Schema mappings play a central role in both data integration and data exchange, and are understood as high-level specifications describing the relationships between data schemas. Based on these specifications, data st...
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Schema mappings play a central role in both data integration and data exchange, and are understood as high-level specifications describing the relationships between data schemas. Based on these specifications, data structured under a source schema can be transformed into data structured under a target schema. During the transformation some structural constraints, both context-free (the structure) and contextual (e.g. keys and value dependencies) should be taken into account. In this work, we present a new formalism for the schema mapping specification. We propose a new class of tree-pattern formulas in order to extend semantics of XML schema mappings by specification of key constraints and value dependencies. We discuss foundations of the method and propose a key-preserving transformation algorithm.
Crime is a universal social issue that affects a society’s nature of life and economic growth. With ever-increasing crime rates, law enforcement agencies have begun to show interest in data mining approaches to analy...
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D2D(Device-to-device) improves communication quality by reusing cellular users' spectrum resources, becoming one of the key technologies for super-large data processing and massive devices accessing in the 5G. Due...
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In recent times,Internet of Things(IoT)and Cloud Computing(CC)paradigms are commonly employed in different healthcare *** gadgets generate huge volumes of patient data in healthcare domain,which can be examined on clo...
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In recent times,Internet of Things(IoT)and Cloud Computing(CC)paradigms are commonly employed in different healthcare *** gadgets generate huge volumes of patient data in healthcare domain,which can be examined on cloud over the available storage and computation resources in mobile *** Kidney Disease(CKD)is one of the deadliest diseases that has high mortality rate across the *** current research work presents a novel IoT and cloud-based CKD diagnosis model called Flower Pollination Algorithm(FPA)-based Deep Neural Network(DNN)model abbreviated as *** steps involved in the presented FPA-DNN model are data collection,preprocessing,Feature Selection(FS),and ***,the IoT gadgets are utilized in the collection of a patient’s health *** proposed FPA-DNN model deploys Oppositional Crow Search(OCS)algorithm for FS,which selects the optimal subset of features from the preprocessed *** application of FPA helps in tuning the DNN parameters for better classification *** simulation analysis of the proposed FPA-DNN model was performed against the benchmark CKD *** results were examined under different *** simulation outcomes established the superior performance of FPA-DNN technique by achieving the highest sensitivity of 98.80%,specificity of 98.66%,accuracy of 98.75%,F-score of 99%,and kappa of 97.33%.
Scholars in life sciences have to process huge amounts of data in a disciplined and efficient way. These data are spread among thousands of databases which overlap in content but differ substantially with respect to i...
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The majority of traffic accidents are caused by human error. To counteract that, Advanced Driver-Assistance Systems (ADAS) are being developed and installed in vehicles. One of those systems is the Lane Keeping Assist...
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With the need to make sense out of large and constantly growing information spaces, tools to support information management are becoming increasingly valuable. In prior work we proposed the "Visual Wiki" con...
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Learning analytics (LA) is one of the promising techniques that has been developed in recent times to effectively utilise the astonishing volume of student data available in higher education. Despite many difficulties...
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Learning analytics (LA) is one of the promising techniques that has been developed in recent times to effectively utilise the astonishing volume of student data available in higher education. Despite many difficulties in its widespread implementation, it has proved to be a very useful way to support failing learners. An important feature of the literature review of LA is that LA has not provided a significant benefit in terms of learner mobility to date since not much research has been carried out to determine the importance of LA in facilitating or enhancing the learning experience of mobile learners. Therefore, this paper describes the potential advantages of using LA techniques to enhance learning in mobile and ubiquitous learning environments from a theoretical perspective. Furthermore, we describe our simplified Mobile and Ubiquitous Learning Analytics Model (MULAM) for analysing mobile learners' data which is based on Campbell and Oblinger's five-step model of learning analytics. Finally, we answer the question why now might be the most suitable time to consider analysing mobile learners' data.
Monitoring, control and management of wine production using sensors, IoT and machine learning methods is becoming more and more common. Wireless connection of sensors requires knowledge of losses due to electromagneti...
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The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. However, the most serious problem associated with the BP is local minima problem and slow converge...
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