Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Defending Against Firmware Cyber Attacks on Safety-Critical Systems

In the past, it was not possible to update the underlying software in many industrial control devices. Engineering teams had to ‘rip and replace’ obsolete components. However, the ability to make firmware updates has provided significant benefits to the companies who use Programmable Logic Controllers (PLCs), switches, gateways and bridges as well as an array of smart sensor/actuators. These updates include security patches when vulnerabilities are identified in existing devices; they can be distributed by physical media but are increasingly downloaded over Internet connections. These mechanisms pose a growing threat to the cyber security of safety-critical applications, which are illustrated by recent attacks on safety-related infrastructures across the Ukraine. Subsequent sections explain how malware can be distributed within firmware updates. Even when attackers cannot reverse engineer the code necessary to disguise their attack, they can undermine a device by forcing it into a constant upload cycle where the firmware installation never terminates. In this paper, we present means of mitigating the risks of firmware attack on safety-critical systems as part of wider initiatives to secure national critical infrastructures. Technical solutions, including firmware hashing, must be augmented by organizational measures to secure the supply chain within individual plants, across companies and throughout safety-related industries

Formal Reasoning Using an Iterative Approach with an Integrated Web IDE

This paper summarizes our experience in communicating the elements of reasoning about correctness, and the central role of formal specifications in reasoning about modular, component-based software using a language and an integrated Web IDE designed for the purpose. Our experience in using such an IDE, supported by a 'push-button' verifying compiler in a classroom setting, reveals the highly iterative process learners use to arrive at suitably specified, automatically provable code. We explain how the IDE facilitates reasoning at each step of this process by providing human readable verification conditions (VCs) and feedback from an integrated prover that clearly indicates unprovable VCs to help identify obstacles to completing proofs. The paper discusses the IDE's usage in verified software development using several examples drawn from actual classroom lectures and student assignments to illustrate principles of design-by-contract and the iterative process of creating and subsequently refining assertions, such as loop invariants in object-based code.Comment: In Proceedings F-IDE 2015, arXiv:1508.0338

Special Session on Industry 4.0

No abstract available

Transformation As Search

In model-driven engineering, model transformations are con- sidered a key element to generate and maintain consistency between re- lated models. Rule-based approaches have become a mature technology and are widely used in different application domains. However, in var- ious scenarios, these solutions still suffer from a number of limitations that stem from their injective and deterministic nature. This article pro- poses an original approach, based on non-deterministic constraint-based search engines, to define and execute bidirectional model transforma- tions and synchronizations from single specifications. Since these solely rely on basic existing modeling concepts, it does not require the intro- duction of a dedicated language. We first describe and formally define this model operation, called transformation as search, then describe a proof-of-concept implementation and discuss experiments on a reference use case in software engineering

Security Toolbox for Detecting Novel and Sophisticated Android Malware

This paper presents a demo of our Security Toolbox to detect novel malware in Android apps. This Toolbox is developed through our recent research project funded by the DARPA Automated Program Analysis for Cybersecurity (APAC) project. The adversarial challenge ("Red") teams in the DARPA APAC program are tasked with designing sophisticated malware to test the bounds of malware detection technology being developed by the research and development ("Blue") teams. Our research group, a Blue team in the DARPA APAC program, proposed a "human-in-the-loop program analysis" approach to detect malware given the source or Java bytecode for an Android app. Our malware detection apparatus consists of two components: a general-purpose program analysis platform called Atlas, and a Security Toolbox built on the Atlas platform. This paper describes the major design goals, the Toolbox components to achieve the goals, and the workflow for auditing Android apps. The accompanying video (http://youtu.be/WhcoAX3HiNU) illustrates features of the Toolbox through a live audit.Comment: 4 pages, 1 listing, 2 figure