Reviewerly/exHarmony huggingface dataset:
Real-time research on functional distributed computer network interconnection

At present, functional distributed computer network interconnection is an important component of LAN applications. For example, regional power grid monitoring centers, aerospace survey ship center systems, and airport ground monitoring systems mostly use this model. It is conceptually different from the distributed computer system of the organization. Each connected computer is still autonomously operated, and it is only functionally distributed. Therefore, the traditional LAN interconnection method such as Ethernet is still adopted in the structure, which is different from the traditional one. In the local area network, the interconnected microcomputers generally have no affiliation and are functionally equivalent.
The Emergence of Interactivity Fields and What it Means for HCI Research

Interaction and interactivity is no longer necessarily something that takes place between a person and a single, clearly defined artifact and interface. A new kind of diffused or confused interaction has become an everyday experience for many of us and we are gradually getting more used to it. We will in this article argue that what we are experiencing reflects the first steps in a larger, coming change in the style and conception of interaction, interactivity, and interfaces. We conceptualize what emerges as interactivity fields. We believe interactivity fields are a new way of thinking about interaction that we will argue, has consequences for HCI research and interaction design practice. We explore the notion of an interactivity field, and what it would consist of in terms meaningful to interaction theory. We continue with a discussion about the impact of interactivity fields and how they may affect users and designers. Finally, we discuss what this emerging new reality may mean for HCI research.
Dense Compounded Features and Data Association Based Multiple People Tracking

People tracking is a wide area of research in computer vision and machine learning. The challenging problem of multiple objects tracking (MOT) is further complicated by factors such as occlusion, varying number of targets, illumination variations and objects' appearances which may be similar. In this paper, a significant approach is proposed for MOT with a single static camera based on dense valuable global and local features. This includes cascaded HOG-III features, texture, and motion information of objects in order to build a robust tracking system. To speed up the system, a simple data association method is employed using Hungarian algorithm to associate candidate response to the target objects. Genetic algorithm is also used to provide a heuristic data association based multiple objects tracking. A comparison between two association algorithms is made based on the tracking results. TUD-crossing and TUD-campus datasets are used for validation purposes. A system's performance can be evaluated using a wide metrics of MOT performance indicators (MOTA, MOTP). The results reach (82.89 and 81.96) in terms of TUD-crossing dataset and (79.30 and 73.06) in terms of TUD-campus dataset respectively. The experiments show that the proposed method can be suitably employed during scale changes or in the presence of a cluttered background environment, in addition, our method achieves competitive results in comparison with state of the art approaches.
VMPC (Variably Modified Permutation Composition) And Multi-Factor RSA In Text File Security

Conveying an information such as a text message file is often disturbed by a third party who wants to know the contents of the message or compose the contents of the message. To secure the message from unwanted parties, cryptography is used, which is a technique to encrypt a file into another form that is difficult to understand by parties that have nothing to do in the process of sending that information. Cryptography has several methods one of which is hybrid cryptography. Hybrid cryptography is a cryptographic method that uses symmetric algorithms to secure asymmetric files and algorithms used to secure keys from symmetric algorithms. This research uses Variably Modified Permutation and Composition algorithm which is a symmetric algorithm and RSA Multi-Factor algorithm (Rivest, Shamir Adleman) which is asymmetric algorithm. The text files tested in this study are extension * .doc, * .docx,* .txt, * .rtf. This research shows that by using hybrid cryptography algorithm Variably Modified Permutation and Composition and RSA Multi-Factor algorithm (Rivest, Shamir Adleman) can secure text file and key for data integrity. In 12 encryption experiments with ciphertext length of 8000 - 160000 the time increase has an average time of 4146 milisecond and in 12 decryption attempts with ciphertext length of 8000 - 160000 time increments have an average time of 5152 miliseconds. The time-consuming encryption and decryption algorithm of Variably Modified Permutation Composition and RSA Multi-Factor algorithm (Rivest, Shamir Adleman) is directly proportional. That is, the longer the character of a file, the greater the time required for the process of encryption and decryption.
Unmanned Aircraft for Transportation in Low-Level Altitudes: A Systems Perspective on Design and Operation

