Reviewerly/exHarmony huggingface dataset:
Examination of Digital Literacy Levels of University Students

In this study, it was aimed to determine the digital literacy levels of university students. The study also aimed to examine the differentiation status of university students in terms of various variables of digital literacy levels. In addition, in the study, the digital literacy levels of university students were determined by gender, type of education (normal/secondary education), higher education level (associate / undergraduate/graduate), higher education program they are enrolled in, grade point average, class, average monthly income, social network with the most time spent. It is also aimed to examine the differentiation status in terms of the variables of average internet usage time during the day, the preferred tool for internet use, and the educational status of the parents. In this study, the survey model, which is one of the quantitative patterns, was used. The population of the study consisted of a total of 17,006 students, 11,500 undergraduate and 5,506 associate degree students, studying in 11 faculties, 4 colleges and 9 vocational colleges in the 2021-2022 academic year at a state university located in the Eastern Anatolia Region. The sample consisted of randomly selected 688 university students. The "Digital Literacy Scale" developed by Bayrakçı and Narmanlıoğlu in 2021 was used as a data collection tool. In the analysis process, nonparametric techniques were used since the data could not meet the assumptions of parametric techniques. As a result of the study, it was seen that the digital literacy levels of university students were low. In addition, it was concluded that there were statistically significant differences between university students' grade point averages, the social network they spend the most time on, the preferred tool in internet use, and the educational status of their parents and their digital literacy levels. Various suggestions were developed considering the results of the study.
Sundanese Stemming using Syllable Pattern

Stemming is a technique to return the word derivation to the root or base word. Stemming is widely used for data processing such as searching word indexes, translating, and information retrieval from a document in the database. In general, stemming uses a morphological pattern from a derived word to produce the original word or root word. In the previous research, this technique faced over-stemming and under-stemming problems. In this study, the stemming process will be improved by the syllable pattern (canonical) based on the phonological rule in Sundanese. The stemming result for syllable patterns gets an accuracy of 89% and the execution of the test data resulted in 95% from all the basic words. This simple algorithm has the advantage of being able to adjust the position of the syllable pattern with the word to be stemmed. Due to some data shortage constraints (typo, loan-word, non-deterministic word with syllable pattern), we can improve to increase the accuracy such as adjusting words and adding reference dictionaries. In addition, this algorithm has a drawback that causes the execution to be over-stemming.
A Hybrid Protection Method to Enhance Data Utility while Preserving the Privacy of Medical Patients Data Publishing

Medical patient data need to be published and made available to researchers so that they can use, analyse, and evaluate the data effectively.However, publishing medical patient data raises privacy concerns regarding protecting sensitive data while preserving the utility of the released data.The privacypreserving data publishing (PPDP) process attempts to keep public data useful without risking the medical patients' privacy.Through protection methods like perturbing, suppressing, or generalizing values, which lead to uncertainty in identity inference or sensitive value estimation, the PPDP aims to reduce the risks of patient data being disclosed and to preserve the potential use of published data.Although this method is helpful, information loss is inevitable when attempting to achieve a high level of privacy using protection methods.In addition, the privacy-preserving techniques may affect the use of data, resulting in imprecise or even impractical knowledge extraction.Thus, balancing privacy and utility in medical patient data is essential.This study proposed an innovative technique that used a hybrid protection method for utility enhancement while preserving medical patients' data privacy.The utilized technique could partition information horizontally and vertically, resulting in data being grouped into columns and equivalence classes.Then, the attributes assumed to be easily known by any attacker are determined by upper and lower protection levels (U P L and LP L).This work also depends on making the false matches and value swapping to make sure that the attribute disclosure is less likely to happen.The innovative technique makes data more useful.According to the results, the innovative technique delivers about 93.4% data utility when the percentage of exchange level is 5% using LP L and 95% using U P L with a 4.5K medical patient dataset.In conclusion, the innovative technique has minimized risk disclosure compared to other existing works.
On the naturalness of fuzzer-generated code

