Reviewerly/exHarmony huggingface dataset:
Improving Nighttime Driving-Scene Segmentation via Dual Image-adaptive Learnable Filters

Semantic segmentation on driving-scene images is vital for autonomous driving. Although encouraging performance has been achieved on daytime images, the performance on nighttime images are less satisfactory due to the insufficient exposure and the lack of labeled data. To address these issues, we present an add-on module called dual image-adaptive learnable filters (DIAL-Filters) to improve the semantic segmentation in nighttime driving conditions, aiming at exploiting the intrinsic features of driving-scene images under different illuminations. DIAL-Filters consist of two parts, including an image-adaptive processing module (IAPM) and a learnable guided filter (LGF). With DIAL-Filters, we design both unsupervised and supervised frameworks for nighttime driving-scene segmentation, which can be trained in an end-to-end manner. Specifically, the IAPM module consists of a small convolutional neural network with a set of differentiable image filters, where each image can be adaptively enhanced for better segmentation with respect to the different illuminations. The LGF is employed to enhance the output of segmentation network to get the final segmentation result. The DIAL-Filters are light-weight and efficient and they can be readily applied for both daytime and nighttime images. Our experiments show that DAIL-Filters can significantly improve the supervised segmentation performance on ACDC_Night and NightCity datasets, while it demonstrates the state-of-the-art performance on unsupervised nighttime semantic segmentation on Dark Zurich and Nighttime Driving testbeds.
Segmentation Guided Deep HDR Deghosting

We present a motion segmentation guided convolutional neural network (CNN) approach for high dynamic range (HDR) image deghosting. First, we segment the moving regions in the input sequence using a CNN. Then, we merge static and moving regions separately with different fusion networks and combine fused features to generate the final ghost-free HDR image. Our motion segmentation guided HDR fusion approach offers significant advantages over existing HDR deghosting methods. First, by segmenting the input sequence into static and moving regions, our proposed approach learns effective fusion rules for various challenging saturation and motion types. Second, we introduce a novel memory network that accumulates the necessary features required to generate plausible details in the saturated regions. The proposed method outperforms nine existing state-of-the-art methods on two publicly available datasets and generates visually pleasing ghost-free HDR results. We also present a large-scale motion segmentation dataset of 3683 varying exposure images to benefit the research community.
GP22: A Car Styling Dataset for Automotive Designers

An automated design data archiving could reduce the time wasted by designers from working creatively and effectively. Though many datasets on classifying, detecting, and instance segmenting on car exterior exist, these large datasets are not relevant for design practices as the primary purpose lies in autonomous driving or vehicle verification. Therefore, we release GP22, composed of car styling features defined by automotive designers. The dataset contains 1480 car side profile images from 37 brands and ten car segments. It also contains annotations of design features that follow the taxonomy of the car exterior design features defined in the eye of the automotive designer. We trained the baseline model using YOLO v5 as the design feature detection model with the dataset. The presented model resulted in an mAP score of 0.995 and a recall of 0.984. Furthermore, exploration of the model performance on sketches and rendering images of the car side profile implies the scalability of the dataset for design purposes.
Symbolic Regression is NP-hard

Symbolic regression (SR) is the task of learning a model of data in the form of a mathematical expression. By their nature, SR models have the potential to be accurate and human-interpretable at the same time. Unfortunately, finding such models, i.e., performing SR, appears to be a computationally intensive task. Historically, SR has been tackled with heuristics such as greedy or genetic algorithms and, while some works have hinted at the possible hardness of SR, no proof has yet been given that SR is, in fact, NP-hard. This begs the question: Is there an exact polynomial-time algorithm to compute SR models? We provide evidence suggesting that the answer is probably negative by showing that SR is NP-hard.
Kolepa Mobile Application Development Based on Android Using Agile Method

Kolepa Minigolf and coffe shop is an instance which run on minigolf services also food and beverages. Kolepa wanted to develope a mobile apps that can be use for Kolepa Customer to check on existing promo and book a table to play. Kolepa Mobile Apps will be integrated with Kolepa database. Based on the interview between Project Manager and owner of Kolepa, there's some feature that must be included on the Mobile Apps, which is Authenticate, Promo, Reservation, and Score Counter. In its implementation, agile methods are applied for each of the functions mentioned above. Aplication will be develope using Dart Programming Languange, which is part of Flutter Framework. Application development is divided into several sprints that are developed with predetermined deadlines. From the results of the development that has been carried out, feature testing is carried out using the blackbox method and it is found that the application has met the functional and non-functional requirements that have been set. With this application, Kolepa can simplify the bussiness they run.
The Relationship between the new Leadership Styles and Nursing Productivity

