Reviewerly/exHarmony huggingface dataset:
Cover dependent watermarking against ambiguity attacks

Digital Image Watermarking using Singular Value Decomposition has a fundamental flaw of false watermark generation when Singular Values of the watermark are embedded into the cover. The proposed work embeds Principal Components of two watermarks instead, to overcome this flaw. These watermarks are embedded into horizontal and vertical sub-band coefficients of 3-level DWT of the cover respectively. Keys based on cover and watermarks are generated and used for cover and watermark verification during extraction. The proposed technique is secure because knowing the keys merely is not sufficient to extract the two watermarks. Correct combination of keys with the respective 3-level DWT coefficients is required. The work is proved to be robust against false watermark generation, false cover claim and general image processing attacks together with high imperceptibility. Colour images are used in HSV colour model and Value plane is used for embedding the watermark.
La educación del siglo XXI y el despertar de las bellas durmientes: una revisión sistemática de la literatura

Although 21st-century education has been widely debated and presented in the literature, the reality of today’s schools, especially in developing countries, shows a very distant image of what should be a flexible, personalized, soft skills-oriented education, based on the use of Information and Communication Technologies (ICT). To address this situation should be the first step in order to understand it and provide concrete work elements for teachers, school principals and policymakers, especially for those who work in adverse educational contexts. This article presents a systematic literature review focused on the identification of critical ideas about 21st-century education as possible factors of a transformation of the current school. The review included 780 research reports on 21st-century education, which were coded and processed through text mining. A selection of 101 reports was read in-depth and qualitatively analyzed. The results revealed that although most of the critical ideas related to 21st-century education are not brand new, they are flourishing, like sleeping beauties, with new possibilities of implementation due to the evolution of current technological development. Some of the educational sleeping beauties to highlight are personal learning paths, research-based teaching, open, flexible and digitally supported curriculum, and lifelong learning.
Inference Procedures on the Ratio of Modified Generalized Poisson Distribution Means: Applications to RNA_SEQ Data

The Poisson and the Negative Binomial distributions are commonly used as analytic tools to model count data. The Poisson is characterized by the equality of mean and variance whereas the Negative Binomial has a variance larger than the mean and therefore is appropriate to model over-dispersed count data. The Generalized Poisson Distribution is becoming a popular alternative to the Negative Binomial. We have considered inference procedures on a modified form of this distribution when two samples are available from two independent populations and the target effect size of interest is the ratio of the two population means. The statistical objective is to construct confidence limits on the ratio. We first test the presence of over dispersion and derive several estimators in the single sample situation. When two samples are available, our interest is focused on the estimation of an effect size measured by the ratio of the respective population means. We have compared two methods; namely the Fieller’s and the delta methods in terms of coverage probabilities. We have illustrated the methodologies on published genomic datasets.
Three approaches to measuring recall on the Web: a systematic review

Purpose The purpose of this paper is to present a review on the use of the recall metric for evaluating information retrieval systems, especially search engines. Design/methodology/approach This paper investigates different researchers’ views about recall metrics. Findings Five different definitions for recall were identified. For the first group, recall refers to completeness, but it does not specify where all the relevant documents are located. For the second group, recall refers to retrieving all the relevant documents from the collection. However, it seems that the term “collection” is ambiguous. For the third group (first approach), collection means the index of search engines and, for the fourth group (second approach), collection refers to the Web. For the fifth group (third approach), ranking of the retrieved documents should also be accounted for in calculating recall. Practical implications It can be said that in the first, second and third approaches, the components of the retrieval algorithm, the retrieval algorithm and crawler, and the retrieval algorithm and crawler and ranker, respectively, are evaluated. To determine the effectiveness of search engines for the use of users, it is better to use the third approach in recall measurement. Originality/value The value of this paper is to collect, identify and analyse literature that is used in recall. In addition, different views of researchers about recall are identified.
Research on a simulating device for electric transmission characteristics of long-distance subsea umbilical cable

