How do people use maps t o navigate through the world?

Design Recipes for FPGAs

Most of the maps used today are what we call pan-scalar maps, i.e. interactive zoomable applications comprised of numerous maps of a particular area at different zoom levels (i.e. scales). We argue that such maps require a pan-scalar map design, which may differ significantly from established map design axioms and standards. This review is twofold. First, it reviews current practices in pan-scalar map design. Second, it summarizes and synthesizes literature about pan-scalar map design, as well as human-computer interaction (HCI) best practices for pan-scalar maps. The review of practices is based on a ScaleMaster analysis of the design of three popular pan-scalar maps: Google Maps, OpenStreetMap, and France's IGN Classic. Discussion centers on both stellar and subpar contemporary pan-scalar map design practices to help guide future practical pan-scalar designs and research on pan-scalar maps broadly.

The 2004 iNEMI Environmentally Conscious Electronics Road map was released to the public in February 2005. This paper outlines the roadmapping process used by the International Electronics Manufacturing Initiative to identify future research, development, and implementation needs to continue the growth of the world-wide electronics industry. It contains nineteen individual technology roadmaps covering all aspects of the global electronics industry and its supply chain. One of these nineteen roadmaps is the Environmentally Conscious Electronics (ECE) Roadmap. The output of this roadmapping process is used to establish projects to close gaps identified in the roadmap. The three generations of NEMI projects to eliminate Pb solder were developed to close identified environmental technology gaps from the 1998, 2000, and 2002 roadmaps. The 2004 ECE roadmap focuses on five key areas: design, energy, recycling, materials, and sustainability. Not only are the technical issues roadmapped in these five areas, but also the regulatory and business issues as well. This paper is the first detailed presentation of the technology and business gaps and research and development needs identified in the five key environmental areas. The paper discusses the findings and recommendations made by the roadmap participants. The paper concludes by discussing the future environmental challenges and recommendations made in the roadmap for the world-wide electronics industry over the next decade.

Road network map is one of the datasets that are used in many different applications. Many smart cities have more than one Road Network map from different sources (government authorities, private enterprise, or volunteered). Be that as it may, there is a high chance of mismatches between road maps that represent the same area for different reasons. These reasons include: one of the datasets is not updated; datasets have different names for the same road; and so on. As a result, matching the roads in such datasets with each other is challenging. This paper introduces a framework that demonstrates methods of how two datasets for the same area can be matched to each other even though there are some data discrepancies. In addition, it gives an overview of each component of the framework and focuses mainly on the similarity measurements. These measurements are local divergence measurements and global divergence measurement. Local divergence measurements compare two roads from different datasets to each other to see if they are similar or not by deciding if these two roads have a similar shape as well as the same length. On the other hand, global divergence measurement is used in order to ensure that these two roads are similar in the real world, not different roads that happen to be beside each other having similar length and shape. This paper discusses several types of applications that could utilize this framework not only for matching different road maps and unify the information for smart cities usages but also data enrichment and being up-to-date.

We propose the use of deep neural networks (DNN) for solving the problem of inferring the position and relevant properties of lanes of urban roads with poor or absent horizontal signalization, in order to allow the operation of autonomous cars in such situations. We take a segmentation approach to the problem and use the Efficient Neural Network (ENet) DNN for segmenting LiDAR remission grid maps into road maps. We represent road maps using what we called road grid maps. Road grid maps are square matrixes and each element of these matrixes represents a small square region of real-world space. The value of each element is a code associated with the semantics of the road map. Our road grid maps contain all information about the roads' lanes required for building the Road Definition Data Files (RDDFs) that are necessary for the operation of our autonomous car, IARA (Intelligent Autonomous Robotic Automobile). We have built a dataset of tens of kilometers of manually marked road lanes and used part of it to train ENet to segment road grid maps from remission grid maps. After being trained, ENet achieved an average segmentation accuracy of 83.7%. We have tested the use of inferred road grid maps in the real world using IARA on a stretch of 3.7 km of urban roads and it has shown performance equivalent to that of the previous IARA's subsystem that uses a manually generated RDDF.

