31156520
An Ontology-based Data Matching Framework: use Case Competency-based HRM
As part of the European PROLIX (Process Oriented Learning and Information eXchange) project, VUB STARLab designed a generic ontology-based data matching framework (ODMF). Within the project, the ODMF is used to calculate the similarity between data elements, e.g. competency, function, person, task, and qualification, based on competency-information. Several ontology-based data matching strategies were implemented and evaluated as part of the ODMF. In this article we describe the ODMF and discuss the implemented matching strategies.
16597693
On Conducting a Decision Group to Construct Semantic Decision Tables
Semantic Decision Table (SDT) was introduced to support collaborative decision making. Semantics, a group of decision makers, mutual understanding and collaborative environment(s) are at the heart of SDT. In practice, it is rather difficult to construct SDT within a decision group. We try to tackle this problem by modeling SDT within the context of information system, which is based on McGrath's Conceptual Framework for the Study of Group. Ontologies and DOGMA (Developing Ontology-Grounded Methods and Applications) approach to ontology engineering are proposed to store the semantics and mutual understanding for SDT. In this paper, we also propose a generic method of guiding a group to construct SDT, which is illustrated with an example of online customer management in the privacy domain.
33017168
An ontology engineering methodology for DOGMA
Although ontologies occupy a central place in the Semantic Web and related research domains, there are currently not many fully fledged ontology engineering methodologies available. In this paper, we want to present an integrated methodology for ontology engineering from scratch, inspired by various scientific disciplines, in particular database semantics and natural language processing.
2826645
PROFILE COMPILER: Ontology-based, community-grounded, multilingual online services to support collaborative decision making
In todaypsilas industries, ontologies and the modern semantic technologies are offered as the potential solutions to support mutual understanding in the collaborative settings. Currently, organizations are unable to cope with collaborative decision making in a particular domain. Mastering domain knowledge and sharing decision rules is a complex yet important issue. In this paper, we first design a generic framework for community-grounded, collaborative decision making enabled, ontology based systems. This framework is constructed with three main engineering tracks: the linguistic engineering track, the ontology engineering track and the group decision engineering track. Each engineering track has its own methodology supported by a tool. Then, we use Semantic Decision Tables to elaborate the knowledge blocks resulting from these three engineering tracks. Semantic Decision Tables are mainly used (1) to elaborate concepts of the domain ontologies, (2) to gather semantically grounded decision rules within a decision group and (3) to provide tabular reports to the users. Finally, an online multilingual knowledge platform - the PROFILE COMPILER is developed as the result. It allows small or medium-sized enterprises (SMEs) to retrieve and personalize existing domain ontology, design and share their decision rules. We illustrate in the domain of Human Resource Management (HRM).
2555681
Judicial Support Systems: Ideas for a Privacy Ontology-Based Case Analyzer
Nowadays, ontology is applied as an integral part of many applications in several domains, especially in the world of law. The ontology based judicial support system is believed as a useful tool to support, for example, the legal argumentation assistant and legal decision taking in court. The privacy case analyzer is considered as one of the most interesting applications of ontology based privacy judicial support systems. The efficiency of privacy case analyzers depend on several factors such as how to tackle the problem of linking cases to legislations, how to imply the guidance of privacy principles, and how to improve the extraction of cases. This paper addresses those items and describes the research issues that will be investigated challenges of ontology based judicial support systems.
17885523
On Constructing Semantic Decision Tables
Decision tables are a widely used knowledge management tool in the decision making process. Ambiguity and conceptual reasoning difficulties arise while designing large decision tables in a collaborative environment. We introduce the notion of Semantic Decision Table (SDT), which enhances a decision table with explicit decision semantics by annotating it properly with a domain ontology. In this paper, we focus on the SDT construction process. First, we map decision items to the ontology by building a rooted tree of decision binary facts and visualize it in a scalable manner. Formal ontological roles are used during this mapping process. Then, we commit the decision rules to the mapping results with a high level pseudo-natural language to ground their semantic. We illustrate with an SDT example from the domain of human resource management.
