scholarly journals Energetic and bonding study of hexamethylenetetramine and fourteen related cage molecules: An ab initio G3 (MP2) investigation

2005 ◽  
Vol 70 (4) ◽  
pp. 661-668 ◽  
Author(s):  
H.O. Ho ◽  
W.K. Li
Keyword(s):  
Ab Initio ◽  
Heat Of Formation ◽  
Experimental Results ◽  
The Other ◽  
Heats Of Formation ◽  
Species Ranges ◽  
Mp2 Method ◽  
Cage Molecules ◽  
Molecular Dimensions

The ab initio G3(MP2)method has been applied to hexamethylenetetramine (HMT) and fourteen related cage systems. The agreement between the calculated and experimental molecular dimensions, which are available for five of the 15 cage species, ranges from satisfactory to excellent. In addition, the G3(MP2) heat of formation at 298 K for HMT is in excellent accord with experimental results. Hence, the calculated heats of formation for the other 14 cage systems should be reliable estimates.

Heat of Formation for the Benzoyl Cation by Photoionization Mass Spectrometry

2009 ◽  
Vol 15 (2) ◽  
pp. 183-188 ◽  
Author(s):  
John C. Traeger
Keyword(s):  
Mass Spectrometry ◽  
Ab Initio Calculations ◽  
Ab Initio ◽  
Heat Of Formation ◽  
Experimental Results ◽  
Photoionization Mass Spectrometry ◽  
Dissociative Photoionization ◽  
High Level

Dissociative photoionization mass spectrometry has been used to measure the PhCO+ appearance energies for several benzoyl compounds. Based on these threshold measurements, an experimental 298 K heat of formation of 738.8 ± 3.3 kJ mol−1 is obtained for the benzoyl cation. The experimental results are supported by high-level ab initio calculations.

The Influence of Water Regime on the Performance of Aquatic Plants

1994 ◽  
Vol 29 (4) ◽  
pp. 127-132 ◽  
Author(s):  
Naomi Rea ◽  
George G. Ganf
Keyword(s):  
Deep Water ◽  
Aquatic Plants ◽  
Water Regime ◽  
Optimal Performance ◽  
Experimental Results ◽  
The Other ◽  
Full Potential ◽  
Influence Of Water ◽  
Emergent Species

Experimental results demonstrate bow small differences in depth and water regime have a significant affect on the accumulation and allocation of nutrients and biomass. Because the performance of aquatic plants depends on these factors, an understanding of their influence is essential to ensure that systems function at their full potential. The responses differed for two emergent species, indicating that within this morphological category, optimal performance will fall at different locations across a depth or water regime gradient. The performance of one species was unaffected by growth in mixture, whereas the other performed better in deep water and worse in shallow.

Mining discriminative patches for script identification in natural scene images

2021 ◽  
Vol 40 (1) ◽  
pp. 551-563
Author(s):  
Liqiong Lu ◽  
Dong Wu ◽  
Ziwei Tang ◽  
Yaohua Yi ◽  
Faliang Huang
Keyword(s):  
Neural Networks ◽  
Experimental Results ◽  
The Other ◽  
Natural Scene ◽  
Fixed Size ◽  
Script Identification ◽  
Aspect Ratios ◽  
Novel Approach ◽  
Public Datasets ◽  
Natural Scene Images

This paper focuses on script identification in natural scene images. Traditional CNNs (Convolution Neural Networks) cannot solve this problem perfectly for two reasons: one is the arbitrary aspect ratios of scene images which bring much difficulty to traditional CNNs with a fixed size image as the input. And the other is that some scripts with minor differences are easily confused because they share a subset of characters with the same shapes. We propose a novel approach combing Score CNN, Attention CNN and patches. Attention CNN is utilized to determine whether a patch is a discriminative patch and calculate the contribution weight of the discriminative patch to script identification of the whole image. Score CNN uses a discriminative patch as input and predict the score of each script type. Firstly patches with the same size are extracted from the scene images. Secondly these patches are used as inputs to Score CNN and Attention CNN to train two patch-level classifiers. Finally, the results of multiple discriminative patches extracted from the same image via the above two classifiers are fused to obtain the script type of this image. Using patches with the same size as inputs to CNN can avoid the problems caused by arbitrary aspect ratios of scene images. The trained classifiers can mine discriminative patches to accurately identify some confusing scripts. The experimental results show the good performance of our approach on four public datasets.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

Study of wave attenuation in concrete

1993 ◽  
Vol 8 (9) ◽  
pp. 2344-2353 ◽  
Author(s):  
J-M. Berthelot ◽  
Souda M. Ben ◽  
J.L. Robert
Keyword(s):  
Experimental Study ◽  
Plane Wave ◽  
Wave Attenuation ◽  
Plane Waves ◽  
Propagation Distance ◽  
Experimental Results ◽  
The Other ◽  
Wave Frequency ◽  
Concrete Composition ◽  
Analytical Expression

The experimental study of wave attenuation in concrete has been achieved in the case of the propagation of plane waves in concrete rods. Different mortars and concretes have been investigated. A transmitter transducer coupled to one of the ends of the concrete rod generates the propagation of a plane wave in the rod. The receiver transducer, similar to the previous one, is coupled to the other end of the rod. The experimental results lead to an analytical expression for wave attenuation as function of the concrete composition, the propagation distance, and the wave frequency.

Heats of Formation of Alkali Metal and Alkaline Earth Metal Oxides and Hydroxides:  Surprisingly Demanding Targets for High-Level ab Initio Procedures

2003 ◽  
Vol 107 (29) ◽  
pp. 5617-5630 ◽  
Author(s):  
Michael B. Sullivan ◽  
Mark A. Iron ◽  
Paul C. Redfern ◽  
Jan M. L. Martin ◽  
Larry A. Curtiss ◽  
...  
Keyword(s):  
Alkali Metal ◽  
Metal Oxides ◽  
Ab Initio ◽  
Alkaline Earth ◽  
Earth Metal ◽  
Heats Of Formation ◽  
Alkaline Earth Metal ◽  
Alkaline Earth Metal Oxides ◽  
High Level

scholarly journals GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 68
Author(s):  
Lei Shi ◽  
Cosmin Copot ◽  
Steve Vanlanduit
Keyword(s):  
Cognitive Load ◽  
Real World ◽  
Robotic Manipulator ◽  
Similarity Score ◽  
Human Robot Interaction ◽  
Experimental Results ◽  
The Other ◽  
Robot Interaction ◽  
Run Length ◽  
The Real

In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario.

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