Reviewerly/exHarmony huggingface dataset:
Review on Lightweight Cryptography Techniques and Steganography Techniques for IOT Environment

In the modern world, technology has connected to our day-to-day life in different forms. The Internet of Things (IoT) has become an innovative criterion for mass implementations and a part of daily life. However, this rapid growth leads the huge traffic and security problems. There are several challenges arise while deploying IoT. The most common challenges are privacy and security during data transmission. To address these issues, various lightweight cryptography and steganography techniques were introduced. These techniques are helpful in securing the data over the IoT. The hybrid of cryptography and steganography mechanisms provides enhanced security to confidential messages. Any messages can be secured by cryptography or by embedding the messages into any media files, including text, audio, image, and video, using steganography. Hence, this article has provided a detailed review of efficient, lightweight security solutions based on cryptography and steganography and their function over IoT applications. The objective of the paper is to study and analyze various Light weight cryptography techniques and Steganography techniques for IoT. A few works of literature were reviewed in addition to their merits and limitations. Furthermore, the common problems in the reviewed techniques are explained in the discussion section with their parametric comparison. Finally, the future scope to improve IoT security solutions based on lightweight cryptography and steganography is mentioned in the conclusion part.
An Improve the Onboarding Process in Trade Finance Applications Using Blockchain Technology

Today, challenges in Know Your Customer (KYC) and Anti-Money Laundering (AML) processes include inefficiencies, data silos, and the risk of fraudulent activities. Integrating blockchain technology offers a transformative solution to these issues. Blockchain's decentralized and tamper-resistant nature ensures a single, verifiable source of truth for customer information, reducing data discrepancies across institutions. Smart contracts can automate AML compliance checks, ensuring real-time monitoring and rapid response to suspicious activities. The immutability of blockchain records enhances auditability, facilitating regulatory compliance. Furthermore, the secure and transparent nature of blockchain instills trust among stakeholders, fostering collaboration in combating financial crimes. By leveraging blockchain in KYC and AML processes, the financial industry can achieve enhanced efficiency, reduced fraud, and strengthened regulatory adherence.
An Analysis of The Language Variations of Luwunese Through Speech Acts (Fokus: Luwu, North Luwu, and East Luwu)

The main objectives of this research were to determine the differences of language variation in the use of regional language especially Luwu, North Luwu and East Luwu in South Sulawesi area. The descriptive qualitative research method was applied by the researcher. The research was conducted at Luwu, North Luwu and East Luwu. The researcher describes that variety of luwu, North Luwu and East Luwu. In this research the researcher using purposive sampling, the researcher observed and interviewed all of the respondents who from Luwu, North Luwu, and East Luwu. The researcher used video recording and field notes to conduct observation. Respondents’ activities and attitudes social was captured on video. Meanwhile, the researcher used field notes to obtain more accurate data. Based on the observation that The language variation in Luwu were different with the language North Luwu people and East Luwu, because the variation Luwu language has same the similarity language spoken Buginese people and near also from the land of Buginese are. There were several factors that caused language variations of Luwunese including internal factors such as self perception, perception of language, language difficulties , and external factors such as social judgment. The factors divided into three categories: linguistic factors, which cover linguistic difficulties, psychological factors, and environmental factors. As a result, it is suggested that the researcher and reader get to know more about the language variations of Luwunese. By becoming acquainted with the language variations of Luwunese, the people has to study about the language of variety, in order that can helping communicate with the kind.
Virtual Reality Based Hypermedia Training for Teachers of MAN 2 Model Makassar

This Community Service Activity (PKM) aims to; (1) provide an introduction to teachers at MAN 2 Model Makassar regarding Virtual Reality learning media as an alternative IT-based learning media, and (2) train MAN 2 Model Makassar teachers to be able to utilize Virtual Reality-based learning media. The methods applied in this service program are the presentation method, the demonstration method, and the practical method. The presentation method is applied in the introduction of hypermedia software using the millers lab application, its benefits, and its application in making virtual reality-based media, demonstration methods regarding program operations and practical methods where teachers practice directly making learning media according to their respective subjects with the use of media-based virtual reality
Pemberdayaan Masyarakat dalam Pemanfaatan Lidah Buaya (Aloe Vera) Sebagai Edable Coating Dalam Memperpanjang Masa Simpan Tomat (Solanum Lycopersicum) Di Sukajadi Bandung

