Adaptive traffic light cycle time controller using microcontrollers and crowdsource data of Google APIs for developing countries

Mishra, S., Bhattacharya, D., Gupta, A., & Singh, V. R. (2018). Adaptive traffic light cycle time controller using microcontrollers and crwodsource data of Google APIs for developing countries. In 3rd International Conference on Smart Data and Smart Cities (4/W7 ed., Vol. 4, pp. 83-90). (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences). DOI: 10.5194/isprs-annals-IV-4-W7-83-2018Controlling of traffic signals optimally helps in avoiding traffic jams as vehicle volume density changes on temporally short and spatially small scales. Nowadays, due to embedded system development with the rising standards of computational technology, condense electronics boards as well as software packages, system can be developed for controlling cycle time in real time. At present, the traffic control systems in India lack intelligence and act as an open-loop control system, with no feedback or sensing network, due to the high costs involved. This paper aims to improve the traffic control system by integrating different technologies to provide intelligent feedback to the existing network with congestion status adapting to the changing traffic density patterns. The system presented in this paper aims to sense real-time traffic congestion around the traffic light using Google API crowdsource data and hence avoids infrastructure cost of sensors. Subsequently, it manipulates the signal timing by triggering and conveying information to the timer control system. Generic information processing and communication hardware system designed in this paper has been tested and found to be functional for a pilot run in real time. Both simulation and hardware trials show the transmission of required information with an average time delay of 1.2 seconds that is comparatively very small considering cycle time.publishersversionpublishe

Semi-automatic assessment of unrestrained Java code: a Library, a DSL, and a workbench to assess exams and exercises

© ACM 2015. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in http://dx.doi.org/10.1145/2729094.2742615Automated marking of multiple-choice exams is of great interest in university courses with a large number of students. For this reason, it has been systematically implanted in almost all universities. Automatic assessment of source code is however less extended. There are several reasons for that. One reason is that almost all existing systems are based on output comparison with a gold standard. If the output is the expected, the code is correct. Otherwise, it is reported as wrong, even if there is only one typo in the code. Moreover, why it is wrong remains a mystery. In general, assessment tools treat the code as a black box, and they only assess the externally observable behavior. In this work we introduce a new code assessment method that also verifies properties of the code, thus allowing to mark the code even if it is only partially correct. We also report about the use of this system in a real university context, showing that the system automatically assesses around 50% of the work.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economíay Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under grant PROMETEOII2015/013. David Insa was partially supported by the Spanish Ministerio de Educación under FPU grant AP2010-4415.Insa Cabrera, D.; Silva, J. (2015). Semi-automatic assessment of unrestrained Java code: a Library, a DSL, and a workbench to assess exams and exercises. ACM. https://doi.org/10.1145/2729094.2742615SK. A Rahman and M. Jan Nordin. A review on the static analysis approach in the automated programming assessment systems. In National Conference on Programming 07, 2007.K. Ala-Mutka. A survey of automated assessment approaches for programming assignments. In Computer Science Education, volume 15, pages 83--102, 2005.C. Beierle, M. Kula, and M. Widera. Automatic analysis of programming assignments. In Proc. der 1. E-Learning Fachtagung Informatik (DeLFI '03), volume P-37, pages 144--153, 2003.J. Biggs and C. Tang. Teaching for Quality Learning at University : What the Student Does (3rd Edition). In Open University Press, 2007.P. Denny, A. Luxton-Reilly, E. Tempero, and J. Hendrickx. CodeWrite: Supporting student-driven practice of java. In Proceedings of the 42nd ACM technical symposium on Computer science education, pages 09--12, 2011.R. Hendriks. Automatic exam correction. 2012.P. Ihantola, T. Ahoniemi, V. Karavirta, and O. Seppala. Review of recent systems for automatic assessment of programming assignments. In Proceedings of the 10th Koli Calling International Conference on Computing Education Research, pages 86--93, 2010.H. Kitaya and U. Inoue. An online automated scoring system for Java programming assignments. In International Journal of Information and Education Technology, volume 6, pages 275--279, 2014.M.-J. Laakso, T. Salakoski, A. Korhonen, and L. Malmi. Automatic assessment of exercises for algorithms and data structures - a case study with TRAKLA2. In Proceedings of Kolin Kolistelut/Koli Calling - Fourth Finnish/Baltic Sea Conference on Computer Science Education, pages 28--36, 2004.Y. Liang, Q. Liu, J. Xu, and D. Wang. The recent development of automated programming assessment. In Computational Intelligence and Software Engineering, pages 1--5, 2009.K. A. Naudé, J. H. Greyling, and D. Vogts. Marking student programs using graph similarity. In Computers & Education, volume 54, pages 545--561, 2010.A. Pears, S. Seidman, C. Eney, P. Kinnunen, and L. Malmi. Constructing a core literature for computing education research. In SIGCSE Bulletin, volume 37, pages 152--161, 2005.F. Prados, I. Boada, J. Soler, and J. Poch. Automatic generation and correction of technical exercices. In International Conference on Engineering and Computer Education (ICECE 2005), 2005.M. Supic, K. Brkic, T. Hrkac, Z. Mihajlovic, and Z. Kalafatic. Automatic recognition of handwritten corrections for multiple-choice exam answer sheets. In Information and Communication Technology, Electronics and Microelectronics (MIPRO), pages 1136--1141, 2014.S. Tung, T. Lin, and Y. Lin. An exercise management system for teaching programming. In Journal of Software, 2013.T. Wang, X. Su, Y. Wang, and P. Ma. Semantic similarity-based grading of student programs. In Information and Software Technology, volume 49, pages 99--107, 2007

