Reviewerly/exHarmony huggingface dataset:
Effects of Age and Fixation Location on Face Identification

Face identification declines with age, potentially because older adults (OA) make less use of information around the eyes, which has been shown to drive face identification accuracy. Previous studies using the forced initial fixation approach in younger adults (YA; Peterson & Eckstein, 2013) showed that face identification accuracy could be modulated by initial fixation point. The current study used the forced initial fixation approach with both YA and OA to investigate whether fixating towards the eye and eyebrow region could improve face recognition performance in older adults. 27 YA (M = 25.7, SD = 0.37) and 41 OA (M = 61.1, SD = 5.28) completed this online study. Ten target faces of Caucasian females were selected from the FACES database. On each trial, participants view a fixation point (500 ms) located in one of four randomly, presented locations distributed equidistant between the forehead and the mouth. Participants then viewed a target face for 200 ms, followed by a post-target mask, after which participants chose the target face out of ten options. Overall, OA showed worse face identification performance than YA. Both age groups showed a similar overall pattern of results as found in Peterson and Eckstein (2013), with best performance for fixation points near the eyes and nose; however, age group also interacted with fixation condition: OA showed greater improvement in face recognition when the initial forced location moved downwards from the forehead to the eye or nose regions, whereas the performance of YA improved by a much smaller amount, and performance differences between YA and OA varied considerably across different initial fixation points. These results suggest that altering initial fixations and/or attentional focus to more informative regions of the face may provide a mechanism to enhance face perception in OA.
Single- and two-photon wave-particle superpositions: Theory and experiment

Simultaneous observation of the wave and particle natures of a quantum object under one experimental arrangement represents the latest development regarding wave-particle duality. In this work, we propose a simple scheme using linear-optics devices to observe either the particle nature or wave nature or the wave-particle superposition (WPS) of photons by controlling a relevant classical parameter. Our setup consists of two stages, the preparation and measurement stages, with the latter stage containing an additional classical variable whose value will be given only after the first stage in order to avoid any possible communication between the two stages and thus rule out the classical hidden-variable model. We not only develop the theory but also perform the corresponding experiments. The experimental observations perfectly agree with the theoretical predictions. Our findings are the following. The frequency (wavelength) of both single- and two-photon systems is independent of whether the photon(s) is wavelike or in a WPS state, with the common fact being that the frequency (wavelength) of two photons as a whole entity is twice (half) that of a single photon. As for the interference-pattern visibility, it is always lower in the case of WPS than in the case of a wavelike state for a single photon as well as for two photons. Remarkably, with a given value of the control parameter, the interference visibility in the case of WPS is always higher in the single-photon scenario than in the two-photon one. Although here we are dealing with photons, the obtained results apply equally well to matter particles.
Research on the Application of Storytelling in Display Spaces

The 21st century is a very perceptual era, the interpretation of happiness and games are highlighted, so interactive space displays are of great significance. In the interactive display space, significant changes are necessitated, driving rapid transformations in display methods. Modern exhibition spaces have shifted from mere listing, explaining, and introducing items to adopting narrative display themes that communicate content and materials in an emotional and vivid manner. This has led to the emergence of a new display method, “displaying the content through stories,” which imbues the experience with fun and interest. The use of narrative techniques in display spaces allows for the simultaneous fulfillment of visitors’ desires to acquire information about the displayed content while offering a more expressive and enjoyable experience. It successfully meets the dual needs of visitors, providing both fun and information at the same time. In addition, it also has the advantage of technology convergence. Through the use of digital media technology, the content of the story can be expanded, allowing visitors to participate in the interactive display, so as to achieve an immersive visiting experience.
Penalized wavelet nonparametric univariate logistic regression for irregular spaced data

