Distributed fuzzy logic for building management systems using local operating networks

This paper describes the development of an experimental distributed fuzzy control system for heating and ventilation (HVAC) systems within a building. Each local control loop is affected by a number of local variables, as well as information from neighboring controllers. By including this additional information it is hoped that a more equal allocation of resources can be achieved.

Modeling the tetraphenylalanine-PEG hybrid amphiphile: from DFT calculations on the peptide to molecular dynamics simulations on the conjugate

The conformational properties of the hybrid amphiphile formed by the conjugation of a hydrophobic peptide with four phenylalanine (Phe) residues and hydrophilic poly(ethylene glycol), have been investigated using quantum mechanical calculations and atomistic molecular dynamics simulations. The intrinsic conformational preferences of the peptide were examined using the building-up search procedure combined with B3LYP/ 6-31G(d) geometry optimizations, which led to the identification of 78, 78, and 92 minimum energy structures for the peptides containing one, two, and four Phe residues. These peptides tend to adopt regular organizations involving turn-like motifs that define ribbon or helicallike arrangements. Furthermore, calculations indicate that backbone ... side chain interactions involving the N-H of the amide groups and the pi clouds of the aromatic rings play a crucial role in Phe-containing peptides. On the other hand,MD simulations on the complete amphiphile in aqueous solution showed that the polymer fragment rapidly unfolds maximizing the contacts with the polar solvent, even though the hydrophobic peptide reduce the number of waters of hydration with respect to an individual polymer chain of equivalent molecular weight. In spite of the small effect of the peptide in the hydrodynamic properties of the polymer, we conclude that the two counterparts of the amphiphile tend to organize as independent modules.

Hyperresolution global land surface modeling: meeting a grand challenge for monitoring Earth's terrestrial water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

A data framework for measuring the energy consumption of the non-domestic building stock

The transition to a low-carbon economy urgently demands better information on the drivers of energy consumption. UK government policy has prioritized energy efficiency in the built stock as a means of carbon reduction, but the sector is historically information poor, particularly the non-domestic building stock. This paper presents the results of a pilot study that investigated whether and how property and energy consumption data might be combined for non-domestic energy analysis. These data were combined in a ‘Non-Domestic Energy Efficiency Database’ to describe the location and physical attributes of each property and its energy consumption. The aim was to support the generation of a range of energy-efficiency statistics for the industrial, commercial and institutional sectors of the non-domestic building stock, and to provide robust evidence for national energy-efficiency and carbon-reduction policy development and monitoring. The work has brought together non-domestic energy data, property data and mapping in a ‘data framework’ for the first time. The results show what is possible when these data are integrated and the associated difficulties. A data framework offers the potential to inform energy-efficiency policy formation and to support its monitoring at a level of detail not previously possible.

Decision making for HVAC&R system selection for a typical office building in the UK

Demands for thermal comfort, better indoor air quality together with lower environmental impacts have had ascending trends in the last decade. In many circumstances, these demands could not be fully covered through the soft approach of bioclimatic design like optimisation of the building orientation and internal layout. This is mostly because of the dense urban environment and building internal energy loads. In such cases, heating, ventilation, air-conditioning and refrigeration (HVAC&R) systems make a key role to fulfill the requirements of indoor environment. Therefore, it is required to select the most proper HVAC&R system. In this study, a robust decision making approach for HVAC&R system selection is proposed. Technical performance, economic aspect and environmental impacts of 36 permutations of primary and secondary systems are taken into account to choose the most proper HVAC&R system for a case study office building. The building is a representative for the dominant form of office buildings in the UK. Dynamic performance evaluation of HVAC&R alternatives using TRNSYS package together with life cycle energy cost analysis provides a reliable basis for decision making. Six scenarios broadly cover the decision makers' attitudes on HVAC&R system selection which are analysed through Analytical Hierarchy Process (AHP). One of the significant outcomes reveals that, despite both the higher energy demand and more investment requirements associated with compound heating, cooling and power system (CCHP); this system is one of the top ranked alternatives due to the lower energy cost and C02 emissions. The sensitivity analysis reveals that in all six scenarios, the first five top ranked alternatives are not changed. Finally, the proposed approach and the results could be used by researchers and designers especially in the early stages of a design process in which all involved bodies face the lack of time, information and tools for evaluation of a variety of systems.

A holistic method to assess building energy efficiency combining D-S theory and the evidential reasoning approach

The assessment of building energy efficiency is one of the most effective measures for reducing building energy consumption. This paper proposes a holistic method (HMEEB) for assessing and certifying building energy efficiency based on the D-S (Dempster-Shafer) theory of evidence and the Evidential Reasoning (ER) approach. HMEEB has three main features: (i) it provides both a method to assess and certify building energy efficiency, and exists as an analytical tool to identify improvement opportunities; (ii) it combines a wealth of information on building energy efficiency assessment, including identification of indicators and a weighting mechanism; and (iii) it provides a method to identify and deal with inherent uncertainties within the assessment procedure. This paper demonstrates the robustness, flexibility and effectiveness of the proposed method, using two examples to assess the energy efficiency of two residential buildings, both located in the ‘Hot Summer and Cold Winter’ zone in China. The proposed certification method provides detailed recommendations for policymakers in the context of carbon emission reduction targets and promoting energy efficiency in the built environment. The method is transferable to other countries and regions, using an indicator weighting system to modify local climatic, economic and social factors.

