Reviewerly/exHarmony huggingface dataset:
Globalness Detection in Online Social Network

Classification problems have made significant progress due to the maturity of artificial intelligence (AI). However, differentiating items from categories without noticeable boundaries is still a huge challenge for machines - which is also crucial for machines to be intelligent. In order to study the fuzzy concept on classification, we define and propose a globalness detection with the four-stage operational flow. We then demonstrate our framework on Facebook public pages inter-like graph with their geo-location. Our prediction algorithm achieves high precision (89 %) and recall (88 %) of local pages. We evaluate the results on both states and countries level, finding that the global node ratios are relatively high in those states (NY, CA) having large and international cities. Several global nodes examples have also been shown and studied in this paper. It is our hope that our results unveil the perfect value from every classification problem and provide a better understanding of global and local nodes in Online Social Networks (OSNs).
Ramifications of E-Learning Within Education

Change is an inevitable reality of life. Countries, cultures, ways of thinking and producing, relations, and nature are constantly changing. The human being is constantly changing. This change and transformation takes place even faster with the advanced technology today. Surely this change and transformation has influenced many aspects of life and brought innovations into education. As a result of this change and transformation, the education process in many countries has turned into a student-centered structure supported by technology, embracing alternative approaches instead of traditional learning-teaching approaches.
Forecasting Software Vulnerabilities Using Time-Series Techniques

This chapter discusses the concepts of time-series applications and forecasting in the context of information systems security. The primary objective in such formulation is the training of the models followed by efficient prediction. Although economic and financial forecasting problems extensively use time-series, predicting software vulnerabilities is a novel idea. The chapter also provides appropriate guidelines for the implementation and adaptation of univariate time-series for information security. To achieve this, the authors focus on the following techniques: autoregressive (AR), moving average (MA), autoregressive integrated moving average (ARIMA), and exponential smoothing. The analysis considers a unique data set consisting of the publicly exposed software vulnerabilities, available from the U.S. Dept. of Homeland Security. The problem is presented first, followed by a general framework to identify the problem, estimate the best-fit parameters of that model, and conclude with an illustrative example from the above dataset to familiarize readers with the business problem.
The Interdisciplinarity of the Information Science

This chapter presents the conceptual evolution of interdisciplinarity, transdisciplinarity, and discipline under information science from a theoretical framework. The text is a research whose primary purpose is to analyze scientific research developed in the context of interdisciplinary information science with participation in more than one area of knowledge. Using the concepts presented and those that contemporary authors studied in different areas for composition of the conceptual framework that presents itself, the results of the research have enabled profiling of research in the area about the use of different approaches and concluded that different forms and levels of interaction are found in information science. It is, therefore, concluded that the concepts have changed and that caused significant changes in their meanings. These changes lead to an ongoing re-evaluation and updating in the context of information science and its implications because it is an interdisciplinary science.
White-Box Testing Automation With SonarQube

Modern work patterns like continuous integration (CI) have an implicit need for testing automation. In current CI solutions, white-box testing is left to the work methodology, typically addressed after code reviews. Code security inspection is often done in specific code reviews focusing on security. SonarQube is a tool that, to a certain extent, can automate white-box design and testing and serve as a guide for formal code reviews. Moreover, this tool can help audit the code for potential security issues. Most web programming today uses components readily available and transparently managed by package managers, like npm for Node.js or Composer for PHP. This use must also be audited at least for potential security problems; yet traditional white-box test design would require a good understanding of the vendor code, which can be difficult/impractical to achieve. This chapter will address SonarQube as a valuable tool to automate white-box and security testing and also provide suggestions on how to manage your vendor branches when there is a need to audit/change the vendor source code.
Software structure evolution and relation to subgraph defectiveness

Network analysis has been successfully applied in software engineering to understand structural effects in the software. System software is represented as a network graph, and network metrics are used to analyse system quality. This study is motivated by a previous study, which represents the software structure as three-node subgraphs and empirically identifies that software structure continuously evolves over system releases. Here, the authors extend the previous study to analyse the relation of structural evolution and the defectiveness of subgraphs in the software network graph. This study investigates the behaviour of subgraph defects through software evolution and their impact on system defectiveness. Statistical methods were used to study subgraph defectiveness across versions of the systems and across subgraph types. The authors conclude that software versions have similar behaviours in terms of average subgraph type defectiveness and subgraph frequency distributions. However, different subgraph types have different defectiveness distributions. Based on these conclusions, the authors motivate the use of subgraph-based software representation in defect predictions and software modelling. These promising findings contribute to the further development of the software engineering discipline and help software developers and quality management in terms of better modelling and focusing their testing efforts within the code structure represented by subgraphs.
Evaluating the Refactoring Index Using Entropy Approach

