Reviewerly/exHarmony huggingface dataset:
Digitalization and Anthropocentrism

The current situation in society is largely constituted by that wave of computeri­zation, or, as someone say, digitalization, which has covered, in fact, the entire society and sets certain behavioral frameworks at all levels of social communica­tion. Computers organized in a network are coordinated today with the many bodily and mental acts that once constituted the characteristic features of the be­ing called human. What makes a person a special being if the computer network surpasses him in many ways? How much does the concept of “human” change if we consider the latter as one of the agents of a vast digital network? How much do we understand those operations that take place in such a network it­self, as well as those that are implemented between a person and a computer? At the same time, it should be taken into account that computers not only trans­form society. They produce and provoke special recursive connections, both among themselves and with a person, giving rise to a special sensitivity in the lat­ter – sensitivity to the virtual. Virtual reality is not only in the network, it is also updated in the physicality of the individual and in his mentality. So, an individ­ual could integrate with computers and use the advantages that they give: upload themselves to the digital world and be one with computers, choice of communi­cation strategies. However, this question can be somewhat redefined. The ape turned man and Kafka’s “Report to the Academy” says: “No, I didn’t want free­dom. All I wanted was an exit… I had to move forward!”. It seems that today it is worth talking not so much about freedom (no matter in what sense of the word), but about finding a way out of a seemingly dangerous, if not cata­strophic, situation.
Robustness Evaluation Method for Spacecraft Anomaly Detection Models

The anomaly detection of spacecraft is critically important for the safety of spacecraft, and for a specific spacecraft, the most suitable anomaly detection method must be chosen. This paper proposes an evaluation method for the robustness of anomaly detection models. Seven common evaluation metrics are calculated for the prediction results of the anomaly detection models. These metrics can be viewed as a point in a seven-dimensional space. Experiments are conducted using data with varying levels of noise, and metric points are calculated. Subsequently, multiple sets of metric points are clustered. The clustered metric points yield average coordinate points representing each cluster of metrics. Experiments are also conducted using noise-free data to calculate metric points as baseline points. The distance between the baseline points and other metric points is then computed, where a smaller distance indicates better model robustness. Experimental results demonstrate that this evaluation method is applicable for assessing the robustness of anomaly detection models for spacecraft.
TimeSplines: Sketch-Based Authoring of Flexible and Idiosyncratic Timelines

Timelines are essential for visually communicating chronological narratives and reflecting on the personal and cultural significance of historical events. Existing visualization tools tend to support conventional linear representations, but fail to capture personal idiosyncratic conceptualizations of time. In response, we built TimeSplines, a visualization authoring tool that allows people to sketch multiple free-form temporal axes and populate them with heterogeneous, time-oriented data via incremental and lazy data binding. Authors can bend, compress, and expand temporal axes to emphasize or de-emphasize intervals based on their personal importance; they can also annotate the axes with text and figurative elements to convey contextual information. The results of two user studies show how people appropriate the concepts in TimeSplines to express their own conceptualization of time, while our curated gallery of images demonstrates the expressive potential of our approach
Sales Forecasting Application Using The Triple Exponential Smoothing Method Based on Android

Forecasting is the art and science of predicting future events. This can be done by involving taking past data and placing it into the future with a form of mathematical model. The application of the Triple Exponential Smoothing Method is very appropriate to solve the above problems because the Triple Exponential Smoothing Method is used in short-term forecasting, usually only 1 month ahead. The Triple Exponential Smoothing method assumes that the data fluctuates around a fixed mean value, without an even trend or growth pattern. the author conducted research related to the calculation of the development of laptop purchases at CV.Gaharu.Com problems often occur, especially the problem of calculating laptop sales predictions such as the absence of a special system in calculating laptop sales in the coming period so that the company's stock often runs low and is not proportional to consumer demand which is growing rapidly and increasing, as well as in making laptop sales reports are still processed with a fairly simple application so that the reports obtained are less accurate. The research method used by the author is using the R&amp;D (Research and Development) research method. The method of data collection was carried out in this study, namely by means of observation, interviews, and literature study. The steps taken are database design and describe the workflow of the application to be built using UML. At this stage the author designs the interface to produce an interface that is in accordance with the functions required for the application to be built. The system development method used by the researcher is the waterfall.
A Study on the Determination of Subjects for Post-Management Investigation Using the Monitoring Results of Self-Consumption Solar Power

