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In the research of non-intrusive load monitoring (NILM), the temporal characteristics of V–I trajectories are often overlooked, and using a single feature for identification may lead to insignificant differences between similar loads. Based on this, this paper proposes a non-intrusive load monitoring method based on time-enhanced multidimensional feature visualization. By adding a time axis to the V–I trajectory, it integrates the rate of change in voltage and current, power factor, and third harmonic to form a three-dimensional spatiotemporal color V–I trajectory, addressing the gap in dynamic characteristics. The ECA-ResNet34 network model is used for load identification, avoiding the problems of network degradation and training difficulties caused by the excessive depth of traditional convolutional neural networks (CNN), and achieving efficient monitoring of household loads. The method was validated on the PLAID dataset, achieving an average F1 score of 97.3%. Furthermore, utilizing transfer learning, the model trained and tested on the PLAID dataset was further tested on the WHITED dataset to increase the model's universality and generalization ability, showing significant effects in identifying loads with similar V–I trajectories and multiple states. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Simplicial complexes are higher-order combinatorial structures which have been used to represent real-world complex systems. In this paper, we focus on the local patterns in simplicial complexes called simplets, a generalization of graphlets. We study the problem of counting simplets of a given size in a given simplicial complex. For this problem, we extend a sampling algorithm based on color coding, from graphs to simplicial complexes, with essential technical novelty. We theoretically analyze our proposed algorithm named SC3, showing its correctness, unbiasedness, convergence, and time/space complexity. Through extensive experiments on sixteen real-world datasets, we show the superiority of SC3 in terms of accuracy, speed, and scalability, compared to the baseline methods. We use the counts given by SC3 for simplicial complex analysis, especially for characterization, which is further used for simplicial complex clustering, where SC3 shows a strong ability of characterization with domain-based similarity. Additionally, we explore a variant of simplet counting (specifically, estimating the relative counts of simplets) under realistic scenarios where the entire simplicial complex is not provided at once but can only be partially accessed, for instance, through a limited number of API calls. For such scenarios, we propose a random-walk-based sampling algorithm, SCRW, and analyze its theoretical properties. In our experiments, SCRW requires, on average, 16.5 × less memory than SC3, while the speed-accuracy trade-offs provided by the two methods are comparable. [ABSTRACT FROM AUTHOR]

Addressing issues such as high hardware costs, low recognition accuracy, and the inability to achieve fine-grained equipment classification, a non-invasive load fine-grained recognition system based on FPGA was developed and tested on a Linux system for online training. A three-dimensional (3D) image construction method based on color coding of voltage–current (V-I) trajectories is proposed to preprocess the collected voltage and current data, allowing for the distinction of features of various electrical equipment in multiple dimensions. First, high-frequency sampling data is preprocessed to extract the V-I trajectory and higher harmonic characteristics of the load. Then, the V-I trajectory is processed using RGB color coding and fused with higher-order harmonic features to construct a 3D image. This results in a 3D color V-I trajectory image that incorporates both color and harmonic features. Finally, the improved ResNet50 network is employed to identify the load characteristics, and the method is validated using the PLAID dataset and measured data. The load identification method achieves an accuracy rate of over 98%, enhancing the information conveyed by the V-I trajectory and improving the uniqueness of load characteristics, thereby enabling fine-grained equipment identification. This advancement holds significant implications for energy conservation and emission reduction in household electricity consumption, as well as for eliminating potential safety hazards associated with electrical equipment. [ABSTRACT FROM AUTHOR]

Background/Objectives: We present a software package called reflimR (Version 1.0.6), which enables rapid and transparent verification of reference intervals from routine laboratory measurements. Our method makes it easy to compare the results with specified target values and facilitates the interpretation of deviations using traffic light colors. Methods: The algorithm includes three procedural steps: (a) definition of an appropriate distribution model, based on Bowley's quartile skewness, (b) iterative truncation, based on a modified boxplot method to obtain the central 95% of presumably inconspicuous results, and (c) extrapolation of reference limits from a truncated normal quantile–quantile plot. Results: All algorithms have been combined into one consolidated library, which can be called in the R environment with a single command reflim (x). Using an example dataset included in the package, we demonstrate that our method can be applied to mixed data containing a substantial proportion of pathological values. It leads to similar results as the direct guideline approach as well as the more sophisticated indirect refineR software package. As compared to the latter, reflimR works much faster and needs smaller datasets for robust estimates. For the interpretation of the results, we present an intuitive color scheme based on tolerance ranges (permissible uncertainty of laboratory results). We show that a relatively high number of published reference limits require careful reevaluation. Conclusions: The reflimR package closes the gap between direct guideline methods and the more sophisticated indirect refineR method. We recommend reflimR for the rapid routine verification of large amounts of reference limits and refineR for a careful analysis of unclear or doubtful results from this check. [ABSTRACT FROM AUTHOR]

