Reviewerly/exHarmony huggingface dataset:
THE EFFECTIVENESS OF USING COMIC MEDIA IN SOCIAL SCIENCE SUBJECT IN MADRASAH TSANAWIYAH OF PAREPARE CITY

This study aims to determine the effectiveness of using comic media in increasing students’ motivation in social science subjects. This study is an experimental study with a draft factorial pre-test post test involving variable use of comic media. This study was conducted at State Madrasah Tsanawiyah (MTsN) of Parepare city which involved two study groups in class VIII with a total of 24 students as respondents. The instrument of comic media use was declared valid and reliable with a Cronbach Alpha value of 0.917 containing 24 statement items. Descriptive analysis of comic media use obtained a mean pre-test value of 46.73 and post-test 82.80 which means that the results showed an increase motivation to learn after being given a learning treatment using comic media. The hypothesis test shows a significance value of 0.0001 which means the use of learning comic media provides better results than the use of learning media in the form of Power points. This happens because comic media is interesting, entertaining, and easy for learners to understand. &#x0D; Abstrak: &#x0D; Penelitian ini bertujuan untuk mengetahui efektivitas penggunaan media komik pada mata pelajaran IPS. Penelitian ini adalah penelitian eksperimen dengan rancangan faktorial pre test-post test yang melibatkan variabel penggunaan media komik. Penelitian ini dilaksanakan di MTs Negeri Kota Parepare yang melibatkan dua rombongan belajar di kelas VIII dengan total 24 siswa sebagai responden dalam penelitian. Instrumen efektivitas penggunaan media komik dinyatakan valid dan reliabel dengan nilai Cronbach Alpha 0.917 yang berisi 24 item pernyataan. Hasil analisis Deskriptif penggunaan media komik diperoleh nilai mean Pre Test 46,73 dan Post Test 82,80 artinya hasil menunjukkan adanya peningkatan setelah diberikan treatmen pembelajaran menggunakan media komik. Uji hipotesis menunjukkan nilai signifikan sebesar 0.0001 yang berarti penggunaan media komik pembelajaran memberikan hasil yang lebih baik dibandingka dengan penggunaan media pembelajaran berbentuk Power point. Hal ini terjadi karena media komik menarik, menghibur, dan mudah untuk dipahami oleh peserta didik.
PLAY-BASED LEARNING FOR CREATING FUN LANGUAGE CLASSROOM

Playing is essential for children. Thus, play-based learning has been argued to create engaging learning. Employing literature review research from George, this study aims to provide a comprehensive review of play-based learning, the types of play-based learning, and their strengths and weaknesses for language learning. The data sources were previous studies published from 2015-2020 in reputable international journals and accredited national journals indexed by Sinta and other relevant sources. Play-based learning can be categorized into three types: child-directed play that results in involuntary creative learning; teacher-directed play, which allows teachers to set up more structured plays; and mutually-directed play, which combines both types of play to provide maximum benefits for both teachers and children. It implies that teachers should select the type of play that suits the children's needs, situation, and learning objectives when choosing to implement play-based learning.&#x0D; Abstrak:&#x0D; Bermain sangat penting bagi anak-anak sehingga pembelajaran berbasis bermain dianggap sebagai pembelajaran yang menarik. Dengan menerapkan model Kajian Pustaka dari George, penelitian ini bertujuan untuk menyajikan paparan komprehensif mengenai pembelajaran berbasis permainan, jenis-jenisnya, serta keunggulan dan kelemahannya untuk pembelajaran bahasa. Sumber data dalam penelitian ini adalah hasil penelitian-penelitian yang diterbitkan pada 2014-2020 di jurnal internasional bereputasi atau jurnal nasional terakreditasi Sinta, serta sumber lain yang relevan. Pembelajaran berbasis permainan dapat dikelompokkan menjadi tiga jenis. Pertama, permainan bebas yang diarahkan anak-anak, yang menghasilkan pembelajaran bahasa spontan dan kreatif tanpa campur tangan guru. Kedua, permainan yang diarahkan guru, yang memungkinkan pembelajaran yang lebih terstruktur dengan arahan guru. Ketiga, permainan kolaborasi yang memberikan manfaat yang maksimal karena baik guru maupun anak-anak merencanakan permainan tersebut. Bagaimanapun, dalam memilih jenis permainan yang akan digunakan, guru diharapkan mempertimbangkan kekuatan dan keterbatasan masing-masing jenis permainan berdasarkan kebutuhan, situasi, dan tujuan pembelajaran anak.
ERN Cryptosystem for the Security of Textual Data based on Modified Classical Encryption Techniques

