| 1. |
- Wang, Qinghua, et al.
(författare)
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Smart Sewage Water Management and Data Forecast
- 2021
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Ingår i: 33rd Workshop of the Swedish Artificial Intelligence Society, SAIS 2021. - USA : Institute of Electrical and Electronics Engineers (IEEE). - 9781665442367
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- There is currently an ongoing digital transformation for sewage and wastewater management. By automating data collection and enabling remote monitoring, we will not only be able to save abundant human resources but also enabling predictive maintenance which is based on big data analytics. This paper presents a smart sewage water management system which is currently under development in southern Sweden. Real-time data can be collected from over 500 sensors which have already been partially deployed. Preliminary data analysis shows that we can build statistical data models for ground water, rainfall, and sewage water flows, and use those models for data forecast and anomaly detection.
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| 2. |
- Amoson, Jonas, 1973-
(författare)
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Building complex GUIs in Plan 9
- 2009
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Ingår i: Proceedings 4th International Workshop on Plan9. - Athens, GA : University of Georgia. ; , s. 15-21
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- How can non-trivial graphical user interfaces be designed in Plan 9 without them losing their minimalistic style? Different toolkits are discussed, and a proposal for a tabbed toolbar is suggested as a way to add functionality without cluttering the interface and avoiding the use of pop-up dialog boxes. A hypothetical port to the GUI in LyX is used as an example.
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| 3. |
- Sodhro, Ali Hassan, 1986-, et al.
(författare)
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Internet of medical things for independent living and re-learning
- 2021
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Ingår i: GLOBAL HEALTH 2021 : The Tenth International Conference on Global Health Challenges At: Barcelona, Spain. - 9781612088921 ; , s. 1-5, s. 1-5
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This position paper gives better insight about the role and importance of Internet of Medical Things (IoMT) for independent living and re-learning for older adults. Sensing Technologies are the paradigm shift for transforming conventional healthcare practices into the smart, and self-assisted activities, which are envisioned for today's medical world. Internet of Things (IoT) and IoMT are the interrelated technologies for promoting independent living and re-learning practices. In this paper, re-learning is defined as the process for adults to recover useful instrumental activities of daily living skills that have been lost after an impairment.
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| 4. |
- Arvidsson, Åke, 1957-, et al.
(författare)
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Modelling user experience of adaptive streaming video over fixed capacity links
- 2021
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Ingår i: Performance evaluation (Print). - 0166-5316 .- 1872-745X. ; 148, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Streaming video continues to experience unprecedented growth. This underscores the need to identify user-centric performance measures and models that will allow operators to satisfy requirements for cost-effective network dimensioning delivered with an acceptable level of user experience. This paper presents an analysis of two novel metrics in the context of fixed capacity links: (i) the average proportion of a video’s playing time during which the quality is reduced and (ii) the average proportion of videos which experience reduced quality at least once during their playing time, based on an M/M/∞ system. Our analysis is shown to hold for the more general M/G/∞ system for metric (i), but not for (ii) and simulation studies show an unexpected form of sensitivity of metric (ii) to the flow duration distribution, contrary to the norm of increasing variance causing worse performance. At typical operational loads these new metrics provide a more sensitive and information rich guide for understanding how user experience degrades, than the widely used average throughput metric does. We further show that only the combined use of this existing and our new metrics can provide a holistic perspective on overall user performance.
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| 5. |
- Lakhan, Abdullah, et al.
(författare)
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Multi-layer latency aware workload assignment of E-Transport IoT applications in mobile sensors cloudlet cloud networks
- 2021
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Ingår i: Electronics. - Switzerland : MDPI. - 2079-9292. ; 10:14, s. 1-25
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Tidskriftsartikel (refereegranskat)abstract
- These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies.
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| 6. |
- Faraon, Montathar, 1983-, et al.
(författare)
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Social media affordances in net-based higher education
- 2011
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Ingår i: Proceedings of the IADIS International Conference on International Higher Education (IHE 2011). - Shanghai, China : IADIS Press. - 9789728939564 ; , s. 11-37
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Konferensbidrag (refereegranskat)abstract
- This paper explores the attitudes, conceptions and use of social media in net-based higher education. By using statistical and content analysis of data generated by two surveys directed to students (n = 109) and teachers (n = 77) involved in net-based higher education, we explore how social media influence the design of learning context in net-based higher education courses. By applying the affordance theory, we describe actual as well as preferred use of social media from an educational, social, and technical perspectives. The results showed that the potential use of social media have not yet been fully found in the context of net-based higher education. However, the perceived benefit of using social media differs in relation to educational topics. The potential use of social media in net-based higher education courses is discussed.
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| 7. |
- Kalaivaani, P. C. D., et al.
(författare)
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Advanced lightweight feature interaction in deep neural networks for improving the prediction in click through rate
- 2021
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Ingår i: Annals of Operations Research. - : Springer. - 0254-5330 .- 1572-9338.
