As the prevalence of producing devices equipped with multiple interfaces, the idea to enhance network resource usage by developing a multipath transmission control protocol has recently captured great attention from m...
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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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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In this paper we present an intrusion detection engine comprised of two main elements;firstly, a neural network for the actual detection task and secondly watermarking techniques for protecting the related information...
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In this paper we present an intrusion detection engine comprised of two main elements;firstly, a neural network for the actual detection task and secondly watermarking techniques for protecting the related information that must be exchanged between nodes. In particular, we exploit information visualization and machine learning techniques in order to achieve efficient and effective intrusion detection. In order to avoid possible modification or alteration of the maps produced by the intrusion detection engine, we focus on safeguarding and authenticating them using a novel embedded watermarking method. Previously, we had shown promising results in the intrusion detection task using this system. This paper focuses on the watermarking technique and gives a detailed exposition that includes an experimental evaluation of its quality.
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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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.
This purpose of this paper is to investigate the role played by different CMC for supporting young parents' reporting of everyday experiences about their baby''s development with geographically separated f...
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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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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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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%.
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