Tareq Z. Ahram

Collaborative systems engineering and social-networking approach to design and modelling of smarter products

Employing systems engineering (SE) methodology and principles to the development of smart products has the potential of establishing a novel field of research. This paper summarises previous work in this area in order to define and characterise a revolutionary SE and social-networking framework for collaborative education, design and modelling of the next generation of smarter products. A conceptual framework and practical applications of SE approaches and social networking to support smarter product development is proposed. Future challenges that collaborative SE and interactive social networking techniques are likely to face in this domain are also discussed.

Interactive Management of Human Factors Knowledge for Human Systems Integration Using Systems Modeling Language

Abstract The field of Human Factors in Knowledge Management is often seen as a problem of capturing, organizing, and retrieving information to build knowledge. This process is inextricably bound up with human cognition and, as such, the management of knowledge occurs within an intricately structured behavioral, cultural, and social context. This paper emphasizes the importance of interactive human factors in knowledge management and introduces a model-based human systems integration framework based on systems modeling language (SysML).

Investigating the relationship between adverse events and infrastructure development in an active war theater using soft computing techniques

We investigate the relationship between adverse events and infrastructure development investments in an active war theater.We develop soft computing techniques (ANN, FIS, and ANFIS) for estimating the number of adverse events based on the occurrence of economic improvement projects.The performance of each model was investigated and compared to all other models using the calculated mean absolute percentage error (MAPE) values.When the model accuracy was calculated based on the MAPE for each of the models, ANN had better predictive accuracy than FIS and ANFIS models, as demonstrated by experimental results.The sensitivity analysis results show that the importance of economic development projects varied based on the specific regions and time period. The purpose of this paper is to investigate the relationship between adverse events and infrastructure development investments in an active war theater by using soft computing techniques including fuzzy inference systems (FIS), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFIS) where the accuracy of the predictions is directly beneficial from an economic and humanistic point of view. Fourteen developmental and economic improvement projects were selected as independent variables. A total of four outputs reflecting the adverse events in terms of the number of people killed, wounded or hijacked, and the total number of adverse events has been estimated.The results obtained from analysis and testing demonstrate that ANN, FIS, and ANFIS are useful modeling techniques for predicting the number of adverse events based on historical development or economic project data. When the model accuracy was calculated based on the mean absolute percentage error (MAPE) for each of the models, ANN had better predictive accuracy than FIS and ANFIS models, as demonstrated by experimental results. For the purpose of allocating resources and developing regions, the results can be summarized by examining the relationship between adverse events and infrastructure development in an active war theater, with emphasis on predicting the occurrence of events. We conclude that the importance of infrastructure development projects varied based on the specific regions and time period.

User-centered systems engineering approach to design and modeling of smarter products

Employing user-centered design principles along with systems engineering methodology to the development of smarter products has the potential of establishing a novel field of research. This paper introduces a novel user-centered human factors knowledge management framework for collaborative design and modeling of the next generation of smarter products. A conceptual framework and practical application of user-centered systems engineering approach to support smarter product development is proposed. The human systems component in collaborative systems engineering aims to ensure that human considerations, for users and designers, have a prominent place in the integrated design and development of sustainable smarter products throughout the total system lifecycle [12]. Future challenges that collaborative user-centered systems engineering techniques are likely to face in this domain are also discussed.

Estimating intrinsic dimensionality using the multi-criteria decision weighted model and the average standard estimator

Information retrieval today is much more challenging than traditional small document retrieval. The main difference is the importance of correlations between related concepts in complex data structures. As collections of data grow and contain more entries, they require more complex relationships, links, and groupings between individual entries. This paper introduces two novel methods for estimating data intrinsic dimensionality based on the singular value decomposition (SVD). The average standard estimator (ASE) and the multi-criteria decision weighted model are used to estimate matrix intrinsic dimensionality for large document collections. The multi-criteria weighted model calculates the sum of weighted values of matrix dimensions which demonstrated best performance using all possible dimensions [1]. ASE estimates the level of significance for singular values that resulted from the singular value decomposition. ASE assumes that those variables with deep relations have sufficient correlation and that only those relationships with high singular values are significant and should be maintained [1]. Experimental results indicate that ASE improves precision and relative relevance for MEDLINE document collection by 10.2% and 12.9% respectively compared to the percentage of variance dimensionality estimation. Results based on testing three document collections over all possible dimensions using selected performance measures indicate that ASE improved matrix intrinsic dimensionality estimation by including the effect of both singular values magnitude of decrease and random noise distracters. The multi-criteria weighted model with dimensionality reduction provides a more efficient implementation for information retrieval than using a full rank model.

