Hasan Selamat

An Agent-Based Supplier Selection Framework: A Case-Based Reasoning Approach

In a competitive environment, those enterprises that always look forward and implement customer-winning supply chain competencies are more profitable than those that do not have such. Existing approaches have not considered customers’ needs in the supplier selection and negotiation processes. This paper aims to present a systematic agent-based framework for supplier selection based on the case-based reasoning approach to evaluate material offers, and negotiate with the suppliers and customers on the price, volume, quality grade, and delivery date of supply materials. The main objective of this research is to take the customers’ needs into consideration and provide them with alternative products which are closest to their first order if their first order was out of stock or they couldn’t get supply from the suppliers. Based on the proposed framework, a numerical example of the known case study is illustrated for highlighting the effectiveness of the approach.

Modeling coherence in mixed-initiative dialogues based on Conversational Acts Theory

In corpus-based response generation, dialogue utterances and strategies are constructed in the form of dialogue models. Previous approaches in dialogue modeling are based on speech acts at different level of abstractions, but often constructed as grammar-based. This paper presents modeling dialogue utterances and strategies based on Conversational Acts Theory. In this approach, learning is more intuitive in the sense that response utterance should robustly satisfy the intention of input utterance. At the same time the response must maintain coherence and relevance, regardless of the surface presentation. This means response generation is constrained by the content of intentions, rather than the lexicons and grammar. Modeling the coherence is performed on a mixed-initiative, transaction dialogue corpus of 64 conversations in theater information and reservation system.

A proof-producing machine-code analyzer for secure information flow

An approach enabling end-users to verify that a downloaded untrusted code will not leak confidential data to unauthorized parties is presented. The approach certifies RISC-style assembly programs for secure information flow by statically analyzing the code based on the idea of Proof Carrying Code (PCC). The proofs that untrusted code does not leak sensitive information are generated and checked on the host machine and if they are valid, then the untrusted code can be installed and executed safely. The proposed security analyzer operates directly on the machinecode requiring only the inputs and outputs of the code be annotated with security levels. The generated proofs serve as evidence that give end-users a guarantee about the security of the untrusted code.