The Probabilistic Description Logic BALC

Description logics (DLs) are well-known knowledge representation formalisms focused on the representation of terminological knowledge. Due to their first-order semantics, these languages (in their classical form) are not suitable for representing and handling uncertainty. A proba- bilistic extension of a light-weight DL was recently proposed for dealing with certain knowledge occurring in uncertain contexts. In this paper, we continue that line of research by introducing the Bayesian extension BALC of the propositionally closed DL ALC. We present a tableau-based procedure for deciding consistency and adapt it to solve other probabilistic, contextual, and gen- eral inferences in this logic. We also show that all these problems remain ExpTime-complete, the same as reasoning in the underlying classical ALC

An abstract machine for restricted and-parallel execution of logic programs

Although the sequential execution speed of logic programs has been greatly improved by the concepts introduced in the Warren Abstract Machine (WAM), parallel execution represents the only way to increase this speed beyond the natural limits of sequential systems. However, most proposed parallel logic programming execution models lack the performance optimizations and storage efficiency of sequential systems. This paper presents a parallel abstract machine which is an extension of the WAM and is thus capable of supporting ANDParallelism without giving up the optimizations present in sequential implementations. A suitable instruction set, which can be used as a target by a variety of logic programming languages, is also included. Special instructions are provided to support a generalized version of "Restricted AND-Parallelism" (RAP), a technique which reduces the overhead traditionally associated with the run-time management of variable binding conflicts to a series of simple run-time checks, which select one out of a series of compiled execution graphs

Software tools for the cognitive development of autonomous robots

Robotic systems are evolving towards higher degrees of autonomy. This paper reviews the cognitive tools available nowadays for the fulfilment of abstract or long-term goals as well as for learning and modifying their behaviour.Peer ReviewedPostprint (author's final draft

The Implementation of Logic Fuzzy Mamdani Method as the Decision Support on the Gradual Selection of New Students

Gradual selection of new students at the program of Accountancy Diplome III STIE Binaniaga Bogor thru scholarship procedure using the average method. Minimum expectation of STIE Binaniaga is that the higher the gradual selection result, the better academic performance of the students will be. Applying the average method has not indicated yet the minimum expectation required since there is still the fluctuative academic achievement of the students happened. The research aims to implement the method of logic fuzzy Mamdani accordingly in order to deterimine whether this method can be applied for each gradual selection of new students. Analytical tools have used the comparison one based on the correlation between the academic achievement and the implemention of logic fuzzy Mamdani method at the end of each selection, The correlation between the cumulative achievement index and the final result of the implemention of average method is 0.559. Correlation between the cumulative achievement index and the final result of the implementation of logic fuzzy Mamdani Method is 0.487 which is still less than 0.559. Nevertheless, the conclusion of this result is that the implementation of logic fuzzy Mamdani Method has not yet been able to replace the existing average method

Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.Comment: 10 pages; 6 figures in Proceedings of the 5th Annual International Conference on ICT: Big Data, Cloud and Security (ICT-BDCS 2015), Singapore July 2015. arXiv admin note: text overlap with arXiv:1402.5764, arXiv:1402.575

INTERACTIVE PROGRAMMING SUPPORT FOR SECURE SOFTWARE DEVELOPMENT

Software vulnerabilities originating from insecure code are one of the leading causes of security problems people face today. Unfortunately, many software developers have not been adequately trained in writing secure programs that are resistant from attacks violating program confidentiality, integrity, and availability, a style of programming which I refer to as secure programming. Worse, even well-trained developers can still make programming errors, including security ones. This may be either because of their lack of understanding of secure programming practices, and/or their lapses of attention on security. Much work on software security has focused on detecting software vulnerabilities through automated analysis techniques. While they are effective, they are neither sufficient nor optimal. For instance, current tool support for secure programming, both from tool vendors as well as within the research community, focuses on catching security errors after the program is written. Static and dynamic analyzers work in a similar way as early compilers: developers must first run the tool, obtain and analyze results, diagnose programs, and finally fix the code if necessary. Thus, these tools tend to be used to find vulnerabilities at the end of the development lifecycle. However, their popularity does not guarantee utilization; other business priorities may take precedence. Moreover, using such tools often requires some security expertise and can be costly. What is worse, these approaches exclude programmers from the security loop, and therefore, do not discourage them from continuing to write insecure code. In this dissertation, I investigate an approach to increase developer awareness and promoting good practices of secure programming by interactively reminding program- mers of secure programming practices in situ, helping them to either close the secure programming knowledge gap or overcome attention/memory lapses. More specifi- cally, I designed two techniques to help programmers prevent common secure coding errors: interactive code refactoring and interactive code annotation. My thesis is that by providing reminder support in a programming environment, e.g. modern IDE, one can effectively reduce common security vulnerabilities in software systems. I have implemented interactive code refactoring as a proof-of-concept plugin for Eclipse (32) and Java (57). Extensive evaluation results show that this approach can detect and address common web application vulnerabilities and can serve as an effective aid for programmers in writing secure code. My approach can also effectively complement existing software security best practices and significantly increase developer productivity. I have also implemented interactive code annotation, and conducted user studies to investigate its effectiveness and impact on developers’ programming behaviors and awareness towards writing secure code