Social networking applications: smarter product design for complex human behaviour modeling

The advent and adoption of internet-based social networking has significantly altered our daily lives. The educational community has taken notice of the positive aspects of social networking such as creation of blogs and to support groups of system designers going through the same challenges and difficulties. This paper introduces a social networking framework for collaborative education, design and modeling of the next generation of smarter products and services. Human behaviour modeling in social networking application aims to ensure that human considerations for learners and designers have a prominent place in the integrated design and development of sustainable, smarter products throughout the total system lifecycle. Social networks blend self-directed learning and prescribed, existing information. The self-directed element creates interest within a learner and the ability to access existing information facilitates its transfer, and eventual retention of knowledge acquired.

Blockchain technology innovations

Digital world has produced efficiencies, new innovative products, and close customer relationships globally by the effective use of mobile, IoT (Internet of Things), social media, analytics and cloud technology to generate models for better decisions. Blockchain is recently introduced and revolutionizing the digital world bringing a new perspective to security, resiliency and efficiency of systems. While initially popularized by Bitcoin, Blockchain is much more than a foundation for crypto currency. It offers a secure way to exchange any kind of good, service, or transaction. Industrial growth increasingly depends on trusted partnerships; but increasing regulation, cybercrime and fraud are inhibiting expansion. To address these challenges, Blockchain will enable more agile value chains, faster product innovations, closer customer relationships, and quicker integration with the IoT and cloud technology. Further Blockchain provides a lower cost of trade with a trusted contract monitored without intervention from third parties who may not add direct value. It facilitates smart contracts, engagements, and agreements with inherent, robust cyber security features. This paper is an effort to break the ground for presenting and demonstrating the use of Blockchain technology in multiple industrial applications. A healthcare industry application, Healthchain, is formalized and developed on the foundation of Blockchain using IBM Blockchain initiative. The concepts are transferable to a wide range of industries as finance, government and manufacturing where security, scalability and efficiency must meet.

Economics of human performance and systems total ownership cost

Financial costs of investing in people is associated with training, acquisition, recruiting, and resolving human errors have a significant impact on increased total ownership costs. These costs can also affect the exaggerate budgets and delayed schedules. The study of human performance economical assessment in the system acquisition process enhances the visibility of hidden cost drivers which support program management informed decisions. This paper presents the literature review of human total ownership cost (HTOC) and cost impacts on overall system performance. Economic value assessment models such as cost benefit analysis, risk-cost tradeoff analysis, expected value of utility function analysis (EV), growth readiness matrix, multi-attribute utility technique, and multi-regressions model were introduced to reflect the HTOC and human performance-technology tradeoffs in terms of the dollar value. The human total ownership regression model introduces to address the influencing human performance cost component measurement. Results from this study will increase understanding of relevant cost drivers in the system acquisition process over the long term.

User-centered Systems Engineering & Knowledge Management Framework for Design & Modeling of Future Smart Cities

Employing human factors and user-centered systems engineering methodology and design principles to the development of smart cities has the potential of establishing a novel field of research. This paper introduces a novel human factors knowledge management framework for collaborative education, design and modeling of the next generation of smarter cities. A conceptual framework and practical applications of systems engineering approaches to support smarter cities development is proposed. The human systems component in collaborative systems engineering aims to ensure that human considerations for learners and designers have a prominent place in the integrated design and development of sustainable, smarter cities throughout the total system lifecycle. Future challenges that collaborative human and systems engineering techniques are likely to face in this domain are also discussed.

Applications of agent-based simulation for human socio-cultural behavior modeling

Agent-based modeling and simulation (ABMS) has gained wide attention over the past few years. ABMS is a powerful simulation modeling technique that has a number of applications, including applications to real-world business problems [1]. This modeling technique has been used by scientists to analyze complex system-level behavior by simulating the system from the bottom up. The major application of ABMS includes social, political, biology, and economic sciences. This paper provides an overview of ABMS applications with the emphasis on modeling human socio-cultural behavior (HSCB).