Reviewerly/exHarmony huggingface dataset:
Being Real on Instagram Reels: An Authentic Tool to Enhance English Speaking Skills

As technology rapidly develops new features, empirical testing of their capability to assist in educational purposes are always needed. This study takes a look at Instagram Reels, which is seldom explored as a language teaching tool, especially for vocational high school students. This study aims at describing students’ perceptions, challenges, and strategies in using Instagram reels as an authentic tool for improving speaking skills. The research used descriptive qualitative research methods. The subjects of the study were five eleventh-grade students from one of the public vocational high schools in Bali, Indonesia. They were selected by conducting a purposive sampling technique. The observation and interview were conducted to collect data. The findings show that a) the perceptions of students on the implementation of Instagram reels to improve speaking skills were favorable. Most students agreed that implementing Instagram reels as an authentic tool in speaking was adaptable, effective, and authentic. It also increased the students’ speaking abilities, which were referred to as positive attitudes. Instagram reels boosted students’ consciousness, motivation, and enhancing their vocabulary, grammar, pronunciation, accent, and cultural knowledge. b) Students faced a variety of challenges when using Instagram reels as a learning medium, such as limited internet access and a lack of digital literacy. To overcome the challenges, students used some strategies, namely using WIFI facilities at school or other public places, practicing a lot, and seeking additional information to improve digital literacy skills using Instagram reels.
Information Technology Risk Analysis and Mitigation Using ISO 31000 and House of Risk (HOR) for SIAK in Western Seram Regency

SIAK stands for population administration information system. It is a computerized system that was established according to administrative service regulations to organize the population administration system in Indonesia, more precisely in the Western Seram Regency. Given the critical function of this application in aiding in identifying regional demographic statistics, it is vital to examine potential dangers while also identifying mitigation measures that may be performed to avoid them. ISO 31000 was utilized in the study to map potential hazards for subsequent reduction using the House of Risk (HOR) methodology. According to the findings of this research, there is one danger that falls into the high category, namely the unstable network. Additionally, based on the results of risk mitigation identification, two mitigation steps are identified that can mitigate 60% of existing risks, namely the construction particular resistant to natural disasters for critical equipment storage and collaboration with internet providers to ensure stable internet and network connections.
Spatial Feature Evolutionary Relationship Discovery Based on Tree Structure Pattern Mining and Spatial Co-Location Pattern Mining in Spatial Cliques

Feature evolutionary relationship discovery based on tree structure pattern mining and spatial co-location pattern mining in spatial cliques aims to combine spatial co-location pattern mining algorithm and tree structure pattern mining algorithm to find spatial cliques in spatial data and evolutionary relationships of spatial features in these spatial cliques. This allows for a deeper analysis of possible causal relationships between spatial features, predicting the occurrence of other spatial features based on the occurrence of certain spatial features, or summarizing general laws. For a spatial clique, the appearance of one spatial feature may lead to the appearance of another spatial feature, which is called evolutionary relationship. Previous spatial co-location pattern mining algorithms (such as join-based) focus on discovering prevalent co-occur spatial features and prevalent co-location patterns. We further discovered evolutionary relationships between prevalent co-occur spatial features in spatial cliques through tree structure pattern mining algorithm.
Review Paper on Smart Video Player

Abstract: In this paper, we have proposed a model for a smart video player which would have two main features .One is the simulation using hand gesture technique and second one is the emotion detection of the video using CNN (ML Algorithm).This model gives an accuracy of 90-96% and hence can be studied for further process .This model yields better results than other models in all aspects.
A Blockchain and Fingerprinting Traceability Method for Digital Product Lifecycle Management

The rise of digitalization, sensory devices, cloud computing and internet of things (IoT) technologies enables the design of novel digital product lifecycle management (DPLM) applications for use cases such as manufacturing and delivery of digital products. The verification of the accomplishment/violations of agreements defined in digital contracts is a key task in digital business transactions. However, this verification represents a challenge when validating both the integrity of digital product content and the transactions performed during multiple stages of the DPLM. This paper presents a traceability method for DPLM based on the integration of online and offline verification mechanisms based on blockchain and fingerprinting, respectively. A blockchain lifecycle registration model is used for organizations to register the exchange of digital products in the cloud with partners and/or consumers throughout the DPLM stages as well as to verify the accomplishment of agreements at each DPLM stage. The fingerprinting scheme is used for offline verification of digital product integrity and to register the DPLM logs within digital products, which is useful in either dispute or violation of agreements scenarios. We built a DPLM service prototype based on this method, which was implemented as a cloud computing service. A case study based on the DPLM of audios was conducted to evaluate this prototype. The experimental evaluation revealed the ability of this method to be applied to DPLM in real scenarios in an efficient manner.
Pravuil: Global Consensus for a United World

