scholarly journals Future-Aware Trend Alignment for Sales Predictions

Information ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 558
Author(s):  
Yiwei Liu ◽  
Lin Feng ◽  
Bo Jin
Keyword(s):  
Original Model ◽  
Data Sets ◽  
Sales Data ◽  
Significant Challenge ◽  
Data Prediction ◽  
Decision Making System ◽  
The Face ◽  
Context Specific ◽  
Almost All ◽  
Better Than

Accurately forecasting sales is a significant challenge faced by almost all companies. In particular, most products have short lifecycles without the accumulation of historical sales data. Existing methods either fail to capture the context-specific, irregular trends or to integrate as much information as is available in the face of a data scarcity problem. To address these challenges, we propose a new model, called F-TADA, i.e., future-aware TADA, which is derived from trend alignment with dual-attention multi-task recurrent neural networks (TADA). We utilize two real-world supply chain sales data sets to verify our algorithm’s performance and effectiveness on both long and short lifecycles. The experimental results show that the accuracy of the F-TADA is better than the original model. Our model’s performance could be further improved, however, by appropriately increasing the length of the windows in the decoding stage. Finally, we develop a sales data prediction and analysis decision-making system, which can offer intelligent sales guidance to enterprises.

scholarly journals Comparison of Perceived Interactivity Measures of Actual Websites Interactivity

2017 ◽  
Vol 13 (1) ◽  
Author(s):  
Velimir Štavljanin ◽  
Milica Jevremović
Keyword(s):  
Digital Marketing ◽  
Experimental Setting ◽  
Perceived Interactivity ◽  
The Face ◽  
Huge Impact ◽  
Marketing Activities ◽  
Almost All ◽  
Better Than

Interactivity is a concept of enormous importance for digital marketing. It was recognized as a key feature of website, a hub of all digital marketing activities. But, almost all interactivity measures were conceptualized one or two decades ago. In the meantime, technological novelties changed the face of websites. Also, a number of interactivity features increased exponentially. Those changes had a huge impact on practice and could influence user’s perception of interactivity. Aim of this paper is to explore whether several selected existing measures of perceived interactivity could cope with those changes. Paper reports a study in which two websites of low and high interactivity were developed and in an experimental setting as stimuli used to test three perceived interactivity measures. Results show that all measures estimated perceived interactivity of a high interactivity website better than of a low interactivity website. Also, results show that particular dimensions of a model could be used to estimate overall interactivity.

scholarly journals Genetic Programming-Based Feature Learning for Facial Expression Classification

2021 ◽  
Author(s):  
Ying Bi ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Facial Expression ◽  
Genetic Programming ◽  
Feature Learning ◽  
Data Sets ◽  
Training Images ◽  
High Classification Accuracy ◽  
The Face ◽  
Almost All ◽  
Facial Expression Classification ◽  
Expression Classification

© 2020 IEEE. Facia1 expression classification is an important but challenging task in artificial intelligence and computer vision. To effectively solve facial expression classification, it is necessary to detect/locate the face and extract features from the face. However, these two tasks are often conducted separately and manually in a traditional facial expression classification system. Genetic programming (GP) can automatically evolve solutions for a task without rich human intervention. However, very few GP-based methods have been specifically developed for facial expression classification. Therefore, this paper proposes a GP-based feature learning approach to facial expression classification. The proposed approach can automatically select small regions of a face and extract appearance features from the small regions. The experimental results on four different facial expression classification data sets show that the proposed approach achieves significantly better results in almost all the comparisons. To further show the effectiveness of the proposed approach, different numbers of training images are used in the experiments. The results indicate that the proposed approach achieves significantly better performance than any of the baseline methods using a small number of training images. Further analysis shows that the proposed approach not only selects informative regions of the face but also finds a good combination of various features to obtain a high classification accuracy.

scholarly journals Genetic Programming-Based Feature Learning for Facial Expression Classification