Software often carries the structural deficiencies that make it hard to understand, change, or test; these deficiencies are categorized as a code smell. This code smell affects the performance of software adversely, thereby increase need of maintainability. Refactoring of code helps in reducing the code smell. But refactoring is an expensive process and hence identifies which and how much code need to refactor a challenging task and is termed as refactoring index. In this chapter, entropy approach is proposed to measure the refactoring index of 20 open source software programs. Refactoring index level is given to identify the critical project which urgently required refactoring in order to improve the quality of the project.
A Universal Approach to Designing an Image Interpolator with an Image Smoothing Filter

A number of conventional interpolation techniques have been proposed.However, it seems that there do not exist good criteria for the design of optimal linear interpolators.Also, such an interpolator can hardly provide a satisfactory solution for interpolating noisy images.In this paper, the novelty of this research is that a universal approach is proposed to design an image interpolator with any one image smoothing filter, thereby not only interpolating a down-sampled image but also preserving the characteristics of the performing filtering.
Fisher-discriminative regularized latent sparse transfer model

Top performing algorithms are trained on massive amounts of labeled data. Alternatively, domain adaptation (DA) provides an attractive way to address the few labeled tasks when the labeled data from a different but related domain are available. Motivated by Fisher criterion, we present the novel discriminative regularization term on the latent subspace which incorporates the latent sparse domain transfer (LSDT) model in a unified framework. The key underlying idea is to make samples from one class closer and farther away from different class samples. However, it is nontrivial to design the efficient optimization algorithm. Instead, we construct a convex surrogate relaxation optimization constraint to ease this issue by alternating direction method of multipliers (ADMM) algorithm. Subsequently, we generalize our model in the reproduced kernel Hilbert space (RKHS) for tracking the nonlinear domain shift. Empirical studies demonstrate the performance improvement on the benchmark vision dataset Caltech-4DA.
Recent Advances in the Evaluation of Ontology Quality

Ontology or domain specific vocabulary is indispensable to a semantic web-based application; therefore, its evaluation assumes critical importance for maintaining the quality. A modular ontology is intuitively preferred to as a monolithic ontology. A good quality modular ontology, in turn, promotes reusability. This chapter is directed at summarizing the efforts towards ontology evaluation, besides defining the process of evaluation, various approaches to evaluation and underlying motivation. In particular, a modular ontology's cohesion and coupling metrics have been discussed in detail as a case study. The authors believe that the body of knowledge in this chapter will serve as a beginning point for ontology quality engineers and at the same time acquaint them with the state-of-art in this field.
Caught in the Act: Law-Enforcement Feedback on Video Surveillance Recordings

Video surveillance systems, designed to provide security, act like a guard in a watchtower-a security solution that has been well understood for thousands of years. Systems are designed to meet security needs of the customer who installs the system. However, such systems rarely work as useful law-enforcement tools, leading to frustration and disappointment for police, store owners, and crime victims. In many cases, a business owner selects a system because it is easy to install and manage, operates it in good faith, but when robbery or some other incident occurs, no conviction follows. The perpetrator cannot be identified because the system failed for one reason or another to produce evidence valid for a prosecution.
Governing Through Technology and the Failure of Written Law

This chapter examines the rift between written law and the technical systems used for governance. To this end, the hazards that might occur as a consequence of the introduction of such technology are discussed, namely the loss of political and legal control, the reliance on nongovernmental entities in the case of functionality crucial to the normal operation of a society, and the implications for legal certainty. Next, based on two use-cases, we argue that written law fails to define provisions for technical systems at a level which would allow for fair competition between system providers. And finally, we outline an argument for why even seemingly minor changes in software systems can challenge the doctrine of legal certainty when dealing with the digital interfaces of governmental systems.
A Requirements Approach for Building an Enterprise Cloud Service Catalog