Building energy efficiency for sustainable development in China: challenges and opportunities

Rapid urbanisation in China has resulted in great demands for energy, resources and pressure on the environment. The progress in China's development is considered in the context of energy efficiency in the built environment, including policy, technology and implementation. The key research challenges and opportunities are identified for delivering a low carbon built environment. The barriers include the existing traditional sequential design process, the lack of integrated approaches, and insufficient socio-technical knowledge. A proposed conceptual systemic model of an integrated approach identifies research opportunities. The organisation of research activities should be initiated, operated, and managed in a collaborative way among policy makers, professionals, researchers and stakeholders. More emphasis is needed on integrating social, economic and environmental impacts in the short, medium and long terms. An ideal opportunity exists for China to develop its own expertise, not merely in a technical sense but in terms of vision and intellectual leadership in order to flourish in global collaborations.

Does regional infrastructure investment stimulate extra housing and commercial building supply? Long-run evidence across the English regions

This paper uses long-term regional construction data to investigate whether increases infrastructure investment in the English regions leads to subsequent rises in housebuilding and new commercial property, using time series modeling. Both physical (roads and harbours) and social infrastructure (education and health) impacts are investigated across nine regions in England. Significant effects for physical infrastructure are found across most regions and, also, some evidence of a social infrastructure effect. The results are not consistent across regions, which may be due to geographical differences and to network and diversionary effects. However, the results do suggest that infrastructure does have some impact but follows differential lag structures. These results provide a test of the hypothesis of the economic benefits of infrastructure investment in an approach that has not been used before.

Building communities: reducing energy use in tenanted commercial property

Reducing energy use in tenanted commercial property requires a greater understanding of ‘buildings as communities’. Tenanted commercial properties represent: (1) the divergent communities that share specific buildings; and (2) the organizational communities represented by multi-site landlord and tenant companies. In any particular tenanted space the opportunity for environmental change is mediated (hindered or enabled) through the lease. This discussion draws on theoretical and practical understandings of (1) the socio-legal relationships of landlords, tenants and their advisors; (2) the real performance of engineering building services strategies to improve energy efficiency; (3) how organizational cultures affect the ability of the sector to engage with energy-efficiency strategies; and (4) the financial and economic basis of the relationship between owners and occupiers. The transformational complexity stems from: (1) the variety of commercial building stock; (2) the number of stakeholders (solicitors, investors, developers, agents, owners, tenants and facilities managers); (3) the fragmentation within the communities of practice; and (4) leasehold structures and language. An agenda is proposed for truly interdisciplinary research that brings together both the physical and the social sciences of energy use in buildings so that technological solutions are made effective by an understanding of the way that buildings are used and communities behave.

Skilloscopy: Bayesian modeling of decision makers' skill

This paper proposes and demonstrates an approach, Skilloscopy, to the assessment of decision makers. In an increasingly sophisticated, connected and information-rich world, decision making is becoming both more important and more difficult. At the same time, modelling decision-making on computers is becoming more feasible and of interest, partly because the information-input to those decisions is increasingly on record. The aims of Skilloscopy are to rate and rank decision makers in a domain relative to each other: the aims do not include an analysis of why a decision is wrong or suboptimal, nor the modelling of the underlying cognitive process of making the decisions. In the proposed method a decision-maker is characterised by a probability distribution of their competence in choosing among quantifiable alternatives. This probability distribution is derived by classic Bayesian inference from a combination of prior belief and the evidence of the decisions. Thus, decision-makers’ skills may be better compared, rated and ranked. The proposed method is applied and evaluated in the gamedomain of Chess. A large set of games by players across a broad range of the World Chess Federation (FIDE) Elo ratings has been used to infer the distribution of players’ rating directly from the moves they play rather than from game outcomes. Demonstration applications address questions frequently asked by the Chess community regarding the stability of the Elo rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The method of Skilloscopy may be applied in any decision domain where the value of the decision-options can be quantified.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

A conceptual framework for aligning business and information systems from organisational learning perspective

The three decades of on-going executives’ concerns of how to achieve successful alignment between business and information technology shows the complexity of such a vital process. Most of the challenges of alignment are related to knowledge and organisational change and several researchers have introduced a number of mechanisms to address some of these challenges. However, these mechanisms pay less attention to multi-level effects, which results in a limited un-derstanding of alignment across levels. Therefore, we reviewed these challenges from a multi-level learning perspective and found that business and IT alignment is related to the balance of exploitation and exploration strategies with the intellec-tual content of individual, group and organisational levels.

Modeling requirement driven architecture of adaptive healthcare system based on semiotics

In order to improve the quality of healthcare services, the integrated large-scale medical information system is needed to adapt to the changing medical environment. In this paper, we propose a requirement driven architecture of healthcare information system with hierarchical architecture. The system operates through the mapping mechanism between these layers and thus can organize functions dynamically adapting to user’s requirement. Furthermore, we introduce the organizational semiotics methods to capture and analyze user’s requirement through ontology chart and norms. Based on these results, the structure of user’s requirement pattern (URP) is established as the driven factor of our system. Our research makes a contribution to design architecture of healthcare system which can adapt to the changing medical environment.

Building climate resilience: lessons of early warning in Africa

Given the high levels of uncertainty and substantial variability in local weather and climate, what constitutes successful adaptation for the 800 million food-insecure people in Africa? In this context there is a need for building climate resilience through effective early warning systems, bringing real-time monitoring and decision-making together with stakeholders. The chapter presents two effective operational early warning systems in Africa: The Radio and Internet (RANET) network and the Rainwatch project. These examples were developed in partnership with local climate scientists and tailored to local development needs, enabled and encouraged with only modest international support. They deliver important lessons about how to prepare for crises using simple real-time monitoring. They also help us identify characteristics of managing for resilience in practice. The chapter concludes that successful adaptation requires adaptive, flexible, linked institutions, together with ground-based collaboration and practical tools. In the context of early warning three features stand out that make these systems successful: effective communication of current weather and climate information, a key individual within a bridging organization with the ability to navigate the governance systems, and sufficient time for innovation development.