Addressing issues such as high hardware costs, low recognition accuracy, and the inability to achieve fine-grained equipment classification, a non-invasive load fine-grained recognition system based on FPGA was developed and tested on a Linux system for online training. A three-dimensional (3D) image construction method based on color coding of voltage–current (V-I) trajectories is proposed to preprocess the collected voltage and current data, allowing for the distinction of features of various electrical equipment in multiple dimensions. First, high-frequency sampling data is preprocessed to extract the V-I trajectory and higher harmonic characteristics of the load. Then, the V-I trajectory is processed using RGB color coding and fused with higher-order harmonic features to construct a 3D image. This results in a 3D color V-I trajectory image that incorporates both color and harmonic features. Finally, the improved ResNet50 network is employed to identify the load characteristics, and the method is validated using the PLAID dataset and measured data. The load identification method achieves an accuracy rate of over 98%, enhancing the information conveyed by the V-I trajectory and improving the uniqueness of load characteristics, thereby enabling fine-grained equipment identification. This advancement holds significant implications for energy conservation and emission reduction in household electricity consumption, as well as for eliminating potential safety hazards associated with electrical equipment.

To address the problems of poor visual quality of synthesized grayscale and insufficient restoration of reconstructed color image in existing methods, this paper proposed an invertible grayscale method based on color coding and image steganography(IG-CCIS). The proposed method utilized an invertible neural network(INN) to construct an efficient color codec, and introduced dense convolutional blocks and channel attention mechanisms to further improve the performance of the network model, comprehensively reducing the loss of color information. In addition, in order to load encoded information into grayscale images and reduce image distortion caused by the embedding processed, it designed an image steganography algorithm based on exploiting modification direction(EMD). Through adaptive weight parameter selection, it could meet different embedding capacity requirements in a near-optimal manner and reduce the modification of grayscale images. Experimental tested on Kodak and McMaster datasets show that compared with existing representative reversible grayscale methods, the proposed method can generate better-quality reversible grayscale images and reconstruct more realistic color images, with better visual effects in image visualization. It also achieves better performance in terms of similarity evaluation metrics with standard reference images. [ABSTRACT FROM AUTHOR]

We analyze the (parameterized) computational complexity of "fair" variants of bipartite many-to-one matching, where each vertex from the "left" side is matched to exactly one vertex and each vertex from the "right" side may be matched to multiple vertices. We want to find a "fair" matching, in which each vertex from the right side is matched to a "fair" set of vertices. Assuming that each vertex from the left side has one color modeling its "attribute", we study two fairness criteria. For instance, in one of them, we deem a vertex set fair if for any two colors, the difference between the numbers of their occurrences does not exceed a given threshold. Fairness is, for instance, relevant when finding many-to-one matchings between students and colleges, voters and constituencies, and applicants and firms. Here colors may model sociodemographic attributes, party memberships, and qualifications, respectively. We show that finding a fair many-to-one matching is NP-hard even for three colors and maximum degree five. Our main contribution is the design of fixed-parameter tractable algorithms with respect to the number of vertices on the right side. Our algorithms make use of a variety of techniques including color coding. At the core lie integer linear programs encoding Hall like conditions. We establish the correctness of our integer programs, based on Frank's separation theorem [Frank, Discrete Math. 1982]. We further obtain complete complexity dichotomies regarding the number of colors and the maximum degree of each side. [ABSTRACT FROM AUTHOR]

Air pollution is known to be one of the major risk factors for premature morbidity and mortality globally, which are preventable. Therefore, the public is informed about air pollution through the Air Quality Index (AQI). The AQI represents integrated data of selected pollutants and produces a combined overall index for specific locations and time. The AQI algorithm generates a range of numbers and categories of colors that indicate likely health risks from air pollutants and the public's actions to minimize the risks. However, it lacks emerging evidence on chemical toxicity or composition. Hence, policymakers may also consider addinga toxicity matrix of fine particles to refine the algorithm, such as oxidative potential. Further, the risk is commonly communicated in numbers and not in color as dictated by the AQI. The AQI values and categories vary significantly between countries for the same pollution concentration, leading to confusion. Hence, we recommend developing a universal AQI (UAQI) with a consistent relationship between colors, concentrations, and toxicity to communicate air pollution risks to the public. Further, communication media should be encouraged to use universal color-coding rather than AQI values, i.e., numbers. Therefore, a global policy framework for regulatory authorities and policymakers is needed to communicate air pollution risk information consistently and to minimize public health exposure.

