Reviewerly/exHarmony huggingface dataset:
The Mediating Effect of Job Satisfaction on the Relationship between Digital Connectivity and Job Performance

This dissertation aims to investigate the extent to which Digital Connectivity affects Job Performance, directly and through the mediation role of Job Satisfaction among employees in Egyptian private engineering consultancy companies. Building on Maslow’s Theory of Motivation/Satisfaction, the Conservation of Resources Theory, and the Job Demands-Resources Model, a questionnaire is distributed on a sample of employees to test the proposed hypotheses. The sample size used for analysis and interpretation consists of 412 respondents. Hypothesis testing is used to test the research hypotheses to conclude probabilistic statements about population parameters. Structural Equation Modeling technique is adopted to explore complex relationships among variables. The results suggest that increased Digital Connectivity is associated with higher levels of Job Performance and Job Satisfaction. Also, increased Job Satisfaction is associated with higher levels of Job Performance. Furthermore, Job Satisfaction has a mediating effect on the relationship between Digital Connectivity and Job Performance. This research recommends organizations in this industry to promote Digital Connectivity among employees, by facilitating access to relevant technologies and fostering a digital-friendly work environment. As such, organizations may be able to enhance employee performance in their assigned job roles. No studies have been found addressing the impact of Digital Connectivity on Job Performance in this context, thus the research contributes to a better understanding of how Digital Connectivity affects Job Performance.
A Novel Non-Linear Model Based on Bootstrapped Aggregated Support Vector Machine for the Prediction of Hourly Global Solar Radiation

The prediction of global solar radiation (GSR) for various regions is of great importance as it provides guidance for the design, modeling, and operation of solar energy conversion systems, the selection of suitable regions, and even informs future investment policies for decision-makers. This paper presents the methods for predicting hourly mean solar radiation using support vector machines (SVM), which is a machine learning algorithm based on statistical learning theory. The primary objective of this paper was to investigate the use of a support vector machine (SVM) based on quantitative structure–activity relationships, specifically a single support vector machine (SSVM) and a bootstrap aggregated support vector machine (BASVM), to predict hourly global solar radiation in Bouzareah city. A dataset consisting of 3603 data points was employed to develop both the SSVM and BASVM models. Bootstrap aggregation of SVM is utilized to enhance the accuracy and robustness of SVM models constructed from limited training datasets. The training dataset is resampled using bootstrap resampling with replacement to create an ensemble of SVM models, each trained on a different sample from the training set. A support vector machine model is developed, and individual Support Vector Machines (SVMs) are then combined to form a Bootstrap Aggregated Support Vector Machine (BASVM). Experimental data for global solar radiation (GSR) were compared to the calculated GSR, and excellent correlation coefficients (R) were found (0.9913) during the testing phase. This novel BASVM model could be utilized by researchers and scientists to design high-efficiency solar devices.
Influence of Principals’ Conflict Resolution Skills on Teachers’ Commitment in Public Secondary Schools in Ogun State

This study investigated the Influence of principals’ conflict resolution skills on teachers’ job commitment in public secondary schools in Ogun State. A descriptive research design was employed. The population for the study consisted of 3,109 teachers. A sample of six hundred and forty-five (645) respondents was selected. Three (03) instruments were used for data collection, namely: demographic data form, organizational commitment scale (r = .91), and Rahim organizational conflict inventory – II (r = .96). Findings showed that there was a significant influence of principals’ conflict resolution skills on teachers’ job commitment (R = .253; R2 = .064; Adj. R2= 063; F (1,636) = 43.508; P&lt; .05). Also, principals’ gender significantly moderated the influence of principals’ conflict resolution skills on teachers’ job commitment. Male principals have a significant moderating influence of principals’ conflict resolution skills on teachers’ job commitment (R =.376; R2 =.141; R2(adj) =.139; F (1,406) =66.563; P&lt;.05). Also, female principals do not have a significant moderating influence of principals’ conflict resolution skills on teachers’ job commitment (R =.048; R2 =.002; R2(adj) =-.002; F (1,230) =.525; P&gt;.05). Based on these findings, it was recommended that regular seminars should be organized to educate principals on conflict resolution strategies. Also, the Ministry of Education should organize extensive in-service development programs and/or encourage the principals to go for short courses in educational management with specific emphasis on leadership skills and styles and conflict management in schools irrespective of their gender.
Analisis Minat Belajar Matematika Siswa Pada Pembelajaran Daring dikelas IV Sekolah Dasar

