMENT OF BRAINWAVES

2018 ◽  
Vol 16 (4) ◽  
pp. 361-374
Author(s):  
Sugiono Sugiono ◽  
Widhayanuriyawan Denny ◽  
Debrina Puspita Andriani
Keyword(s):  
Traffic Accident ◽  
Occipital Lobe ◽  
Test Results ◽  
Simulation Test ◽  
Alert System ◽  
Strong Signal ◽  
Rural Road ◽  
The Impact ◽  
The City ◽  
Brain Parts

A driver’s mental and physical states while driving on hazardous roads significantly determine the incident of traffic accident. The objectives of this paper are to analyze the impact of road complexity on the psychophysiological load experienced by drivers through the use of Electroencephalography (EEG). Three conditions were examined through driving simulation, namely motorway, rural road, and city road. The data were collected from three respondents (drivers) who had different driving experiences, including < 3 years, 3 to 5 years, and > 5 years. Besides, each respondent would go through two tests with different situations: a normal situation and interfered situation (noises). The tool used was Emotive EPOC neuroheadset with 5 channels (electrode) which represent brain parts, such as the frontal (AF3 and AF4), temporal (T7 and T8), and parietal/occipital Pz. The simulation test results show that the beta signal for the motorway road situation in the occipital lobe, which functioned as visual, is more dominant compared to electrodes in other parts. Meanwhile, data from the rural road and the city road indicate a strong signal of emotions and visuals. In addition, based on the metrics performance result, the drivers’ level of stress reached its highest on the city road, as much as 45, followed by the rural road = 44 and the motorway = 42. While for the concentration index, the city road achieved 47, the rural road = 50 and the motorway = 53. EEG can be used as the basis for drivers performance assessment within different road situations so that the alert system for drivers can be engineered better.

scholarly journals Self-Adaptive Approximate Mobile Deep Learning

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2958
Author(s):  
Timotej Knez ◽  
Octavian Machidon ◽  
Veljko Pejović
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real World ◽  
Edge Computing ◽  
Major Drawback ◽  
High Resource ◽  
Average Accuracy ◽  
Resource Requirements ◽  
And Performance ◽  
Network Compression

Edge intelligence is currently facing several important challenges hindering its performance, with the major drawback being meeting the high resource requirements of deep learning by the resource-constrained edge computing devices. The most recent adaptive neural network compression techniques demonstrated, in theory, the potential to facilitate the flexible deployment of deep learning models in real-world applications. However, their actual suitability and performance in ubiquitous or edge computing applications has not, to this date, been evaluated. In this context, our work aims to bridge the gap between the theoretical resource savings promised by such approaches and the requirements of a real-world mobile application by introducing algorithms that dynamically guide the compression rate of a neural network according to the continuously changing context in which the mobile computation is taking place. Through an in-depth trace-based investigation, we confirm the feasibility of our adaptation algorithms in offering a scalable trade-off between the inference accuracy and resource usage. We then implement our approach on real-world edge devices and, through a human activity recognition application, confirm that it offers efficient neural network compression adaptation in highly dynamic environments. The results of our experiment with 21 participants show that, compared to using static network compression, our approach uses 2.18× less energy with only a 1.5% drop in the average accuracy of the classification.

Development of an oncology quality metric evaluation and prioritization tool (QMEPT).

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 260-260
Author(s):  
Randall F. Holcombe ◽  
Michelle Evangelista
Keyword(s):  
Patient Outcomes ◽  
Care Delivery ◽  
Quality Metrics ◽  
Lung Cancers ◽  
Quality Metric ◽  
High Resource ◽  
It Resources ◽  
Resource Requirements ◽  
Oncology Care ◽  
Composite Scores

260 Background: For reporting purposes and to enable ongoing quality improvement, it is essential that metrics reflective of quality oncology care delivery are tracked and reviewed on an ongoing basis. Collection of performance data and incorporation into a usable dashboard can require significant IT resources, both in personnel time and direct costs. The Tisch Cancer Institute (TCI) identified a myriad of cancer quality metrics that required prioritization in order to best allocate limited IT resources and a standardized process to facilitate comparison across different disease groups. Methods: Quality metrics were identified from various sources: CMS, PQRS, Commission on Cancer, QOPI, AHRQ and others recommended by TCI disease management teams (DMTs). All measures were evaluated with QMEPT according to the following domains: 1) Regulatory (CMS or other certifications), 2) Cost & Feasibility (resource intensiveness of the collection process), 3) Patient Outcomes – (existence of standard benchmarks or known underperformance) and 4) Financial – (influence on payor contracting). All metrics were scored to generate a composite score for each metric and then weighted with 40% for Regulatory, 20% for Cost & Feasibility, 40% for Patient Outcomes. Financial was not weighted but given a yes/no designation. Results: Metrics across all disease sites were scored, weighted and compared. Composite scores ranged from 1.56 to 2.67 (range 1 - 3). Weighted scores ranged from 1.4 to 2.8. In general, metrics related to breast, prostate, colorectal and lung cancers scored higher because of the required reporting and existence of evidence-based standardized benchmarks. Metrics proposed by the DMTs were frequently found to have high resource requirements for data collection. Following the scoring process, information was disseminated to the DMTs, leading to alteration of many of the quality metric requests. Metrics with the highest priority scores were submitted to the IT group for incorporation into the quality dashboard. Conclusions: The QMEPT allowed comparison of quality metrics across disparate oncology disease groups, prioritization for incorporation into a quality dashboard and rational allocation of limited IT resources.