Subsea umbilical cable is an important link to transmit power and signals in subsea production system, often lasts for tens of kilometers in deep-sea projects. It is expensive, bulky, and inconvenient to transport. In this article, a compact, low-cost umbilical cable electrical simulator is proposed, which can be equivalent to the real umbilical cable in power transmission characteristics and can adjust parameters in a certain range. By studying the electrical transmission characteristics of long umbilical cable, the calculation method of electrical transmission characteristics is determined. A simulation device for simulating the transmission characteristics of umbilical cable is designed, which can be used to simulate the umbilical cable diameter of 10 and 16 mm 2 . The voltage drop characteristics, signal transmission attenuation characteristics, and power carrier characteristics of the umbilical cable electrical simulation device are simulated and experimentally analyzed. The experimental results show that the voltage drop characteristics, signal transmission attenuation characteristics, and power carrier characteristics of the umbilical cable electrical simulator are in good agreement with the real umbilical cable. The simulation device of umbilical cable can well simulate the power and signal transmission characteristics of real umbilical cable.
Extracting Headless MWEs from Dependency Parse Trees: Parsing, Tagging, and Joint Modeling Approaches

An interesting and frequent type of multi-word expression (MWE) is the headless MWE, for which there are no true internal syntactic dominance relations; examples include many named entities (“Wells Fargo”) and dates (“July 5, 2020”) as well as certain productive constructions (“blow for blow”, “day after day”). Despite their special status and prevalence, current dependency-annotation schemes require treating such flat structures as if they had internal syntactic heads, and most current parsers handle them in the same fashion as headed constructions. Meanwhile, outside the context of parsing, taggers are typically used for identifying MWEs, but taggers might benefit from structural information. We empirically compare these two common strategies—parsing and tagging—for predicting flat MWEs. Additionally, we propose an efficient joint decoding algorithm that combines scores from both strategies. Experimental results on the MWE-Aware English Dependency Corpus and on six non-English dependency treebanks with frequent flat structures show that: (1) tagging is more accurate than parsing for identifying flat-structure MWEs, (2) our joint decoder reconciles the two different views and, for non-BERT features, leads to higher accuracies, and (3) most of the gains result from feature sharing between the parsers and taggers.
New Pieri Type Formulas for Jack Polynomials and their Applications to Interpolation Jack Polynomials

We present new Pieri type formulas for Jack polynomials. As an application, we give a new derivation of higher order difference equations for interpolation Jack polynomials originally found by Knop and Sahi. We also propose Pieri formulas for interpolation Jack polynomials and intertwining relations for a kernel function for Jack polynomials.
Realization and Optimization of Quantum Equivalent Circuits of Reversible Combinational Circuits

Energy dissipation is the important constrain in the design and implementation of VLSI circuits. Usage of Reversible logic circuit is the best solution for lower energy dissipation. In this paper, basic reversible gates and some existing gates and KMD gates are realized using the Quantum Equivalent structure and the Controlled- V and V + gate structure from their functional expression. Using the qubit gate reduction procedure of quantum circuit, the quantum cost and number of primitive gates of the functional expression are deduced. After synthesizing the Quantum Cost (QC), Gate count (GC), Garbage Output (GO), number of gates, constant inputs are compared with the non-optimized circuit. The quantum circuit and controlled V and V + structure are realized in RCViewer + tool using .tfc (“Toffoli-Fredkin Cascade”) code.
Gesture Classification for a Hand Controller Device Using Neural Networks.

This paper presents a convolutional neural network-based classification of the hand flexion and extension gestures used in wrist recovery after injury. The hand gesture recognition device used in our study is the Leap Motion controller. The Leap Motion device's inability to accurately differentiate the left hand from the right hand when performing hand rotation gestures was eliminated by introducing hand and thumb direction vectors into the database used to train the neural network. A 3D environment was created for the introduction of the data describing the gesture into the database. A classification accuracy of 95% was achieved for the hand flexion and extension gesture divided into three levels for each hand. The populated database may also be used to classify other gestures involving hand rotation.
Strategies for College Teachers Development in the Era of MOOC

