Reviewerly/exHarmony huggingface dataset:
Sinhala and English Document Alignment using Statistical Machine Translation

Document alignment is the process of identifying documents that have the same content in different languages. Document alignment is a very useful prerequisite for creating parallel corpora to be used in Machine Translation (MT). Hybrid document alignment techniques are commonly used, where a set of heuristics are used along with an existing MT system. In these systems, first all the target documents are translated into source language using an existing MT system. Candidate pairs are identified using a heuristics such as web domain or published date. Similarity of these candidate pairs is calculated using a similarity calculation algorithm. Heuristics are used either to reduce the candidate pair count or to improve the accuracy of alignment. However, the considered heuristics are dependent on the selected document sources. In this paper, we present a hybrid document alignment system for Sinhala and English, where a set of source-independent heuristics is used on the output of an MT system. In addition, we demonstrate how transliteration between Sinhala and English is exploited to improve the performance of the document alignment process.
Illocutionary Act Used By Muniba Mazari In Inspirational And Motivational Video On Youtube

This study aimed explaining the pragmatic study of the follow-up, which is about the types of action, direct or indirect language and the context of speech used in Muniba Mazari in motivational videos on YouTube. It is expected to provide insight to the reader about types of illocutionnary act in order to improve pragmatic competence. The research was presented in a qualitative form because the data were presented in sentence form. The data were collected from Muniba Mazari’s speech. This research also applies the theory of J. R Searle (1979) on the follow-up to identify the types of follow-up, context, and meaning of sentences. Further, this study used the theory of Geogre Yule (1996) to know the language style directly or indirectly. The results of this study showed that there were 44 data found in the video of Muniba Mazari. They are: telling (3), claiming (3), sating (4), affirming (7), describing (9), suggesting (2), commanding (2), warning (3), vowing (3), promising (3), declaring (1), thanking (3), disliking (1). The most dominant in Muniba Mazari’s speech were representatives. It is because Muniba often reveals and informs about her life story to motivate the audience. Keywords: pragmatic, Illocutionary act, stydirect speech act, indirect speech acts
Review of State-of-Art Image Restoration Techniques

In recent years, image processing is an essential technique for most of the applications such as business, government sectors, medial industry, cinema field, and etc. In image processing, most of the subdomains are there which helps to do their respective process. Among that, Image Restoration (IR) is one of the important domain which helps to retrieve the original image information from the noisy image. Normally, input image is affected by noise during the transmission. So, noise need to be removed to get the original input image information. In this paper, different kind of IR techniques are explained which is implemented in Field Programmable Gate Array (FPGA). In VLSI domain, FPGA is the important process which is used to identify the hardware utilization of the entire algorithm. The process and different methods of IR is studied in this paper.
Text Visualization Using t-Distributed Stochastic Neighborhood Embedding (t-SNE)

Data visualization is most important task to be done before classification and building a model. By data visualization we can easily know whether problem is directly classifiable or not. Below paper contains presentation of t-SNE visualization for donors choose data vectorized by different techniques like Term frequency-inverse document frequency, Bag of words, Tf-Idf weighted Word2Vec. Data visualization here means indirectly reducing dimensions of our data. Different data visualizations in below paper are done using different perplexity values of t-SNE. Pre-processing and vectorization are done accordingly for different features and numerical features are standardized before giving it to t-SNE.
Security and Privacy Aspects Using Quantum Internet

Quantum internet is an innovative approach to secure communication. Quantum internet is the next revolution in technology that enables the devices to perform operations that are beyond the classical internet. Quantum internet with quantum cryptography is one of the best solutions for secure data communication. Quantum internet uses the fundamental laws of quantum physics, which make it secure against sophisticated network attacks. In this research, the authors described quantum cryptography, which enhances the secure transmission over quantum internet using cryptographic protocols. These protocols use random bits transformations, which prevent attackers to make out the patterns of random bits transformations. Also, they introduced the conceptual OSI model for quantum internet, which makes it easy to understand the working of the quantum internet at different layers. Quantum internet can be implemented in intelligence network, satellite communication, critical infrastructure, etc. This can mark a significant change in secure communication.
IMPLEMENTATION OF AUTHOR CONCEPT OF I. O. SIKORSKY IN THE ACTIVITIES OF THE KIEV FROEBEL PEDAGOGICAL INSTITUTE (1907–1920)

