scholarly journals Transportation Energy Analytics Dashboard (TEAD)

2021 ◽  
Author(s):  
Mark Franz ◽  
◽  
Michael Pack ◽  
Stanley Young ◽  
Jacob Holden ◽  
...  
Keyword(s):  
Transportation Energy ◽  
Energy Analytics

Joint DOE/NRCan study of North American transportation energy futures: Discussion of the study, presentation of Phase 2 results

2003 ◽  
Author(s):  
Philip Patterson ◽  
David Greene ◽  
Elyse Steiner ◽  
Steve Plotkin ◽  
Margaret Singh ◽  
...  
Keyword(s):  
North American ◽  
Phase 2 ◽  
Transportation Energy ◽  
Energy Futures

scholarly journals Detection of metal ions in biological systems: A review

2020 ◽  
Vol 39 (1) ◽  
pp. 231-246 ◽  
Author(s):  
Xian Zheng ◽  
Wenyu Cheng ◽  
Chendong Ji ◽  
Jin Zhang ◽  
Meizhen Yin
Keyword(s):  
Metal Ions ◽  
Metal Ion ◽  
Metabolic Regulation ◽  
Organic Dyes ◽  
Biological Systems ◽  
High Sensitivity ◽  
Transportation Energy ◽  
Material Transportation ◽  
High Fluorescence ◽  
Metal Ion Detection

Abstract Metal ions are widely present in biological systems and participate in many critical biochemical processes such as material transportation, energy conversion, information transmission and metabolic regulation, making them indispensable substance in our body. They can cause health problems when deficiency or excess occurs. To understand various metabolic processes and facilitate diseases diagnosis, it is very important to measure the content and monitor the distribution of metal ions in individual cells, tissues and whole organisms. Among the various methods for metal ion detection, fluorescent sensors with organic dyes have attracted tremendous attention due to many advantages such as high fluorescence quantum yield, facile modification approaches and biocompatibility in addition to operation ease, high sensitivity, fast detection speed, and real-time detection. This review summarizes the recent progress on the detection and imaging of the metal ions in biological systems including Na+, K+, Ca2+, Mg2+, Fe2+/Fe3+, Zn2+, and Cu2+ provides an opinion on remaining challenges to be addressed in this field.

Prediction of transportation energy demand: Multivariate Adaptive Regression Splines

Energy ◽  
2021 ◽  
Vol 224 ◽  
pp. 120090
Author(s):  
Mohammad Ali Sahraei ◽  
Hakan Duman ◽  
Muhammed Yasin Çodur ◽  
Ecevit Eyduran
Keyword(s):  
Energy Demand ◽  
Multivariate Adaptive Regression Splines ◽  
Regression Splines ◽  
Transportation Energy ◽  
Adaptive Regression ◽  
Adaptive Regression Splines

Information System for Transportation Energy

1977 ◽  
Vol 103 (5) ◽  
pp. 635-650
Author(s):  
Vasily Kouskoulas ◽  
Jeffrey L. Staley ◽  
Raymond E. Goodson
Keyword(s):  
Information System ◽  
Transportation Energy

Call Admission Control Algorithm with Efficient Handoff for Both 4G and 5G Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 1-08
Author(s):  
Maharazu Mamman ◽  
Zurina Mohd Hanapi
Keyword(s):  
Admission Control ◽  
Mobile Networks ◽  
Call Admission Control ◽  
Blocking Probability ◽  
Health Sector ◽  
5G Networks ◽  
Transportation Energy ◽  
Call Blocking Probability ◽  
Call Admission ◽  
Performance Challenges

Recently, many generations of mobile networks have changed from one transition to another transition. The mode of transition from the first generation (1G) to the fifth generation (5G) is characterized by a lot of performance challenges such as delay, speed of the users, mobility, and variety of services. Currently, different from prior generations, 5G is not only concerned with the mobile networks but also, with various applications and different services such as health sector, transportation, energy consumption, safety well as Smart City. All these services are incorporated by 5G. In this paper, we proposed a call admission control (CAC) algorithm with an efficient handoff for both 4G and 5G networks. Simulation is used to evaluate the effectiveness of the proposed algorithm, and the obtained results indicate it considerably performs better than do other algorithms based on valuable metrics such as data throughput, call blocking probability (CBP), and call dropping probability (CDP).

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