Reviewerly/exHarmony huggingface dataset:
Islamic Banking Third-party Funds Grouping uses the Data Mining Clustering

Abstract Islamic banking as an intermediary institution (intermediary) between people with excess funds and people who lack funds has a very important influence on the Indonesian economy. In this study, the third-party funds discussed were third-party funds of Islamic banking. The purpose of this study is to analyze the grouping of Islamic banking third-party funds on Indonesia’s economic growth over the past 11 years, from 2009 to 2019 using the K-means algorithm. The data of this study uses time-series data from Islamic banking statistics, namely data on third-party funds for Islamic banking financing sourced from the official website of the Financial Services Authority. The findings of this analysis are in the context of a clustering of Islamic banking third-party funds containing 2 clusters: low (C1) and high (C2). The results obtained are there are 7 data with low clusters and 4 data with high clusters. The results of calculations carried out manually and testing using Rapid Miner, produce the same data grouping.
Soft Computing Technique for Block Chain Enabled Secure Healthcare System

Recent study shows that the integration of AI and Blockchain in the field of healthcare we can decrease many loopholes by integrating AI & Blockchain techniques. AI algorithms works better based on data input, which should be strong, deduce, and make final judgments. The machine learning algorithms work better when information is gathered from a data vault that is solid, secure, trusted, and tenable. On other hand Blockchain which is a scattered information system on which information are kept and transferred in a way that's cryptographically authenticated, certified, and acceptable by all mining nodes. The sensitive personal data of the patients are often securely stored within the Blockchain system which is stored with high reliable and tough, and can't be tampered with. When Smart Agreement are used for machine learning algorithms to form decisions and perform analytics, the result of those decisions are often trusted and undisputed. These blockchain secured dataset are used for the AI and ML algorithms. We use support vector machine algorithm as a Soft Computing Technique to demonstrate here. The main feature e of support vector machine algorithm is to find a hyper plane in an N-dimensional space (N - the number of features) that separates and categories the data points. Our objective is to find decision boundaries that classify maximum distance between data points of both the objects. We get better reinforcement by finding margins having more distance which also helps future data points that can be segregated with more confidence. The integration of AI and blockchain helps in creating strong and secure decentralized system for the real world application like healthcare system wherein AI-driven systems must collect, store, and utilize.
Fusing Temporally Distributed Multi-Modal Semantic Clues for Video Question Answering

Video Question Answering (VideoQA) is an intriguing topic, attracting increasing interest among the broad AI community. Yet videoQA is a difficult task. An algorithm competently tackle this task that needs to be able to: 1) extract rich semantics supplied in each modality of a video and incorporate them across modalities, and 2) identify and integrate such multimodal semantics from pertinent moments of a video, which may or may not be temporally adjacent or nearby, while filtering away irrelevant or even detractive portions of the video, to yield the most precise and sensible semantic context for executing the QA task. In response to the above requirements, a novel deep VideoQA solution is proposed in this paper, which comprises a multi-modal semantic clue extraction module, driven by a series of deep networks, each dedicated to digesting signals of a distinct modality type, to develop the first algorithmic QA capability, and a multi-modal temporal QA module empowered by a deep graph attention network to build the second algorithmic QA capability. Comprehensive experiments are conducted on publicly available benchmark data to validate advantages of the new solution in the end.
SPECIFIC FEATURES AND CLASSIFICATION OF DOCUMENTS AND INFORMATION RESOURCES

The purpose of the article is to clarify the specific features of documentary information resources determine the theoretical foundations of the process of their classification, development of classification models based on documentary and source methodology. Research methodology. Methods of historical document science, source studies, archival science were applied, which allowed establishing the attribute of the documentary information resource and its classification within the limits of document science theory. The scientific novelty of the work is to establish the specific features of documentary information resources, identify information characteristics, disclose internal and external features of documents, their further classification as a documentary source of information stored in archives, museums, and libraries. Conclusions. The study made it possible to generalize the theoretical knowledge of historical records management and source study about the specific features of the documentary-information resource and the process of their subsequent classification. Systematization and classification of documentary and information resources expand the possibilities of studying the theoretical foundations of a document, allows you to create a holistic comprehensive vision of the external and internal features of a document as an information resource and a means of communication from the point of view of theoretical and thematic-applied problems. Historical records management, archival studies, and source studies provide for the use of interdisciplinary methodological foundations of scientific research of documentary and information resources. The process of classifying documentary and informational resources of a specific problem-historical study includes the fact that they are an organic component of the informational past of Ukraine.Key words: classification, documentary information resource, document, historical document science, source science, archival science, social communication.
Motionsnap: A Motion Sensor-Based Approach for Automatic Capture and Editing of Photos and Videos on Smartphones

