| 1. |
- van Laere, Joeri, et al.
(författare)
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Challenges for critical infrastructure resilience : Cascading effects of payment system disruptions
- 2017
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Ingår i: Proceedings of the 14th ISCRAM Conference. - Linköping : Linköping university. ; , s. 281-292, s. 281-292, s. 281-292
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Konferensbidrag (refereegranskat)abstract
- Critical infrastructures become more and more entangled and rely extensively on information technology. A deeper insight into the relationships between critical infrastructures enables the actors involved to more quickly understand the severity of information technology disruptions and to identify robust cross-functional mitigating actions. This study illustrates how and why disruptions in the payment system in Sweden could create cascading effects in other critical infrastructures with potentially severe consequences for many citizens, government institutions and companies. Data from document studies, interviews and workshops with field experts reveal seven challenges for collective cross-functional critical infrastructure resilience that need to be dealt with: 1) Shortage of food, fuel, cash, medicine; 2) Limited capacity of alternative payment solutions; 3) Cities are more vulnerable than the countryside; 4) Economically vulnerable groups in society are more severely affected; 5) Trust maintenance needs; 6) Crisis communication needs; 7) Fragmentation of responsibility for critical infrastructures across many actors.
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| 2. |
- Alklind Taylor, Anna-Sofia, 1975-, et al.
(författare)
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Guardian Angel : Using Lighting Drones to Improve Traffic Safety, Sense of Security, and Comfort for Cyclists
- 2023
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Ingår i: Lecture Notes in Computer Science. - Cham : Springer. - 9783031480461 - 9783031480478 ; , s. 209-223
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Konferensbidrag (refereegranskat)abstract
- Active mobility, such as biking, faces a common challenge in Swedish municipalities due to the lack of adequate lighting during the dark winter months. Insufficient lighting infrastructure hinders individuals from choosing bicycles, despite the presence of well-maintained bike paths and a willingness to cycle. To address this issue, a project has been undertaken in the Swedish municipality of Skara for an alternative lighting solution using drones. A series of tests have been conducted based on drone prototypes developed for the selected bike paths. Participants were invited to cycle in darkness illuminated by drone lighting and share their mobility preferences and perception. This paper summarizes the users’ perception of drone lighting as an alternative to fixed lighting on bike paths, with a special focus on the impact on travel habits and the perceived sense of security and comfort. Most participants were regular cyclists who cited bad weather, time, and darkness as significant factors that deterred them from using bicycles more frequently, reducing their sense of security. With drone lighting, the participants appreciated the illumination’s moonlight-like quality and its ability to enhance their sense of security by illuminating the surroundings. On the technology side, they gave feedback on reducing the drone’s sound and addressing lighting stability issues. In summary, the test results showcase the potential of drone lighting as a viable alternative to traditional fixed lighting infrastructure, offering improved traffic safety, sense of security, and comfort. The results show the feasibility and effectiveness of this innovative approach, supporting transformation towards active and sustainable mobility, particularly in regions facing lighting challenges.
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| 3. |
- Najjar Azali, Negin, 1992-, et al.
(författare)
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On the Need of BIM Implementation in the Historical Buildings Renovation : An Analytical KMS-based Approach Toward Upgrading the Existing Renovation Design Methods to the Building Information Model in Iran
- 2016
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Konferensbidrag (refereegranskat)abstract
- BIM (Building Information Modeling) is the new trend in accordance with the management of the information related to building design and construction; some countries such as Denmark, Singapore and the United Kingdom have mandated the implementation of BIM method for their public construction projects and considered BIM documentation/implementation as a part of their national regulations/codes. So far, there is not such a ground rule/platform in Iran to provide and improve public construction/design contracts based on BIM implementation. This gap makes the management of the generated associated knowledge difficult to capture and eventually would not support the needed effective dissemination of the prospect knowledge. Particularly the practical implementation, the associated knowledge acquisition, and application of BIM remain a major issue, in our case for the renovation projects in Iran, although the related software are in common usage. The ultimate goal of this paper is to gain a more acute perspective into the implementation of Building Information Modeling (BIM) through the renovation of the cultural/historic places/buildings and the related innovative operational approach, addressing various projects around the world by developing a conceptual model as a Knowledge Management System (KMS); it reveals that BIM adaptation for public historical renovations in Iran which not only helps to mitigate the Knowledge Management problems but also attract global actors to participate in the mentioned field beside the platform development of the KM. The establishment of the KMS and the associated dynamism must be through the core management approach and strategy of the contributing enterprises, providing the human, financial and material resources to the process; additionally, it is essential to capture and systematized generated information and knowledge throughout the lifecycle of the renovation projects. The methodology is based on a literature review of the BIM-oriented renovation investigating of the actual projects and the development of a conceptual model toward fulfilling the gap of the key management factors such as indecisive sustainability, weak project execution, unclear or divergent project goals, lack of funding or resources, lack of design and renovation standards, etc. By implementation of BIM as a knowledge-based approach in the renovation of historical and cultural projects, our conceptual model uses BIM as an information exchange framework to manage knowledge in renovation project. The paper concludes with a potential broad discussion of suggestions supporting the adaptation of BIM at the renovation stage of historical projects in Iran based on the research findings.