Objectives:To develop an algorithm based on classical encryption techniques that cannot be cryptanalyzed easily.Methods: We have proposed a new hybrid approach for the encryption and decryption of data.In this technique, some bits from the plain text, after converting it into binary form, are deleted and permuted in another place and placed back in the text.Findings: We examine the encryption and decryption times of various plaintexts of different sizes.Here, we compare the proposed ERN (Ekta Ritu and Niram) Cryptosystem with the algorithm based on 2's complement method based on time complexity and efficiency.Novelty: A table displaying the encryption and decryption times of several input files of various sizes for the proposed algorithm and the already existing algorithm is given, with a relevant graph, proves the novelty of the cryptosystem.The experimental results show that the ERN cryptosystem has better performance and efficiency than the algorithm based on 2's complement method.
Taman Baca dan Belajar “Ransel Buku” Sebagai Aksi Nyata Menumbuhkan Kecintaan Anak Pada Buku dan Kegiatan Literasi

This research aimed to describe the real action of the Reading and Learning center “Ransel Buku” Center to increase children's love of books and literacy activities in Petuk Katimpun Village, Jekan Raya District, Central Kalimantan Province so that it can become an inspiration and motivation for readers to actively participate in foster and promote a love of books and literacy activities for the community, especially for children in the surrounding environment.&#x0D; This research was conducted using a descriptive qualitative method. The data collection method in this study was the interview method, namely by conducting a dialogue with the founder of the Reading and Learning center “Ransel Buku” and making direct and indirect observations.&#x0D; From the results of the data obtained, it can be concluded that Reading and Learning center “Ransel Buku” from its inception to today has provided real action in fostering children's love of books and literacy activities. This can be seen from the various activities carried out such as book reading activities, teaching and learning activities, “Ransel Buku” boat, and many others. In addition, the number of reading books available in Reading and Learning “Ransel Buku” ack has reached 8,000 book titles. The Reading and Learning center“Ransel Buku” has won many awards both at the provincial and national levels.
Representation of Female Characters in the Novel "Women at Point Zero" by Nawal EL Saadawi using the Sara Mills Perspective Approach

This study aims to describe the representation of female characters in the novel Woman at Zero Point by Nawal El Saadawi in terms of the subject-object position and in terms of the reader's position using the Sara Mills perspective approach. This research is qualitative with a qualitative descriptive method. The data source is the novel Woman at Zero Point by Nawal El Saadawi. The research results are as follows. First, the position of the female character as the subject describes the female character who is considered to have committed a rebellion in the form of resistance against men through physical violence. Second, in the position of the character as an object, the female character suffers injustice throughout her life from childhood to adulthood, causing her to fall into the valley of humiliation. Third, in the reader's position, female characters are described as experiencing injustice in the form of stereotypes, prostitution, and violence.
Design and Implementation of Intelligent Key Cryptography using Time and Tamil Unicode

Objectives: To propose a new novel and unique cryptosystem with interfaces for the designed cryptosystem and to implement and test the new designed methodologies.Methods: The Tamil Unicode is used to convert the Plain text (Sender's message) to Intelligent Key Cryptography system (IKC) Intermediary code.This intermediary code is converted to IKC cipher text by transpositioning characters with integer digit values of Time in positive direction.IKC decryption of cipher text (received message) to Intermediary code is done using Tamil Unicode and then this is converted to plain text by trans-positioning characters with integer digit values of Time in negative direction.The IKC algorithm developed thus address the discrepancies for the existing algorithms based on the literary survey done.Findings: In the proposed IKC algorithm, the key and key space are generated dynamically from the system Time and the system font Tamil Unicode; thus, reducing the key maintenance problems of the existing algorithms.In current cryptography algorithms, work is based on the assumption that the key value never comes to zero.But all the algorithms are mathematical calculations which will return to zero at an infinite point.This drawback is overcome in IKC algorithm by taking the Time the real infinity.The value of the time once passed will never return.The entire algorithm works in a secure shell developed using C++ and has proved to satisfy the needs of the objective of a robust cryptosystem.Comparative analysis shows that IKC works better compared to the existing system.Novelty: The IKC algorithm displays as: (i) keys are generated dynamically, (ii) cipher once formed is never repeated, even if the same plaintext is enciphered again, and (iii) it satisfies NIST policies.
Deep Learning Based Channel Estimation for MIMO-OFDM System with Modified ResNet Model

