Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI MODEL TGT BERBANTU MEDIA GAYANG SEBAGAI UPAYA PENINGKATAN HASIL BELAJAR IPAS KELAS V SEKOLAH DASAR

The importance of learning science in the world of basic education makes teachers required to be able to create a pleasant learning atmosphere and be able to motivate students to collaborate in the learning process. From the data in the field, the results of observations made by researchers during the pre-cycle on August 31, 2023 at Noborejo 01 Salatiga State Elementary School in the learning process using a classical model and centered on the teacher alone. solution to the application of the TGT (Teams Games Tournament) model with the help of gayang media as an increase in student learning outcomes. The existence of this TGT type cooperative learning model provides opportunities for students to be able to develop their thinking skills in solving problems and foster a spirit of learning and a sense of responsibility for fellow members in their group. The results of observations on the positive activities of students were 70% in cycle I and increased to 89% in cycle II, learning management was originally 72% in cycle I to 88% in cycle II, with the implementation of the TGT (Teams Games Tournament) cooperative model assisted by Gayang media (Puppet Pictures) the learning outcomes of students increased, this was shown from an average of 70.0 in cycle I to 77.8 in cycle II. As well as an increase in students' learning completeness from 69% in cycle I to 86% in cycle II.
Augmented Reality: The Future of Movie Promotion for Malaysian Youth Cinemagoers

Posters are great ways to promote movies. They visually show crucial components that stimulate excitement and interest in upcoming films. Nevertheless, using posters as movie promotional tools presents certain issues. Given the high volume of film releases annually, it can be challenging to differentiate oneself in a saturated market. Moreover, assessing their efficacy can pose a significant challenge. The movie advertising industry stands to benefit significantly from augmented reality's (AR) rapid development. It has the potential to generate interest in upcoming films by creating interactive and immersive experiences. This study aims to understand how Malaysian youths view AR movie promotion to determine the best approaches to creating AR-based movie promotions. Three augmented reality (AR) experiences promoting the local film "Roh" were developed and tested on university students aged 18 to 25. The results illustrate the perceptions of the Malaysian youths regarding AR movie promotion and suggest optimal approaches to creating AR-based movie promotions that appeal to this demographic.
PENERAPAN MODEL PEMBELAJARAN MAKE A MATCH PADA MATA PELAJARAN IPA UNTUK MENINGKATKAN HASIL BELAJAR SISWA DI KELAS V SDN DURI KEPA 13

This study is classroom action research (PTK) with the aim of improving learning outcomes in science subjects with the material "Animal and Human Movement Organs" through the application of the Make a Match learning model to class V students at SDN Duri Kepa 13. The research involved 27 students from class V D, which consists of 12 male students and 15 female students. The research was carried out in two cycles, with each cycle consisting of two meetings involving four research stages, namely planning, implementing actions, observing and reflecting. Data was obtained through observation and tests. Data analysis was carried out in a comparative descriptive manner by comparing the results between the two cycles. The research results showed that: (1) there was an increase in student activity in the Make a Match model learning, with the average percentage of student activity increasing from 75% in cycle I to 90% in cycle II; (2) there was an increase in the average value of student learning outcomes and the percentage of completeness of student learning outcomes, with the average value increasing from 62.28 in cycle I to 76.36 in cycle II, and (3) the percentage of completeness of student learning outcomes increased from 60% in cycle I to 88% in cycle II. Based on these findings, it can be concluded that the use of the Make a Match learning model is effective in improving student learning outcomes in science subjects with the material "Animal and Human Movement Organs" in class V.
Social Media Exposure and Grammar Proficiency of Junior High School Students’: A Correlational Study

Social media has emerged as a contemporary form of media with diverse attributes and characteristics. It serves as a means of instruction, and the younger generation frequently engages with it for various social interactions and communication purposes. While social media offers features not limited to education and is readily accessible to students, it can also impact certain academic aspects through this new digital medium. This study investigated the association between social media exposure and grammar proficiency among junior high school students, specifically spelling and punctuation marks usage. The researchers employed a correlational design and collected quantitative data. Through, total population sampling method, students from Grades 7, 8, 9, and 10 in a laboratory school in Eastern Visayas were chosen. The questionnaire included a spelling and punctuation examination, and the results were analyze using statistical methods such as mean, percentage, standard deviation, Pearson correlation (r), and Eta – correlation. This study's findings indicate no significant relationship between the grammar proficiency of the respondents and their social media exposure, as there is a relatively low correlation and association between the time spent on social media and grammar proficiency test scores. However, the study also revealed a positive correlation between age and grammar proficiency, implying that the older the respondents, the higher their knowledge about correct spelling and punctuation marks usage. Furthermore, the study also suggests conducting further research to explore the relationship between other components of grammar competency and specific social media platforms, such as TikTok, which has the highest hours of exposure.
Optimized Swarm Enabled Deep Learning Technique for Bone Tumor Detection using Histopathological Image