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| 4. |
- Gerdes, Mike, et al.
(författare)
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Decision Trees and the Effects of Feature Extraction Parameters for Robust Sensor Network Design
- 2017
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Ingår i: Eksploatacja i Niezawodność – Maintenance and Reliability. - : Polskie Naukowo - Techniczne Towarzystwo Eksploatacyjne. - 1507-2711 .- 2956-3860. ; 19:1, s. 31-42
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Tidskriftsartikel (refereegranskat)abstract
- Reliable sensors and information are required for reliable condition monitoring. Complex systems are commonly monitored by many sensors for health assessment and operation purposes. When one of the sensors fails, the current state of the system cannot be calculated in same reliable way or the information about the current state will not be complete. Condition monitoring can still be used with an incomplete state, but the results may not represent the true condition of the system. This is especially true if the failed sensor monitors an important system parameter. There are two possibilities to handle sensor failure. One is to make the monitoring more complex by enabling it to work better with incomplete data; the other is to introduce hard or software redundancy. Sensor reliability is a critical part of a system. Not all sensors can be made redundant because of space, cost or environmental constraints. Sensors delivering significant information about the system state need to be redundant, but an error of less important sensors is acceptable. This paper shows how to calculate the significance of the information that a sensor gives about a system by using signal processing and decision trees. It also shows how signal processing parameters influence the classification rate of a decision tree and, thus, the information. Decision trees are used to calculate and order the features based on the information gain of each feature. During the method validation, they are used for failure classification to show the influence of different features on the classification performance. The paper concludes by analysing the results of experiments showing how the method can classy different errors with a 75% probability and how different feature extraction options influence the information gain.
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| 5. |
- Gerdes, Mike, et al.
(författare)
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Fuzzy condition monitoring of recirculation fans and filters
- 2016
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Ingår i: International Journal of Systems Assurance Engineering and Management. - : Springer. - 0975-6809 .- 0976-4348. ; 7:4, s. 469-479
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Tidskriftsartikel (refereegranskat)abstract
- A reliable condition monitoring is needed to be able to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies however only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that outputs similarity values for decision trees. Experiments confirmed that the method works and showed good classification results. Different fuzzy functions were evaluated to show how the method can be adapted to different problems. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. The goal is to have the probabilities of a sample belonging to each class. Performed experiments showed that the concept is reliable and it also works with decision tree forests (which is shown during this paper) to increase the classification accuracy. Overall the presented concept has the same classification accuracy than a normal decision tree but it offers the user more information about how certain the classification is.
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| 6. |
- Nawani, Neelu, et al.
(författare)
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Status of metal pollution in rivers flowing through urban settlements at Pune and its effect on resident microflora
- 2016
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Ingår i: Biologia. - Bratislava : Springer. - 0006-3088 .- 1336-9563. ; 71:5, s. 494-507
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Tidskriftsartikel (refereegranskat)abstract
- This study illustrates the sporadic distribution of metals in fluvial systems flowing from catchments to urban settlements. This is a detailed study prognosticating the deteriorating quality of rivers at specific locations due to metal pollution. Heavy metals like cadmium, lead, nickel and mercury are prominent in industrial sector. Contour plots derived using spatial and temporal data could determine the focal point of metal pollution and its gradation. Metal values recorded were cadmium 157 mg/L, lead 47 mg/L, nickel 61 mg/L and mercury 0.56 mg/L. Prokaryote diversity was less in polluted water and it harboured metal tolerant bacteria, which were isolated from these polluted sites. Actinomycetes like Streptomyces and several other bacteria like Stenotrophomonas and Pseudomonas isolated from the polluted river sites exhibited changes in morphology in presence of heavy metals. This stress response offered remedial measures as Streptomyces were effective in biosorption of cadmium, nickel and lead and Stenotrophomonas and Pseudomonas were effective in the bioaccumulation of lead and cadmium. The amount of 89 mg of lead and 106 mg of nickel could be adsorbed on one gram of Streptomyces biomass-based biosorbent. Such biological remedies can be further explored to remove metals from polluted sites and from metal contaminated industrial or waste waters.
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| 7. |
- Hooshyar Yousefi, Bahram, Senior Lecturer, 1977-, et al.
(författare)
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Integration of BIM and IoT in the Building Heritage : A KM Conceptual Framework
- 2018
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Ingår i: Landscape in Transition. - Tehran : IFLA, Middle East. - 9786220005025 ; , s. 11-23
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Konferensbidrag (refereegranskat)abstract
- The current progress in the field of Building Informa on Modeling (BIM) and the new possibili es facilitated by IoT (Internet of Things) pla orms could contribute to the stream of the integra ng improvement of the knowledge-based built heritage management. In this paper, ُthe concept of integra on of BIM and IoT would appear as a process of coordina on of all phases under a proper knowledge-based strategic approach. The op mal provided model would eventually be essen al to integrate common sub-processes grounded on the developed BIM-IoT principles/model. The eventual model has been conceptualized through the correspondence of BIM with WSN (Wireless Sensors Network) as the central management brain of the opera on and maintenance of the buildings referring to the sustainability concept and conducts as a Knowledge Management System (KMS).