As a prominent visual phenomenon, the color environment influences the landscape design of the Lingnan region in three aspects: shape, color, and texture. The purpose of this paper is to examine the landscape nature of color by analyzing the psychological perception characteristics of color and the evolution of Lingnan’s color landscape system. We propose color clustering extraction methods for both single and batch Lingnan landscape images, combining them with color space conversion algorithms like RGB and YIQ to extract colors and segment Lingnan landscape images. We look at the performance parameters of various reconstructed images at various compression ratios. We also draw the performance convergence curves of the clustering algorithm, the JPEG, and the JPEG2000 algorithms to talk about how well they code. Taking the Lingnan region (Guangzhou) as the main object of analysis, we divide the regional color qualities and analyze the evolution and development of landscape color characteristics in the Lingnan region. Most of the Lingnan architectural landscapes have color brightness values in the medium-high range of 5-7. For wall color brightness, most of the brightness class level values are in the high brightness range of 7–10, followed by the medium brightness range of 4–7, and a small portion is in the low brightness range of 1-3.

For health, environmental, and animal welfare reasons, an increase in the consumption of meat in our diet is of great concern in today's society. Meat substitutes have been advocated for a long time as a solution to these problems and are evolving continuously with technological advancements. Despite these efforts, it is remarkable that meat alternatives only account for a small portion of the global meat market. As a result, we examined the factors that affect Flemish consumers' preferences for meat substitutes in Belgium using a discrete choice experiment. We also examined consumers' preferences after providing additional information, as well as the impact of color-coding certain attribute levels on their preferences. The study was conducted using a sample size of 162 participants selected via convenience sampling. The findings show that it is important to keep the sensory properties of meat substitutes similar to those of actual meat. The results also indicate that additional information regarding the environmental and health impact of meat consumption can help to promote meat substitutes. The traffic light color coding of the levels of saturated fat and ecofootprint attributes increases the preference for healthy and environmentally friendly alternatives. Finally, we observed that individual-level variations in the utility attributed to meat substitutes are explained significantly by age, gender, education, current diet group, and attitudinal factors. Overall, we can conclude that the promotion of meat substitutes can be achieved via a combined strategy that focuses on improving the taste, appearance, and nutritional profile of meat substitutes, as well as raising consumers' awareness of the environmental and health impact of meat consumption. [ABSTRACT FROM AUTHOR]

In France, national guidelines recommend early detection and management of overweight and obesity in children, with multi-year systematic generation of children's body mass index (BMI) curves in primary care. It is important for the parents to understand the BMI curves displayed in the child's health notebook and to become involved in the care with health professionals. The aim of the current study was to compare parents' understanding of a BMI curve displayed using color coding versus their understanding of the same curve displayed without color coding. An observational, cross-sectional, comparative study was performed between February 1, 2021 and November 15, 2021. Adult parents with at least one child attending primary school were included. Two questionnaires testing parents' understanding were completed: one showing BMI curves without color coding (five questions) and one showing BMI curve with color coding (five questions). The primary endpoint was the proportion of parents achieving fully correct answers. Comparisons of endpoints between the color-coded and non-color-coded curve were performed using the McNemar test. Factors associated with the primary endpoint were investigated by mixed logistic regression models with the subject as a random effect. The 109 participants (45.4% response rate) had an average age of 39.4 ± 6.6 years; 81.7% were women. A total of 214 complete questionnaires were compared: The proportion of participants with fully correct responses was significantly higher using the BMI curve with color coding compared to the curve without color coding (86.0% vs. 54.2%, p <0.0001). In multivariate analysis, the use of color coding was significantly associated with a higher likelihood of achieving fully correct responses (odds ratio: 5.9, 95% CI: 3.0–11.2, p <0.0001). The use of color coding improved parents' understanding of BMI curves. Further research should explore equally the benefits and risks associated with weight loss and mental health when using a colored BMI curve for the detection and management of overweight and obese children. [ABSTRACT FROM AUTHOR]

The acquisition of Chinese Characters (CCs) is challenging for learners. Chinese Semantic Radicals (SRs) are semantic components of CCs. The memorization of SRs facilitates the acquisition of CCs when learning Chinese as a second language. This study investigates the effectiveness of Visual Instructions (VIs) in the memorization of SRs by beginners. A preliminary study and three other studies have been conducted. The results have shown that the use of color-coded illustrations helps learners remember the meanings, shapes, and positions of SRs. This could be seen in the significantly increased accuracy of the responses in memory tests. These findings are an important contribution to research on VIs and on the memorization of SRs by beginners. [ABSTRACT FROM AUTHOR]

