| 1. |
- Aagerup, Ulf, 1969-
(författare)
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Building nightclub brand personality via guest selection
- 2020
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Ingår i: International Journal of Hospitality Management. - Oxford : Elsevier. - 0278-4319 .- 1873-4693.
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Tidskriftsartikel (refereegranskat)abstract
- This paper identifies that guest selection at exclusive nightclubs is a brand building process, and that the guests’ primary value to the clubs therefore is the image they bestow on the brand. The paper contributes to theory by providing empirical support for several mechanisms that have previously been stipulated in literature. It validates that companies build brand personality by controlling typical user imagery, and that for self-expressive product categories, negative user stereotypes are particularly powerful. It supports the theory of symbolic brand avoidance, as well as the notion that social rejection encourages people to elevate their perceptions of their rejecters and strengthens their predilection to affiliate with them. For practitioners, the paper shows managers in the hospitality industry that it is possible to build brands by controlling who is allowed to become a brand-user, and under which conditions this applies.
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| 2. |
- Abdeljaber, Osama, et al.
(författare)
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Analysis of the Trajectories of Left-turning Vehicles at Signalized Intersections
- 2020
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Ingår i: Transportation Research Procedia. - : Elsevier BV. ; , s. 1288-1295, s. 1288-1295
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Konferensbidrag (refereegranskat)abstract
- Internationally, an annual number of more than a million fatalities are caused by road traffic crashes, with particularly signalized intersections being crash prone locations within the highway system. An accumulation of conflicts between drivers is caused by the different movements (through and turning) from different directions at the intersection; hence, studying the trajectories of turning vehicles is an important step towards improving traffic safety performance of these facilities. In view of that, the current paper aims at providing further insight into the behaviour of left-turning vehicles (right-hand traffic rule) at signalized intersections in the State of Qatar. At first, a total of 44 trajectories of free-flowing vehicles were manually extracted from a recorded video for a single approach of Lekhwair signalized intersection in Doha City, State of Qatar. After that, the extracted trajectories were statistically analysed in an attempt to explore the factors affecting the path of left-turning vehicles at signalized intersections. The results suggest that the characteristics of the extracted paths are significantly related to the vehicle’s entry speed, minimum speed throughout its turning manoeuvre, and the lateral distance between the exit point and the curb (i.e., targeted exit lane). Provided that the speed parameters can be fairly an indication to the driving behaviour, it can be concluded that the driver’s attitude plays an important role in drawing the manoeuvre of a turning vehicle as does the pre-selection of the exit lane. Finally, the effort presented in this paper can be regarded as a way forward towards understanding the behaviour of turning vehicles at signalised intersection in the State of Qatar.
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| 3. |
- Abdeljaber, Osama, et al.
(författare)
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Extraction of Vehicle Turning Trajectories at Signalized Intersections Using Convolutional Neural Networks
- 2020
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Ingår i: Arabian Journal for Science and Engineering. - Heidelberg : Springer. - 2193-567X .- 2191-4281 .- 1319-8025. ; 45, s. 8011-8025
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims at developing a convolutional neural network (CNN)-based tool that can automatically detect the left-turning vehicles (right-hand traffic rule) at signalized intersections and extract their trajectories from a recorded video. The proposed tool uses a region-based CNN trained over a limited number of video frames to detect moving vehicles. Kalman filters are then used to track the detected vehicles and extract their trajectories. The proposed tool achieved an acceptable accuracy level when verified against the manually extracted trajectories, with an average error of 16.5 cm. Furthermore, the trajectories extracted using the proposed vehicle tracking method were used to demonstrate the applicability of the minimum-jerk principle to reproduce variations in the vehicles’ paths. The effort presented in this paper can be regarded as a way forward toward maximizing the potential use of deep learning in traffic safety applications.
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| 4. |
- Aboelwafa, Mariam M. N., et al.
(författare)
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A Machine-Learning-Based Technique for False Data Injection Attacks Detection in Industrial IoT
- 2020
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Ingår i: IEEE Internet of Things Journal. - Piscataway : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 7:9, s. 8462-8471
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Tidskriftsartikel (refereegranskat)abstract
- The accelerated move toward the adoption of the Industrial Internet-of-Things (IIoT) paradigm has resulted in numerous shortcomings as far as security is concerned. One of the IIoT affecting critical security threats is what is termed as the false data injection (FDI) attack. The FDI attacks aim to mislead the industrial platforms by falsifying their sensor measurements. FDI attacks have successfully overcome the classical threat detection approaches. In this article, we present a novel method of FDI attack detection using autoencoders (AEs). We exploit the sensor data correlation in time and space, which in turn can help identify the falsified data. Moreover, the falsified data are cleaned using the denoising AEs (DAEs). Performance evaluation proves the success of our technique in detecting FDI attacks. It also significantly outperforms a support vector machine (SVM)-based approach used for the same purpose. The DAE data cleaning algorithm is also shown to be very effective in recovering clean data from corrupted (attacked) data. © 2014 IEEE.
