Reviewerly/exHarmony huggingface dataset:
The blockchain technologies in online social media: insights, technologies, and applications

Online social media (OSMs) have transformed the way of communication and have gained popularity in the life of users globally. Ever since their inception in 1996, OSMs have succeeded to infiltrate 4.48 billion people worldwide and there is an increased drift perennially highly influencing the privacy issues in OSMs. For example, the distribution of misleading information on OSMs as the platform is incapable to moderate the content successfully. It has been witnessed in recent times of the COVID-19 epidemic that OSNs have permitted individuals to spread fake news on diverse social media platforms. Even before the COVID-19 outbreak, OSMs were struggling to overcome issues such as censorship, privacy, and user control. To solve the significant issues in OSMs decentralization of social services is considered a potential solution and blockchain technology at present is the most prominent technique for decentralization of online social platforms. However, a dearth of studies extensively discussing the merits of blockchain technology for OSMs. This chapter presents an overview of concerns related to traditional OSMs and explores what happens when blockchain is incorporated in OSMs emphasizing the prominent services and features of a few trending OSM platforms based on blockchain technology.
Privacy provisioning on blockchain transactions of decentralized social media

Blockchain is one of the most disruptive and emerging technology in the present era, due to its unique characteristics immutability and decentralization. The transactions in a blockchain are publicly available, thereby accessible to all users. So, the privacy provisioning in blockchain for transactions of decentralized social media as well as privacy of the identities of members is needful. The chapter provides a comprehensive study of privacy provisioning on the blockchain. In the existing literature, there are a variety of scalability, security, and privacy concerns with blockchain, including key management for recovery, on-chain privacy protection, transaction linkability, and adherence to privacy laws. Following the self-sovereign identity (SSI) model, new privacy-preserving blockchain solutions are emerging to address these issues. These solutions allow users to anonymize themselves in all types of electronics transfer ledgers and regain control of their personal information. This chapter provides a comprehensive study of privacy provisioning schemes along with their challenges in this fascinating and disruptive technology.
5G multimedia communication and blockchain technology: emerging potential and challenges

The integration of Blockchain (BC) technology with 5G networks is newly emerging area. Driven by the dramatically increased capacity of 5G networks and recent breakthroughs in BC technology, 5G services are expected to contribute to rapid development and bring significant benefits to future society. Multimedia communication can potentially reach a wide range of areas and touch people&apos;s lives in profound and different ways. In recent years, great progress has been made in defining approaches, architectures, standards, and solutions. 5G applications have evolved significantly, including voice, video, wireless, information access, and social interaction networks. More interestingly, BC helps establish secure multimedia communication among users and potentially reduces communication latency, transaction costs, and provides global accessibility for all users. Today, social media is a platform for establishing connections, sharing content and social interaction of a huge number of users. Digital media has changed the way we connect and share our experiences. Multimedia content is a key ingredient of social media, and BC integration optimizes content management and immersive communication.Our aim in the chapter is to discuss the opportunities, challenges, and prospective solutions that BC-based 5G technologies are expected towards the 6G era. An overview of the BC technology in communication systems along with key features of multimedia communication is given. Several aspects of BC integration in 5G such as interoperability and standardization requirements, application and services, security and privacy, robustness and data integrity, resource allocation and management as well as energy efficiency, are analyzed. As concluding remarks, we identified some open issues and future research directions that should be considered in more innovative solutions and studies in this promising area.
Development of cloud automation evaluation system based on typical ADAS functions

Aiming at the deficiencies and deficiencies in the existing intelligent networked car event evaluation system, an innovative evaluation system based on cloud system automatic scoring is proposed. Conducting competitions through cloud servers is an effective way for international teams to participate in competitions and technical exchanges when international exchanges are affected by the epidemic. Taking typical ADAS functions as an example, the construction ideas, technical routes, program design, and achievement interface settings of the cloud automation evaluation system are researched and constructed. The effect of the cloud-based automated evaluation system for typical ADAS functions shows the convenience of cloud-based competition refereeing and the extensiveness of application-oriented objects.
Practical Applications of An Investor’s Guide to Crypto