GIS Technology Applied in Urban Plot Ratio Statistics and Land Suitability Evaluation

2014 ◽  
Vol 638-640 ◽  
pp. 2146-2150
Author(s):  
Da Xi Ma ◽  
Chun Qin Zeng ◽  
Qiang Ai
Keyword(s):  
Spatial Data ◽  
Land Development ◽  
Land Suitability ◽  
Gis Technology ◽  
Important Indicator ◽  
Suitability Evaluation ◽  
Land Suitability Evaluation ◽  
Development And Utilization ◽  
Plot Ratio ◽  
The City

GIS technology can be used to support spatial data collection, management, processing, analysis, modeling and display to solve complex planning and manage problems. [2,3] Plot ratio is an important indicator in the reasonable development and utilization. City land suitability evaluation is the basis of urban land development direction. [1] This paper using superposition analysis module and spatial analysis extension module in ARCGIS10.1 software to volume rate statistics, carry out the city land suitability evaluation, and make the results visualization.

The Study of the Method of China Cities Underground Space Development and Utilization

2012 ◽  
Vol 209-211 ◽  
pp. 600-604 ◽  
Author(s):  
Peng Dai ◽  
Xiu Ting Wei
Keyword(s):  
Residential Building ◽  
Scientific Development ◽  
Underground Space ◽  
City Development ◽  
Compact City ◽  
Sustainable City ◽  
Cycle Economy ◽  
Development And Utilization ◽  
City Construction ◽  
The City

The city of today, its economy is one of the biggest problems to solve, development and utilization of urban underground space, the construction "compact" city, become the key to the gate open city construction. This paper mainly through urban underground expressway, underground residential building, underground sewage system, public facilities "common ditch", underground green space, underground recreation places, geothermal, underground city, the several potential city development and utilization of underground ways, this paper puts forward the scientific development view in the central guidance, to build a "harmonious society", the development of "the cycle economy" and construction "sustainable city" is of great significance.

scholarly journals Large-scale evaluation of an AI system as an independent reader for double reading in breast cancer screening

2021 ◽  
Author(s):  
Nisha Sharma ◽  
Annie Y Ng ◽  
Jonathan J James ◽  
Galvin Khara ◽  
Eva Ambrozay ◽  
...  
Keyword(s):  
Large Scale ◽  
Standard Of Care ◽  
Clinical Work ◽  
Recall Rate ◽  
Screening Mammography ◽  
Substantial Part ◽  
Double Reading ◽  
High Resource ◽  
Resource Requirements ◽  
Screening Population

Screening mammography with two human readers increases cancer detection and lowers recall rates, but high resource requirements and a shortage of qualified readers make double reading unsustainable in many countries. The use of AI as an independent reader may yield more objective, accurate and outcome-based screening. Clinical validation of AI requires large-scale, multi-site, multi-vendor studies on unenriched cohorts. This retrospective study evaluated the performance of the MiaTM version 2.0.1 AI system from Kheiron Medical Technologies on an unenriched sample (275,900 cases from 177,882 participants) collected across seven screening sites in two countries and four hardware vendors, and is representative of a real-world screening population over 10 years. Performance was determined for standalone AI and simulated double reading to assess non-inferiority and superiority on relevant screening metrics. Standalone AI showed superiority on sensitivity and non-inferiority on specificity while detecting 29.7% of cancers found within three years after screening, and 29.8% of missed interval cancers. Double reading with AI was at least non-inferior compared to human double reading at every metric, with superiority for recall rate, specificity and positive predictive value (PPV). AI as an independent reader reduced the workload, but increased arbitration rate from 3.3% to 12.3%. Applying the AI system under investigation would have reduced the overall number of human reads required by 44.8%. The recall rate was reduced by a relative 4.1%, suggesting there could be fewer follow-up procedures, reduced stress for patients, and less administrative and clinical work. Using the AI system as an independent reader maintains the standard of care of double reading, detects cancers missed by human readers, while automating a substantial part of the workflow, and could therefore bring significant clinical and operational benefits.

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