Reviewerly/exHarmony huggingface dataset:
On the Condition of Complete Controllability of Stage-by-Stage Changing Linear Dynamic Systems with Varying Dimension of the Control Vector

The control problem of stage-by-stage changing linear dynamic systems with varying dimension of the control vector is considered. A necessary and sufficient condition for complete controllability of the stage-by-stage changing linear non-stationary systems with varying dimension of the control vector is obtained; when the condition is satisfied the system can be transferred from any given initial state specified at the first stage to any final state specified for the last stage with the corresponding control actions. The condition of complete controllability for a stage-by-stage changing linear stationary system is expressed directly through the initial parameters of the system and is comparable with the well-known Kalman condition for the ordinary systems. The qualitative properties of controllability of such systems are revealed.
Unleashing the VEP Triplet Count of Virtually Created 3D Bangla Alphabet to Integrate with Augmented Reality Application

This paper demonstrates the process of calculating VEP triplet count of Bangla Alphabet which are unlike traditional hand written or printed letters, but created entirely in 3 dimensional virtual environment to effectively use in Augmented Reality Based applications. This count can be a potential support for 3d modelers, Augmented Reality based application developers and academic researchers. The challenges that we faced and the limitations of our contribution are also mentioned here. It is expected that future academic researchers and commercial application developers will get a great support on developing 3D Bangla alphabet from our research.
Study of Information Retrieval Method by Understanding User Situation from Computer Screen

Information workers involved in business operations such as data entry or help-desk support often have a hard time searching for information, especially when a situation is unfamiliar. In this paper, we propose a method that automatically retrieves text information shown on workers' computer screens to analyze their situations and recommend helpful information to support their operations. We evaluated the effectiveness of our approach by using 96 situations (=computer screens) collected from help-desk tasks and 204 enterprise documents containing related business rules for those tasks. We evaluated the way of utilizing words in the situations to retrieve helpful information effectively. In our findings, necessary words to retrieve helpful information were not included in the words that appear frequently in the 96 situations but the words that only appear in certain situations. Moreover, when recommending a helpful page that contains fewer business rules, word selection becomes highly important. We also analyzed what kinds of situations and information quantity in documents changed the effectiveness of our approach.
Frequent Item-Set Mining Using Lexicographical Sequential Tree Construction on Map Reduce Framework

Frequent itemset mining is playing an important research role for many aspirants all over the world. In all the research aspects efficiency and scalability are main retrospects which are being improved in FIM which is intensive. In the current scenario, the implementation of a sequential growth algorithm on the big data map reduce framework the lexicographic sequential tree construction for the identification of the frequent itemsets using the lexicographical order over the databases of transaction without incorporating any extreme search methodologies. The result signifies a wide variety of large database executions to prove the execution of this methodology as an efficient and improved scalability of the methodology. Further the incorporation of this technique with other pattern mining is quite beneficial on big data.
Blind-Depth Light Field Super-Resolution

Abstract Light field cameras have drawn much attention due to the ability of post-capture adjustments such as refocusing and 3D reconstruction. However, the low resolution has been the bottleneck of them and limits their further application. To solve this problem, various methods have been proposed to increase the resolution, namely, to recover details and reconstruct a high resolution (HR) image of the scene from several low resolution (LR) observations. Most of the previous super-resolution (SR) frameworks depend on prior knowledge of depth information, which is an indispensable part in their SR approaches. However, it may be difficult to obtain precise depth information in some practical situations. In this paper, we propose a novel light field super-resolution (LFSR) framework independent of the prior depth information. The framework combines a variational regularization-based SR approach with light field refocusing process, which can super-resolve the focused region while preserve the unfocused region and generate a series of multi-focus super-resolved images. We then employ a multi-focus image fusion algorithm based on stationary wavelet transform (SWT) and finally obtain an all-in-focus HR image. Synthetic and real-world datasets are utilized to demonstrate the effectiveness of the proposed framework both quantitatively and visually.
MSFA-Net: a Network for Single Image Deraining

