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关键词： Estimation   Load management   Pricing   Load modeling   Recruitment   Electrical engineering   Computer science   Demand response   baseline estimation   baseline inflation  

摘要： In this paper, we propose a novel incentive based Demand Response (DR) program with a self reported baseline mechanism. The System Operator (SO) managing the DR program recruits consumers or aggregators of DR resources. The recruited consumers are required to only report their baseline, which is the minimal information necessary for any DR program. During a DR event, a set of consumers, from this pool of recruited consumers, are randomly selected. The consumers are selected such that the required load reduction is delivered. The selected consumers, who reduce their load, are rewarded for their services and other recruited consumers, who deviate from their reported baseline, are penalized. The randomization in selection and penalty ensure that the baseline inflation is controlled. We also justify that the selection probability can be simultaneously used to control SO's cost. This allows the SO to design the mechanism such that its cost is almost optimal when there are no recruitment costs or at least significantly reduced otherwise. Finally, we also show that the proposed method of self-reported baseline outperforms other baseline estimation methods commonly used in practice.

关键词： Geographical information technologies (GIT)   Institutions   Post-adoption   GIT drivers   Mozambique   Computer science  

摘要： This study aims to understand the determinants of geographical information technologies at the scale of post-adoption use and intention to increase the level of use in Mozambican institutions. Three known theories (diffusion of innovation, theory, technology - organisation - environment framework, and institutional oval theory) have been used in order to accomplish the study. The data analysis showed that the variables compatibility, geographical scope, expansion opportunities, and normative pressure contribute to explaining GIT use. Relative advantage, complexity, coercive pressure, and mimetic pressure contribute to explaining the intention to increase GIT levels of use. The model revealed substantial power of explanation for GIT post-adoption.

关键词： Computer science   STEM education   User interface   User experience   Cyberlearning environment   Usability evaluation  

摘要： Despite the widespread availability and increasing use of cyberlearning environments, there remains a need for more research about their usefulness in undergraduate education, particularly in STEM education. The process of evaluating the usefulness of a cyberlearning environment is an essential measure of its success and is useful in assisting the design process and ensuring user satisfaction. Unfortunately, there are relatively few empirical studies that provide a comprehensive test of the usefulness of cyberlearning in education. Additionally, there is a lack of standards upon whose usefulness evaluators agree. In this research, we present multiple user studies that can be used to assess the usefulness of a cyberlearning environment used in Computer Science and Software Engineering courses through testing its usability and measuring its utility using user interface and user experience evaluations. Based on these assessments, we propose an evaluation framework to evaluate cyberlearning environments. To help illustrate the framework utility and usability evaluations, we explain them through an example SEP-CyLE (Software Engineering and Programming Cyberlearning Environment). The evaluation techniques used are cognitive walkthroughs with a think-aloud protocol and a heuristic evaluation survey. We further use a network-based analysis to find the statistically significant correlated responses in the heuristic evaluation survey with regard to the students' perceptions of using SEP-CyLE. Our goal is to improve cyberlearning practice and to emphasize the need for evaluating cyberlearning environments with respect to its designated tasks and its users using UI/UX evaluations. Our experiments demonstrated participants were able to utilize SEP-CyLE efficiently to accomplish the tasks we posed to them and to enhance their software development concepts, specifically, software testing. We discovered areas of improvement in the visibility and navigation of SEP-CyLE's current de

关键词： Computer science   Sliced binary pattern   Representation learning   Feature extraction   Classification  

摘要： We present an Algorithm to understand Inter-pixel similarity, which shall be observed in images with the help of a data structure Full Binary Tree. The Full Binary Tree has certain properties like every node must have 2 children or none. Based on this property of Binary Tree, the method of Sliced Binary Pattern is proposed. The inter-pixel similarity may be observed by converting any pixel information of an image within a block of size 3 x 3 to its binarized form, as the pixel information, whose similarity with neighboring pixel cannot be exploited, when it is in decimal form. Thus, we convert all pixel information within a block of size 3 x 3 to its binarized form then we compare the binary pattern of a central pixel with its 8-nearest neighbors. If there is a binary pattern match between central pixel and its 8-nearest neighbors of a block, we assign weights to it, where the weights are determined by the position of match that exist between central pixel and 8-other neighboring pixels of an image. This process helps in determining the inter-pixel similarity of 8-nearest neighbors with respect to central pixel of a block. Every block of 3 x 3 pixels is processed with this strategy to obtain the similarity between patterns in an image. The erected Weighted Full Binary Tree-Sliced Binary Pattern analyzes an image in RGB-Dimensions based on patterns of Inter-Pixel Similarity by tracing the similarity path. The proposed RGB-D texture based inter-pixel similarity addresses the verification of facial similarity. Further, the proposed WFBT-SBP has yielded a good classification accuracy of 77.4%, 77.3%, 77.98%, and 77.94% over a relations of F-S, F-D, M-S, M-D of KinfaceW-I and 76.89%, 76.72%, 77.01%, 76.99% over a relations of F-S, F-D, M-S, and M-D of KinfaceW-II respectively.