Background: Current and innovative trend leadership styles entail transformational, laissez-faire, passive-avoidant, and transactional leadership styles. Aim: To examine the relationship between nurse leaders’ new leadership styles and nursing productivity at King Fahad Hospital in Al Medina Al Munawara. Material and Methods: A descriptive correlational research design was used to collect the appropriate data. A convenient sampling (n=47) of all nurse's leaders at King Fahad Hospital in Al Madinah Al-Munawara filled three data collection tools. The tools queried demographic data, Multifactor Leadership Questionnaire Rater Form to measure leadership and NHS Knowledge and Skills Framework to measure nurse's productivity. Pearson correlation was used to investigate the correlation further with a significance level of at P= &lt;0.05. Results: Transformational and transactional leadership styles increase staff nurses skills as communication, personnel and Professional development, health safety, security, quality, equality, and diversity. Additionally, the leadership styles improve service improvement, interventions, and treatments. Conclusion and Recommendations: The implementation of transformational and transactional leadership styles is imperative for the nursing practice that seeks to increase the productivity of the nurses, a new leadership style has effect of transactional, transformational, passive-avoidant, and laissez-faire confirms the varied respondents of different demographic groups. Keywords: Relationship, new leadership, styles, nursing, productivity
The role of digital media in the popularization of scientific knowledge: realities and challenges

The article deals with the problems of modern interaction between science and innovative technologies of mass media. Аn important role in the popularization of promoting scientific research is played by the media, which broadcast scientific knowledge to society. However, to date, scientific research is of little interest to journalists. The author describes the possibilities of digital journalism in the promotion of scientific knowledge and the involvement of governmental agencies in the activities of Kazakhstani scientists. The purpose of the article is to consider the possibilities of the multimedia environment in creating a high-quality information base on scientific developments and their introduction into the modern economy and society. Digital media of Kazakhstan should actively participate in the promotion of current knowledge, offering various forms of presentation of scientific and popular-science information. The scientific significance of the article consists in an attempt to take a new look at the popularization of scientific knowledge; new functions of the media in the context of promoting a civilized worldview. The research methodology provides a systematic approach, a method of comparative analysis, classification. The aim of the research is to identify new challenges facing the media in the modern period within the framework of scientific and popular-science discourse. Mass media contribute to the popularity of scientific knowledge and form a special attitude to science as a phenomenon on which the existence of modern civilization depends, which determines the scientific value of this article. The practical significance lies in the possibility of introducing the results of the research into teaching at journalism faculties in specialized and elective disciplines, as well as in advanced training courses for journalists specializing in the topic of science. Keywords: journalism, science, digital journalism, digital media, scientific journalism, popular- science journalism.
None Shall Pass: A blockchain-based federated identity management system

Authentication and authorization of a user's identity are generally done by the service providers or identity providers. However, these centralized systems limit the user's control of their own identity and are prone to massive data leaks due to their centralized nature. We propose a blockchain-based identity management system to authenticate and authorize users using attribute-based access control policies and privacy-preserving algorithms and finally returning the control of a user's identity to the user. Our proposed system would use a private blockchain, which would store the re-certification events and data access and authorization requests for users' identities in a secure, verifiable manner, thus ensuring the integrity of the data. This paper suggests a mechanism to digitize documents such as passports, driving licenses, electricity bills, etc., issued by any government authority or other authority in an immutable and secure manner. The data owners are responsible for authenticating and propagating the users' identities as and when needed using the OpenID Connect protocol to enable single sign-on. We use advanced cryptographic algorithms to provide pseudonyms to the users, thus ensuring their privacy. These algorithms also ensure the auditability of transactions as and when required. Our proposed system helps in mitigating some of the issues in the recent privacy debates. The project finds its applications in citizen transfers, inter-country service providence, banks, ownership transfer, etc. The generic framework can also be extended to a consortium of banks, hospitals, etc.
Relationships Among Higher Education EFL Student Perceptions Toward Fully Online Language Learning and Computer Self-efficacy, Age, Gender, and Proficiency Level in Emergency Remote Teaching Settings