Abstract Rain streaks degrade the quality of image. Many methods have been proposed to solve single image rain streaks removal recently. However, some methods over-smooth the recovered image. A deep network architecture called Multi-Scale Feature Attention Network (MSFA-Net) is proposed in this paper. We propose a novel basic block structure to exploit the image features, which consists of multi-scale residual learning block and feature attention block. Several basic block structures with a local residual learning compose a group architecture. The outputs of each group architecture are concatenated for final multi-scale feature fusion. Then the features are fed into feature attention block and reconstruction module. Finally, a global residual learning module restore the clean image. Besides, the feature attention block combines channel attention with spatial attention. The proposed MSFA-Net removes the rain streaks which study a non-linear mapping relationship between the rainy and clean image from synthesized dataset. Through comparing with other state-of-the-art algorithms, our algorithm performs better for both synthesized rainy image data and real rainy image data.
Zweilous: A Decoupled and Flexible Memory Management Framework

Currently, with the booming growth of cloud computing, workloads from broad ranges of functions and demands are crammed into a single physical machine. They lay considerable stress on the need of evolution of the operating system underneath, especially the memory subsystem. Even enhancing large pages with main memory compression is not intuitively straightforward due to rigid rules imposed by the state-of-the-art manager Buddy System from the beginning of the design. To relieve the aforementioned problems and provide broader design space for system designers, we propose Zweilous, a clean slate physical memory management framework. It is self-contained, highly decoupled, and thus can co-exist with the vanilla memory manager. Separate self-contained metadata/functions guarantee a flexible extension with little modification to current frameworks. To show it is easy to add enhanced functions that accelerate the evolution of the memory management subsystem, we implement Hzmem, a new large page memory manager redesign enhanced with the function of main memory compression. Our method achieves competitive performance compared with native and virtualized large page support, effective memory size increased and fewer impacts on other parts of the operating system.
Rock Image Automatic Annotation based on Deep Neural Network

The automatic image annotation is a technology that uses deep neural network to extract features from the input image, and finally converts it into text description. It is currently one of the hot researches of explainable artificial intelligence. The thin section image of rock is an important data source in the field of geological exploration and oil and gas development. It can reflect the microstructure inside the rock. However, in actual research, if you only rely on manual observation to extract features from hundreds of rock images, it will affect the research efficiency and take time and effort. This paper uses GoogLeNet model in the deep convolutional neural network to implement the feature extraction of rock images, and also uses the LSTM model in the deep recurrent neural network to convert the image features into text features, and finally converts the rock images into text descriptions. The automatic image annotation technology of rock images based on deep neural networks not only realizes a step of converting rock images into text, but also assists scholars in the field of petroleum geology to realize efficient research.
Qualified Electronic Signature SaaS Solution for Google Docs &amp; Google Sheets Documents

Qualified e lectronic s ignatures ( QES) a re legally equated with handwritten signatures and are the main mechanism to ensure the authenticity and integrity of electronic data. In E.U., adoption of QES services became easier from the user's perspective, thanks to the adoption of the Regulation (EU) No 910/2014 (the "eIDAS" Regulation) which enables cloud QES. According to the new legislative definitions f rom t he eIDAS Regulation, the signatory is no longer required to own a hardware cryptographic device to obtain a QES, but the secure signature creation device can be managed by the issuing certification authority, namely the trust service provider (TSP). The sole control of the user over her/his private keys stored and used in the cloud shall be assured through the remote signature protocol exposed by the TSP, compliant to corresponding ETSI standards. Thanks to their interoperable character, services exposed by the TSPs are suitable for integration in different document management platforms. However, the full potential of cloud QES has not been reached yet. In order to sustain the adoption of QES, this paper proposes a Software-as-a-Service (SaaS) solution to enable platforms like Google Docs and Google Sheets to directly apply QES on the documents created and used in the cloud. The implemented proof of concept is compliant with the two main signature creation standards: Cloud Signature Consortium (CSC) and OASIS Digital Signature Service (DSS). This paper presents the architecture and implementation details of the proposed solution and also the main challenges encountered during the development of the SaaS platform to offer remote QES services. This paper presents the architecture and implementation details of the proposed solution. Also, we present the main challenges encountered during the development of the SaaS platform to offer QES services.
MPT.Br Maturity Model: implementation in a telecommunications company