The background of this research was made after the arrival of the covid-19 virus outbreak which caused changes in the learning system. Interest has a great meaning in learning activities because interest has a very large role in supporting success. Someone will be successful when interested in something that is being studied and will automatically show their activeness in participating in learning. Therefore, it is important to find out around the categorization of students' interest in learning, especially in learning mathematics. This study uses a quantitative style with a quantitative descriptive method. The sample in this study was the fourth-grade elementary school students totaling 40 people. The descriptive method consists of describing students' interest in learning mathematics in the current online learning situation. The instrument used by researchers in collecting data is in the form of questionnaires and interviews. The study revealed that the online learning process was carried out using the WhatsApp application media. The use of WhatsApp is used to adjust the ability of teachers and school policy agreements. The learning process takes place quite effectively and is easy to reach by teachers, students, and parents. Then it is seen that the interest in learning mathematics in online learning is very diverse. There is very high interest in learning as many as 16 students (40%), quite high interest in learning as many as 18 (45%) students, high interest in learning as many as 5 (12.5%) and those who have a very low interest are 4 students (2,5%).
Analisis Tanggung Jawab Belajar Siswa dalam Model Pembelajaran E-Learning di Kelas III SDN Mekarsari I Kabupaten Tangerang

Elementary School which conducts basic education is an educational institution that organizes educational programs as a basis for student preparation that can be used for higher. Responsibility on learning somehow become important for students in an online learning situation for elementary school students. This research was conducted to analyze the learning responsibility of students in the Mekarsari I public elementary school, Tangerang district. This research uses a qualitative approach with a case study method. The subjects of this study were teachers and students. Through research instruments in the form of observation sheets, interview sheets, and student questionnaires, researchers conducted research in class III with a total of 36 students. The results showed that learning responsibilities such as doing assignments on time and being responsible for the rules that apply in the school of students in the e-learning model in class III Mekarsari I public elementary school was good enough. Because every time students did learning they were responsible according to what was done and according to their abilities with the help of the role of teacher and parents and the role of students learning public elementary school although not optimal or not always perfect.
Terampil Membaca Dengan Pengajaran Kelancaran Membaca Gaya Credo

In this study, the researcher tried to explain the application of credo-style fluency teaching to improve reading skills of elementary school students, where they have gone through the prefix reading process so that high-grade students should be able to read fluently with understanding. But in reality, after students are tested using the KBPM standard (Correct Words Per Minute), there are still many students who get scores below their class ability level. Respondents in this study were grade 6 elementary school students. This research uses qualitative methods with case studies. The data in this study were obtained through observations made virtually due to the pandemic, interviews with teachers and the Credo team, and documentary studies to see the implementation plan of learning and student outcomes after teaching. The conclusion of this study is the teaching of Credo style fluency is carried out in three stages, namely pre-test, teaching, and post-test. To be able to carry out Credo style teaching, a preliminary test must be carried out to see the students' abilities. All students who took fluency teaching experienced a significant change as seen from the increased KBPM score during the post-test and the student's ability to answer questions during text discussion. Out of a total of 7 students, 4 students managed to advance one level from their pre-teaching ability. It concluded that Credo style was assumed as effective to elementary school.
Pengaruh Penerapan Belajar Dari Rumah Terhadap Motivasi Belajar Siswa SDN Serdang Wetan

This study aims to examine whether the application of learning from home affects students' learning motivation. The research method uses a survey method with a quantitative approach and the research instrument uses a questionnaire with a Likert scale of 5 answer choices. The population in this study were all upper-level class students of Serdang Wetan State Elementary School in Legok District, Tangerang Regency, Banten. The sample of this study consisted of 30 students who were randomly selected from 3 classes, the sampling was determined by probability sampling technique with the type of simple random sampling. The results showed that (1) the implementation of learning activities from home has a implementation percentage value of 69.43% which is categorized as good enough; (2) student motivation in learning and participating in learning carried out from home has a percentage value of 79.11% which is categorized as good enough. The implication of this research is that good student self-motivation can certainly encourage learning motivation to carry out learning carried out from home.
Explainability-based Metrics to Help Cyber Operators Find and Correct Misclassified Cyberattacks