The rapid popularization of "MOOC" (short for Massive Open Online Courses) around the world has brought college teachers abundant high-quality education resources and a lot of opportunities to display their talent, which has broadened their horizon on the teaching reform as well.MOOC has also brought a lot of challenges to college teacher's academic authority and innovation ability.College teachers should not stand still or refuse to make progress.Only by following the trend of big data era, cultivating innovation consciousness, keeping life-long learning, and especially improving information literacy, can the teachers transform resource advantages of MOOC into practicable advantages in their teaching.The development of modern educational technology has a profound impact on teaching.On the one hand, it promotes the reform of teaching methods, optimizes the teaching process, improves the teaching efficiency, and changes the teaching strategies and modes.On the other hand, it also changes the learning environment, improves learning approach, and effectively promotes personalized learning.Teaching is a creative activity, in this process, whether the teacher can reasonably and creatively use modern educational technology has become one of the key factors to improve the quality of teaching.Technological disadvantage and lack of teachers' capability will limit the development of online education.Therefore, it is necessary to further strengthen the research on the application of big data in education, and cultivate special interdisciplinary talents, so as to realize the educational ideal of "teaching students according to their aptitude" as soon as possible.Online education does have some advantages that traditional education cannot match, but we should not blindly overthrow the traditional education system or try to replace it with online education.Online education has actually incomparable advantages over traditional education, but it should be positioned as an important supplement to traditional education, because face-to-face communication between people is still playing an important part of education, and the teacher's guidance to students is still playing a key role in teaching as well.We should not blindly pursue technology, but should adhere to the essence of education.Integration of online and offline teaching will promote the development of education.
Optimization of English Automated Translation Depending on Weak Grammar Rules

Abstract Machine translation was first produced in the 1940 s, it with birth of computer technology and a new subject, the purpose of machine translation is to use computers as a platform for natural language translation, but for complex languages, machine translation is still lacking. Most of the language mechanisms formed by machine translation are crude and rely too much on the manual summary of language experts. In this way, it is easy for translation errors to occur in machine processing languages. In this case, how to effectively improve English machine translation under weak grammar rules has become a major problem that has not been solved in the computer field. This paper firstly analyses the principle of English machine translation and the improvement method of English machine translation under the weakening of grammar rules, and proposes an improvement and optimization method of English machine translation under the weakening of grammar rules.
Data Mining for Big Dataset-Related Thermal Analysis of High Performance Computing (HPC) Data Center

Greening of Data Centers could be achieved through energy savings in two significant areas, namely: compute systems and cooling systems. A reliable cooling system is necessary to produce a persistent flow of cold air to cool the servers due to increasing computational load demand. Servers’ dissipated heat effects a strain on the cooling systems. Consequently, it is necessary to identify hotspots that frequently occur in the server zones. This is facilitated through the application of data mining techniques to an available big dataset for thermal characteristics of High-Performance Computing ENEA Data Center, namely Cresco 6. This work presents an algorithm that clusters hotspots with the goal of reducing a data centre’s large thermal-gradient due to uneven distribution of server dissipated waste heat followed by increasing cooling effectiveness.
Compensated Pulse Response Analysis of Ship Motor in Marine Environment Based on Electromagnetic Theory

Li, X.; Yu, M., and Hou, H., 2020. Compensated pulse response analysis of ship motor in marine environment based on electromagnetic theory. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 382–386. Coconut Creek (Florida), ISSN 0749-0208.In the geomagnetic environment, due to the existence of electromagnetic field in sea water, the vibration and time slot disturbance error of the ship's motor are caused, which affects the ship's pulse response. Firstly, the controlled object is described, and the control constraints are analyzed according to the receiving coil of the marine motor, and the control objective function is constructed to realize the control of the motor. According to the control objective function, the time slot interference error of the marine motor is compensated, and the impulse response of the motor is obtained. The BLT equation is established by applying the theory of electromagnetic topology, and the parameters of the equation are set. The scattering matrix, propagation matrix and excitation matrix of BLT equation are solved, and the compensation pulse response is analyzed. The experimental results show that the distribution of the whole magnetic field and the local magnetic field is balanced.
Parameterised Verification of Strategic Properties in Probabilistic Multi-Agent Systems

We present a framework for verifying strategic behaviour in an unbounded multi-agent system. We introduce a novel probabilistic semantics for parameterised multi-agent systems and define the corresponding verification problem against two probabilistic variants of alternating-time temporal logic. We define a verification procedure using an abstract model construction. We show that the procedure is complete for one variant of our specification language, and partial for the other. We present an implementation and report experimental results.
Uncertainty-Driven Semantic Segmentation through Human-Machine Collaborative Learning

Deep learning-based approaches achieve state-of-the-art performance in the majority of image segmentation benchmarks. However, training of such models requires a sizable amount of manual annotations. In order to reduce this effort, we propose a method based on conditional Generative Adversarial Network (cGAN), which addresses segmentation in a semi-supervised setup and in a human-in-the-loop fashion. More specifically, we use the discriminator to identify unreliable slices for which expert annotation is required and use the generator in the GAN to synthesize segmentations on unlabeled data for which the model is confident. The quantitative results on a conventional standard benchmark show that our method is comparable with the state-of-the-art fully supervised methods in slice-level evaluation requiring far less annotated data.
Text Mining Analysis of Comments in Thai Language for Depression from Online Social Networks