Background: The gel part of the aloe vera plant can be used as an edible coating for fruit or vegetables. Using aloe vera gel as a coating is an alternative to chemical preservatives. This activity empowers the community to use aloe vera gel as a tomato fruit coating (Solanum lycopersicum). Method: This interactive discussion was attended by 22 RW cadres. 01 Sukawarna Village, Sukajadi District, Bandung City. Counseling and assistance in making aloe vera gel to preserve tomatoes were also conducted after an interactive discussion. Results: there was an increase in knowledge about food additives by 5%, and knowledge about the benefits of aloe vera gel as a tomato coating increased by 84.6%. Skills in making aloe vera gel as a tomato coating material increased by 36.4%. Conclusion: There was increased public knowledge and skills in using aloe vera gel as a natural coating for tomatoes.
Home Automation for Disable Person Using Gesture Control and Artificial Intelligence

For an extended time, gestures communique has performed a giant function in conveying information. Before the evolution of human beings, while no verbal mode of communique changed into the present, gesture communique changed into the simplest manner to interact with different human fellows. After evolution, with language improvement, the want of gestures for brief variety communique changed into removed. However, it became nonetheless giant in conveying messages at large distances, i.e., by lightening the hearth place at a far-off place. The modern generation is gaining this mode of communique, and it has correctly translated those gestures into the virtual world. The improvement of augmented truth is an instance of it. With the arrival of deep gaining knowledge of algorithms like Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), the issue in records evaluation and sample recognition has come to be very smooth and robust. In this undertaking, we've advanced a mind gestures (signals) reputation machine that controls home automation home equipment for bodily impaired people.
Training on Making Digital Learning Media to Improve Motivation and Learning Outcomes of Elementary School Students for Teachers SD Negeri 068332 Medan

Learning media today is one thing that is very important in supporting the success of the student learning process at school. Monotonous learning only in the form of narration makes students bored with the learning process, so teachers must change student learning methods to make it more interesting and of course to improve the learning outcomes of these students. The demands of the times have required teachers to understand digital learning media. Of course, it is accompanied by the teacher's ability to mix and design in such a way that the learning process and the material presented can be in line and not boring. The learning process is basically a communication process through interaction between teachers and students. In the communication process the message is conveyed by the teacher to the recipient of the message or student. In the context of learning in the classroom, the message conveyed can be in the form of teaching materials delivered verbally (oral and written) and / or nonverbally (gestures). Not only teachers as communicators, learners can also act as communicators or messengers. This can happen in the midst of an increasingly modern learning system. Teachers are no longer the only source of learning, but learners can explore themselves to dig up information from various sources and communicate it in the learning process. Thus, there will be two-way communication or multiways traffic communication. Learning with both communication models requires the role of learning media to increase the effectiveness of achieving goals or competencies.
Evaluation of Time Constraints for Providing Electronic Medical Record Documents at Murni Teguh Hospital, Medan

The impact of errors in storing medical records causes delays for officers in searching for medical record documents so that services at the polyclinic are hampered. It is necessary to control the incidence of incorrect insertion of medical record documents so that the incidence of incorrect insertion of medical record documents can be reduced. Electronic Medical Record (RME) is a form of health information service that is computerized and recorded. Health service facilities that implement RME in an effort to improve the quality and quality of services. This research is a qualitative research, case study design which aims to evaluate the timing of providing electronic medical record documents for outpatients at Murni Teguh Hospital. Determination of research subjects using purposive sampling technique. The research subjects consisted of the Director of Murni Teguh Hospital, the head of the Medical Record Installation as the main informant, the Patient Registration Officer, and 3 medical record staff as triangulation informants. In collecting data, researchers conducted in-depth interviews, direct observation and document studies. Data analysis was carried out using interactive models, data reduction processes, verification and drawing conclusions. In this study, it was found that the time required to provide electronic medical record documents for outpatients at Murni Teguh Hospital was a minimum of 4 minutes, a maximum time of 9 minutes with an average time needed to provide electronic medical record documents was 6.6 minutes. Obstacles encountered are errors during use, as well as HR who still do not understand the use of electronic medical record systems. By providing electronic medical record documents, the work of the patient medical record department becomes more efficient, makes it easier for officers to search for patient medical records and the benefits that patients get are shorter waiting times.
Cyber Crimes in the State of Tamilnadu with Special Reference to Investigation Process

