Reviewerly/exHarmony huggingface dataset:
Decision-Making Support Using Nonmonotonic Probabilistic Reasoning

The goal of this paper is to introduce a decision-making support by rule-based nonmonotonic reasoning enhanced with probabilities. As a suitable rule-based tool, we analyze answer set programming (Asp) and explore its probabilistic extension that permits the use of probabilistic expressions of two types. The first type represents an externally given prior probability distribution on literals in an answer set program \(\varPi \). The second type represents a posterior distribution conditioned on individual decisions and choices made, together with their consequences represented by answer sets of \(\varPi \). The ability to compare aspects of both the prior and posterior probabilities in the language of the program \(\varPi \) has interesting uses in filtering solutions/decisions one is interested in. A formal characterization of this probabilistic extension to Asp is provided in addition to examples demonstrating its potential use. It is also shown that the proposed techniques do not increase the complexity of standard Asp-based reasoning.
A Phoneme Sequence Driven Lightweight End-To-End Speech Synthesis Approach

Abstract This paper develops an end-to-end neural network model for text-to-speech (TTS) system based on phoneme sequence. Inspired by the Tacotron-2, the proposed model adopts an encoder-decoder model with attention mechanism and applies mel-spectrogram to measure the intermediate acoustic feature. Phoneme sequence is used to replace the character sequence in order to overcome the shortage of the character feature used in Tacotron-2. Unlike the conventional concatenate methodology based TTS system, our model can generate waveform directly from phoneme sequence. In addition, analogue from text analysis, a new analysis methodology is proposed for phoneme analysis. Experiment result on LJ Speech dataset shows that, compared with char-based model, our model can get a comparative or better performance.
PCTL model checking based on Giraph

At present, ensuring system security and verifying whether the system meets the given requirements have been the focus of computer engineers. Model checking is an automatic and exhaustive technique to prove whether there has absence of such errors in a system which has been widely applied. It has a regular requirement for a system model under consideration and a desired property. Then it systematically checks whether or not the given model satisfies this property. However, the traditional algorithm on Hadoop for checking Computation Tree Logic (CTL) formula does not scale well because of the need of conducting a huge number of states with each passing day. To deal with the state space explosion problem, we propose a scalable algorithm on the platform of Giraph, which is a new rising iterative graph processing platform with high scalability and employs the Bulk Synchronous Parallel (BSP) model. We also address this problem by selecting Probabilistic Computation Tree Logic (PCTL) as the property specification, which is strictly more expressive and makes a great advancement on using probability to describe the probability of an event occurring. This paper comes up with a novel method based on Giraph to verify one PCTL formula, which is used to represent a maximum probability of reaching a certain state, being regarded as a quantitative description of a property in system detection. Owing much to the Giraph platform, our experiment is of great interest as it displays much more efficiently than current methods which are based on Hadoop and so on. Ultimately, we discover that the processing time of Giraph platform applying message model is much shorter than that of Hadoop platform applying iterative model through experimental comparison.
Two Implementations of Real-Time Sequence Generator for {n&lt;sup&gt;3&lt;/sup&gt; | n=1, 2, 3, ... } and Their Comparison

A cellular automaton (CA) is a well-studied non-linear computational model of complex systems in which an infinite one-dimensional array of finite state machines (cells) updates itself in a synchronous manner according to a uniform local rule. A sequence generation problem on the CA model has been studied for a long time and a lot of generation algorithms has been proposed for a variety of non-regular sequences such as {2n | n = 1, 2, 3,...}, prime, and Fibonacci sequences etc. In this paper, we study a real-time sequence generator for {n3 | n=1, 2, 3, ...}. In the previous studies, Kamikawa and Umeo(2018) showed that sequence {n3 | n=1, 2, 3, ...} can be generated in real-time by an eight-state CA. We present a new six-state implementation of real-time sequence generator for {n3 | n=1, 2, 3, ...} rather than reducing the internal state of the Kamikawa and Umeo's sequence generator and give a formal proof of the correctness of the generator. In addition, we show the number of state-changes and number of cells of sequence generators, and compare sequence generators.
Solar Energy Resource and Its Global Distribution