2021 ◽  
Author(s):  
Ying Bi ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Facial Expression ◽  
Genetic Programming ◽  
Feature Learning ◽  
Data Sets ◽  
Training Images ◽  
High Classification Accuracy ◽  
The Face ◽  
Almost All ◽  
Facial Expression Classification ◽  
Expression Classification

© 2020 IEEE. Facia1 expression classification is an important but challenging task in artificial intelligence and computer vision. To effectively solve facial expression classification, it is necessary to detect/locate the face and extract features from the face. However, these two tasks are often conducted separately and manually in a traditional facial expression classification system. Genetic programming (GP) can automatically evolve solutions for a task without rich human intervention. However, very few GP-based methods have been specifically developed for facial expression classification. Therefore, this paper proposes a GP-based feature learning approach to facial expression classification. The proposed approach can automatically select small regions of a face and extract appearance features from the small regions. The experimental results on four different facial expression classification data sets show that the proposed approach achieves significantly better results in almost all the comparisons. To further show the effectiveness of the proposed approach, different numbers of training images are used in the experiments. The results indicate that the proposed approach achieves significantly better performance than any of the baseline methods using a small number of training images. Further analysis shows that the proposed approach not only selects informative regions of the face but also finds a good combination of various features to obtain a high classification accuracy.

The Alternatives to War

2018 ◽  
Author(s):  
James Pattison
Keyword(s):  
Just War ◽  
Just War Theory ◽  
Economic Sanctions ◽  
Responsibility To Protect ◽  
Military Action ◽  
Comprehensive Account ◽  
The Face ◽  
Normative Issues ◽  
Better Than

If states are not to go to war, what should they do instead? In The Alternatives to War: From Sanctions to Non-violence, James Pattison considers the case for the alternatives to military action to address mass atrocities and aggression. He covers the normative issues raised by measures ranging from comprehensive economic sanctions, diplomacy, and positive incentives, to criminal prosecutions, non-violent resistance, accepting refugees, and arming rebels. For instance, given the indiscriminateness of many sanctions regimes, are sanctions any better than war? Should states avoid ‘megaphone diplomacy’ and adopt more subtle measures? What, if anything, can non-violent methods such as civilian defence and civilian peacekeeping do in the face of a ruthless opponent? Is it a serious concern that positive incentives can appear to reward aggressors? Overall, Pattison provides a comprehensive account of the ethics of the alternatives to war. In doing so, he argues that the case for war is weaker and the case for many of the alternatives is stronger than commonly thought. The upshot is that, when reacting to mass atrocities and aggression, states are generally required to pursue the alternatives to war rather than military action. Pattison concludes that this has significant implications for pacifism, Just War Theory, and the responsibility to protect doctrine.

Extensions of the Pseudo-Potential Method

2018 ◽  
Author(s):  
Sauro Succi
Keyword(s):  
Potential Method ◽  
Original Model ◽  
Original Formulation ◽  
The Face ◽  
Pseudo Potential

This chapter provides an account of subsequent extensions of the Shan-Chen pseudo-potential method, including more elaborated potentials which extend beyond the first Brillouin cell. These extensions permit us to lift a number of limitations of the original model and considerably expand its scope and range of applications. In Chapter 27, a variety of LB techniques for nonideal fluids have been discussed. As usual, each method comes with its ups and downs, but actual evidence shows that the Shan–Chen (SC) model has enjoyed increasing popularity over the years. Interestingly, such popularity stands in the face of a fair amount of substantial criticism. In this chapter, first the Shan–Chen model is revisited in some more detail along with a discussion of ways out of the above criticism. Subsequently, the extension of the SC technique to the case of multi-range potentials extending beyond the first Brillouin cell is discussed. This extension proves pretty effective in softening many of the weaknesses of the original formulation, thereby considerably expanding its scope and range of applications.

scholarly journals Simulation and Nonlinearity Optimization of a High-Pressure Sensor

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4419
Author(s):  
Ting Li ◽  
Haiping Shang ◽  
Weibing Wang
Keyword(s):  
High Pressure ◽  
Pressure Sensor ◽  
Pressure Sensors ◽  
Original Model ◽  
Ansys Software ◽  
Nonlinear Error ◽  
Sensor Model ◽  
Optimized Model ◽  
Simulation Results ◽  
Better Than