The society and its needs changes with the time therefore the criminal law is required as per the situation. Thus the prime object of criminal law is the protection of the public by the maintenance of law and order in every situation even in the age of information technology. The progress of civilization is evidenced by the everchanging information technology, which is easily accessible by use of computers and no doubt, put to use for improvement in the living ofHuman Beings. Information Technology has made improvements in every aspect of human life such as education, industry, commerce, governance, personal lifestyle, and social life around the world.Crime is a social and economic phenomenon and is also old as human society. Crime is a legal concept and has the sanction of the law Crime or an Offence is a wrong that can be followed by criminal proceedings which may result in punishments. The hallmark of criminality is that it is a breach of criminal law. As per Lord Atkin “ the criminal quality of an act cannot be discovered by reference to any standard but one: is the act prohibited with penal consequences”. Many of the cyber-crimes penalized by the IPC and the IT Act have the same ingredients and even nomenclature. The punishment prescribed for offenses under sections 67A and 67B of the IT Act is on first conviction, imprisonment of either description for a term which may extend to 5 (five) years, to be accompanied by a fine which may extend to Rs. 10,00,000 (Rupees ten lac) and in the event of second or subsequent conviction, imprisonment of either description for a term which may extend to 7 (seven) years and also with fine which may extend to Rs. 10,00,000 (Rupees ten lac).
A Novel Profound Learning-Based System for Breast Cancer Location and Classification Utilizing Exchange Learning

Breast cancer is the leading cause of death in Asian women. Breast cancer can be detected early and treated aggressively. In this paper, we propose a new deep learning framework utilizing the index learning concept for breast cancer diagnosis and imaging. Typically, in-depth questions from experts are designed and presented in a specific format. Unlike classical learning paradigms, which are based on parallel development and emergence, the goal is to use the knowledge gained from solving one problem to solve another problem. In this study, we used CNN pretrainers to extract features from images, such as Google Net, VGGNet (Visual Geometry Group Network), and ResNet (Unsupervised Network), which combine the principles of neural networks and social networks. This has already happened. Contains partial information. Use the blunt treasure in the veil. A standard data model was used to evaluate the proposed optical products. Chemical images of different types of breast cancer have been discovered in archaeological finds and have proven useful in educational exploration into the unknown.
Toxic Comment Classification based on Personality Traits Using NLP

Concerns about the frequency of harmful remarks have been raised by the growth of online communication platforms, which makes it difficult to create inclusive and safe digital spaces. This study explores the creation of a strong framework that uses machine learning algorithms and natural language processing (NLP) methods to categorise harmful comments. In order to improve the accuracy and comprehensiveness of categorization, the study investigates the integration of personality trait analysis in addition to identifying hazardous language. A wide range of online comments comprised the dataset that was gathered and put through extensive preparation methods such as text cleaning, lemmatization, and feature extraction. To facilitate the training and assessment of machine learning models, textual data was converted into numerical representations by utilising TF-IDF vectorization and word embeddings. Furthermore, personality traits were extracted from comments using sentiment analysis and language clues, which linked linguistic patterns with behavioural inclinations. The study resulted in the development and assessment of complex categorization models that combined features from textual content and inferred personality traits. The findings show encouraging associations between specific personality qualities and the use of toxic language, providing opportunities to identify subtle differences in toxic comment contexts. In order to provide insights into developing more sophisticated and successful methods of reducing toxicity in online discourse, this study outlines the methodology, major findings, and consequences of incorporating personality traits analysis into the classification of toxic comments.
Hybrid Convolution neural Network and Graph Neural network for Detection of Leukocyte