Objectives: The purpose of this study was to explore Chilean higher education English as a foreign language (EFL) students’ perceptions toward components of their fully online learning experience and their computer self-efficacy during the CoVID-19 pandemic and assess how these variables are influenced by age, gender, and language proficiency. Method: Participants of the study were 236 undergraduate students (110 males and 126 females) who took a fully online EFL course in a professional institute in Chile. Likert-scale questionnaires were used to gather data on perceptions toward fully online language learning components (online participation, collaborative group work, instructional materials, and learning strategies and styles) and computer self-efficacy (CSE). Findings: Participants held overall positive views toward fully online language learning components but had negative views toward online participation. Findings revealed significant relationships between computer self-efficacy and perceptions toward fully online language learning components. The perceptions that learners held toward fully online courses seem to be unaffected by gender and proficiency level, although gender did impact CSE. Implications for Theory and Practice: Feeling disconnected from peers and the learning experience in general can lead to negative attitudes toward online learning as well as feelings of isolation. Learners may feel unmotivated, frustrated, and discouraged to continue participating in the course. Teachers can nurture a sense of community in the classroom by facilitating dialogue, providing timely feedback, moderating student discussions, and building social networks around learners. It is also important to promote healthy levels of computer self-efficacy that can positively influence perceptions toward group work and learning strategies. Conclusion: Emergency remote teaching can have a negative impact on online participation. As more educational institutions provide their students with online options for attending classes, teachers should focus on increasing peer collaboration and interaction.
Netcast: Low-Power Edge Computing with WDM-defined Optical Neural Networks

This paper analyzes the performance and energy efficiency of Netcast, a recently proposed optical neural-network architecture designed for edge computing. Netcast performs deep neural network inference by dividing the computational task into two steps, which are split between the server and (edge) client: (1) the server employs a wavelength-multiplexed modulator array to encode the network's weights onto an optical signal in an analog time-frequency basis, and (2) the client obtains the desired matrix-vector product through modulation and time-integrated detection. The simultaneous use of wavelength multiplexing, broadband modulation, and integration detection allows large neural networks to be run at the client by effectively pushing the energy and memory requirements back to the server. The performance and energy efficiency are fundamentally limited by crosstalk and detector noise, respectively. We derive analytic expressions for these limits and perform numerical simulations to verify these bounds.
PENGEMBANGAN BAHAN AJAR BAHASA DAN SASTRA INDONESIA DENGAN MENGGUNAKAN PENDEKATAN TEMATIS PADA SISWA KELAS XI SMA NEGERI 1 TAPAKTUAN

Education at SMA Negeri 1 Tapaktuan is still faced with 4 obstacles in improving the quality of education, namely: (1) limited number of teachers and TU; (2) the uneven distribution of teachers; (3) lack of teacher professionalism; and (4) various facilities for teaching and learning activities that do not meet the standards, in particular the lack of procurement of Indonesian language textbooks that are relevant to the needs of students, schools, and regions in accordance with the demands of K-13. This research was conducted with the objectives of: (1) formulating the need for teaching materials according to teachers and students; (2) developing prototypes into Indonesian language and literature teaching materials with a thematic approach in high school; (3) knowing the effectiveness of the developed teaching materials; and (4) determine the feasibility of teaching materials for Indonesian language and literature with a thematic approach in high school. The research and development (R&amp;D) method is used in this research to produce teaching materials. The results obtained: 1) the need for teaching materials according to teachers and students, paying attention to: (a) the language context for various language purposes, (b) keeping up with the times, (c) according to K13 by raising themes around students, (d) relevance between teacher and student teaching materials; (f) assignments/practices can activate students, (g) the material attracts students' interest, is clear, and easy to understand, and (h) is relatively ready to use in minimal school facilities; 2) developing prototypes into Indonesian language and literature teaching materials with a thematic approach in high school is done by: (a) compiling syllabus, lesson plans, teacher teaching materials and student teaching materials, (b) authentic materials and assignments/exercises developed thematically and situational and develop intellectual and affective insight, and (c) the assessment process is carried out by classroom assessment; 3) the results of the effectiveness test with a non-independent t-test showed that the thematic teaching materials were effective; and 4) the results of the feasibility of developing Indonesian language and literature teaching materials with a thematic approach are stated to be good with components of content/material feasibility assessment 77.92%, linguistics 73.40%, material presentation 77.92%, and graphics 70.
Perancangan Sistem Informasi Pembayaran Sekolah Menggunakan Model Rapid Application Development (RAD)

In today's era of globalization, information technology is advancing rapidly. Information obtained because of technological devices such as computers that were created to facilitate human work, especially in the IT field. SMA Muhammadiyah 18 Jakarta is in dire need of an information system to support school needs. For this reason, the author tries to make research on the payment system at SMA Muhammadiyah 18 Jakarta which is currently not computerized. SMA Muhammadiyah 18 Jakarta is a business charity engaged in education under the auspices of the Muhammadiyah Cipulir College, Kebayoran Lama Branch. The existing school payment system is still done manually. Starting from the process of receiving payments to making reports, making it possible during the process there were errors in recording, less accurate reports made and delays in finding the required data. The design of a payment information system is the best solution to solve the problems that exist in this school. Therefore, a computerized system is better than a manual system so that it runs more effectively, efficiently and the current payment system is more conducive than the previous system. The result of this research is a payment system design that utilizes information technology that can solve various problems that occur in the current system.
On bounded solutions of differential systems