The global trend of renewable energy generation and the advent of the Internet of Things technology has popularized inexpensive integrated monitoring technology. Accordingly, the Renewable Energy Monitoring System (REMS) project, which monitors solar plants subsidized by National funds, has been expanding its target since 2018. Concurrently, the mandatory post-management system became effective in 2020 to strengthen the post-management system. The 3-sigma rule is used to determine the control chart for the normal operation of solar systems from the monitoring data. In this study, solar plants with normal operation within the control chart were suggested to be excluded from field investigation with a focus on the management of solar plants with abnormal operation outside the control chart to improve the overall investigation into inefficiencies in the mandatory post-management system. Improvements to the monitoring system operation plan were also suggested.
Interplay Between Computational Neuroscience and Humanoid Robotics: Past and Future

The interplay between computational neuroscience and humanoid robotics, both historically and looking forward, is presented, with a particular focus on two significant projects: the ERATO Kawato Dynamic Brain and the ICORP Computational Brain. Discussion revolves around pivotal brain regions, namely the cerebellum, basal ganglia, and cerebrum, and the associated computational models.
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening.

generated work. The first algorithm applies ordering globally to reduce computations, and the second algorithm applies ordering locally at the level of threads to minimize the synchronization overhead. We use two different implementations of Luby’s algorithm variants as baseline to compare the performance of the presented algorithms: (1) vertex-centric Luby A and Luby B implementations, and (2) the CombBLAS linear-algebra Luby A implementation. Results show that proposed algorithms outperform both implementations of Luby algorithms, especially in distributed execution. Furthermore, we show that for low-diameter graphs the algorithm that applies global ordering scales better than other algorithms and for high diameter graphs the original asynchronous algorithm and thread-level ordering algorithm show better performance.
A Compact Delayed Photocurrent Model Based on a Reduced Order Data-Driven Exponential Time Integrator.

and then use physics knowledge to refine its structure. Numerical studies demonstrate the potential of the model and establish some empirical guidelines for its training.
Development and Validation of Digital Literacy Scale for University Students

The purpose of this study was to develop and validate a scale that can measure digital literacy competency of university students in the context of higher education. To achieve the purpose of the study, a theoretical model was constructed based on previous studies related to digital literacy, and the statistical validity of the theoretical model was verified through a survey. The sample included 63,391 students from 111 universities in Korea, and exploratory factor analysis and confirmatory factor analysis were applied. As a result, the final scale of digital literacy consisted of 23 items of four factors. Specifically, digital tool utilization (5 items), data literacy (8 items), digital ethics (5 items), and digital-based learning experience(5 items) were included. The study provided theoretical and practical implications. It contributes to academic development related to digital literacy and presents policy implications for digital literacy competency education for the growth and development of university students.
Improving Educators Digital Literacy Through Assistance in the Development of Lectora Inspire- Based Mathematics Learning Media

The competence of an educator is the main key to the success of a lesson. The problems that exist in schools partner are that educators complain about the low numeracy skills of students and the minimal use of technology in learning. Teachers are the main key to the success of nursery human resources. Teachers are required to be more creative, innovative and inspiring in designing quality learning activities to welcome Indonesia's golden generation, especially in learning mathematics. Digital-based learning media can attract students to be more enthusiastic about learning mathematics. One of the software that can be used to develop mathematics learning media is the Lectora Inspire software. In order to develop a technology-assisted learning media, educators' digital competencies really need to be built so that educators can be more creative in creating interesting and not boring learning. Therefore, a teacher competency development assistance is needed, where a forum for the development of pedagogic and professional competencies for teachers at SMPN 6 Tanggul in Kramat Sukoharjo Village. Community service activities are packaged by applying the ADDIE (Analysis-Design-Development-Implementation-Evaluation) training model. Based on the results of the pretest and posttest, the percentage of N-Gain was 76%. Based on the category of interpretation of the effectiveness of N-Gain, the value is included in the effective category because it meets the value of . That is, learning media based on lecturera inspire is effective in increasing student understanding.
Eco-Brick-Making Workshop for Cianjur Disaster Survivors