A review of the last 50 years finds that the traditional breakdown of Soviet cartography into its specialized research disciplines no longer conforms to current needs. Soviet cartography has been divided historically into mathematical cartography, map science (the study of maps and their uses), map compilation and editing, map design and production. A growing specialization in cartography by thematic disciplines (geomorphic mapping, agricultural mapping, etc.) with widely differing requirements and principles of compilation and editing suggests the need for a restructuring of the research disciplines. In addition to mathematical cartography, concerned with map projections and map measurements, the new structure would include: technical cartography (the study of source materials, map design and production); natural-historic cartography (principles of compilation and editing of maps of the physical environment), and socioeconomic cartography (concerned with the mapping of human phenomena).

Schematic drawings of route directions are one of the most common forms of graphic communication. People make sketches to communicate geographical ideas, and professionally designed schematic maps give orientation to thousands of users of a public transport system. Creating a schematic map for representing a transport network may be seen as a straightforward task; however, the underlying design of such maps can be quite complex. Map designers apply, consciously or subconsciously, various cartographic generalization techniques to emphasize important information and to improve the clarity of map content. At present, traditional mapping and GIS literature offers very little guidance to a map designer seeking cartographic rules or practical ideas for representing the elaborate route data of public transport systems schematically. This article aims to contribute to the design challenges of schematic, route-based mapping. Information about schematic maps and symbolization of route-based data is given. A case study of schematic map design for a public transport network is presented to show the need for support of cartographic science for the creation of schematic transport maps.

A modular symptom-specific (MSS) programme of early intervention group cognitive behaviour therapy for psychosis might confer additional therapeutic benefits and clinical and financial efficiency, but the approach is empirically untested. Therefore, we devised a novel MSS programme to test - in a culturally diverse 'Real World' early intervention service - its relevancy, feasibility, acceptability and safety. The MSS programme comprised six different groups across 33 sessions: Psycho-Education (3), Mood-Management (5), Delusions (8), Auditory Hallucinations (8), Past Auditory Hallucinations (3) and Negative Symptoms (6). All patients were eligible for psycho-education, but other groups required a specific symptom. Patients (n = 166, 37% White) showed wide heterogeneity in the activity, type and number of symptoms, and group-relevant symptoms were common. Eighteen groups have run so far, each type of group at least once, 58/166 (35%) of patients attended across 281/412 (68%) group sessions, 46/58 (79%) of patients re-attended, and the 58 patients attended groups a mean of 4.8 times. Patients were significantly (P < 0.05) more likely to attend the programme if they had a schizophrenia diagnosis, a longer psychotic illness length or one active group-relevant (psychotic/mood) symptom. Diagnostically uncertain psychosis patients were almost significantly (P = 0.05) less likely to attend the programme. duration of untreated psychosis and ethnicity were unrelated to attendance/re-attendance. No group-related risk incidents occurred. A MSS programme approach is highly relevant to early intervention symptom heterogeneity and is feasible, culturally acceptable and safe; it also appears particularly efficient. Future research should now test its clinical efficacy.

The road map in this research proves that the universe emerged from SUSY. Proving that, we link between two different classes of SM, fermions, and bosons in supersymmetry with their properties in the Standard Model of particle physics. According to SM properties, the bosons have spin one, while fermions have spin 1/2. We suggest differentiating between bosons and fermions angular momentum in our real world with a supersymmetrical state. We presume that bosons and fermions in their supersymmetric environment will have akin graviton spin angular momentum 2, while their superpartners will have spin one. In addition to that, in the supersymmetric environment, the fermion, boson, and their counterparts experience CPT conservation. They enjoy eternity with "Gravitons." Once upon a time, the boson and fermion descended from a supersymmetric state down through string theories' dimensions and M-theory's branes, stabilizing and forming SM quarks and, therefore, everything in our real world

ABSTRACTFloods are one of the most significant hazards in Europe. This paper describes an iterative approach consisting of designing and evaluating static flood risk maps. In the first step, the use of different colour schemes and background types (e.g. topographic map, street map, and satellite images) is evaluated in an online survey. Next the design is optimized based on the outcomes of dedicated focus groups. The usability tests include the users’ preference, also considering their characteristics (age, gender, and expertise). The obtained results of each step are integrated to optimize the design of evacuation route maps and flood depth maps.

IntroductionAugmented Reality (AR) overlays context-sensitive information onto the real world in a meaningful way. As AR bridges the gap between the real and virtual world, it holds potential to enhance...

