Reviewerly/exHarmony huggingface dataset:
Identifikasi Rendahnya Hasil Belajar Peserta Didik saat Pembelajaran Daring Menggunakan Aplikasi WhatsApp Mata Pelajaran IPA Kelas V SDN 7 Menteng

This research was carried out aimed at describing the factors causing the low learning outcomes of students during online learning using the application WhatsApp on science subjects. The method used in this research is a qualitative method with a type of case study. The data collection techniques used were observation, interviews, and documentation. The object studied was 3 students, class teachers, and triangulation of data on school principals, school operators (TU), and students' parents. The results of the research conclusions indicated that: (1) students were less interested in participating in online learning in science subjects. (2) Students do not like science subjects online. (3) the teacher only uses the WhatsApp application to carry out online learning. (4) the teacher only notifies and sends the material to be studied without being explained first. (5) the teacher always gives assignments to students so that it makes students dislike online learning. (6) the students are less motivated to take part in learning.
Developing disciplinary competencies in an “hybrid model” comparing “on-line” versus “face-to-face” interaction between students and lecturers

From March 2019 through September 2021, most universities in our country had to turn into an online model in all the courses and programs. When students started to attend the lectures in September 2021, the universities implemented a hybrid model, having simultaneously students on-line and face-to-face. The teachers and lecturers since then have faced the challenge to pay the same level of attention to on-line and face-to-face students. Both types of students are getting the same information, the same material, and the same activities so we are questioning the level of knowledge acquired and competencies developed in the different attending circumstances. After at least one academic period attending lectures &#x201C;on-line&#x201D; or &#x201C;face-to-face&#x201D;, students enrolled in the Civil Engineering program between 6<sup>th</sup> through 8<sup>th</sup> semester, answered polls and surveys that provided the information about their perception on the level of attention received, knowledge acquired, and the competencies developed. The objective of this paper is to obtain the students&#x2019; perception of the effectiveness of the hybrid method for acquiring knowledge and basic concepts regarding the disciplinary competencies within the subject's topic, so we asked them for their perception in a qualitative manner to understand how they are interpreting and understanding the need of these hybrid models.
Advance Digital Voice Assistance with Voice Recognition Intelligence

In this modern era, day to day life become smarter &amp; interlinked with technology. We already know some voice assistant like google, Siri etc. Now in our voice assistant system, it can act as your smart friend, daily schedule manager, to do writer, calculator &amp; search tool. This project works on speech input &amp; give output through speech &amp;text on screen. This assistant attaches with the world wide web to provide result that the user required. Natural language processing algorithm helps machines to engage in communication using natural human language in many forms.
Digital Competences and Teaching Performance in Regular Basic Teachers of Lima

The purpose of the research was to determine the relationship between digital skills and teaching performance in an educational institution in Lima. It was developed under the quantitative approach, type of basic research, nonexperimental cross-sectional design, descriptive correlational. Regarding the sample, it was made up of 57 teachers from the secondary level of said study center; The field work was developed through the survey and instrument technique, questionnaires from which a high reliability was obtained through the Cronbach's Alpha of digital skills (0.903) and teaching performance (0.871). A very high positive correlation (0.926) between the variables was determined by the bilateral significance of (0.000). There is evidence of a significant relationship between digital skills and teaching performance in an educational institution in Lima; therefore, the use of technology is pertinent in the work of the teacher, since the empowerment of digital skills was achieved in them, in addition to being at the forefront of the demands of the competitive world that demands more and more teachers prepared to train citizenship competencies and achieve the student's graduation profile at the end of regular basic education.
Researching Social and Emotional Learning in the Middle Grades

Strahan and Poteat’s (2020, 2022) studies on SEL provide small-scale explorations of the ways seventh and eighth grade students perceive their social-emotional development when teachers integrate SEL with academics. These works align with research questions identified in the Middle Level Education Research Special Interest Group’s research agenda. Using CASEL’s SEL framework the studies found SEL programs embedded within daily teaching practices can have significant positive outcomes for young adolescent learners. These studies demonstrate a commitment to participatory research and aim to highlight “teaching with” SEL versus “teaching to” SEL. This chapter offers a critique of Strahan and Poteat’s work and recommends (a) a more extensive review of the literature to position the study within the extant body of current research, (b) underpinning the research with a strong theoretical framework, (c) transparency in the methodology, and (d) greater connections between findings and the larger body of literature to strengthen study implications.
Attentive Amigo - Student's alertness Indicator app