In the context of cloud computing, the service catalog is a critical component of the cloud computing architecture. Most cloud computing projects will invariably begin with a discussion of what IT services an enterprise needs. Even when end users have a cloud environment, the business still wants to know which cloud services we need and how much does it costs. Information Technology Infrastructure Library (ITIL) service design defines a service catalog as a list of technology-enabled services that an organization provides, often to its employees or customers. More specifically, the service catalog is an expression of the operational capability of a service provider or enterprise within the context of an end customer, a market space, or an internal business unit stakeholder. Unfortunately, most service catalogs are built by technologists for technologists. This design methodology is fine assuming the user of the catalog is an information technology professional.
Dynamic Epistemic Reasoning with Awareness and Its Legal Application

Concerning a software tool of legal reasoning, it is important to describe the prediction about the result of a criminal action, because a crime is often caused by the unpredictability of the result of the defendant. In the court, the judge needs to investigate the predictability and the intention of the agent. Previously, we have formalized the reasoning process of judgment by action model in dynamic epistemic logic (DEL) and have attempted to describe the precedents. However, the prediction in legal cases depends not only on the states of knowledge but also on the limited degree of attention by agents. In this paper, we employ DEL with awareness for multi-agent to represent the predictability and model the typical criminal precedents. We propose a revised semantics of action model with awareness which can define each basic action model to reproduce the agent’s considering process. To describe the legal reasoning we introduce an extension of modeling program DEMO to include the awareness (we call it DEMO[Formula: see text]) and present a GUI in this extended program to calculate the updated epistemic model easily and to classify precedents according to the degree of prediction. In the end, we calculate the epistemic models of typical criminal precedents by this newly developed tool and estimate them.
A Swan-like note for a family of binary pentanomials

In this note, we employ the techniques of Swan (Pac J Math 12(3):1099–1106, 1962) with the purpose of studying the parity of the number of the irreducible factors of the penatomial $$X^n+X^{3s}+X^{2s}+X^{s}+1\in \mathbb {F}_2[X]$$ , where s is even and $$n>3s$$ . Our results imply that if $$n \not \equiv \pm 1 \pmod {8}$$ , then the polynomial in question is reducible.
Image region label refinement using spatial position relation graph

With the exponential growth of massive image data, automatic image annotation is becoming more important in image management and retrieval. Traditional image region annotation methods, through machine learning and low-level visual features, typically yield incorrect annotation results owing to the influence of the Semantic Gap. We herein propose a novel label refinement method for improving the image region annotation results. A spatial position relation graph with co-occurrence relations and spatial position relations among labels is proposed to analyze the latent semantic correlations among image region labels. Moreover, an incremental iterative random-walking algorithm is proposed to reconstruct the region relation graph for detecting non-dependable regions whose labels do not fit the semantic context of an image. Subsequently, a graph matching algorithm with semantic correlation and spatial relation analysis is proposed for non-dependable region label completion. Experiments on Corel5K demonstrate that our proposed spatial-position-relation-graph- based label refinement method can achieve good performance for image region label refinement.
Enrichment Ontology via Linked Data

The automatic construction of ontologies from texts is usually based on the text itself, and the domain described is limited to the content of the text. In order to design semantically richer ontologies, the authors propose to extend the classical methods of ontology construction (1) by taking into account the text from the point of view of its structure and its content to build a first nucleus ontology and (2) enriching the ontology obtained by exploiting external resources (general texts and controlled vocabularies of the same domain). This chapter describes how these different resources are analyzed and exploited using linked data properties.
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation

One major technique debt in video object segmentation is to label the object masks for training instances. As a result, we propose to prepare inexpensive, yet high quality pseudo ground truth corrected with motion cue for video object segmentation training. Our method conducts semantic segmentation using instance segmentation networks and, then, selects the segmented object of interest as the pseudo ground truth based on the motion information. Afterwards, the pseudo ground truth is exploited to finetune the pretrained objectness network to facilitate object segmentation in the remaining frames of the video. We show that the pseudo ground truth could effectively improve the segmentation performance. This straightforward unsupervised video object segmentation method is more efficient than existing methods. Experimental results on DAVIS and FBMS show that the proposed method outperforms state-of-the-art unsupervised segmentation methods on various benchmark datasets. And the category-agnostic pseudo ground truth has great potential to extend to multiple arbitrary object tracking.
Spam Filtering and Detection

