Reviewerly/exHarmony huggingface dataset:
A Two-Stage Self-Training Framework for Nighttime Semantic Segmentation

Nighttime semantic segmentation is a challenging task due to the poor lighting in the night scenes. Since it is difficult to acquire pixel-level annotations of nighttime images, the existing works attempt to adapt a model learned on annotated daytime images to unlabeled nighttime images. Due to the gap between daytime and nighttime images, the model tends to over-fit daytime images and learn wrong annotation patterns for overexposed regions in nighttime images. To handle these issues, we propose a two-stage self-training framework, which synthesizes high-quality pseudo-labels for nighttime images based on overexposure detection. The synthetic pseudo-labels are then utilized as supervision information to retrain a new segmentation model, which significantly mitigates labeling errors in overexposed regions. Experiments on the DarkZurich dataset verify the effectiveness of the proposed method.
Performance Comparison of Different Load Balancing Algorithms in Cloud Computing

Cloud computing offers economical, scalable, and instantaneous computing resources to enterprises, allowing them to manage substantial traffic volumes and cater to a multitude of users. But the need for effective load balancing techniques has grown significantly as cloud computing becomes more and more popular. To guarantee the best possible performance, availability, and dependability of apps and services, load balancing is a crucial component of cloud computing. This paper offers a comparative study of different cloud computing technologies and load balancing strategies. We present a performance comparison of software-based load balancing; our analysis compares various service broker policies, such as closest distance, optimized, and reconfigurable, with algorithms such as round robin, throttled, and equally spread. Overall, this paper helps readers understand load balancing mechanisms in cloud computing.
Blockcloud: Merger of two Big Technologies Blockchain &amp; Cloud Computing

A Blockchain is a continuous list - a structure like a file containing blocks connected by links, and the storage of blocks is done with the help of cryptography whereas Cloud computing is the need for computing resources, especially data storage (cloud storage) and computing power, without the direct control of users. Large cloud operations are often distributed across multiple locations, each with a data center. Both these technologies have their individual working and responsibilities and plays their roles very perfectly which makes them high demanding in today’s world but if they both work together then it will upgrade the future of IT market because Blockchain makes a difference in cloud storage which keeps information secure and tamper-proof. Companies can be certain that their information is secure; erasing information from a computer does not erase information held on other blockchain arrange gadgets. In this way, information put away within the cloud utilizing blockchain innovation is secure and secure. In cloud computing, blockchain can make an organize of hubs that share data and handle vitality. This guarantees that companies don't require a central benefit supplier. Instep, they can depend on organized computers that are not controlled by a single company which is beneficial in all aspect. This paper showcase all benefits by merging these two big technologies Blockchain and Cloud computing and propose new term for this Merger as “BlockCloud”.
Chinese Remainder Theorem based Performance Analysis of RSA Cryptosystem

Message security and authenticity is a very important issue which cannot neglect in wireless network. This paper explains how the RSA algorithm can be used to achieve both, over a wireless network. The RSA-CRT technique was premeditated for data decryption and operative illustration of cryptograpghy using the Chinese Remainder Theorem (CRT) for message security which is nearly four times faster.
The Impact of Technological Advancements on Society: Examining the Possibility of a Brave New World

Purpose: This research paper aims to explore the impact of technology on society in various areas, including social interactions, education, the economy, and the environment. Methodology: The first section will provide an overview of the major technological advancements and their impact on society. The second section will examine how technology has affected social interactions, including whether people are becoming more isolated due to the prevalence of technology and the potential benefits of technology on social interactions. The third section will focus on technology’s impact on education, including the benefits and potential drawbacks of technology in education. The fourth section will explore technology’s impact on the economy, including the potential benefits and risks that come with technological advancements. Finally, the fifth section will examine the impact of technology on the environment, including the potential benefits and risks of technology on the environment. Findings: Through this comprehensive examination, this research paper shed light on the complex relationship between technology and society and provides an insight into the possibility of a brave new world. Value: The study contributes to a better understanding of the multifaceted effects of technology on society, encompassing social, educational, economic, and environmental aspects, ultimately addressing the potential implications of these advancements on the creation of a new societal landscape.
Utilizing the Factory Method Design Pattern in Practical Manufacturing Scenarios