Extended Reality (XR) applications, which may encompass Augmented Reality (AR) and Virtual Reality (VR), commonly involve immersive virtual environments that are based on real physical environments. Transmitting the extensive color and depth image data for representing a physical environment over a communication network to create a corresponding immersive environment at a remote location is very challenging due to the enormous data volumes and the time constraints of real-time immersion. We explore semantic compression, which conveys the semantic meaning of the data through color-codes (CCs) to reduce the transmitted data volume. The creation of an immersive environment conventionally involves five steps (with corresponding output): calibration (single-frame point cloud), registration (registered point cloud), volume reconstruction (voxel frame), marching cubes (meshes), and rendering (3D environment). We develop the novel cXR+ semantic compression that splits the volume reconstruction into a client-side virtual network function (VNF) that represents the registered point cloud as CCs for network transmission to a server-side VNF that decodes the CCs to obtain the voxel frames so as to complete the volume reconstruction. We consider an analogous splitting of the calibration into two VNFs with Graph Coloring (GC) compression of the color and depth image data as a comparison benchmark. Additionally, we consider the transmission of the raw and JPG compressed point cloud data as well as the volume reconstruction at the client-side and subsequent transmission of the voxel frames as benchmarks. We conduct measurements of the compression (computing) time, transmission time, compression ratio, and reconstruction accuracy for real-world data sets so as to elucidate the trade-offs in employing voxel-based semantic compression for transmitting immersive environments over communication networks.

We provide here a brief outline of data on color vision in animals and humans, along with the history and methods used in studying it. Results from basic research in this area obtained using adaptive optics and scanning laser ophthalmoscopy (AOSLO) in combination with densitometry, phase-sensitive optical coherence tomography (AO-PSOCT), and calcium imaging (Ca2+ imaging) are described. These methods provided the first in vivo evidence for the mosaic of cones in the human retina, allowing maps of the locations of cones of three different types (L, M, S) to be built and human color perception in response to stimulation of single cones to be investigated. [ABSTRACT FROM AUTHOR]

Development of novel approaches to behavioral test data analysis is of considerable importance for both fundamental research and experimental neuropharmacology. Antipsychotic agents used to treat positive and negative symptoms in schizophrenia are of particular interest. Although antipsychotics exert potent effects on animal behavior in simple behavioral tests, they can be difficult to distinguish from other CNS-depressing agents, such as sedatives. In this paper, we propose color coding of video sequences as a method for the analysis of behavioral pattern structure in rats, using the effects of haloperidol, a typical antipsychotic, in the Open field test as an example. The study was carried out on outbred albino male rats weighing 250–300 g. Three-min video sequences of rat behavior in the Open field test were processed using Python and the OpenCV library in the Google Colab 3 environment. Color coding allowed the present (t = 0), near-future (t = 0.33 s), and the more distant-future (t = 1.66 s) location of an animal in the Open field arena to be marked with different colors and overlaid within a single frame. Using the proposed 3-timepoint color coding method, we were able to detect specific effects of haloperidol on animal behavioral patterns, which are undetectable via conventional techniques of behavioral data analysis in the Open field test. This method proved effective for data analysis and processing, and the results were in accordance with other author's data obtained using computerized and conventional visualization techniques. [ABSTRACT FROM AUTHOR]

We present new, faster pseudopolynomial time algorithms for the k-Subset Sum problem, defined as follows: given a set Z of n positive integers and k targets t 1 , … , t k , determine whether there exist k disjoint subsets Z 1 , ⋯ , Z k ⊆ Z , such that Σ (Z i) = t i , for i = 1 , … , k . Assuming t = max { t 1 , … , t k } is the maximum among the given targets, a standard dynamic programming approach based on Bellman’s algorithm can solve the problem in O (n t k) time. We build upon recent advances on Subset Sum due to Koiliaris and Xu, as well as Bringmann, in order to provide faster algorithms for k-Subset Sum. We devise two algorithms: a deterministic one of time complexity O ~ (n k / (k + 1) t k) and a randomised one of O ~ (n + t k) complexity. Additionally, we show how these algorithms can be modified in order to incorporate cardinality constraints enforced on the solution subsets. We further demonstrate how these algorithms can be used in order to cope with variations of k-Subset Sum, namely Subset Sum Ratio, k-Subset Sum Ratio and Multiple Subset Sum. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, rotating dominating set is an efficient method for balancing the energy consumption of nodes, and thereby extending the network operational time. This method can be abstracted as $k$ -Lifetime Dominating Set in bipartite graph, that partitions the set of graph vertices representing sensors into $k$ disjoint dominating sets. However, the considered problem has been proven to be NP-hard, and there is no hope of solving it in polynomial time unless P = NP. Existing studies mainly focus on developing approximation or heuristic algorithms, which usually cannot guarantee a solution for a given problem yes instance. In this study, we first propose a randomized algorithm that can generate a solution with guaranteed probability 1- $\varepsilon $ ( $0 < \varepsilon < 1$ ). Using the color coding method, we show that the randomized algorithm can be improved to guarantee the generation of a solution for a given problem yes instance in exponential time. Based on the idea of randomized partition, we further present a more practical centralized greedy algorithm, and then a distributed implementation. Simulation results indicate that the centralized algorithm can efficiently generate optimal solutions for almost all the given problem instances if the partition redundancy is above a certain limit. Compared with existing algorithm, the centralized algorithm increases the number of dominating sets by factors between 0% and 21%.