Taking photos and videos with smartphones has become part of our daily life. However, it is still challenging to capture a brief action at the right time (e.g. jump photos), and video editing (e.g. local slow motion) remains a manual, time-consuming task. To address this problem, we present a motion sensor-based approach that leverages the advanced technical features of modern smartphones to facilitate the capture and editing tasks. Concretely, we simultaneously record the motion sensor data from a smartphone carried by the object of interest, as well as a video from a remote smartphone cam-era. Taking advantage of the motion sensor data, our approach can automatically "snap" the video editing effect to the input video, i.e. apply the effect (e.g. local slow motion) at the right time. The proposed approach is shown to be effective in various applications. Moreover, we implemented it as an app for Android smartphones, running in a fully automatic manner.
Risk Classification Method of Vehicle Cyber Security Based on Hybrid Analysis

With the rapid development of the network technology of intelligent connected vehicles, the cyber security risk classification of vehicles will provide a good reference for the cyber security management of intelligent connected vehicles. This paper introduces the method of cyber security risk classification of automotive parts in the process of risk assessment. By using the hybrid analysis method of qualitative and quantitative, the cyber security related items of automotive are identified and the key feature information is extracted. At the same time, the risk level is calculated by using the quantitative evaluation method based on attack potential. In addition, the effectiveness of this method is verified by taking the vehicle information terminal T-Box as an example.
Block-based pseudo-relevance feedback for image retrieval

Pseudo-relevance feedback (PRF) is a relevance feedback (RF) technique for information retrieval that treats the top k retrieved images as relevance feedback. PRF is used to avoid the limitations of the traditional RF approach, which is a human-in-the-loop process. Although the pseudo-relevance feedback set contains noise, PRF can perform retrieval reasonably effectively. For implementing PRF, the Rocchio algorithm has been considered reasonably effective and is a well-established baseline method. However, it simply treats all of the top k feedback images as being equally similar to the query. Therefore, we present a block-based PRF approach for improving image retrieval performance. In this approach, images in the positive and negative feedback sets are further divided into predefined blocks, each of which contains one to several images, and blocks containing higher- or lower-ranked images will be assigned higher or lower weights, respectively. Experiments using the NUS-WIDE-LITE and Caltech 256 datasets and two different feature representations consistently show that the proposed approach using 30 blocks outperforms the baseline PRF in terms of P@10, P@20, and P@50. Furthermore, we show that a system that incorporates the user’s feedback allows the 30-block-based PRF approach to perform even better.
An Exact Solution for a Class of Kalman Smoothers

Choosing the correct interval length for a fixed interval smoother is not obvious. To address this problem, this chapter develops an exact solution to the finite difference equations corresponding to a class of Kalman smoothers. Specifically, the fixed interval smoothers that result from linear, Gaussian discretized continuous-time kinematic models with one-dimensional measurements and one- and two-dimensional state vectors. The solution decay for a single nonzero measurement at or near the center of the smoothing interval gives a clear indication of the required interval length for different choices of the measurement noise variance and process noise power spectral density. The solutions are parameterized by the tracking index to simplify the analysis and make the results more useful.
Performing the cyborg self: explicit and implicit examples of body hacking the distributed self

Today, as many work and socialize completely online, we are more acutely aware than ever of the cybernetic relationship between the body (in-situ) and the virtually or digitally extended self. However, even before the onset of the current global pandemic (COVID-19), the contemporary ‘body’ had to be understood as extended beyond physical flesh, through global communications systems. How do our practices on these platforms reveal our evolving relationships with a distributed and digitally mutable body? Drawing on my own construction of cyborg theory as a subset of posthuman discourse, this paper links the practices of explicitly cyborg performance, like Stelarc and ORLAN, with the increasingly banal practice of body-hacking as it is realized in the performance of the self (both consciously and unconsciously) on distributed, social media platforms. These discussions touch both on identified trends in contemporary self-representation as well as artists whose work within those spaces acts as a comment, critique, and application of those practices. Through this discussion, I show how these practices can be understood as body hacking and how that body hacking can both reflect an increasing sense of personal empowerment in relation to the body as well as a morally ambiguous algorithmic redefinition of the paradigmatic body.
Edge Technology Enabled IOT Blockchain-Based Health Monitoring for Chronically Sick Patients

