Reviewerly/exHarmony huggingface dataset:
Assessing the Social Agency of Pedagogical Agents in Adaptive Training Systems

Pedagogical agents (PAs) could be used to mimic a one-on-one human tutoring experience in adaptive training systems. Social agency theory (SAT) is one perspective that describes how humans learn from PAs. However, there are no measures to test the components of SAT and their effects on learning. Therefore, we discuss the development of a subjective measure, the Social Agency Theory Questionnaire (SATQ), to assess components of the social agency theory framework: social cues, the cooperation principle, and deep cognitive processing. Next, we present a study that investigates the effectiveness of a PA instructor who provides error-sensitive human-voiced feedback to learners in an adaptive training system (PA-Present group), compared against an instructionally equivalent text-based instructor system (PA-Absent group). We hypothesize that the PA-Present group will exhibit higher learning outcomes than the PA-Absent group. Additionally, we hypothesize that participants in the PA-Present group will rate the "instructor" higher on all three subscales of the SATQ than participants in the PA-Absent group. Data collection for this project is currently underway. Future analyses will examine between-group differences on performance and learning outcomes, and their association with subjective ratings on SATQ subscales. In addition, we will present psychometric analyses of the SATQ and proposed revisions to the scale.
Smart Pedagogy: Concepts, Components, Outcomes

Smart pedagogy is a set of innovative teaching strategies, methods and practices to provide smart features - adaptation, sensing, inferring, self-learning, anticipation and self-optimization - for educational processes, objects, and environment. This paper presents the outcomes of long-term project at the Department of Computer Science and Information Systems and the InterLabs Research Institute at Bradley University (IL, USA) to develop, implement, test and refine various innovative teaching strategies as components of smart pedagogy for Science, Technology, Engineering and Mathematics (STEM) courses. The ultimate goal of smart pedagogy is two-fold: a) increase student interest in learning activities and overall satisfaction of learning process, and b) maximize the effectiveness of teaching and quality of learning outcomes in STEM courses. A set of implemented and thoroughly tested innovative teaching strategies include 1) Learning-by-Doing, 2) Crowdsourcing, 3) Smart Learning Analytics, 4) Flipped Classroom, 5) Collaborative Learning, and 6) Gamification/Badging based approaches. The obtained student feedback about implemented innovative teaching strategies undoubtedly demonstrate students’ keen interest in active use of smart pedagogy in STEM courses.
Tibetan Literature Recommendation Based on Vague Similarity of Cited Number and Downloads

In scientific research, it is very important to quickly and accurately retrieve relevant important documents. This paper sorts the keywords according to their importance and calculates the fuzzy membership degree of keywords; The literatures with the same keywords enter the recommendation set, and two kinds of experiments are carried out on the literatures entering the recommendation set: one is to use vague similarity technology to recommend documents according to keywords; Second, on the basis of the first experiment, vague similarity technology is used to fuse the cited numbers and downloads for literature recommendation. Experiments show that the recommendation algorithm proposed in this paper is reasonable and effective, and can give a reasonable ranking, which meets the needs of researchers to retrieve literatures.
Customer-Product Matches in Online Social Referrals: A Graph Embedding Approach

New social media has been enlarging the impact of social referrals on product diffusion. There is, however, no direct evidence on how effectively referrers match products with referred customers that, in turn, leads to high returns for online social referrals. To answer this question, we analyzed 137,622 referrals of 20,169 instant apps from 11,668 referrers to 84,166 recipients (those referred), and 1,141,363 (100 per referrer) unique contacts randomly selected from referrers' local social networks excluding the recipients. We leveraged a state-of-the-art graph embedding framework to estimate users' latent preferences for the apps based on a massive amount of user-app historical usage sequences. We find that referrers recommend products to contacts with substantially stronger preferences for the referred products than the non-referred contacts have. Referrers' contacts have significantly greater preferences for the referred products than do their non-contacts. These results confirm the effectiveness of active (actively screening and selecting contacts to match products) and passive (homophily-based) matching in online social referrals. We also find that referrers exhibit the strongest preferences for the referred products. The matching outperforms among narrow-appeal products and for more engaged referrers and those with a smaller local social network. Our findings shed light on the mechanisms and management of social referrals.
Investigating STEM Students’ First-Time Experience with Smart Glasses

We study how STEM students experience the use of smart glasses for the first time. We evaluate the glasses’ usability, degree of technological acceptance, experience, and elicited emotional response. To this end, we resort to several quantitative instruments and semi-structured interviews. We found that students greatly appreciate the potential and current support that smart glasses and AR provide as educational tools. We discuss our findings and identify opportunities for further research with these devices to support educational activities.
Argumentation Structures and Operations