In today's world of globalization and technology without borders, the emergence of the internet and the rapid development of telecommunications have made the world a global village. Recently, the email service has become immensely used, and the main means of communication because it is cheap, reliable, fast, and easy to access. In addition, it allows users with a mailbox (BAL) and email address to exchange messages (images, files, and text documents) from anywhere in the world via the internet. Unfortunately, this technology has become undeniably the original source of malicious activity, in particular the problem of unwanted emails (spam), which has increased dramatically over the past decade. According to the latest report from Radicati Group, which provides quantitative and qualitative research with details of the e-mail, security, and social networks, published in 2012, 70-80% of email traffic consists of spam. The goal of the chapter is to give a state of the art on spam and spam techniques and the disadvantages of this phenomenon.
Approximation of incoherent probabilities

In order to explore making incoherent probabilistic knowledge more applicable, we considered the approach of using mathematically precise probability to approximate set functions that represent incoherent subjective knowledge. The approximation approach has the advantage of being applicable to any kind of set function whereas other transformation methods are mainly restricted to a certain subclass. The projection method was developed for approximation using Euclidean distance. We analyze its advantages and disadvantages in comparison with normalization for additive set functions. Here, we present novel properties of both, the projection method and normalization. Thus, in the context of additive set functions, the question of which method is superior remains open, but with further arguments on both sides.
Region Secure and Pattern Based Alternate 2B-3C Steganography Approach for Data Security in Color Images

Background and Objective: The public and group communication carried out in the social, cloud, and mobile networks suffer from unauthorized users. The data security is required for secure authentication, monetary transactions and other sensitive information. The steganography methods empower the user with invulnerable communication in public domain. In this paper, a region secure and pattern based alternate 2B-3C (2Bit-3Channel) Steganography method is proposed to improve the content reliability and data security. Methods: In this method, the cover pixels are retrieved by applying the spiral rectangular pattern over the cover image. This spiral pattern also secures the core content region and the pixels from the core ROI (Region of Interest) is used as a cover only for larger size secret information. In this proposed steganography method, two channels are considered alternatively based on the defined rules. The LSB (Least Significant Bit) of both channels is XOR with input data bits and key to perform data hiding. The method is applied on real time color images taken from COREL and USC-SIPI-ID. The evaluation of proposed steganography approach is done using MSE (Mean Square Error), PSNR (Peak Signal-to-Noise Ratio), BER (Bit Error Rate), NCC (Normalized Cross Correlation) and SSIM (Structural Similarity Index Matrix). Result: The comparative results are generated for 50 real time images against the existing LSB (Least Significant Bit), LSBM (Least Significant Bit Modulation), LSBMR (Least Significant bit Matched Revisited), SCC (Stego Color Cycle), SHSI (Simple Hue-Saturation-Intensity), HIS-MLSB(Simple Hue-Saturation-Intensity-Modified LSB) and IMMEA(Iterative Magic Matrix Encryption Algorithm) methods. Conclusion: The experimentation results verified that the proposed 2B-3C approach improved the data hiding in qualitative and quantitative aspects.
RASSS: a hijack‐resistant confidential information management scheme for distributed systems

In distributed systems there is often a need to store and share sensitive information (e.g., encryption keys, digital signatures, login credentials etc.) among the devices. It is also generally the case that this piece of information cannot be entrusted to any individual device since the malfunction or compromising of one node could jeopardize the security of the entire system. Even if the information is split among the devices, there is still a risk when an attacker can compromise a group of them. Therefore we have designed and implemented a secure and robust secret sharing scheme to enable a more resilient sharing of confidential information. This solution provides three important features: (i) it uses threshold secret sharing to split the information into shares to be kept by all devices in the system; so the information can only be retrieved collaboratively by groups of devices; (ii) it guarantees the privacy of the confidential information under a certain number of passive hijacking attacks; and (iii) it ensures the integrity of the confidential information against any number of hijackers who actively and collusively attack the devices. It is able to identify all the compromised devices, while still keeping the secret unforgeable to attackers.
A 40-dimensional extremal Type II lattice with no 4-frames

We construct a $40$-dimensional extremal Type II lattice not having any subsets consisting of $40$ orthogonal minimal vectors, and determine the automorphism group. This lattice gives an example different from the $16470$ lattices constructed from binary codes by classical constructions.