The Internet of things is a trending technology that is integrated with diverse real-time applications to form a interdisciplinary research outcomes. Internet of things can be implemented in all the real-time business and commercial market to attract the customers and to evolve itself as the future of Internet. Similar to Internet of things, blockchain is also emerging field that can be integrated to provide openness and security to each sensors in the applications. Monitoring and servicing the sensors that are connected in IoT framework still remain unsolved problem. With this background, this paper attempts to integrate Internet of things and blockchain together in designing the proposed framework for IoT blockchain-based health monitoring system. Illegal users are not allowed to perform any fault transaction inside the blockchain network with its ability to involve in smart contract and consensus, thereby increasing the security between the doctors and the chronically ill patients. This system is designed by keeping immovable aged patients in mind who are affected by chronical diseases which need on time treatment and continuous observation by the doctor. The proof of concept for the proposed IoT blockchain-based health monitoring system with Ethereum private blockchain network under a genesis block is designed in this paper to analyze the performance.
QUIET: Quatro-Inverse Exponential Cipher Technique

Majority of the available traditional symmetric key cipher techniques rely on a single key encoding scheme to secure the data before transmitting it over insecure channel. Here, in this chapter a new symmetric shared key cipher technique “QUIET: Quatro-Inverse Exponential Cipher Technique” has been proposed. The technique makes use of multiple keys such as User’s Personal keys, his geographical location along with dynamic session key (256 bit to 512 bit), all of which play a very significant role in the process of hiding user’s critical information before transmitting it on the network. The newly introduced cryptographic technique is symmetric key technique that deals with encrypting and decrypting the text message by using a set of four keys blended with a set of mathematical operations on those keys. The simulation of the proposed QUIET, Quatro-Inverse Exponential Cipher Technique, was successfully performed in Java programming language and the results, when compared with Triplicative Cipher technique, have been positive and encouraging.
Virtual exhibition as a means of implementing cultural function of the library

This article examines the transformation of cultural function of the libraries of pedagogical universities, considering challenges and changes in the digital educational environment. Leaning on the modern scientific research on creation and content arrangement of web resources, the author analyzes the libraries of 37 pedagogical universities nationwide, as well as interrelation between cultural function and thematic headings. The object of this research is the description of peculiarities of implementing cultural function of the library in the common information space of an educational institution. The subject of this research is the virtual book exhibitions as an instrument of promoting publishing projects and a synthesis of traditional and innovative ways of conveying information to the readers. The main conclusions are as follows: in implementation of cultural function, the university library pursues the goal development of spiritual and moral personality traits. The libraries make a considerable contribution to the becoming and socialization of an individual by preserving and augmenting cultural wealth of literary sources. The implementation of cultural function should take into account the abundance and availability of information in modern world. The stylistics of messages and sources does not always correspond to generally accepted norms and morals. The libraries also aim to draw interest to cultural environment and develop the in skills of working with literary sources among the readers, as well as form a deliberate cultural assessment of the surrounding reality.
Fine Tuning BERT for Unethical Behavior Classification

Social media allows people to express themselves, however, there exists a threat of abuse and harassment. This threat leads to a negative impact on society which results in a change in people behaviour and they stop expressing their ideas freely. Classification of unethical behaviour in comments is a multi-label classification task. Due to the limited availability of the dataset, training does not yield worthy accuracies. Hence, a large training corpus is needed. This work, therefore, proposes to supplement training data by making use of transfer learning. Bi-directional Encoder Representations from Transformers (BERT) pre-trained model is fine-tuned to detect unethical users' behaviour. The approach used in this work achieved competitive accuracy for the task of multi-label classification on the toxicity dataset of Wikipedia Comments Corpus.
Precognition of Content by Interpreting Human Language Into Computer Automated Data Processing

Text has become a major part of our life. We use text as way to communicate and express ourselves in this sophisticated world. Since we are predicting the next probable we will be using text as input data for our algorithm. Predictive typing is basically predicting the most probable word following the given set of words or a particular word. In this contemporary world where mobile devices and computers dominate communication, like emails, social media and even blogs and newsletters, we require a method for speeding up the responding process to keep ourselves with the fast-paced world. Predictive typing is a widely used procedure for faster and eloquent communication but the robustness and scalability along with the speed is always a concern. The main aim of our algorithm is to develop a next word predictor that helps to significantly reduce the number of key-strokes by the user along with accuracy. This predictive typing algorithm’s core is based on the N-grams model.
The application and research of multimedia technology in music Solfeggio teaching strategy

