Health and mortality in humans are influenced by various factors, with daily step count being a significant contributor to overall well-being. This study introduces a novel approach to identify the optimal walking rou...
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In the aftermath of natural disasters, decision-makers often clash when tackling the challenge of choosing suitable temporary housing unit (THU) site locations. Site location considerably impacts temporary housing (TH...
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In the aftermath of natural disasters, decision-makers often clash when tackling the challenge of choosing suitable temporary housing unit (THU) site locations. Site location considerably impacts temporary housing (TH) delivery time and the displaced population's (DP's) satisfaction. At the same time, selecting a suitable site isimportant to help increase the performance of the THUs in their subsequent life. To this end, this study aimed todesign a new model for selecting site location based on sustainability concepts. The new model combines theintegrated value model for sustainable assessment (MIVES) and the knapsack algorithm to identify a subset ofsustainable sites amongst the possible options based on the required area. The new model was applied to determinethe best subset of sites for THUs for a seismic hazard along the Mosha fault in Tehran, Iran. The results show that weighting techniques can result in inappropriate weights for some indicators.
The wireless sensors has wide range of applications. The sensor network consist of many tiny sensors and each sensor is assigned to perform specific mission that is some node are transmitting node some are receiving a...
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ISBN:
(纸本)9781538603741
The wireless sensors has wide range of applications. The sensor network consist of many tiny sensors and each sensor is assigned to perform specific mission that is some node are transmitting node some are receiving and others are intermediate sensing nodes. Once sensor nodes are deployed, thereafter no additional actions are performed. In typical WSNs, the sensor nodes collect the information from the environment and the collection of the data is done in the intermediate nodes. The collected data is the send to the base station. Reliable communication, power efficiency and network survivability issues are critical concerns, because all the operation is done in sensor nodes. Energy consumption and end to end delay is a major issue in WSNs [8]. In this work we propose a scheme named data acquisition along with knapsack algorithm for reliable and efficient data transmission and delay optimization in the presence of transfaulty nodes. To prevent information loss in WSN due to transfaulty behavior of sensor nodes, in the proposed scheme we construct the network using sensor nodes having dual mode of communication-RF, acoustic and also we use knapsack algorithm for reliable data transmission. knapsack algorithm is to increase the in-order packets and decrease the out-of-order packets simultaneously, which helps for delay optimization.
Multimedia transmission over Mobile Ad-hoc Networks (MANETs) is crucial to many applications. However, MANETs possess several challenges including transmitting large size packets, minimizing delay, loss-tolerant and b...
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Multimedia transmission over Mobile Ad-hoc Networks (MANETs) is crucial to many applications. However, MANETs possess several challenges including transmitting large size packets, minimizing delay, loss-tolerant and buffer size estimation. For effective multimedia transmission, delay should be minimized and packets should be received in the defined order. The existing standards such as 802.11b and 802.11e perform well in wireless networks, but exhibit poor response in MANETs for multimedia traffic, especially in multi-hop networks. In this paper, we first establish the dependency of delay on buffer size and packet size, and then present a delay optimization approach for multimedia traffic in MANETs. We use knapsack algorithm for buffer management to maximize the in-order packets and minimize the out-of-order packets simultaneously. Our approach exploits the buffer internals and dynamically adjusts the buffer usage so that a node transmits the packets in the desired order to its successive nodes. Careful estimation of packet size and buffer size helps in minimizing the delay, improving the capability of receiving packets in the correct order and reducing out-of-order packets in the buffer at intermediate nodes. Our approach also controls the loss of multimedia data packets during transmission. We validate our approach with real-world examples using network simulator. (C) 2015 Elsevier Ltd. All rights reserved.
Autonomous smart waste management services are becoming an essential component of sustainable urbanization. However, the lack of data and insights from current service-providers impedes a reliable transition from labo...
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Autonomous smart waste management services are becoming an essential component of sustainable urbanization. However, the lack of data and insights from current service-providers impedes a reliable transition from labor-intensive to autonomous services. Deploying information gathering devices makes services expensive and resource-demanding. In project MARBLE (Mobile Autonomous RoBot for Litter Emptying) we are currently investigating the implementation of a fleet of service robots. In this framework, we could show that the absence of filling data of litter bins (LBs) hinders the possibility of providing an energy-efficient and time-effective service. Hence, we introduce an approach where machine learning-based predictions for filling levels of LBs, derived from our extensive data gathering, are used to effectively manage the autonomous emptying process. The novel Simulated Rebalancing approach in route-planning combined with the knapsack algorithm ensures efficient service in comparison to the Nearest Neighbor algorithm. A promising 82% filling level prediction accuracy was achieved with the XGBoost binary classifier, as compared to the 59% baseline accuracy. Through incorporating the predicted filling level data in the Simulated Rebalancing approach, a reduction of 26% in operational time and 31% in energy consumption was achieved for our simulated tests for service-event-area (SEA) James-Simon-Monbijoupark in Berlin with 49 LBs.