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| 5. |
- Aghanavesi, Somayeh, 1981-, et al.
(författare)
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Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
- 2020
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Ingår i: Journal of Sensors. - London : Hindawi Publishing Corporation. - 1687-725X .- 1687-7268. ; , s. 1-14
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this paper is to investigate the feasibility of using the Dynamic Time Warping (DTW) method to measure motor states in advanced Parkinson's disease (PD). Data were collected from 19 PD patients who experimented leg agility motor tests with motion sensors on their ankles once before and multiple times after an administration of 150% of their normal daily dose of medication. Experiments of 22 healthy controls were included. Three movement disorder specialists rated the motor states of the patients according to Treatment Response Scale (TRS) using recorded videos of the experiments. A DTW-based motor state distance score (DDS) was constructed using the acceleration and gyroscope signals collected during leg agility motor tests. Mean DDS showed similar trends to mean TRS scores across the test occasions. Mean DDS was able to differentiate between PD patients at Off and On motor states. DDS was able to classify the motor state changes with good accuracy (82%). The PD patients who showed more response to medication were selected using the TRS scale, and the most related DTW-based features to their TRS scores were investigated. There were individual DTW-based features identified for each patient. In conclusion, the DTW method can provide information about motor states of advanced PD patients which can be used in the development of methods for automatic motor scoring of PD. © 2020 Somayeh Aghanavesi et al.
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| 6. |
- Agnoletto, Daniel, et al.
(författare)
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Time slot transmission scheme with packet prioritization for Bluetooth low energy devices used in real-time applications
- 2020
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Ingår i: International Journal of Wireless Information Networks. - New York, NY : Springer Science+Business Media B.V.. - 1068-9605 .- 1572-8129. ; 27:4, s. 518-534
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Tidskriftsartikel (refereegranskat)abstract
- Bluetooth Low Energy (BLE) is one of the most important technologies that feed the growing field of Internet of Things and Wireless Sensor Networks. Due to its flexibility and unique low power-consumption, an increasing number of industrial devices, household appliances and wearables are being designed using it. However, the real-time demands of these networks such as timing and Quality of Service are not fully covered by the protocol itself. To help improve and offer some control over these characteristics, this paper presents a time slot transmission scheme with packet prioritization. It is based on the division and allocation of the connection interval to two types of messages: real-time and ordinary. The goal is to offer the lowest packet loss and time guarantees for real-time messages, while providing acceptable throughput for ordinary ones. Since the probability of a BLE connection to close increases with the number of packets sent through it, the position where a real-time packet is being sent as well as the number of ordinary messages in a connection represent key factors. The use of the first and last slot for real-time packets with ordinary flow restricted to the space between them decreases the transmission delay uncertainty and allows probability tuning based on the number of ordinary messages. Simulations were performed using the proposed scheme and a reduction of more than 100 times in the delay variance was observed for real-time transmissions. Regarding reliability, around 5% of the packets were lost for a bit error rate of 10−3. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
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| 7. |
- Aikens, Ellen O., et al.
(författare)
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Wave-like Patterns of Plant Phenology Determine Ungulate Movement Tactics
- 2020
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Ingår i: Current Biology. - Cambridge : Cell Press. - 0960-9822 .- 1879-0445. ; 30:17, s. 3444-3449
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Tidskriftsartikel (refereegranskat)abstract
- Animals exhibit a diversity of movement tactics [1]. Tracking resources that change across space and time is predicted to be a fundamental driver of animal movement [2]. For example, some migratory ungulates (i.e., hooved mammals) closely track the progression of highly nutritious plant green-up, a phenomenon called "green-wave surfing" [3-5]. Yet general principles describing how the dynamic nature of resources determine movement tactics are lacking [6]. We tested an emerging theory that predicts surfing and the existence of migratory behavior will be favored in environments where green-up is fleeting and moves sequentially across large landscapes (i.e., wave-like green-up) [7]. Landscapes exhibiting wave-like patterns of green-up facilitated surfing and explained the existence of migratory behavior across 61 populations of four ungulate species on two continents (n = 1,696 individuals). At the species level, foraging benefits were equivalent between tactics, suggesting that each movement tactic is fine-tuned to local patterns of plant phenology. For decades, ecologists have sought to understand how animals move to select habitat, commonly defining habitat as a set of static patches [8, 9]. Our findings indicate that animal movement tactics emerge as a function of the flux of resources across space and time, underscoring the need to redefine habitat to include its dynamic attributes. As global habitats continue to be modified by anthropogenic disturbance and climate change [10], our synthesis provides a generalizable framework to understand how animal movement will be influenced by altered patterns of resource phenology.© 2020 Elsevier Inc.
