Design Led Innovation : exploring the synthesis of needs, technologies and business models

The term Design is used to describe a wide range of activities. Like the term innovation, it is often used to describe both an activity and an outcome. Many products and services are often described as being designed, as they describe a conscious process of linking form and function. Alternatively, the many and varied processes of design are often used to describe a cost centre of an organisation to demonstrate a particular competency. However design is often not used to describe the ‘value’ it provides to an organisation and more importantly the ‘value’ it provides to both existing and future customers. Design Led Innovation bridges this gap. Design Led Innovation is a process of creating a sustainable competitive advantage, by radically changing the customer value proposition. A conceptual model has been developed to assist organisations apply and embed design in a company’s vision, strategy, culture, leadership and development processes.

Strategy content analysis for service identification : a case study on government agencies

In a resource constrained business world, strategic choices must be made on process improvement and service delivery. There are calls for more agile forms of enterprises and much effort is being directed at moving organizations from a complex landscape of disparate application systems to that of an integrated and flexible enterprise accessing complex systems landscapes through service oriented architecture (SOA). This paper describes the analysis of strategies to detect supporting business services. These services can then be delivered in a variety of ways: web-services, new application services or outsourced services. The focus of this paper is on strategy analysis to identify those strategies that are common to lines of business and thus can be supported through shared services. A case study of a state government is used to show the analytical method and the detection of shared strategies.

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.

Genome-wide identification and expression analysis of the NF-Y family of transcription factors in Triticum aestivum

Nuclear Factor Y (NF-Y) is a trimeric complex that binds to the CCAAT box, a ubiquitous eukaryotic promoter element. The three subunits NF-YA, NF-YB and NF-YC are represented by single genes in yeast and mammals. However, in model plant species (Arabidopsis and rice) multiple genes encode each subunit providing the impetus for the investigation of the NF-Y transcription factor family in wheat. A total of 37 NF-Y and Dr1 genes (10 NF-YA, 11 NF-YB, 14 NF-YC and 2 Dr1) in Triticum aestivum were identified in the global DNA databases by computational analysis in this study. Each of the wheat NF-Y subunit families could be further divided into 4-5 clades based on their conserved core region sequences. Several conserved motifs outside of the NF-Y core regions were also identified by comparison of NF-Y members from wheat, rice and Arabidopsis. Quantitative RT-PCR analysis revealed that some of the wheat NF-Y genes were expressed ubiquitously, while others were expressed in an organ-specific manner. In particular, each TaNF-Y subunit family had members that were expressed predominantly in the endosperm. The expression of nine NF-Y and two Dr1 genes in wheat leaves appeared to be responsive to drought stress. Three of these genes were up-regulated under drought conditions, indicating that these members of the NF-Y and Dr1 families are potentially involved in plant drought adaptation. The combined expression and phylogenetic analyses revealed that members within the same phylogenetic clade generally shared a similar expression profile. Organ-specific expression and differential response to drought indicate a plant-specific biological role for various members of this transcription factor family.

Expected values for steps/day in special populations

Objective To assemble expected values for free-living steps/day in special populations living with chronic illnesses and disabilities. Method Studies identified since 2000 were categorized into similar illnesses and disabilities, capturing the original reference, sample descriptions, descriptions of instruments used (i.e., pedometers, piezoelectric pedometers, accelerometers), number of days worn, and mean and standard deviation of steps/day. Results Sixty unique studies represented: 1) heart and vascular diseases, 2) chronic obstructive lung disease, 3) diabetes and dialysis, 4) breast cancer, 5) neuromuscular diseases, 6) arthritis, joint replacement, and fibromyalgia, 7) disability (including mental retardation/intellectual difficulties), and 8) other special populations. A median steps/day was calculated for each category. Waist-mounted and ankle-mounted instruments were considered separately due to fundamental differences in assessment properties. For waist-mounted instruments, the lowest median values for steps/day are found in disabled older adults (1214 steps/day) followed by people living with COPD (2237 steps/day). The highest values were seen in individuals with Type 1 diabetes (8008 steps/day), mental retardation/intellectual disability (7787 steps/day), and HIV (7545 steps/day). Conclusion This review will be useful to researchers/practitioners who work with individuals living with chronic illness and disability and require such information for surveillance, screening, intervention, and program evaluation purposes. Keywords: Exercise; Walking; Ambulatory monitoring

Methodology for evaluating the landscape character of Malaysian heritage urban river corridors