The latest developments in blockchain technology have conceptualised very efficient consensus protocols that have not yet been able to overcome older technologies. This paper presents Pravuil, a robust, secure, and scalable consensus protocol for a permissionless blockchain suitable for deployment in an adversarial environment such as the Internet. Using zero-knowledge authentication techniques, Pravuil circumvents previous shortcomings of other blockchains: Bitcoin’s limited adoption problem (as transaction demand grows, payment confirmation times grow much less than that of other PoW blockchains); higher transaction security at a lower cost; more decentralisation than other permissionless blockchains; impossibility of full decentralisation; the blockchain scalability trilemma (decentralisation, scalability, and security can be achieved simultaneously); and Sybil resistance for free implementation of the social optimum. Pravuil goes beyond the economic limits of Bitcoin and other PoW/PoS blockchains, leading to a more valuable and stable cryptocurrency.
Computer Vision: Classification of Images Based On Deep Learning with the CNN Architecture Model

Deep learning is a scientific field in Machine Learning (ML) that is developing with various applications, one of which is visual image processing technology. With the excellent capabilities of computer vision, image processing from computer visuals is used to duplicate the human ability to understand object information in the image. One of the Machine Learning (ML) methods that can be used for object classification in images is the Convolution Neural Network (CNN) method. The two core stages when processing object classification in the image, the first stage is image classification using feedforward, and the second stage applies the backpropagation method. In this study, before the classification stage, this method was first carried out through preprocessing, which is useful as an image separation to focus on the object to be classified. Furthermore, it is carried out by conducting pre-training using the feedforward method with the bias weights, which are updated after every training process. The observations of this study, the results of image classification training with a degree of ambiguity, resulted in a good average accuracy validation value of 0.91 in a confidence interval with a range of 0-1. So, it can be concluded that applying the Convolution Neural Network (CNN) method to distinguish objects in an image can classify them well.
DEVELOPING ENGLISH LANGUAGE MATERIAL FOR HIGH SCHOOL LEVEL USING PICTURES MEDIA TO IMPROVE STUDENTS SPEAKING SKILLS

This study aims to determine the effect of developing teaching materials on the learning of high school students and knowing the effect of developing teaching materials English image media on the speaking ability of high school students (SENIOR HIGH SCHOOL). The design of research and development of teaching materials used refers to research design and development modification of the Borg &amp; Gall development model (1985) and Kemp &amp; Dayton (1985). The subject of the study were the students of High School students. The result of this study is 13 units of varied material. The material consists of variety of topics related to tourist spots and well known places in South Kalimantan.
The utilization of digital technology in music education at Universitas Negeri Yogyakarta

As is known, the most Indonesians have used digital technology in their daily lives, including in representing the art of music. As one of the adaptive educational institutions, Universitas Negeri Yogyakarta (UNY) is deemed necessary to further enhance the essence of music education that is integrated with digital technology. Based on the results of the literature studies and best practices regarding music technology and art, with a qualitative method that produces descriptive data, it can be seen that the foundation of today's music technology is to represent sound into a series of digital data. The fundamental shift of sound representation to digital media, has challenged the orientation of digital technology and its various effects on the process of music creation, presentation and publication. In this paper, the author examines three main functions of using digital technology in the context of music, namely music technology as a tool, instrument and collaboration media. The results of this study are suggestions for an integrated approach between music and digital technology in the educational process for music arts students. Keywords: Music, Technology, Integration
Blockchain and Open Source

Abstract This chapter discusses blockchain technology. Here, the use of open source software in blockchain requires an understanding of blockchain technology and the broader category of ‘Distributed Ledger Technology’ (‘DLT’). Furthermore, blockchain is divided into three layers: protocol layer, network layer, and data layer. This chapter focuses on the protocol layer software such as Bitcoin, Ethereum, EOS, and Cordera. However, the software stack for blockchain systems which build on top of these protocol layers is very complex and varies based on the blockchain system. The protocol layers, such as Bitcoin and Ethereum, are sometimes referred to as ‘Layer 1’ or the ‘base layer’. Some blockchain systems also have ‘Layer 2’ software such as the ‘Lightening Network’ for Bitcoin. Blockchain systems also host application software, with smart contacts, tokens, and ‘DApps’, all of which are software.
SPDX and Software Bill of Materials ISO/IEC 5962L 2021

