Reviewerly/exHarmony huggingface dataset:
Prediction of Direct and Diffuse Solar Radiation on Pokhara, Nepal

The measurement of direct and diffuse solar radiation is not easily possible because instruments are quite expensive. The main objective of this study was to predict direct solar radiation (IB) and diffuse solar radiation (ID) on Pokhara (28.186643o N, 83.97518o E, 800 m asl) for a period of one year (2017). Daily data of spectral Aerosol optical depth (AOD) and total ozone column are obtained from NASA website. The maximum value of direct solar radiation and diffuse solar radiation values were found 932.9 ± 65.9 W/m2 in January and 363.0 ± 87.9 W/m2 in February respectively. The minimum value of direct solar radiation and diffuse solar radiation values were found 692.8 ±142.0 W/m2 in April and 107.7 ± 20.4 W/m2 in July respectively. The diffuse solar radiation changes with season. The annual average of direct solar radiation and diffuse solar radiation are found 808.1± 133.7 W/m2 and 220.8 ± 102.8 W/m2 and respectively. The results of this research work will help further identification, impact and analysis of solar radiation in different locations in Nepal with the same geographic conditions.
Salary Prediction Based on the Dual-Adaboosting System

This paper aims to build a salary prediction model based on the Dual-Adaboosting System which is an improvement method of the Adaboosting algorithm.Adaboosting feature importance ranking method is employed for the paper to conduct feature filtering after the dataset is cleaned and preprocessed.Afterward, regression prediction models were established using different methods to help obtain comparative and analytical results based on RMSE and MAE, serving as a control experiment.Finally, we conducted experiments using the Dual-Adaboosting system and obtained the final salary prediction model.This model definitely has practical reference significance for human resources management and the improvement of the Adaboosting algorithm.
Design and Implementation of Donation Information Traceability System Based on Blockchain

With the development of philanthropy and people's growing attention to charity activities, the role of online donation platforms is becoming increasingly prominent.To solve the problems of opaque information on the existing donation platform, maliciously tampered information on the flow of donations, we designed and implemented a donation information traceability system based on the blockchain.The system can be divided into two parts: the donation and the aided module, and has three major layers: a data storage layer, a functional module layer, and an application layer.The donation information traceability system not only enhances the transparency of the donations' information but also reduces the labor cost required for information disclosure.Moreover, the system expands the role of the charity sector in Chinese society.
Innovation and Entrepreneurship: Key Insights from a Multidisciplinary Review of Big Data and Blockchain Literature

Big data and blockchain technology are critical enablers of innovation and entrepreneurship.These technologies provide entrepreneurs access to valuable data insights and new business ways, enabling them to create new products and services, identify new markets and opportunities, and develop more effective marketing strategies.In this paper, the scientometric analysis method is used to systematically search the Web of Science (WoS) database and a total of 221 research papers retrieved from 1900 to 2023 are selected.Based on the analysis and visualization of the results using Vosviewer and Bibliometrix software.The results show that this research topic has shown rapid growth since 2017, and there are three groups of keywords, including entrepreneurship, and value & creation, and dynamic & capabilities, which correspond to the most research contributions.Among the subject countries, China, Italy, and the United Kingdom are the most important in this field.
Feasibility of Implementing a Metadata Service for Cataloguing in Tamil

This study examined the feasibilityy of introducing a metadata service for cataloguing records in Tamil. Thee main objective was to determine the potential benefits and challenges aasssociated with this service. To achieve this, a survey methodology was emmployed to collect data and assess the feasibility of the metadata service. TThe results of the study indicate that a metadata service would be a valuabblle e tool for cataloguing records in Tamil. However, the study also highlightss technical difficulties, such as internet connectivity issues, that may presenntt significant challenges in implementing the service. The study also idennttifies the need for computer literacy programmes for librarians beforee implementing the metadata service. Furthermore, the study concludes thhaat the introduction of a metadata service is unlikely to reduce cataloguing timme or the need for human resources. The study specifically offers valuable iinnsights into the potential benefits and challenges that arise from the introodduction of a metadata service in public libraries located in the Jaffna districtt.
AROUND THE ERDÖS–GALLAI CRITERION