Color and spatial layout are important factors that affect users’ icon cognition and play a huge role in the visual search process of icons. Guided by the user’s interactive needs, this paper aims to improve the visual search efficiency of mobile map navigation icons. The mixed design within and between subjects is adopted through the combination of theoretical and experimental research, and the subjective questionnaire method is used to explore the research. This paper explores the visual search problem of mobile map navigation icons based on color coding and layout coding. The experimental results mainly include reaction time, accuracy rate, user experience, and statistical and variance analysis. The results show that the layout of the mobile map navigation icons significantly impacts the user’s visual search. The navigation icons that use color for layout coding have the highest visual search efficiency and better user experience. Among the icons, the layout with regular color distribution and a larger area of the same color has the highest visual search efficiency for users and the best user experience; the visual search efficiency of navigation icons using color for layout coding is significantly higher than that of mobile map navigation icons.Relevance to industry: The user scale of mobile information maps is huge and the usage rate is high, but the large number of navigation icons increases the burden of user information identification and acquisition. As a result, the efficiency of user information acquisition is low, and the user experience is reduced. A clear, easy-to-search navigation icon design can enhance the user experience of the entire product. The results of this research provide theoretical support and practical guidance for the design optimization and improvement of mobile map navigation icons.

Communication with other road users is very essential for autonomous as they might drive slower and the person on the driver's seat does not necessarily look on the street. To evaluate exterior displays, we build a full‐scale mock‐up with a RGB LEDs matrix display with 80 cm × 40 cm (128 × 64 pixel). Even text with a height of 10 cm was judged as readable from 50 m distance. Other results were the identification of signs with 40 cm height from 50 m. This is in accordance with common traffic sign standards. [ABSTRACT FROM AUTHOR]

Background. Currently, the introduction of telemedicine systems is one of the important factors in improving the efficiency of medical care. The paper considers the problem of building systems for multi-parametric telemedicine monitoring of human health. Data sources are various information-measuring systems. The task of building software for integrating data from various sources, their analysis and display is outlined. Materials and methods. Some similar telemedicine systems described in Russian and foreign sources are analyzed. To display data, it is proposed to organize a graphical interface according to a hierarchical principle, use mnemonic symbols and color coding of parameter values. Results. An application architecture is proposed for processing data from multiparameter telemedicine monitoring and implementing measurement data alert systems about the state of human health. An application algorithm has been developed that allows integrating data from various sources, analyzing and displaying relevant data using mnemonic symbols and color coding, depending on whether the parameter value is within or outside the normal range. Conclusions. To build a telemedicine system for multi-parameter monitoring, it is required to use heterogeneous data that must be processed and analyzed by software and displayed in an integral form.

Previous work has identified attribute level overlap and level color coding as effective and attractive strategies to reduce task complexity and improve behavioral efficiency in discrete choice experiments (DCEs). However, the simultaneous and combined impact of level overlap and level color coding on attribute non-attendance and choice consistency has not yet been investigated. To address this limitation and to strengthen the available evidence base, this paper re-analyzed an existing randomized controlled DCE from the Netherlands (N = 2,731) and analyzed a new randomized controlled DCE conducted in the United Kingdom (N = 3,084) using heteroskedastic attribute non-attendance mixed logit models. Both randomized controlled experiments were based on a relatively complex instrument with 5 attributes with 5 levels each and the results from both experiments were remarkably similar. In the base-case study arms without level overlap and color coding, only about half of the attributes are attended to. Level color coding as a stand-alone strategy improves attribute attendance but reduces respondents' choice consistency. In contrast, level overlap as a stand-alone strategy improves attribute attendance while simultaneously increasing respondents' choice consistency. The combination of level overlap and color coding is even more effective: it results in approximately full attribute attendance and a 30% increase in respondents' choice consistency. Experimental designs with level overlap are therefore recommended as a default design strategy and level color coding recommended to further increase respondents' behavioral efficiency in complex DCEs. • This paper (re)analyzes two large randomized controlled DCEs with a total of 11 study arms and 5,815 respondents. • Without level overlap and color coding, respondents attend to about half of the included attributes. • With level overlap and color coding, respondents attend to (almost) all attributes and their choice consistency increases by about 30%. • Not all color coding schemes are equally effective and some have stronger distortionary effects than others. [ABSTRACT FROM AUTHOR]