Sustainable Design and Building Information Modelling: Case Study of Energy Plus House, Hieron's Wood, Derbyshire UK

In this paper the method for sustainable design analysis (SDA) integration with building information modelling (BIM) is explored, through the prism of a complex case study based research. BIM model federation and integration challenges are reported, including issues with combining geometry and managing attribute data. The research defines SDA as rapid and quantifiable analysis of multitude of sustainable alternatives and ‘what if’ questions posed by a design team during the early stages of the project, when the benefits of correct decisions can significantly exceed the actual investment required. The SDA concept and BIM integration findings are explained from conceptualisation to calculation stage, emphasising the importance of an iterative over a linear approach. The research approach adopted has led to more informed sustainable solutions at earlier stages of project development, with a generally lower level of development (LOD) and computational/modelling effort required

Emergent requirements for supporting introductory programming

The problems associated with learning and teaching first year University Computer Science (CS1) programming classes are summarized showing that various support tools and techniques have been developed and evaluated. From this review of applicable support the paper derives ten requirements that a support tool should have in order to improve CS1 student success rate with respect to learning and understanding

Index to Library Trends Volume 33

published or submitted for publicatio

Commercialisation of precision agriculture technologies in the macadamia industry

A prototype vision-based yield monitor has been developed for the macadamia industry. The system estimates yield for individual trees by detecting nuts and their harvested location. The technology was developed by the National Centre for Engineering in Agriculture, University of Southern Queensland for the purpose of reducing labour and costs in varietal assessment trials where yield for individual trees are required to be measured to indicate tree performance. The project was commissioned by Horticulture Australia Limited

Special Libraries, Winter 1986

Volume 77, Issue 1https://scholarworks.sjsu.edu/sla_sl_1986/1000/thumbnail.jp

Benefits of Computer Based Content Analysis to Foresight

Purpose of the article: The present manuscript summarizes benefits of the use of computer-based content analysis in a generation phase of foresight initiatives. Possible advantages, disadvantages and limitations of the content analysis for the foresight projects are discussed as well. Methodology/methods: In order to specify the benefits and identify the limitations of the content analysis within the foresight, results of the generation phase of a particular foresight project performed without and subsequently with the use of computer based content analysis tool were compared by two proposed measurements. Scientific aim: The generation phase of the foresight is the most demanding part in terms of analysis duration, costs and resources due to a significant amount of reviewed text. In addition, the conclusions of the foresight evaluation are dependent on personal views and perceptions of the foresight analysts as the evaluation is based merely on reading. The content analysis may partially or even fully replace the reading and provide an important benchmark. Findings: The use of computer based content analysis tool significantly reduced time to conduct the foresight generation phase. The content analysis tool showed very similar results as compared to the evaluation performed by the standard reading. Only ten % of results were not revealed by the use of content analysis tool. On the other hand, several new topics were identified by means of content analysis tool that were missed by the reading. Conclusions: The results of two measurements should be subjected to further testing within more foresight projects to validate them. The computer based content analysis tool provides valuable benchmark to the foresight analysts and partially substitute the reading. However, a complete replacement of the reading is not recommended, as deep understanding to weak signals interpretation is essential for the foresight