Studying Software Engineering Patterns for Designing Machine Learning Systems

Machine-learning (ML) techniques have become popular in the recent years. ML techniques rely on mathematics and on software engineering. Researchers and practitioners studying best practices for designing ML application systems and software to address the software complexity and quality of ML techniques. Such design practices are often formalized as architecture patterns and design patterns by encapsulating reusable solutions to commonly occurring problems within given contexts. However, to the best of our knowledge, there has been no work collecting, classifying, and discussing these software-engineering (SE) design patterns for ML techniques systematically. Thus, we set out to collect good/bad SE design patterns for ML techniques to provide developers with a comprehensive and ordered classification of such patterns. We report here preliminary results of a systematic-literature review (SLR) of good/bad design patterns for ML

Designing and Implementing Embodied Agents: Learning from Experience

In this paper, we provide an overview of part of our experience in designing and implementing some of the embodied agents and talking faces that we have used for our research into human computer interaction. We focus on the techniques that were used and evaluate this with respect to the purpose that the agents and faces were to serve and the costs involved in producing and maintaining the software. We discuss the function of this research and development in relation to the educational programme of our graduate students

Business Process Innovation using the Process Innovation Laboratory

Most organizations today are required not only to establish effective business processes but they are required to accommodate for changing business conditions at an increasing rate. Many business processes extend beyond the boundary of the enterprise into the supply chain and the information infrastructure therefore is critical. Today nearly every business relies on their Enterprise System (ES) for process integration and the future generations of enterprise systems will increasingly be driven by business process models. Consequently process modeling and improvement will become vital for business process innovation (BPI) in future organizations. There is a significant body of knowledge on various aspect of process innovation, e.g. on conceptual modeling, business processes, supply chains and enterprise systems. Still an overall comprehensive and consistent theoretical framework with guidelines for practical applications has not been identified. The aim of this paper is to establish a conceptual framework for business process innovation in the supply chain based on advanced enterprise systems. The main approach to business process innovation in this context is to create a new methodology for exploring process models and patterns of applications. The paper thus presents a new concept for business process innovation called the process innovation laboratory a.k.a. the Ð-Lab. The Ð-Lab is a comprehensive framework for BPI using advanced enterprise systems. The Ð-Lab is a collaborative workspace for experimenting with process models and an explorative approach to study integrated modeling in a controlled environment. The Ð-Lab facilitates innovation by using an integrated action learning approach to process modeling including contemporary technological, organizational and business perspectivesNo; keywords

Optimization of stand-alone photovoltaic system by implementing fuzzy logic MPPT controller

A photovoltaic (PV) generator is a nonlinear device having insolation-dependent volt-ampere characteristics. Since the maximum-power point varies with solar insolation, it is difficult to achieve an optimum matching that is valid for all insolation levels. Thus, Maximum power point tracking (MPPT) plays an important roles in photovoltaic (PV) power systems because it maximize the power output from a PV system for a given set of condition, and therefore maximize their array efficiency. This project presents a maximum power point tracker (MPPT) using Fuzzy Logic theory for a PV system. The work is focused on a comparative study between most conventional controller namely Perturb and Observe (P&O) algorithm and is compared to a design fuzzy logic controller (FLC). The introduction of fuzzy controller has given very good performance on whatever the parametric variation of the system