Retinal drawing with a color-coding system brings uniformity in representation of fundus findings so that clinician can decipher various lesions on a two-dimensional drawing. Existing color coding addresses most of the common retinal pathologies including preretinal, intraretinal, and subretinal lesions. However, with the advent of various imaging modalities there is deeper understanding of microanatomy of retina and associated pathologies. With this, there appears further need of newer set of color coding to include the minute details of fundus findings clinically. Through this article, we discuss few common pathologies at different levels of retina layers with color-coding dilemma which calls for a better preciseness in its clinical representations.

Contribution: A new operational definition of series connections is given based on elements belonging to the same two meshes, which is properly dual to the usual definition of parallel elements being connected to the same two nodes. Furthermore, computer-based exercises have been developed and tested to teach students about such connections in gateway linear circuits courses, using color coding of nodes and meshes as a pedagogical device. Background: Series and parallel connections are a crucial but difficult concept. Existing textbooks give them limited attention, resulting in later difficulties learning circuit analysis. Research Questions: RQ1: Can an improved definition of series elements aid student understanding and student satisfaction? RQ2: Can a computer-based “game” lead to effective mastery and student satisfaction at a wide range of institutions, including minority-serving ones? Methodology: Standard and new definitions were elaborated in a multiple-choice tutorial. A game was developed focusing on identifying series and parallel connections, with color coding of both nodes and meshes. Student learning was assessed over eight years using pretest and posttest in 14 varied institutions. Student opinions were assessed using several types of surveys. Findings: Strong learning gains were observed every semester from built-in pretest and posttest, with average scores of 28% and 87%, respectively. Large improvements were observed at every institution including five minority-serving ones. The posttest score is increased by a statistically significant amount after introducing the new definition of series elements. Students preferred the new definition of series and recommended its use, and very strongly endorsed color coding. [ABSTRACT FROM AUTHOR]

Digital learning increasingly makes use of realistic visualizations, although realism can be demanding for learners. Color coding is a popular way of helping learners understand visualizations and has been found to aid in learning with detailed visualizations. However, previous research has shown that color coding must not always be an effective aid, and that it even may reduce retention when used with simple visualizations. This study assessed whether the presence of color coding in learning tests has an effect after having learned using a detailed visualization that either featured color cues or one that did not. The results indicate that color coding helps learners the most if the learning tests also feature color coding. Importantly, learning with color-coded visualizations and being tested without color cues leads to the worst results in retention and transfer tests. Regarding transfer, color coding in the testing visualization boosts performance regardless of the presence of color cues in the learning phase. The results of this study challenge popular perspectives aiming at optimizing learning by removing potential sources of difficulty. Depending on the learning test, it may be more effective to keep a certain level of difficulty in the learning task when learning with digital media. [ABSTRACT FROM AUTHOR]

Introduction: Errors are a byproduct of human information processing or cognitive functioning. Although everyone is disposed to an error while performing various activities, individual differences in cognitive abilities can lead to various types and rates of errors committed in similar situations. Human errors are one of the most important challenges in work environments, including health care systems, wherein such errors are abundantly occurring. Errors in the delivery of correct medications due to the resemblance in appearance and name are thus one of the cognitive errors that come about in health care systems. The main purpose of this systematic review was to evaluate evidence and approaches recently practiced to reduce medication errors caused by the use of look-alike-sound-alike (LASA) medications. Material and Methods: The study was conducted on August 30, 2018, through searches in the databases of PubMed and Embase, all available years, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) instructions. The searches were done in the titles or abstracts of the articles using the intended terms and the Medical Subject Headings (MeSH) index in combination. These studies were selected based on the inclusion and exclusion criteria and then categorized based on the type of interventions and outputs. Finally, the data were analyzed descriptively. Results: The research designs and methods varied widely among the studies. There were also discrepancies in the number of participants, number of tests, type of medications, and test conditions. The approaches examined in these studies were tall-man lettering, color-coding, label background variations, and use of signs and symbols. Accordingly, 11 studies had utilized tall-man lettering and the most important reported in all articles were “error rate” and “response times”. As well, a wide range of medication names had been tested. It should be noted that medication Conclusion: errors have different dimensions, but the errors caused by the look-alike-sound-alike (LASA) medications and the effect of tall-man lettering of medication name were only investigated in the present study. Laboratory studies in this respect have shown that tall-man lettering contributes to mitigating the rate of errors, which might be due to the better legibility of labels, but evaluations in real work environments are needed to reinforce this conclusion. There is also insufficient evidence to support color-coding, as well as several other approaches such as use of signs and symbols. Because of the novelty of the studies in this field, no uniform mechanism has been so far introduced.

