Reviewerly/exHarmony huggingface dataset:
Parallelization and multi-threaded latency constrained parallel coding of JPEG XS

This paper discusses the background, challenges, opportunities for parallelization of low-latency video transport of JPEG XS streams over the real-time network protocol (RTP). Transport of compressed video signals over a constant bitrate channel requires smoothing buffers at encoder and decoder side. To limit their sizes in partical implementations, part 2 of the JPEG XS standard defines a normative buffer model along a sequential hypothetical reference decoder. Due to its sequential nature, it cannot be directly applied to high-speed applications that necessarily depend on multithreading. In this paper, the JPEG XS Part 2 buffer model is introduced, then the current state of JPEG XS RTP transport standardization is discussed, and multiple strategies for multithreaded encoding under latency contraints within this application are reported and analyzed.
Towards hand gesture-based control of virtual keyboards for effective communication

Abstract Individuals with disabilities are often restricted from performing certain daily life activities that the non-disabled persons would normally perform. One of such restrictions is regarding daily life communication that would require listening, speaking, and sometimes movement of one’s body part often referred to as a gesture. Thus, disabled persons without fingers and cannot speak fluently finds it challenging to communicate effectively during daily life activities. Therefore, a virtual Graphical User Interface (GUI)-based keyboard communication tool is developed in this study to aid such individuals in their daily life activities. The developed virtual GUI-based keyboard can support the different directional movement of the hand including up, down, left, and right, that were coded as different communication signs. The choice “select” can be done by turning the wrist up and “erasing” by turning the wrist down. Every hand movement is read and translated by a leap motion sensor. There are two kinds of GUI used in this research, the first GUI with the Alphabet key is equipped with a pictorial word while the second GUI Qwerty comes with a pictorial word. Experimental results concerning the effectiveness of the typing effectiveness show the alphabet GUI has a faster typing time than the Qwerty GUI with an average difference of fewer than 15 seconds.
New results on the minimal polynomials of modified de Bruijn sequences

Modified de Bruijn sequences are generated by removing a single zero from the longest run of zeros of de Bruijn sequences. It is known that the minimal polynomial of a modified de Bruijn sequence of order n at least has an irreducible factor of degree n. Based on this observation, we give some new results on the minimal polynomial of a modified de Bruijn sequence in this paper. First, it is shown that the minimal polynomial of a modified de Bruijn sequence of order n cannot be the product of an irreducible polynomial of degree n and the irreducible polynomial of degree 2. Second, it is proved that the minimal polynomial of a modified de Bruijn sequence of order n cannot be the product of an irreducible polynomial of degree n and a primitive polynomial of degree k with n≥8k. This is a generalization of the main result in the paper Kyureghyan (2008) [3] which only considered products of two primitive polynomials. Third, it is proved that the minimal polynomial of a modified de Bruijn sequence of order n cannot be a product of an irreducible polynomial f(x) of degree n and a polynomial of order t dividing 2k−1 with gcd⁡(ord(f(x)),t)=1 and n≥4k. As an application, for the cases n=2pe and n=p1⋅p2 where p,p1,p2 are prime numbers and 2pi−1 is also a prime number for i=1,2, a non-trivial lower bound is given for the linear complexity of a modified de Bruijn sequence of order n distinct from m-sequences, which could not be proved by the previous techniques.
Application of CCC–Schoenberg operators on image resampling

Image resampling is a widely used tool in image processing. The upsampling increases the number of pixels and introduces new information to the image which can have undesired effects, like ringing artifacts and oscillations, aliasing “jagged” lines effect, or introduces too much numerical diffusion. Histopolation upsampling methods produce much sharper images but are more prone to aliasing and ringing effect and oscillations which appear as spurious signals near sharp transitions in color intensity. In this paper, we propose an efficient and fast quasi-histopolation algorithm based on the Canonical Complete Chebyshev–Schoenberg operator approximations, applied dimension by dimension. These approximations, because of their shape preserving properties, avoid oscillations. Presented methods have several tunable parameters that control tension and shape properties of the approximation which are used to reduce the aliasing effect while keeping the image visually sharp. Numerical tests on real and artificial images demonstrate the effectiveness and show the computational efficiency of the proposed algorithm.
Public Opinion Guidance Under the Background of Big Data Technology

The rising and increasing maturity of big data technology has fundamentally changed the way of information dissemination and challenged the guidance of public opinion. This paper discusses the new propagation characteristics of information under the background of big data technology, and puts forward the countermeasures of constructing two new models to predict, supervise and guide public opinion for various organizations.
Implementing a Real-Time Image Captioning Service for Scene Identification Using Embedded System

