Top N optimization issues in MM databases

Introduction In multi media (MM) DBMSs the usual way of operation in case of a MM retrieval query is to compute some ranking based on statistics and distances in feature spaces. The MM objects are then sorted by descending relevance relative to the given query. Since users are limited in their capabilities of reviewing all objects in that ranked list only a reasonable top of say N objects is returned. However, this can turn out to be a quite time consuming process. The first reason is that the number of objects (i.e. documents) in the DBMS is usually very large (10 6 or even more). From the information retrieval field it is known that usually half of all objects (e.g. documents) contains at least one query term; so, even considering only these objects might be very time consuming. The same may hold for MM in general. The problem of top N MM query optimization is to find techniques to limit the set of objects taken into consideration during th

Data collection, analysis methods and equipment for naturalistic studies and requirements for the different application areas. PROLOGUE Deliverable D2.1

Naturalistic driving observation is a relatively new method for studying road safety issues, a method by which one can objectively observe various driver- and accident related behaviour. Typically, participants get their own vehicles equipped with some sort of data logging device that can record various driving behaviours such as speed, braking, lane keeping/variations, acceleration, deceleration etc., as well as one or more video cameras. In this way normal drivers are observed in their normal driving context while driving their own vehicles. Optimally, this allows for observation of the driver, vehicle, road and traffic environments and interaction between these factors. The main objective of PROLOGUE is to demonstrate the usefulness, value, and feasibility of conducting naturalistic driving observation studies in a European context in order to investigate traffic safety of road users, as well as other traffic related issues such as eco-driving and traffic flow/traffic management. The current deliverable aims to develop an inventory of the current and appropriate data collection and data analysis equipment for naturalistic observation studies together with a theoretical analysis of the requirements for different application areas. The deliverable also discusses data quality issues and top level data base management requirements. Among the reviewed literature, maximal use is made of the extensive knowledge and experience that comes from the EU projects FESTA and EuroFOT, the 100car study and the SHRP2 preparatory safety

Level 4 commercial autonomous vehicle control system transition to an open-source solution

This paper introduces a novel approach for transferring the entire set of low-level control systems from one robot bus, i.e., an autonomous vehicle (AV) shuttle, to another with distinct electronics and mechanical specifications. The research entails a series of experiments to assess the reliability and safety of the AV shuttle after integrating the critical control systems responsible for steering, accelerating, and braking into the target shuttle. The ultimate goal is to meet the necessary requirements for registering the target AV shuttle as a legal vehicle on the roads in Estonia. Consequently, several crucial tests of the shuttleâs low-level control system were conducted, e.g., intentionally disconnecting different subsystems to simulate sudden failures and evaluate whether the shuttle responds in accordance with the appropriate protocols. As a case study, the upgraded autonomous shuttle was tested on the streets of Tallinn. The most relevant findings are introduced in the second part of this paper. The outcomes of the study demonstrate the feasibility of seamlessly transferring low-level control systems between various models of autonomous shuttles, eliminating the risk of encountering safety or reliability issues

Analyzing data in the Internet of Things

The Internet of Things (IoT) is growing fast. According to the International Data Corporation (IDC), more than 28 billion things will be connected to the Internet by 2020—from smartwatches and other wearables to smart cities, smart homes, and smart cars. This O’Reilly report dives into the IoT industry through a series of illuminating talks and case studies presented at 2015 Strata + Hadoop World Conferences in San Jose, New York, and Singapore. Among the topics in this report, you’ll explore the use of sensors to generate predictions, using data to create predictive maintenance applications, and modeling the smart and connected city of the future with Kafka and Spark. Case studies include: Using Spark Streaming for proactive maintenance and accident prevention in railway equipment Monitoring subway and expressway traffic in Singapore using telco data Managing emergency vehicles through situation awareness of traffic and weather in the smart city pilot in Oulu, Finland Capturing and routing device-based health data to reduce cardiovascular disease Using data analytics to reduce human space flight risk in NASA’s Orion program This report concludes with a discussion of ethics related to algorithms that control things in the IoT. You’ll explore decisions related to IoT data, as well as opportunities to influence the moral implications involved in using the IoT

Automating the Implementation of the Updated Grade Severity Rating System (GSRS) for Wyoming Mountain Passes