This chapter and the following two deal with argumentative operations that weave together arguments to produce complex arguments. An argumentative operation is a process by which two or more arguments are integrated into a single, more complex, argument. Many argumentative connectors are commonly used as signs of argumentative operations. An argumentative operation yields an argumentative structure: the arrangement of parts in an argument, either simple or complex. Thus, e.g. the operation of concatenation yields a subordinative argument. The successive interventions of the participants in an argumentative exchange can be seen as applications of these operations, by means of which participants interactively weave a macro-argument in the course of an argumentative exchange.
Deep Learning Based Residual Network Features for Telugu Printed Character Recognition

In India, Telugu is one of the official languages and it is a native language in the Andhra Pradesh and Telangana states. Although research on Telugu optical character recognition (OCR) began in the early 1970s, it is still necessary to develop effective printed character recognition for the Telugu language. OCR is a technique that aids machines in identifying text. The main intention in the classifier design of the OCR systems is supervised learning where the training process takes place on the labeled dataset with numerous characters. The existing OCR makes use of patterns and correlations to differentiate words from other components. The development of deep learning (DL) techniques is useful for effective printed character recognition. In this context, this paper introduces a novel DL based residual network model for printed Telugu character recognition (DLRN-TCR). The presented model involves four processes such as preprocessing, feature extraction, classification, and parameter tuning. Primarily, the images of various sizes are normalized to 64x64 by the use of the bilinear interpolation technique and scaled to the 0, 1 range. Next, residual network-152 (ResNet 152) model-based feature extraction and then Gaussian native Bayes (GNB) based classification process is performed. The performance of the proposed model has been validated against a benchmark Telugu dataset. The experimental outcome stated the superiority of the proposed model over the state of art methods with a superior accuracy of 98.12%.
Usm-Unet:U-Net and Unsharp Masking Based Underwater Image Restoration Algorithm

Due to the existence of a large number of underwater media that can absorb light, the propagation of light underwater will experience varying degrees of attenuation. Therefore, underwater images usually have problems such as blue color, low contrast, and blurred details. There are many algorithms to solve these problems. However, the existing algorithms often solve the color deviation and low contrast of underwater images, while losing the details of the image. In this paper, we propose an USM-Unet algorithm that can not only solve color deviation and contrast but also preserve image details. For the USM-Unet, the residual block and attention mechanism are introduced into the encoding and decoding block of U-Net to improve the network, and the improved U-Net is trained on the EUVP dataset used for color recovery. The improved U-Net can avoid the gradient disappearance by using the residual block. Moreover, we use noise reduction before sharpening to improve unsharp masking algorithm. The improved unsharp masking algorithm is used to enhance the image, and the details of the image are increased without expanding the noise. The experimental results show that the proposed algorithm has remarkable restoration effect on underwater image restoration by comparing with the classical algorithms.
A Blockchained Secure and Integrity-Preserved Architecture for Military Logistics Operations

The employment of 5G Internet of Things (5G-IoT), smart automation, and AI analytics can provide improved military logistics, by enhancing inventory control, reordering, accuracy, flexibility mobility, and real-time monitoring, from the factory and warehouses to the battlefield. On the other hand, there are inherent risks that include cybersecurity issues, such as authentication, integrity, privacy, and confidentiality of the communicated data. Moreover, there are concerns relevant to prioritization, scalability, resilience, and continuous availability of the military supply chain operations. This paper introduces the development of a holistic blockchain integrity-focused scalable architecture, based on two main principles: the data is not stored in a central point and therefore make it vulnerable to attack and sensitive data is not transmitted through open communication channels. Fully homomorphic encryption is used to perform calculations and analysis. Remote independent observers who are eligible to have information access or to search for specific content with visual output, cannot determine the source of the information. The proposed architecture is based on the Hyperledger Fabric Project which provides the foundation for developing modular applications or solutions, allowing plug-and-play components, such as consensus and membership services. Its modular and versatile design satisfies a broad range of military operations. Besides, it offers a unique consensus approach that enables scalable performance, while preserving integrity and security. The significance of the proposed architecture is highlighted, by demonstrating its employment in the ammunition supply chain (from production to remote mobile ammunition consumers). Finally, the paper discusses the utilization of the architecture to other domains of military operations, beyond logistics such as C2 systems.
Simple Dependent Types for OSTRICH