This work aims to implement a real-time scene identification system using an image captioning model on an embedded system. The image captioning model can translate the image captured by a webcam installed on the embedded system into a human-readable sentence immediately. Users can get the information quickly by reading only the sentences. There are two stages in the image captioning model. First, a deep neural network extracts features from images captured from the webcam. Second, a long-short term memory generates the corresponding sentence. Due to the portability of the embedded system, our scene identification system can be placed anywhere at home or in the company. We evaluate the execution time in different aspects on several embedded systems and demonstrate the generated sentences from the captured images by our scene identification system.
Data Privacy and Academic Libraries: Non-PII, PII, and Librarians’ Reflections (Part 2)

Using personally identifiable information (PII) (patron data) to make informed decisions in academic libraries through learning analytics programs has increasingly become more commonplace. In this column, we discuss how libraries around the world have used PII to make informed decisions about hours (gate count), electronic resources (collection usage and authentication), and research assistance (virtual reference). In addition, we discuss the use of learning analytics in library environments including the benefits and concerns associated with its use. Finally, we discuss how we have used PII at our institution's library and the data metrics we plan utilize at some point in the future.
A Hierarchical SVM Based Behavior Inference of Human Operators Using a Hybrid Sequence Kernel

To train skilled unmanned combat aerial vehicle (UCAV) operators, it is important to establish a real-time training environment where an enemy appropriately responds to the action performed by a trainee. This can be addressed by constructing the inference method for the behavior of a UCAV operator from given simulation log data. Through this method, the virtual enemy is capable of performing actions that are highly likely to be made by an actual operator. To achieve this, we propose a hybrid sequence (HS) kernel-based hierarchical support vector machine (HSVM) for the behavior inference of a UCAV operator. Specifically, the HS kernel is designed to resolve the heterogeneity in simulation log data, and HSVM performs the behavior inference in a sequential manner considering the hierarchical structure of the behaviors of a UCAV operator. The effectiveness of the proposed method is demonstrated with the log data collected from the air-to-air combat simulator.
Multi-authority Attribute-Based Encryption with User Revocation and Outsourcing Decryption

Abstract Attribute based encryption scheme is widely used to share sensitive data in cloud storage environment because it can realize fine-grained access control. Aiming at the problem of user revocation and high cost of decryption in cloud storage environment, a multi-authority attribute based encryption scheme with efficient user revocation and outsourcing decryption was proposed. It supports large universe. Each authority manages a specific set of attributes and distributes attribute keys to users with corresponding attributes, avoiding the problem that a single authority may easily become a system bottleneck. The user revocation algorithm of the scheme can realize the efficient revocation of the authorized users, ensuring the forward security of ciphertext. It’s proved to be statically-secure under random oracle and the efficiency analysis shows that it reduces user decryption cost greatly
Research on the Application of Item-based Collaborative Filtering Algorithms in MOOC

Abstract In the learning process, the recommendation system can recommend learning resources that are in line with the learning situation of the learning objects and help the learning objects to learn more easily and naturally. By analyzing the characteristics of item-based collaborative filtering algorithm, this paper applies it to the recommendation system of mooc learning resources to avoid the possible defects of this algorithm, such as low performance and offline processing in other scenarios, and gives full play to its good real-time performance and high recommendation efficiency. By analyzing the log files of imooc, this paper obtains the learned learning resources of the learning objects in imooc, takes the first 80% data of historical records, obtains the recommended list of learning resources through recommendation algorithm, and then compares the data of the last 20% of historical records. Finally, the algorithm is optimized according to the accuracy of the recommendation algorithm in the experiment and the actual learning scene.
Security in Cloud Computing: State-of-the-Art, Key Features, Challenges, and Opportunities

Cloud computing is used for storing, processing, and exchanging information within a community or organization on demand. It presents an excellent business model for organizations in order to exploit better IT services with a lower cost, and less investment. However, a range of security issues predetermines such approach to use. This study incorporates an exploratory method of research by collecting state of the art literature on security and privacy of cloud computing with showing the possible solutions presented in multiple research studies. We then discussed cloud computing architecture, cloud computing security, and highlighted the major challenges of cloud computing security. This is necessary to understand the details of the chosen solution to the widespread security issues associated with cloud computing. Another major contribution of this research is the development of a framework that can be used by enterprises to evaluate the level of threats and damages in their virtual environment. The framework is supported by previous theories that were reviewed in this study.
Patronization for Orphans and Adoption Using Android Application