RS08220Truck crashes on steep downgrades caused by excessive brake heating is an ongoing concern for the Wyoming Department of Transportation (WYDOT). Crashes resulting from brake failure on downgrades cause a devastating toll on lives and property. To counter such crashes, WYDOT initiated a research project in 2016 to update a previous Grade Severity Rating System (GSRS) model originally developed in 1981. This was necessary due to the previous GSRS model being considered insufficiently representative of current truck characteristics, which have undergone significant changes over the decades. This study sought to fulfill Phase II of the GSRS study and was aimed at achieving three objectives. The first objective was to validate the GSRS model for trucks that have only drum brakes installed. The second objective was to make the updated GSRS fully implementable by incorporating horizontal curves into the formulation of the weight specific speed (WSS) signs. The final objective was to develop a software that simplifies the implementation of the GSRS and the formulation of WSS signs by generating maximum descent speeds for different weight categories as output

Distributed and Communication-Efficient Continuous Data Processing in Vehicular Cyber-Physical Systems

Processing the data produced by modern connected vehicles is of increasing interest for vehicle manufacturers to gain knowledge and develop novel functions and applications for the future of mobility.Connected vehicles form Vehicular Cyber-Physical Systems (VCPSs) that continuously sense increasingly large data volumes from high-bandwidth sensors such as LiDARs (an array of laser-based distance sensors that create a 3D map of the surroundings).The straightforward attempt of gathering all raw data from a VCPS to a central location for analysis often fails due to limits imposed by the infrastructure on the communication and storage capacities. In this Licentiate thesis, I present the results from my research that investigates techniques aiming at reducing the data volumes that need to be transmitted from vehicles through online compression and adaptive selection of participating vehicles. As explained in this work, the key to reducing the communication volume is in pushing parts of the necessary processing onto the vehicles\u27 on-board computers, thereby favorably leveraging the available distributed processing infrastructure in a VCPS.The findings highlight that existing analysis workflows can be sped up significantly while reducing their data volume footprint and incurring only modest accuracy decreases. At the same time, the adaptive selection of vehicles for analyses proves to provide a sufficiently large subset of vehicles that have compliant data for further analyses, while balancing the time needed for selection and the induced computational load

Flexible and scalable digital library search

In this report the development of a specialised search engine for a digital library is described. The proposed system architecture consists of three levels: the conceptual, the logical and the physical level. The conceptual level schema enables by its exposure of a domain specific schema semantically rich conceptual search. The logical level provides a description language to achieve a high degree of flexibility for multimedia retrieval. The physical level takes care of scalable and efficient persistent data storage. The role, played by each level, changes during the various stages of a search engine's lifecycle: (1) modeling the index, (2) populating and maintaining the index and (3) querying the index. The integration of all this functionality allows the combination of both conceptual and content-based querying in the query stage. A search engine for the Australian Open tennis tournament website is used as a running example, which shows the power of the complete architecture and its various component

A workflow for geocoding South African addresses

There are many industries that have long been utilizing Geographical Information Systems (GIS) for spatial analysis. In many parts of the world, it has gained less popularity because of inaccurate geocoding methods and a lack of data standardization. Commercial services can also be expensive and as such, smaller businesses have been reluctant to make a financial commitment to spatial analytics. This thesis discusses the challenges specific to South Africa as well as the challenges inherent in bad address data. The main goal of this research is to highlight the potential error rates of geocoded user-captured address data and to provide a workflow that can be followed to reduce the error rate without intensive manual data cleansing. We developed a six step workflow and software package to prepare address data for spatial analysis and determine the potential error rate. We used three methods of geocoding: a gazetteer postal code file, a free web API and an international commercial product. To protect the privacy of the clients and the businesses, addresses were aggregated with precision to a postcode or suburb centroid. Geocoding results were analysed before and after each step. Two businesses were analysed, a mid-large scale business with a large structured client address database and a small private business with a 20 year old unstructured client address database. The companies are from two completely different industries, the larger being in the financial industry and the smaller company an independent magazine in publishing

Fully Scalable Train Braking Simulation Environment

DTFR5311D00008LTransportation Technology Center, Inc. (MxV Rail), through a research project funded by Federal Railroad Administration (FRA), developed a Concept of Operations (ConOps), documented the infrastructure design, and developed software to support a virtualized fully scalable train braking simulation environment (FSTBSE) that expands upon the capabilities of an existing simulation environment originally developed for evaluation of braking algorithms for Positive Train Control (PTC) applications. The new environment will provide the ability to complete simulations more efficiently and support a concept for on-demand simulations to support new software functions and processes with the potential to improve the safety and operational efficiency of train control and other applications, such as Interoperable Train Control (ITC) PTC and Energy Management Systems (EMS)