The demand to develop more applications and in a faster way has been increasing over the years. Even non-experienced developers are jumping into the market thanks to low-code development platforms such as OutSystems. OSTRICH, a type-safe rich template language for the OutSystems platform, allows for the definition and instantiation of type-safe templates while ensuring a clear separation between compile-time and runtime computations. We formalise this two-stage language and introduce new features to the OSTRICH language, namely parametric polymorphism and a simplified form of dependent types. Such features enable instantiating the most commonly used OutSystems templates, reducing the knowledge required by the developer and easing the development process.
State estimation and sensor fusion

In autonomous vehicle (robot) systems, Bayesian filters such as the Kalman filter have a wide range of applications. They are not limited to the state estimation of targets as they also have very wide applications in multisensor fusion, localization, simultaneous localization, and mapping, and so on. The mastery and skillful use of Kalman filter algorithms in the engineering applications of autonomous systems are thus important. To ensure good state estimation, we focus on the Kalman filter algorithm, discuss the extended Kalman filter for dealing with nonlinear systems, and finally evaluate the unscented Kalman filter.
New Representative Collective Signatures Based on the Discrete Logarithm Problem

The representative collective digital signature scheme allows the creation of a unique collective signature on document M that represents an entire signing community consisting of many individual signers and many different signing groups, each signing group is represented by a group leader. On document M, a collective signature can be created using the representative digital signature scheme that represents an entire community consisting of individual signers and signing groups, each of which is represented by a group leader. The characteristic of this type of letter is that it consists of three elements (U, E, S), one of which (U) is used to store the information of all the signers who participated in the formation of the collective signature on document M. While storing this information is necessary to identify the signer and resolve disputes later, it greatly increases the size of signatures. This is considered a limitation of the collective signature representing 3 elements. In this paper, we propose and build a new type of collective signature, a collective signature representing 2 elements (E, S). In this case, the signature has been reduced in size, but it contains all the information needed to identify the signer and resolve disputes if necessary. To construct the approved group signature scheme, which is the basic scheme for the proposed representative collective signature schemes, we use the discrete logarithm problem on the prime finite field. At the end of this paper, we present the security analysis of the AGDS scheme and a performance evaluation of the proposed collective signature schemes.
Managing Uncertainty and Complexity: Emerging Challenges in Cyber Security

Uncertainty and complexity are two key issues to understand and explore in the current digital context. The management of these two issues becomes relevant for cyber security as the increase in connectivity and convergence of technologies creates not only opportunities for organizations and nations, but also spaces of instability and disruption that must be identified, anticipated and addressed. Therefore, this paper presents some concrete proposals to manage uncertainty and complexity in order to break the status quo of certainties and assume instability and volatility as natural sources in strategic and tactical decision making for both security/cyber security professionals and executives of companies and nations.
Virtual Equipment System: Toward Bag of Holding and Other Extradimensional Storage in Extended Reality

The term ‘storage’ in real life typically refers to a container that occupies physical space, such as rooms, closets, warehouses, etc. Our interactions with items stored within are constrained by physics in real life. However, Virtual Reality allows us to ignore certain rules. Inspired by a Bag of Holding from Dungeons & Dragons and other entertainment media, we envision a storage which can store more items than the physical space the container occupies by linking it to another dimension. Users can interact with the stored item as they would with containers in VR or physically enter the storage. We refer to this approach as ‘Extradimensional Storage’. During our design and implementation of Extradimensional Storage, we identified five core components of a generic storage system, which are storage space, container, access, stored items and interactor. By altering the properties associated with the core components, we are able to implement Extradimensional Storage. We further applied the five core components to reinterpret the inventory taxonomy proposed by Cmentowski et al. Thus, our contributions include a general framework for storage, an implementation of a specialized version known as Extradimensional Storage, additions to the inventory taxonomy, and how properties of the core storage components can be utilized for different scenarios.
Outlook on the Future Regulatory Requirements for AI in Europe

This report was drafted as part of the research project ‘fAIr by design – solutions for discrimination reduction in AI development’. The aim of the project is to develop models and strategies to mitigate discrimination risks in the development phase of AI systems. The large-scale use of AI systems in everyday situations carries with it the risk that certain individuals or groups will suffer harm or may be disadvantaged by an algorithmic decision. If such risks are to be addressed and ultimately avoided as early as during the product development phase, it is essential to clarify how they are to be classified in legal terms. Therefore, the report first assesses the concepts of fairness, bias and discrimination and illustrates the differences between these terms. In a next step, the existing legal framework is examined with regard to regulations that are already relevant for AI. Building on this analysis, special consideration is given to the Proposal of the European Commission on Artificial Intelligence (AI Act Proposal), which is set to play a fundamental role for the future regulation of AI. The second part of the report comprises a summary of expert interviews with representatives from law, ethics and AI research, as well as standardisation organisations.
Toolkit Carrying Drone For Maintenance Of High Altitude Transmission Lines