The question of the existence of bounded solutions on an infinite interval of a linear inhomogeneous system of ordinary differential equations in a finite-dimensional space is considered. The study of bounded solutions of systems of ordinary differential equations is one of the most important problems in the qualitative theory of differential equations. In the study of the asymptotic behavior of solutions to differential systems, the works of A. Poincare and A.M. Lyapunov. Various conditions for the existence of bounded solutions of a linear system of ordinary differential equations have been obtained by many authors. Note the works of O. Perron, A. Walter, H. Shpet, D. Caligo, N.I. Gavrilova, M. Hukukara, M. Nagumo, M. Caratheodori, U. Barbouti, N. Ya. Lyashchenko,&nbsp; B.P. Demidovich, A. Wintner, R. Bellman, Yu.S. Bogdanov, Z. Vazhevsky, &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;N. Levinson, M. Markus, L. Cesari and others. In this paper, we establish sufficient conditions for the boundedness of all solutions of a linear inhomogeneous system of differential equations on an infinite interval. A coefficient criterion for the boundedness of all solutions on an infinite interval of a linear inhomogeneous system of differential equations in a certain class of differential systems is given. Applied methods of differential equations and function theory. The results obtained are used in applications of differential equations and are of practical value.
Professional development e-course on how to integrate interdisciplinary approach into the learning process in schools that practise multimodality and use interactive educational online services

Problem and goal. The problem of implementation and realization of interdisciplinary approach in the learning process at schools is demonstrated. The goal of this research is to create professional development e-course for teachers, which can include practical approaches to integrate interdisciplinarity and to develop multimodality through the application of online services. Methodology. The practical research is carried out based on organizing an experimental (93 people) and control (71 people) groups of students in different ages (4-8th grades) and disciplines. The students from an experimental group are taught by the teachers who took part in the designed e-course. These teachers use practice-based methods and strategies to integrate interdisciplinary approach in the lessons of Geography, Mathematics, Russian, English, Social Studies and Literature in a primary school. They apply online services such as Padlet, Zoom and Google Tools as well. Analysis of interdisciplinary skills level is carried out with the help of control diagnostics before and after the experiment. Results. The tools for the integration of interdisciplinary approach and the application of online services in educational process have appeared to be effective. The evidence of this conclusion is the toolbox with methodological interdisciplinary materials and resources which has been created for the learning process with the help of online services which can help students develop transfer skills, creative and critical thinking. The tools and services demonstrated in this research allow students and teachers to develop agency, i.e. the ability to be responsible for their life, in particular for their learning, to make a choice and to have a voice. They also help increase motivation to the process of learning. Such tools and online services can play a significant role for informatization of the learning process because they have an impact on the development of students’ multimodality. Conclusion. The results allow to identify the effectiveness of the implementation and integration of interdisciplinary approach in educational process, especially in the framework of narrow disciplines, with the help of online services. Teachers, who had taken part in a designed professional development e-course, used strategies and tools, online services in practice. The students demonstrated an enhanced level of creative and critical thinking and transfer skills during control diagnostics after the research.
Empirical Analysis of Vehicle Tracking Algorithms for Extracting Integral Trajectories from Consecutive Videos

This study introduces a novel methodological frame-work for extracting integral vehicle trajectories from several consecutive pictures automatically. The frame-work contains camera observation, eliminating image distortions, video stabilising, stitching images, identify-ing vehicles and tracking vehicles. Observation videos of four sections in South Fengtai Road, Nanjing, Jiangsu Province, China are taken as a case study to validate the framework. As key points, six typical tracking algorithms, including boosting, CSRT, KCF, median flow, MIL and MOSSE, are compared in terms of tracking reliability, operational time, random access memory (RAM) usage and data accuracy. Main impact factors taken into con-sideration involve vehicle colours, zebra lines, lane lines, lamps, guide boards and image stitching seams. Based on empirical analysis, it is found that MOSSE requires the least operational time and RAM usage, whereas CSRT presents the best tracking reliability. In addition, all tracking algorithms produce reliable vehicle trajecto-ry and speed data if vehicles are tracked steadily.