The paper delves into the utilization of design patterns, specifically focusing on the Factory Method, within the field of software engineering. It underscores the importance of design patterns in addressing recurring problems in a flexible, elegant, and reusable manner. The document explores various categories of design patterns and their practical applications, with special attention to the Factory Method's role in streamlining object creation and enhancing system maintainability. To illustrate the practicality of the Factory Method, a real-world use case in a manufacturing context is presented, showcasing its influence on software architecture and maintainability. The study concludes by underscoring the advantages of design patterns in software development, particularly in terms of their ability to promote reusability and efficiency when dealing with common software design challenges.
Development of a noninvasive method for determining blood viscosity

The aim of the study is to develop a new method for noninvasive determination of dynamic viscosity. In the developed method, the methods of mathematical modelling and the laws of rheology, mechanics, biomechanics and human physiology were used. It has been shown that an increase in blood viscosity leads to functional failure of various organs and tissues, disorders of the coronary and cerebral circulation. As a result of the analysis, it was revealed that blood can be considered as a colloidal suspension in which particles of erythrocytes and platelets are suspended, and the viscosity of such a colloidal system in microcirculation does not obey the Newtonian law. At the same time, the main factors that significantly affect blood viscosity include: blood pressure of hematocrit, platelet count, absolute amount of fibrinogen proteins and microglobulins, and lipoprotein concentration. A mathematical model has been obtained for determining the viscosity of the colloidal dispersed blood system, considering the concentration of the dispersed phase (blood cells) and the structure formation of blood; a model for determining the thickness of the boundary layer of blood corpuscles adsorbed on the inner surface of blood vessels is proposed and the mechanism of blood structure formation associated with the surface charges of erythrocytes and platelets is shown.
Census of speech therapist of the Sicily

The survey on the employment status of speech therapists who carry out their professional activity in Sicily was conceived by the Commission of the Register of Speech Therapists of the TSRM-PSTRP Order of Palermo, in collaboration with the Commissions of the Register of Speech Therapists of the TSRM-PSTRP Orders throughout Sicily, i.e.: Board of Directors of Speech Therapists of Catania, Caltanissetta-Agrigento, Enna, Messina, Ragusa, Syracuse and Trapani.&#x0D; The census of Sicilian speech therapists has proven to be a very useful tool for identifying important information and data regarding the employment status of colleagues and the methods and types of contracts. These data will be crucial in reference to the reorganization of the hospital network and territorial services to guarantee the LEAs (outpatient and rehabilitation LEAs) considering the low incidence of speech therapists working in the public sector compared to the total number of professionals active in the Region. The questionnaire used for the survey allowed us to highlight strengths and weaknesses related to the speech therapist profession. The possibility of comparing data and observing their evolution over time provides the possibility of highlighting the critical issues that have emerged and planning future actions for better governance of the profession.
Evaluating the Performance and Accuracy of Supervised Learning Models on Sentiment Analysis of E-Wallet

This study has purpose to evaluate the performance and accuracy of supervised learning Models used on Sentiment Analysis of E-Wallet. User comment data was taken using the web scraping method on 4 major E-wallet applications in Indonesia namely, Ovo, Dana, Doku, and LinkAja. The data was taken in January-May 2023 with the amount of data after preprocessing are 11267 with 6349 negative labels and 4918 positive labels. Data labeling uses a star scale that has been pinned by the user, 1-3 stars are labelled negative and 4-5 stars are labelled positive labels. The labeling results were tested using supervised learning model including SVM (Support Vector Machine), Multinomial Naive Bayes, Bagging with Multinomial Naive Bayes, and Random Forest algorithms. The performance of these algorithms is measured using Precision, Recall, F1-Score, and Support. The accuracy of the algorithms is also evaluated using train accuracy score, test accuracy score, train ROC-AUC Score, test ROC-AUC score, area under precision-recall curve, and area under ROC-AUC. This study shows that labeling generates a significant value, which means that the user’s negative and positive comments need to be considered by the E-wallet manager in order to improve the quality of the system and services.
A Proxy-Layer Approach to Secure Smart Contract Deployment on Private EVM-Based PoA Blockchains

Within the enterprise sector, there is a growing trend of adopting private and consortium blockchains to leverage the benefits of blockchain technology. Networks based on Proof-of-Authority (PoA) and compatible with the Ethereum Virtual Machine (EVM) are particularly advantageous in this scenario, providing both efficiency and straightforward setup. While private blockchains inherently enhance security by their permissioned nature, which restricts node participation to authorised entities only, it’s crucial to recognise the ongoing necessity for additional safeguards. These safeguards are essential to guarantee that only verified and trustworthy smart contracts are deployed. A key concern in this realm is addressing particular attack vectors, such as front-running attacks. This paper presents an innovative proxy-layer solution designed to integrate effortlessly with any EVM-compatible blockchain, thereby strengthening both governance and security aspects.
Practical approach for replacement concept in curative system operation