8498633
The Data Scales in Multi-valued Context Based on Formal Concept Analysis
Formal Concept Analysis has very important meaning in mathematical methods for data mining and knowledge processing. In the face of the variety of the data structure, traditional methods can hardly meet decider’s need. This paper summarizes a few of data structure for the concept analysis and present the data scale methods for each other based on their own characters. It not only extends the application of the concept analysis, but also makes the data scale methods more efficiently.
1201413
LeakSurvivor: Towards Safely Tolerating Memory Leaks for Garbage-Collected Languages
Continuous memory leaks severely hurt program performance and software availability for garbage-collected programs. This paper presents a safe method, called LeakSurvivor, to tolerate continuous memory leaks at runtime for garbage-collected programs. Our main idea is to periodically swap out the "Potentially Leaked" (PL) memory objects identified by leak detectors from the virtual memory to disks. As a result, the virtual memory space occupied by the PL objects can be reclaimed by garbage collectors and available for future uses. If a swapped-out PL object is accesses later, LeakSurvivor will restore it from disks to the memory for correct program execution. Furthermore, LeakSurvivor helps developers to prune false positives. 
 
We have built the prototype of LeakSurvivor on top of Jikes RVM 2.4.2, a high performance Java-in-Java virtual machine developed by IBM. We conduct the experiments with three Java applications including Eclipse, SPECjbb2000 and Jigsaw. Among them, Eclipse and Jigsaw contain memory leaks introduced by their developers, while SPECjbb2000 contain a memory leak injected by us. Our results show that LeakSurvivor effectively tolerates memory leaks for two applications (Eclipse and SPECjbb2000), i.e., no cumulative performance degradation and no software failures when facing continuous memory leaks at runtime. For Jigsaw, LeakSurvivor extends the program lifetime by two times and improves the performance by 46% compared with native runs. Furthermore, when there are no memory leaks, LeakSurvivor imposes small runtime overhead, i.e., 2.5% over the leak detector and 23.7% over the native runs.
14763261
Zero-Efficient Buffer Design for Reliable Network-on-Chip in Tiled Chip-Multi-Processor
Network-on-chip (NoC) is a promising solution for efficient interconnection between processor cores in chip-multi-processor (CMP). This paper is focusing on the energy-efficient design of buffers, a group of the most important components in NoC. From our investigation, an overwhelming majority of "zero" is contained in the packets transmitting in NoC for CMP. A zero-efficient buffer design is proposed as well as the error control scheme. Compared with conventional design, up to 43% energy consumption can be saved. We use a 90 nm CMOS process in our simulation.
12737531
Accelerating the 2D Mallat decomposition algorithm with cyclical convolution and FNTT
This paper presents a novel approach to accelerate the 2D Mallat decomposition algorithm. In particular the proposed approach performs the 2D Mallat decomposition algorithm by way of computing the 2D cyclical convolution, and further completes the 2D cyclical convolution with the fast number theoretical transform (FNTT). Therefore, the 2D Mallat decomposition algorithm can be speeded up. The results obtained from the theoretical analysis and the experiment show that the 2D Mallat decomposition algorithm is significantly improved.
38545491
Defining Re-usable Composite Aspect Patterns: An FDAF Based Approach
Architecting secure systems is an important and challenging problem. Solutions to model individual, or atomic, security capabilities have been proposed, including security patterns, component based, aspect-oriented, and service-oriented approaches. However, little work is available on how to model reusable compositions of security capabilities, where the security capabilities interact with each other and other parts of the system design. Here, an aspect-oriented approach to modeling composite aspects is presented. The approach is defined as an extension to the Formal Design Analysis Framework (FDAF). The FDAF metamodel is extended to support the static representation of composite aspects and an approach to defining the compositions is introduced. A composite aspect that provides Account Lockout with Selective Event Logging (ALSEL) capabilities is used as an example.