All around the world, every 30 seconds two children become orphans. Almost there are more than 100 million orphans worldwide. In Asia alone there may be 65 million orphans. They are hungry, afraid and lonely. Their main issues are lack of foods and clothes for their daily usage and lack of education and money. Here, we are introducing an android application which will defeat these issues in an easy manner as well as quickly without spending more time. The notion of this paper is to support orphans of different orphanages by the people who wish to contribute the children and adopting children through online by using our android application. They can help orphans in the orphanages by contributing foods and clothes to the particular orphanage they wish, through online. The people who wish to adopt children can use this application to see the children's details with their photos in different orphanages and they can choose the child they like and other formalities is done by visiting that particular orphanage where the chosen orphan is. Fund transaction is also made by our application. This paper will be beneficial for the orphans. The weary persons can make use of this application for contributing orphans and adopting children. This android application not only indulges in the process of adopting the orphans and providing shelter but also impulses their life by donating food, clothes and money.
A Performance Study of Image Quality Attributes on Smoothened Image Obtained by Anisotropic Diffusion-Based Models

Image acquisition systems usually acquire images with distortions due to various factors associated with digitization processes. Poisson is one of the common types of noises present in the image, and it distorts the fine features. Hence, it is necessary to denoise the noisy image by smoothing it to extract the features with fine details. Among the denoising methods, anisotropic diffusion method provides more adequate results. In this chapter, the authors dealt with existing models such as Perona-Malik (PM), total variation, Tsai, Chao, Chao TFT, difference eigen value PM, adaptive PM, modified PM, and Maiseli models. The performances of the models were tested on synthetic image added with the Poisson noise. Quality metrics are used to quantify and to ensure the smoothness of the resultant images. However, in order to ensure the completeness of the denoising effect, the qualitative attributes such as sharpness, blurriness, blockiness, edge quality, and false contouring are considered on smoothened images. The analysis results are shown the completeness of the denoising effect of the models.
Is "Deny Access" a Valid "Fail-Safe Default" Principle for Building Security in Cyberphysical Systems?

In 1975, Saltzer and Schroeder (S&S) elucidated eight design principles that shaped decades of security research and development. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> Some of them are listed as key tenets of security protocols <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in software design methodologies, such as Microsoft's Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privilege threat model, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3,4</sup> and in McGraw's 2004 article "Software Security" in IEEE Security & Privacy. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup>
Soft Computing in Robotics: A Decade Perspective

As soft computing deals with development of approximate models in finding solutions to real world problems, it is considered as one of the emerging area of research in all fields of engineering and sciences. Because of rapid development in mechanization, vast research has also been carried out by the researchers in the field of robotics for the development of robots in various applications such as industry, medical, rehabilitation, agriculture, military etc. to assist human being. In this paper, a comprehensive analytical perspective of soft computing techniques and their application in robotics has been illustrated. Further, the analysis is a witness of the fact that problems emerging in the robotics can be solved aptly using soft computing techniques. Also, this paper sheds light on various issues and challenges of the discussed research area to demonstrate the dominance of soft computing techniques in the development of various applications in robotics.
Privacy Protection in Transformer-based Neural Network

With the great success of neural networks, it is important to improve the information security of application systems based on them. This paper investigates a scenario where an attacker eavesdrops the intermediate representation computed by the encoder layers and tries to recover the private information of the input text. We propose a new metric to evaluate the encoder's ability to protect privacy and evaluate the Transformer-based encoder, which is the first privacy research conducted on Transformer-based neural networks. We also propose an adversarial training method to enhance the privacy of Transformer-based neural networks.
The CARINA Metacognitive Architecture

Metacognition has been used in artificial intelligence to increase the level of autonomy of intelligent systems. However, the design of systems with metacognitive capabilities is a difficult task due to the number and complexity of processes involved. The main objective of this article is to introduce a novel metacognitive architecture for monitoring and control of reasoning failures in artificial intelligent agents. CARINA metacognitive architecture is based on precise definitions of structural and functional elements of metacognition as defined in the MISM meta-model. CARINA can be used to implement real-world cognitive agents with the capability for introspective monitoring and meta-level control. Introspective monitoring detects reasoning failure (for example, when expectation is violated). Metacognitive control selects strategies to recover from failures. The article demonstrates a CARINA implementation of reasoning failure detection and recovery in an intelligent tutoring system called FUNPRO.
Dual branches network for image super‐resolution