The Paper focuses on the planning process for the replacement concept of a curative measure with limited operating time, using the example of a battery storage. The article outlines the essential steps involved in the curative use of battery storage and describes a practical approach to determining the replacement concept, including the identification of critical network usage cases and the regulatory and power plant deployment processes.
Ensuring Customer Satisfaction on Long Distance Train Journeys: An Indian Railways Case Study

Imagine embarking on a long journey, only to realize that a smartphone charger or the smart LED display in front of your seat is not functional. Ensuring customer satisfaction is important in building a loyal customer base and making the customer feel satisfied about the quality of their journey. This paper probes a significant lacuna within the Indian Railways that pushes the onus on the passenger to report a problem and then follow it up until resolution. Myriad ways of reporting problems confuse travelers. This paper advocates collection of passenger comfort data thru a smart phone application. An initial categorization of the problem is explained followed by building an intelligent system that solves problems quickly. Smarter resolution, with active participation of on-board staff and ways to incentivize the passenger reporting the problem are suggested. Unique customer satisfaction metrics and factors affecting them with examples to apply in the railways are explored. Equipment failure data gathered via the app, could be integrated with asset management databases for predicted maintenance. Finally, a staged implementation plan is proposed that uses Machine Learning (ML) models for life cycle assessment of parts.
Day-ahead PV Output Power Forecasting Utilizing Boosting Recursive LightGBM-LSTM Framework

Recently, global photovoltaic (PV) system installations have surged. Precise forecasting is vital for their grid integration and carbon emission cuts. However, due to fluctuating solar radiation, predicting PV output is difficult. Machine learning models, notably Long Short-Term Memory (LSTM) networks, offer a solution. This study presents a novel framework using a boosted recursive Light Gradient Boosting Machine (LightGBM)-LSTM network to forecast daily PV output at hourly intervals. Conducted in Northern Europe—a region with significant solar radiation variability—the models trained on meteorological and historical data showed a 12% improvement in RMSE, a 13% reduction in MAPE, and a 5% increase in the R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> score compared to standalone LSTM models.
Defining Functional Illiteracy to Empower Inclusive Technology Design

Limited literacy presents a significant challenge in HCI research, yet the field lacks consistent definitions and measurement criteria. Researchers often interchange terms such as 'functional illiterates,' 'low literates,' and 'semi-literates,' further complicating the field. This paper conducts a systematic literature review (SLR) of 33 HCI studies, revealing concerns about the absence of a definition in 41% of the studies and the lack of measurement technique in 74%. Based on the results from our SLR and relevant research beyond HCI, we propose the following work-in-progress definition. 'Functional illiterates are motivated adults with some familiarity with text but insufficient to fully comprehend meanings and low skills in the measured digital skill, with enough language proficiency in the study language if they are literate in their native language. This understanding, coupled with addressing the identified issues, will empower the HCI4D community to design more inclusive technology solutions for functionally illiterate users in developing countries.
SOCIAL ASPECTS OF EDUCATIONAL INFORMATIZATION

The article analyzes the impact of information on education. This computerization is seen as a social phenomenon. The author refers to the origins of the formation of Social Informatics of the last century, highlighting the social significance of informatization of society as a whole. Understanding the educational space as part of the social, the author shows the influence of information as a social phenomenon on all components of the educational space, while stressing the four leading social aspects. These aspects of the conviction of the author are the following: changes in the components of the educational process under the influence of informatization; change themselves subjects of educational space under the influence of informatization; alteration of the boundaries of space and proper educational change axiological field of educational space, requiring information security measures. The article convincingly proved the lack of educational research in the analysis of social values and social aspects of informatization of educational space. Because of this kind of research is carried out in the sociology and philosophy, pedagogy open to the prospects of new research areas.
Interpreting the Body

Broadening the landscape of body and embodiment theory, the chapters curated and juxtaposed in this edited collection draw attention to the processes and problems of understanding bodies within and across different social contexts and interpretive frameworks. The range of analytic perspectives employed by the book’s contributors offers a unique opportunity to investigate the conjunctions and disjunctions between different interpretive traditions’ respective approaches to grasping the meaning and matter of bodies and social life. The theoretical paradigms advanced within the volume challenge the limits of what we know about bodies and interpretation and highlight the promise of interpretation as a focal metaphor for analyzing bodies and embodiment. Interpretation as a concept advances the study of the body as a simultaneously material and semiotic entity. It directs us to consider how and why some aspects or details of the body and embodiment emerge as more notable or important than others, thus revealing how patterns of social, moral, and political salience generate the attentional topography of the body’s materiality. This explicit attention to interpretation as process is part of what distinguishes interpretation from prior concepts of the social construction of the body, which, when centered in systems of language, tend to overlook the structural or material processes and mechanisms through which the social construction of the body takes place.
A Correlational Study Between Students’ Learning Motivation, Vocabulary Mastery And Pronunciation