By an (integer) partition we mean a non-increasing sequence \(\lambda=(\lambda_1, \lambda_2, \dots)\) of non-negative integers that contains a finite number of non-zero components. A partition \(\lambda\) is said to be graphic if there exists a graph \(G\) such that \(\lambda = \mathrm{dpt}\,G\), where we denote by \(\mathrm{dpt}\,G\) the degree partition of \(G\) composed of the degrees of its vertices, taken in non-increasing order and added with zeros. In this paper, we propose to consider another criterion for a partition to be graphic, the ht-criterion, which, in essence, is a convenient and natural reformulation of the well-known Erdös–Gallai criterion for a sequence to be graphical. The ht-criterion fits well into the general study of lattices of integer partitions and is convenient for applications. The paper shows the equivalence of the Gale–Ryser criterion on the realizability of a pair of partitions by bipartite graphs, the ht-criterion and the Erdös–Gallai criterion. New proofs of the Gale–Ryser criterion and the Erdös–Gallai criterion are given. It is also proved that for any graphical partition there exists a realization that is obtained from some splitable graph in a natural way. A number of information of an overview nature is also given on the results previously obtained by the authors which are close in subject matter to those considered in this paper.
IMPLEMENTATION OF THE TWO STAY TWO STRAY MODEL TO INCREASE SOCIAL STUDIES LEARNING OUTCOMES

This study examines how effective the application of the Two stay Two Stray model is in increasing social studies learning outcomes in grade IV public elementary school 2 Pungan. This research uses a type of classroom action research where two cycles will be carried out, each cycle consisting of two meetings. The subjects in this study were all 14 students of class IV. Sources of data in the study were obtained from the learning outcomes of 14 students, there were 9 students who had not yet mastered the teaching criteria and 5 students had achieved mastery. Data collection techniques were obtained from the results of observations at each meeting and the administration of written tests. The research procedure consists of problem identification, problem analysis, preparation of action plans, implementation of observations, and preparation of a final report. This research will be carried out in two cycles. In each cycle, two meetings are held which describe the action, action planning, implementation of observation, analysis and reflection at the end of each meeting. Based on data on social studies learning outcomes, class IV students have experienced an average increase starting from before being given treatment (pre-action), cycle I, and cycle 2. The average score before being given treatment using the two stay two stray learning model is 59.3, after given learning improvement treatment in cycle 1 the average was 71.3 and 87.7 in cycle 2 with KKM 70.
IMPROVING INTENSIVE READING SKILLS WITH THE KNOW WANT TO KNOW LEARNED STRATEGY

The problem in this study is the low intensive reading skills of students in Indonesian content which is below the KKM. This study aims to describe the difference in the effect of the intensive reading skills of students in the experimental class who received the Know Want To Know Learned learning strategy and the control class who did not receive the Know Want To Know Learned learning strategy and to describe the differences in the improvement of intensive reading skills of the experimental class students who used the strategy. Know Want To Know Learned learning with a control class that does not use the Know Want To Know Learned learning strategy. The method used is Quasi-Experimental, and the research design is Nonequivalent Control Group Design. The research subjects were 41 students of class V SD Negeri Cigarukgak. The instrument used in this research is a description test. The results showed that the posttest results were greater than the pretest results. There are differences in students' intensive reading skills after being given treatment using the Know Want To Know Learned learning strategy. The difference in increasing intensive reading skills can be seen from the results of the n-gain test, namely the medium category to the high category. There is a difference in the increase in students' intensive reading skills using the Know Want To Know Learned learning strategy.
PEMANFAATAN MEDIA PEMBELAJARAN MATEMATIKA DIGITAL BERBASIS EDUGAME WORDWALL TINGKAT SEKOLAH DASAR DI DESA SIDOREJO

One of the aims of this Potential-Based Community Service is to increase enthusiasm for learning mathematics and introduce fun mathematics learning for children in Sidorejo Village. Because all this time learning mathematics seems very scary and less fun if it is studied with the wrong method. This problem becomes a separate focus point for each element of education. The implementation method in this activity was carried out in Sidorejo Village, Jabung District, Malang Regency by applying face-to-face edugame wordwall-based digital mathematics learning with elementary school level children. After implementing this activity, it can be concluded that by utilizing digital mathematics learning media with wordwall software, it can improve students' abilities and enthusiasm in learning mathematics.
Using Quality Measures During the Software Development Process: Case Study of Cameroonian Software Industry

Many studies on software quality use a variety of techniques and tools to assess quality in IT organizations. However, it is still difficult to ensure the proper use of measures to guarantee software quality. Cameroon, like many developing countries, faces a number of challenges in its software industry including limited market size, poor infrastructure, and lack of software engineering best practices. This study evaluates the software quality measurement practices in Cameroon and identifies potential areas of improvement. This study conducted a questionnaire survey of 30 companies by identifying five main categories and nine research questions. 57% of the companies surveyed consider that the impact of the measures on the success of the project is significant, and the measurement findings are, by large, accessible to executives as well as to the staff concerned. Furthermore, the adoption of a measurement tool can improve the monitoring and management of software projects.
Scheduling Hybrid Spark Jobs Based on Deep Reinforcement Learning