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Tidskriftsartikel (refereegranskat)abstract
- Online advertising has expanded to a hundred-dollar billion industry in recent years, with sales growing at faster rate in every year. Prediction of the click-through rate (CTR) is an important role in recommended systems and online ads. Click through rating (CTR) is the newest evolution in the advertising and marketing digital world. It is essential for any online advertising company in real time to display the appropriate ads to the right users in the correct context. A huge amount of research work proposed considers each ad separately and does not takes in the relationship with other ads that may have an impact on Click Through Rate. A Factorization machine, a more generalized predictor like support vector machines (SVM) is not able to estimate reliable parameters under sparsity. The main drawback is that the primary features and existing algorithms considers the large weighted parameters. KGCN (Knowledge graph-based convolution network) overcomes the drawback and works on alternating graphs which creates additional clustering and node comparison with high latency and performance. A new framework DeepLight Weight is proposed to resolve the high server latency and high usage of memory issues in online advertising. This work presents a framework to improve the CTR predictions with an objective to accelerate the model inference, prune redundant parameters and the dense embedding vectors. Field Weighed Factorization machine helps to organize the data features with high structure to improve the accuracy. For clearing latency issues, structural pruning makes the algorithm work with dense matrices by combining and executing the individual matrix values or neural nodes.
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| 8. |
- Lakhan, Abdullah, et al.
(författare)
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Cost-efficient service selection and execution and blockchain-enabled serverless network for internet of medical things
- 2021
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Ingår i: Mathematical Biosciences and Engineering. - 1547-1063 .- 1551-0018. ; 18:6, s. 7344-7362
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Tidskriftsartikel (refereegranskat)abstract
- These days, healthcare applications on the Internet of Medical Things (IoMT) network have been growing to deal with different diseases via different sensors. These healthcare sensors are connecting to the various healthcare fog servers. The hospitals are geographically distributed and offer different services to the patients from any ubiquitous network. However, due to the full offloading of data to the insecure servers, two main challenges exist in the IoMT network. (i) Data security of workflows healthcare applications between different fog healthcare nodes. (ii) The cost-efficient and QoS efficient scheduling of healthcare applications in the IoMT system. This paper devises the Cost-Efficient Service Selection and Execution and Blockchain-Enabled Serverless Network for Internet of Medical Things system. The goal is to choose cost-efficient services and schedule all tasks based on their QoS and minimum execution cost. Simulation results show that the proposed outperform all existing schemes regarding data security, validation by 10%, and cost of application execution by 33% in IoMT.
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| 9. |
- Atxutegi, Eneko, et al.
(författare)
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On the move with TCP in current and future mobile networks
- 2017
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Ingår i: Proceedings of the 8th International Conference on the Network of the Future, London, United Kingdom, November 2017.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Mobile wireless networks constitute an indispensable part of the global Internet, and with TCP the dominating transport protocol on the Internet, it is vital that TCP works equally well over these networks as over wired ones. This paper identifies the performance dependencies by analyzing the responsiveness of TCP NewReno and TCP CUBIC when subject to bandwidth variations related to movements in different directions. The presented evaluation complements previous studies on 4G mobile networks in two important ways: It primarily focuses on the behavior of the TCP congestion control in medium- to high-velocity mobility scenarios, and it not only considers the current 4G mobile networks, but also low latency configurations that move towards the overall potential delays in 5G networks. The paper suggests that while both CUBIC and NewReno give similar goodput in scenarios where the radio channel continuously degrades, CUBIC gives a significantly better goodput in scenarios where the radio channel quality continuously increases. This is due to CUBIC probing more aggressively for additional bandwidth. Important for the design of 5G networks, the obtained results also demonstrate that very low latencies are capable of equalizing the goodput performance of different congestion control algorithms. Only in low latency scenarios that combine both large fluctuations of available bandwidths and a mobility pattern in which the radio channel quality continuously increases can some performance differences be noticed.
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| 10. |
- Dootio, Mazhar Ali, et al.
(författare)
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Secure and failure hybrid delay enabled a lightweight RPC and SHDS schemes in Industry 4.0 aware IIoHT enabled fog computing
- 2021
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Ingår i: Mathematical Biosciences and Engineering. - 1547-1063 .- 1551-0018. ; 19:1, s. 513-536
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Tidskriftsartikel (refereegranskat)abstract
- These days, the Industrial Internet of Healthcare Things (IIT) enabled applications have been growing progressively in practice. These applications are ubiquitous and run onto the different computing nodes for healthcare goals. The applications have these tasks such as online healthcare monitoring, live heartbeat streaming, and blood pressure monitoring and need a lot of resources for execution. In IIoHT, remote procedure call (RPC) mechanism-based applications have been widely designed with the network and computational delay constraints to run healthcare applications. However, there are many requirements of IIoHT applications such as security, network and computation, and failure efficient RPC with optimizing the quality of services of applications. In this study, the work devised the lightweight RPC mechanism for IIoHT applications and considered the hybrid constraints in the system. The study suggests the secure hybrid delay scheme (SHDS), which schedules all healthcare workloads under their deadlines. For the scheduling problem, the study formulated this problem based on linear integer programming, where all constraints are integer, as shown in the mathematical model. Simulation results show that the proposed SHDS scheme and lightweight RPC outperformed the hybrid for IIoHT applications and minimized 50% delays compared to existing RPC and their schemes.
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