Research and analysis on drones is increasing rapidly nowadays in various fields of application. One of the major problem which arises in the drone application is its ability of lifting heavy loads when attached to it that requires proper design and selection of the required type of drone for its ability to carry out various missions including lifting a heavy load. One of the important type of drone that is widely used is hexacopter drone. This paper shows the design of hexacopter drone that lifts the toolkit which has to be delivered for maintenance of transmission lines at high altitude. It is designed with the help of calculation and analysis of the criteria and constraints by the aid of software. The calculations shows the ability of hexacopter drone of lifting a toolkit and delivering it to the location at higher altitude.
Application of BLOCKCHAIN in Agriculture: An Instance of Secure Financial Service in Farming

In the just gone study, it has been observed that numerous incidents associated with farmer suicides on account of bankrupt and underperforming agriculture. The worlwide population is increasing rapidly and hence the dependence of land to build housing as well as industrial areas is also demanding more in the same propotion. The productive lands for agriculture are declining and more returns must be produced for meeting the country’s needs. Although demand increases, farmers suffer from some important problems such as an increase in initial investment to establish the soild ground because of high rate of interest, the actual price of the crops as the mediation of intermediaries in the market and surveying bazaar bias as well as need of the buyer. Novelties of this article are to resolve these issues by the proposed block-chain architecture. In this architecture, the farmer and the banker are entirely keep apart by the intermediaries. The moderness of the article is to implement blockchain technology, security issues, and digital consciousness in Agriculture Farming. The objective is to provide the sustainable utility of this technology in financing.
Combining Virtual Reality and Eye Tracking to Recognize Users’ Aesthetic Preference for Product Modeling

As one of the unique cultural products and representative symbols of China, Yixing teapots have a unique aesthetic connotation. The cultural and creative products of Yixing teapot have played a positive role in the inheritance of intangible cultural heritage, however, they still face higher requirements in terms of design innovation and adaptation to users’ aesthetic needs. Although several methods of evaluating and measuring user experience have been established, such as subjective reporting and questionnaire surveys, designers still need objective methods to evaluate users’ perception and response for Yixing teapots modeling. This paper aims to combine virtual reality and eye tracking technology to recognize users’ aesthetic preference for the 3D modeling of Yixing teapots. Eye tracking signals were recorded in a preference categorization task, and users’ aesthetic preference was analyzed via eye tracking data and users’ subjective evaluation. The results showed that the fixation count and time of first fixation in different AOIs had significant effects on users’ subjective evaluation. The study provides an objective method in recognizing users’ aesthetic preference, and can provide practical reference for the future modeling design of Yixing teapots.
Research and development of the mathematic models of cryptosystems based on the universal Diophantine language

This paper shows the objective necessity of improving the information security systems under the development of information and telecommunication technologies. The paper for the first time involves a new area of NP-complete problems from Diophantine analysis, namely, multi-degree systems of Diophantine equations of a given dimension and degree of Tarry-Escott type. Based on a fundamentally new number-theoretic method, a mathematical model of an alphabetic information security system (ISS) has been developed that generalizes the principle of building cryptosystems with a public key – the so called dissymmetric bigram cryptosystem. This implies to implement direct and inverse transformations according to a given algorithm based on a two-parameter solution of a multi-degree system of Diophantine equations. A formalized algorithm has been developed for the specified model of a dissymmetric bigram cryptosystem and a training example based on a normal multi-degree system of Diophantine equations of the fifth degree is presented.
Secure Sharing of Medical Images Using Watermarking Technique

The advanced healthcare system needs to share electronic patient record (EPR) among different hospitals and specialists for better and easy treatment of patient. However, the protection of the EPR from unauthorized access and malicious attacks is primary concern to preserve the privacy and proper diagnosis. Medical image watermarking in E-health care system is a suitable technique for safety and confidentiality of EPR. In this paper the medical image is separated into region of interest (ROI) and region of non interest (RONI) part, subsequently additive encryption technique is applied to embed patient record into ROI part of cover media. Backup of original information is embedded into RONI part for tamper detection. Thereafter visible hospital logo is embedded into watermarked medical image for identification purpose. Result of this algorithm tested over few medical images and that produces effectiveness of data payload and integrity.