关键词： Computer science   Data hiding   Interval type-2 fuzzy logic system   Similarity measure   Image steganography  

摘要： Similarity measure, also called information measure, is a concept used to distinguish different objects. It has been studied from different contexts by employing mathematical, psychological, and fuzzy approaches. Image steganography is the art of hiding secret data into an image in such a way that it cannot be detected by an intruder. In image steganography, hiding secret data in the plain or non-edge regions of the image is significant due to the high similarity and redundancy of the pixels in their neighborhood. However, the similarity measure of the neighboring pixels, i.e., their proximity in color space, is perceptual rather than mathematical. Thus, this paper proposes an interval type-2 fuzzy logic system (IT2 FLS) to determine the similarity between the neighboring pixels by involving an instinctive human perception through a rule-based approach. The pixels of the image having high similarity values, calculated using the proposed IT2 FLS similarity measure, are selected for embedding via the least significant bit (LSB) method. We term the proposed procedure of steganography as 'IT2 FLS-LSB method'. Moreover, we have developed two more methods, namely, type-1 fuzzy logic system based least significant bits (T1FLS-LSB) and Euclidean distance based similarity measures for least significant bit (SM-LSB) steganographic methods. Experimental simulations were conducted for a collection of images and quality index metrics, such as PSNR (peak signal-to-noise ratio), UQI (universal quality index), and SSIM (structural similarity measure) are used. All the three steganographic methods are applied on dataset and the quality metrics are calculated. The obtained stego images and results are shown and thoroughly compared to determine the efficacy of the IT2 FLS-LSB method. We have also demonstrated the high payload capacity of our proposed method. Finally, we have done a comparative analysis of the proposed approach with the existing well-known steganographic methods to sho

关键词： Artificial neural networks   Sociology   Statistics   Optimization   Learning systems   Predictive models   Computer science   Dynamic optimization problem (DOP)   information transfer   neural network (NN)  

摘要： In dynamic optimization problems (DOPs), as the environment changes through time, the optima also dynamically change. How to adapt to the dynamic environment and quickly find the optima in all environments is a challenging issue in solving DOPs. Usually, a new environment is strongly relevant to its previous environment. If we know how it changes from the previous environment to the new one, then we can transfer the information of the previous environment, e.g., past solutions, to get new promising information of the new environment, e.g., new high-quality solutions. Thus, in this paper, we propose a neural network (NN)-based information transfer method, named NNIT, to learn the transfer model of environment changes by NN and then use the learned model to reuse the past solutions. When the environment changes, NNIT first collects the solutions from both the previous environment and the new environment and then uses an NN to learn the transfer model from these solutions. After that, the NN is used to transfer the past solutions to new promising solutions for assisting the optimization in the new environment. The proposed NNIT can be incorporated into population-based evolutionary algorithms (EAs) to solve DOPs. Several typical state-of-the-art EAs for DOPs are selected for comprehensive study and evaluated using the widely used moving peaks benchmark. The experimental results show that the proposed NNIT is promising and can accelerate algorithm convergence.

关键词： Gender   STEM   identity   stereotypes   gender roles  

摘要： Three studies examine the relationship between women's expression of interest in computer science and identity expression threat, the concern about conveying an identity inconsistent with one's gender role. Undergraduates perceive academic majors to signal who they are to peers (Study 1). Women imagining majoring in computer science report greater identity expression threat from their peers outside computer science than from those inside the field (Study 2). Women report greater identity expression threat in computer science (but not biology or English) than do men. Identity expression threat mediates gender differences in reported likelihood of downplaying interest in computer science (Study 3). Women considering computer science perceive they will be doubly isolated, both from those within and outside the field.

关键词： Students  

摘要： With the number of Computer Science (CS) jobs on the rise, there is a greater need for Computer Science graduates than ever. At the same time, most CS departments across the country are only seeing 25-30% of female students in their classes, meaning that we are failing to draw interest from a large portion of the population. In this work, we explore the gender gap in CS at a large public research university, using three data sets that span thousands of students across 5.5 academic years. By combining these data sets, we can explore many issues such as retention as students progress through the CS major. For example, we find that a large percentage of women taking the Introductory CS1 course for majors do not intend to major in CS, which contributes to a large increase in the gender gap immediately after CS1. This finding implies that a large part of the retention task is attracting these women to further explore the major. We report findings in three areas of research in the context of the CS department at our university: the CS environment, the computing background of our students, and the students’ grades. These findings may also be applicable to computing programs at other large public research universities. Copyright © 2020, The Authors. All rights reserved.

关键词： artificial intelligence   computer science   general news   humanities   machine learning   political   sciences  

关键词： artificial intelligence   computer science   general news   humanities   machine learning   political   sciences