The objectives of this research were to analyze the relationship of the phrases or words commonly found in the comments from depression hashtag on Twitter using the association rules. The data used in this study were collected from comments in Thai language via depression hashtag on Twitter during 1 January 2019 to 31 January 2019, in total of 1,500 comments. According to the comments in Thai language on social media collected by using Rapidminer Studio 9 software to get the word about depression and used to analyze relationships of words from a text comment to get the format data Association. The frequency of words and phrases in a form of presentation is used to describe the various opinions about the depression that has a presentation on social media. According to the model performance in each of the above methods, it was found that Euclidean Distance provided the best result due to the smallest average distance at all points in each cluster which was equal to 152.504. The association analysis, a total of 30 association rules were obtained, the support of 0.5% and the 80% confidence.
Score level fusion in representation-based classification method for face recognition

Recent years have witnessed the success of representation-based classification method (RBCM) in the domain of face recognition. Collaborative representation-based classification (CRC) and linear regression-based classification (LRC) are two representative approaches. CRC is a global representation method which uses all training samples to represent test samples and utilizes representation residuals to perform classification, whereas LRC is a local representation method which exploits training samples from each class to represent test samples. Related researches indicate that the combination of LRC and CRC can fully exploit the representation residuals produced by them, thus improving the performance of RBCM. However, the representation coefficients obtained by CRC usually contain negative values which may result in overfitting problem. Therefore, to solve this problem to some extent, the combination of LRC and non-negative least square-based classification (NNLSC) is proposed in this paper. Experimental results on benchmark face datasets show that the proposed method is superior to the combination of LRC and CRC and other state-of-the-art RBCMs. The source code of our proposed method is available at https://github.com/li-zi-qi/score-level-fusion-of-NNLS-and-LRC .
Did That Lost Ballot Box Cost Me a Seat? Computing Manipulations of STV Elections

Mistakes made by humans, or machines, commonly arise when managing ballots cast in an election. In the 2013 Australian Federal Election, for example, 1,370 West Australian Senate ballots were lost, eventually leading to a costly re-run of the election. Other mistakes include ballots that are misrecorded by electronic voting systems, voters that cast invalid ballots, or vote multiple times at different polling locations. We present a method for assessing whether such problems could have made a difference to the outcome of a Single Transferable Vote (STV) election – a complex system of preferential voting for multi-seat elections. It is used widely in Australia, in Ireland, and in a range of local government elections in the United Kingdom and United States.
Pictures on the second homotopy module of the group from Kronecker product on the representation quaternion group

Abstract This paper discusses pictures on the second homotopy module of the group from the Kronecker product on the representation quaternion group. It needs three notions to construct the second homotopy module, which is the presentation of the group, word, and spherical picture. In this paper, it has used the presence of a group that is obtained from the group Kronecker product on the representation of the quaternion group. This presentation has four generators and five relations. Based on this presentation, we got word, and then a picture can be drawn. It uses van Kampen Lemma to construct the picture and operation on picture to obtain a spherical picture. It has presented pictures with one and all of the generators in the presentation of the group. It has used relations in the presentation of a group to make the picture become a spherical picture. We conclude that the spherical picture, which becomes generators built all pictures.
Intention-Aware Multiagent Scheduling

The Belief Desire Intention (BDI) model of agency is a popular and mature paradigm for designing and implementing multiagent systems. There are several agent implementation platforms that follow the BDI model. In BDI systems, the agents typically have to pursue multiple goals, and often concurrently. The way in which the agents commit to achieving their goals forms their intentions. There has been much work on scheduling the intentions of agents. However, most of this work has focused on scheduling the intentions of a single agent with no awareness and consideration of other agents that may be operating in the same environment. They schedule the intentions of the single-agent in order to maximise the total number of goals achieved. In this work, we investigate techniques for scheduling the intentions of an agent in a multiagent setting, where an agent is aware (or partially aware) of the intentions of other agents in the environment. We use a Monte Carlo Tree Search (MCTS) based approach and show that our intention-aware scheduler generates better outcomes in cooperative, neutral (selfish) and adversarial settings than the state-of-the-art schedulers that do not consider other agents' intentions.