The earthquake that rocked Cianjur on November 21 2022 with a magnitude of 5.6 caused around 58,000 residents to be forced to flee. The large number of evacuees and volunteers has caused a pile of garbage at the evacuation site. Seeing this fact, the Faculty of Psychology, Jayabaya University, in collaboration with Putra Indonesia Cianjur University, took the initiative to provide education and training in making eco-brick from used plastic drink bottles. Eco-brick is an easy and inexpensive way to reduce plastic waste that is difficult to decompose. The activity was carried out at MTSN 6 Cianjur on December 28, 2022. From this training, it is hoped that the community will have the ability to utilize waste bottled drinks in goods that have high economic value. Eco-bricks can be used as chairs, tables and even building additives. This activity is also a form of application of environmental psychology as a branch of psychology that studies the interrelationships between individuals and the physical environment, both the natural environment and the human-built environment; set an example and increase public awareness and concern to always maintain the cleanliness of the surrounding environment under any circumstances.
REAL TIME DETECTION OF CHICKEN EGG QUANTITY

A common problem currently being faced in the chicken egg production home industry is difficulty in counting the number of eggs. Currently, calculating the number of eggs is still done manually, which is less than optimal and prone to errors, so many entrepreneurs often experience losses. The manual system currently used also has the potential for this to happen. The use of technology on an MSME scale among laying hen breeders has not been widely adopted, this is due to limited access and understanding of technology. One alternative solution to deal with this problem is to build a real-time computerized system. The system that will currently be built in this research uses GLCM feature extraction and the SVM classification method. This system will detect egg production via CCTV cameras and will be stored in a database to be displayed on the website. The advantage of this system is that egg entrepreneurs can monitor chicken egg yields in real time. The results of trials that have been carried out using GLCM feature extraction and the SVM classification method in calculating the number of eggs using the SVM method with a polynomial kernel are highly recommended for use in this research because it can achieve 95% accuracy.
Javanese language learning assistance through digital media for teachers and students

In the millennial era, our students are already infatuated with digital. Javanese language which is included in the local content of Junior High Schools, students are presented with local languages which have shifted a lot in usage. Students rarely use Javanese which is difficult in the form of pronunciation. The problems are (1) students in reading, writing and speaking Javanese do not understand and find it difficult to apply aspects of pronunciation and phonetics in their use. (2) the lack of interest of millennial students in preserving regional languages. (3) based on observations, today's students are lacking, mastering Javanese is called "ora njawani". And (4) the lack of teaching materials to attract students' interest, especially in the current trend, through digital. Teachers can use digital media Student Pocket Book Products which contain content from the creativity of students and teachers. In addition, students are used to using digital features. The solution to the problem of Servants is to train and assist teachers and students using digital-based learning methods and media and maintain culture. The Jombangan dictionary digital book product is used as a blended learning’s medium media. This book is equipped with a barcode that contains infographic content or Javanese Jombangan YouTube content that can trigger student motivation in applying Javanese. So that students can use digital dictionaries independently and innovatively. This method can help students and teachers learn Javanese pronunciation.
ADDRESSING KNOWLEDGE MANAGEMENT ISSUES AT UNIVERSITY OF HOUSTON: OVERCOMING OBSTACLES TO IMPROVE ORGANIZATIONAL PERFORMANCE

Effective knowledge management (KM) is crucial for corporate success in today's fast-paced business landscape. This theoretical study explores how KM processes impact organizational performance. It provides a comprehensive framework drawn from existing literature to explain how KM can enhance decision-making, innovation, and operational efficiency when employed strategically. The study highlights key KM components: knowledge creation, dissemination, storage, and application, shaping business success. It categorizes and examines these elements, revealing their intricate relationships. The research explores how an open, collaborative culture promotes knowledge sharing and organizational performance. Additionally, it delves into the role of leadership in fostering a KM-focused culture, emphasizing leaders' influence on knowledge-driven initiatives. It shows how KM practices drive innovation by integrating insights from diverse areas. The study emphasizes leveraging digital platforms for information sharing, despite potential challenges like information hoarding and resistance. Overall, it underscores KM's vital role in organizational performance and provides insights for strategic decision-making in dynamic business environments.
Analysis of Mobile-Based Archive Management Information System Design

Information technology has become a very common thing in today's society, therefore with the existence of fast and easy information technology it is expected to be able to process the desired information. At this time the existence of information systems presents a new innovation. The rapid development of information technology has penetrated into various sectors including offices. In the digital era, people are increasingly aware that communication technology is an important tool in dealing with the increasingly rapid flow of information. Information has developed and arrived in the digital era, one of which is information processing which has developed from conventional to digitally managed. As a memory center for organizations or agencies, letters are something important and need to be stored properly. But storage is still done conventionally, it will be difficult when you want to do a search. This study aims to design a mail archive information system using qualitative methods as a research method, UML as a system design that will facilitate the flow of research in designing systems and using a waterfall as a system development method. The results of this study are in the form of a design for a mail archive information system which is expected to be able to solve this problem.
Effective Irradiance Monitoring Using Reference Modules.