In pathology and medical diagnostics, the identification of leukocytes, white blood cells essential for immune system function, is significant. The hybrid neural network model used in this study, which combines the strengths of convolutional neural networks (CNNs) and graph neural networks (GNNs), gives a unique method for the identification of leukocytes. Due to the intricate spatial and relational patterns visible in microscopic pictures of blood samples, leukocyte identification is difficult. The proposed hybrid model incorporates a GNN module to record the contextual associations among leukocytes in a blood sample and a CNN module to extract fine-grained characteristics from individual leukocyte pictures. Each leukocyte picture is seen in this paradigm as a node in a network, with the edges denoting the interactions between the cells' locations or contexts. While the GNN module uses graph-based representations to capture the connections and dependencies between leukocytes within a blood sample, the CNN module efficiently extracts local visual characteristics from leukocyte pictures. These two modules are used to produce a thorough and context-sensitive depiction of the leukocyte detection issue. The importance of this study resides in its potential to increase the precision and effectiveness of leukocyte identification in pathology and medical diagnostics, leading to better patient care and illness diagnosis. This hybrid CNN-GNN model may also be used for a variety of other medical image analysis tasks that call for taking both local and contextual information into account. In successfully identifying leukocytes in microscopic images, this hybrid CNN-GNN technique shows promising results. Accuracy, precision, recall, and F1-score are common assessment metrics used to assess the model's performance.
Improving The Efficiency Of Video Transmission In Computer Networks

In-depth examination of current techniques for enhancing the efficiency of video transmission over digital networks is provided in this study. Due to the growing need for high-quality video content, optimizing video transmission is an important area of research. This review categorizes and in-depth examines a range of methods proposed in the literature to enhance video transmission effectiveness. ABR, DNN architecture, adaptive streaming, Quality of Service (QoS), error resilience, congestion control, video compression, and hardware acceleration for video provisioning are just a few of the cutting-edge techniques that are covered in the discussion, which ranges from the more traditional to the cutting-edge. This essay provides a methodical evaluation of the numerous tactics that are available, along with an analysis of their guiding principles, advantages, and disadvantages. The paper also offers a comparative analysis of various approaches, highlighting trends, gaps, and potential future research directions in this crucial domain, all of which help to create more efficient video compression and transmission paradigms in computer networks.
PRIDNet based Image Denoising for Underwater Images

Underwater image enhancement has become a popular research topic due to its importance in aquatic robotics and marine engineering. However, the underwater images frequently experience signal-dependent speckle noise when transmitting and acquiring data, which can limit certain applications such as detection, object tracking. In the recent years, the existing underwater image enhancement algorithms efficiency has been analysed and evaluated on a small number of carefully chosen real-world images or synthetic datasets. As such, it is challenging to predict how these algorithms might function with images acquired in the wild under various circumstances. This paper introduces a new solution for noise removal from underwater images called Pyramid Real Image Noise Removal Network (PRIDNet) with patches.PRIDNet is a three-level network design using image patches. The tests were carried out on a dataset of actual noisy images demonstrate that, in terms of quantitative metrics, our proposed denoising model reduction performs better with the exixting denoisers. We determine the effectiveness and constraints of existing algorithms using benchmark assessments and the suggested model, offering valuable information for further studies on underwater image enhancement.
Sentiment Analysis for Online Product Reviews and Recommendation Using Deep Learning Based Optimization Algorithm

Recently, online shopping is becoming a popular means for users to buy and consume with the advances in Internet technologies. Satisfaction of users could be efficiently improvised by carrying out a Sentiment Analysis (SA) of larger amount of user reviews on e-commerce platform. But still, it is a challenge to envision the precise sentiment polarity of the user reviews due to the modifications in sequence length, complicated logic, and textual order. In this study, we propose a Hybrid-Flash Butterfly Optimization with Deep Learning based Sentiment Analysis (HFBO-DLSA) for Online Product Reviews. The presented HFBO-DLSA technique mainly aims to determine the nature of sentiments based on online product reviews. For accomplishing this, the presented HFBO-DLSA technique applies data pre-processing at the preliminary stage to make it compatible. Besides, the HFBO-DLSA model uses deep belief network (DBN) model for classification. The HFBO algorithm is used as a hyperparameter tuning process to improve the SA performance of the DBN method. The experimental validation of the presented HFBO-DLSA method has been tested under a set of datasets. The experimental results reveal that the HFBO-DLSA approach surpasses recent techniques in terms of SA outcomes. Specifically, when compared to various existing models on the Canon dataset, the HFBO-DLSA technique achieves remarkable results with an accuracy of 97.66%, precision of 98.54%, recall of 94.64%, and an F-score of 96.43%. In comparative analysis, other approaches such as ACO, SVM, and NN exhibit poorer performance, while TextCNN, BiLSTM, and RCNN approaches yield slightly improved SA results.