The Usability of Unmanned Aerial Vehicles (UAVs) for Pedestrian Observation

The monitoring of pedestrian activity is challenging, primarily because its traffic levels are typically lower and more variable than those of motorized vehicles. Compared with other on-the-ground observation tools, unmanned aerial vehicles (UAVs) could be suitable for counting and mapping pedestrians in a reliable and efficient way. Thus, this study establishes and tests a new method of pedestrian observation using UAVs. The results show that UAV observations demonstrate high levels of interrater reliability (intraclass correlation coefficient = 0.99) and equivalence reliability (Cronbach’s α = .97 with on-the-ground counts and .73 with Google Street View). Practical implications of the new tool are discussed

International Conference on Civil Infrastructure and Construction (CIC 2020)

This is the proceedings of the CIC 2020 Conference, which was held under the patronage of His Excellency Sheikh Khalid bin Khalifa bin Abdulaziz Al Thani in Doha, Qatar from 2 to 5 February 2020. The goal of the conference was to provide a platform to discuss next-generation infrastructure and its construction among key players such as researchers, industry professionals and leaders, local government agencies, clients, construction contractors and policymakers. The conference gathered industry and academia to disseminate their research and field experiences in multiple areas of civil engineering. It was also a unique opportunity for companies and organizations to show the most recent advances in the field of civil infrastructure and construction. The conference covered a wide range of timely topics that address the needs of the construction industry all over the world and particularly in Qatar. All papers were peer reviewed by experts in their field and edited for publication. The conference accepted a total number of 127 papers submitted by authors from five different continents under the following four themes: Theme 1: Construction Management and Process Theme 2: Materials and Transportation Engineering Theme 3: Geotechnical, Environmental, and Geo-environmental Engineering Theme 4: Sustainability, Renovation, and Monitoring of Civil InfrastructureThe list of the Sponsors are listed at page 1

The metric tide: report of the independent review of the role of metrics in research assessment and management

This report presents the findings and recommendations of the Independent Review of the Role of Metrics in Research Assessment and Management. The review was chaired by Professor James Wilsdon, supported by an independent and multidisciplinary group of experts in scientometrics, research funding, research policy, publishing, university management and administration. This review has gone beyond earlier studies to take a deeper look at potential uses and limitations of research metrics and indicators. It has explored the use of metrics across different disciplines, and assessed their potential contribution to the development of research excellence and impact. It has analysed their role in processes of research assessment, including the next cycle of the Research Excellence Framework (REF). It has considered the changing ways in which universities are using quantitative indicators in their management systems, and the growing power of league tables and rankings. And it has considered the negative or unintended effects of metrics on various aspects of research culture. The report starts by tracing the history of metrics in research management and assessment, in the UK and internationally. It looks at the applicability of metrics within different research cultures, compares the peer review system with metric-based alternatives, and considers what balance might be struck between the two. It charts the development of research management systems within institutions, and examines the effects of the growing use of quantitative indicators on different aspects of research culture, including performance management, equality, diversity, interdisciplinarity, and the ‘gaming’ of assessment systems. The review looks at how different funders are using quantitative indicators, and considers their potential role in research and innovation policy. Finally, it examines the role that metrics played in REF2014, and outlines scenarios for their contribution to future exercises

Development of Automatic Digitization of Truck Number in Open Cast Mines Using Microcontroller

Geological condition in mines appears to be extremely complicated and there are many intelligence security problems. Production is falsely transfer by the unauthorized truck from mine pits also at loading point. It also lifted in wrong ways by malfunctioning of the truck weight in Weigh Bridge. Mining organizations are under the control of mafia and countless can be added to the mines mafia. An intelligence security system is need to monitor truck number in automatically using image acquisition method, automatic detection, recognition process, communication technology, information technology and microcontroller innovation to understand the working specification of the mining region. Tracking of the number plate from the truck is an important task, which demands intelligent solution. Intelligent surveillance in open casts mine security network using data accession is a prime task that protects the secure production of mines. So automatic truck number recognition technique is used to recognize the registration number of the truck which is used for transferring the mine production as well as track record the amount of the production. It also preserves the mines and thus improving its security. For extraction and recognition of number plate from truck image the system is uses MATLAB software tool. It is assumed that images of the truck have been captured from digital camera. The data acquisition terminal uses the PIC16F877A microcontroller as a core chip for sending data. The data are communicated through USB to TTL converter (RS232) with the main circuit to realize intelligent monitoring. To store the data in permanently it is uses EEPROM chip. Alphanumeric Characters on plate has been extracted and recognized using template images of alphanumeric characters. The proposed system performs the real time data monitoring to recognize the registration number plate of the trucks for getting required important information. It also provides to maintenance the history of data and support access contro

Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization

Automatic speech recognition (ASR) has recently become an important challenge when using deep learning (DL). It requires large-scale training datasets and high computational and storage resources. Moreover, DL techniques and machine learning (ML) approaches in general, hypothesize that training and testing data come from the same domain, with the same input feature space and data distribution characteristics. This assumption, however, is not applicable in some real-world artificial intelligence (AI) applications. Moreover, there are situations where gathering real data is challenging, expensive, or rarely occurring, which can not meet the data requirements of DL models. deep transfer learning (DTL) has been introduced to overcome these issues, which helps develop high-performing models using real datasets that are small or slightly different but related to the training data. This paper presents a comprehensive survey of DTL-based ASR frameworks to shed light on the latest developments and helps academics and professionals understand current challenges. Specifically, after presenting the DTL background, a well-designed taxonomy is adopted to inform the state-of-the-art. A critical analysis is then conducted to identify the limitations and advantages of each framework. Moving on, a comparative study is introduced to highlight the current challenges before deriving opportunities for future research