The sun is an extremely powerful energy resource, and the solar energy is an important renewable energy. Solar energy can be used for producing heat and generating electricity. The amount of solar energy incident on earth is enormous, and it is larger than current and predicted energy requirements in the future. In this chapter, the basic concepts and parametrical performance of the sun and its radiation across the space and earth surface including solar irradiance on earth(i.e., diffuse irradiance and direct normal irradiance, the solar constant, extraterrestrial solar spectrum, extraterrestrial solar irradiance, and extraterrestrial solar radiation on a surface), ground-level solar radiation characteristics(atmosphere effects and solar spectrum), solar angles(i.e., the earth–sun angles, hour angle, declination angle, latitude angle, solar altitude, zenith, and azimuth angles), are described. Solar energy global distribution by belt and nation at variable geometrical regions on the globe is also presented.
Survey on astroturfing awareness

This paper describes astroturfing as an organized effort to influence someone's thinking in order to gain benefit in various ways. Insufficient information and lack of critical thinking are good grounds for using false assumptions to influence the minds of others and their actions. This paper focuses on the survey conducted among students of the Polytechnic of Rijeka about astroturfing awareness or lack thereof. The results show that astroturfing has to be taken seriously because it is a powerful tool for manipulation and a threat to the credibility of initiatives and organizations which has a negative impact on the entire Internet community. The most effective detection techniques are development of education and critical thinking and acquaintance with astroturfing and its methods.
Examination of genuine, disguised, and simulated signatures

FDEs are often tasked with determining whether a signature is genuine or is a simulation. The FDE has to consider if the signature is genuine, but disguised. Disguised signatures often bear similar features with simulated signatures. This chapter discusses the characteristics of these three types of signature behavior and means of evaluating and differentiating them.
The importance of integration of information security management systems (ISMS) to the organization's Enterprise Information Systems (EIS)

The interconnected information systems and networks drive the organizations into a critical situation that determines the need for explicit measures for information protection. The "culture of security" becomes a very important part of the business competition and security policy is a crucial component of business management. The organizations generate, use, store and transmit a huge amount of information which is vital to their functioning and prosperity. It is necessary the information be kept confidential when required, to be available when and where needed and protected from modification and loss of integrity. On this paper, I would like to explain the importance and the impact that information security management system may have on the general enterprise information system. This paper explains the processes that must be taken to integrate the ISMS to EIS, how this integration will help the organizations to protect their data and how this integration will affect on the growth of the business value and trust to the consumers.
Usability of University Recruitment Web Pages from International Doctoral Students’ Perspectives

This study examined a group of international doctoral students’ interactions with the recruitment web pages at the University of Tennessee, Knoxville (UTK). It employed eye-tracking and exit interviews. Students performed six assigned search tasks, and their task outcomes were measured based on success, dwell time, and time-based efficiency. Time to first eye fixation and fixation counts were measured using heatmaps and Area of Interests (AOIs), respectively. The findings showed that while the students were able to use the websites and find answers to most of the search tasks, they faced challenges with the usability of these websites. The findings have implications for designing recruitment web pages that are user-centered and supportive of international doctoral students’ information needs and interaction behaviors.
Let-Binding in a Linear Lambda Calculus with First-Class Continuations

In our previous work, we proposed a linear lambda calculus with first-class continuations. In the usual lambda calculus, an argument value can be duplicated and deleted, but the continuation cannot. In our calculus, a value is allowed to be neither duplicated nor deleted, but a continuation is allowed, so it can be considered to be dual with the usual lambda calculus. In this paper, we extend a linear lambda calculus with first-class continuations by adding let-binding. We define a syntax, a call-by-value reduction, and a type system of the calculus. Then, we discuss the let-polymorphism in our calculus.
Blockchain as a Value Enabler

Blockchain technology was envisaged to bring a universal solution to strengthen digital democracy: ensure digital trust, distribute power between members, minimise e-monopoly, and it all through the innovative way of digitising and transacting 'value'. The latter however was deemed to represent financial assets only, neglecting the value created by the intangibles - the non-financial value. Nevertheless, intangibles are established to play a significant role in impacting financial value and therefore need to be incorporated into the existing value chain system. This paper explores how blockchain technology can capture and transact not just financial value, but non-financial one, conveying this way total value.
Trust in Cloud Computing Challenges: A Recent Survey

With the widespread use of computer networks, the challenge of distributed systems is to support multiple security policies. Notably, the cloud computing that represents a revolution in computer system, with its hype today, the services providers migrate to the integration of the said systems in different areas. Despite his advantages such speed, Qos and performance, actually, the cloud does not present a solution to address the problems of computer systems which stay more complex, namely security. In practice, cloud computing defines several security limitations because of the problem of virtualization and segmentation of data, therefore, several approaches have been proposed to address security issues, including authentication. In this paper we implement cloud authentication issues while emphasizing the different principles namely the Trusted Third Party (TTP) and the Third Party Auditor (TPA) as well as the authentication techniques based on these two principles in order to define the specific security requirements for the cloud.
Project management guidelines/frameworks in the era of agility and complexity