In recent situations, the majority of the learning has been moved to e-learning modes which are internet-based classes. But in a live class, an educator can continually screen the understudies by visual examination and dynamic learning. Because of virtual learning, this ability of the educators becomes less efficient. The students are not able to gain enough knowledge as usually they should. The proposed work points towards giving the educator an itemized examination forevery one of the understudies dependent on a physical and passionate investigation of their state during the study hours. Our model analyses live recordings of students and uses factors such as the student's posture, the enthusiastic look on the face, the location of the eyelids, and the student's stance to provide the educator with a certainty score that he or she can use to determine the students' mentality during the class. By knowing which students were attentive and inattentive, the teacher may need to keep a high focus on the inattentive ones. With the effective tecution of our proposed work, it will aid to build up a relationship among the attributes that have been picked and foster this model that will help the instructors to perceive the result of the students, so they can bring better learning techniques nearer to the understudies, while in the security of their own houses, with the help of deep learning and pre-trained data sets to know the behaviour of the students. The utilization of these techniques of mechanically progressed educational strategies and upgraded individual learning examinations will take into consideration the setting up of the labourforce of tomorrow to be exceptionally prepared and able.
Completeness and expressiveness for gs-monoidal categories

Formalised in the study of symmetric monoidal categories, string diagrams are a graphical syntax that has found applications in many areas of Computer Science. Our work aims at systematising and expanding what could be thought of as the core of this visual formalism for dealing with relations and partial functions. To this end, we identify gs-monoidal categories and their graphical representation as a convenient, minimal structure that is useful to formally express such notions. More precisely, to show that such structures naturally arise, we prove that the Kleisli category of a strong commutative monad over a cartesian category is gs-monoidal. Then, we discuss how other categories providing a formalisation of "partial arrows", such as p-categories and restriction categories, are related to gs-monoidal categories. This naturally introduces a pre-order enrichment on gs-monoidal categories, and an equivalence of arrows, called "gs-equivalence": we conclude presenting a completeness result of this equivalence for models defined as lax functors to $\mathbf{Rel}$.
Rethinking the Digital Divide: Using an Internet Survey in a Flint Water Crisis Medicaid Population

This project examined the preferred mode of response (internet, phone, mail) to a health services survey. Data were collected via survey responses from a subsample of Flint Water Crisis Medicaid Expansion Waiver enrollees (N=2,584). Analyses were stratified by age, residency, race, and income. Chi-square tests were used to detect categorical differences. The majority of participants responded by internet (55.5%), followed by mail (39.4%), and phone (5.2%). Of those responding by internet, 75% used smartphones for connectivity. Black and White respondents used the internet at a greater rate than Hispanic respondents (p&lt;.01). Respondents at 200% federal poverty level (FPL) or higher used the internet mode at greater rates than those below 200% FPL (p&lt;.01). Our findings suggest greater internet use in a vulnerable population than expected, but the digital divide persists. In the advent of COVID-19, this finding can inform future health programming using digital communication and telehealth.
What is Digital Forensics?

Abstract The definition of digital forensics is the process of uncovering and interpreting electronic data for use in a court of law, writes Shahrzad Zargari, Senior Lecturer and Course Leader in Cybersecurity with Forensics, after recently hosting the BCS webinar, Digital Forensics 101.
Bidirectional path planning based on improved genetic algorithm

Aiming at the problems of premature convergence and long time-consuming in traditional path planning of mobile robots, a bidirectional path planning method based on an improved genetic algorithm was designed. Firstly, an environment map is established, and the physical space is abstracted into an abstract space that can be processed by the path planning algorithm by using the grid method. Then, simulated annealing algorithm is used to improve the population selectivity and diversity; and indicators such as path tortuosity are added to the fitness function, and two-way search rules are added and set. Improve the smoothness of the path of the mobile robot, making it easier to drive. And using matlab for simulation verification, the results show that compared with the classical genetic algorithm, the improved algorithm is more efficient in mobile robot path planning.
A Survey of Self-Efficacy in English Learning of Junior Middle School Students in Rural Areas

To understand the current situation of rural junior middle school students' self-efficacy in English learning and explore the different roles of different information sources of self-efficacy in students' English learning, a questionnaire survey is conducted on junior middle school students from a rural middle school in D city, S Province, China. The results show that: 1. the overall level of self-efficacy in English learning of rural junior middle school students is lower than average; 2. academic record is the strongest self-information source of self-efficacy in English learning; 3. English teachers, classmates, and parents all have a significant positive correlation with their Self-efficacy in English learning, and classmates have the most significant correlation. According to the influence of different information sources on students' self-efficacy in English learning, this paper puts forward relevant suggestions from students, teachers, classmates, and parents.
Educational Feedback in Teaching English