Cancer subjugates a community that lacks proper care. It remains apparent that research studies enhance novel benchmarks in developing a computer-assisted tool for prognosis in radiology yet an indication of illness detection should be recognized by the pathologist. In bone cancer (BC), Identification of malignancy out of the BC’s histopathological image (HI) remains difficult because of the intricate structure of the bone tissue (BTe) specimen. This study proffers a new approach to diagnosing BC by feature extraction alongside classification employing deep learning frameworks. In this, the input is processed and segmented by Tsallis Entropy for noise elimination, image rescaling, and smoothening. The features are excerpted employing Efficient Net-based Convolutional Neural Network (CNN) Feature Extraction. ROI extraction will be employed to enhance the precise detection of atypical portions surrounding the affected area. Next, for classifying the accurate spotting and for grading the BTe as typical and a typical employing augmented XGBoost alongside Whale optimization (WOA). HIs gathering out of prevailing scales patients is acquired alongside texture characteristics of such images remaining employed for training and testing the Neural Network (NN). These classification outcomes exhibit that NN possesses a hit ratio of 99.48 percent while this occurs in BT classification.
Spatio-Temporal Pattern Analysis of Forest Fire in Malang based on Remote Sensing using K-Means Clustering

Forest and land fire significantly impact the balance of the environment, such as haze pollution, destruction of ecosystems, the high release of carbon in the air, deterioration of health, and losses in various other fields. Based on these factors, developing an early warning system is essential to prevent forest fires, especially in forest and land areas. One of the data that can be used to monitor areas where there are frequent fires is hotspot data taken from the NASA MODIS Fire satellite. Data mining techniques are carried out to process the hotspot data so that the distribution of hotspot swarms is obtained. The data on the distribution of the clustering of hotspots are used to detect areas that are prone to fire from year to year. This study used the K-Means clustering algorithm. The data used in this study is hotspot data from Malang District, Indonesia. The range of hotspot data from January 2018 to June 2022. We use Silhouette coefficient testing to get the best number of classes in the cluster—this study's most recent application of the K-means clustering method to analyze hotspot distribution in a spatial-temporally. We use hotspot data in Malang's forest and land area using hotspot confidence levels &gt;80%.
Cognitive diagnostic assessment of reading comprehension for high- stakes tests: Using GDINA model

Cognitive diagnostic assessment (CDA) is used to study cognitive and educational psychology, and designed to diagnose the underlying abilities of test takers in comprehension language skills such as reading comprehension. Through applying CDA, a test has undergone accurate studies to remove biased test items which yield great impact on individuals, educational systems and societies. In this case, psychometric statistical analyses were applied, Differential Attribute Functioning (DAF)) was also used to detect the probability of the mastery of attributes among test takers, and Differential Item Functioning (DIF) was estimated to show item performance among different candidates in terms of gender, their GPAs in BA, and MA degrees. The randomly selected participants of this study were 7,420 females and males sitting for the nationwide PhD admission test to pursue their education in Applied Linguistics. Moreover, a Q-matrix was developed, data were fed into R studio software, and the Generalized Deterministic Inputs, Noisy “and” Gate (GDINA) model was run. The results of the study flagged large DIF in gender group in 2019; and in gender, BA, and MA groups in 2020. In sum, this study is an attempt to raise the awareness of test developers to shed light on the critical discursive sources of inequity and bias. The implication of this study can provide pedagogically useful diagnostic information for test designers and teachers since a proficiency test needs to be valid, reliable, and fair in the context of high-stakes tests so that it would lead to positive changes.
The effect of using paired verbal fluency on students speaking activities

This research purpose to know whether speaking using paired verbal fluency strategies can improve Students activities and to find out how the application of using paired verbal fluency strategy in learning process. This research was conducted through pre-experimental research. The object of this research Were students SMA N 1 Idi which is located on Medan-Banda Aceh street, Tanoh Anou village, Idi Rayeuk, Aceh Timur. The research conducted at August 2022. It was conducted in one class. The research took X MIA 2 Class which consisted of 30 students. To collect quantitative data, the researcher conducted tests before and after treatment. The researcher used (t) test. To analyze the quantitative data, the research used the mean scores of the test. The findings of this research showed that the mean score in pre-test in grammar was (10) and post-test was (15). The mean score in pre-test vocabulary was (11.1) and post-test was (18.5). the mean score in pre-test comprehension (11.5) and post-test was (19). The mean score in fluency (11.5) and post-test was (18). The mean score in pronunciation was (11.3) and post-test was (18). And the total result pre-test was (11.1) and post-test (17.1). So, this is showed students got improvement in their speaking after using paired verbal fluency strategy.
Histological Outcome of Needle Core Biopsies in Breast Lesions and Advantage of Using Reporting Categories of Royal College of Pathologists, London (UK)

