Developing a knowledge-based urban development analysis framework : the case of multimedia super corridor, Malaysia

Purpose: In the global knowledge economy, investment in knowledge-intensive industries and information and communication technology (ICT) infrastructures are seen as significant factors in improving the overall socio-economic fabric of cities. Consequently knowledge-based urban development (KBUD) has become a new paradigm in urban planning and development, for increasing the welfare and competitiveness of cities and regions. The paper discusses the critical connections between KBUD strategies and knowledge-intensive industries and ICT infrastructures. In particular, it investigates the application of the knowledge-based urban development concept by discussing one of South East Asia’s large scale manifestations of KBUD; Malaysia’s Multimedia Super Corridor. ----- ----- Design/methodology/approach: The paper provides a review of the KBUD concept and develops a knowledge-based urban development assessment framework to provide a clearer understanding of development and evolution of KBUD manifestations. Subsequently the paper investigates the implementation of the KBUD concept within the Malaysian context, and particularly the Multimedia Super Corridor (MSC). ----- ----- Originality/value: The paper, with its KBUD assessment framework, scrutinises Malaysia’s experince; providing an overview of the MSC project and discussion of the case findings. The development and evolution of the MSC is viewed with regard to KBUD policy implementation, infrastructural implications, and the agencies involved in the development and management of the MSC. ----- ----- Practical implications: The emergence of the knowledge economy, together with the issues of globalisation and rapid urbanisation, have created an urgent need for urban planners to explore new ways of strategising planning and development that encompasses the needs and requirements of the knowledge economy and society. In light of the literature and MSC case findings, the paper provides generic recommendations, on the orchestration of knowledge-based urban development, for other cities and regions seeking to transform to the knowledge economy.

The influence of underreported crashes on hotspot identification

Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.

Real-time volume estimation of a dragline payload

This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%.

Domestication to crop improvement: Genetic resources for sorghum and saccharum (Andropogoneae)

Background Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

Structural Systematics of the Anhydrous 1:1 Proton-Transfer Compounds of 3,5-Dinitrosalicylic Acid with Aniline and Monosubstituted Anilines

The crystal structures of the proton-transfer compounds of 3,5-dinitrosalicylic acid (DNSA) with a series of aniline-type Lewis bases [aniline, 2-hydroxyaniline, 2-methoxyaniline, 3-methoxyaniline, 4-fluoroaniline, 4-chloroaniline and 2-aminoaniline] have been determined and their hydrogen-bonding systems analysed. All are anhydrous 1:1 salts: [(C6H8N)+(C7H3N2O7)-], (1), [(C6H8NO)+(C7H3N2O7)-], (2), [(C7H10NO)+(C7H3N2O7)-], (3), [(C7H10NO)+(C7H3N2O7)-], (4), [(C6H7FN)+(C7H3N2O7)-], (5), [(C6H7ClN)+(C7H3N2O7)-], (6), and [(C6H9N2)+(C7H3N2O7)-], (7) respectively. Crystals of 1 and 6 are triclinic, space group P-1 while the remainder are monoclinic with space group either P21/n (2, 4, 5 and 7) or P21 (3). Unit cell dimensions and contents are: for 1, a = 7.2027(17), b = 7.5699(17), c = 12.9615(16) Å, α = 84.464(14), β = 86.387(15), γ = 75.580(14)o, Z = 2; for 2, a = 7.407(3), b = 6.987(3), c = 27.653(11) Å, β = 94.906(7)o, Z = 4; for 3, a = 8.2816(18), b = 23.151(6), c = 3.9338(10), β = 95.255(19)o, Z = 2; for 4, a = 11.209(2), b = 8.7858(19), c = 15.171(3) Å, β = 93.717(4)o, Z = 4; for 5, a = 26.377(3), b = 10.1602(12), c = 5.1384(10) Å, β = 91.996(13)o, Z = 4; for 6, a = 11.217(3), b = 14.156(5), c = 4.860(3) Å, α = 99.10(4), β = 96.99(4), γ = 76.35(2)o, Z = 2; for 7, a = 12.830(4), b = 8.145(3), c = 14.302(4) Å, β = 102.631(6)o, Z = 4. In all compounds at least one primary linear intermolecular N+-H…O(carboxyl) hydrogen-bonding interaction is present which, together with secondary hydrogen bonding results in the formation of mostly two-dimensional network structures, exceptions being with compounds 4 and 5 (one-dimensional) and compound 6 (three-dimensional). In only two cases [compounds 1 and 4], are weak cation-anion or cation-cation π-π interactions found while weak aromatic C-H…O interactions are insignificant. The study shows that all compounds fit the previously formulated classification scheme for primary and secondary interactive modes for proton-transfer compounds of 3,5-dinitrosalicylic acid but there are some unusual variants.

Process mining manifesto

Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

Exploring Rhythmic Automata

The use of Cellular Automata (CA) for musical purposes has a rich history. In general the mapping of CA states to note-level music representations has focused on pitch mapping and downplayed rhythm. This paper reports experiments in the application of one-dimensional cellular automata to the generation and evolution of rhythmic patterns. A selection of CA tendencies are identified that can be used as compositional tools to control the rhythmic coherence of monophonic passages and the polyphonic texture of musical works in broad-brush, rather than precisely deterministic, ways. This will provide the composer and researcher with a clearer understanding of the useful application of CAs for generative music.

Acoustic hazard detection for pedestrians with obscured hearing

Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

SeqSLAM : visual route-based navigation for sunny summer days and stormy winter nights

Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

Tampere region under the microscope : a critical analysis from the knowledge perspective

Purpose – In the context of global knowledge economy, knowledge-based urban development (KBUD) is seen as an effective development strategy for city-regions to survive, flourish and become highly competitive urban agglomerations – i.e., a knowledge city-region. This paper aims to evaluate the KBUD dynamics, capacity and potentials of a rapidly emerging knowledge city-region of Finland – Tampere region. Design/methodology/approach – The paper undertakes a review of the literature on regional development in the knowledge economy era. It adopts a qualitative analysis technique to scrutinize the dynamics, capacity and potentials of Tampere region. The semi-structured interview process starts with the pre-determined key actors of the city-region with an aim of determining the other key players. Next, with the participation of all key players to the interviews, the research reveals the principal issues, assets and mechanisms that relate to KBUD, and portrays the strengths, weaknesses, opportunities and threats of the city-region. A critical analysis of the findings along with the previous studies is undertaken to provide a clear picture of the dynamics, capacity and potentials of the emerging knowledge city-region. Originality/value – This paper reports the findings of a pioneering study focusing on the investigation of the KBUD dynamics, capacity and potentials of Tampere region. The paper critically evaluates the city-region from the knowledge perspective with the lens of KBUD, and the lessons learned and the methodological approach of the paper shed light to other city-regions seeking such development. Practical implications – The paper discusses the findings of a study from Tampere region that critically scrutinizes the KBUD experience of the city-region. The research provides an invaluable opportunity to inform the regional decision-, policy- and plan-making mechanisms by determining key issues, actors, assets, processes and potential development directions for the KBUD of Tampere region.