Compiler fuzzing tools such as Csmith have uncovered many bugs in compilers by randomly sampling programs from a generative model. The success of these tools is often attributed to their ability to generate unexpected corner case inputs that developers tend to overlook during manual testing. At the same time, their chaotic nature makes fuzzer-generated test cases notoriously hard to interpret, which has lead to the creation of input simplification tools such as C-Reduce (for C compiler bugs). In until now unrelated work, researchers have also shown that human-written software tends to be rather repetitive and predictable to language models. Studies show that developers deliberately write more predictable code, whereas code with bugs is relatively unpredictable. In this study, we ask the natural questions of whether this high predictability property of code also, and perhaps counter-intuitively, applies to fuzzer-generated code. That is, we investigate whether fuzzer-generated compiler inputs are deemed unpredictable by a language model built on human-written code and surprisingly conclude that it is not. To the contrary, Csmith fuzzer-generated programs are more predictable on a per-token basis than human-written C programs. Furthermore, bug-triggering tended to be more predictable still than random inputs, and the C-Reduce minimization tool did not substantially increase this predictability. Rather, we find that bug-triggering inputs are unpredictable relative to Csmith's own generative model. This is encouraging; our results suggest promising research directions on incorporating predictability metrics in the fuzzing and reduction tools themselves.
Investigating Real-Time Feedback of Energy Consumption and Emission Data Through Sonic Interaction Design

As buildings become increasingly automated and energy efficient, the relative impact of occupants on the overall building carbon footprint is expected to increase. Research shows that by changing occupant behaviour energy savings between 5 and 15 % could be achieved. A commonly used device for energy-related behaviour change is the smart meter, a visual-based interface which provides users with data about energy consumption and emissions of their household. This paper approaches the problem from a Sonic Interaction Design point of view, with the aim of developing an alternative, sound-based design to provide feedback about some of the data usually accessed through smart meters. In this work, we experimented with sonic augmentation of a common household object, a door mat, in order to provide a non-intrusive everyday sonic interaction. The prototype that we built is an energy-aware sonic carpet that provides real-time feedback on home electricity consumption and emissions through sound. An experiment has been designed to evaluate the prototype from a user experience perspective, and to assess how users understand the chosen sonifications.
State-of-the-art and next-generation integrated photonic design

The relentless need for higher bandwidth, lower power and lower cost data communications has driven tremendous innovation in integrated photonics in recent years. This innovation has been supported by state-of-the-art electronic-photonic design automation (EPDA) workflows, which enable process design kit (PDK) centred schematic driven design and layout, as well as statistically enabled electro-optical simulation. In addition, custom components can be introduced and optimized for a specific foundry process using advanced methods such as photonic inverse design and machine learning. While much of the innovation has been motivated by data communications, it has enabled a variety of different applications such as sensing, integrated LiDAR and quantum information technologies. We discuss the latest innovations in EPDA workflows and show how a silicon photonic ring-based wavelength demultiplexing (WDM) system can be easily designed, simulated and implemented. In addition, we discuss the extension of these workflows to support the design and simulation of quantum photonic devices, enabling designers to consider the effects of realistic sources and manufacturing imperfections when designing quantum building blocks to meet specific fidelity and fault tolerance thresholds.
A Novel Machine Learning-based Framework for Detecting Religious Arabic Hatred Speech in Social Networks

Social media platforms generate a huge amount of data every day.However, liberty of speech through these networks could easily help in spreading hatred.Hate speech is a severe concern endangering the cohesion and structure of civil societies.With the increase in hate and sarcasm among the people who contact others over the internet in this era, there is a dire need for utilizing artificial intelligence (AI) technology innovation that would face this problem.The rampant spread of hate can dangerously break society and severely damage marginalized people or groups.Thus, the identification of hate speech is essential and becoming more challenging, where the recognition of hate speech on time is crucial in stopping its dissemination.The capacity of the Arabic morphology and the scarcity of resources for the Arabic language makes the task of distinguishing hate speech even more demanding.For fast identification of Arabic hate speech in social network comments, this work presents a comprehensive framework with eight machine learning (ML) and deep learning (DL) algorithms, namely Gradient Boosting (GB), K-Nearest Neighbor (K-NN), Logistic Regression (LR), Naive Bayes (NB), Passive Aggressive Classifier (PAC), Support Vector Machine (SVM), Ara-BERT, and BERT-AJGT are implemented.Two representation techniques have been used in the proposed framework in order to extract features: a bag of words followed by BERT-based context text representations.Based on the result and discussion part, context text representation techniques with Ara-BERT and BERT-AJGT outperform all other ML models and related work with accuracy equal to 79% for both models.
Analysis of the Effect of Black Box Adversarial Attacks on Medical Image Classification Models