Machine Learning (ML)-based Intrusion Detection Systems (IDS) have shown promising performance. However, in a human-centered context where they are used alongside human operators, there is often a need to understand the reasons of a particular decision. EXplainable AI (XAI) has partially solved this issue, but evaluation of such methods is still difficult and often lacking. This paper revisits two quantitative metrics, Completeness and Correctness, to measure the quality of explanations, i.e., if they properly reflect the actual behaviour of the IDS. Because human operators generally have to handle a huge amount of information in limited time, it is important to ensure that explanations do not miss important causes, and that the important features are indeed causes of an event. However, to be more usable, it is better if explanations are compact. For XAI methods based on feature importance, Completeness shows on some public datasets that explanations tend to point out all important causes only with a high number of features, whereas Correctness seem to be highly correlated with prediction results of the IDS. Finally, besides evaluating the quality of XAI methods, Completeness and Correctness seem to enable identification of IDS failures and can be used to point the operator towards suspicious activity missed or misclassified by the IDS, suggesting manual investigation for correction.
On Detecting Biased Predictions with Post-hoc Explanation Methods

We develop a methodology for the analysis of machine learning (ML) models to detect and understand biased decisions and apply it to two specific scenarios. In particular, we show how analyzing model predictions across the dataset, comparing models trained on different subsets of the original data, and applying model-agnostic post-hoc explanation tools can help identify bias in a model in general as well as in specific instances. Further, we consider several definitions of bias and fairness, and show how each provides a different interpretation of the model decisions.
Active Few-shot Learning For RouteNet-Fermi

Machine-learning-based Network Modeling requires a compact training data set that contains diversified network topology and configurations covering different congestion levels. We formalize the problem of modeling network delay using Multi-stage Message Passing Graph Neural Networks (GNNs) under the constraints of a limited number of training samples and a limited number of nodes for the topology of each sample as a few-shot learning problem. To tackle it, we propose an active learning algorithm that selectively randomizes initial features that are invariant of node numbers and then uses pool-based uncertainty sampling for selecting the approximated optimal network topology based on the Shannon entropy. The approximation could be theoretically proven and confirmed with experimental results.
DataZoo: Streamlining Traffic Classification Experiments

The machine learning communities, such as those around computer vision or natural language processing, have developed numerous supportive tools and benchmark datasets to accelerate the development. In contrast, the network traffic classification field lacks standard benchmark datasets for most tasks, and the available supportive software is rather limited in scope. This paper aims to address the gap and introduces DataZoo, a toolset designed to streamline dataset management in network traffic classification. DataZoo provides a standardized API for accessing three extensive datasets--CESNET-QUIC22, CESNET-TLS22, and CESNET-TLS-YEAR22. Moreover, it includes methods for feature scaling and realistic dataset partitioning, taking into consideration temporal and service-related factors. The DataZoo toolset simplifies the creation of realistic evaluation scenarios, making it easier to cross-compare classification methods and reproduce results.
Semantic aspects of musical language

Music is a multifaceted phenomenon: it carries the mission of aesthetic education and enlightenment, performs therapeutic functions and is not only a source of information, but also the subject of filling human consciousness with a sense of joy, drama, and a high spiritual beginning. All the above is provided due to the many components that constitute the whole picture of musical art. These include intonation and rhythm, tempo and dynamics, timbre and texture, and more voluminous components: genre and form. Each of its elements represents a certain category, which, in turn, carries a semantic load or semantic aspect belonging to it. Having a centuries-old history of existence, music and, accordingly, its components have undergone considerable evolution. The purpose of the study is to show the semantic aspects of musical language as an integral system in their continuous dynamics of development, updating, and complication of content. The history of sound creativity is a vivid picture of styles and techniques of writing, images, and themes inherent in a particular era. The above is inextricably linked with the deep evolution of semantic aspects that convey the content and importance of all the leading categories of music. They represent, regardless of the period, an integral system of elements, the transformation of which is discussed in this article. The definition of the boundaries of "evolution" in relation to music, the disclosure of its action at various levels (the evolution of musical thinking, the evolution of national style, artistic area, the evolution of individual compositional style), the development of the theory of evolution in the field of functioning of musical phenomena – these and other problems are priorities for modern scientific musicology and art criticism. Realising the complexity and globality of the problem posed, the basis of which is the consideration of musical phenomena in the aspect of the theory of evolution, this article includes one of the possible approaches to solving this issue, involving the "general theory of systems" created in the 20th century. For that reason, this publication is relevant. It combines the most important theses of researchers investigating the problem of the semantics of the musical language in the context of such disciplines as pedagogy, quantum physics, medicine, social science. The study searches for the materials on the studied subject, their systematisation, and provides a panoramic display of the analysis of the semantic aspects of musical art. The author also shares the prospects of analysis of the mentioned phenomenon. The need for this research is conditioned by the essence of the subject, since it constantly changes, gets enriched with new qualities, actively responding to what is happening in real-time.
Social Media and Computer-Mediated Communication