Objectives:The effectiveness of wireless communication systems is significantly influenced by channel estimation.In order to accurately estimate the Channel Impulse Response (CIR) of the channel under varied circumstances, channel estimation is a crucial procedure in the functioning of MIMO-OFDM (Multi-Input and Multi-Output -Orthogonal Frequency Division Multiplexing) systems.Methods: The proposed Deep Learning(DL) based Convolutional Neural Network (CNN) with modified ResNet architecture channel estimation method improves the Bit Error Rate(BER) and Mean Square Error(MSE) performance compared to conventional channel estimation methods.We have compared the proposed CNN method with the Least square (LS), Minimum Mean Square Error(MMSE) and Deep Neural Network(DNN) based channel estimation methods.The results have been discussed by using BER and MSE versus SNR graphs.The simulation results are being performed on the MATLAB platform of the R2021b version.Findings: The DL-based MIMO-OFDM channel estimation can achieve better performance over multipath fading channels if Channel coefficients are perfectly estimated at the receiver.The simulation test is carried out in different test conditions by considering the different number of transmitter and receiver antennas with respect to different QAM modulation order values.Novelty: The DL-based modified ResNet architecture comprises a set of layers modified to estimate the optimal channel parameters.For achieving a great reduction of MSE and BER compared to conventional channel estimation methods, the layers of the ResNet-model are modified.
Deep Learning-Based SOLO Architecture for Re-Identification of Single Persons by Locations

Analyzing and judging of captured and retrieved images of the targets from the surveillance video cameras for person re-identification have been a herculean task for computer vision that is worth further research. Hence, re-identification of single persons by locations based on single objects by locations (SOLO) model is proposed in this paper. To achieve the re-identification goal, we based the training of the re-identification model on synchronized stochastic gradient descent (SGD). SOLO is capable of exploiting the contextual cues and segmenting individual persons by their motions. The proposed approach consists of the following steps: (1) reformulating the person instance segmentation as: (a) prediction of category and (b) mask generation tasks for each person instance, (2) dividing the input person image into a uniform grids, i.e., G×G grid cells in such a way that a grid cell can predict the category of the semantic and masks of the person instances provided the center of the person falls into the grid cell and (3) conducting person segmentation. Discriminating features of individual persons are obtained by extraction using convolution neural networks. On person re-identification Market-1501 dataset, SOLO model achieved mAP of 84.1% and 93.8% rank-1 identification rate, higher than what is achieved by other comparative algorithms such as PL-Net, SegHAN, Siamese, GoogLeNet, and M 3 L (IBN-Net50). On person re-identification CUHK03 dataset, SOLO model achieved mAP of 82.1 % and 90.1% rank-1 identification rate, higher than what is achieved by other comparative algorithms such as PL-Net, SegHAN, Siamese, GoogLeNet, and M 3 L (IBN-Net50). These results show that SOLO model achieves best results for person re-identification, indicating high effectiveness of the model. The research contributions are: (1) Application of synchronized stochastic gradient descent (SGD) to SOLO training for person re-identification and (2) Single objects by locations using semantic category branch and instance mask branch instead of detect-then-segment method, thereby converting person instance segmentation into a solvable problem of single-shot classification.
Raspberry Based Hand Gesture Recognition Using Haar Cascade and Local Binary Pattern Histogram

Many companies and even public institutions for civil servants currently use photo-taking for the attendance. However, this strategy is still considered ineffective since the employees still can hack the attendance by making their own photos and put them in their desks. Therefore, an alternative that can complement the current face detection method is highly needed so that the employee’s attendance can be directly monitored. One of the methods that can be used to detect the attendance is hand gesture detection. This research aims to detect hand gestures made by the employees to ensure whether they really come to work or not. This research make the chance for manipulation using photo or fake GPS is quite small. For the purpose of hand gesture recognition, this study utilized Local Binary Pattern Histogram algorithm. The hand gesture image was first taken using a raspberry pi camera and then processed by the device to examine whether it matches the registered ID or not. The results showed that ID recognition by using hand gestures is detectable. The number recognition in hand gestures includes numbers 1 to 10. The test results showed that for 5 trials, the average time required for reading hand gestures using a laptop was 9.2 seconds, while that of using raspberry was 14.2 seconds. The results of this research show that the system has not been able to distinguish which hand is read first, so numbers that have the same number are considered the same, such as 81 and 18. So, the motion reading using a raspberry takes longer than that of using a laptop because the laptop's performance is higher than that of a raspberry and system cannot distinguish between numbers consisting of the same number.
Hotel Employees’ Attitude and Acceptance Toward Human-Robot Co-Working Based on the Industry 5.0 Concept

The emergence of AI-powered machines and robotics technology has strongly influenced the service industry, especially the hotel business. The effects of their introduction to the work environment on the human workforce have been a subject of much debate. However, practical studies in this regard are relatively limited. Therefore, this study investigates the employees’ attitude and acceptance toward working alongside robots in a sample of employees working in luxury hotels in Yekaterinburg, Russia. This study employed a self-administered questionnaire as the data collection instrument. Two hundred questionnaire forms were distributed. Among them, 167 forms were completed and valid for analysis. Data were analyzed descriptively using IBM SPSS (Version 28). The findings revealed that, although the employees agreed to interact with robots and indicated that robots are helpful, enjoyable, and productive, they also pointed out that robots would control jobs. Besides, the extensive introduction of robots will lead to social issues such as losing contact with humans. The study conclusion has practical implications for hotel managers and can guide further research for academics.
Social Media Algorithms

