Reviewerly/exHarmony huggingface dataset:
An Artificial Intelligence (AI) based Energy Efficient and Secured Virtual Machine Allocation Model in Cloud

Ensuring security in cloud systems is one of the most significant tasks for users facing security problems in load balancing. Many conventional works have developed secured load balancing models for allocating Virtual Machines (VMs) in cloud systems. Still, it limits by the problems of high migration overhead, increased processing time, storage complexity, high energy consumption, and lack of security. So, the proposed work objects to implement an energy-efficient and secured Artificial Intelligence (AI) based VM allocation model for cloud load balancing. The novel contribution of this work is to develop an Intelligent Mine Blow Optimization (IBMO) technique to securely allocate the VMs in the cloud. Also, it helps to mitigate the security risks created by the attacks of VMs from multiple users. Moreover, it maintains the workloads among all VMs in the cloud server. The primary advantages of this work are reduced energy consumption, resource consumption, and overhead. During analysis, the performance and results of the proposed IBMO-based VM allocation model are validated and compared using various evaluation indicators.
Survey on use of Augmented Reality in Early Childhood Education: Teachers Perspective

Learner motivation and engagement plays an important role in effective learning. Selecting the right teaching strategies to increase engagement and motivation are equally important. Innovations in multimedia, technology, computers and internet have given rise to the use of new methods and tools in the classroom. Augmented reality is an instrumental tool used by educators to teach their students. As technology changes and is part of the curriculum, augmented reality finds space as a learning tool to increase student engagement and motivation. This study will help researchers and developers acquire valuable knowledge to understand the various challenges of early learning from a teacher's perspective. It will help understand how the use of Augmented Reality technology can help improve student engagement, motivation and academic performance and understand the limitations in existing applications that need to be addressed while developing AR applications for early stages.
A Survey on Identification of Hate Speech on Social Media Post

In the age of social media and mobile internet, the development of autonomous methods for online detection of hate speech or abusive language is vital for societal and community empowerment because social media is accessible worldwide via the internet. Anybody may simply attack someone or a group who adheres to a different culture or ideology on social media. While everyone has the freedom to express their own opinions, it should not be destructive, and everyone has the right to be free to say anything. To learn about hate speech, a review process include a large number of research articles which were published in the period of year 2017 to year 2022. After an exhaustive review process, we have found the common findings, strengths, weaknesses, gaps and solution approaches & their results.
Analysis and Comparison of Various Contrast Enhancement Techniques

Contrast enhancement assumes an important part in image processing which makes an image more clear and bright. It essentially improves the image quality which makes the image's content easy to recognize. In this paper the analysis of four popular contrast enhancement techniques have been done to overcome the brightness and preservation issues and also keeps up the quality of the image. These four techniques are Histogram Equalization (HE), Brightness Preserving Bi- Histogram Equalization (BBHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and Recursive Mean-Separate Histogram Equalization (RMSHE). Additionally the work also shows the estimation of various parameters like: Signal to noise ratio (SNR), Mean square error (MSE), Root mean square error (RMSE), Mean absolute error (MAE), Peak signal to noise ratio (PSNR), and Structure similarity index (SSIM) for each technique.
A Survey on Blockchain for Bitcoin and Its Future Perspectives

The term cryptocurrency refers to a digital currency based on cryptographic concepts that have become popular in recent years. Bitcoin is a decentralized cryptocurrency that uses the distributed append-only public database known as blockchain to record every transaction. The incentive-compatible Proof-of-Work (PoW)-centered decentralized consensus procedure, which is upheld by the network's nodes known as miners, is essential to the safety of bitcoin. Interest in Bitcoin appears to be growing as the market continues to rise. Bitcoins and Blockchains have identical fundamental ideas, which are briefly discussed in this paper. Various studies discuss blockchain as a revolutionary innovation that has various applications, spanning from bitcoins to smart contracts, and also about it being a solution to many issues. Furthermore, many papers are reviewed here that not only look at Bitcoin’s fundamental underpinning technologies, such as Mixing and the Bitcoin Wallets but also at the flaws in it.
Legal challenges of the Croatian legislature with regard to the hate speech and committing certain criminal offenses