AbstractThis paper concerns the study of a non-smooth logistic regression function. The focus is on a high-dimensional binary response case by penalizing the decomposition of the unknown logit regression function on a wavelet basis of functions evaluated on the sampling design. Sample sizes are arbitrary (not necessarily dyadic) and we consider general designs. We study separable wavelet estimators, exploiting sparsity of wavelet decompositions for signals belonging to homogeneous Besov spaces, and using efficient iterative proximal gradient descent algorithms. We also discuss a level by level block wavelet penalization technique, leading to a type of regularization in multiple logistic regression with grouped predictors. Theoretical and numerical properties of the proposed estimators are investigated. A simulation study examines the empirical performance of the proposed procedures, and real data applications demonstrate their effectiveness.Keywords: Nonparametric binary regressionpenalized log-likelihoodproximal algorithmsthresholdingwaveletsMathematics Subject Classifications: 62H12MSC 60K35MSC 62G08 AcknowledgmentsThe authors thank the reviewers for their comments on the original version of the paper. Part of this work was completed while A. Antoniadis and I. Gijbels were visiting the Istituto per le Applicazioni del Calcolo ‘M. Picone’, National Research Council, Naples, Italy. I. De Feis acknowledges the INdAM-GNCS 2023 Project ‘Metodi computazionali per la modellizzazione e la previsione di malattie neurodegenerative' and the project 'TAILOR (H2020-ICT-48 GA: 952215)'.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingI. Gijbels gratefully acknowledges financial support from the C16/20/002 project of the Research Fund KU Leuven, Belgium.
Klasifikasi Citra Mengkudu Berdasarkan Perhitungan Jarak Piksel pada Algoritma K-Nearest Neighbour

Noni fruit is included in exported food commodities in Indonesia. The size of noni fruit, based on human vision, generally has varied shapes with distinctive textures and various patterns, so that the process of filtering fruit based on color and shape can be done in large quantities. In this study, K-Nearest Neighbor (KNN) has been implemented as a classification algorithm because it has advantages in classifying images and is resistant to noise. Noni imagery is a personal image taken from a noni garden in the morning and undergoes a background subtraction process. The imagery quality improvement technique uses the Hue Saturation Value (HSV) color feature and the Gray Level Co-Occurrence Matrix (GLCM) characteristic feature. KNN accuracy without features is lower than using HSV and GLCM features. From the experimental results, the highest accuracy was obtained using HSV-GLCM at K is 1 and d is 1, namely 95%, while the lowest accuracy was 55% using KNN only at K is 5 and d is 8.
Strategic Planning as a Way to Increase the Competitiveness of Universities of the Novosibirsk Region

After the events that occured in February 2022, due to the imposition of sanctions, Russian education was on the verge of changes. An essential part of the international educational process and an increase of competitiveness of universities is the system of ranking educational institutions. The object of the study is the level of development of Russian universities, the subject of the study is the economic and organizational aspects of the implementation of a set of measures aimed at increasing the competitiveness of Russian universities. The purpose of the article is t analyze the level of development of universities, quotes in rankings and provide an approach to improving competitiveness. In this article, special and general scientific methods are used, which include: methods of matching and comparison, systematization and generalization, as well as various types of analysis: statistical, factorial, structural-functional, historiographic and others. The methodological framework used in the research is based on quotations in university rankings. Universities compete with each other in the market of educational services, which makes it necessary to intensify efforts to find new approaches to creating a strategy to increase competitiveness. Each university, increasing its competitiveness, contributes not only to its own development, but also to the development of the country. By improving the rankings in the domestic and international market of educational services, universities ensure an inflow of new investments, increase their competitiveness, and achieve strategically important goals in the field of higher education. Universities can implement this approach through the introduction of development programs and projects. A model and a method are proposed, that allow to achieve the set goals. Universities are included in the system of higher education, which is the basis for the socio-economic and scientific and technological development of the state. One of the key factors of the knowledge economy is human capital, which is formed by the higher education. In order to achieve the goals in the field of higher education and increase competitiveness, universities need to create their own programs and development projects based on project management methods.
Design and Implementation of Digital Circuit Virtual Simulation Experimental System Based on Serious Games

Serious games are used in medical, training, the military, and other sectors as an innovative teaching tool. This paper incorporates serious games into digital circuit simulation experiments, creates a virtual simulation experiment environment with rich sensory experience and good interactive experience, and addresses the recent problems of poor interactivity and low immersion in digital circuit simulation experiment software. To begin, various classical experiments in digital circuits are chosen as virtual simulation objects to build realistic virtual experiment scenes and implement scene control and circuit connection functionalities. Second, each circuit's logic analysis and algorithm processing are performed in order to replicate output feedback and experimental phenomena. To lessen user cognitive load, gesture detection and identification are performed using the Media Pipe architecture, and a gesture connection function is implemented. Finally, add registration and login functions, experiment with scene roaming, and other functions to improve the system. The digital circuit virtual simulation experiment system based on serious games offers a novel approach to digital circuit experimentation.
An Identity-Based Adaptor Signature Scheme and its Applications in the Blockchain System