In the traditional non-invasive load monitoring (NILM) algorithms, the identification accuracy is enhanced with the increased network scale while sacrificing the calculation speed, which restricts the efficiency of the load identification. In this study, a multi-feature (active/reactive power and current peak-to-peak value) fusion algorithm is proposed, which can achieve enhanced identification accuracy with a smaller network scale while maintaining the calculation speed. The features of the power and current amplitudes of the loads are transformed into the values of red-green-blue (RGB) color channels by color coding and then fused into the V-I trajectory features. After that, the true-color feature image with higher discrimination is generated and input into the convolutional neural network (CNN). The testing results on the PLAID data set indicate that in comparison with the traditional load identification algorithm, the algorithm proposed in this study performs higher identification accuracy with a smaller neural network parameter scale, which significantly improves the identification efficiency.

In the present study, we tested the effectiveness of color coding on the programming learning of students who were learning from video lectures. Effectiveness was measured using multimodal physiological measures, combining eye tracking and electroencephalography (EEG). Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions (color-coded vs. grayscale). The participants' eye tracking and EEG signals were recorded while watching the assigned video, and their learning performance was subsequently assessed. The results showed that the color-coded design was more beneficial than the grayscale design, as indicated by smaller pupil diameter, shorter fixation duration, higher EEG theta and alpha band power, lower EEG cognitive load, and better learning performance. The present findings have practical implications for designing slide-based programming learning video lectures; slides should highlight the format of the program code using color coding. [ABSTRACT FROM AUTHOR]

In the present study, we tested the effectiveness of color coding on the programming learning of students who were learning from video lectures. Effectiveness was measured using multimodal physiological measures, combining eye tracking and electroencephalography (EEG). Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions (color-coded vs. grayscale). The participants’ eye tracking and EEG signals were recorded while watching the assigned video, and their learning performance was subsequently assessed. The results showed that the color-coded design was more beneficial than the grayscale design, as indicated by smaller pupil diameter, shorter fixation duration, higher EEG theta and alpha band power, lower EEG cognitive load, and better learning performance. The present findings have practical implications for designing slide-based programming learning video lectures; slides should highlight the format of the program code using color coding.

Objectives, purpose, or aim: We report a two-part wayfinding intervention, considering four quality criteria (visibility, usability, efficiency and overall effectiveness) from staff perspectives. Background: Few studies to date have explored wayfinding in the Emergency Department (ED). Yet, as ED usage continues to grow, effective wayfinding in these high-stress, fast-paced environments is likely to become increasingly important. At an adult ED located in the U.S. Southeast, wayfinding has been a persistent problem. We subsequently developed a two-part wayfinding intervention: colored routes to key destinations in the ED and corresponding visitor badges. Methods: Quality criteria were formulated using the Donabedian model: visibility (structure), usability (process), efficiency (process), and overall effectiveness (outcome). Assessments consisted of staff surveys, which were distributed from March to early April 2019. Results: The strong ratings across quality criteria, added to affirmative comments from staff, provide evidence that the color coding system made a positive impact on wayfinding. Conclusions: While the results should be generalized with caution, the two-part intervention may be highly portable to other contexts. Future studies might examine the effect of colored routes alone. They might illuminate relations between structure, process, and outcomes as they relate to the assessment of wayfinding. They might also expand wayfinding quality criteria. Ultimately, such studies should improve not only the productivity but also the accessibility and user experience of the ED. [ABSTRACT FROM AUTHOR]

Retinal drawing with a color-coding system brings uniformity in representation of fundus findings so that clinician can decipher various lesions on a two-dimensional drawing. Existing color coding addresses most of the common retinal pathologies including preretinal, intraretinal, and subretinal lesions. However, with the advent of various imaging modalities there is deeper understanding of microanatomy of retina and associated pathologies. With this, there appears further need of newer set of color coding to include the minute details of fundus findings clinically. Through this article, we discuss few common pathologies at different levels of retina layers with color-coding dilemma which calls for a better preciseness in its clinical representations. [ABSTRACT FROM AUTHOR]

This article presents the description of color designations with national and cultural content in the Ukrainian, Russian, Bulgarian, Romanian languages, the speakers of which have long inhabited the multi-ethnic region of Danube. For this purpose associations of Ukrainians, Russian Moldovans, Bulgarians for main colors were analyzed. The perception of color and its choice by different ethnic groups depends not only on the language of the individual, but on cultural and historical features. Color designations in different languages have both international semantics and various connotations. Knowledge of such information contributes to the mutual enrichment of the linguistic and cultural experience of speakers and the preservation of the ethnic characteristics of the peoples of our region.