In <ext-link><bold><italic>An Investor’s Guide to Crypto</italic></bold></ext-link>, from the November 2022 issue of <bold><italic>The Journal of Portfolio Management</italic></bold>, <bold>Campbell Harvey,</bold> of <bold>Duke University</bold>, and <bold>Tarek Abou Zeid</bold>, <bold>Teun Draaisma</bold>, <bold>Martin Luk</bold>, <bold>Henry Neville</bold>, <bold>Andre Rzym</bold>, and <bold>Otto Van Hemert</bold>, all of <bold>Man Group</bold>, offer several key insights about cryptocurrencies. First, they find that, although cryptocurrencies are notoriously volatile, the volatility is manageable. Second, they find that the correlations between cryptocurrencies and equities increase during equity market declines, thus reducing or eliminating perceived diversification benefits. Third, they explain that regulatory uncertainty and custody issues (relating primarily to cryptographic keys) create challenges for institutional crypto investors that individual investors do not face. In addition, the authors provide a summary of the various types of cryptocurrencies in the market and discuss the challenges of estimating cryptocurrency values on both absolute and relative bases.
Automatic Software Bug Prediction Using Adaptive Artificial Jelly Optimization With Long Short-Term Memory

Abstract In the software maintenance and development process, software bug detection is an essential problem because it is related to complete software success. It is recommended to begin anticipating defects at the early stages of creation rather than during the assessment process due to the high expense of fixing the found bugs. The early stage software bug detection is used to enhance software efficiency, reliability, and software quality. Nevertheless, creating a reliable bug-forecasting system is a difficult challenge. Therefore, in this paper, an efficient, software bug forecast is developed. The presented technique consists of three stages namely, pre-processing, feature selection, and bug prediction. At first, the input datasets are pre-processed to eliminate the identical data from the dataset. After the pre-processing, the important features are selected using an adaptive artificial jelly optimization algorithm (A 2 JO) to eliminate the possibility of overfitting and reduce the complexity. Finally, the selected features are given to the long short-term memory (LSTM) classifier to predict whether the given data is defective or non-defective. In this paper, investigations are shown on visibly obtainable bug prediction datasets namely, promise and NASA which is a repository for most open-source software. The efficiency of the presented approach is discussed based on various metrics namely, accuracy, F- measure, G-measure, and Matthews Correlation Coefficient (MCC). The experimental result shows our proposed method achieved the extreme accuracy of 93.41% for the Promise dataset and 92.8% for the NASA dataset.
We Need to Focus on How Our Data Is Used, Not Just How It Is Shared

Toward better understanding of the different ways data circulates between users and platforms.
1 Blockchain Technology for Library Services: Challenges and Opportunities for Libraries from a Nigerian Perspective

This chapter examines blockchain technology and the challenges and opportunities for its use in libraries. It reports on a study undertaken in federal uni­versity libraries in Southeastern Nigeria. The study sought to establish the level of awareness of blockchain technology in libraries, ascertain its relevance in library services and operations, and identify the challenges associated with its usage in libraries. A qualitative research design was adopted targeting academic librarians at the five federal university libraries in Southeastern Nigeria .The research find­ings revealed various potential uses of blockchain in the library including but not limited to building an enhanced metadata system, hosting peer-to-peer sharing, and serving as a Digital Rights Management (DRM) tool. The findings identified many challenges to implementation including lack of funding, irregular power supply, poor broadband connectivity, and a shortage of competent personnel. Strategies are proffered to ameliorate the challenges and to encourage libraries to adopt and use a remarkable new technology, blockchain.
Earthquake Epicenter Localization Using Fiber Optic Distributed Acoustic Sensing for Earthquake Early Warning Purposes

This paper presents an approach for locating an earthquake epicenter that is faster than what we showed earlier. The new method incorporates time difference of arrivals of P waves to locate earthquakes. It provides enhanced early warning possibility by faster localization using distributed acoustic sending.
Polynomial Graph Filter Design Using Legendre Polynomials

Polynomial graph filter (PGF) is an important tool for processing the irregular data captured from various complex networks, so the design of PGF is studied in this paper. First, Legendre polynomials are briefly reviewed and the basics of graph signal processing (GSP) are described. Second, the PGF design using Legendre polynomials is presented. The closed-form solution of filter coefficients is derived for lowpass, bandpass and highpass filters. Third, an efficient implementation structure of PGF based on recurrence relation of Legendre polynomials is investigated. Finally, the signal denoising application of sensor network data is demonstrated to show that the PGF method has better performance than the conventional smoothness-based method in term of the improvement of signal to noise ratio.
STANDARDIZATION IN COMBATING CYBERCRIME AREA

