Tourism is a major foreign exchange earner in Kenya contributing to 10% of the gross domestic product (GDP). Whereas Kenyan government strives to boost its GDP through improved arrivals, lack of effective tourism mark...Tourism is a major foreign exchange earner in Kenya contributing to 10% of the gross domestic product (GDP). Whereas Kenyan government strives to boost its GDP through improved arrivals, lack of effective tourism marketing strategies hinders growth in tourist arrivals in Kenya. To advertise and market the untold wealth of tourist destinations, the government utilizes campaigns through print and electronic media, which are expensive and limited in updating. This study addresses the gap by designing a web Geographic Information System (GIS) portal for marketing and promotion of tourism. To realize this a multimedia GIS database was created using PostgreSQL/PostGIS software to store spatial and multimedia tourism data, while itinerary planning tools were designed using Dijkstra algorithm and Travelling Salesman Problem (TSP) approach. The result was a web GIS portal interface containing tourist information enhanced with text and/or video/audio descriptions. Facebook advertisement was used to popularize the tourism products available in Kenya through visitor engagements as well as directing traffic to the portal fast and inexpensively.展开更多
The use of unmanned aerial vehicles(UAVs) in the collection of data from wireless devices, sensor nodes, and the Internet of Things(IoT) devices has recently received significant attention. In this paper, we investiga...The use of unmanned aerial vehicles(UAVs) in the collection of data from wireless devices, sensor nodes, and the Internet of Things(IoT) devices has recently received significant attention. In this paper, we investigate the data collection process from a set of smart meters in advanced metering infrastructure(AMI) enabled by UAVs. The objective is to minimize the total annual cost of the electric utility by jointly optimizing the number of UAVs, their power source sizing, the charging locations as well as the data collection trip planning. This is achieved while considering the energy budgets of batteries of UAVs and the required amount of collected data. The problem is formulated as a mixed-integer nonlinear programming(MINLP), which is decoupled into two sub-problems where a candidate UAV and a number of buildings are first grouped into trips via genetic algorithms(GAs), and then the optimum trip path is found using a traveling salesman problem(TSP) branch and bound algorithm. Simulation results show that the battery capacity or the number of UAVs increases as the coverage area or the density increases.展开更多
Recent advancements in cloud computing(CC)technologies signified that several distinct web services are presently developed and exist at the cloud data centre.Currently,web service composition gains maximum attention ...Recent advancements in cloud computing(CC)technologies signified that several distinct web services are presently developed and exist at the cloud data centre.Currently,web service composition gains maximum attention among researchers due to its significance in real-time applications.Quality of Service(QoS)aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS.But these models have failed to handle the uncertainties of QoS.The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users.On the other hand,trip planning is an essential technique in supporting digital map services.It aims to determine a set of location based services(LBS)which cover all client intended activities quantified in the query.But the available web service composition solutions do not consider the complicated spatio-temporal features.For resolving this issue,this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model(F3L-WSCM)in a cloud environment for location awareness.The presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking,hotels,car rentals,etc.At the next stage,the firefly algorithm is applied to generate composition plans to minimize the number of composition plans.Followed by,the fuzzy subtractive clustering(FSC)will select the best composition plan from the available composite plans.Besides,the presented F3L-WSCM model involves four input QoS parameters namely service cost,service availability,service response time,and user rating.An extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy,execution time,and efficiency.展开更多
文摘Tourism is a major foreign exchange earner in Kenya contributing to 10% of the gross domestic product (GDP). Whereas Kenyan government strives to boost its GDP through improved arrivals, lack of effective tourism marketing strategies hinders growth in tourist arrivals in Kenya. To advertise and market the untold wealth of tourist destinations, the government utilizes campaigns through print and electronic media, which are expensive and limited in updating. This study addresses the gap by designing a web Geographic Information System (GIS) portal for marketing and promotion of tourism. To realize this a multimedia GIS database was created using PostgreSQL/PostGIS software to store spatial and multimedia tourism data, while itinerary planning tools were designed using Dijkstra algorithm and Travelling Salesman Problem (TSP) approach. The result was a web GIS portal interface containing tourist information enhanced with text and/or video/audio descriptions. Facebook advertisement was used to popularize the tourism products available in Kenya through visitor engagements as well as directing traffic to the portal fast and inexpensively.
基金supported by project#EFRG18-GER-CEN-10 from the American University of Sharjah。
文摘The use of unmanned aerial vehicles(UAVs) in the collection of data from wireless devices, sensor nodes, and the Internet of Things(IoT) devices has recently received significant attention. In this paper, we investigate the data collection process from a set of smart meters in advanced metering infrastructure(AMI) enabled by UAVs. The objective is to minimize the total annual cost of the electric utility by jointly optimizing the number of UAVs, their power source sizing, the charging locations as well as the data collection trip planning. This is achieved while considering the energy budgets of batteries of UAVs and the required amount of collected data. The problem is formulated as a mixed-integer nonlinear programming(MINLP), which is decoupled into two sub-problems where a candidate UAV and a number of buildings are first grouped into trips via genetic algorithms(GAs), and then the optimum trip path is found using a traveling salesman problem(TSP) branch and bound algorithm. Simulation results show that the battery capacity or the number of UAVs increases as the coverage area or the density increases.
文摘Recent advancements in cloud computing(CC)technologies signified that several distinct web services are presently developed and exist at the cloud data centre.Currently,web service composition gains maximum attention among researchers due to its significance in real-time applications.Quality of Service(QoS)aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS.But these models have failed to handle the uncertainties of QoS.The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users.On the other hand,trip planning is an essential technique in supporting digital map services.It aims to determine a set of location based services(LBS)which cover all client intended activities quantified in the query.But the available web service composition solutions do not consider the complicated spatio-temporal features.For resolving this issue,this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model(F3L-WSCM)in a cloud environment for location awareness.The presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking,hotels,car rentals,etc.At the next stage,the firefly algorithm is applied to generate composition plans to minimize the number of composition plans.Followed by,the fuzzy subtractive clustering(FSC)will select the best composition plan from the available composite plans.Besides,the presented F3L-WSCM model involves four input QoS parameters namely service cost,service availability,service response time,and user rating.An extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy,execution time,and efficiency.
