Reviewerly/exHarmony huggingface dataset:
Exploration on English Teaching Reform under the Combination of Big Data and Artificial Intelligence Technology

With the development and application of new technologies such as big data (BD) and artificial intelligence (AI), English teaching has shown a trend of intelligence, and the mutual interaction between educators and learners is becoming more and more serious in the classroom, which has significantly improved the quality of English teaching.This paper studied the construction of English teaching system under the combination of BD and AI technology, aiming to analyze the improvement of students' English level through experimental tests.Based on the findings of the experiment, it can be seen that the average satisfaction of teachers with the English teaching system under the combination of BD and AI technology was 91.73 points on average.The improvement of students' overall English scores was up to 26.3%, which showed that the worth of English teaching could be greatly enhanced with the combination of BD and AI.
Bridging Educational Gaps Among University Students During the New Normal through the Kumustahan Project: A Focus Group Discussion Initiative for Higher Education

I. Introduction A year after World Health Organization declared Covid-19 as a global pandemic, most universities across the world are still struggling to face the new normal. Online learning has become the means universities have in continuing education. While most progressive universities are digitally prepared, there is another gap that these universities have to deal with – the continuing divide between those who are able to study digitally, and those that are left behind due to economic factors. In a recent study by Grishchenco (2020), most of the students living in rural areas have been greatly affected by the sudden shift to full digital learning due to the limitations of technology. Beaunoyer, Dupéré, and Guitton (2020) pointed out that the digital divide has already been existing even in the pre-pandemic days. It, however, exacerbated when students were left with no other means but through online learning. The series of lockdowns caused a lot of limitations to the students. From technological limitations to financial and even social challenges (Lassoued, Alhendawi, &amp; Bashitialshaaer, 2020; Peters, et al., 2020), students are also challenged when it comes to their mental health and psychological wellness (Cao, et al., 2020), causing greater issues on inclusion – both academically and socially. In the Philippines, the readiness of students in a fully-digital learning space remains low on students’ demographics who belong to lower income and rural areas (Alipio, 2020). Approximately 2,400 Higher Education Institution in the Philippines are challenged to bridge the gap between the economically-able students and those who are being left behind. Prior to the 2020 Pandemic, Oztok et al. (2013) surveyed different means of conducting digital learning to alleviate such gap, through synchronous and asynchronous learning. Years later, the acceptance of synchronous and asynchronous mode of online learning has become a staple in the New Normal set-up of education.
UPAYA GURU DALAM MENGEMBANGKAN KEMAMPUAN MEMBACA DAN MENULIS SISWA KELAS I SDN 177 PEKANBARU

The problems that often occur in grade I are related to reading and writing. The difficulties experienced by students when reading and writing activities are that students find it difficult to distinguish several letters such as letters d from letters b and p, and reading is still not fluent. The purpose of this research is to describe the strategies and methods used by the teacher to improve the reading and writing skills of grade I students. This research method is qualitative with a case study type. Data collection techniques are using interviews, observation and documentation. The data source involved 2 teachers and 4 students. Testing the validity of the data using triangulation. Data analysis techniques namely data collection, data reduction, data presentation and drawing conclusions. The results of the study show that the teacher has made efforts to develop students' reading and writing skills even though they have not shown maximum results such as the lack of use of interesting learning media in the learning process. The inhibiting factor for the teacher's efforts to develop reading and writing skills is the ability of students who are not the same, then the class atmosphere is not conducive and there is a lack of guidance from parents to accompany their children when studying at home, causing a lack of interest in student learning. The conclusion from the research results is that the efforts made by the teacher in developing reading and writing skills are using the spelling method, using interesting teaching materials and learning media, the teacher also gives additional hours to students who are not fluent in reading and writing, and there is collaboration between parents and teachers in developing students' reading and writing abilities
PUBLIC UNIVERSITY LIBRARIES’ SERVICES: EVIDENCES FROM AR-RANIRY ISLAMIC STATE UNIVERSITY AND SYIAH KUALA UNIVERSITY BANDA ACEH

