Suchergebnisse

Multi-connectivity and network densification are two solutions intended to improve performance and reliability. These solutions can improve 5G NR's system performance especially when using high-frequency bands. This work focuses on the user equipment (UE) performance using multi-connectivity within an ultra-dense deployment in a city environment. By being connected to more than one access node simultaneously, the UE should benefit from increased reliability and performance. However, this improved performance comes at the expense of a potentially increased power consumption. Simulation results show that multi-connectivity improves performance by up to 46% and 27% in downlink and uplink resp., increases UE energy efficiency by up to 30% and improves reliability for highly mobile users by up to 37%. The price to pay is an increased UE power consumption of up to 25% and 60% for dual-connectivity and tri-connectivity resp. A multi-connectivity scheme is presented to reduce the secondary connection's transmit power. ; Finansiär: European Union ISBN för värdpublikation: 978-1-7281-7158-6

Sweden, as a small alliance free state with powerful neighbors, has a military history ofwhat we nowadays call systems of systems thinking. Since the beginning of the Cold War thishas been expressed in an air force on the forefront of exploiting military innovations, not leastwith regard to sensor networks, datalinks, information sharing and distributed decisionmaking. How can this history and the lessons learned come to use when future systems andtechnologies are to be developed to meet the uncertain future and changing threats? How doesthis fit with current trends such as capability-based approach and system of systemsengineering methodology? What could this mean for the development of the next generationfighter aircraft - after the Gripen E and contemporary aircraft? These questions have beenstudied from both a government and industry perspective, following the trend in the defensesector of a more intertwined relationship between the two, necessitated by adopting acapability view on aircraft development. This paper presents preliminary lessons identifiedfrom a case study on the project Flygvapnet 2000 (FV2000), which preceded the Net CentricWarfare era at the turn of the millennium. The analysis was based on characteristics of bestpractice systems of systems engineering derived from a review of literature presenting themethodology theory on capability-based approaches for analyzing, acquiring, developing, andmanaging military capabilities. The findings from this project will contribute to thedevelopment of systems of systems engineering methods and will spur proposals for futureresearch.

Abstract

Aims
To evaluate the efficacy and monitoring capabilities of a breathalyser-based eHealth system for patients with alcohol use disorder (AUD) and to investigate the quality and validity of timeline follow-back (TLFB) as outcome measure in clinical trials and treatment.


Methods
Patients (n = 115) were recruited to clinical trials from a 12-step aftercare programme (12S-ABS) and from hospital care with abstinence (HC-ABS) or controlled drinking (HC-CDR) as goal and randomly divided into an eHealth and a control group. The effect of the eHealth system was analysed with TLFB-derived primary outcomes—change in number of abstinent days (AbsDay) and heavy drinking days (HDDs) compared to baseline—and phosphatidyl ethanol (PEth) measurements. Validity and quality of TLFB were evaluated by comparison with breath alcohol content (BrAC) and eHealth digital biomarkers (DBs): Addiction Monitoring Index (AMI) and Maximum Time Between Tests (MTBT). TLFB reports were compared to eHealth data regarding reported abstinence.


Results
The primary outcome (TLFB) showed no significant difference between eHealth and control groups, but PEth did show a significant difference especially at months 2 and 3. Self-reported daily abstinence suffered from severe quality issues: of the 28-day TLFB reports showing full abstinence eHealth data falsified 34% (BrAC measurements), 39% (MTBT), 54% (AMI) and 68% (BrAC/MTBT/AMI). 12S-ABS and HC-ABS patients showed severe under-reporting.


Conclusions
No effect of the eHealth system was measured with TLFB, but a small positive effect was measured with PEth. The eHealth system revealed severe quality problems with TLFB, especially regarding abstinence—should measurement-based eHealth data replace TLFB as outcome measure for AUD?

Now-a-days, the natural irrigation system is under pressure due to the growing water shortages, which are mainly caused by population growth and climate change. Therefore, the control of water resources to increase the allocation of retained water is very important. It has been observed in the last two decades, especially in the Indian sub-continent, the change of climate affects the agricultural crops production significantly. However, the prediction of good harvests before harvesting, enables the farmers as well as the government officials to take appropriate measures of marketing and storage of crops. Some strategies for predicting and modelling crop yields have been developed, although they do not take into account the characteristics of climate, and they are empirical in nature. In the proposed system, a Cuckoo Search Algorithm has been developed, allowing the allocation of water for farming under any conditions. The various parameters such as temperature, turbidity, pH., moisture have been collected by using Internet of Things (IoT) platform, equipped with related sensors and wireless communication systems. In this IoT platform the sensor data have been displayed in the cloud environment by using ThingSpeak. The data received in the ThingSpeak used in the proposed Cuckoo Search Algorithm, allowing the selection of appropriate crops for particular soil

An earthquake is a tremor felt on the surface of the earth created by the movement of the major pieces of its outer shell. Till now, many attempts have been made to forecast earthquakes, which saw some success, but these attempted models are specific to a region. In this paper, an earthquake occurrence and location prediction model is proposed. After reviewing the literature, long short-term memory (LSTM) is found to be a good option for building the model because of its memory-keeping ability. Using the Keras tuner, the best model was selected from candidate models, which are composed of combinations of various LSTM architectures and dense layers. This selected model used seismic indicators from the earthquake catalog of Bangladesh as features to predict earthquakes of the following month. Attention mechanism was added to the LSTM architecture to improve the model's earthquake occurrence prediction accuracy, which was 74.67%. Additionally, a regression model was built using LSTM and dense layers to predict the earthquake epicenter as a distance from a predefined location, which provided a root mean square error of 1.25. ; Validerad;2021;Nivå 2;2021-04-19 (alebob); Finansiär: Informationand Communication Technology division of the Governmentof the People's Republic of Bangladesh