A man's perennial desire and the struggle for freedom of speech, and freedom of expression, will experience the paradigm and reality in today's time, despite the evolutionary development of such desire and struggle about power and the legislator who will eventually articulate these desires. Freedom of expression is the highest human, social and humanistic evolutionary value in a liberal democracy in which an individual or group of people can convey their views, thoughts, and criticisms to other people, groups, and the governing structure. Unfortunately, freedom of expression in the 1920s began to demonstrate the dysfunction and anomalies of such values in public, media space, especially through electronic media, electronic publications, and modern electronic platforms, which are accessible by many people. In concrete terms, and considering the Croatian reality(ies) and experience with the above-mentioned phenomenon, it is indisputable that we are witnessing the abuse or misunderstanding of the limits of freedom of expression due to extensive interpretation or misunderstanding of democracy, radicalizes and abuses freedom of expression. The emergence of abuse of freedom of expression results in hate speech and the commission of certain crimes (public incitement to terrorism, terrorism, public incitement to violence, and hatred). Thus, we can say that there is a(n) (in)direct link between the freedom of expression provided for in Articles 9 and 10(1) of the European Convention for the Protection of Human Rights and Fundamental Freedoms and other constitutional and legal provisions of the Republic of Croatia. The abuse of the exercise of these rights results in the commission of certain criminal offenses. Although hate speech and the radicalization of the media space through new electronic platforms have disavowed freedom of speech and opinion, it has also raised the question of the sufficiency of the existing legislative framework and the need for a new legislative response (example of Austrian counter-terrorism measures) with which, as a new form of legal struggle, these phenomena would be prevented and sanctioned. All of the above poses a legal challenge to existing constitutional provisions and the legislative framework in Croatia. Having this in mind, should Croatian legislators follow the example of the Austrian legislator and respond to abuses and violations of freedom of expression? Recognizing the above phenomena and connections between the abuse of freedom of expression with the commission of certain criminal offenses, the author uses scientific analysis and comparative method to examine the legal challenges and/or the strength of the Croatian legislative framework and asks whether there are perhaps new legal mechanisms that should be a response to these phenomena to further strengthen and protect the of freedom of expression.
Evaluation of remote learning at technical universities during a pandemic – the perspectives for the future

This article is a summary of a research conducted in the conditions of remote teaching of undergraduate and postgraduate students at technical university. The research referred to the effectiveness and perspectives of web-based education (under the conditions of lockdown) during the COVID-19 pandemic. The aim of the research was to assess the quality of courses and involvement of students in the learning process. One year after the introduction of this form of learning at universities, certain phenomena can be observed, which allow us to draw the first conclusions. In the final part of the study, the author discusses the possibility to continue and use this form of education once the pandemic has passed. The familiarisation and adaptation of students to this specific character of courses in the conditions of a pandemic was a stimulus to interpret this state as a long-term form of education that can change future ways and forms of teaching at universities, including technical universities
A hidden threat

Manufacturing is a prime target for cyber criminals, but companies can employ a range of methods to protect themselves and their IP
Decision Support System for Movie Recommendations Based on Multi User Preferences Using the Simple Additive Weighting Method

At this time advances in technology and information have experienced rapid progress, one of which is in the field ofentertainment, both audio and visual. And one of the entertainments is movies. With the increasing number of movies,there are several classifications of movie genres to assist users in finding and selecting movies to watch, but the genreclassification itself is still very general. Due to the above factors, especially in genre, subgenre, rating, movie durationwhich always develops over time according to a certain pattern and also audiences who have different moviepreferences, the researcher sees that there is a need for an application that can recommend movies with preferencesthat can be set according to the wishes of movie lovers. From the problems that arise, this research was built using theSimple Additive Weighting (SAW) method which aims to make it easier for users to determine which movie to choose.This system produces a web-based information system using several parameters, namely the main genre of a movie,subgenre, movie rating, movie duration, and year of making.
Social unrest and corporate behaviour during the Arab Spring period

While several facets of social unrest have been well-studied in the literature, one aspect which has remained largely unaddressed is its impact on corporate behaviour. To examine this closely, integrating data on 12 MENA country-firms covering both oil exporters and oil importers during 2001–2015 with a newly constructed measure of social unrest, we exploit the natural experiment of the Arab Spring to tease out the impact of social unrest on firm behaviour. The findings suggest that there is an increase in leverage, driven mainly by an increase in long-term leverage, although at a higher cost. Robustness tests reveal a cyclical pattern in the evolution of such leverage wherein short-term leverage declines and rises thereafter, whereas the reverse holds for long-term leverage. We undertake several robustness tests of the baseline findings and continue to find evidence in favour of a discernible impact of social unrest on corporate behaviour.
On the Granularity of Explanations in Model Agnostic NLP Interpretability