The article carries out a retrospective logical-system analysis of the scientific heritage of the first rector of the Kiev Froebel Pedagogical Institute I.O. Sikorsky (1842–1919) – a doctor of medicine, a well-known teacher and psychologist, a professor of the University of St. Volodymyr, chairman of the Kiev Froebel Society of the Promotion of Education. It was found out that the scientist considered the comprehensive knowledge of the child by a chain that unites family and school, and the integration of knowledge on psychology, medicine, upbringing and development of the family was a foundation for effective education of the individual. The interpretation of the ultimate goal of education by I.O. Sikorsky defined as the achievement of harmonious development of the spirit and body, mental and physical, as the balance of mental, moral and aesthetic principles. The directions and mechanisms of implementation of the author's medical-psychological-pedagogical concept I.O. Sikorsky are investigated in the content of vocational and pedagogical training of the Kiev Froebel Pedagogical Institute (1907–1920).
Facial Expression Recognition System Using a Neural Network and Simulation on FPGA

The objective of the proposed algorithm is to recognize facial expressions from digital images. There are specific and predefined features of the image that need to be extracted to detect facial expressions. As an example, 21 points can be identified in the human face that changes as a result of emotional states. Also by following these feature points, facial expressions can be detected. In this paper, the MLP neural network is employed to classify facial expressions. Moreover, edge detection is used to find and disassemble facial parts. After designing an accurate algorithm, it is modeled using MATLAB programing for an FPGA chip by hardware description language VHDL. Face images have been preprocessed in few steps including binary image conversion and noise elimination. Then, feature extraction has been performed on images, and eight features have been selected. A neural network was then designed with eight neurons in the input layer, seven neurons in the hidden layer, and six neurons in the output layer. To test and quantify the results, the JAFFE dataset has been used. By performing different simulations, we observe that the average accuracies of the proposed algorithm in MATLAB and Quartus for facial expression recognition are 91.76% and 86.67% respectively.
Secure and Traceable Attribute-Based Sequential Aggregate Signature

Attribute-based signatures allow a signer with a set of attributes to anonymously sign a message about some signature policy. However, in the environments that require accountability and preventing abuse, the anonymity revocation function is vital important and necessary. In order to meet the requirements that multiple different authorized participants can sequentially aggregate and sign the same message while maintain the accountability of the signers, we propose a secure and traceable attribute-based sequential aggregate signature scheme with multiple attribute authorities. It is based on the flexible threshold access structure, and it also supports extension to any linear secret sharing scheme access structures. Our scheme can be proved secure under the CDH assumption and subgroup decision assumption in the selective model without random oracle. The security analysis shows that our attribute-based sequential aggregate signatures scheme can realize existential unforgeability, traceablity and unlinkability. It is believed that it can also be widely used in e-commerce and e-government related applications.
Automatic Detection of Landmarks for Fast Cardiac MR Image Registration

Inter-subject registration of cardiac images is a vital yet challenging task due to the large deformations influenced by the cardiac cycle and respiration. Various intensity-based cardiac registration methods have already been proposed, but such methods utilize intensity information over the entire image domain and are thus computationally expensive. In this work, we propose a novel pipeline for fast registration of cardiac MR images that relies on shape priors and the strategic location of surface-approximating landmarks. Our holistic approach to cardiac registration requires minimal user input. It also reduces the computational runtime by $$60\%$$ on average, which amounts to an 11-min speedup in runtime. Most importantly, the resulting Dice similarity coefficients are comparable to those from a widely used elastic registration method.
Application of Reversible Data Hiding for Printing with Special Color Inks to Preserve Compatibility with Normal Printing