The aim of this research is to find out whether there is significant correlation between the students’ learning motivation, vocabulary mastery and pronunciation skill at SMPN 5 Langsa. The method of this research is quantitative with correlational design. The research object of this research is 55 students. The data were collected by applying test and questionnaire. Indeed, based on the result of the research, it showed that there is a positive correlation between students’ learning motivation and pronunciation skill at SMPN 5 Langsa, there is a positive correlation between students’ vocabulary mastery and pronunciation skill, and there is a positive correlation between students’ learning motivation, vocabulary mastery and pronunciation skill. It can be concluded that students’ learning motivation gives contribution to both their vocabulary mastery and their pronunciation skill. Additionally, when students have high motivation in learning, it can be beneficial to them in order to improve their vocabulary mastery and their pronunciation skill.
Abacus Algorithms: A Pure Mathematical Approach to Ancient Calculation Tools

The abacus is one of the oldest calculating tools still in use today. Despite its simplicity, the bead-based interface allows users to conduct complex mathematical operations through a system of sliding beads along wires or rods. While the physical abacus itself provides an intuitive and visual approach to calculation, the underlying operations rely on fundamental mathematical principles. This paper provides a comprehensive mathematical framework that formally describes the algorithms behind abacus calculations. Beginning with basic abacus configuration, we define key components like rods, beads, and bead values required to model abacus states. We then characterize the core abacus algorithms for addition, subtraction, multiplication, and division through set notation, recurrence relations, and state transition diagrams. Our formalized abacus algorithms leverage concepts from number theory, modular arithmetic, combinatorics, and algebra. In addition to offering new mathematical insights into ancient technologies, our work helps bridge connections between the tangible abacus interface and the abstract algorithms powering it. Through examples and proofs, we show how bead manipulations precisely correspond to mathematical transformations. This level of formalization not only helps explain the effectiveness of the abacus, but also illustrates how even rudimentary calculation tools utilize profound mathematical ideas. Our mathematical abacus framework lays the foundation for further analysis as well as modifications and extensions of the classic abacus approach.
Using Adaptive Communications to Encourage Septic Conversion Through a Community-driven Process

Using Adaptive Communications to Encourage Septic Conversion Through a Community-driven ProcessAbstractAs part of a multi-pronged strategy to reduce nutrients for the Chesapeake Bay, the Anne Arundel County Department of Public Works (the County) launched a voluntary Septic-to-Sewer connection program in 2021 designed to make public sewer connections more affordable. HDR launched a public outreach program that emphasizes the public education of septic impacts on water quality and provides information on the new program. During more than two dozen outreach meetings, the project team gained important feedback from the community. At the end of the first program application cycle, the team compiled lessons learned in an application debrief meeting. The collaborative discussion informed program changes including communications strategies as well as policy changes. During the second application cycle the team further adjusted its approach to revise its message and the level of detail, which resulted in greater understanding by homeowners. Adaptive management of community outreach has fostered continuous improvement of program messaging.In 2021, Anne Arundel County, Maryland launched a voluntary Septic-to-Sewer connection program. HDR helped establish an outreach program to educate the public on water quality and to inform residents about the new program. During more than two dozen outreach meetings, the team compiled lessons learned and continued to adjust its message and level of detail, resulting in a greater understanding by homeowner.SpeakerHe, ZiweiPresentation time15:30:0016:00:00Session time15:30:0017:00:00SessionCommunications Plans and Actions: Septics, Source Control, and StakeholdersSession locationRoom S401a - Level 4TopicCollection Systems, Fundamental Level, PFAS, Public Communication and Outreach, Utility Management and LeadershipTopicCollection Systems, Fundamental Level, PFAS, Public Communication and Outreach, Utility Management and LeadershipAuthor(s)Heiner, GeorgeAuthor(s)G. Heiner 1; E. Shea 2 ; Z. He 2; R. Nance 2; G. Heiner 1;Author affiliation(s)Anne Arundel County Department of Public Works 1; HDR 2 ; HDR 2; Anne Arundel County Department of Public Works 1;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159119Volume / Issue Content sourceWEFTECCopyright2023Word count12