We study an important case of integer linear programs (ILPs) of the form max{ cT x | scrA x = b, l leq x leq u, x in Znt} with nt variables and lower and upper bounds ell, u in Znt. In n-fold ILPs nonzero entries only appear in the first r rows of the matrix scrA and in small blocks of size s times t along the diagonal underneath. Despite this restriction, many optimization problems can be expressed in this form. It is known that n-fold ILPs are fixed-parameter tractable (FPT) regarding the parameters s, r, and Delta, where Delta is the greatest absolute value of any entry in scrA. The state-of-the-art technique is a local search algorithm that subsequently moves in an improving direction where the number of iterations and the search for such an improving direction each take time Omega (n). This leads to a running time quadratic in n. We introduce a technique based on color coding which allows us to compute these improving directions in logarithmic time after a single initialization step. This yields an algorithm for n-fold ILPs with a running time that is near-linear in nt, the number of variables. More precisely, our algorithm runs in time (rsDelta)scrO (r2s+s2)L2nt logscrO (1)(nt), where L is the encoding length of the largest integer in the input. Further, in contrast to the algorithms in recent literature, we do not need to solve the LP relaxation in order to handle unbounded variables. Instead we give a structural lemma to introduce appropriate bounds. On the other hand, if we are given such an LP solution, the running time can be decreased by a factor of L. [ABSTRACT FROM AUTHOR]

Compression of point clouds has so far been confined to coding the positions of a discrete set of points in space and the attributes of those discrete points. We introduce an alternative approach based on volumetric functions that are functions defined not just on a finite set of points but throughout space. As in regression analysis, volumetric functions are continuous functions that are able to interpolate values on a finite set of points as linear combinations of continuous basis functions. Using a B-spline wavelet basis, we are able to code volumetric functions representing both geometry and attributes. Geometry compression is addressed in Part II of this paper, while attribute compression is addressed in Part I. Attributes are represented by a volumetric function whose coefficients can be regarded as a critically sampled orthonormal transform that generalizes the recent successful Region-Adaptive Hierarchical (or Haar) Transform to higher orders. Experimental results show that attribute compression using higher order volumetric functions is an improvement over the first-order functions used in the emerging MPEG point cloud compression standard. [ABSTRACT FROM AUTHOR]

We study an important case of integer linear programs (ILPs) of the form max{cTx | Ax = b, l ≤ x ≤ u, xZnt} with nt variables and lower and upper bounds l, u ε Znt. In n-fold ILPs nonzero entries only appear in the first r rows of the matrix A and in small blocks of size s \times t along the diagonal underneath. Despite this restriction, many optimization problems can be expressed in this form. It is known that n-fold ILPs are fixed-parameter tractable (FPT) regarding the parameters s, r, and Delta, where Delta is the greatest absolute value of any entry in A. The state-of-the-art technique is a local search algorithm that subsequently moves in an improving direction where the number of iterations and the search for such an improving direction each take time Omega (n). This leads to a running time quadratic in n. We introduce a technique based on color coding which allows us to compute these improving directions in logarithmic time after a single initialization step. This yields an algorithm for n-fold ILPs with a running time that is near-linear in nt, the number of variables. More precisely, our algorithm runs in time (rs Δ)O(r²s+s²) L²nt logO(1) (nt), where L is the encoding length of the largest integer in the input. Further, in contrast to the algorithms in recent literature, we do not need to solve the LP relaxation in order to handle unbounded variables. Instead we give a structural lemma to introduce appropriate bounds. On the other hand, if we are given such an LP solution, the running time can be decreased by a factor of L. [ABSTRACT FROM AUTHOR]

The fruit fly Drosophila melanogaster can process chromatic information for true color vision and spectral preference. Spectral information is initially detected by a few distinct photoreceptor channels with different spectral sensitivities and is processed through the visual circuit. The neuroanatomical bases of the circuit are emerging. However, only little information is available in chromatic response properties of higher visual neurons from this important model organism. We used in vivo whole-cell patch-clamp recordings in response to monochromatic light stimuli ranging from 300 to 650 nm with 25-nm steps. We characterized the chromatic response of 33 higher visual neurons, including their general response type and their wavelength tuning. Color-opponent-type responses that had been typically observed in primates and bees were not identified. Instead, the majority of neurons showed excitatory responses to broadband wavelengths. The UV (300–375 nm) and middle wavelength (425–575 nm) ranges could be separated at the population level owing to neurons that preferentially responded to a specific wavelength range. Our results provide a first mapping of chromatic information processing in higher visual neurons of D. melanogaster that is a suitable model for exploring how color-opponent neural mechanisms are implemented in the visual circuits. [ABSTRACT FROM AUTHOR]