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In order to reduce radiation hazards, a mobile robot for detecting and grasping radioactive sources is designed. The robot is based on the ROS platform, uses the radioactive source detector to locate the radioactive source and moves to the radioactive source, and uses the mechanical gripper carried by the body to grab the corresponding radioactive source. In order to improve its stability and adaptability, a remote real-time control method is used to realize the motion capture of the detection robot. The robot operates the radioactive source, reducing the environmental pollution of the open-air radioactive source, and at the same time avoiding the radiation damage to the corresponding staff.

In order to achieve precise control of the motion state of a working robot in a nuclear environment, and to ensure that the working robot can work stably in a complex nuclear environment, a neural network PID algorithm is carried out on the driving system of the wheeled mobile robot; in multiple groups of walking units A speed compensator is designed between the control systems to make the control systems of multiple groups of walking units have a coupling relationship, which can ensure the synchronization between multiple groups of walking units. Use the corresponding program code to experiment and simulate the above control method. The experimental results show that the neural network PID can realize the precise control of the robot's motion state. Compared with the traditional PID, it has the characteristics of small overshoot and short transition time; it is realized by the speed compensator established between multiple groups of walking units. The synchronized and coordinated operation of multiple sets of walking units enhances the smoothness of the operation robot and can meet the operation requirements of the operation robot in a nuclear environment.

In this article, we use the Alexnet network in deep learning to determine whether the lung CT images are infected with covid-19.First of all, in the data preprocessing stage, the original CT image data is scaled and normalized to reduce noise interference. The batch operation of training set and test set can increase the training speed;Secondly, build an eight-layer Alexnet network model, set reasonable hyperparameters for each layer of the network, define the loss function and optimizer, and use the processed data to train the weight parameters of each layer in the network model.Finally, three indicators of accuracy, accuracy and recall are used to quantify the effect of model classification, and the impact of different training times on these three indicators is compared to select the best classification model.At the same time, use pyqt5 to write the corresponding auxiliary detection interface to facilitate the display of test results and the selection of classification models.The construction of the network model, the definition of the loss function and the definition of the optimizer are all based on the Pytorch deep learning framework.

A robot is designed for radiation source detection and disposal, which uses a six-wheel suspension mobile platform. The robot carries a radiation source detector to collect the dose rate of the radiation source and locate it. The robot system is composed of a remote control terminal and a mobile robot, which can complete the autonomous positioning and manually searching for the radiation source. The experimental results show that the robot can complete the detection and disposal of the out of control radiation source, and the system runs stably and reliably, ensuring the safety of relevant personnel in the radiation source search process.

New trends in GIS such as Volunteered Geographical Information (VGI), Citizen Science, and Urban Sensing, have changed the shape of the geoinformatics landscape. The OpenStreetMap (OSM) project provided us with an exciting, evolving, free and open solution as a base dataset for our geoserver and spatial data provider for our research. OSM is probably the best known and best supported example of VGI and user generated spatial content on the Internet. In this paper we will describe current results from the development of quality indicators for measures for OSM data. Initially we have analysed the Ireland OSM data in grid cells (5km) to gather statistical data about the completeness, accuracy, and fitness for purpose of the underlying spatial data. This analysis included: density of user contributions, spatial density of points and polygons, types of tags and metadata used, dominant contributors in a particular area or for a particular geographic feature type, etc. There greatest OSM activity and spatial data density is highly correlated with centres of large population. The ability to quantify and assess if VGI, such as OSM, is of sufficient quality for mobile mapping applications and Location-based services is critical to the future success of VGI as a spatial data source for these technologies.

In this paper we describe the software architecture of a prototype web-based GIS system for the deliver environmental research data in Ireland. The central component in this system is OpenStreetMap which provides the base layers of geographical data. An OpenStreetMap data collection campaign for our university town was carried out earlier this year yieldeding a spatially rich OpenStreetMap representation of Maynooth. Our server (OpenStreetMap database, supporting software, and specially generated map tiles) has been used by several GIS and location-based services projects in our department. One such example is a mobile device-based pedestrian navigation system is described in this paper. We describe some of the components of our server system. This includes a description of the management of the local copy of the OpenStreetMap database and the generation of sets of customised map tiles.

