Although reengineering is strategically advantageous fororganisations in order to keep functional and sustainable, safety must remain apriority and respective efforts need to be maintained. This paper suggeststhe combination of soft system methodology (SSM) and Pareto analysison the scope of safety management performance evaluation, and presents theresults of a survey, which was conducted in order to assess the effectiveness,efficacy and ethicality of the individual components of an organisation’s safetyprogram. The research employed quantitative and qualitative data and ensureda broad representation of functional managers and safety professionals, whocollectively hold the responsibility for planning, implementing and monitoringsafety practices. The results showed that SSM can support the assessment ofsafety management performance by revealing weaknesses of safety initiatives,and Pareto analysis can underwrite the prioritisation of the remedies required.The specific methodology might be adapted by any organisation that requires adeep evaluation of its safety management performance, seeks to uncover themechanisms that affect such performance, and, under limited resources, needsto focus on the most influential deficiencies.
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Terms like ‘big data’, ‘data science’, and ‘data visualisation’ have become buzzwords in recent years and are increasingly intertwined with journalism. Data visualisation may further blur the lines between science communication and graphic design. Our study is situated in these overlaps to compare the design of data visualisations in science news stories across four online news media platforms in South Africa and the United States. Our study contributes to an understanding of how well-considered data visualisations are tools for effective storytelling, and offers practical recommendations for using data visualisation in science communication efforts.
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Scheepvaart, landbouw, zand- en kleiwinning hebben, naast hoogwaterveiligheid, eeuwenlang de inrichting en het beheer van het rivierengebied bepaald. In de jaren tachtig van de vorige eeuw (her)ontdekte men het natuurpotentieel van het rivierengebied. Ook voor wonen en recreatie richtte men de aandacht op het rivierengebied. Het werd gecompliceerd toen de eerste effecten van de klimaatverandering zichtbaar werden met de extreme hoogwaters van 1993 en 1995. Het verenigen van alle ruimteclaims bleek geen eenvoudige opgave. Er werd naarstig gezocht naar modellen waarbij ook regionale en lokale partijen hunsteentje zouden bijdragen aan de gewenste functiecombinaties. Sindsdien is de behoefte aan co-creatie in het rivierengebied alleen nog maar groter geworden. Hoe is het eigenlijk met die experimenten afgelopen? En welke stappen worden nu ondernomen om co-creatie in het rivierengebied verder te optimaliseren?
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Repeat victimization has been widely studied from the perspective of environmental criminology for several decades. During this period, criminologists have identified a set of repeat victimization premises that are observed for many crimes; however, it is unknown whether these premises are also valid for cybercrime. In this study we rely on more than 9 million Zone-H data records from 2010 to 2017 to test whether these premises apply for the cybercrime of website defacement. We show that the phenomenon of repeat victimization is also observed in defaced cyber places (i.e. websites). In particular, we found that repeats contributed little to crime rates, that repeats occurred even several years after the original incident, that they were committed disproportionately by prolific offenders, and that few offenders returned to victimize previous targets. The results suggest that some traditional premises of repeat victimization may also be valid for understanding cybercrime events such as website defacement, implying that environmental criminology theories also constitute a useful framework for cybercrime analysis. The implications of these results in terms of criminological theory, cybercrime prevention, and the limitations derived from the use of Zone-H data are discussed
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Repeat victimization has been widely studied from the perspective of environmental criminology for several decades. During this period, criminologists have identified a set of repeat victimization premises that are observed for many crimes; however, it is unknown whether these premises are also valid for cybercrime. In this study we rely on more than 9 million Zone-H data records from 2010 to 2017 to test whether these premises apply for the cybercrime of website defacement. We show that the phenomenon of repeat victimization is also observed in defaced cyber places (i.e. websites). In particular, we found that repeats contributed little to crime rates, that repeats occurred even several years after the original incident, that they were committed disproportionately by prolific offenders, and that few offenders returned to victimize previous targets. The results suggest that some traditional premises of repeat victimization may also be valid for understanding cybercrime events such as website defacement, implying that environmental criminology theories also constitute a useful framework for cybercrime analysis. The implications of these results in terms of criminological theory, cybercrime prevention, and the limitations derived from the use of Zone-H data are discussed.
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Planning of transport through inland shipping is complex, highly dynamic and very specific. Existing software support is focusing on road transport planning and/or is merely a visual representation of shipments to be manually assigned to particular vessels. As a result inland shipment planning is time-consuming and highly relies on the personal skills of the planner. In this paper we present a business rules based model that aims to further support inland shipping organizations in their shipment planning by identifying the characteristics and constraints that are of interest and the related explicated business rules. The model is derived from transport-related literature, explorative expert interviews and transport management software vendors. The usability and applicability of the model is subsequently successfully empirically tested using identified performance measures through a case study at a major European inland shipping broker
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In recent years video game consoles, such as the Nintendo Wii™ and the Microsoft Kinect™, have been introduced into residential facilities. This paper presents a review of current studies documenting the benefits and detriments the Wii could have on adults aged 60 years and over in residential facilities, concentrating on the common uses of the Wii in care facilities: maintaining physical fitness, promoting mental well-being, encouraging social interaction and both physical and mental rehabilitation. Furthermore, this paper discusses the potential use of the Microsoft Kinect in care for older persons. The Wii can have a positive impact on the physical and mental health of older adults living in care facilities, but additional work should still be conducted, including assessing the use of games outside of Wii Sports and Wii Fit and possible non-gaming application of the Wii in care for older adults. Results for the Wii display potential for use of the Kinect in care facilities but further exploration is required to assess the potential physical impact and interaction viability.
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Routine immunization (RI) of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe. Pakistan being a low-and-middle-income-country (LMIC) has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases (VPDs). For improving RI coverage, a critical need is to establish potential RI defaulters at an early stage, so that appropriate interventions can be targeted towards such population who are identified to be at risk of missing on their scheduled vaccine uptakes. In this paper, a machine learning (ML) based predictive model has been proposed to predict defaulting and non-defaulting children on upcoming immunization visits and examine the effect of its underlying contributing factors. The predictive model uses data obtained from Paigham-e-Sehat study having immunization records of 3,113 children. The design of predictive model is based on obtaining optimal results across accuracy, specificity, and sensitivity, to ensure model outcomes remain practically relevant to the problem addressed. Further optimization of predictive model is obtained through selection of significant features and removing data bias. Nine machine learning algorithms were applied for prediction of defaulting children for the next immunization visit. The results showed that the random forest model achieves the optimal accuracy of 81.9% with 83.6% sensitivity and 80.3% specificity. The main determinants of vaccination coverage were found to be vaccine coverage at birth, parental education, and socio-economic conditions of the defaulting group. This information can assist relevant policy makers to take proactive and effective measures for developing evidence based targeted and timely interventions for defaulting children.
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This study explores how journalists in highspeed newsrooms gather information, how gathering activities are temporally structured and how reliability manifests itself in information-gathering activities.
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To benefit from the social capabilities of a robot math tutor, instead of being distracted by them, a novel approach is needed where the math task and the robot's social behaviors are better intertwined. We present concrete design specifications of how children can practice math via a personal conversation with a social robot and how the robot can scaffold instructions. We evaluated the designs with a three-session experimental user study (n = 130, 8-11 y.o.). Participants got better at math over time when the robot scaffolded instructions. Furthermore, the robot felt more as a friend when it personalized the conversation.
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