As a popular big data computing framework, Spark requires effective job scheduling to optimize resource utilization and execute applications efficiently.However, the hybrid jobs (jobs with and without deadlines) and the heterogeneous clusters bring great challenges for job scheduling.In this paper, a job scheduling based on deep reinforcement learning is proposed.A weight-based job sorting strategy is designed to obtain better job scheduling.The proposed method is evaluated with large-scale real-world data.Experimental results show that more jobs can satisfy deadline constraints and the cost of cluster utilization is reduced.
Research on Mobile Financial Crime Prevention Strategy Based on Blockchain Technology

Due to the difficulty of collecting evidence and supervision, mobile financial crimes face governance difficulties.By using the unique technical advantages of blockchain, such as decentralization and multiple digital signature, it can help with the punishment and evidence collection of mobile financial crimes and form a mutual trust mechanism of mobile financial ecosystem.When blockchain technology is applied to to prevent mobile financial crimes, it is essential to continuously optimize the prevention strategy through the construction of mobile financial supervision information application platform and a mobile financial crime early warning system, to improve the crime fighting strength and governance efficiency.
A COMMON FIXED POINT THEOREM FOR FOUR LIMIT COINCIDENTLY COMMUTING SELFMAPS OF A S-METRIC SPACE

In this paper we prove a common fixed point theorem for four selfmaps of a S -metric space.Also we deduce a common fixed point theorem for four selfmaps of a complete S-metric space.Moreover we show that a common fixed point theorem for four selfmaps of a metric space proved by Brian Fisher follows as a particular case.
Many-Criteria Optimisation and Decision Analysis Ontology and Knowledge Management

In this chapter, we present a Many-Criteria Optimisation and Decision Analysis (MACODA) Ontology and MACODA Knowledge Management Web-Based Platform (named MyCODA, available at http://macoda.club ) for the research community. The purpose of this initiative is to allow for the collaborative development of an ontology to represent the MACODA knowledge domain and to make available a set of integrated tools for its use by researchers and practitioners. MyCODA is a knowledge-based platform to identify and describe MACODA research constructs, and to explore how these constructs relate to each other. It is designed to model and systematise the knowledge created by the MACODA research community, supporting features such as querying and reasoning, by means of formal logics, and use cases such as training new learners and finding research gaps in the MACODA research domain.
Morphological anomalies of blood cells in COVID-19 patients

Since March 2020, the laboratorys workflow has been significantly modified and implemented to address the pandemic. Molecular as well as morphological features
Virtual Reality Photo-based Tours for Teaching Filipino Vocabulary in an Online Class in Japan: Transitioning into the New Normal

When educational institutions worldwide scrambled for ways to continue their classes during lockdowns caused by the COVID-19 pandemic, the use of information and communication technology (ICT) for remote teaching has become widely considered to be a potential solution. As universities raced to implement emergency remote teaching (ERT) strategies in Japan, some have explored innovative interventions other than webinar platforms and learning management systems to bridge the gap caused by restricted mobility among teachers and learners. One such innovation is virtual reality (VR). VR has been changing the landscape of higher education because of its ability to "teleport" learners to various places by simulating real-world environments in the virtual world. Some teachers, including the authors of this paper, explored integrating VR into their activities to address issues caused by geographical limitations brought about by the heightened restrictions in 2020. Results were largely encouraging. However, rules started relaxing in the succeeding years as more people got vaccinated. Thus, some fully online classes in Japan shifted to blended learning as they moved toward fully returning to in-person classes prompting educators to modify how they implemented their VR-based interventions. This paper describes how a class of university students in Japan who were taking a Filipino language course experienced a VR-based intervention in blended mode, which was originally prototyped during the peak of the ERT era. Moreover, adjustments and comparisons regarding methodological idiosyncrasies and findings between the fully online iteration and the recently implemented blended one are reported in detail. &#x0D; Keywords: virtual reality, immersive open pedagogies, immersive learning
Non-Gaussian State Generation Using A Photon Detector With Finite Timing Jitter

We formulate for the first time the effect of photon detector's timing jitter on non-Gaussian state generation. As a result, we obtain the quantitative relation between the jitter and the fidelity of the generated state.
CSF-Glioma: A Causal Segmentation Framework for Accurate Grading and Subregion Identification of Gliomas

Deep networks have shown strong performance in glioma grading; however, interpreting their decisions remains challenging due to glioma heterogeneity. To address these challenges, the proposed solution is the Causal Segmentation Framework (CSF). This framework aims to accurately predict high- and low-grade gliomas while simultaneously highlighting key subregions. Our framework utilizes a shrinkage segmentation method to identify subregions containing essential decision information. Moreover, we introduce a glioma grading module that combines deep learning and traditional approaches for precise grading. Our proposed model achieves the best performance among all models, with an AUC of 96.14%, an F1 score of 93.74%, an accuracy of 91.04%, a sensitivity of 91.83%, and a specificity of 88.88%. Additionally, our model exhibits efficient resource utilization, completing predictions within 2.31s and occupying only 0.12 GB of memory during the test phase. Furthermore, our approach provides clear and specific visualizations of key subregions, surpassing other methods in terms of interpretability. In conclusion, the Causal Segmentation Framework (CSF) demonstrates its effectiveness at accurately predicting glioma grades and identifying key subregions. The inclusion of causality in the CSF model enhances the reliability and accuracy of preoperative decision-making for gliomas. The interpretable results provided by the CSF model can assist clinicians in their assessment and treatment planning.
Channel Prediction-Based Security Authentication for Artificial Intelligence of Things