We propose an efficient framework with compatibility between normal printing and printing with special color inks in this paper. Special color inks can be used for printing to represent some particular colors and specific optical properties, which are difficult to express using only CMYK inks. Special color layers are required in addition to the general color layer for printing with special color inks. We introduce a reversible data hiding (RDH) method to embed the special color layers into the general color layer without visible artifacts. The proposed method can realize both normal printing and printing with special color inks by using a single layer. Our experimental results show that the quality of the marked image is virtually identical to that of the original image, i.e., the general color layer.
Ecosystem Preparedness &amp; Learning 4.0: A Case Study of Higher Education Scenario in Goa

The study aims to measure the preparedness of the Higher Educational Ecosystem in terms of computer and network technology to implement Learning 4.0 in the state of Goa. The gap analysis between the learning 4.0 scenario and the current situations has been done. Digital network platforms and devices are one of the major drivers of Learning 4.0. The strength of these drivers in the study is based on three aspects of an institution the competency of teachers in understanding and adapting digital technology, the competency of students in using digital technology and the digital environment / ecosystem in the institute. Each of these aspects was measured on a scale 0-1 with higher values indicating a positive outcome for the aspect. From the survey conducted over 5000 students studying in the Colleges in Goa, it was observed that there is more scope for teachers to take initiatives in using digital technology in the curriculum whereby making the students learn about the latest technology available. Additional efforts are required in motivating and encouraging the teachers to efficiently use digital technology in the process of teaching-learning. In case untoward incidents arise, it becomes difficult for students and teachers to be present in a classroom. Expertise in efficient usage of digital technology in the process of teaching-learning may ensure that under such circumstances, teaching-learning is not hampered.
Marine TT&amp;C Software Quality Evaluation based on AHP and FCE

This paper analyzes the requirements of TT& C task marine TT& C software quality assurance and ability evaluation for perform task, designs a fuzzy comprehensive evaluation model for the quality marine TT& C software, constructs a comprehensive evaluation index system for the quality of marine TT& C software, and puts forward a fuzzy comprehensive evaluation model based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) to evaluate the task software quality and ability to perform task. The actual application results show that the application of AHP and FCE in the evaluation of the performing task ability of marine TT& C software is feasible. The method and model can evaluate the performing task ability of marine TT& C software comprehensively, and has been applied to the task preparation nicely.
On the Development Community of Foreign Language Teachers in Colleges and Universities Based on the Internet

With the continuous development and progress of science and technology in China, more and more schools and teachers are beginning to combine the "Internet" technology for teaching. Under the background of the Internet, teachers should strive to create a relaxed, equal and democratic atmosphere in the classroom, so that they can impart knowledge to students well and students can master it better. In campus, both tacit knowledge and explicit knowledge need teachers to keep pace with the times, give full play to the advantages of computer and Internet, and effectively impart knowledge to students. By the combination of "Internet" and foreign language teaching in colleges and universities, the community teaching mode has made the foreign language curriculum in colleges and universities better developed. Under the background of "Internet ", the community construction of teachers' professional development makes teachers' professional development closely related to the Internet, which is the inevitable trend of teachers' professional development.
Articulatory-to-Acoustic Conversion of Mandarin Emotional Speech Based on PSO-LSSVM

The production of emotional speech is determined by the movement of the speaker’s tongue, lips, and jaw. In order to combine articulatory data and acoustic data of speakers, articulatory-to-acoustic conversion of emotional speech has been studied. In this paper, parameters of LSSVM model have been optimized using the PSO method, and the optimized PSO-LSSVM model was applied to the articulatory-to-acoustic conversion. The root mean square error (RMSE) and mean Mel-cepstral distortion (MMCD) have been used to evaluate the results of conversion; the evaluated result illustrates that MMCD of MFCC is 1.508 dB, and RMSE of the second formant (F2) is 25.10 Hz. The results of this research can be further applied to the feature fusion of emotion speech recognition to improve the accuracy of emotion recognition.
Identification of Brand Logos from Video Feed