This research presents a practical solution for mobile routing services for small towns using open sources. Free mapping application program interfaces (API) provided by web map services, including routing services, are available to create customised map based web services combining their cartographic base data with the users own data. However, most applications focus on big cities. Location based services in small towns are generally few as many people believe there is a little demand in such areas. However, the demand of LBS applications in some small towns can be as strong as big cities, for example university towns and tourist resorts. Better location based services, especially routing services, can help strangers get familiar with the environment in a short time and lead them to places of interest. However, there are two problems to overcome for such systems. One is cost both in terms of data costs and development time. Open source data and mash-up technology could provide an answer. The other problem is the availability of suitable data of the required accuracy and detail. This is more serious as most free map services, such as Google Maps and Microsoft Bing Maps (Virtual Earth), don’t provide sufficient detailed and accurate data for routing services. One feasible and economical way is to create the map ourselves and have it updated by the public. OpenStreetMap (OSM) is a free, open and fast developing map of the world. Detailed data was collected using a GPS logging device and uploaded to OpenStreetMap. The CloudMade API was used to provide multi-mode routing services together with turn-by-turn descriptions for car users, bicycle riders, and pedestrians. This solution is relatively easy and fast to deploy. Maynooth, a small university town in County Kildare Ireland, was used as a test bed. A prototype navigation system was developed for mobile users using the Windows Mobile platform. The system demonstrates that a solution to detailed navigational services for pedestrians, cyclists and drivers can be economical and feasible for small towns.

Feedback control theory has been widely used in many fields; this paper introduces this theory into a model for a pedestrian navigation system. Based on the model, several feedback channels are designed and analysed using control theory. The pedestrian is not only a data receiver but also a data collector. All collected information is stored in a temporal database and can be used for spatial-temporal analysis. At the same time, feedback control theory can integrate all modules of the system as whole, which can help to improve the overall effectiveness. Based on information fed back and feedback control theory, the pedestrian navigation system will help users to "see more, understand better, and decide more quickly."

The university campus of NUI Maynooth forms a substantial part of Maynooth town. Location based services (LBS) could be important for visitors to the campus and town in assisting them to make the mast of their stay, particularly if they are not familiar with the town. In this paper we discuss an LBS application for Maynooth university campus and Maynooth town based on OpenStreetMap. The solution uses open source software and public participation rules to build its database. The work provides a prototype LBS system for NUI Maynooth which is currently under active development. The paper mainly describes some completed components of the work: data acquisition and pedestrian navigation algorithm design. Future work on path optimization and 3D applications is also discussed.

We present a web-based, multi-lingual, campus guidance system with emphasis on pedestrian navigation aimed at providing support for delegates attending International Conferences at the National University of Ireland Maynooth (NUIM) campus. A special campus guidance system could improve the logistics of the conference. Potentially such improvements could attract more delegates to the conference. The Cloudmade Web Map Lite API which uses OpenStreetMap has been used for creating this interface. The system generates shortest pedestrian paths using both outdoor pavements and indoor corridors between various buildings and points of interests (POI). For visual assistance in pedestrian navigation geotagged images are used along the path at certain points in the route, such as road intersections, when the user needs to get their orientation correct. The interface is available in both English and Chinese language.

The importance of a good campus navigation system cannot be ignored as the users will vary from students, special guests, visitors and multi-lingual attendees. Providing a navigation and guidance system with a multi-lingual interface helps in personalizing the system according to the user’s preference for the language of interaction. [Pascal Neis, 2009] is an example of a multi-lingual routing application for navigation developed at the University of Bonn where optimal paths are generated with textual description in the user’s preferred language. Natural language generation (NLG) is the subfield of artificial intelligence and computational linguistics. It is concerned with the construction of computer systems that can produce understandable texts in human languages and form some underlying non-linguistic representation of information in order to meet specified communicative goals [McDonald D.D., 1987].