The research aims to analyze and reflect on the theoretical corpus of educational feedback in the teaching of English carried out through publications registered in high-impact databases. It is part of the interpretive paradigm of literature analysis in relation to educational feedback. Consequently, the study has used the qualitative method with a hermeneutical design framed in the analysis reading of the writings published in articles in relation to feedback. The documentary analysis technique was used as criteria and indicator. Feedback has changed over time, adapting to new educational approaches. For a long time, in the educational context, it has been continuous to identify the teacher by providing feedback. Feedback was used as a didactic tool in the teaching process. However, currently, the orientation of feedback in its conceptualization, in its understanding and educational expression is changing according to the documents reviewed. After analyzing what has been written about the feedback, it can be indicated that its conception is not univocal or static; that is, it does not have a single meaning and has not maintained its conceptualization over time. Which leads to suggest that feedback in education is changing since it has gone from having a unidirectional sense to being multivariate in its conception and expression. Feedback is no longer conceived only in the instructional educational process; but in any space where an error can be corrected, where you can interact, where you seek to be effective to achieve a desired result and can be done using technological supports.
A Blockchain Based Portal for Online E-Voting

In place of traditional electoral systems, the implementation of e-voting systems is widely adopted which still has major problems in the results. Online voting is an alternative to the old paper voting system and today's popular Electronic Vote Machine (EVM). E-voting systems are very susceptible to manipulation issues, such as alteration of election results by hacking or by the manufacturer of the voting system. To solve this problem, we use distributed ledger technology to create a voting application that is accessible to everyone and everywhere. Blockchain, which is the technology behind the first Bitcoin cryptocurrency, has attracted a lot of attention globally in recent years. This paper proposes a blockchain-based voting system that removes some limitations of existing voting systems. The application is based on the Ethereum blockchain which makes the entire system secure and immutable in nature. The presented implementation is suitable for small-scale elections such as inside corporate homes, meeting rooms, and more.
UPDATING STRATEGIES FOR DISTANCE BASED CLASSIFICATION MODEL WITH RECURSIVE LEAST SQUARES

Abstract. The idea is to create a self-learning Minimal Learning Machine (MLM) model that is computationally efficient, easy to implement and performs with high accuracy. The study has two hypotheses. Experiment A examines the possibilities of introducing new classes with Recursive Least Squares (RLS) updates for the pre-trained self learning-MLM model. The idea of experiment B is to simulate the push broom spectral imagers working principles, update and test the model based on a stream of pixel spectrum lines on a continuous scanning process. Experiment B aims to train the model with a significantly small amount of labelled reference points and update it continuously with (RLS) to reach maximum classification accuracy quickly.The results show that the new self-learning MLM method can classify new classes with RLS update but with a cost of decreasing accuracy. With a larger amount of reference points, one class can be introduced with reasonable accuracy. The results of experiment B indicate that self-learning MLM can be trained with a few reference points, and the self-learning model quickly reaches accuracy results comparable with nearest-neighbour NN-MLM. It seems that the self-learning MLM could be a comparable machine learning method for the application of hyperspectral imaging and remote sensing.
RePAIR: A ReRAM-based Processing-in-Memory Accelerator for Indel Realignment

Genomic analysis has attracted a lot of interest recently since it is the key to realizing precision medicine for diseases such as cancer. Among all the genomic analysis pipeline stages, Indel Realignment is the most time-consuming and induces intensive data movements. Thus, we propose RePAIR, the first ReRAM-based processing-in-memory accelerator targeting the Indel Realignment algorithm. To further increase the computation parallelism, we design several mapping and scheduling optimization schemes. RePAIR achieves 7443× speedup and is 27211× more energy efficient over the GATK3.8 running on a CPU server, significantly outperforming the state-of-the-art.
Correlation between Students' Aptitude and their Academic Achievement at Secondary School Level in Khanewal District

Students' aptitude is an important factor that determines the students' success in the summative assessment. Similarly, teachers play an important role in the development of scientific attitudes in the personality of students. The main objective of this study was to find out the relationship between students' aptitude and their academic performance at the secondary level. In the same way, it was also investigated what the role of teachers in developing the students' personality attitudes is. The population of this study was the secondary school teachers in district Khanewal. The sample of this study was 200 teachers selected through convenience sampling. The sample was selected in a proportional way on the basis of various demographics so that the findings of this research study may be generalized to various variables. In order to collect primary data survey method was applied. The findings of this study revealed that there was a significant difference in the perception of male and female teachers regarding students' aptitude.
The evolution and maturation of the electric guitar as a system