At present, with the rapid development of multimedia technology and gradually inseparable from our life, many scholars in China have applied the multimedia operating system to the training of practical talents. With the continuous progress of science, in the course of music teaching in most colleges and universities in China, this training mechanism shows a very active gesture and its influence on the education level of Chinese students has gradually entered the field of vision of all walks of life. The further promotion of this education and training mode has led to the rapid growth of computer media teaching process, which has formed a vast educational park for talents in this field. This paper takes music Solfeggio teaching as the research object, compares and analyzes the advantages and disadvantages of traditional teaching and multimedia technology in music Solfeggio teaching, and points out the necessity of multimedia teaching in music Solfeggio teaching, and expounds the significance of introducing the multimedia teaching in the music education, and tries to put forward some feasible suggestions for the realization of the multimedia music teaching in the future.
Polynomial versus Exponential Time

In this chapter we explain how to analyze the time an algorithm takes to solve a given problem and specifically whether it takes polynomial or exponential time. We consider a variety of well-known problems from computer science to illustrate polynomial-time versus exponential-time algorithms. In these analyses, we build on a common distinction between three types of problems: optimization problems, search problems, and decision problems. While the first two are most commonly adopted in cognitive science, the last one is widely used for computational complexity analyses. As we will explain in subsequent chapters, the distinction is overcome during complexity analyses by understanding the close relationship between these problem types. We will also see that while it is possible to "prove by example" that a problem is of polynomial-time complexity (viz., give an algorithm that solves the problem that runs in polynomial time) proving that a problem does not allow for any such polynomial-time algorithm requires different proof methods.
Literature Study: Utilization of Android-Based Learning Media Using Adobe Flash CS 6 (As An Educational Solution During The Covid-19 Pandemic)

Abstract This literature study aims to determine the use of Android -Based Learning Media as a solution during the Covid-19 pandemic in Indonesia. The data used is secondary data using the literature method, namely by studying and reading literature related to the problems that are the object of research, such as books, articles, journals, surveys, news and other documents. The results of the study reveal that the number of Android users in Indonesia is quite high and increasing every year, such as in 2015-2018 an increase of 27%, so it will be effective if used as a learning medium. In addition, this pandemic condition causes the need for the use of Android -based Learning Media to be quite significant. In contrast to the ability of educators in mastery of technology, there are only 40% of educators who are ready for technology because for media creation at this time sufficient technological capabilities are needed, so the use of Android -Based Learning Media is quite low, especially those using Android applications based on Adobe Flash CS6 . Where it is necessary to have regular training so that the competence of Educators is in accordance with the demands and conditions of the times. Especially with the current condition of the Covid-19 Pandemic, the ability of teachers in technology is needed to support the learning process. so that the use of Android -Based Learning Media is quite low, especially those that use Android applications based on Adobe Flash CS6 . Where it is necessary to have regular training so that the competence of Educators is in accordance with the demands and conditions of the times. Especially with the current condition of the Covid-19 Pandemic, the ability of teachers in technology is needed to support the learning process. so that the use of Android -Based Learning Media is quite low, especially those that use Android applications based on Adobe Flash CS6 . Where it is necessary to have regular training so that the competence of Educators is in accordance with the demands and conditions of the times. Especially with the current condition of the Covid-19 Pandemic, the ability of teachers in technology is needed to support the learning process.
Artifact Description/Artifact Evaluation

Several systems research conferences now incorporate an artifact description and artifact evaluation (AD/AE) process as part of the paper submission. Authors of accepted papers optionally submit a plethora of artifacts: documentation, links, tools, code, data, and scripts for independent validation of the claims in their paper. An artifact evaluation committee (AEC) evaluates the artifacts and stamps papers with accepted artifacts, which then receive publisher badges. Does this AD/AE process serve authors and reviewers? Is it scalable for large conferences such as SCxy? Using the last three SCxy Reproducibility Initiatives as the basis, this talk will analyze the benefits and the miseries of the AD/AE process. Several systems research conferences now incorporate an artifact description and artifact evaluation (AD/AE) process as part of the paper submission. Authors of accepted papers optionally submit a plethora of artifacts: documentation, links, tools, code, data, and scripts for independent validation of the claims in their paper. An artifact evaluation committee (AEC) evaluates the artifacts and stamps papers with accepted artifacts, which then receive publisher badges. Does this AD/AE process serve authors and reviewers? Is it scalable for large conferences such as SCxy? Using the last three SCxy Reproducibility Initiatives as the basis, this talk will analyze the benefits and the miseries of the AD/AE process.