Fast decision on picture adaptive frame/field coding for H.264

2005 ◽  
Author(s):  
Peng Yin ◽  
Alexis Michael Tourapis ◽  
Jill Boyce
Keyword(s):  
MedienJournal ◽  
2018 ◽  
Vol 42 (1) ◽  
pp. 11-32 ◽  
Author(s):  
Franzisca Weder

The present study examines the relevance and framing of Corporate Social Responsibility in the mass media. Challenged by the ethically (over)loaded issue of responsibility, communication studies are searching for a new understanding of framing to investigate phenomena of new economic values like Corporate Social Responsibility in public discourses. For the quantitative content analysis put forward herein, frames are described as footprints of diverse positions, which determine a given public discourse. The longitudinal analysis of 26 German-speaking newspapers in Germany, Austria, and Switzerland between 1999 and 2008, a phase where CSR was aligned in business practices and CSR communication established in public discourses, aims at identifying CSR-frames as well as inquiring into the existence of a public discourse about CSR. The results show that there is no discourse on CSR itself. Instead of the assumed multiple issue-specific frames, CSR itself is (ab)used as a masterframe or “buzz word” in economic discourses.


Author(s):  
Eva García-Martín ◽  
Niklas Lavesson ◽  
Håkan Grahn ◽  
Emiliano Casalicchio ◽  
Veselka Boeva

AbstractRecently machine learning researchers are designing algorithms that can run in embedded and mobile devices, which introduces additional constraints compared to traditional algorithm design approaches. One of these constraints is energy consumption, which directly translates to battery capacity for these devices. Streaming algorithms, such as the Very Fast Decision Tree (VFDT), are designed to run in such devices due to their high velocity and low memory requirements. However, they have not been designed with an energy efficiency focus. This paper addresses this challenge by presenting the nmin adaptation method, which reduces the energy consumption of the VFDT algorithm with only minor effects on accuracy. nmin adaptation allows the algorithm to grow faster in those branches where there is more confidence to create a split, and delays the split on the less confident branches. This removes unnecessary computations related to checking for splits but maintains similar levels of accuracy. We have conducted extensive experiments on 29 public datasets, showing that the VFDT with nmin adaptation consumes up to 31% less energy than the original VFDT, and up to 96% less energy than the CVFDT (VFDT adapted for concept drift scenarios), trading off up to 1.7 percent of accuracy.


Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4446
Author(s):  
Do-In Kim

This paper presents an event identification process in complementary feature extractions via convolutional neural network (CNN)-based event classification. The CNN is a suitable deep learning technique for addressing the two-dimensional power system data as it directly derives information from a measurement signal database instead of modeling transient phenomena, where the measured synchrophasor data in the power systems are allocated by time and space domains. The dynamic signatures in phasor measurement unit (PMU) signals are analyzed based on the starting point of the subtransient signals, as well as the fluctuation signature in the transient signal. For fast decision and protective operations, the use of narrow band time window is recommended to reduce the acquisition delay, where a wide time window provides high accuracy due to the use of large amounts of data. In this study, two separate data preprocessing methods and multichannel CNN structures are constructed to provide validation, as well as the fast decision in successive event conditions. The decision result includes information pertaining to various event types and locations based on various time delays for the protective operation. Finally, this work verifies the event identification method through a case study and analyzes the effects of successive events in addition to classification accuracy.


Author(s):  
Ibrahim Suleiman Yahaya ◽  
Maryam M.B Yusuf

This paper The search paper aimed at introducing new development in decision-making and problem-solving models which will enable the decision-makers to have more options on the way of handling any give scenarios that might occur in the process of daily life or organizational activities, this will improve fast decision by individual or organization. Decision making is an acceptable part of human daily life. People have to make different important decisions nearly every day, hence the reason that often-making decisions can be a difficult action to take. However, a significant number of observational studies have shown that most individuals are much worse in decision-making in organizations. Thus, people started paying more attention to learning how to make an acceptable decision through the related hypotheses and models that fit their scenarios. Along with the line hundred (100) sample of the design developed model with a Likert-Scale from 1-5 was attached and sent to some prominent leaders who virtually make a decision and solved problems almost every day, for their assessment’s/analysis in order to collect data to determine both input and output of the developed model which some accepted as it was designed while some make changes and other make a recommendation for future research work. The decision-making tools are needed at the critical time of Covid.


Molecules ◽  
2022 ◽  
Vol 27 (1) ◽  
pp. 326
Author(s):  
Emilio Celotti ◽  
Georgios Lazaridis ◽  
Jakob Figelj ◽  
Yuri Scutaru ◽  
Andrea Natolino

The oxidation processes of white wines can occur during storage and commercialization due to several factors, and these can negatively affect the color, aroma, and quality of the wine. Wineries should have faster and simpler methods that provide valuable information on oxidation stability of wines and allow fast decision-making procedures, able to trigger suitable technological interventions. Using a portable prototype instrument for light irradiations at different wavelengths and times was considered and evaluated on sensorial, spectrophotometric, and colorimetric parameters of white wines. The sensorial analysis revealed that white and light blue were the most significant, after only 1 h of irradiation. The experimental results showed that hydrogen peroxide could enhance the effect of light treatment, allowing a contemporary evaluation of the oxidation stability of wine against light and chemical stresses. As expected, a good correlation (R2 > 0.89) between optical density at 420 nm and b* parameter was highlighted. The synergic effect of light and H2O2 was also studied on the hydrolyzable and condensed tannins’ additions to white wine. The proposed methodology could be used to evaluate the oxidative stability of white wines, but also to evaluate the effect of some oenological adjuvants on wine stability.


2004 ◽  
Vol 77 (6) ◽  
pp. 2061-2065 ◽  
Author(s):  
Parwis Massoudy ◽  
Yi-Young Kim ◽  
Murat Cetin ◽  
Matthias Thielmann ◽  
Ulf Herold ◽  
...  

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