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| 8. |
- Aksoy, Eren, 1982-, et al.
(författare)
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SalsaNet : Fast Road and Vehicle Segmentationin LiDAR Point Clouds for Autonomous Driving
- 2020
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Ingår i: IEEE Intelligent Vehicles Symposium. - Piscataway, N.J. : IEEE. ; , s. 926-932
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Konferensbidrag (refereegranskat)abstract
- In this paper, we introduce a deep encoder-decoder network, named SalsaNet, for efficient semantic segmentation of 3D LiDAR point clouds. SalsaNet segments the road, i.e. drivable free-space, and vehicles in the scene by employing the Bird-Eye-View (BEV) image projection of the point cloud. To overcome the lack of annotated point cloud data, in particular for the road segments, we introduce an auto-labeling process which transfers automatically generated labels from the camera to LiDAR. We also explore the role of imagelike projection of LiDAR data in semantic segmentation by comparing BEV with spherical-front-view projection and show that SalsaNet is projection-agnostic. We perform quantitative and qualitative evaluations on the KITTI dataset, which demonstrate that the proposed SalsaNet outperforms other state-of-the-art semantic segmentation networks in terms of accuracy and computation time. Our code and data are publicly available at https://gitlab.com/aksoyeren/salsanet.git.
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| 9. |
- Alatalo, J. M., et al.
(författare)
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Bryophyte cover and richness decline after 18 years of experimental warming in alpine Sweden
- 2020
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Ingår i: Aob Plants. - Oxford : Oxford University Press (OUP). - 2041-2851. ; 12:6
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Tidskriftsartikel (refereegranskat)abstract
- Climate change is expected to affect alpine and Arctic tundra communities. Most previous long-term studies have focused on impacts on vascular plants, this study examined impacts of long-term warming on bryophyte communities. Experimental warming with open-top chambers (OTCs) was applied for 18 years to a mesic meadow and a dry heath alpine plant community. Species abundance was measured in 1995, 1999, 2001 and 2013. Species composition changed significantly from original communities in the heath, but remained similar in mesic meadow. Experimental warming increased beta diversity in the heath. Bryophyte cover and species richness both declined with long-term warming, while Simpson diversity showed no significant responses. Over the 18-year period, bryophyte cover in warmed plots decreased from 43 % to 11 % in heath and from 68 % to 35 % in meadow (75 % and 48 % decline, respectively, in original cover), while richness declined by 39 % and 26 %, respectively. Importantly, the decline in cover and richness first emerged after 7 years. Warming caused significant increase in litter in both plant communities. Deciduous shrub and litter cover had negative impact on bryophyte cover. We show that bryophyte species do not respond similarly to climate change. Total bryophyte cover declined in both heath and mesic meadow under experimental long-term warming (by 1.5-3 degrees C), driven by general declines in many species. Principal response curve, cover and richness results suggested that bryophytes in alpine heath are more susceptible to warming than in meadow, supporting the suggestion that bryophytes may be less resistant in drier environments than in wetter habitats. Species loss was slower than the decline in bryophyte abundance, and diversity remained similar in both communities. Increased deciduous shrub and litter cover led to decline in bryophyte cover. The non-linear response to warming over time underlines the importance of long-term experiments and monitoring.
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| 10. |
- Aldrin, Emilia, 1982-
(författare)
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Försök att dekonstruera kön. Konnotationer till etablerade förnamn och förhållningssätt till androgyna förnamn bland studenter
- 2020
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Ingår i: Studia Anthroponymica Scandinavica. - Uppsala : Kungliga Gustav Adolfs Akademien. - 0280-8633. ; 35, s. 141-158
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Tidskriftsartikel (refereegranskat)abstract
- The primary aim of this article is to test the relevance of phonetic symbolism for people's conceptions of gender connotations in first names. Students were asked to grade their perceptions of seven female and male names. Primarily for female names certain phonetic properties correlated with higher perceived degree of femininity. However, the study also showed resistance towards gendering first names and attempts of "undoing gender".© Aldrin 2020
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