Objective: To determine the frequency of various categories of lesions in needle core biopsies done in breast lumps and the utility of using the reporting categories (B1 – B5) of the Royal College of Pathologists London (United Kingdom).&#x0D; Study Design: Cross-sectional study.&#x0D; Place and Duration of Study: Department of Histopathology, Foundation University Medical College, Islamabad Pakistan, from Jan to Dec 2021.&#x0D; Methodology: The study included one hundred cases of needle core biopsies done on breast lumps. After processing the tissue, the slides were made and stained with Hematoxylin and Eosin. Microscopic evaluation was done by the consultant Histopathologist. The frequency of various breast lesions was analyzed, and they were categorized into different ‘B’ categories according to Royal College of Pathologists guidelines.&#x0D; Results: The lesions included in B1 category (Normal tissue) comprised five cases (5%), B2 category (Benign) twenty cases (20%), B3 category (Uncertain malignant potential) twelve cases (12%), B4 category (Suspicious for malignancy) three cases (3%) and B5 category (Malignant) sixty cases (60%).&#x0D; Conclusion: Reporting of needle core biopsies, according to the reporting categories of the Royal College of Pathologists, London (B1–B5), gives a precise diagnosis of most lesions and provides the clinician with a clear road map for further management. B5 Category (Malignant) lesions are needle core biopsies' most common histological outcomes.
Lessons Learned about Working from Home During a Pandemic

A survey of 23 questions was sent out to various library related listservs during the fall of 2020 to investigate the unique impact of the COVID-19 pandemic. Traditionally, library technical services departments conducted most, if not all, work in the office. This was mainly because all the necessary equipment, supplies and access to records would prove cumbersome and costly to establish at home. The investigators thus felt as if technical services would experience numerous challenges transitioning to working from home during the pandemic.&#x0D; &#x0D; The results of the survey were mixed. Many but not all elements of technical services tasks were successfully completed at home. Aspects, such as lack of necessary equipment, administrative support and even Wi-Fi made it difficult to completely conduct tasks. In short, investigators found that short-term technical services operations can occur from home. Long term, however, is questionable and dependent upon individual institution’s abilities to financially support technical services.&#x0D; &#x0D; This article hopes to illuminate systematic flaws that create obstacles for technical services employees to work from home. Hopefully, it will also expose critical issues that can be researched in the future.
Ethical Compass: The Need for Corporate Digital Responsibility in the Use of Artificial Intelligence in Financial Services

Service research and business ethics literature intersect concerning the question of artificial intelligence (AI) service robot accountability. In financial services, there is a broad spectrum of potential ethical issues, from data usage to customer vulnerabilities. This article scrutinizes the impact of morality and where accountability resides in the use of AI service robots in financial services. To address this challenge, we discuss the role of Corporate Digital Responsibility (CDR) for firms and illustrate how to implement a conceptual framework on the ethical implications of AI service robot applications, drawing on normative ethical theory. The framework elaborates on how the locus of morality (from human to AI agency) and moral intensity combine within context-specific AI service robot applications, and how this might influence associated accountability. We provide examples of AI robots’ use for different purposes, differentiating between four 'accountability clusters': (1) professional norms, (2) business responsibility, (3) inter-institutional normativity, and (4) supra-territorial regulations cluster. We also discuss the CDR implications in different clusters. Ethical implications of using AI service robots and associated accountability challenges are relevant for a network of actors—from customers and designers to firms and the government. Implementation of the framework incorporates a range of internal and external stakeholders that firms need to consider.
Multi-Sensor Data Fusion for Accurate Human Activity Recognition with Deep Learning

In the era of pervasive computing and wearable technology, the accurate recognition of human activities has gained paramount importance across a spectrum of applications, from healthcare monitoring to smart environments. This paper introduces a novel methodology that leverages the fusion of multi-sensor data with deep learning techniques to enhance the precision and robustness of human activity recognition. Our approach commences with the transformation of accelerometer and gyroscope time-series data into recurrence plots, facilitating the distillation of temporal patterns and dependencies. Subsequently, a dual-path convolutional network framework is employed to extract intricate sensory patterns independently, followed by an attention module that fuses these features, capturing their nuanced interactions. Rigorous experimental evaluations, including comparative analyses against traditional machine learning baselines, validate the superior performance of our methodology. The results demonstrate remarkable classification performance, underscoring the efficacy of our approach in recognizing a diverse range of human activities. Our research not only advances the state-of-the-art in activity recognition but also highlights the potential of deep learning and multi-sensor data fusion in enabling context-aware systems for the benefit of society.
PyDraw Tkinter Example Application