The effects of rapid development have increased pressures on these places exacerbated by the competition between two key industry sectors, commercial base and tourism development. This, in supplement with urbanisation and industrialisation, has posted a high demand for the uses of these spaces. The political scenario and lack of adaptation on ecological principles and public participations in its design approach have sparked stiff environmental, historical and cultural constraint towards its landscape character as well as the ecological system. Therefore, a holistic approach towards improving the landscape design process is extremely necessary to protect human well being, cultural, environmental and historical values of these places. Limited research also has been carried out to overcome this situation. This further has created an urgent need to explore better ways to improve the landscape design process of Malaysian heritage urban river corridor developments that encompass the needs and aspirations of the Malaysian multi-ethnic society without making any drastic changes to the landscape character of the rivers. This paper presents a methodology to develop an advanced Landscape Character Assessment (aLCA) framework for evaluating the landscape character of the places, derived from the perception of two keys yet oppositional stakeholders: urban design team and special interest public. The triangulation of subjectivist paradigm methodologies: the psychophysical approach; the psychological approach; and, the phenomenological approach will be employed. The outcome will be used to improve the present landscape design process for future development of these places. Unless a range of perspectives can be brought to bear on enhancing the form and function of their future development and management, urban river corridors in the Malaysian context will continue to decline.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Modeling object identification and tracking errors on image-based safety assessment of earthmoving operations

Object identification and tracking have become critical for automated on-site construction safety assessment. The primary objective of this paper is to present the development of a testbed to analyze the impact of object identification and tracking errors caused by data collection devices and algorithms used for safety assessment. The testbed models workspaces for earthmoving operations and simulates safety-related violations, including speed limit violations, access violations to dangerous areas, and close proximity violations between heavy machinery. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of device and algorithm errors were investigated for safety planning purposes.

Fast content-based file type identification

Digital forensic examiners often need to identify the type of a file or file fragment based only on the content of the file. Content-based file type identification schemes typically use a byte frequency distribution with statistical machine learning to classify file types. Most algorithms analyze the entire file content to obtain the byte frequency distribution, a technique that is inefficient and time consuming. This paper proposes two techniques for reducing the classification time. The first technique selects a subset of features based on the frequency of occurrence. The second speeds classification by sampling several blocks from the file. Experimental results demonstrate that up to a fifteen-fold reduction in file size analysis time can be achieved with limited impact on accuracy.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Probabilistic subgroup identification using Bayesian finite mixture modelling : a case study in Parkinson’s disease phenotype identification

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).

Why a child needs a critical eye, and why the art classroom is central in developing it

It is a common acceptance that contemporary schoolchildren live in a world that is intensely visual and commercially motivated, where what is imagined and what is experienced intermingle. Because of this, contemporary education should encourage a child to make reference to, and connection with their ‘out-of-school’ life. The core critical underpinnings of curriculum based arts appreciation and theory hinge on educators and students taking a historical look at the ways artists have engaged with, and made comment upon, their contemporary societies. My article uses this premise to argue for the need to persist with pushing for critique of/through the visual, that it be delivered as an active process via the arts classroom rather than as visual literacy, here regarded as a more passive process for interpreting and understanding visual material. The article asserts that visual arts lessons are best placed to provide fully students with such critique because they help students to develop a ’critical eye’, an interpretive lens often used by artists to view, analyse and independently navigate and respond to contemporary society.

Gender patterns for aspirations for transitional employment and training and development in local government

Purpose – The purpose of this paper is to determine the patterns of transitional employment (TE) aspirations and training and development (T&D) needs of women within local government. Design/methodology/approach – A quantitative survey methodology was used to identify aspirations in a sample of 1,068 employees from the Australian Local Government Association. Findings – Mature-aged women were very interested in continuous learning at work despite their limited formal education. Their training preferences consisted of informal delivery face-to-face or online in the areas of management or administration. Younger women were interested in undertaking university courses, while a minority were interested in blue collar occupations. Practical implications – Through the identification of patterns of TE and T&D aspirations, long term strategies to develop and retain women in local government may be developed. Findings suggest that mature-aged women would benefit from additional T&D to facilitate entry into management and senior administration positions, as well as strategies to facilitate a shift in organizational climate. Social implications – Mature-aged women were found to be a potentially untapped resource for management and senior administrative roles owing to their interest in developing skills in these fields and pursuing TE. Younger women may also benefit from T&D to maintain their capacity during breaks from employment. Encouragement of women in non-traditional areas may also address skill shortages in the local government. Originality/value – Mature-aged women were found to be a potentially untapped resource for management and senior administrative roles owing to their interest in developing skills in these fields and pursuing TE. Younger women may also benefit from T&D to maintain their capacity during breaks from employment. Encouragement of women in non-traditional areas may also address skill shortages in the local government.