Dynamic workflow scheduling (DWS) is a challenging and important optimization problem in cloud computing, aiming to execute multiple heterogeneous workflows on dynamically leased virtual machine resources satisfy user-defined Quality of Service requirements. For the popular deadline-constrained DWS problem, selection rule (VMSR) task (TSR) need be designed simultaneously minimize rental fee deadline violation penalty. this purpose, Dual-Tree Genetic Programming (DTGP) has been previously...

This study proposes a new approach to creating virtual flight test environment by integrating digital twin of an iron bird rig with engineering simulator. Generating twins for rigs in aviation is rare and innovative approach. The simulator used this incorporates real hands-on throttle stick provide pilots realistic experience. A validated trainer aircraft, fully equipped encompassing hydraulic, mechanical, control, landing gear systems, was as the basis generating its twin. then update...

We review key constraints in the context of XML as introduced by Buneman et al. demonstrate that: (1) one proposed inference rules is not sound general, and (2) are incomplete for implication, even nonempty sets simple paths. This shows, contrast to earlier statements, that axiomatizability keys still open, efficient algorithms deciding their implication need be developed. Solutions these problems have a wide range applications including consistency validation, schema design, data exchange...

Enterprise application providers are increasingly moving their workloads to the cloud for technical and economic benefits. Multi-cloud environment makes it possible orchestrate multiple resources. With increasing number of available resources provided by at different locations with prices, face challenge select proper deploy applications in form a workflow component service units. Existing studies usually consider minimizing execution time or/and deployment cost. From perspective providers,...

Rolling element bearings are one of the most critical components rotating machinery, with bearing faults amounting up to 50% in electrical machines. Therefore, fault diagnosis has attracted attention many researchers. Typically, is performed using vibration signals from machine. In addition, by deep learning algorithms on signals, detection accuracy close 100% can be achieved. However, measurement requires an additional sensor, which not present majority Nevertheless, alternative approach,...

We investigate the implication problem for classes of data dependencies over SQL table definitions. Under Zaniolo's “no information” interpretation null markers we establish an axiomatization and algorithms to decide combined class functional multivalued in presence NOT NULL constraints. The resulting theory subsumes three previously orthogonal frameworks. further show that this is equivalent a propositional fragment Schaerf Cadoli's [1995] family para-consistent S-3 logics. In particular, S...

Multi-cloud is becoming a popular cloud ecosystem because it allows enterprise users to share the workload across multiple service providers achieve high-quality services with lower operation cost and higher application resilience. In multi-cloud, are widely distributed at different locations differentiated prices. Therefore, Web face challenge select proper for replication deployment aim of minimizing cost. Meanwhile, deployed replicas must satisfy constraint on request response time...

Journal Article On Codd Families of Keys over Incomplete Relations Get access Sven Hartmann, Hartmann 1Department Informatics, Clausthal University Technology, Clausthal-Zellerfeld, Germany Search for other works by this author on: Oxford Academic Google Scholar Uwe Leck, Leck 2Department Mathematics and Computer Science, Wisconsin, Madison, WI, USA Sebastian Link * 3School Information Management, Victoria Wellington, New Zealand *Corresponding author: Sebastian.Link@vuw.ac.nz The Journal,...

AC machines may be subjected to different electrical or mechanical faults during their operation. Fault patterns can detected in the DC current from machine's E-Drive system with help of Deep Machine Learning algorithms. However, algorithms require large amounts dataset for training and without availability a fail generalize give optimal performance. Collecting data faulty machine tedious task. It is expensive not always possible. In some cases, completely damaged even before sufficient...

Scenario-based approaches have recently been widely adopted in the automotive and aviation industries.They aim to define manage test cases a better way, thereby significantly reducing risks defining safety argument for system.To improve complement conditions, Operational Design Domain (OOD) defines operational boundaries of driving automation system specify scope case, represented by human machinereadable languages.Many standards that involve essential modelling concepts introduced represent...

While any simulation study starts with a scenario, scenario development is usually conducted in an unstructured and ad hoc manner.In order to streamline development, formal approach envisioned the research flight simulator facility of German Aerospace Center (DLR), namely Air Vehicle Simulator (AVES).System Entity Structure (SES) which high level ontology that was introduced specify set system structures parameter settings proposed as foundations.The paper outlines model-based methodology...

The importance of accurate intrusion detection is growing tremendously as the malicious network traffic activities have also grown significantly. Intrusion Detection Systems (IDSs) provide automatic for security violation like denial service (DoS), virus, port scans, buffer overflows, CGI attacks, clogging or flooding etc. For and host based systems, most widely used effective approach data analysis with signature-based methods. Thus, success system depends on real appearance violation,...