Current methods for Black-Box NLP interpretability, like LIME or SHAP, are based on altering the text to interpret by removing words and modeling the Black-Box response. In this paper, we outline limitations of this approach when using complex BERT-based classifiers: The word-based sampling produces texts that are out-of-distribution for the classifier and further gives rise to a high-dimensional search space, which can’t be sufficiently explored when time or computation power is limited. Both of these challenges can be addressed by using segments as elementary building blocks for NLP interpretability. As illustration, we show that the simple choice of sentences greatly improves on both of these challenges. As a consequence, the resulting explainer attains much better fidelity on a benchmark classification task.
Initial validation of the GUESS-18 for usability in virtual reality gaming environments: a pilot study

Virtual reality (VR) technology has developed rapidly in recent years with head-mounted displays (HMDs), which provide immersive VR experiences by inserting users into an artificially constructed digital world. However, there is currently no standardized tool for measuring usability in VR environments. The purpose of this study was to provide initial validation of the GUESS-18, a usability questionnaire for video games, for measuring usability of VR in a gaming environment. Participants played a racing game with an HMD in VR and a traditional monitor and completed the GUESS-18 and the System Usability Scale (SUS). Confirmatory factor analysis was performed to determine GUESS-18 validity. The Comparative Fit Index (CFI) and Root Mean Square Error of Approximation (RMSEA) values indicate appropriate model fit, with values of 0.967 and 0.056, respectively. Internal consistency (Cronbach’s alpha) was satisfactory for all factors except for social connectivity. Scores from the GUESS-18 were significantly higher with VR by about 6.4%, but SUS scores were equivalent between display types. Playing the game in VR resulted in greater immersion and personal gratification than playing with the monitor. Overall, the GUESS-18 can measure usability of VR games as it distinguishes VR from traditional monitor environments and shows satisfactory validity and consistency.
Benefits for the bunker industry in adopting blockchain technology for dispute resolution

The bunker industry has faced negative perception to their trust and credibility in recent times. This is further compounded by the need for the industry to answer new challenges to meet the requirement of the International Maritime Organization 2020. The aim of this work is to illustrate how blockchain technology may be adopted for aiding in bunker dispute resolution. To demonstrate how blockchain may aid in disputes within the bunker industry, this paper first examines the existing bunker supply process, which involves the formation of contracts under English law, the Bunker Delivery Notes, the different types of disputes that may arise during a bunker transaction and the methods of dispute resolution utilised by the industry. Furthermore, the current literature in relation to blockchain technology and blockchain smart contracts is examined. Finally, interviews and surveys within the industry have been conducted to identify the benefits, and challenges, in adopting blockchain technology. The research found that blockchains may benefit the bunker supply chain resolving the effective resolution of bunker quality disputes. Furthermore, blockchains may also serve as a verification tool for electronic bunker delivery notes, which may aid quality and quantity bunker disputes as well as compliance with the new International Maritime Organisation 2020 requirements. As a result, despite the research having shown blockchain to be situationally dependent and having an element of legal uncertainty, blockchain does offer a solution to aid in bunker disputes and for improving the trust and credibility within the bunker industry.
Dynamic Surface Capture for Human Performance by Fusion of Silhouette and Multi-view Stereo

We present a multi-camera based 3D dynamic surface capture solution, which supports high-fidelity generation of 3D dynamic content for various performance scenes. Our system uses a set of RGB cameras to synchronously acquire scene image sequences and performs a processing pipeline to produce 4D videos. We propose a multi-view point cloud reconstruction method which integrates volumetric based guidence and contraint into a coarse-to-fine depth estimation framework. It gives accurate point cloud models and can handle well with the scenes where textureless objects and multiple subjects present. We also present new methods and introduce modifications for several other key computation modules of the processing pipeline, including foreground segmentation, multi-camera calibration, mesh surface reconstruction and registration, texturing, 4D video compression, etc. Experiments on captured scenes show that our system can produce highly accurate and realistic 4D models of the human performances. We develop a 4D video player and toolkit plugins, and demonstrate the use of integrating the 4D content in VR and AR applications.
Exploring the Use of Smartphones as Input Devices for the Mixed Reality Environment

Nowadays, researches on mixed reality (MR) have made a lot of exploration in the aspects of user experience, hardware devices, interaction technologies, application systems, etc. However, more research is still needed to explore how to improve the experience in the shared MR Environment and design appropriate collaborative interaction models. The traditional VR handle can realize tool simulation and 3D interaction, while smartphones can realize 2D interactions such as fast 2D gestures, text input and handwriting. Using the mobile phone as the handle of the MR headset can realize the complementary advantages of the two. In this study, we design a cross-device collaborative system sharing a hybrid reality environment. In the MR Environment, the smartphone will realize the functions of the controller for remote selection and manipulation of objects, and its advantages in 2D interaction can be well applied to some special tasks. We design the user interface with three levels of immersion: high, medium and low. High immersion: We provide a hybrid user interface combining a HoloLens2 and a smartphone. Medium immersion: We provide a 3D user interface represented by HoloLens2. Low immersion: We provide a multi-touch user interface represented by tablet. User studies show that the hybrid user interfaces can bring users satisfactory immersion and interactive experience, but it also needs to design accurate and efficient input methods according to the interactive tasks.
Multi-View Fusion for Sign Language Recognition through Knowledge Transfer Learning