Since at least 15 years, software testing has been one of the areas of software engineering that is increasing its importance in many organizations around the world. Due to this, guides, standards, and maturity models, such as the Brazilian Test Process Improvement model (MPT.Br), are gaining visibility to ensure that a company or organization, even a small one, has a quality level in their testing processes. Such models are important to ensure customer satisfaction and quality analysis of business processes in the production of a system. Given this context, this research aims to present the implementation of the MPT.br (in the first two maturity levels) in a telecommunications company in Brazil to present the benefits of defining the software test process according to a maturity model. To achieve the research goal, we are using a research method called action-research, which is based on empirical studies in software engineering. As results, we expect that this deployment in the company will contribute to a significant improvement in its testing processes, thus contributing to the improvement of the entire organization.
Study on the Preparation and Application of Vector Reference Map

In scene matching, we use vector data instead of raster data to prepare a reference map. The BSP -algorithm is used to manage the vector data and then it is loaded on the aircraft. During the guidance process, reference maps are real-time prepared based on the track information and camera parameters. As the vector reference map is very different from the real-time map, conditional generation adversarial networks are used to convert the real-time map to a vector-style image and then match it to the vector reference map, which can achieve 86% matching accuracy.
Software requirements profile: life cycle and his relation with development processes

Priority task of software development is forming of set of requirements for him.Process of forming such set of software requirements named software requirements profiling and his product (set of requirements) named software requirements profile.It should be noted, that profiling can use for other objects of profiling, for example, for forming software characteristics, potential risks of software, software tests, techniques and metrics of software quality verification.Analysis of software development processes, which describe in [1] are represented in article.Further, processes for which profiling is mandatory is defined.As result, between profiling different objects and software development processes establish some conformities.Following software life cycle models: cascade, V-shaped, spiral are analysed.Between software life cycle stages and different profiling objects is established conformity.Implementation of software requirements profiling i.e. forming software requirements profile (this is product of software requirements profiling process) is very important and responsible task for expert.It is connect to the fact that software requirements profiling defines software requirements profile quality -particular «basis» or «foundation» of developed software.The objective of the work is representation and describe life cycle of software requirements profile taking into account possible gaps.Software requirements profile life cycle, which includes following 6 stages: requirements profile in thinking (RPT), requirements profile formulated (RPF), requirements profile for representing (RPR), requirements profile for developing (RPD), requirements profile in software (RPS), requirements profile after verification (RPV) are represented in article.In during transition his from stage to stage according to life cycle of software requirements profile can be some differences (gaps) in software requirements profile.In this connection, full set of chains of differences in software life cycle profile requirements software was formed.Examples of describe such chains were represented also.
An experimental design on the SPEM 2.0 process model element classification algorithm of the AVISPA tool through ANOVA variance analysis

Introduction: This publication is the product of research: “SPEM 2.0 Process Model Metrics in the Reliability of its Visual Analysis” throughout 2019, which supports the work of a master’s degree in Systems Engineering at the University of Cauca.&#x0D; Objective: Rebase a process model metrics set in order to increase AVISPA reliability to support the visual analysis of SPEM 2.0 software process models.&#x0D; Methodology: In order to improve AVISPA, a systematic literature review had been performed to find software process model metrics that are potentially apt to be represented in AVISPA. Next, a set of assessments were performed in order to enhance visual analysis tool. Finally, an ANOVA statistical assessment was realized in order to find a variance differential between AVISPA versions by comparing their F1-Score process model elements classification values.&#x0D; Results: AVISPA significantly improved its general classification algorithm. Most of errors were found in SPEM 2.0 variability resolution feature and collections with duplicated elements. Multiple misclassifications still persists.&#x0D; Conclusion: General AVISPA process model elements classification is improved. However, some process model samples remain scattered according to ANOVA results.&#x0D; Originality: AVISPA is a recent solution for SPEM 2.0 software process model assessment. It's recent emergence carried to a lack of articles about software process model metrics and few works about AVISPA improvements. These are the main contributions of this paper.&#x0D; Limitations: The project has been widely expensive in terms of execution time, traceability with all software process model elements, and mainly to find experts in software process that can meet the research requirements
Efficient Technique of Impulsive Noise Detection and Replacement in Color Digital Images

In this paper, a very efficient method of impulsive noise suppression in color digital images is presented. The new filtering design exploits the concept of digital paths connecting the boundary of the filtering window with its center pixel. If the minimum connection cost of a path linking the window center with its border exceeds a predefined threshold, then the pixel is considered as distorted and filtered, otherwise, it is preserved. For finding the path with minimum cost, the Dijkstra algorithm is applied. The noisy pixels are restored using a new approach, which is based on the overdetermined system of equations used in the Laplace inpainting technique. The experimental results show that the application of the impulse detection relying on the connection cost, combined with a robust method of pixel replacement, significantly excels over existing techniques designed for impulsive noise reduction in digital color images.
Requirements Elicitation: Questions Coordinated with Key Dimensions of DeLone and McLean Information Systems (IS) Success Model