In the field of medical science, the reliability of the results produced by deep learning classifiers on disease diagnosis plays a crucial role. The reliability of the classifier substantially reduces by the presence of adversarial examples. The adversarial examples mislead the classifiers to give wrong prediction with equal or more confidence than the actual prediction. The adversarial attacks in the black box type is done by creating a pseudo model that resembles the target model. From the pseudo model, the attack is created and is transferred to the target model. In this work, the Fast Gradient Sign Method and its variants Momentum Iterative Fast Gradient Sign Method, Projected Gradient Descent and Basic Iterative Method are used to create adversarial examples on a target VGG-16 model. The datasets used are Diabetic Retinopathy 2015 Data Colored Resized and SARS-CoV-2 CT Scan Dataset. The experimentation revealed that the transferability of attack is true for the above described attack methods on a VGG-16 model. Also, the Projected Gradient Descent attack provides a higher success in attack in comparison with the other methods experimented in this work.
Literacy Program to Increase Reading interest in Third-Grade Elementary School Students

The aim of this study was to determine the role of literacy in increasing reading interest in 3rd grade elementary school students. The research method used in this research is qualitative research. The informants of this study were the principal, the homeroom teacher, and 3rd grade elementary school students. Data collection techniques through observation, interviews, and documentation The collected data is then processed through the phases of data reduction, data presentation, and data verification. The results showed that the literacy program was good at increasing reading interest in 3rd grade elementary school students. The role of literacy is very important in increasing students' interest in reading in Grade III. The literacy program is phased, with an emphasis on the habituation phase (15-minute reading), the development phase (answers to enriching books), and the learning phase (linking literacy in all subjects). From this, it can be concluded that the better the implementation of the school literacy movement supports the increase in the students' interest in reading. Therefore, the implementation of literacy in primary schools needs to be improved, not only for reading skills but also for other literacy.
The Research Comparison Between the Consonants of Bahasa Indonesia and Chinese Mandarin

Indonesian Students face a lot of difficulties when learning Chinese Mandarin, it is very common that them to mispronounce the consonants of Chinese Mandarin. There are not a lot of Indonesian Students who can pronounce Chinese Mandarin consonants accurately. Phonetics teaching is a very important part of learning other languages. Bahasa Indonesia is classified as “The Family of Austronesian Language”, and Chinese Mandarin is classified as Sino-Tibetan Language System. Although they have a different language systems, the two languages have a lot of similarities and differences in every aspect of it. If we look at the consonants of Bahasa Indonesia and Chinese Mandarin, Bahasa Indonesia has 23 consonants, and Chinese Mandarin has 22 consonants. These 2 kinds of languages have similarities and different points of the pronunciation and pronunciation methods.
Recurrent Neural Networks for Recommender Systems

The Internet is becoming one of the biggest sources of information in recent years, keeping people updated about everyday events. The information available on it is also growing, with the increase in the use of the Internet. Due to this, it takes a great deal of time and effort to locate relavent knowledge that the user wants. Recommender systems are software mechanisms that automatically suggest relavent user-needed information. Recurrent Neural Networks has lately gained importance in the field of recommender systems, since they give improved results in building deep learning models with sequential data. Unlike conventional recommendation models, RNN models more easily capture irregular and complex user-item relations. This paper provides a thorough analysis of the research content of recommendation systems based on RNN models. Keyword : Recommender systems, Recurrent Neural Networks, Recommendations, Gated Recurrent Unit, Long Short Term Memory.
Teacher and Students' Perceptions in Using Quipper School in English Teaching and Learning During Pandemic Related to Islam and Science

The COVID-19 pandemic is not over yet. Rasulullah SAW taught that when a pandemic occurs, we must avoid the outbreak, this is also in accordance with government policy, which is to change the learning system to online. This study investigated how teachers and students perceive the use of an online platform, namely Quipper School, in the implementation of English learning. The researcher used a qualitative descriptive method by observing the implementation of learning and interviewing 1 teacher and 5 students. The researcher concluded that the interest of teachers and students in using the Quipper platform was quite low. In addition, there were many challenges that must be faced by teachers, one of which was the low motivation of students in learning during the pandemic. Therefore, a teacher needs to increase the spirit of learning to his students in accordance with Islam and science.
A Framework of Information Systems Development Concepts

Abstract Background: Information Systems Development (ISD) is responsible for designing and implementing information systems that support organizational strategy, leveraging business models and processes. Several perspectives on this activity can be found in the literature, addressing – often in an undifferentiated manner – approaches, lifecycles, methodologies, and process models, among others. Objectives: The vast diversity of ideas and concepts surrounding ISD and the multiple underlying views on the subject make it harder for researchers and practitioners to understand the relevant aspects of this important activity. This article aims to systematize and organize ISD’s main concepts to create a coherent perspective. Methods/Approach: We conducted a literature review and thematic analysis of ISD’s main concepts. Results: To contribute to filling the research gap, this article proposes a new framework that addresses the key aspects related to ISD. Conclusions: The framework comprises ISD’s core concepts, such as lifecycles, process models, deployment approaches, and methodologies.
Study of hysteretic behavior in the recorder