Banda Aceh is the provincial capital of Aceh and has been declared as an economic mobility and education center. This period was marked by the establishment of several public and private schools, as well as public and private universities. Education is a process of learning that aims to develop a generation to be more reliable and capable. Facilities and infrastructure are critical components of education. An essential educational facility for both students and educators is the library. As a public institution, the library must comply with applicable rules and regulations namely UU No. 25 of 2009. The purpose of this study is to establish public services at the UIN Ar-Raniry and USK libraries. This research employs a qualitative approach. The findings indicated that the two libraries were extremely capable of providing services to these public institutions. Numerous supporting aspects contribute to the creation of satisfactory service. Additionally, there are various obstacles to the implementation of public services. Minor errors that occur in each institution are a constant source of progress that must be developed over time. This study concludes that public services provided to UIN Ar-Raniry and USK libraries have begun to show results in compliance with UU No. 25 of 2009. However, further efforts are required on the side of the library's internal and external stakeholders to ensure that the implementation of future services sincerely achieves the law's standardization&#x0D;
The effect of business intelligence on the development of human resources in Jordanian banks

The study aims to investigate the adoption and utilization of business intelligence systems by banks in Jordan for the purpose of managing their human resources. Additionally, the study sought to identify effective strategies for developing the human capital of these banks. The study emphasizes the importance of business intelligence systems in enhancing human capital development as a strategic imperative. This study utilized a descriptive and analytical methodology to collect data from male and female bank employees in Jordan. In order to gather the necessary data, the researcher distributed a questionnaire among the participants of the study. A total of 350 surveys were administered. The data that was gathered was subsequently analyzed utilizing the SPSS software. According to the study's findings, the practice of online analytical processing, business performance management, and competitive intelligence was reported to be of moderate prevalence. Based on employees' perspectives, there was a moderate level of implementation observed in terms of employee knowledge, experience, skills, value, training, as well as invention and innovation. The study further demonstrated that the mean level of engagement with the independent variable, business intelligence, as well as the dependent variable, human capital development, were both of a medium degree.
Hybrid Feature-Learning-Based PSO-PCA Feature Engineering Approach for Blood Cancer Classification

Acute lymphoblastic leukemia (ALL) is a lethal blood cancer that is characterized by an abnormal increased number of immature lymphocytes in the blood or bone marrow. For effective treatment of ALL, early assessment of the disease is essential. Manual examination of stained blood smear images is current practice for initially screening ALL. This practice is time-consuming and error-prone. In order to effectively diagnose ALL, numerous deep-learning-based computer vision systems have been developed for detecting ALL in blood peripheral images (BPIs). Such systems extract a huge number of image features and use them to perform the classification task. The extracted features may contain irrelevant or redundant features that could reduce classification accuracy and increase the running time of the classifier. Feature selection is considered an effective tool to mitigate the curse of the dimensionality problem and alleviate its corresponding shortcomings. One of the most effective dimensionality-reduction tools is principal component analysis (PCA), which maps input features into an orthogonal space and extracts the features that convey the highest variability from the data. Other feature selection approaches utilize evolutionary computation (EC) to search the feature space and localize optimal features. To profit from both feature selection approaches in improving the classification performance of ALL, in this study, a new hybrid deep-learning-based feature engineering approach is proposed. The introduced approach integrates the powerful capability of PCA and particle swarm optimization (PSO) approaches in selecting informative features from BPI mages with the power of pre-trained CNNs of feature extraction. Image features are first extracted through the feature-transfer capability of the GoogleNet convolutional neural network (CNN). PCA is utilized to generate a feature set of the principal components that covers 95% of the variability in the data. In parallel, bio-inspired particle swarm optimization is used to search for the optimal image features. The PCA and PSO-derived feature sets are then integrated to develop a hybrid set of features that are then used to train a Bayesian-based optimized support vector machine (SVM) and subspace discriminant ensemble-learning (SDEL) classifiers. The obtained results show improved classification performance for the ML classifiers trained by the proposed hybrid feature set over the original PCA, PSO, and all extracted feature sets for ALL multi-class classification. The Bayesian-optimized SVM trained with the proposed hybrid PCA-PSO feature set achieves the highest classification accuracy of 97.4%. The classification performance of the proposed feature engineering approach competes with the state of the art.
Bayesian Formula and Its Application Analysis

Bayesian formula is a very important and widely used formula in probability and statistics courses, which can simplify the probability calculation of certain complex events. This article not only introduces the relevant theories of Bayesian formula, but also explores its practical applications in daily life through examples.
Carbon-efficient Virtual Machine Placement in Cloud Datacenters over Optical Networks