Cybercrime is an area where improving the effectiveness and interaction of law enforcementagencies is becoming increasingly important today. Standards, understood as technical documentscontaining rules, guidelines or definitions, can be used for this purpose. The article characterisesthe different standards and the standardisation organisations responsible for their development. Itthen presents the common standards operating in the field of cybercrime, in particular, those thatcan be implemented by any organisation that decides to take steps for a so-called 'incidentresponse'. Against this backdrop, a standard linked to the conduct of criminal investigations ischaracterised in more detail, which provides guidance for the handling of digital evidence and canbe used by police organisations to increase the effectiveness of their operations and improveinteroperability. Finally, the results of a study on priority standardisation domains in the area ofcybercrime were presented. These domains were developed based on standardisation proposalsmade by law enforcement representatives from European countries and then prioritised in terms ofimportance and urgency. The resulting recommendations should serve as a basis forstandardisation work in the near future.
Pemberdayaan Kelompok Guru Matematika Menerjemahkan Sumber Teks Penalaran Tingkat Tinggi Berbahasa Inggris dengan Google Translate Berbasis Android di Kabupaten Soppeng

English is the world's social language, but teachers still have limitations, especially in translating English texts. The purpose of the service is to provide counselling, training and then assistance for groups of teachers who are involved in the mathematics teacher consultations. The activity involved 28 mathematics teachers as delegates for each school or madrasa in Soppeng Regency. The activity was carried out on two days from 08.00 to 16.00 WITA. Each stage is carried out pre-test and post-test. Data analysis used percentages and paired t-tests with a significance level of 0.05. The results of the service show that 1) the participants' gestures before and after the activity have improved in a better direction, 2) the participants' understanding of translating text in the form of words, syllables, sentences and paragraphs has increased, 3) the skills of participants in translating English texts have increased by an average of 80%, 4 ) there was a significant difference in the improvement before and after counselling, training, and teacher assistance in translating high-level reasoning English text sources. Therefore, improving the ability and skills of translating English texts can use three stages, namely counselling, training and then assistance using text sources from international journals or international standard mathematics questions.
Initial Response

This chapter details the initial response to a serious incident. This starts the very first moment an initial call or report is received by a call handler regarding a crime or incident and continues with subsequent attendance and management of any crime scene(s) and investigation. Any investigation is given a significant boost if things are done properly by first responders who are in essence initial investigating officers (IIOs). As the Senior Investigating Officer (SIO) is rarely a first responder themselves, they need to check and review what important decisions have been/not been made, actions (not) taken, and information gathered. The chapter then looks at the ‘Golden Hour(s)’ principle and the Five Building Blocks principle. It also considers the process of report receiving and call handling, as well as the preservation of crime scenes.
Clustering IoT Data Using Machine Learning Methods: A Survey

Clustering is one of the important task of data mining. Clustering helps to discover patterns or groups from the data. The innovations in technology have led to the increase in data over the internet. The usage of various Internet of things (IoT) devices has increased and, the data is increasing continuously in large volumes. Big data handles such voluminous data with variety. Clustering using machine learning methods is done for large data analysis. This paper presents a survey of the various clustering algorithms based on machine learning methods for analyzingIoT data. The paper review various traditional clustering algorithms, modern-clustering algorithms, parallel clustering algorithms, applications that need assistance of clustering for managing IoT data. The paper also discusses the evaluation measure for performance assessment used for cluster analysis.
Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA

The extreme-scale computing landscape is increasingly dominated by GPU-accelerated systems. At the same time, in-situ workflows that employ memory-to-memory inter-application data exchanges have emerged as an effective approach for leveraging these extreme-scale systems. In the case of GPUs, GPUDirect RDMA enables third-party devices, such as network interface cards, to access GPU memory directly and has been adopted for intra-application communications across GPUs. In this paper, we present an interoperable framework for GPU-based in-situ workflows that optimizes data movement using GPUDirect RDMA. Specifically, we analyze the characteristics of the possible data movement pathways between GPUs from an in-situ workflow perspective, and design a strategy that maximizes throughput. Furthermore, we implement this approach as an extension of the DataSpaces data staging service, and experimentally evaluate its performance and scalability on a current leadership GPU cluster. The performance results show that the proposed design reduces data-movement time by up to 53% and 40% for the sender and receiver, respectively, and maintains excellent scalability for up to 256 GPUs.
ODIN: Overcoming Dynamic Interference in iNference Pipelines

As an increasing number of businesses becomes powered by machine-learning, inference becomes a core operation, with a growing trend to be offered as a service. In this context, the inference task must meet certain service-level objectives (SLOs), such as high throughput and low latency. However, these targets can be compromised by interference caused by long- or short-lived co-located tasks. Prior works focus on the generic problem of co-scheduling to mitigate the effect of interference on the performance-critical task. In this work, we focus on inference pipelines and propose ODIN, a technique to mitigate the effect of interference on the performance of the inference task, based on the online scheduling of the pipeline stages. Our technique detects interference online and automatically re-balances the pipeline stages to mitigate the performance degradation of the inference task. We demonstrate that ODIN successfully mitigates the effect of interference, sustaining the latency and throughput of CNN inference, and outperforms the least-loaded scheduling (LLS), a common technique for interference mitigation. Additionally, it is effective in maintaining service-level objectives for inference, and it is scalable to large network models executing on multiple processing elements.
A JavaScript Library for User Interface by Tapping Smartphone Bodies