Requirements elicitation is the practice of discovering the requirements of a system from users' perspectives before the system is developed. It is one of the activities carried out during the analysis phase in Software Development Life Cycle (SDLC) Model. The challenge of this requirements elicitation is particularly prevalent among junior programmers as they have lack of knowledge, exposure and experience in identifying what kind of questions should be asked to the system's users when formulating their requirements. Hence, this study aims to construct a list of standard questions, coordinated with key dimensions in the DeLone and McLean Information Systems (IS) Success Model to assist these junior programmers to identify the system requirements in more detail as the user wishes. Three (3) steps are conducted to be used as methodology for this study: 1) exploration of the DeLone and McLean's key dimensions, 2) keywords identification according to the key dimensions explored, and 3) construction of important and standard questions, coordinated with the key dimensions of DeLone and McLean IS Success Model. The first two steps involve literature from established online databases, while the third step is the main contribution of the authors. At the end of this study, a list of 60 important and standard questions to be answered by users during requirements elicitation is meticulously constructed. With that comprehensive and standard questions, it is positive that junior programmers can better investigate and comprehend the user's needs, problems and even their requests during requirements elicitation.
Quantum High Secure Direct Communication with Authentication

A quantum high secure direct communication with authentication protocol is proposed by using single photons. The high security of the protocol is achieved on levels. The first level involves the verification of the quantum channel security by using fake photons. The authentication process is also ensured by the fake photons. The second level of security is given by the use of multiple polarization bases. The secret message is encoded in groups of photons; each single character of the message is associated with m (m≥7) photons. Thus, at least 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">7</sup> (128) characters will be encoded. In order to defeat the quantum teleportation attack, the string of bits associated to the secret message is encrypted with a secret string of bits by using XOR operator. Encryption of the sender's identity string and the receiver's identity string by the XOR operator with a random string of fake photons defends quantum man-in-the-middle attack efficiently. Quantum memory is required to implement our protocol. Storage of quantum information is a key element in quantum information processing and provides a more flexible, effective and efficient communication. Our protocol is feasible with current technologies.
All Nearest Smallers Made Simple

In this paper, a parallel algorithm for all nearest smallers problem without using doubly logarithmic tree is described. It is shown that using only [Formula: see text] time routines for merging and prefix minima, we can easily get an [Formula: see text] time parallel algorithm for the all Nearest Smallers problem.
Reverse Engineering Website Navigation Using an Information Architecture Approach (Case Study: Kanal Pengetahuan Universitas Gadjah Mada)

Abstract In its development, the website of Kanal Pengetahuan UGM is built through a practical approach, so there are many shortcomings in defining the need and strategy information for the needs of the service business. As for the current problem, i.e., poor navigation related to the definition of primary content and links in the navigation menu. This is causing the granularity of information that makes users difficult to understand and find the information they need. This research aims to do reverse engineering of website navigation using the information architecture method to investigate the way how users to find and interact with information content from the website. The main contribution of this research is the analysis of the result of card sorting has directed the research to gain insight into how the users in categorizing information on the website. As a result, in the current system, there are only 3 categories that have not yet represented all the information provided by the website, so that research conducted with 102 participants produced a new navigation proposal with 4 new categories that fit the user’s mental model.
Using the DSM

This chapter suggests that Data Safety analysis policies, strategies and plans are produced and maintained by Data-Centric Organisations that address Safety-Related Systems. Given the potential for multi-dimensional change, analysis planning should incorporate a definition of the system context, one or more System Definitions and their respective Interface Agreements. The Data Safety Model development and subsequent analysis should be repeatable, auditable and suitable for external audit and assessment. This chapter walks through the development of a Data Safety Model employing Critical Control Points and the Transformation-Abstraction-Process model. It does so initially for a new Data-Centric system and then considers the variation required for a change to an existing system. The process establishes context, identifies threats, establishes risk requirements, evaluates the current system proposal and aids proposal of monitoring of the data safety model using lagging and leading indicators.