Abstract This chapter discusses the Software Package Data Exchange (‘SPDX’) specification. SPDX defines a common language for communicating the components, licenses, security information, and copyrights associated with software. The SPDX specification describes the necessary sections and fields to produce a valid SPDX document. This grass-roots effort has had participation over the years from a wide variety of software developers, systems and tool vendors, foundations, and the legal community — all committed to creating a common language for products, components, and software packages to be able to exchange Software Bill of Materials (‘SBOM’) data efficiently and effectively. By providing a common syntax and vocabulary for organisations and communities to share this software bill of materials data, compliance can be automated, and this improved transparency facilitates vulnerability identification and remediation.
Language Technology Tools and Services

At the time of writing, the European Language Grid includes more than 800 LT services of varied types, including machine translation (MT), automatic speech recognition (ASR), text-to-speech synthesis (TTS), and text analysis ranging from simple tokenisers and part-of-speech taggers through to complete named entity recognition and sentiment analysis systems. This chapter gives a high-level summary of the development of the ELG service catalogue over time and digs deeper to discuss the process of service integration by looking at a few example services.
Textual Paraphrase Dataset for Deep Language Modelling

Abstract The Turku Paraphrase Corpus is a dataset of over 100,000 Finnish paraphrase pairs. During the corpus creation, we strived to gather challenging paraphrase pairs, more suitable to test the capabilities of natural language understanding models. The paraphrases are both selected and classified manually, so as to minimise lexical overlap, and provide examples that are structurally and lexically different to the maximum extent. An important distinguishing feature of the corpus is that most of the paraphrase pairs are extracted and distributed in their native document context, rather than in isolation. The primary application for the dataset is the development and evaluation of deep language models, and representation learning in general.
Event Extraction for Military Target Motion in Open-source Military News

Open-source military news is the data source of open-source intelligence analysis, which can assist intelligence analysis by event extracting. Military events include the military target motion events which involve changes in multiple places. It is very important to infer the movement trajectory of a military target from the location-changing process of multiple place arguments. However, the traditional event extraction cannot reflect the location-changing process of multiple place arguments during the target moving. To solve this problem, this paper designs multiple place roles to learn location semantics relationship among place arguments for reflecting the location-changing process of multiple place arguments. We adopt the method of sequence labeling to convert military target moving event extraction into a multi-classification problem. This paper uses the pre-trained model Roberta for feature learning and a linear layer for a trigger word (or argument) classification. Since there is no standard military event dataset, this paper constructs an event dataset of military target moving. On this dataset, the F <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> of event extraction reaches 72.7%, which is a certain improvement compared with each benchmark model.
Investigation of an Influence of a Ratio,, Swarm Size - Iterations Number” on Particle Swarm Optimization Performance

Particle swarm optimization (PSO) performance is greatly influenced by the size of a swarm and the number of iterations. In order to define the reasonable ratio,, swarm size - iteration number” in PSO four well-known benchmark functions were used during poor calculation resources. Multiplication of swarm size and iterations number was used as the calculation resources indicator. It was found, that an application of the swarms, which include up to 50 particles, is reasonable for poor calculation resources.
A defense mechanism analysis for Dynamic Heterogeneous Redundancy

Dynamic Heterogeneous Redundancy (DHR) is a proactive defense architecture. A limited number of heterogeneous executors can be switched and combined, ensuring the security of systems. In this paper, we demonstrate the DHR architecture defense mechanism by the game theory. Combining incomplete information dynamic game with DHR, the attacker and the legitimate user are treated as the visitors and the defender as the server. Then, a DHR game model under incomplete information is proposed, which formally describes strategies and payoffs of all players in the game. Finally, Gimbit and NS2 simulation experiments verify the effectiveness and correctness of the game reasoning.
Omnichannel Architecture Enterprise Modeling on The Core Processes of the Culinary Industry using the TOGAF Architecture Development Method (ADM)

Omnichannel is a service method between the company and the customer that aims to increase the company's needs, customer satisfaction, and sales. Researchers use omnichannel enterprise architecture modeling to design the company's main business process requirements, so as to create conformity between the business being run and information technology. The Open Group Framework (TOGAF) is an architectural framework that provides methods and tools for developing data to help design enterprises. Implementing the TOGAF ADM Framework in omnichannel enterprise architecture is expected to improve work performance and results, especially regarding production and partnership services, through various information technology-based communication channels, so that the company's targets are achieved. The implemented methodology will produce a blueprint for designing an omnichannel enterprise architecture because it is more detailed in managing the balance between business and information technology. The blueprint for enterprise architecture design that has been verified by the user is expected to provide benefits as a proposal to evaluate the company.
A 40nm 5.6TOPS/W 239GOPS/mm<sup>2</sup> Self-Attention Processor with Sign Random Projection-based Approximation