Adaptor signature, as a new emerging cryptographic primitive, has become one promising method to mitigate the scalability issue on blockchain. It can transform an incomplete signature into a complete signature by revealing the witness of a pre-set hard relation, which can be applied to atomic swap, payment channel, payment hub, and other blockchain scenarios. Recently, a general transformation for constructing adaptor signatures has been proposed for some signature schemes with specific structures, e.g., Schnorr, ECDSA, SM2 signatures. However, we note that there is no identity-based adaptor signa-ture method so far. In this paper, we put forward an adaptor signature scheme for the identity-based signature scheme in the IEEE P1363 standard. Then, we formally prove the security of our scheme under the random oracle model. We also present the computation and communication costs, compared with other adaptor signatures. Finally, we show our scheme's potential use in atomic swaps and payment channel networks of blockchain.
Multi-UAV Cooperative Trajectory Planning Based on the Modified Cheetah Optimization Algorithm

The capacity for autonomous functionality serves as the fundamental ability and driving force for the cross-generational upgrading of unmanned aerial vehicles (UAVs). With the disruptive transformation of artificial intelligence technology, autonomous trajectory planning based on intelligent algorithms has emerged as a key technique for enhancing UAVs’ capacity for autonomous behavior, thus holding significant research value. To address the challenges of UAV trajectory planning in complex 3D environments, this paper proposes a multi-UAV cooperative trajectory-planning method based on a Modified Cheetah Optimization (MCO) algorithm. Firstly, a spatiotemporal cooperative trajectory planning model is established, incorporating UAV-cooperative constraints and performance constraints. Evaluation criteria, including fuel consumption, altitude, and threat distribution field cost functions, are introduced. Then, based on its parent Cheetah Optimization (CO) algorithm, the MCO algorithm incorporates a logistic chaotic mapping strategy and an adaptive search agent strategy, thereby improving the home-returning mechanism. Finally, extensive simulation experiments are conducted using a considerably large test dataset containing functions with the following four characteristics: unimodal, multimodal, separable, and inseparable. Meanwhile, a strategy for dimensionality reduction searching is employed to solve the problem of autonomous trajectory planning in real-world scenarios. The results of a conducted simulation demonstrate that the MCO algorithm outperforms several other related algorithms, showcasing smaller trajectory costs, a faster convergence speed, and stabler performance. The proposed algorithm exhibits a certain degree of correctness, effectiveness, and advancement in solving the problem of multi-UAV cooperative trajectory planning.
Real-Time Detection of Distracted Driving Behaviors Using Naturalistic Driving Study Data

Distracted driving seriously affects traffic safety and is one of the main causes of traffic accidents. In this study, a convolutional neural network (CNN) real-time detection method is proposed to detect distracted driving behaviors based on naturalistic driving experimental data. The distracted driving behaviors were categorized into using cell phone, makeup, diet and water (i.e., eating and drinking); chatting with passengers; and the normal (undistracted) driving behavior as a reference. The results show that (1) the correct detection rate for the categories of using cell phone (84.0%), makeup (77.0%), diet and water (82.0%) was about 80%; and (2) the detection accuracies of normal driving behavior (36.0%) and chatting with passengers (55.0%) were relatively low due to the similarity of these two types of behaviors being high. The findings of this paper suggest that the AlexNet model could be specifically appropriate and effective for real-time distraction detection.
Study on the Career Development of Young Teachers in Vocational Colleges

The quality of the teaching staff is crucial to the development of vocational education. Skilled and knowledgeable teachers can provide students with specialized technical knowledge and practical skills. In addition to teaching, teachers also act as mentors in providing guidance and support in all areas to students. However, the development of young teachers faces many problems, such as unclear career plans and a lack of attention to operational skills. This paper analyzes the research findings of past scholars and uses a questionnaire to analyze the problems faced by young teachers in their career development. Based on this, this paper puts forward some targeted suggestions, which can provide guidelines for the career development of young teachers.
P‐56: An Advanced High Dynamic Range Display Technology with Power Saving Algorithm of Adaptive Real‐time Controllable Backlight

An advanced high dynamic range (HDR) liquid crystal display (LCD) with the excellent performance was developed. The HDR Display technology can enhance the contrast ratio of pictures and reduce power consumption by utilizing adaptive controlled dynamic backlight. Improved methods about simplification of lookup tables (LUT), improvement of accuracy, and maintenance of details and chroma were studied, which make it a promising technique for displays.
SELF-EFFICACY AND INDONESIAN JUNIOR HIGH SCHOOL STUDENTS’ READING ABILITY IN ONLINE CLASSES

