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Significant effort is being put into developing industrial applications for artificial intelligence (AI), especially those using machine learning (ML) techniques. Despite the intensive support for building ML applications, there are still challenges when it comes to evaluating, assuring, and improving the quality or dependability. The difficulty stems from the unique nature of ML, namely, system behavior is derived from training data not from logical design by human engineers. This leads to black-box and intrinsically imperfect implementations that invalidate many principles and techniques in traditional software engineering. In light of this situation, the Japanese industry has jointly worked on a set of guidelines for the quality assurance of AI systems (in the Consortium of Quality Assurance for AI-based Products and Services) from the viewpoint of traditional quality-assurance engineers and test engineers. We report on the second version of these guidelines, which cover a list of quality evaluation aspects, catalogue of current state-of-the-art techniques, and domain-specific discussions in five representative domains. The guidelines provide significant insights for engineers in terms of methodologies and designs for tests driven by application-specific requirements.

Singapore's TCM Practitioner Board Sets up New Guidelines on Ethical Conduct.

This article reports on the recent developments to the regulation of human cloning and genetic testing and research in Singapore.

The following topics are under this section:

• Dawn of the Big Machine
• Overcoming Cultural Barriers to SSI Prevention Guidelines

The ability to efficiently and effectively reuse ontologies is commonly acknowledged to play a crucial role in the large scale dissemination of ontologies and ontology-driven technology, being thus a pre-requisite for the ongoing realization of the Semantic Web. In this article, we give an account of ontology reuse from a process point of view. We present a methodology that can be utilized to systematize and monitor ontology engineering processes in scenarios reusing available ontological knowledge in the context of a particular application. Notably, and by contrast to existing approaches in this field, our aim is to provide means to overcome the poor reusability of existing resources — rather than to solve the more general issue of building new, more reusable knowledge components. To do so we investigate the impact of the application context of an ontology — in terms of tasks this ontology has been created for and will be utilized in — has on the feasibility of a reuse-oriented ontology development strategy and provide guidelines that take these aspects into account. The applicability of the methodology is demonstrated through a case study performed in collaboration with an international eRecruitment solution provider.

Artificial Intelligence (AI) is moving into a new phase where it is demonstrating the ability to supplement or replace humans across a range of decision-making activities. The transformative power of AI will require sensible regulation and heightened ethical sensitivity to ensure that it enhances rather than undermines human capabilities and values. The successful management of AI will necessitate coordination at the national, international and supranational levels among stakeholders of all types. Moreover, the shape of an AI-supplemented world will be heavily influenced by the rivalry between China and the United States as the world’s leading economic and AI powers. This paper will weave together the above themes to outline the relevant issues and stakes and the manner in which they can be managed to yield a productive AI-supplemented future, wherein AI’s promise is maximized and its potential perils avoided or mitigated.

After every cyber breach, security experts can be found castigating users for lacking “cyber hygiene”—the term used to describe all manner of best practices that would have protected them. Whenever pressed on what cyber hygiene really means, experts resort to conceptual analogies, explaining cyber hygiene in terms of personal hygiene. But is this conceptual leap justified? Is cyber hygiene really analogous to personal hygiene? This is an important question, not just for informing better theory, but also because many practice suggestions, even solutions, are inspired by such thinking. The paper examines the roots of the cyber hygiene concept, and the conceptual similarities and differences between cyber and personal hygiene. The paper then presents a definition of cyber hygiene that is empirically focused on users’ awareness, knowledge, technical capacity, and enactment of cyber security practices. The paper culminates with a presentation of the Cyber Hygiene Inventory (CHI), a multi-item and multidimensional index for measuring user cyber hygiene, and presents examples of how the CHI can be implemented for assessing awareness-knowledge gaps among users and for tracking the effectiveness of awareness training efforts within organizations.

Data mining and knowledge discovery is described from pattern recognition point of view along with the relevance of soft computing. Key features of the computational theory of perceptions (CTP) and its significance in pattern recognition and knowledge discovery problems are explained. Role of fuzzy-granulation (f-granulation) in machine and human intelligence, and its modeling through rough-fuzzy integration are discussed. New concept of rough-fuzzy clustering is introduced with algorithm. Merits of fuzzy granular computation, in terms of performance and computation time, for the task of case generation in large scale case based reasoning systems are illustrated through examples. Rough-fuzzy clustering is applied for segmenting brain MR images. Results show the superior performance in terms of β index.

We present Chebyshev cardinal functions method for solving a second-order boundary-value problems associated with obstacle, unilateral, and contact problems. There are some properties of cardinal functions which make them efficient to interpolate functions in one and higher dimensions. In this paper, we describe the method for solving a system of an obstacle boundary value problem. This technique reduces a system of second-order boundary-value differential equations to a system of linear equations. Moreover, using the auxiliary variable provides the flexibility with respect to initial and boundary conditions. The experimental results confirm the computational efficiency and simplicity of the proposed method.

Polymorphic acetylation of drug and xenobiotics is a known cause of interindividual variability in drug pharmacokinetics and in the risk of developing adverse drug events. Acetylation ability is strongly linked to variations in the arylamine N-acetyltransferase 2 (NAT2) gene, and several procedures have been developed to predict acetylation phenotypes based on genetic tests. This chapter analyses the most salient issues inherent to NAT2 genotyping, haplotype reconstruction and phenotype inference, as well as the clinical implications of the polymorphic acetylation of drugs such as aminoglutethimide, amonafide, caffeine, clonazepam, dapsone, hydralazine, isoniazid, metamizole, nitrazepam, phenelzine, phenytoin, procainamide, sulfamethazine, sulfamethoxazole and sulfasalazine. These drugs and/or their metabolites are polymorphically acetylated, and for many of these drugs, acetylation status (either phenotype or genotype) causes pharmacokinetic changes and often adverse drug events. We identify potential areas needing additional research before NAT2 genetic testing can be used for the development of clinical practice pharmacogenomics guidelines.

Transaction scheduling algorithm is to establish transaction scheduling model contact feedback the relation of transactions, and converts it into an equivalent graph coloring problem, vertex shader graph, in order to achieve a scheduling conflict issues. Compared with the general graph coloring method is the use of different colored nodes to achieve ideological transaction scheduling. The scheduling algorithm is applied to solve practical problems in the current widespread use of RFID technology in the Internet of Things reader conflict in scheduling. By scheduling algorithm can solve the conflict and increase equipment reliability.