Recent studies have shown that deep convolutional neural networks (CNNs) significantly boosted the performance of single-image super-resolution (SISR). In this Letter, the authors present a novel dual branches network (DBN) for SISR. Different from traditional CNN, the authors' DBN utilises the benefits of the residual structure and the densely connected structure together. Their key strategy is to divide the input path of the network into dual branches: a residual branch and a dense branch. This dual branches structure reuses valuable features and explores new features effectively. Experimental comparisons demonstrated the high ability of their DBN over the state-of-the-art framework for SISR with alleviating blurs of output images.
Describing Interfaces in the Framework of Adaptive Interface Ecosystems

Currently, we can find a large number of user interfaces made by developers who do not follow of current UX premises, i.e. they are not adapted. Normally this is due to financing problems and resources of software projects. In order to study, develop and reuse adaptive user interfaces in a fast and non-invasive way, a new method of interface description is proposed, which would provide to an external library with enough information to restructure the interface in accordance with the use and habits of the user. This way of defining the interfaces is directly linked to the use of Adaptive Interface Ecosystems (AIE), components that work at sight level and whose mechanics can be applied to interfaces independently of their physical nature. Following this methodology of description of the interface, the AIE will be able to carry out an adaptive design of the interface, with very low production and development costs.
Revisiting Conditional Preferences: From Defaults to Graphical Representations

A conditional preference statement takes the form “in context c, a is preferred to not a”. It is quite similar to the piece of knowledge “if c is true, a is more plausible than not a”, which is a standard way of understanding the default rule “if c then generally a”. A set of such defaults translates into a set of constraints that can be represented in the setting of possibility theory. The application of a minimum specificity principle, natural when handling knowledge, enables us to compute a priority ranking between possible worlds. The paper investigates if a similar approach could be applied to preferences as well. Still in this case, the use of a maximum specificity principle is as natural as the converse principle, depending on the decision maker attitude in terms of pessimism or optimism. The paper studies the differences between this approach and qualitative graphical approaches to preference modeling such as $$\pi $$ -pref-nets (based on possibility theory) and CP-nets (relying on ceteris paribus principle). While preferences in a conditional preference network can always be expressed as “default-like” constraints, there are cases where “non monotonic” preferences cannot be associated with a preference network structure, but can still be dealt with as constraints. When both approaches can be applied, they may lead to different orderings of solutions. The paper discusses this discrepancy and how to remedy it.
Audio steganography applications using auditory features watermarking

Abstract Watermarking is a technique for hiding data or information on a digital multimedia (image, sound and video) and is not visible to the ordinary eye and is resistant to digitization (editing media, noising, blurring, etc.). While audio watermark is defined as a technique of hiding data or confidential information into an audio data for “boarding” (audio host), people do not aware of the existence of additional data on the data host. Coding phase is hiding data by exchanging the original phase of the initial segment of the sound signal with the absolute phase of the watermark signal, while maintaining the relative phase between the signal segments using different phase segments of the original signal. When the phase difference between the original signal and the modified signal is small, the difference in sound produced is not detected by human hearing. To recognize ownership of multimedia content, testing is done first by combining the cover and watermark files. Experiment result on audio files shows that audio files successfully compressed on 50% efficiency without reducing the duration of the audio. After compression process, One of our audio sample which size is 3.37MB can be reduce to 1.68MB without reducing the duration of the audio.
Evaluation of the spatial frequency response and the uncertainty for a commercial structured light system

Structured light systems (SLS) have become increasingly important for three-dimensional shape measurements. A quantitative evaluation of the spatial resolution is also becoming increasingly important. The spatial frequency response of the instrument is a reasonable metric for resolution and is commonly referred to as the instrument transfer function (ITF). In this paper, we present a methodology to estimate the ITF of a commercial SLS (the EinScan-Pro 3D Scanner) and its uncertainty. A measurement of a step artifact is used for the ITF estimation. We also discuss a method to check the validity of the artifact used for the measurement. The ITF dependence on step orientation and position in the measurement volume is also presented, in addition to a comparison between ITF and the modulation transfer function (MTF) for the cameras in the instrument.
Software architecture knowledge sharing with the architecture knowledge base (AKB)

The Software Architecture Knowledge Base (AKB) is a web-based application for architecture knowledge sharing. It uses compact architecture knowledge descriptions, which we call architecture profiles, as building blocks for establishing a community-driven software architecture knowledge base. The tool facilitates documentation, sharing and reuse of architectural knowledge both within and across different software projects. We have used it in different student projects and are currently evaluating it in an industrial context.