Word-level sign language recognition (WSLR), which aims to translate a sign video into one word, serves as a fundamental task in visual sign language research. Existing WSLR methods focus on recognizing frontal view hand images, which may hurt performance due to hand occlusion. However, non-frontal view hand images contain complementary and beneficial information that can be used to enhance the frontal view hand images. Based on this observation, the paper presents an end-to-end Multi-View Knowledge Transfer (MVKT) network, which, to our knowledge, is the first SLR work to learn visual features from multiple views simultaneously. The model consists of three components: 1) the 3D-ResNet backbone, to extract view-common and view-specific representations; 2) the Knowledge Transfer module, to interchange complementary information between views; and 3) the View Fusion module, to aggregate discriminative representations for obtaining global clues. In addition, we construct a Multi-View Sign Language (MVSL) dataset, which contains 10,500 sign language videos synchronously collected from multiple views with clear annotations and high quality. Extensive experiments on the MVSL dataset shows that the MVKT model trained with multiple views can achieve significant improvement when tested with either multiple or single views, which makes it feasible and effective in real-world applications.
Computer-vision Classification-algorithms Are Inherently Creative When Error-prone

Whether coming from a linear support vector machine, from logistic regression, or a quasi-Newtonian, the fine-tuning of the decision boundary in any given data set is essential to mitigate the loss term so that neural nets in image recognition can divide a data space into separate sections and correctly classify an input. By their very nature, neural nets are logically non-deterministic but rest on probability-weighted associations, which are adjusted recursively to enhance the similarity of intermediate results to the target output, the remaining difference being the ‘error.’ However, taxonomies should not be crisp but seen as fuzzy classes, allowing for hybrid exemplars that transgress category boundaries. The associative and similarity orientation of neural nets and deep learning makes such systems inherently creative in that misclassifications are at the basis of creative crossovers in information processing. This new conceptualization of network errors is supported by the ratings of 40 top-ranking designers of 20 image-recognition mistakes on the dimensions of creativity and innovativeness.
Unsupervised Embroidery Generation Using Embroidery Channel Attention

It is a challenging task to synthesize an embroidery image with complex texture from a colorful image. Existing style transfer methods to synthesize embroidery images will lead to color shift and texture clutter. In this paper, the generative adversarial network architecture with embroidery channel attention is proposed to synthesize embroidery images based on the unaligned dataset. Our method can synthesize the color and texture images generated separately from the features of the input image without extra data and cycle network. The generator with embroidery channel attention in our network can generate three attention masks (texture attention mask, color attention mask, original attention mask) and two content masks (color content mask and texture content mask). The color image and texture image of embroidery are synthesized separately with these masks. Meanwhile, a color loss function is proposed to encourage the color of the generated image to be close to that of the original image. In addition, a white padding processing technology is proposed to improve the stability of global embroidery texture synthesis. Existing extensive experiments show that our method synthesizes the embroidery images with realistic color and stable texture to solve the color shift and texture clutter. In the case of ensuring the content of the input images, the results synthesized by our method are closer to the real embroidery.
A Low-cost Efficient Approach to Synchronize Real-world and Virtual-world Objects in VR via In-built Cameras

Virtual reality (VR) technology has become a growing force in entertainment, education, science, and manufacturing due to the capability of providing users with immersive experiences and natural interaction. Although common input devices such as controllers, gamepads, and trackpads have been integrated into mainstream VR systems for user-content interaction, they cannot provide users with realistic haptic feedback. Some prior work tracks and maps the physical objects into the virtual space to allow users to interact with these objects directly, which improves users’ sense of reality in the virtual environment. However, most of them use additional hardware sensors, which inevitably increases the cost. In this research, a lightweight approach is proposed to synchronize the positions and motions between physical and digital objects without any extra costs. We use the real-time captured video data from in-built cameras on a VR headset and employ feature points based algorithms to generate projections of the physical objects in the virtual world. Our approach does not rely on additional sensors but just uses components available in a VR headset. Our approach allows users to interact with target objects with their hands directly without the need for specially designed trackers, markers, and other hardware devices as used in previous work. With our approach, users can get more realistic operational feedback when interacting with corresponding virtual objects.