Self-efficacy in reading is considered to be the cause and result of academic achievement, especially in online learning where students need to learn independently. In this study, the researchers attempted to find out the impacts of self-efficacy on the reading ability of 9th-grade students at SMP 5 Purwokerto during online learning. There were 32 students from class 9A who participated in this study. The research question was: What is the perceived effect of self-efficacy on the reading ability of 9th-grade students at SMP 5 Purwokerto? The researchers used the qualitative method with two research instruments. The results reveal that 9th-grade students have a high level of self-efficacy, can find solutions to every problem, and read a lot of new things from the internet, newspapers, novels, or magazines. Online classes, therefore, bring students’ independence to find solutions from the problems. This study contributes to learning English on reading skills during online school.
READINESS OF EARLY CHILDHOOD EDUCATION TEACHERS TO ATTEND TRAINING THROUGH DISTANCE LEARNING

Research related to distance learning for students has been widely carried out, contrary to research related to teachers. The lack of opportunities and facilities for early childhood education teachers to develop their competencies is the background for the theme of this research. This article will be focused on explaining the readiness of Early Childhood Education teachers to face training conducted through distance learning. This research was conducted through a survey method by sending questionnaires to 409 participants. Participants are teachers or assistants from SPS, Playgroups and Kindergartens. The results of this study indicate that most of the participants are interested in participating in distance learning. This shows the high motivation of the participants to improve competence through distance learning. Various obstacles that may be faced cause participants to have difficulty accessing distance learning.
Policy-Based Method for Applying OAuth 2.0-Based Security Profiles

Two problems occur when an authorization server is utilized for a use case where a different security profile needs to be applied to a unique client request for accessing a distinct type of an API, such as open banking. A security profile can be applied to a client request by using the settings of an authorization server and client. However, this method can only apply the same security profile to all client requests. Therefore, multiple authorization servers or isolated environments, such as realms of an authorization server, are needed to apply a different security profile. However, this increases managerial costs for the authorization server administration. Moreover, new settings and logic need to be added to an authorization server if the existing client settings are inadequate for applying a security profile, which requires modification of an authorization server's source code. We aims to propose the policy-based method that resolves these problems. The proposed method does not completely rely on the settings of a client and can determine an applied security profile using a policy and the context of the client's request. Therefore, only one authorization server or isolated environment, such as a realm of an authorization server, is required to support multiple different security profiles. Additionally, the proposed method can implement a security profile as a pluggable software module. Thus, the source code of the authorization server need not be modified. The proposed method and Financial-grade application programming interface (FAPI) security profiles were implemented in Keycloak, which is an open-source identity and access management solution, and evaluation scenarios were executed. The results of the evaluation confirmed that the proposed method resolves these problems. The implementation has been contributed to Keycloak, making the proposed method and FAPI security profiles publicly available.
3D Vehicle Detection for Autonomous Buses

The development of automatic driving technology and Advanced Driver Assistance Systems (ADAS) has become more and more mature, and has led to the development of 3D object detection technologies and discussions. Most of the researches are focus on the applications of small cars, but not common in large vehicles, such as buses and trucks, although such applications are more important for them. Therefore, this study mainly uses the bus data to verify the feasibility of the existed model, and by adjusting the loss function, the prediction accuracy of the class and bounding box can be improved. Based on our experimental results, we found that the model trained by KITTI dataset can predict acceptable result refers to the input images from the bus viewpoint. As a result, we can expect that the ADAS for large vehicles can be implemented based on the sample model structure, and its accuracy is able to be improved by fine-tuning based on more large vehicle viewpoint data.
Towards Assessment of Practicality of Introductory Programming Course Using Vocabulary of Textbooks, Assignments, and Actual Projects

In an assignment-based introductory programming course, a teacher makes a daily class plan based on a textbook and assigns tasks to the students. Assignments are prepared by the teacher so that students can have a better understanding of programming language constructs explained in the course. On the other hand, it is unclear how those language constructs are useful for practical programming tasks. To analyze the practicality of a programming course, this study proposes to compare the vocabularies of code used in textbooks, assignments, and regular programming tasks. If the vocabularies of the textbooks and assignments are closer to that of source code in actual projects, the programming course is considered more practical. As a case study, we have applied the method to evaluate a programming course focusing on data science for graduate students. The result revealed inconsistency between the programming language constructs taught in the course and frequently used in data analysis programs on the Kaggle platform.