We present a JavaScript library constructed in order for a web application on a smartphone to take actions in response to the user tapping the smartphone body in somewhere other than the display. The library offers six different events in total of tapping (1) top right, (2) bottom right, (3) top left, (4) bottom left corners of the smartphone in the portrait orientation, (5) top right, (6) top left corners in the landscape orientation. A machine learning algorithm is employed to detect and classify those six events according to signals from the six-axis accelerometer built in the smartphone. Adding event listeners that relate each event to its handler function, we can make a web application that reacts to the user events of tapping the smartphone body by hand.
An Early Warning System by PoseNet for Pedestrians

We propose an early warning system that alerts pedestrians when bicycle riders or other pedestrians are approaching from behind with their eyes looking aside or down. The designed prototype system is made up of (1) a 360-degree neckband camera for live video streaming the rear-view image of the user via his/her smartphone, (2) a server computer to capture the streamed video frames, (3) its image analysis software to detect persons looking aside or down in the frames with the help from PoseNet and YOLOv3, (4) another software to send an alert to the user’s smartphone via LINE Notify API, and (5) the user’s smartwatch paired to his/her smartphone to notify the user of the approaching dangers by vibration. The prototype system is tested to work with respect to its basic functions although it does not work in a practicable response time obviously because of the time delay in video streaming.
A Practical Algorithm for Max-Norm Optimal Binary Labeling of Graphs

This paper concerns the efficient implementation of a method for optimal binary labeling of graph vertices, originally proposed by Malmberg and Ciesielski (2020). This method finds, in quadratic time with respect to graph size, a labeling that globally minimizes an objective function based on the $$L_\infty $$ -norm. The method enables global optimization for a novel class of optimization problems, with high relevance in application areas such as image processing and computer vision. In the original formulation, the Malmberg-Ciesielski algorithm is unfortunately very computationally expensive, limiting its utility in practical applications. Here, we present a modified version of the algorithm that exploits redundancies in the original method to reduce computation time. While our proposed method has the same theoretical asymptotic time complexity, we demonstrate that is substantially more efficient in practice. Even for small problems, we observe a speedup of 4–5 orders of magnitude. This reduction in computation time makes the Malmberg-Ciesielski method a viable option for many practical applications.
Cyber-Crime and Computer Misuse

This chapter discusses cyber-crime, including cyber-enabled crime which does not require the use of a computer for their commission. It highlights the misuse of a computer hardware or software which involve one or more of four offences under ss 1, 2, 3 and 3ZA of the Computer Misuse Act 1990 (CMA 1990). It also looks at the unauthorised access to computer material that covers all forms of computer hacking, including hacking by someone who simply seeks access because of the challenge of breaking through a security system. The chapter reviews the unauthorized access to a program or data held in a computer by someone who is not entitled to control access or does not have consent to access. It emphasizes how a person with the authority to view data may still be considered unlawful if they access data with the intention of altering or copying it.
Identification Methods

This chapter discusses identification by witnesses who have seen a crime committed by a person that may feature in a video identification or identification parade. It cites Code D of the Police and Criminal Evidence Act (PACE) 1984, which is concerned with methods of identification, the keeping of records, and the taking of photographs of arrested people. It also looks at general principles that apply to all methods by which identification can be made. The chapter describes persons other than police officers that may be allowed to carry out procedures or tasks at the police station if the law allows. The chapter reviews the materials in Code D, which includes the identification of a suspect by an eyewitness. It covers recognition by controlled and uncontrolled showing of films, photographs, and other images.
Cybercrime

This chapter explains that the notion of cybercrime encompasses a wide range of criminal activity that involves some form of electronic or digital technology. It defines cybercrime as an umbrella term used to describe two distinct, but closely related criminal activities: cyber-dependent and cyber-enabled crimes. The five main ways that digital technology can impact crime range between being the target, aiding the crime, as a communication tool, being a witness, or acting as a storage medium. The chapter highlights the importance of a police officer recognizing new forms of crime in new environments and taking appropriate and timely actions. It notes that the international nature of evidence gathering is one of the main complications when dealing with cybercrime.