Swedish Institute of Computer Science Publications Database
Not a member yet
2787 research outputs found
Sort by
On the global solution of a fuzzy linear system
No full textThe global solution of a fuzzy linear system contains the crisp vector solution of a real linear system. So discussion about the global solution of a n × n fuzzy linear system Ax˜ = b˜ with a fuzzy number vector b in the right hand side and crisp a coefficient matrix A is considered. The advantage of the paper is developing a new algorithm to find the solution of such system by considering a global solution based upon the concept of a convex fuzzy numbers. At first the existence and uniqueness of the solution are introduced and then the related theorems and properties about the solution are proved in details. Finally the method is illustrated by solving some numerical examples.
Keywords: Fuzzy linear system, Algebraic solution, Fuzzy number
Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making
No full textOne of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation
Combinatorial Spill Code Optimization and Ultimate Coalescing
No full textThis paper presents a novel combinatorial model that integrates global register allocation based on ultimate coalescing, spill code optimization, register packing, and multiple register banks with instruction scheduling (including VLIW). The model exploits alternative temporaries that hold the same value as a new concept for ultimate coalescing and spill code optimization.
The paper presents Unison as a code generator based on the model and advanced solving techniques using constraint programming. Thorough experiments using MediaBench and a processor (Hexagon) that are typical for embedded systems demonstrate that Unison: is robust and scalable; generates faster code than LLVM (up to 41% with a mean improvement of 7%); possibly generates optimal code (for 29% of the experiments); effortlessly supports different optimization criteria (code size on par with LLVM).
Unison is significant as it addresses the same aspects as traditional code generation algorithms, yet is based on a simple integrated model and robustly can generate optimal code
Experiencing art through kinesthetic dialogue
No full textFrom the analysis of how the Lega, a touch, motion, and location sensitive device that allows museum visitors to share their experiences, we identified kinaesthetic dialogue as an orienting concept for the understanding and the design of movement-based social interaction and experiences. It provides an analytical lens which captures critical aspects of kinaesthetic action in aesthetic experiences, as well as for better understanding of how users appropriate such artefacts in interaction. We believe that kinaesthetic dialog is a promising candidate for a meta-concept to capture interaction design knowledge in movement based technologies
Trusted Geolocation-Aware Data Placement in Infrastructure Clouds
No full textData geolocation in the cloud is becoming an increasingly pressing problem, aggravated by incompatible legislation in different jurisdictions and compliance requirements of
data owners. In this work we present a mechanism allowing cloud users to control the geographical location of their data, stored or processed in plaintext on the premises of Infrastructure-as-a-Service cloud providers. We use trusted computing principles and remote attestation to establish platform state. We enable cloud users to confine plaintext data exclusively to the jurisdictions they specify, by sealing decryption keys used to obtain plaintext data to the combination of cloud host geolocation and platform state. We provide a detailed description of the implementation as well as performance measurements on an open source cloud infrastructure platform using commodity hardware
Fault Diagnosis of Heavy Duty Machines: Automatic Transmission Clutches
No full textThis paper presents a generic approach to fault diagnosis of heavy duty machines that combines signal processing, statistics, machine learning, and case-based reasoning for on-board and off-board analysis. The used methods complement each other in that the on-board methods are fast and light-weight, while case-based reasoning is used off-board for fault diagnosis and for retrieving cases as support in manual decision making. Three major contributions are novel approaches to detecting clutch slippage, anomaly detection, and case-based diagnosis that is closely integrated with the anomaly detection model. As example application, the proposed approach has been applied to diagnosing the root cause of clutch slippage in automatic transmissions
Search-Based Testing for Embedded Telecom Software with Complex Input Structures
No full textIn this paper, we discuss the application of search-based software testing techniques for unit level testing of a real-world telecommunication middleware at Ericsson. Our current implementation analyzes the existing test cases to handle non-trivial variables such as uninitialized pointers, and to discover any setup code that needs to run before the actual test case, such as setting global system parameters. Hill climbing (HC) and (1+1) evolutionary algorithm (EA) metaheuristic search algorithms are used to generate input data for branch coverage. We compare HC, (1+1)EA, and random search with respect to effectiveness, measured as branch coverage, and efficiency, measured as number of executions needed. Difficulties arising from the specialized execution environment and the adaptations for handling these problems are also discussed
Scaling HDFS with a Strongly Consistent Relational Model for Metadata
No full textThe Hadoop Distributed File System (HDFS) scales to store tens of petabytes of data despite the fact that the entire file system's metadata must fit on the heap of a single Java virtual machine. The size of HDFS' metadata is limited to under 100 GB in production, as garbage collection events in bigger clusters result in heartbeats timing out to the metadata server(NameNode).
In this paper, we address the problem of how to migrate the HDFS' metadata to a relational model, so that we can support larger amounts of storage on a shared nothing, in-memory, distributed database. Our main contribution is that we show how to provide at least as strong consistency semantics as HDFS while adding support for a multiple-writer, multiple-reader concurrency model. We guarantee freedom from deadlocks by logically organizing inodes (and their constituent blocks and replicas) into a hierarchy and having all metadata operations agree on a global order for acquiring both explicit locks and implicit locks on subtrees in the hierarchy. We use transactions with pessimistic concurrency control to ensure the safety and progress of metadata operations. Finally, we show how to improve performance of our solution by introducing a snapshotting mechanism at NameNodes that minimizes the number of roundtrips to the databas