It is known that flue instruments can exhibit hysteretic behavior, by which we mean that the tone produced by a particular fingering with a particular blowing pressure can depend on the prior history of the blowing pressure. However, the factors that determine and affect such behavior are not well understood. We report studies of this hysteresis using experiments and Navier-Stokes-based simulations of two simple instruments: (1) a commercial soprano recorder head (Yamaha YRS23) connected to a cylindrical resonator and (2) a complete Yamaha YRS23. Instrument (1) had no tone holes while instrument (2) had a tapered bore and all tone holes closed. In both instruments the total length and fundamental frequency of the lowest note (C5, f1 ˜520 Hz) were equal to those of a soprano recorder. Our experimental and simulation studies in which the blowing pressure is swept either upwards or downwards with time both show that the thresholds for switching from C5 to C6 (dominant spectral component ˜2xf1) can be quite different for upward and downward sweeps. We also find that at pressures between the upward and downward transition points the same final blowing conditions can produce tones with very different spectral contents depending on the blowing history.
Interdisciplinary integration as a means of university students’ financial literacy improvement

Currently, much attention is paid to the improvement of financial literacy in the Russian Federation. In modern conditions, financial literacy can be improved on the basis of the idea of interdisciplinary integration. One of the content and procedural characteristics of the educational potential of interdisciplinary integration is to increase the level of practice orientation of the educational process. The purpose of this study is to identify the possibilities of using interdisciplinary integration for university students financial literacy improvement by solving practice-oriented tasks. The educational course Physics has a special practical benefit when using such integration. The paper presents an example of a practice-oriented task that implements the principle of interdisciplinary integration. In the proposed problem, the content part is related to the course of general physics, mathematics provides the process of building a model and solving the problem in the language of the model. The following points are given: the statement of the problem, recommendations for the solution, the main characteristics of the problem and its solutions. The evaluation of the results obtained in the task and the choice of the most optimal solution contribute to the improvement of financial literacy and positive financial behavior. The task in question illustrates that solving physical problems associated with a certain kind of economic situations is a necessary condition for personal financial well-being. The results of the study can be used in the educational process of higher education organizations.
Pollen and Spores Recovery in Tunga Buzu Carbonaceous Shale Type Section Member: Significance in Sequence Stratigraphy, Age Dating and Paleoenvironment Deduction of the Early Miocene Gwandu Formation, Sokoto Basin, Northwestern Nigeria

Feld samples were collected from an outcrop at Tunga Buzu with the intention of comparing field relationship between the claystone member and the underlying carbonaceous shale Type Section for palynological study. The study was carried out in order to determine the geologic age relationship of the facies sequence, sequence stratigraphy and paleoenvironment of deposition of the sediments. Lithological description of the beds follows notation of colour, facies composition, texture, fossil content, structure and post depositional diagenetic effects. Laboratory preparation of palynological slides involved decarbonisation, sample digestion using hydrofluoric acid, sieving with 10µm mesh, bleaching of organic debris with nitric acid, maceral separation with zinc bromide, rinsing of separated maceral with ethanol and final mounting of the organomaceral on the slides for microscopic analysis.The carbonaceous shale is light grey in colour, fissile, carbonaceous, slightly bioturbated and ferruginized. Pollen, spores, dinoflagellates and algae were recovered from samples N1-N4. The samples N1-N3 are claystone samples characterised by relatively low assemblage assemblage of miospores with downhole increase in dinoflagellate cysts. The carbonaceous shale (sample N4) is relatively rich in palynomorphs with corresponding high palynomorph population and diversity compared with the claystone facies. Both the claystone and carbonaceous shale contain marker fossils such as Striamonocolpites sp., Retibrevitricolporites obodoensis, Verrutricolporites sp., Praedapollis sp., Belskipollis elegans and Peregnipollis nigericus; indicative of Early Miocene age. The litho-sequence of claystone and carbonaceous shale indicated alternation of continental and marginal marine deposits characterised by paucity and preponderance of peridinacean dinocysts. This suggests eustatic change in sea level of continental Lowstand Systems Tract (LST) and marginal marine Transgressive Systems Tract (TST) deposits respectively. The Tunga Buzu Carbonaceous Shale Type Section constitutes a member of the Early Miocene Gwandu Formation of the Sokoto Basin, Nigeria.