We propose an ILP scheme for virtual machine (VM) placement in cloud datacenters(DCs) to minimize the overall carbon emissions of cloud DCs while satisfying the communication demands and latency requirements of VM services.
Motion Matters: Difference-based Multi-scale Learning for Infrared UAV Detection

Unmanned Aerial Vehicle (UAV) detection in the wild is a challenging task due to the presence of background noise and the varying size of the object. To address these obstacles, we propose a novel learning framework for robust UAV detectors, which we call Difference-based Multi-scale Learning (DML). We argue that motion information matters in UAV detection because of the low recognition in one frame. Our method utilizes the frame difference of multiple previous frames, extracting motion information and blocking background noise. We also fuse multiple spatial-temporal scales for training and inferencing, enabling fusion from different sources. In addition, to better evaluate the performance of UAV detection in different scales, we propose Multi-Scale Average Precision (MSAP) metric to aggregate the detection accuracy over multiple scales. Through extensive experiments, we demonstrate that our proposed approach improves the detection accuracy of baseline models. Notably, we achieve SOTA performance in the 3rd Anti-UAV Challenge, with 2nd place in Track 2 and 4th place in Track 1. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>
Optimized Embedded Model for Time Sequence Alignment within Distributed Video Streams Environment

When the same action is captured from different perspectives, different video sequences will be recorded. For video alignment in a distributed video stream environment, learning the visual invariance features of different frames from different viewpoints is affected by the change of foreground and background, which makes learning much more difficult. Note that, the 2D human pose sequences extracted from multiple consecutive images of the video contain the main behavioral information of the person in the video. To reduce the difficulty of model learning, we explore learning visual invariance features from 2D human pose sequences in different video streams. We map the 2D human pose sequences into the embedding space, and the Euclidean distance in the embedding space quantifies the similarity between different frame sequences. Experimental results show that: (i) In the alignment task of distributed video streams, compared to methods that directly learn the similarity between video image sequences, our approach achieves better alignment results with a smaller model. (ii) In the multi-view human pose retrieval task, compared with 3D pose estimation models, our embedding model achieves higher accuracy when retrieving 2D poses projected from the same 3D pose across different camera views. (iii) We exploit the similarity between consecutive multiple frames and treat it as a classification task, which allows our model to learn visual invariance features with higher resolution.
Latent factors of elementary school students' self-control in online learning

Online learning during the pandemic has been a contributing factor to learning loss. However, for students who possess self-control, their learning outcomes still fall within the good category. This research aims to analyze the latent factors of self-control among elementary school students in the context of online learning. This study applied coding analysis, exploratory and confirmatory factor analysis. It involves 6th-grade students (N=24) purposively selected from one elementary school in the Tanjungpandan district for the coding analysis study, resulting in 84 responses that formed 16 codes for designing the students' self-control instrument model. Additionally, 4th to 6th-grade elementary school students (N=146) from four districts in Belitung, Bangka Belitung, Indonesia were randomly selected for the factor analysis study to construct latent factors based on the 16 formed codes. The data for the coding analysis and factor analysis were collected through online surveys. The coding analysis survey used open-ended questions, while the factor analysis survey used items designed on a Likert scale with a response model based on the degree of "alwaysness". The results of the coding analysis have been presented. The factor analysis yielded two latent factors, each constructed from 6 and 10 codes, respectively. The findings of this research reveal the results of the reduction technique applied to each set of 6 and 10 codes into self-control factors in online learning, namely: (1) productive learning habits, and (2) effective learning strategies. These two factors can be considered for students' self-control during online learning.
Accelerable Lottery Tickets with the Mixed-Precision Quantization

In recent years, the lottery tickets hypothesis has gained widespread popularity as a means of network compression. However, the practical application of lottery tickets for hardware acceleration is difficult due to their element-wise unstructured sparsity nature. In this paper, we argue that network pruning can be seen as a special case of network quantization, and relax the hard network pruning with mixed-precision quantization in an unstructured manner, which makes it possible for real hardware acceleration. We successfully validate the wide existence of quantized lottery tickets, namely MPQ-tickets, that can match or even surpass the performance of corresponding full-precision dense networks on various representative benchmarks. Also, we demonstrate that MPQ-tickets have much higher flexibility than vanilla lottery tickets, and largely benefit from pruning when compared to QNNs. Moreover, the MPQ-tickets achieve up to 8× hardware acceleration of inference speed and 14× less memory consumption than full-precision models.
ANALISIS PENGELOLAAN KOLEKSI GREY LITERATUR DI PERPUSTAKAAN