Nowadays, the role of project management (PM) as a prerequisite for successful project execution is globally acknowledged. Several PM frameworks have been introduced during the last years to help project managers and project stakeholders to understand their role in projects, to make them be aware of their expected operations, and to systematically guide their actions during project execution. The dominant PM frameworks as well as their similarities and differences are presented with emphasis given to PM body of knowledge guide. Furthermore, the notion and the dimensions of complexity in projects in general and in software projects in particular with its implications in PM are presented.
On foundational aspects of optical quantum communication

Using a simple model of the quantized photon field in an optical fibre we suggest a model of quantum teleportation of continuous variables which is more realistic than the usual one in the sense that the localization properties of the quantities to be teleported are taken into account.
Ensuring Equity and Inclusion in Higher Education Provision: Ghana’s Approach

The current economic stage of the world is argued to be that of a knowledge economy. This refers to a shift from the dependence on natural resources to a new paradigm where the production and use of knowledge are paramount. Countries all over the world are striving to have full participation in the knowledge economy by providing opportunities for equitable access to higher education in order to provide advance knowledge to all citizens. Ghana is striving hard to achieve equitable higher education and use it as the agency for spearheading its full participation in the global knowledge economy, but so far, Ghana’s approach to equitable higher education, which is worth sharing, has not been synthesized and shared with the scholarly community. This chapter analyzes and synthesizes the various initiatives Ghana has undertaken to promote equitable higher education, draws attention to the gaps between rhetoric and realities, and makes recommendations for improvements in the initiatives.
Metascience and Metacognition

Rosenbloom (2013) gave reasons why Computing should be considered as a fourth great domain of science, along with the Physical sciences, Life sciences, and Social sciences. This paper adapts Rosenbloom’s ‘metascience expression language’ to support descriptions and comparison of metascience and metacognition, and discusses the similarity of metascience and metacognition.
ELM-Based Improved Layered Ensemble Architecture for Time Series Forecasting

In this paper, an extreme learning machine (ELM)-based improved layered ensemble architecture (EILEA) for time series forecasting is proposed. Compared with multilayer perceptron (MLP)-based layered ensemble architecture (named LEA), our proposed structure has improved in two aspects. First of all, we proposed an inflection point estimation-based density peaks clustering algorithm to replace K-means algorithm used by LEA, which can automatically determine the number of clusters without the influence of the choice of initial cluster centers on the clustering results. Second, EILEA employs ELM as individual learners, taking advantage of its high learning speed to greatly improve the prediction speed. The proposed architecture has been tested on the time series data of neural network (NN)3 competition. In terms of forecasting accuracy and speed, the experimental results have revealed clearly that our proposed structure is better than LEA.
A New Model for Creating Layer Planes Using Steganography for Text Hiding

Steganography is the art and science of hiding messages in a secret way such that only the sender and receiver know. This allows one party to communicate with another without a third party knowing that the connection is taking place. Here, the data is hidden inside a safe “cover”, where even if a third party can capture the cover, there will be nothing to show what data is hidden inside. Meanwhile, the cover can be an image, sound, video or document. Steganography has two primary aspects: security - whether the hidden data is perceptible by either a person or a computer; and capacity - how much data can be hidden in a given cover file. Because the system works within a spatial domain, it can hide a large amount of information, while embedding and extraction processes require less time in terms of execution than methods using transform domains. This paper explains how to use steganography through a modern technique with a practical understanding.
Feasible coordination of multiple homogeneous or heterogeneous mobile vehicles with various constraints

We consider the problem of feasible coordination control for multiple homogeneous or heterogeneous mobile vehicles subject to various constraints (nonholonomic motion constraints, holonomic coordination constraints, equality/inequality constraints etc). We develop a general framework involving differential-algebraic equations and viability theory to describe and determine coordination feasibility for a coordinated motion control under heterogeneous vehicle dynamics and various constraints. A heuristic algorithm is proposed for generating feasible trajectories for each individual vehicle. We show several application examples and simulation experiments on multi-vehicle coordination under various constraints to validate the theory and the effectiveness of the proposed algorithm and control schemes.
The examination of signatures on nonoriginal documents

