Multi-agent information-inferencing fusion system for decision support system

In this paper we address the utilization of multi-agent approach to an information-inferencing fusion system.Information-inferencing fusion is an emulation of the way human fuses information delivered by human sensing organs after observing a phenomenon in his/her environment.The fused information is used as the basis for making a decision or an action to face the current situation or anticipate the situation that can probably occur in the future.This human capability is then emulated to Multi-Agent Information-inferencing Fusion System (MAIIFS) based on A3S (ArwinAdang-Aciek-Sembiring). From the results presented in this paper, the A3S method information-inferencing fusion method can deliver comprehensive information in a very quick manner so the decision maker can have situation awareness quicker.Therefore, he can to make the decision in accurate and quick manner

Cognitive Artificial Intelligence: Concept and Applications for Humankind

Computation within the human brain is not possible to be emulated 100% in artificial intelligence machines. Human brain has an awesome mechanism when performing computation with new knowledge as the end result. In this chapter, we will show a new approach for emulating the computation that occurs within the human brain to obtain new knowledge as the time passes and makes the knowledge to become newer. Based on this phenomenon, we have built an intelligent system called the Knowledge-Growing System (KGS). This approach is the basis for designing an agent that has ability to think and act rationally like a human, which is called the cognitive agent. Our cognitive modeling approach has resulted in a model of human information processing and a technique called Arwin-Adang-Aciek-Sembiring (A3S). This brain-inspired method opens a new perspective in AI known as cognitive artificial intelligence (CAI). CAI computation can be applied to various applications, namely: (1) knowledge extraction in an integrated information system, (2) probabilistic cognitive robot and coordination among autonomous agent systems, (3) human health detection, and (4) electrical instrument measurement. CAI provides a wide opportunity to yield various technologies and intelligent instrumentations as well as to encourage the development of cognitive science, which then encourages the intelligent systems approach to human intelligence

Development of a governance framework for delivery of collaborative and security-minded BIM projects

This study explores secure-collaboration for BIM projects in response to concerns as to whetherproject environments concerned with critical national infrastructure are able to govern digitalsecurity-risks whilst also reconciling tensions between collaborative motives, leading to difficultiesin sharing enough information to ensure stakeholder efficiency whilst not exposing sensitivitiesand elevating security-risk. This research aims to address these issues by: Devising a conceptualprocess and data governance framework to enable secure collaboration for BIM projects. Inachieving this aim, the study captures the framework’s requirements by answering the firstresearch question: What is the nature of tensions between collaboration and security motiveswithin security-minded BIM projects that are barriers to achieving secure-collaboration? Thisquestion’s answer is central to answering the second question: What is the nature of the processand data governance framework that is required to resolve existing tensions and enable securecollaboration?This thesis captures requirements via a thorough study (primary and secondary) in the contextof security-minded BIM projects. The design-science methodology was adopted to guide theframework development and evaluation; semi-structured interviews with 13 experts were used todiagnose the tensions concerning: security-risk governance, BIM process and technologyimplementation, alongside BIM governance limitations. Based upon findings, the framework’srequirements for comprising process and data governance concepts were developed. Theframework was evaluated with 8 experts via a qualitative feedback categorisation technique toassess its capacity to facilitate secure-collaboration.The outcome of the diagnostics process revealed that tensions arise within projects due to a lackof a holistic security-risk governance approach, and a misalignment between project collaborationand security requirements. This leads to a cascade of incompatible project implementationxviiichoices, which limits the efficacy of information governance to appropriately secure critical assets,whilst diminishing collaboration capacity to ensure a timely and cost-effective project-delivery.Stakeholders are also constrained by security-measures which are not integrated with theirinformational needs, resulting in issues such as securely coordinating sensitive informationamongst partners, or professionals being unable to access information due to inaccuratesensitivity classification and clearance constraints. These tensions are also linked to divergentcultural pressures for increased digitisation and openness, versus the need for security-mindedapproaches which are accompanied by administrative, commercial and contractual burdens.These tensions are the sources of great frustration within security-minded environmentsinterviewed in effortlessly achieving secure collaboration, whereas a bleaker picture is present forthe broader AEC sector as to whether organisations can support the secure digitisation needs ofinexperienced clients and protect their assets within an evolving digital security-risk landscape.Alleviating such tensions requires clients to apply holistic security-risk governance approachesand define integrated project requirements that reconcile security, collaboration and efficiencymotives. Findings also indicate that information-flow tensions are present for professionals to beable to seamlessly share and receive only the necessary information, when and to who necessary,at an appropriate and secured level of detail. Alleviating such tensions is difficult as they are tiedto the limitations of BIM-based governance approaches utilised within practices. To resolve suchinformation-flow tensions, findings propose that the key elements to be integrated into theprocess and data governance framework are considerations for information planning, transactionand governance concepts. At an overarching level, this is by ensuring practitioners securely shareand receive only the atomic information-sets which are necessary for them to deliver high-qualityproject outcomes. The proposed framework has been validated via a high-level qualitativetechnique as the framework is conceptual in nature. Therefore, future research is required toimplement and validate the framework in real-life project settings