This chapter builds on the GUI library presented in the last two chapters to illustrate how a larger application can be built.
Machine Learning in Python

This chapter explores the use of machine learning algorithms to perform further Data Science types takes. It does this by taking the data sets used in the Pandas and data analytics chapter and applies several machine learning systems to create predictors for people’s behaviour based on the 2020 COVID data.
Stream IO

In this chapter we will explore the stream I/O model that under pins the way in which data is read from and written to data sources and sinks. One example of a data source or sink is a file but another might be a byte array. The remainder of this chapter first introduces the stream model, discusses Python streams in general and then presents the classes provided by Python. It then considers what is the actual effect of using the open() function presented in the last chapter.
Performance Monitoring and Profiling

This chapter considers performance monitoring and profiling of Python programs. It considers why you might want to monitoring performance and memory, and the difference between monitoring and profiling. It then presents tools available for both monitoring and behaviour and memory profiling.
Tkinter GUI Library

The Tkinter library is a cross-platform GUI library (or toolkit) for Python. This chapter introduces Tkinter. It allows programmers to develop highly graphical user interfaces for their programs using common concepts such as menu bars, menus, buttons, fields, panels and frames. This chapter introduces Tkinter.
Regular Expressions in Python

Regular expression is a very powerful way of processing text while looking for recurring patterns; they are often used with data held in plain text files (such as log files), CSV files as well as Excel files.
PyTest Testing Framework

There are several testing frameworks available for Python, although only one, unittest comes as part of the typical Python installation. In this chapter we will look at PyTest and how it can be used to write unit tests in Python for both functions and classes.
Pip and Conda Virtual Environments

Many Python developers use a virtual environment to handle the modules installed for a particular project. For many developers pip virtual environments are the go-to way of handling such configurations. For the majority of this book this is the approach we have assumed. However, within the Data Science world just as many developers use conda and the associated Anaconda environment. This chapter introduces conda, Anaconda and why they are so popular with data scientist.
Alternatives to Pandas

This chapter considers alternatives to Pandas 2.x including Pandas 1.x, Polars and R.
Logging in Python

Python has included a built-in logging module since Python 2.3. This module, the logging module, defines functions and classes which implement a flexible logging framework that can be used in any Python application/script or in Python libraries/modules. This chapter introduces the logging module in Python.
The __init__ Versus __new__ and __call

Python classes have many special methods that are of the form __<name of method>__. These methods are sometimes referred to as magic methods or double underscore methods (also dunder methods which is short for double underscore methods). Many of these support operators such as __eq__ (for the equality operator==) or __lt__ (for the less than operator<) or for specification functionality such as __len__ for determining the length of an object or __str__ and __repr__ for converting objects into string formats. However, two special methods that often get confused are __new__ and __init__. These two special methods are associated with instance creation but have different roles and are run at different times in the object creation process. For many developers they only ever use __init__ and may not even realise that there is a __new__ method available. This chapter looks at these two methods, their roles and how they are defined. The chapter concludes by briefly introducing the __call__ method.
Introduction to Logging

Many programming languages have common logging libraries including Java and C#, and of course Python also has a logging module. Indeed the Python logging module has been part of the built-in modules since Python 2.3. This chapter discusses why you should add logging to your programs, what you should (and should not) log and why just using the print() function is not sufficient.
Class Slots

Python classes are very flexible, they allow data and behaviour to be defined when the class is created, but also dynamically at any point in the lifetime of the class and its instances. This technique is known as Monkey Patching and can be extremely useful. However, in other situations, allowing the data or behaviour of a class to change dynamically after the class has been defined, might be very confusing and make the system harder to maintain. The issue is that a class’s attributes can be added at any time, and there is no formal specification of the attributes—that is until we look at slots. Slots allow us to specify what attributes a class will have and to ensure that those attributes and only those attributes are used with the class and its instances. This chapter introduces Python class slots.
Introduction to Sockets and Web Services

In the following two chapters we will explore socket-based and web service approaches to interprocess communications. These processes may be running on the same computer or different computers on the same local area network or may be geographically far apart. In all cases information is sent by one program running in one process to another program running in a separate process via internet sockets.
Threading

Threading is one of the ways in which Python allows you to write programs that multitask; that is appearing to do more than one thing at a time.