Neutral-temperature district heating and cooling (NT-DHC) is a recent concept in the district heating sector. The current literature does not directly address the ability to create comprehensive master plans for NT-DH...
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Neutral-temperature district heating and cooling (NT-DHC) is a recent concept in the district heating sector. The current literature does not directly address the ability to create comprehensive master plans for NT-DHC systems and reliably model their performance. This research presents a new approach for the evaluation and planning of NT-DHC systems. The methodology involves the use of a knapsack optimization algorithm to perform a comprehensive analysis of the conditions that make the NT-DHC solution competitive against individual heating and cooling technologies. The algorithm determines the optimal combination of potential extensions that maximizes overall economic value. The results of a case study, which was conducted in Italy, show that NT-DHC is more suitable in dense urban areas, while air-to-water heat pumps are better suited for low heat density zones. This methodology aims to reduce the risks associated with energy demand and provide more certainty about which areas a network can expand into to be competitive. It is targeted at energy planners, utilities experts, energy engineers, and district heating experts who require assistance and guidance in the planning and early stages of designing a NT-DHC system. This method might enable pre-feasibility studies and preliminary design to determine the opportunities and limitations of a system of this kind from an economic and technological perspective.
Maintaining road pavement is a challenging task, due to the vast size of the roads network and the limited maintenance budget available to road agencies. Therefore, most agencies aim at selecting the most deteriorated...
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Maintaining road pavement is a challenging task, due to the vast size of the roads network and the limited maintenance budget available to road agencies. Therefore, most agencies aim at selecting the most deteriorated road segments for maintenance, within their available budget. However, the majority of the current developed asset management tools aim at improving the average performance of the roads network, regardless of the condition of the maintained segments. To overcome this limitation, this study first proposes a novel measure for roads network performance using reliability theory, then it proposes a hybrid optimization approach that is integrated with the proposed performance measure to enable road agencies to focus on the most deteriorated segments in the network while maximizing the network performance. The hybrid optimization approach combines dynamic programming with a traditional genetic algorithm. The proposed algorithm was applied to two major road systems in Jordan and validated by comparing its performance with that of a traditional genetic algorithm. The results show that the proposed algorithm outperforms the traditional genetic algorithm, because of its ability to select the most deteriorated segments in the network, while achieving better network condition at lower cost.
This paper introduces an advanced framework for optimizing task offloading and service caching in Vehicle-to-Vehicle (V2V) communication networks. The proposed approach leverages a greedy algorithm to address key chal...
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In order to solve the problem of long solving time caused by the complexity of the optimization model in the optimal scheduling of distribution network, this paper proposes a multi-type resource demand response day-ah...
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The evolved Multimedia Broadcast Multicast Service (eMBMS) using the Multicast Broadcast Single Frequency Network (MBSFN) technique was designed for having multimedia streaming services using the multicast/broadcast w...
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The evolved Multimedia Broadcast Multicast Service (eMBMS) using the Multicast Broadcast Single Frequency Network (MBSFN) technique was designed for having multimedia streaming services using the multicast/broadcast way over the cellular network. Since (1) the unit of resource allocation in eMBMS-MBSFN is a subframe, (2) the code rate of an eMBMS-MBSFN session is based on the lowest Modulation and Coding Scheme (MCS) among involved User Equipments (UEs) of the eMBMS-MBSFN session and (3) the resource allocation for eMBMS-MBSFN cannot be so instantly and dynamically adjusted based on the status of involved UEs, triggering eMBMS-MBSFN in the inappropriate time and allocating inappropriate resource to eMBMS, for which a framework of how to set the configuration of the allocated resource for eMBMS-MBSFN has been defined in the standard, may cause (1) the radio resources to be wasted and (2) the low streaming quality and code rate. Based on the MBMS operation on Demand (MooD) concept, this work proposed the Incremental Allocation of Radio Resource between Unicast and Multicast (IARR-UM) method to dynamically allocate radio resources to eMBMS based on the current Radio Access Network's (RAN's) congestion situation such that some suitable multimedia streaming services are switched to eMBMS and others still use unicast communication. To effectively use eMBMS to mitigate RAN's congestion, the proposed IARR-UM method (1) dynamically increases/decreases the amount of radio resources allocated to eMBMS, i.e., modifying the configuration of the allocated resource for eMBMS-MBSFN using the standard's framework, based on the situation of RAN's congestion, (2) uses the knapsack algorithm to select a subset of suitable multimedia streaming services to be eMBMS sessions according to the given amount of radio resources allocated to eMBMS, and then (3) design a Common Subframe Allocation (CSA) pattern that can have the lower amount of redundant radio resources allocated to eMBMS. The r
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