Impact of Cold Climates on Vehicle Emissions: The Cold Start Air Toxics Pulse

This project measured cold start emissions from four vehicles in winter using fast response instrumentation to accurately measure the time variation of the cold start emission pulse. Seventeen successful tests were conducted over a temperature range of -4°C to 10°C in winter 2015 at the Washington State University campus. Vehicle cold starts are thought to be a significant source of air toxic compounds in cold winter environments due to the rapid increase in mass emission rates with decreasing temperature. We used a proton transfer reaction mass spectrometer for high time resolution measurement of the emissions the air toxic compounds benzene, formaldehyde, acetaldehyde, in addition to toluene and C2-alkylbenzenes. Measured molar emission ratios relative to toluene in the cold start pulse were compared with cold start emission profiles for E10 fueled vehicles used in the EPA MOVES2014 model. We found that the measured acetaldehyde-to-toluene emission ratio was about a factor of 8 greater than the emission ratio used in MOVES2014. Measured formaldehyde-to-toluene emission ratios were a factor of 5 greater. Our study suggests that emission of the air toxics acetaldehyde and, likely, formaldehyde is significantly underestimated in wintertime by the MOVES2014 model

COMPETITIVE-SEARCH EQUILIBRIUM IN MONETARY ECONOMIES

This is a comment on the work of Rocheteau and Wright (2005) who have recently introduced competitive search into monetary economics. We extend their work by eliminating the restriction that the fees market makers charge to enter a submarket must be either non-negative or identical for buyers and sellers. Without this restriction, buyers pay a positive fee to enter the submarket they visit and nothing else when they meet a seller. Sellers are remunerated by the market makers from the entry fees collected from the buyers. This trading arrangement allows buyers to perfectly predict their expenses, so the opportunity cost of holding idle money balances is eliminated.competitive search, monetary search.

A Comparative Study of Productivity and Quality Gain Between Post-Editing and Translating From Scratch

Using machine translation (MT) input represents a fundamental change in translators’ work mode. The issue of efficacy of MT uses is worth investigating since it is at the heart of understanding translators’ choices in post-editing MT results or translating from scratch. This study focuses on a comparative study of the impact of post-editing MT on productivity and translation quality of student translator subjects with different levels of translation experiences. This study also looks into the influence of translators’ translation experiences on their performances. The keylogging experiment results show that MT input contributes positively to productivity gain and time savings with some variations caused by translation experiences, and that the overall final text quality is significantly affected when translating with or without MT input though to a varying degree of quality gain. These findings suggest a positive role of post-editing MT in translator training

IMPROVING THE PERFORMANCE AND TIME-PREDICTABILITY OF GPUs

Graphic Processing Units (GPUs) are originally mainly designed to accelerate graphic applications. Now the capability of GPUs to accelerate applications that can be parallelized into a massive number of threads makes GPUs the ideal accelerator for boosting the performance of such kind of general-purpose applications. Meanwhile it is also very promising to apply GPUs to embedded and real-time applications as well, where high throughput and intensive computation are also needed. However, due to the different architecture and programming model of GPUs, how to fully utilize the advanced architectural features of GPUs to boost the performance and how to analyze the worst-case execution time (WCET) of GPU applications are the problems that need to be addressed before exploiting GPUs further in embedded and real-time applications. We propose to apply both architectural modification and static analysis methods to address these problems. First, we propose to study the GPU cache behavior and use bypassing to reduce unnecessary memory traffic and to improve the performance. The results show that the proposed bypassing method can reduce the global memory traffic by about 22% and improve the performance by about 13% on average. Second, we propose a cache access reordering framework based on both architectural extension and static analysis to improve the predictability of GPU L1 data caches. The evaluation results show that the proposed method can provide good predictability in GPU L1 data caches, while allowing the dynamic warp scheduling for good performance. Third, based on the analysis of the architecture and dynamic behavior of GPUs, we propose a WCET timing model based on a predictable warp scheduling policy to enable the WCET estimation on GPUs. The experimental results show that the proposed WCET analyzer can effectively provide WCET estimations for both soft and hard real-time application purposes. Last, we propose to analyze the shared Last Level Cache (LLC) in integrated CPU-GPU architectures and to integrate the analysis of the shared LLC into the WCET analysis of the GPU kernels in such systems. The results show that the proposed shared data LLC analysis method can improve the accuracy of the shared LLC miss rate estimations, which can further improve the WCET estimations of the GPU kernels