Within a cyberpragmatic framework rooted in cognitive pragmatics (Yus 2011), context is basically information that is brought to bear in turning the schematic coded input (e.g., spoken, written, or typed words) into interpretations. Although it is undeniable that contextual information may stem from different sources, eventually what is at stake in contextualization is to mentally assess and select the appropriate quality and quantity of information that allows us to reach meaningful interpretations. Regarding the specificity of social media and internet communication overall, several challenges for pragmatic analysis arise, some of which will be addressed in this chapter. Specifically, what interests most in an analysis of context online are: (a) the role of the interfaces in favoring/limiting the contextualization of utterances; (b) the role of the physical-virtual interface in today’s internet-mediated communication; and specially (c) the differentiation of the user’s personal, interactive, and social contexts managed in everyday virtual communication.
Statistical Serialism and <i>Vagues, chemins, le souffle</i> (1970–1972)

This chapter and the next focus respectively on Grisey’s last two student compositions, in which salient features of his mature music begin to appear in germinal form. Vagues, chemins, le souffle is scored for two spatialised orchestras and amplified clarinet. The chapter details how Grisey adopted and creatively modified techniques from the post-war modernist composers Xenakis, Boulez, and Stockhausen, and how the latter music, often referred to as sound-mass music, should be considered in actuality a continuation of serialism’s principles applied to statistical masses. In this regard, Grisey’s music developed through creative engagement with serialism. The aspects of Grisey’s music covered are the use of resonance models and the harmonic spectrum, the composition of auditory processes, the composition of sound metabolisms, and the notion of a large-scale orchestral simulation of a small-scale instrumental timbre.
Dynamic illumination in phase-shifting interferometry

Phase-shifting interferometry is the premier measurement technique for high-precision surface form metrology. Generally, the measurement cavity is illuminated with a stationary, on-axis, point-like source of coherent light situated at the interferometer source plane. We describe how to enable a variety of useful functions to aid interferometric metrology applications by dynamically moving the source point during a phase-shifting measurement using steering mirror technology. Called Dynamic Illumination, these motions describe trajectories that often take the form of geometric primitives like points, lines, arcs, circles, and spirals. A fixed point on the optical axis represents conventional operation, but measurements using different trajectories enable different functions. We highlight three exemplary functions in this paper; phase shifting, autofocus, and coherent noise reduction techniques.
High-precision 3D metrology for stacked diffractive augmented reality waveguides

Diffractive waveguides for Augmented Reality (AR) are often stacks of 2 or 3 single waveguides, with each individual waveguide designed for 1 or 2 narrow-band wavelength bands. For best image quality, the optical axes of all elements of the waveguide stack must coincide to well below 1 arcmin for all 3 RGB colors, otherwise chromatic aberration effects at edges occur, severely reducing the image quality for the user. Therefore,1) the optical axis of each waveguide in the stack must be characterized after manufacturing and compatible sets of waveguides must be matched; 2) the stacking process must not introduce tilt errors. Metrology solutions for both 1) and 2) and the effect of errors on the image quality of the finished waveguide will be presented.
Absolute shape measurement with coaxial deflectometry: towards interferometric accuracy

Deflectometry (shape measurement of a mirror from the distortion of the image of a monitor screen displaying fringes) has been known for a long time, but suffers from intrinsic features that make accurate absolute measurements very difficult. In particular, all the metrological quality depends on the ultra precise identification of the system geometry: ray trajectories in the object space, shape of the monitor screen, position of this screen and position of one point of the measured object, all these in the camera frame of reference. We present an instrument that permits all these identifications in a simple push-button way. The fundamental ambiguity of deflectometry (a single measurement may correspond to an infinite number of object shapes, due to the unknown constant after slopes integration) is raised with our patented coaxial deflectometry approach: two measurements are made with an axial movement of the camera, and only one shape is compatible with these two measurements. We present the identification methodology of the system, and results for absolute measurements of spheres, aspheres and freeforms, within a &lambda;/40 accuracy, with some comparisons with results obtained with a Taylor-Hobson LUPHOScan&reg;.