A pressure sensor in the range of 0–120 MPa with a square diaphragm was designed and fabricated, which was isolated by the oil-filled package. The nonlinearity of the device without circuit compensation is better than 0.4%, and the accuracy is 0.43%. This sensor model was simulated by ANSYS software. Based on this model, we simulated the output voltage and nonlinearity when piezoresistors locations change. The simulation results showed that as the stress of the longitudinal resistor (RL) was increased compared to the transverse resistor (RT), the nonlinear error of the pressure sensor would first decrease to about 0 and then increase. The theoretical calculation and mathematical fitting were given to this phenomenon. Based on this discovery, a method for optimizing the nonlinearity of high-pressure sensors while ensuring the maximum sensitivity was proposed. In the simulation, the output of the optimized model had a significant improvement over the original model, and the nonlinear error significantly decreased from 0.106% to 0.0000713%.

scholarly journals Contactless Video-Based Heart Rate Monitoring of a Resting and an Anesthetized Pig

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 442
Author(s):  
Meiqing Wang ◽  
Ali Youssef ◽  
Mona Larsen ◽  
Jean-Loup Rault ◽  
Daniel Berckmans ◽  
...  
Keyword(s):  
Heart Rate ◽  
Estimation Error ◽  
Well Being ◽  
Absolute Error ◽  
Mean Value ◽  
Video Data ◽  
Window Functions ◽  
The Face ◽  
Short Time ◽  
Better Than

Heart rate (HR) is a vital bio-signal that is relatively easy to monitor with contact sensors and is related to a living organism’s state of health, stress and well-being. The objective of this study was to develop an algorithm to extract HR (in beats per minute) of an anesthetized and a resting pig from raw video data as a first step towards continuous monitoring of health and welfare of pigs. Data were obtained from two experiments, wherein the pigs were video recorded whilst wearing an electrocardiography (ECG) monitoring system as gold standard (GS). In order to develop the algorithm, this study used a bandpass filter to remove noise. Then, a short-time Fourier transform (STFT) method was tested by evaluating different window sizes and window functions to accurately identify the HR. The resulting algorithm was first tested on videos of an anesthetized pig that maintained a relatively constant HR. The GS HR measurements for the anesthetized pig had a mean value of 71.76 bpm and standard deviation (SD) of 3.57 bpm. The developed algorithm had 2.33 bpm in mean absolute error (MAE), 3.09 bpm in root mean square error (RMSE) and 67% in HR estimation error below 3.5 bpm (PE3.5). The sensitivity of the algorithm was then tested on the video of a non-anaesthetized resting pig, as an animal in this state has more fluctuations in HR than an anaesthetized pig, while motion artefacts are still minimized due to resting. The GS HR measurements for the resting pig had a mean value of 161.43 bpm and SD of 10.11 bpm. The video-extracted HR showed a performance of 4.69 bpm in MAE, 6.43 bpm in RMSE and 57% in PE3.5. The results showed that HR monitoring using only the green channel of the video signal was better than using three color channels, which reduces computing complexity. By comparing different regions of interest (ROI), the region around the abdomen was found physiologically better than the face and front leg parts. In summary, the developed algorithm based on video data has potential to be used for contactless HR measurement and may be applied on resting pigs for real-time monitoring of their health and welfare status, which is of significant interest for veterinarians and farmers.

scholarly journals A Novel LSTM Model with Interaction Dual Attention for Radar Echo Extrapolation

2021 ◽  
Vol 13 (2) ◽  
pp. 164
Author(s):  
Chuyao Luo ◽  
Xutao Li ◽  
Yongliang Wen ◽  
Yunming Ye ◽  
Xiaofeng Zhang
Keyword(s):  
Short Term Memory ◽  
Weather Forecast ◽  
Vital Role ◽  
Data Sets ◽  
Short Term ◽  
Learning Techniques ◽  
Radar Echo ◽  
Hidden States ◽  
Better Than