The purpose of this study was to find out how to manage the gray literature collection, both theses, theses and dissertations at the UIN Raden Fatah Palembang Library. The method used in this article is a qualitative method with a case study approach, with the technique of collecting observations and literature sources. The results of this article show the management of the gray literature collection (thesis, thesis and dissertation) at the UIN Raden Fatah Palembang Library. Where in the thesis library, theses and accompanied by alumni students or students who have just distributed theses, theses and dissertations must be managed first so that information retrieval for students who need references can be easily found. And the management of the gray literature collection has been carried out with the available resources, and the management system is structured from tasting, recording, class, inputting, labeling and giving colors according to the presentation and placement of theses, theses and dissertations according to the shelves of each study program. However, the management still needs improvement in several aspects, such as facilities such as lacking library shelves, networks and chips to detect if the thesis is taken or stolen.
Automatic speaker recognition with variation across vocal conditions: a controlled experiment with implications for forensics

Automatic Speaker Recognition (ASR) involves a complex range of processes to extract, model, and compare speaker-specific information from a pair of voice samples.Using heavily controlled recordings, this paper explores the impact of specific vocal conditions (i.e.vocal setting, disguise, accent guises) on ASR performance.When vocal conditions are matched, ASR performance is generally excellent (whisper is an exception).When conditions are mismatched, as in most forensic cases, we see an increase in discrimination and calibration error in some cases.The most problematic mismatches are those involving whisper and supralaryngeal vocal settings; these produce the greatest phonetic changes to speech.Mismatches involving high pitch also produce poor performance, although this appears to be driven by speaker-specific differences in articulatory implementation.We discuss the implications of the findings for the use of ASR in forensic casework and the interpretability of system output.
The Development of Malang City Virtual Tourism for Preservation of Traditional Culture using React 360

Malang is one of the tourist destinations in East Java, and always visited by both domestic and foreign tourists. However, Malang isn’t the first destination in tourism, this is due to the lack of intense promotion. Virtual tourism is a virtual reality technology for promoting tourism. Based on these problems, the researchers developed a virtual reality application that can provide immersive experiences to users assembled with tourist destinations in Malang. Application was developed using React 360 framework, because of its ease of development and can be developed for various platforms. The Software Development Life Cycle (SDLC) is the waterfall method. The implementation using VR Headset and VR Controller. In testing, researchers conducted functional testing and non-functional testing. Functional testing is done using black box testing and non-functional testing is done by the System Usability Scale (SUS) method. The results of functional testing using black box are 100% valid. In the usability test, the System Usability Scale (SUS) questionaire obtained a score of 89. From the scores that have been obtained, this application is acceptable, with Grade A and adjective rating Excellent.
Pengaruh Pop Up Book Dalam Mengenalkan Huruf Alphabet Di Taman Kanak-Kanak Bhakti Bunda Padang

The purpose of this article is to disuss the results of research on how much influence Pop Up Books have in introducing letters of the alphabet at Bhakti Bunda Padang Kingdergarten. In the introduction of alphabet letters, they have not used Pop Up Book media and learning still seems monotonous. As a result, shildren are less interested and respond during learning. This is because the media used in learning is only blackboards and letter cards. This research is a quantitative research using Quasi Experiment method. The population in this study were all students of Bhakti Bunda Padang Kingdergarten with the Cluster Sampling technique (area sampling) namely selecting or taking samples based on certain characteristic needed in the study. Based on the data above, the classes that will be used as samples are classes B1 and B3 where groups B1 and B3, taking into account the homogeneity of the same children aged 5-6 years and the same learning facilities.Based on the hypothesis test table in the sig column. (2-tailed) obtained a sig value of 0.024. this value indicates that the sig value is 0.024 &lt;0.05. in accordance with the measurement criteria in the hypothesis test, if a sig value &lt;0.05 is abtained, it can be concluded that there is a significant effect of Pop Up Books in introducing alphabet letters in Bhakti Bunda Padang Kingdergarten.