The electric guitar came to its initial prominence in the 1940s when its volume allowed jazz guitarists like Charlie Christian to step out in front of the rhythm section like other soloists, competing with the brass, wind, and piano. Further changes in the playing and design of the instrument came with exploitation of the interaction of the electric guitar, tube amplifiers, and analog effects as a larger system. Especially in the rock and funk idioms, the playing and construction of the overall instrument evolved and expanded rapidly with the mainstream embrace of digital technology. This talk will consider the evolution of the electric guitar as a system up through today and consider why it seems the instrument has fully evolved and is unlikely to experience further seismic shifts, especially as the overall thrust of music has shifted to digitally-manipulated sound that is often entirely independent of the physical playing of any instrument.
Automating Defeasible Reasoning in Law

The paper studies defeasible reasoning in rule-based systems, in particular about legal norms and contracts. We identify rule modifiers that specify how rules interact and how they can be overridden. We then define rule transformations that eliminate these modifiers, leading in the end to a translation of rules to formulas. For reasoning with and about rules, we contrast two approaches, one in a classical logic with SMT solvers as proof engines, one in a non-monotonic logic with Answer Set Programming solvers.
Hardware control design of intelligent garbage recycling vehicle

Based on the concept of multi-sensor fusion, this paper proposes an autonomous walking intelligent garbage recycling vehicle with NUC 7i5BNK as the main controller. The recycling vehicle is mainly designed from the system hardware. The main contents of the hardware design include the detection module, control module, and drive module. The detection module is each sensor, which feeds back the real-time status of the recycling vehicle. The core processing chip of the control module is NUC 7i5BNK, which is connected to the embedded connection to obtain the data information fed back by the sensor, fuses the information, and sends instructions to the motor driver board of the execution module to control the operation of the motor. After many actual measurements, the intelligent recycling vehicle can accurately perform autonomous walking and automatic obstacle avoidance. In the process of autonomous walking, the intelligent recycling vehicle has a small output error of attitude angle, high walking path accuracy, stable operation, high flexibility, and wide coverage.
On evaluating CT image enhancement techniques for deep learning based 3D liver segmentation

Medical image pre-processing plays a crucial role in designing a robust computer-aided diagnostic system. The liver is difficult to segment from volumetric images because its intensity values are similar to those of nearby organs. The pre-processing step aids in the accurate feature extraction of an organ such as the liver from the given data and reduces false positive results, which reduces error in the later stages of diagnosis. In this paper, three image enhancement techniques, Hounsfield Unit (HU), contrast limited histogram equalization (CLAHE), and the combination of Hounsfield Unit and CLAHE (HU+CLAHE), have been evaluated for 3D computed tomographic (CT) volumetric images from the LiTS17 dataset to enhance image quality. We have first applied the HU and CLAHE separately as well as a pipeline of HU and then CLAHE that is first HU and then CLAHE is used to pre-process the images. After pre-processing, liver is segmented using 3D V-Net, a deep learning neural network. The 3D V-Net is trained end-to-end using the pre-processed 3D volumes obtained from the schemes described above. Dice coefficient has been used to evaluate the three pre-processing pipelines and scores achieved for CLAHE, HU and HU+CLAHE are 0.970, 0.964 and 0.971 respectively.
A Secure Data Deduplication in Cloud Using Hashing and AES Algorithm

Data de-duplication is a way used to compress data helping withinside the elimination of reproduction copies of data. It has been powerful in cloud garage; it decreases the specified garage area to steady such facts through thinking about de-duplication this concurrent technique has been projected. In the identical way, introducing fewer new replica exams for engineers ought to growth new de-duplication improvement assisting techniques. Security research have proven that this approachment is steady regarding the descriptions proven withinside the projected protection model. This paper will actualize a prototype of a suggested, sanctioned replica test plan and carry out experiments the use of the prototype. The look at will display that the proposed prototype reasons inconsequential overhead-differentiated archetypal processes. This paper offers and analyses a brand new scheme to deal with the difficulty of eternal cloud garage get right of entry to structures through imparting AES Algorithm primarily based totally solution. Addressing the difficulty of Data garage withinside the latest instances is the intention of the paper and is being completed the use of the latest AES Algorithm. Data protection and time constraint for facts retrival from the cloud server is likewise taken under consideration whilst enforcing the scheme.