the convolution of spectral response with solar irradiance are considered. The second is the most accurate technique.
Study of the Educational Process Participants Readiness to Applying Digital Technologies in Education

&lt;p&gt;The article presents an overview of various digital technologies used in the educational process; the problem of their perception and application by teachers and students is investigated. The purpose of the article is to identify the level of readiness of direct participants of the educational process to use digital technologies in their activities. The study was conducted on the basis of analysis and generalization of domestic and foreign scientific publications devoted to the problem of the use of digital technologies by participants of educational institutions. A sociological study was conducted by online questionnaire of students. The research methods are comparison, concretization, system and comparative analysis. The authors have revealed that the teachers' perception of the use of digital educational technologies in their activities depends on various factors, such as: age, gender, availability and degree of development of organizational and communicative abilities of a person, on the degree of motivation, as well as on the level of creativity of the teacher's personality. It is revealed that there are various barriers to the use of TSOT by teachers. Regarding the readiness of students to use TSC, it was found that students are not fully ready to use TSC in teaching, in particular, they are not aware of the essence of the concept of immersive technologies and do not identify them with virtual or augmented reality technologies. A significant part of students uses digital services that are quite similar in functionality. The actual digital technologies used in teaching in the world practice are revealed. The necessity of using digital services in virtual educational environments, including metaverses, is substantiated. In order to increase the ability of teachers to use TSOT, it is necessary that the curricula include courses on the use of TSOT in education in the context of vocational training. It is also proposed to encourage teachers to use technology in the educational process by allocating additional funding. Universities need to create conditions for students to use digital technologies.&lt;/p&gt;
Dewarping Document Image in Complex Scene by Geometric Control Points

In the process of document digitization, document images captured by mobile devices suffer from physical distortion, which is detrimental to subsequent document processing. Geometric information of the distorted document images provide global and local constraints that can assist in document dewarping. In this paper, we propose a novel document dewarping method which focus on utilizing the geometric control points such as document boundaries and textlines. Specifically, our method first extracts the boundary source control points and textline source control points and predicts their corresponding forward mapping as target control points. Eventually the sparse mapping between control points is converted into a dense backward mapping by Thin Plate Splines interpolation. Our method can obtain the backward mapping directly and explicitly by interpolation between control points, without solving the time-consuming optimization problem. Quantitative and qualitative evaluation show that our method can dewarp document images with various distortion types, and improve the inference speed by a factor of three over the existing geometric element based rectification methods.
Bridging Distinct Spaces in Graph-Based Machine Learning

Graph-based machine learning, encompassing Graph Edit Distances (GEDs), Graph Kernels, and Graph Neural Networks (GNNs), offers extensive capabilities and exciting potential. While each model possesses unique strengths for graph challenges, interrelations between their underlying spaces remain under-explored. In this paper, we introduce a novel framework for bridging these distinct spaces via GED cost learning. A supervised metric learning approach serves as an instance of this framework, enabling space alignment through pairwise distances and the optimization of edit costs. Experiments reveal the framework’s potential for enhancing varied tasks, including regression, classification, and graph generation, heralding new possibilities in these fields.
Object Detection with Depth Information in Road Scenes

In recent years, depth estimation has witnessed significant advancements because of the development of deep learning. It's important to note that depth estimation tasks focus solely on predicting the depth of each pixel in an image and do not include object detection or object recognition. Depth estimation is the use of pixel transformations in the image to obtain distance information from each point in the scene to the camera to generate a depth map. Object detection is the process of classifying and localizing an image, given a picture, so as to identify the objects in the picture and determine their location. To overcome this limitation and integrate object detection into the depth estimation process, this paper proposes a novel self-supervised monocular depth estimation algorithm that leverages an attention mechanism. By combining object detection and depth estimation, a real-time multi-task model is designed to enable simultaneous detection and depth estimation of objects. The framework comprises four essential components: an object detection sub-network, a depth estimation sub-network, a lateral sharing unit, and an attention loss. These components work collaboratively to enhance distance estimation accuracy for objects and improve the object detection performance. Throughout experiments, it is evident that the proposed approach can effectively estimate distances to objects and enhances the accuracy of object detection.