Using Unmanned Aircraft Systems (UAS) for transportation is an increasingly widespread concept. However, the majority of UAS only carry payloads of a few kilograms. This payload limitation will change in the future. New regulatory approaches facilitate the use of larger UAS with significantly increased payload capacities by incorporating the operational risks during certification. To assess the risk, the Specific Operations Risk Assessment (SORA) can be used, which defines a method that incorporates all safety affecting factors holistically. However, so far these factors ranging from automation or autonomy, aircraft configurations and design, airspace infrastructure and integration, certification and assurance, to the economics of potential use-cases have been studied in literature independently. The reason for this separation is the complexity of such holistic analysis of the aircraft system and operation. To overcome this complexity, this chapter identifies four segments of particularly strong interdependencies. This segmentation allows to map the air and ground risk classes of the SORA to the different system and operational components. At the same time, it supports balancing the level of autonomy with the reliability of required external services. Furthermore, it allows to study and adjust potential use-cases with the resulting system and operational requirements. The segmentation is discussed in detail based on the results of the research project Automated Low Altitude Air Delivery (ALAADy). The project conceptually studied transport UAS with payload capacities of up to one metric ton. Several technology demonstrations and flight experiments are included within this project. The following sections present a comprehensive view of the project’s results and conclude four years of research on unmanned aerial transport at the German Aerospace Center (DLR).
Metacognitive Strategies of Social Intelligence and Creativity Through Digital Communication Tools

Metacognitive skills help students better understand and master the subjects of study. The efficiency of metacognitive strategies depends on the nature of the task to be accomplished. Exploratory research at 5 Russian universities during the 2020–2021 academic year, under conditions of social isolation, showed preference for a visual expression of emotional support as evidence of social intelligence for routine tasks and exercises, and the predominance of articulation in verbalized form of ideas for creative and collective tasks. Focus-groups, discussions and observations of students’ group project defenses allowed researchers to draw conclusions regarding the impact of digital tools used for everyday communication respective to diversity perception and creative growth, digital tools contribute to the broader search for various sources of information, as well as leading to the interest to check, confirm or reject information found on the internet. The metacognitive strategies concern the generation of individual knowledge, but also the construction of social structures and relationships that are crucial for the motivation and efficiency of collective creative activities.
An Empirical Study on the Second Creation Defense in the Chinese Copyright Law

In the era of We Media, network communication is decentralized and arbitrarily enhanced, which brings challenges to network monitoring. In judicial practice, online works are frequently complained by the original copyright owners. Due to the game of interests, all parties still reached no consensus on the boundary of the second creation works. In this regard, it should not only discuss the extension of secondary creation from the Copyright Law itself, but also determine the scope of secondary creation as a reasonable defense from the judgment of judicial practice.
Interaction Design to Female Technological Collective Activism: Geek Girls Portugal Case Study

This work aims to reflect on the collective female activism in technology under the prism of human-computational interaction, the culture of participation and cyberfeminism from Geek Girls Portugal community (the first launched in the country) ethnographic case study. From the monitoring of the group’s digital platforms, information was collected to configure an organizational and communicational system, as well as allowing reflection on the autonomy of members’ decisions, using tools of non-discretionary use for the inclusion of women in technology in one of the domains in which patriarchy dominates. Conceptual paradoxes about the culture of participation and the emergence of digital platforms, from the launch of the Web in parallel to the beginning of cyberfeminism, will be presented. This article will also present preliminary results of doctoral research on how female technological communities play a catalytic role in the inclusion, education and activism of Brazilian and Portuguese women in technology.
GDPR Compliant Data Processing and Privacy Preserving Technologies: A Literature Review on Notable Horizon 2020 Projects

This paper presents a practical literature review focusing on privacy preserving technologies and organizational measures developed and proposed for GDPR-compliant data processing. Based on the selected Horizon 2020 projects, it identifies the substantial data processing and big data challenges relevant to data protection and privacy. Then, it visits the prominent privacy preserving technologies and organizational measures addressing these challenges. Finally, it analyzes the focus areas of the selected projects, identifies the solution they propose, draws quantitative conclusions, and asserts recommendations for future projects.
Where NeuroIS Helps to Understand Human Processing of Text: A Taxonomy for Research Questions Based on Textual Data

Several research questions from information systems (IS) are based on textual data, such as product reviews and fake news. In this paper, we investigate in which areas NeuroIS is best suited to better understand human processing of text and subsequent human behavior or decision making. To evaluate this question, we propose a taxonomy to distinguish these research questions depending on how users’ corresponding response is formed. We first review all publications about textual data in the IS basket journals from 2010–2020. Then, we distinguish text-based research questions along two dimensions, namely, if a user’s response is influenced by subjectivity and if additional information is required to make an objective assessment. We find that NeuroIS research on textual data is still in its infancy. Existing NeuroIS studies focus on texts, where users’ responses are subject to a higher need for additional data, which is not part of the text.
Research Skills Session 3: Finding Research Papers