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| 8. |
- Trapero, Juan R., et al.
(författare)
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On the identification of sales forecasting models in the presence of promotions
- 2015
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Ingår i: Journal of the Operational Research Society. - : Taylor & Francis. - 0160-5682 .- 1476-9360. ; 66:2, s. 299-307
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Tidskriftsartikel (refereegranskat)abstract
- Shorter product life cycles and aggressive marketing, among other factors, have increased the complexity of sales forecasting. Forecasts are often produced using a Forecasting Support System that integrates univariate statistical forecasting with managerial judgment. Forecasting sales under promotional activity is one of the main reasons to use expert judgment. Alternatively, one can replace expert adjustments by regression models whose exogenous inputs are promotion features (price, display, etc). However, these regression models may have large dimensionality as well as multicollinearity issues. We propose a novel promotional model that overcomes these limitations. It combines Principal Component Analysis to reduce the dimensionality of the problem and automatically identifies the demand dynamics. For items with limited history, the proposed model is capable of providing promotional forecasts by selectively pooling information across established products. The performance of the model is compared against forecasts provided by experts and statistical benchmarks, on weekly data; outperforming both substantially.
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| 9. |
- Kharrazi, Sogol, 1980-, et al.
(författare)
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Sustainable smart-parking management for connected and autonomous vehicles
- 2020
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Traffic induced by parking-spot seekers is a growing challenge and constitutes a considerable portion of the traffic in city centers. New opportunities to solve this problem are emerging by connected vehicles and infrastructure. For instance, ultrasonic and magnetic sensors are already mounted on the ceiling of many parking lots to detect the availability of a parking spot. These sensors can provide parking spot availability information in real-time. Further, traffic-aware smart sensors which can detect the movement of individual vehicles are also available in many city and highway areas. This report suggests an algorithm for a cloud-based parking service that exploits these streams of data to choose the best parking lot in a given parking area.The parking seeking problem is subject to a range of criteria that may include user, municipality and parking operator preferences. Users may have some preferences with respect to walking distance to destination. Municipalities prefer to spread the traffic to reduce congestion in the urban core. Parking operators seek to maximize parking lot utilization in order to increase the revenue on real-estate investments. To solve this problem, an optimization algorithm based on multicriteria decision making process is used.The proposed SmartPark algorithm employs a discrete Markov-chain model to demystify the future state of a parking lot. The algorithm features three modular sections:• First, a search process is triggered to identify the expected arrival time periods to all parking lots in the targeted parking area. This process utilizes smart pole data streams reporting congestion rates across the targeted parking area.• Then, a predictive analytics phase uses consolidated historical data about past parking dynamics to infer a state transition matrix, showing the transformation of available spots in a parking lot over short periods of time.• Finally, this matrix is projected against similar future seasonal periods to predict the actual vacancy of a parking lot at the arrival time.
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| 10. |
- Atif, Yacine, 1967-, et al.
(författare)
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Internet of Things data analytics for parking availability prediction and guidance
- 2020
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Ingår i: European transactions on telecommunications. - : Wiley-Blackwell Publishing Inc.. - 1124-318X .- 2161-3915 .- 2161-5748. ; 31
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Tidskriftsartikel (refereegranskat)abstract
- Cutting-edge sensors and devices are increasingly deployed within urban areas to make-up the fabric of transmission control protocol/internet protocol con- nectivity driven by Internet of Things (IoT). This immersion into physical urban environments creates new data streams, which could be exploited to deliver novel cloud-based services. Connected vehicles and road-infrastructure data are leveraged in this article to build applications that alleviate notorious parking and induced traffic-congestion issues. To optimize the utility of parking lots, our proposed SmartPark algorithm employs a discrete Markov-chain model to demystify the future state of a parking lot, by the time a vehicle is expected to reach it. The algorithm features three modular sections. First, a search pro- cess is triggered to identify the expected arrival-time periods to all parking lots in the targeted central business district (CBD) area. This process utilizes smart-pole data streams reporting congestion rates across parking area junc- tions. Then, a predictive analytics phase uses consolidated historical data about past parking dynamics to infer a state-transition matrix, showing the transfor- mation of available spots in a parking lot over short periods of time. Finally, this matrix is projected against similar future seasonal periods to figure out the actual vacancy-expectation of a lot. The performance evaluation over an actual busy CBD area in Stockholm (Sweden) shows increased scalability capa- bilities, when further parking resources are made available, compared to a baseline case algorithm. Using standard urban-mobility simulation packages, the traffic-congestion-aware SmartPark is also shown to minimize the journey duration to the selected parking lot while maximizing the chances to find an available spot at the selected lot.
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