The Helsinki Office Environment Study: Air Change in Mechanically Ventilated Buildings

Abstract The objective of this study was to assess the magnitude and balance of mechanical ventilation in the rooms of Helsinki metropolitan office buildings with different types of ventilation systems. A random sample of 50 office buildings was selected from the Building Registry. Of these buildings, the 33 that have a mechanical ventilation system were included in this study. Most office buildings in the Helsinki metropolitan area have a ducted supply and exhaust system and hot water radiator heating. Air recirculation is used in about half of the buildings which have a mechanical supply and exhaust system. The average exhaust airflow was 1.2 L/s, m² (SD 0.73) or 17.2 L/s per person (SD 11.6). The variation of the airflows was found to be very high among the buildings, and among the rooms within the buildings. Therefore, even though the ventilation rates on average comply with the Finnish building code, it was found that many people were working in offices with airflows which were either too low or unnecessarily high.     

REPLICA MBTAC: multithreaded dual-mode processor

Prevailing trend in design of chip multiprocessors (CMP) has been that single-core processors are replicated. Therefore, they typically define asynchronous computational model, require heavily locality-aware memory allocation, and present high overheads in intercommunication. This kind of properties make parallel programming very challenging and prone to errors. We introduce our new dual-mode MultiBunched/Threaded Architecture with Chaining (MBTAC) processor core, the main building block of the REPLICA CMP. It provides a modern, sophisticated way for writing general purpose parallel programs backed up by native execution capabilities/realization of key concepts. These include support for cost-efficient machine instruction-level synchronization and uniform shared global memory for enabling easy-to-program memory allocation of data structures and data movement. MBTAC makes use of low-overhead thread-context switching solution; it has parallel computing savvy functional unit organization to exploit inter-thread instruction-level parallelism and highly efficient multioperations. To evaluate the goodness of our proposal, we implemented three MBTAC constellations featuring up to 2048 parallel threads on FPGA, compared it with respect to DLX and Intel’s Core i7 processors. The results point toward high performance in communication-intensive problems, simplified parallel programmability, and regular, implementation-friendly structure.     

Performance and programmability comparison of the thick control flow architecture and current multicore processors

The Journal of Supercomputing - Commercial multicore central processing units (CPU) integrate a number of processor cores on a single chip to support parallel execution of computational tasks....     

On the cosimulation of multibody systems and hydraulic dynamics

Multibody System Dynamics - The simulation of mechanical devices using multibody system dynamics (MBS) algorithms frequently requires the consideration of their interaction with components of a...     

Using regression makes extraction of shared variation in multiple datasets easy

In many data analysis tasks it is important to understand the relationships between different datasets. Several methods exist for this task but many of them are limited to two datasets and linear relationships. In this paper, we propose a new efficient algorithm, termed cocoreg, for the extraction of variation common to all datasets in a given collection of arbitrary size. cocoreg extends redundancy analysis to more than two datasets, utilizing chains of regression functions to extract the shared variation in the original data space. The algorithm can be used with any linear or non-linear regression function, which makes it robust, straightforward, fast, and easy to implement and use. We empirically demonstrate the efficacy of shared variation extraction using the cocoreg algorithm on five artificial and three real datasets.     

Novel Packet Switching for Green IP Networks

A green technology for reducing energy consumption has become a critical factor in ICT industries. However, for the telecommunications sector in particular, most network elements are not usually optimized for power efficiency. Here, we propose a novel energy‐efficient packet switching method for use in an IP network for reducing unnecessary energy consumption. As a green networking approach, we first classify the network nodes into either header or member nodes. The member nodes then put the routing‐related module at layer 3 to sleep under the assumption that the layer in the OSI model can operate independently. The entire set of network nodes is then partitioned into clusters consisting of one header node and multiple member nodes. Then, only the header node in a cluster conducts IP routing and its member nodes conduct packet switching using a specially designed identifier, a tag. To investigate the impact of the proposed scheme, we conducted a number of simulations using well‐known real network topologies and achieved a more energy‐ efficient performance than that achieved in previous studies.     

Wastewater treatment: New insight provided by interactive multiobjective optimization

In this paper, we describe a new interactive tool developed for wastewater treatment plant design. The tool is aimed at supporting the designer in designing new wastewater treatment plants as well as optimizing the performance of already available plants. The idea is to utilize interactive multiobjective optimization which enables the designer to consider the design with respect to several conflicting evaluation criteria simultaneously. This is more important than ever because the requirements for wastewater treatment plants are getting tighter and tighter from both environmental and economical reasons. By combining a process simulator to simulate wastewater treatment and an interactive multiobjective optimization software to aid the designer during the design process, we obtain a practically useful tool for decision support. The applicability of our tool is illustrated with a case study related to municipal wastewater treatment where three conflicting evaluation criteria are considered.     

Seasonality: Nature,People's Preferences and Urban Planning in Oulunsalo,Finland

Seasonal changes are particularly strong in northern Europe. Daylight, temperature, flora, fauna and landscape change from day to day. We discuss how seasonality exists in nature, is felt by people and is reflected in urban planning. The case study regards Oulunsalo municipality with a population of 9,000 at the northern most Baltic Sea coast in Finland. In 2003 the mean temperature of the coldest month in Oulunsalo was ?16.4 and the warmest +19.5 centigrade. The longest day was 22 hours 3 minutes and the shortest 3 hours and 35 minutes. A survey among the adult Oulunsalo population shows that summer is the best season for the majority of people (72%)—more often for men (78%) than for women (66%). Almost everybody (96%) likes the change of seasons. Seasons and seasonal preferences should be considered more in urban planning processes and land-use plans.     

Genetic programming through bi-objective genetic algorithms with a study of a simulated moving bed process involving multiple objectives

A new bi-objective genetic programming (BioGP) technique has been developed for meta-modeling and applied in a chromatographic separation process using a simulated moving bed (SMB) process. The BioGP technique initially minimizes training error through a single objective optimization procedure and then a trade-off between complexity and accuracy is worked out through a genetic algorithm based bi-objective optimization strategy. A benefit of the BioGP approach is that an expert user or a decision maker (DM) can flexibly select the mathematical operations involved to construct a meta-model of desired complexity or accuracy. It is also designed to combat bloat – a perennial problem in genetic programming along with over fitting and under fitting problems. In this study the meta-models constructed for SMB reactors were compared with those obtained from an evolutionary neural network (EvoNN) developed earlier and also with a polynomial regression model. Both BioGP and EvoNN were compared for subsequent constrained bi-objective optimization studies for the SMB reactor involving four objectives. The results were also compared with the previous work in the literature. The BioGP technique produced acceptable results and is now ready for data-driven modeling and optimization studies at large.     

Free-field characterization via directional transmission through a nanoaperture

We propose a scheme based on extraordinary transmission of light through a single nanoaperture, surrounded by periodic corrugations, for direct characterization of focal-region optical fields with subwavelength-scale structure. We describe the design of the device on the basis of rigorous diffraction theory and fabricate a prototype using a process that involves electron beam lithography, dry etching, and template stripping. First experimental results performed with a transmission-type confocal optical microscope demonstrate the potential of the method.