Finding research papers (resources) within a specific research area can be done based on many aspects, such as keywords set, subject area, journal name, author profile, and dominant institution or country. The most important aspect, is the selected keywords set. Researchers are usually spending a long time on the net to find their interesting papers and keeping them. Reference management software offer an easy way of finding relevant literature, collecting references, organizing them in a database, and insert citations works in a manuscript with proper citation style. The workshop concentrates on how to find and keep the right papers for your research interest.
Multi-label Learning by Exploiting Imbalanced Label Correlations

Multi-label classification refers to the supervised learning problem where an instance may be associated with multiple labels. It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically assume that the distribution of classes is balanced. In many real-world applications, multi-label datasets with imbalanced class distributions occur frequently, which may make various multi-label learning methods ineffective. Since the existing multi-label learning algorithms pay less attention to the problem of correlation with imbalanced label sets, this paper proposed a Multi-Label learning model by exploiting Imbalanced Label Correlations (ML-ILC). ML-ILC uses graph convolution neural network to learn the correlation between labels. At the same time, we suggest that the regularization of minority classes is stronger than that of frequent classes, which can improve the generalization error of minority classes. To investigate the performance of the proposed multi-label learning model, we considered two benchmark datasets including VOC2007 and COCO. The proposed method successfully achieved better classification performance compared to the state-of-the-art compression methods.
Design and Implementation of a Control Interface for Indoor Position Detection of Moving Omnidirectional Access Point Robot Using Super Sonic Signals

Recently, various communication technologies have been developed in order to satisfy the requirements of many users. Especially, mobile communication technology continues to develop rapidly and Wireless Mesh Networks (WMNs) are attracting attention from many researchers in order to provide cost efficient broadband wireless connectivity. The main issue of WMNs is to improve network connectivity and stability in terms of user coverage. In our previous work, we presented a Moving Omnidirectional Access Point (MOAP) robot and implemented an indoor position detecting system using super sonic signals for MOAP Robot. In order to realize a moving Access Point (AP), the MOAP robot should move omnidirectional in 2 dimensional space. It is important that the MOAP robot moves to an accurate position in order to have a good connectivity. Thus, MOAP robot can provide good communication and stability for WMNs. In this paper, we design and implement a control interface for MOAP robot. The experimental results show that the implemented interface has a good accuracy for MOAP robot control.
Design of a Smart Community Inspection Robot

Aiming at the security requirements of smart community, an intelligent inspection robot was present in this paper. The environmental characteristics of the smart community were described in detail, and the characteristics of community inspection robot were summarized. According to the idea of modularization, the mechanical structure of the inspection robot was designed, which makes the inspection robot has the advantages of good off-road performance, strong climbing ability, and good ability of adapting to the complex terrain environment. The control system of this robot was designed based on the distributed structure design concept, the multi-sensor information acquisition system of this robot was constructed, and the motion control scheme of this robot was designed. Finally, the prototype of this inspection robot was designed, and the functional test and demonstration application were carried out in indoor and outdoor environment. The experimental results indicated that the proposed robot has a good motion performance, and meets the requirements of intelligent community inspection task.
WITHDRAWN: Integration of block chain technology in a healthcare sector

This article has been retracted at the request of the Publisher. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal
Computer Modeling in Musical Creative Work: An Interdisciplinary Research Example

Currently, when planning research, we can use the most active research approaches, such as experiment and modeling. Taking as an example a model of a musical fragment based on the statistics of notes, this article presents a sample of an interdisciplinary study. The idea of the study is to develop several equations that can quantify some of the verbal characteristics of a musical fragment. To prove the relevance of these equations, we found out the relationship between the parameters of the integral model and the values assigned by experts characterizing the psychological impression from music of a certain musical fragment. We used the group of 70 students as experts who evaluate the music fragments for several verbal values. Then we used several formulas on the model parameters (probability matrix determinants). Taking each pair of expert and calculated values we try to find the correlation. If the correlation is high for some pair of calculated data and expert data, we can use this equation to estimate the verbal characteristic of a musical fragment. As the result of this study we have proven formulas (on the music fragment probability matrix) that can evaluate some verbal characteristics of any music fragment. The development of musical computer technologies (MCTs) and digital musical instruments allows for appropriate experiments, also related to the field of music education. The results of modeling the process of musical creativity using MCTs are of particular importance for the implementation of various types of inclusive music education.
Arabic part-of-speech tagging using a combined rule-based and data-driven approach