Transformer architecture is one of the most remarkable recent breakthroughs in neural networks, achieving state-of-the-art (SOTA) performance on various natural language processing (NLP) and computer vision tasks. Self-attention is the key enabling operation for transformer-based models. However, its quadratic computational complexity to the sequence length makes this operation the major performance bottleneck for those models. Thus, we propose a novel self-attention accelerator that skips most of the computation by utilizing an approximate candidate selection algorithm. Implemented in a 40nm CMOS technology, our 5.64 mm2 chip operates at 100–600 MHz consuming 48.3-685 mW to achieve the energy and area efficiency of 0.354-5.61 TOPS/W and 239 GOPS/mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , respectively.
Text Encryption using Transform Dimension, Bit Plane Slicing, and Chaos System

This study proposes the chaos 2D encryption method for text which is widely used in digital images. For this method, two levels of dimensional transformation are carried out on text messages. The bit-plane slicing operation is performed to separate the entire bit-plane. There are seven bit-planes in plain text. Chaos encryption is performed on all bit-plane messages using different p, q values and iterations to increase security. The values of p, q and the number of iterations are derived from two keys that come from user input and plain text performed by the SHA-256 hash operation. Based on the testing results, the proposed method can improve encryption performance from statistical and differential control. The decryption process can also work perfectly, as evidenced by the value of BER and CER = 0.
Super Encryption Video Cryptography : Combination of Vigenere Cipher and Myszkowski Transposition

Cryptography is a method used to protect the confidentiality of data. In super encryption, two or more encryption algorithms are combined to make it more secure. In this work Vigenere Cipher and Myszkowsi Transposition are combined to form a super encryption. Vigenere cipher is a technique of encoding messages with Caesar cipher using the characters in the key used. The key used in this algorithm is a symmetric key and the characters in the key will be used repeatedly if all the characters in the message have not been processed while the Myszkowski Transposition is a type of cipher transposition algorithm that has its own uniqueness The specialty of this algorithm is that it has the need for keywords with identically numbered repeated letters. The key used in this algorithm is in the form of words or letters that are converted into a sequence of numbers. The alphabetical arrangement of the letters in the keyword determines the numbers. The first letter in the alphabetical order will be the number 1, the second letter in the alphabetical order will be 2, and so on. The super encryption is expected to be both easy-to-implement and more secure. The data integrity is still guaranteed because the two algorithms work together to secure the data and enable its return to plaintext.
An Improved Handwritten Javanese Script Recognition using Adaptive Threshold and Multi-Feature Extraction

Image quality greatly affects the object recognition process in the image. If the image quality is not good, the recognition process becomes more difficult. Preprocessing, feature extraction, and classifier are the most important parts of the object recognition process in the image. This process will determine object recognition accuracy, precision, and recall. The preprocessing section plays an important role in carrying out a kind of quality improvement so that objects can be easily identified before feature extraction is carried out. This study proposes using an adaptive thresholding method to enhance recognition accuracy in machine learning-based Javanese scripts. The use of adaptive thresholding is carried out in the image binarization process. By using adaptive thresholding, complement, median filter, and dilation operations can be performed to produce a more natural form and pattern of Javanese script writing. Thus, more accurate feature extraction is obtained. Classification is done with the KNN classifier. With a value of K=3, an increase in accuracy of 5% is obtained compared to the previous method.
A Mixed Reality Interface for Tactical Data Management in Geographic Information Systems

The requirements of security systems evolve as the complexity of risks and dangers increases in modern times. Due to the nature of security operations, the operator's stress and cognitive load increase, as the operators must strictly report events that occur in certain situations. In this paper, we present an alternative interface design for a command and control software traditionally used in regional security systems. We propose a mixed reality application that uses holograms and superimposition methods to enhance the operator's experience. The proposed interface is tested on four different security operation scenarios which are operational planning, unit tracking, surveillance, and alarm detection. According to the results of applied questionnaires such as NASA TLX, PSSUQ, and SUS, it has been observed that the created interface is more informative and more usable compared to the traditional command and control software in terms of security operations.