The measure of map information has been one of the key issues in assessing cartographic quality and map generalization algorithms. It is also important for developing efficient approaches to transfer geospatial information. Road network is the most common linear object in real world. Approximately describe road network information will benefit road map generalization, navigation map production and urban planning. Most of current approaches focused on node diversities and supposed that all the edges are the same, which is inconsistent to real-life condition, and thus show limitations in measuring network information. As real-life traffic flow are directed and of different quantities, the original undirected vector road map was first converted to a directed topographic connectivity map. Then in consideration of preferential attachment in complex network study and rich-club phenomenon in social network, the from and to weights of each edge are assigned. The from weight of a given edge is defined as the connectivity of its end node to the sum of the connectivities of all the neighbors of the from nodes of the edge. After getting the from and to weights of each edge, edge information, node information and the whole network structure information entropies could be obtained based on information theory. The approach has been applied to several 1 square mile road network samples. Results show that information entropies based on edge diversities could successfully describe the structural differences of road networks. This approach is a complementarity to current map information measurements, and can be extended to measure other kinds of geographical objects.

Three characteristics of hardcopy maps, scale, interrelatedness of symbols, and standardized symbology, are reviewed. Their implications for future map-related research and design are discussed. Research on types of coding used in visual displays is discussed in terms of its applicability to hardcopy maps. Specific suggestions for hardcopy map design are based on the literature comparing different kinds of map products.

PurposeThis research study seeks to identify what graduating students and alumni perceive to be of most value in courses, and in turn the relationship of those perceptions with the information in evaluations conducted by students at the conclusion of courses.Design/methodology/approachThe project involves empirical research utilizing standard student course evaluation data, and rigorous matching alumni survey data. A focus group, as well as prior academic research, informs the design.FindingsThere are several key conclusions from this study comparing student and alumni perceptions of course satisfaction. Consistent with end‐of‐program survey and focus group observations, career relevance clearly grows with time in importance for determining course satisfaction. Career relevance is not a statistically significant factor for course satisfaction using end‐of‐course student survey responses, but grows to a statistically significant determinant utilizing alumni survey data, larger than both the extent of learning and instructor performance; moreover, instructor performance appears to become less important.Research limitations/implicationsWhile survey responses for individuals as both students and alumni cannot be linked in this study, the high response rate of alumni and the pooling of data suggest results are robust.Practical implicationsIf instructors want students, once they become alumni, to be satisfied with their course experience, they need to teach material which will be truly useful in their careers, even if students do not fully appreciate it during class. And if university presidents want satisfied alumni, they need to ensure their school's curriculum includes material that may be applied in the real world, and that the measures of teaching effectiveness utilized for compensation purposes do not stress too highly traditional measures of student satisfaction.Social implicationsEducators can provide students with a more long‐term satisfying educational experience by ensuring curriculum includes practical material that is truly relevant for careers.Originality/valueStudent evaluations have been commonly used in determining the success of a course, and the effectiveness of their instructors. However, there has only been limited analysis of student evaluations as a measure of what matters most – the benefit to the student once they graduate and move into the working world. Empirical results based on student and alumni survey data identify differences in perceptions between students and alumni, and suggest key recommendations for both instructors and university administrators.

University-derived research (e.g. science) is useful in ‘real world’ business applications, so effective collaboration is desirable. However, for work to actually proceed, strategic and policy-level drivers must align with the incentive structures and constraints upon individual university-based scientists and their motivations. This briefing aims to foster collaborations by providing a view from the perspective of individual academics. Specifically, it examines workload (i.e. specified tasks) and incentive structures (i.e. assessment criteria) to tackle two questions: What motivates academics to do specific work? And, reciprocally, what might constrain them? In light of this specific, pragmatic actions, including short-term and time-efficient steps are proposed in a ‘user guide’ to help initiate and nurture collaborations. And, some modes of institutional support are suggested. Main Points - Like other professions academics suffer time pressure, i.e. amid 20-50 key duties up to 0.5 days per week might potentially be found for activities with ‘real world’ impact. - Typically, for impact-related activities others must be sacrificed (e.g. research), creating a tension. - As yet, even in countries strongly promoting collaboration, the overriding imperative remains for academics to publish research (i.e. peer-reviewed journal articles). - Thus, to justify working with business, impact-related work must inspire curiosity and facilitate future novel research (e.g. science) to mitigate this conflict.