The need and desire to communicate information, ideas, and emotions has been strong in humans. It has evolved from traditional forms such as story-telling, plays, paintings, carvings, community gatherings to digital forms of communication. As digital social media platforms are growing at a rapid pace and are touching billions of people worldwide, it becomes important to understand how these platforms work and their effect on users and the society. The present paper analyzes social media algorithms, how they rank content, and how Machine Learning drives these algorithms. The shortcomings of social media algorithms and their future are also discussed.
Towards Service Level Agreement Quantification on Service-Based Computing

A service Level Agreement is an agreement between service providers and consumers that contains the rights and obligations of both parties, particularly in terms of the delivery of services provided during the subscription period on service-based computing. Once approved, normally, the Service Level Agreement will not change until the end of the subscription period. SLA violations are often positioned between yes and no. As a result, service providers must deal with severe penalties or compensation. In this paper, the use of weightage for each SLA parameter is introduced in this paper. Such quantification using weightage is the main contribution. SLA violation detection cases in service-based computing are used to demonstrate how SLA quantification works. In the simulation scenario of SLA quantification, the presence of weightage and its aggregates along with the upper and lower bound is able to help the SLA violation detection process more appropriate. Violations are no longer seen between Yes and No, but the severity of the violation can also be determined. The number of violated parameters is not very influential in determining the level because the main determinant is the weightage. At the same time, the upper and lower limits are also very helpful in determining the level of violation. It is believed that SLA quantification is the way forward for better SLA management.
11 Automated healthcare system using gamification and AI-based chatbot

Due to the current global pandemic in the form of Corona virus, healthcare industry is under immense pressure to meet the ends of patient’s needs. Doctors and nurses are working relentlessly to treat and help the patients in best possible way and still they are facing issues in terms of time management, technical resources, healthcare infrastructure, support staff as well as healthcare personnel. This type of viral pandemic has created a very high demand to use our resources and manpower to a great extent in order to just cure this virus. Due to this most of the medical professionals have been busy finding solutions and vaccines to treat the virus hence unknowingly decreasing the attention toward the treatment of patients suffering from various other existing diseases. Owing to the current technical advancements in the field of artificial intelligence and machine learning, we, as engineers, can help the healthcare industry to a significant level. In this paper, we aim to create an automated Healthcare System using gamification and AI-based chatbot which can prove to be a boon to medical professionals to assist them in treating the patients as well as justifying the robust technological advancements to be of great use. Chatbot is a software application designed to simulate conversation with human users through interactive and tailored content. It is often described as the most trending and promising expressions of interaction between humans and machines using artificial intelligence and natural language processing. Furthermore, we will add a module of gamification to make the website more interactive and user friendly such as healthcare quizzes and/or health score generators. Through this study, we aim to create a fully functional chatbot which will help the patients/users to know about the disease by simply entering the symptoms they possess. Additionally, they can find nearby hospitals and book appointments. This paper presents the study and usage of AI-based chatbot in healthcare industry for basic diagnostic evaluation and suggesting robust measures for the patients/users.
Bystanders or change makers? Where do management controllers fit in the digital world?

This new digital age implies radical changes, not only for companies but also for corporate functions. This includes, of course, management control. Nowadays, management controllers have two missions, data reliability for decision-making and supporting managers at all levels of the company. In this context, the ongoing digital transformation raises new tensions in the role of management controllers. They have to make a significant effort in data collection and reliability, leaving them with little time to advise managers. Despite this, there is the promise for management controllers to avoid being locked into these technical tasks, mastering the new digital tools and consequently contributing to the digital transformation of their firms. As such, management controllers may give value to Big Data, making sense of new opportunities and accompanying top management with their knowledge.
A Survey Paper on Sign Language Recognition System using OpenCV and Convolutional Neural Network

Abstract: Communication is a very important part of our Human life to express feelings and thoughts. People like the Deaf &amp; Dumb always face difficulty as they cannot speak in their regional languages. Language performs a very important role in communication, it can be verbal i.e. using words to speak, read and write or non-verbal using facial expressions and sign language. So, people like the Deaf and Dumb have the only choice to speak in Sign language means non-verbal. However, Sign language is a very important mode of their community. But it is difficult for people who are unaware of sign language. Hence, here is a system “Sign Language Recognition System Using Open CV and Convolutional Neural Network”. We proposed a system that converts sign language to their appropriate alphabet, words in a standard language to make easily understood by all. We also make some default gestures that we daily use in our day-to-day life. The project works on a learning algorithm, it requires the collection of datasets which includes images of each alphabet, and digits to train the model. For the classification of the image convolutional neural network is used. Also for accessing the camera and taking input we used an open cv.