The examination of signatures on nonoriginal documents presents additional challenges for the FDE as compared with the examination of an original signature. Nonoriginals exist, for example, as photocopies, fax copies, and carbon copies. The FDE must be aware of limitations imposed by nonoriginal documents and take them into account during an examination.
Efficient Estimation of Number of Short Lattice Vectors in Search Space under Randomness Assumption

Lattice basis reduction algorithms are widely-used heuristic methods for solving the Shortest Vector Problem (SVP) on lattices. Recently, the sampling reduction approach has achieved high performance solving the SVP on high-dimensional lattices. It repeats a generation process of short lattice vectors and a lattice basis reduction algorithm alternately. In the generation process, it generates a lot of lattice vectors in a search space based on a current lattice basis and selects short lattice vectors from them. Therefore, it is quite important for investigating and accelerating the sampling reduction to estimate the number of short lattice vectors in a search space. In this paper, we propose a new method for estimating the number of short lattice vectors by the Gram-Charlier A series under the randomness assumption. The Gram-Charlier A series is a basic asymptotic expansion of any probability distribution by utilizing the higher order cumulants such as the skewness and the kurtosis. The proposed method uses a "parametric" model, which gives a calculable and continuous function of the number of short lattice vectors. The proposed method is much more efficient than the previous methods using the non-parametric estimation. Moreover, its convergence speed can be evaluated theoretically. This is expected to enable us to investigate lattice basis reduction algorithms intensively in various situations and clarify their properties. Numerical experiments verified that this method can estimate the number of short lattice vectors of an actual lattice basis quite accurately.
Edge-Preserving Image Smoothing Via a Total Variation Regularizer and a Nonconvex Regularizer

Image smooth plays an important role in image pre-processing. For classical image smoothing models, a convex total variation regularizer or a nonconvex regularizer has been widely used to protect image edges and to smooth noise. In this paper, we propose a new effective model in which the total variation regularizer and the nonconvex regularizer are combined to be a new weighted regularizer. The main advantage of our combined regularizer is that some undesirable details such as noise can be removed more effectively, while some important edge details can be preserved better. In addition, an efficient algorithm is designed to solve our model. In our algorithm, an iteratively reweighted process with the Chambolle’s projection algorithm are coupled with each other. Numerical results demonstrate that our proposed model can generate better image smoothing results than those generated by total variation based models and those generated by nonconvex regularizer based models.
An Efficient Anomaly Detection Framework for Electromagnetic Streaming Data

The electromagnetic signal is a kind of communication signal whose intensity can reflect the electromagnetic condition of the current space. The continuous electromagnetic signal data can be seen as a kind of time-series flow data. During actual monitoring, the use of wireless devices can affect the electromagnetic space distribution and alter the signal strength at the corresponding frequency point. By detecting the changes of signal strength, the use of wireless devices can be effectively found. Based on the isolation forest algorithm and the Storm streaming computing platform, an efficient framework for wireless devices usage detection is proposed. The experiments results based on the real-world electromagnetic streaming data demonstrate that the framework can accurately and efficiently detect abnormal signals.
Augmenting neuro-evolutionary adaptation with representations does not incur a speed accuracy trade-off

Representations, or sensor-independent internal models of the environment, are important for any type of intelligent agent to process and act in an environment. Imbuing an artificially intelligent system with such a model of the world it functions in remains a difficult problem. However, using neuro-evolution as the means to optimize such a system allows the artificial intelligence to evolve proper models of the environment. Previous work has found an information-theoretic measure, R, which measures how much information a neural computational architecture (henceforth loosely referred to as a brain) has about its environment, and can additionally be used speed up the neuro-evolutionary process. However, it is possible that this improved evolutionary adaptation comes at a cost to the brain's ability to generalize or the brain's robustness to noise. In this paper, we show that this is not the case; to the contrary, we find an improved ability of the to evolve in noisy environments when the neuro-correlate R is used to augment evolutionary adaptation.
Reshaping the Teaching Ecology with the Construction of Informationalized Teaching Mode

With the further application of information technology in the field of education, the education informationization gradually moves from shallow application to deep integration. The promotion of education informationization makes the integration problem more complicated, so it is urgent to study and discuss how to promote the deepening of the application of information instruction in school. Based on the view of education ecology, this paper puts forward a teaching model to promote the deep integration of information technology in teaching, and to establish an information-based teaching ecological model, and also puts forward the idea to reconstruct the school teaching ecology from the concept layer, pattern layer and practice layer. At the same time, combined with the examples of middle school information teaching ecology remodeling, this paper expounds how to optimize and reform the teaching ways, organization management mode and campus culture through teaching model construction.