In today’s competitive business environment,the cost of a product is one of the most important considerations for its sale.Businesses are heavily involved in research strategies to minimize the cost of elements that ...In today’s competitive business environment,the cost of a product is one of the most important considerations for its sale.Businesses are heavily involved in research strategies to minimize the cost of elements that can impact on the final price of the product.Logistics is one such factor.Numerous products arrive from diverse locations to consumers in today’s digital era of online businesses.Clearly,the logistics sector faces several dilemmas from order attributes to environmental changes in this regard.This has specially been noted during the ongoing Covid-19 pandemic where the demands on online businesses have increased several fold.Consequently,the methodology to optimise delivery cost and its impact on environmental focus by reducing CO_(2) emissions has gained relevance.The resultant strategy of Shipment Consolidation that has evolved is an approach that combines one or more transport orders in the same vehicle for delivery.Shipment Consolidation has been categorized in three order scheduling approaches:Time based consolidation,Quantity based consolidation,and a Hybrid(Time-Quantity)based consolidation.In this paper,a new Hybrid Consolidation approach is presented.Using the Hybrid approach,it has been shown that order delivery can be facilitated by taking into account not only the order pick up time,but also the total order quantity.These results have shown that if a time window is available in respect of the order delivery time,then the order can be delayed from pickup to consolidate it with other orders for cost optimization.This hybrid approach is based on four consolidation principles,two of which work on fixed departure and two,on demand departure.Three of these rules have been implemented and tested here with an application case study.Statistical analysis of the results is illustrated with different planning evaluation indicators.The Result analyses indicate that consolidation of orders is increased with each implemented rule hence motivating us towards the implementation of the fourth rule.Testing with bigger data sets is required.展开更多
Currently,many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces.The context offers the information base for the development of Adaptive user interface(AUI)...Currently,many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces.The context offers the information base for the development of Adaptive user interface(AUI)frameworks to overcome the heterogeneity.For this purpose,the ontological modeling has been made for specific context and environment.This type of philosophy states to the relationship among elements(e.g.,classes,relations,or capacities etc.)with understandable satisfied representation.The contextmechanisms can be examined and understood by anymachine or computational framework with these formal definitions expressed in Web ontology language(WOL)/Resource description frame work(RDF).The Protégéis used to create taxonomy in which system is framed based on four contexts such as user,device,task and environment.Some competency questions and use-cases are utilized for knowledge obtaining while the information is refined through the instances of concerned parts of context tree.The consistency of the model has been verified through the reasoning software while SPARQL querying ensured the data availability in the models for defined use-cases.The semantic context model is focused to bring in the usage of adaptive environment.This exploration has finished up with a versatile,scalable and semantically verified context learning system.This model can be mapped to individual User interface(UI)display through smart calculations for versatile UIs.展开更多
Internet-of-Things(IoT)has attained a major share in embedded software development.The new era of specialized intelligent systems requires adaptation of customized software engineering approaches.Currently,software en...Internet-of-Things(IoT)has attained a major share in embedded software development.The new era of specialized intelligent systems requires adaptation of customized software engineering approaches.Currently,software engineering has merged the development phases with the technologies provided by industrial automation.The improvements are still required in testing phase for the software developed to IoT solutions.This research aims to assist in developing the testing strategies for IoT applications,therein ontology has been adopted as a knowledge representation technique to different software engineering processes.The proposed ontological model renders 101 methodology by using Protégé.After completion,the ontology was evaluated in three-dimensional view by the domain experts of software testing,IoT and ontology engineering.Satisfied results of the research are showed in interest of the specialists regarding proposed ontology development and suggestions for improvements.The Proposed reasoning-based ontological model for development of testing strategies in IoT application contributes to increase the general understanding of tests in addition to assisting for the development of testing strategies for different IoT devices.展开更多
基金The authors would like to acknowledge the support of the Deputy for Research and Innovation,Ministry of Education,Kingdom of Saudi Arabia for this research through a grant(NU/IFC/INT/01/008)under the institutional Funding Committee at Najran University,Kingdom of Saudi Arabia.
文摘In today’s competitive business environment,the cost of a product is one of the most important considerations for its sale.Businesses are heavily involved in research strategies to minimize the cost of elements that can impact on the final price of the product.Logistics is one such factor.Numerous products arrive from diverse locations to consumers in today’s digital era of online businesses.Clearly,the logistics sector faces several dilemmas from order attributes to environmental changes in this regard.This has specially been noted during the ongoing Covid-19 pandemic where the demands on online businesses have increased several fold.Consequently,the methodology to optimise delivery cost and its impact on environmental focus by reducing CO_(2) emissions has gained relevance.The resultant strategy of Shipment Consolidation that has evolved is an approach that combines one or more transport orders in the same vehicle for delivery.Shipment Consolidation has been categorized in three order scheduling approaches:Time based consolidation,Quantity based consolidation,and a Hybrid(Time-Quantity)based consolidation.In this paper,a new Hybrid Consolidation approach is presented.Using the Hybrid approach,it has been shown that order delivery can be facilitated by taking into account not only the order pick up time,but also the total order quantity.These results have shown that if a time window is available in respect of the order delivery time,then the order can be delayed from pickup to consolidate it with other orders for cost optimization.This hybrid approach is based on four consolidation principles,two of which work on fixed departure and two,on demand departure.Three of these rules have been implemented and tested here with an application case study.Statistical analysis of the results is illustrated with different planning evaluation indicators.The Result analyses indicate that consolidation of orders is increased with each implemented rule hence motivating us towards the implementation of the fourth rule.Testing with bigger data sets is required.
基金This research is supported by the Ministry of Culture,Sports and Tourism and Korean Creative Content Agency(Project No:2020040243).
文摘Currently,many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces.The context offers the information base for the development of Adaptive user interface(AUI)frameworks to overcome the heterogeneity.For this purpose,the ontological modeling has been made for specific context and environment.This type of philosophy states to the relationship among elements(e.g.,classes,relations,or capacities etc.)with understandable satisfied representation.The contextmechanisms can be examined and understood by anymachine or computational framework with these formal definitions expressed in Web ontology language(WOL)/Resource description frame work(RDF).The Protégéis used to create taxonomy in which system is framed based on four contexts such as user,device,task and environment.Some competency questions and use-cases are utilized for knowledge obtaining while the information is refined through the instances of concerned parts of context tree.The consistency of the model has been verified through the reasoning software while SPARQL querying ensured the data availability in the models for defined use-cases.The semantic context model is focused to bring in the usage of adaptive environment.This exploration has finished up with a versatile,scalable and semantically verified context learning system.This model can be mapped to individual User interface(UI)display through smart calculations for versatile UIs.
基金This work was supported by the King Saud University(in Riyadh,Saudi Arabia)through the Researcher Support Project Number(RSP-2021/387).
文摘Internet-of-Things(IoT)has attained a major share in embedded software development.The new era of specialized intelligent systems requires adaptation of customized software engineering approaches.Currently,software engineering has merged the development phases with the technologies provided by industrial automation.The improvements are still required in testing phase for the software developed to IoT solutions.This research aims to assist in developing the testing strategies for IoT applications,therein ontology has been adopted as a knowledge representation technique to different software engineering processes.The proposed ontological model renders 101 methodology by using Protégé.After completion,the ontology was evaluated in three-dimensional view by the domain experts of software testing,IoT and ontology engineering.Satisfied results of the research are showed in interest of the specialists regarding proposed ontology development and suggestions for improvements.The Proposed reasoning-based ontological model for development of testing strategies in IoT application contributes to increase the general understanding of tests in addition to assisting for the development of testing strategies for different IoT devices.