The task of precipitation nowcasting is significant in the operational weather forecast. The radar echo map extrapolation plays a vital role in this task. Recently, deep learning techniques such as Convolutional Recurrent Neural Network (ConvRNN) models have been designed to solve the task. These models, albeit performing much better than conventional optical flow based approaches, suffer from a common problem of underestimating the high echo value parts. The drawback is fatal to precipitation nowcasting, as the parts often lead to heavy rains that may cause natural disasters. In this paper, we propose a novel interaction dual attention long short-term memory (IDA-LSTM) model to address the drawback. In the method, an interaction framework is developed for the ConvRNN unit to fully exploit the short-term context information by constructing a serial of coupled convolutions on the input and hidden states. Moreover, a dual attention mechanism on channels and positions is developed to recall the forgotten information in the long term. Comprehensive experiments have been conducted on CIKM AnalytiCup 2017 data sets, and the results show the effectiveness of the IDA-LSTM in addressing the underestimation drawback. The extrapolation performance of IDA-LSTM is superior to that of the state-of-the-art methods.

Quantitative analysis of static equilibrium in women after mastectomy

2014 ◽  
Vol 14 (1) ◽  
pp. 81-87
Author(s):  
Maciej Rachwał ◽  
Justyna Drzał-Grabiec ◽  
Katarzyna Walicka-Cupryś ◽  
Aleksandra Truszczyńska
Keyword(s):  
Mean Amplitude ◽  
Control Group ◽  
Foot Pressure ◽  
Locomotor System ◽  
Center Of Foot Pressure ◽  
The Mean ◽  
Almost All ◽  
Posture Stability ◽  
Mastectomy Group ◽  
Better Than

Abstract Background: The post-mastectomy changes to the locomotor system are related to the scar and adhesion or to the lymphatic edema after amputation which, in turn, lead to local and global distraction of the work of the muscles. These changes lead to body statics disturbance that changes the projection of the center of gravity and worsens motor response due to changing of the muscle sensitivity. Objective: The aim of the study was to evaluate the static balance of women after undergoing mastectomy. Methods: The study included 150 women, including 75 who underwent mastectomy (mean age: 60±7.6) years, mean body mass index (BMI): 26 (±3.6) kg/m2) and 75 who were placed in the control group with matched age and BMI. The study was conducted using a tensometric platform. Results: Statistically significant differences were found for almost all parameters between the post-mastectomy group and group of healthy women, regarding center of foot pressure (COP) path length in the Y and X axes and the mean amplitude of COP. Conclusions: First, the findings revealed that balance in post-mastectomy women is significantly better than in the control group. Second, physiotherapeutic treatment of post-mastectomy women may have improved their posture stability compared with their peers.

Stereotypes in the face of reality: Intergroup contact inconsistent with group stereotypes changes attitudes more than stereotype-consistent contact

2020 ◽  
pp. 136843022094681
Author(s):  
Tibor Zingora ◽  
Loris Vezzali ◽  
Sylvie Graf
Keyword(s):  
Intergroup Contact ◽  
The Face ◽  
Positive Contact ◽  
Better Than

In a longitudinal two-wave study we examined the effects of positive and negative intergroup contact on outgroup attitudes in participants who perceived positive, negative, or ambivalent group stereotypes. We focused on stereotype-consistent contact, occurring when the valence of participants’ contact matches the valence of the perceived group stereotype (e.g., negative–negative), and on stereotype-inconsistent contact, occurring when the valence of contact contradicts the valence of the group stereotype (e.g., positive–negative). In relations of the Czech majority ( N = 890) with two distinctly stereotyped minorities, the Roma and the Vietnamese, stereotype-inconsistent contact predicted changes in attitudes better than stereotype-consistent contact. In the case of negatively stereotyped groups, positive intergroup contact is a viable way to improve attitudes. For positively stereotyped groups, negative contact can worsen attitudes, while positive contact does not have any attitude-improving effect. Interventions aimed at improving outgroup attitudes need to be applied with caution, considering the valence of group stereotypes.

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