The emerging physical-layer unclonable attribute-aided authentication (PLUA) schemes are capable of outperforming traditional isolated approaches, with the advantage of having reliable fingerprints. However, conventional PLUA methods face new challenges in artificial intelligence of things (AIoT) applications owing to their limited flexibility. These challenges arise from the distributed nature of AIoT devices and the involved information, as well as the requirement for short end-to-end latency. To address these challenges, we propose a security authentication scheme that utilizes intelligent prediction mechanisms to detect spoofing attack. Our approach is based on a dynamic authentication method using long short term memory (LSTM), where the edge computing node observes and predicts the time-varying channel information of access devices to detect clone nodes. Additionally, we introduce a Savitzky–Golay filter-assisted high order cumulant feature extraction model (SGF-HOCM) for preprocessing channel information. By utilizing future channel attributes instead of relying solely on previous channel information, our proposed approach enables authentication decisions. We have conducted extensive experiments in actual industrial environments to validate our prediction-based security strategy, which has achieved an accuracy of 97%.
Role of Order and Layers on the Polarimetric Response of Self-assembled, Metaphotonic Films

The polarized diffraction from conducting-polymer nanofibrous hollow spheres is varied with film doping, layering, and multiple scales of order (fiber, grain, and crystal). We characterize the metaphotonic response of varied structures for future information-processing applications.
Wavelength-Selective Distribution of Polarization Entanglement over Deployed Fiber

We demonstrate distribution of polarization entangled photon-pairs across multiple channels in a 6 km loop of deployed fiber. We use an all-optical networking switch to route Bell-state photons in three different wavelength pairs and verify entanglement distribution in all channel pairs by measuring two-photon interference fringes.
Ultra-Efficient Plasmonic Phase-Change Devices on SOI Platform

Small footprints and low energy consumption are the long-seeking metrics for photonic computing. Here, we combine grating structures with plasmonic nanogap devices and demonstrate less than 4pJ optical switching energy with stable multilevel performance.
Current Approaches for Engaging Parents in Students’ Academic Performance: Basis for Parental Engagement Policy

This action research aims to determine the current approaches that the school has employed to enhancing parental engagement on the academic performance of the students in the new normal. The participants were of the selected 35 high school teacher, which contains 21 Junior High School teachers and 14 Senior High School teacher, from Valeriano E Fugoso Memorial High School at Boys Town Complex Parang, Marikina City. Parental engagement at school approaches includes volunteering, conferencing with teachers, attending workshops, involvement at school decision making. Also, the parental engagement in the student’s education at home approaches includes helping on homework, communicating encouragement and educational expectation. Results displayed that these approaches enabled parental engagement. Mostly, optimistic comment information from the parents were stimulated and promoted better insight of their child’s performance in school. A significant effect on the academic performance of the learner in PreCalculus course towards the engagement of the parents, whether at home or at school in the new normal. Similarly, parents became more involved both at home and school activities because of the effect of the several approaches which have improved performance in PreCalculus.
PENGARUH MEDIA PAPAN BALIK (FLIPCHART) TERHADAP HASIL BELAJAR IPS MATERI PEMANFAATAN SUMBER DAYA ALAM KELAS IV SDN JEPARA 1/90 SURABAYA

This study aims to describe the effect of Flipchart Media on the social studies learning outcomes of fourth grade students at SDN JEPARA 1/90 Surabaya. The urgency of this research is the need for efforts to improve the quality of the process and student learning outcomes. Social studies learning process that only utilizes learning resources from books and is not interactive can have an impact on student learning outcomes that are not optimal. The approach used is a quantitative approach with experimental research. The type of design used is Quasi Experimental Design. The population used in this study amounted to 72 students and the research sample amounted to 36 students. The data collection used is multiple choice test questions. The test technique used is pre-test and post-test to determine student learning outcomes. Based on data analysis, it is concluded that: 1) There is an effect of using flipchart media on the learning outcomes of fourth grade students at SDN JEPARA 1/90 2021/2022. This is evidenced by the results of hypothesis testing pairs 1 and 2 which reject H0 and accept Ha with a sig value. 2Tailed 0.000 &lt; 0.05.