Abstract This article presents a hybrid approach to part-of-speech tagging for undiacritized (or unvocalized) Arabic text which avoids the need for a large training set of manually tagged material. The approach is hybrid as it combines both rule-based and statistical (or data-driven) techniques. The key idea is that the training data are obtained by applying a rule-based tagger to a corpus of diacritized (or vocalized) text; a small subset of the output of the rule-based tagger is then hand-corrected, which is a much easier task than annotating it from scratch, and the results of this process are used as the training data for tagging undiacritized text. The advantage of this approach is that it requires very little manual effort. The only manual intervention is in the correction of the original training set. The accuracy obtained with this method is comparable to other state-of-the-art taggers for Arabic.
Measuring the Use of Mobile Applications in Higher Education

The proliferation of use of mobile applications has increased access to information and the way we communicate and collaborate. Higher education institutions must follow this trend and cannot ignore this. They should make efforts to integrate them in their routines, namely in their students. This chapter aims to extend the understanding about the actual use of mobile applications and how users report using them, namely in the classrooms. The main objective of this literature review is to conduct a critical literature review on this use. For this purpose, an analysis of several articles in reference publishers and journals was carried out. As a result of the analysis and cross-checking of literature data, it could be concluded that the use of mobile applications that users make and the one they claim to make may differ. It is intended to understand this problematic and analyse methods that may result in more precise data in this context. These data may be used, for example, to define strategies, namely helping higher institutions defining the use of m-learning.
Blockchain Security Framework for Government Private Blockchain Consortium

Blockchain is a revolutionary technology that allows data transactions to be made in a decentralized structure without having trusted central authorities. Governments have taken steps to unleash the potential of blockchain technology to explore the use of blockchain as critical infrastructure, create new business models, and transform government services and functions. Governments are exploring many blockchain use cases that require establishing a private blockchain consortium. However, the absence of a blockchain security control framework is a challenge faced by governments seeking to adopt best security practices for blockchain. In this chapter, we study the potential of cybersecurity threats associated with establishing and operating a private blockchain consortium for governments. Accordingly, a blockchain security control framework is proposed to guide the government entities to address the risks related to private blockchain consortium.
Quantifying the Particle Aspect of Quantum Systems

The possibility of a quantum system to exhibit properties that are akin to both the classically held notions of being a particle and a wave, is one of the most intriguing aspects of the quantum description of nature. These aspects have been instrumental in understanding paradigmatic natural phenomena as well as to provide nonclassical applications. A conceptual foundation for the wave nature of a quantum state has recently been presented, through the notion of quantum coherence. We introduce here a parallel notion for the particle nature of a quantum state of an arbitrary physical system. We provide elements of a resource theory of particleness, and give a quantification of the same. Finally, we provide evidence for a complementarity between the particleness thus introduced, and the coherence of an arbitrary quantum state.
Continual learning for scene classification of high resolution remote sensing images

Deep learning has achieved great success in optical image classification tasks including high resolution remote sensing image classification and segmentation. However, recent deep learning models usually use static training methods, therefore, long time and huge data are needed during training. The traditional end-to-end deep learning models are difficult to achieve incremental learning, which is learning new knowledge without forgetting learned knowledge. The continual learning was recently used to overcome this catastrophic forgetting problem. It is mainly on continual updating and optimizing the learning model to learn knowledge incrementally. In this paper, we proposed a continual learning model for the classification of high resolution remote sensing image scenes. It is a memory consolidation method using fixed representation. Fixed representation learning divides the network into three parts to be trained separately to adapt for continual learning scenarios, and the memory consolidation method solves the catastrophic forgetting problem through distillation loss, optimal sample replay, and classification layer correction. We compared the proposed method with the existing continual learning methods elastic weight consolidation (EWC), and learning without forgetting (LWF) methods, the experimental results show that the proposed method is effective for remote sensing scenarios classification, and has good performance on suppressing catastrophic forgetting. We also comprehensively analyzed the proposed method in multiple angles, and it is seen that there is still room for optimizing the proposed method in terms of model architecture, loss value, and training method.