scholarly journals Cold Start SI Passenger Car Emissions from Real World Urban Congested Traffic

2015 ◽  
Author(s):  
Ahmad Khalfan ◽  
Hu Li ◽  
Gordon Andrews
Keyword(s):  
Real World ◽  
Cold Start ◽  
Passenger Car ◽  
Congested Traffic

Characterization of Regulated and Unregulated Cold Start Emissions for Different Real World Urban Driving Cycles Using a SI Passenger Car

2008 ◽  
Author(s):  
Hu Li ◽  
Gordon E. Andrews ◽  
Dimitrios Savvidis ◽  
Basil Daham ◽  
Karl Ropkins ◽  
...  
Keyword(s):  
Real World ◽  
Cold Start ◽  
Passenger Car ◽  
Driving Cycles

The effectiveness of lane departure warning systems—A reduction in real-world passenger car injury crashes

2017 ◽  
Vol 18 (2) ◽  
pp. 225-229 ◽  
Author(s):  
Simon Sternlund ◽  
Johan Strandroth ◽  
Matteo Rizzi ◽  
Anders Lie ◽  
Claes Tingvall
Keyword(s):  
Real World ◽  
Warning Systems ◽  
Lane Departure Warning ◽  
Passenger Car ◽  
Lane Departure

Improving recommender systems’ performance on cold-start users and controversial items by a new similarity model

2016 ◽  
Vol 12 (2) ◽  
pp. 126-149 ◽  
Author(s):  
Masoud Mansoury ◽  
Mehdi Shajari
Keyword(s):  
Real World ◽  
Design Methodology ◽  
Cold Start ◽  
Selection Function ◽  
Data Sets ◽  
Real World Data ◽  
Content Type ◽  
User Similarity ◽  
Active User ◽  
Similarity Model

Purpose This paper aims to improve the recommendations performance for cold-start users and controversial items. Collaborative filtering (CF) generates recommendations on the basis of similarity between users. It uses the opinions of similar users to generate the recommendation for an active user. As a similarity model or a neighbor selection function is the key element for effectiveness of CF, many variations of CF are proposed. However, these methods are not very effective, especially for users who provide few ratings (i.e. cold-start users). Design/methodology/approach A new user similarity model is proposed that focuses on improving recommendations performance for cold-start users and controversial items. To show the validity of the authors’ similarity model, they conducted some experiments and showed the effectiveness of this model in calculating similarity values between users even when only few ratings are available. In addition, the authors applied their user similarity model to a recommender system and analyzed its results. Findings Experiments on two real-world data sets are implemented and compared with some other CF techniques. The results show that the authors’ approach outperforms previous CF techniques in coverage metric while preserves accuracy for cold-start users and controversial items. Originality/value In the proposed approach, the conditions in which CF is unable to generate accurate recommendations are addressed. These conditions affect CF performance adversely, especially in the cold-start users’ condition. The authors show that their similarity model overcomes CF weaknesses effectively and improve its performance even in the cold users’ condition.

scholarly journals Particulate emissions of a modern diesel passenger car under laboratory and real-world transient driving conditions

2020 ◽  
Vol 265 ◽  
pp. 114948 ◽  
Author(s):  
Hugo Wihersaari ◽  
Liisa Pirjola ◽  
Panu Karjalainen ◽  
Erkka Saukko ◽  
Heino Kuuluvainen ◽  
...  
Keyword(s):  
Real World ◽  
Particulate Emissions ◽  
Passenger Car ◽  
Driving Conditions

scholarly journals Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhao Li ◽  
Haobo Wang ◽  
Donghui Ding ◽  
Shichang Hu ◽  
Zhen Zhang ◽  
...  
Keyword(s):  
Real World ◽  
Contextual Information ◽  
Cold Start ◽  
Training Data ◽  
Learning To Learn ◽  
User Interests ◽  
Synthetic Datasets ◽  
Fresh Products ◽  
Embedding Performance ◽  
Deep Interest

Nowadays, people have an increasing interest in fresh products such as new shoes and cosmetics. To this end, an E-commerce platform Taobao launched a fresh-item hub page on the recommender system, with which customers can freely and exclusively explore and purchase fresh items, namely, the New Tendency page. In this work, we make a first attempt to tackle the fresh-item recommendation task with two major challenges. First, a fresh-item recommendation scenario usually faces the challenge that the training data are highly deficient due to low page views. In this paper, we propose a deep interest-shifting network (DisNet), which transfers knowledge from a huge number of auxiliary data and then shifts user interests with contextual information. Furthermore, three interpretable interest-shifting operators are introduced. Second, since the items are fresh, many of them have never been exposed to users, leading to a severe cold-start problem. Though this problem can be alleviated by knowledge transfer, we further babysit these fully cold-start items by a relational meta-Id-embedding generator (RM-IdEG). Specifically, it trains the item id embeddings in a learning-to-learn manner and integrates relational information for better embedding performance. We conducted comprehensive experiments on both synthetic datasets as well as a real-world dataset. Both DisNet and RM-IdEG significantly outperform state-of-the-art approaches, respectively. Empirical results clearly verify the effectiveness of the proposed techniques, which are arguably promising and scalable in real-world applications.

scholarly journals Real-world performance of catalytic converters

2005 ◽  
Vol 219 (7) ◽  
pp. 881-888 ◽  
Author(s):  
S Samuel ◽  
D Morrey ◽  
M Fowkes ◽  
D H C Taylor ◽  
C P Garner ◽  
...  
Keyword(s):  
United Kingdom ◽  
Real World ◽  
Systematic Approach ◽  
Catalytic Converters ◽  
Passenger Vehicle ◽  
Passenger Car ◽  
The Real ◽  
The United Kingdom ◽  
Light Duty ◽  
Car Driving

This paper investigates experimentally the performance of a three-way catalytic (TWC) converter for real-world passenger car driving in the United Kingdom. A systematic approach is followed for the analysis using a Euro-IV vehicle coupled with a TWC converter. The analysis shows that the real-world performance of TWC converters is significantly different from the performance established on legislative test cycles. It is identified that a light-duty passenger vehicle certified for Euro-IV emissions reaches the gross polluting threshold limits during real-world driving conditions. This result is shown to have implications for overall emission levels and the use of remote emissions sensing and on-board diagnostics (OBD) systems.

Real-world driving speciated VOC hot start emissions of the 2001 French passenger car fleet

2001 ◽  
Vol 27 (1/2/3/4) ◽  
pp. 140 ◽  
Author(s):  
Yannick Flandrin ◽  
Robert Vidon ◽  
Fabrice Cazier ◽  
Stephanie Hue ◽  
Jean Claude Dechaux ◽  
...  
Keyword(s):  
Real World ◽  
Passenger Car ◽  
Hot Start
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