In this paper we have made an attempt to build a Machine Learning model based on Yolo algorithm to calculate the brand visibility of sponsored advertisements during live sports events such as cricket matches and based on brand visibility, we have calculated effective and accurate advertising cost. To calculate the brand visibility, we have restricted ourselves to brand logos only which are visible on cameras. As a result of our analysis, we observed that in a cricket match Brand A had 26% visibility while brand B had 67% visibility and yet brand A was charged much higher than brand B by the advertising companies and hence machine learning based analytical tools can be of great use while effectively calculating the advertising costs.
Research on BOLD-fMRI Data Denoising Based on Bayesian Estimation and Adaptive Wavelet Threshold

The acquisition of functional magnetic resonance imaging (fMRI) images of blood oxygen level-dependent (BOLD) effect and the signals to be analyzed is based on weak changes in the magnetic field caused by small changes in blood oxygen physiological levels, which are weak signals and complex in noise. In order to model and analyze the pathological and hemodynamic parameters of BOLD-fMRI images effectively, it is urgent to use effective signal analysis techniques to reduce the interference of noise and artifacts. In this paper, the noise characteristics of functional magnetic resonance imaging and the traditional signal denoising methods are analyzed. The Bayesian decision criterion takes into account the probability of the total occurrence of all kinds of references and the loss caused by misjudgment and has strong discriminability. So, an improved adaptive wavelet threshold denoising method based on Bayesian estimation is proposed. By using the correlation characteristics of multiscale wavelet coefficients, the corresponding wavelet components of useful signals and noises are processed differently; while retaining useful frequency information, the noise is weakened to the greatest extent. The new adaptive threshold wavelet denoising method based on Bayesian estimation is applied to the actual experiment, and the results of OEF (oxygen extraction fraction) are optimized. A series of simulation experiments are carried out to verify the effectiveness of the proposed method.
Tracking Stability of Software Evolution Using Statistical Process Control Limit

The way software systems evolve is a process that needs strict and careful tracking, monitoring and evaluation; it is therefore pertinent that software evolutionary cyclical states are tracked, monitored and analyzed to ensure that the process does not get out of control, guaranteeing the stability of the software system as it evolves. This research utilized a statistical process control approach to monitor, track and evaluate whether the change process is in control or not, and discover situations where the process is in or out of kilter. Statistical process control provides the means through which a process stability can be analyzed, controlled and managed. Some of the contributions of this research include the introduction of SCAR metric that allows the collapsing of data about software module maintenance activities over the period in which the software system evolves; and a methodology that helps monitor and track software evolution process guaranteeing that it does not move towards chaos, degradation and decay.
Power Analysis Side-Channel Attacks on Symmetric Block Cipher Magma.

This paper presents an overview of power analysis side-channel attack and experimental results of power consumption measurements charts for encryption algorithm Magma (GOST R 34.12 - 2015 (n = 64)). Magma cipher was implemented at Arduino electric board (namely Arduino Uno). Measurements were made by using a LECROY WavePro 7100A oscilloscope with a 1 GHz bandwidth and 10 GHz / 4 channel sampling frequency. Our experiments led to finding segments and getting power value of each encryption operations and marked segments of each encryption rounds.
The Resource Scheduling Algorithm of Energy Consumption Optimization

This for the relatively large random tasks in cloud computing system, the resource scheduling algorithm of energy consumption optimization (RSEC) based on the task patience value was proposed. The executed tasks of cloud system were studied. The concept of relaxation time was brought forth and the task time-out patience function was defined. The waiting time of the tasks were reduced by adjusting the allocation of resources. The patience function value can be calculated through the current network important level and the duration of time of task execution in cloud system. The energy consumption model of resource scheduling based on the task patience value was proposed and the resource scheduling algorithm was designed to optimize energy consumption. The experiments show that the proposed algorithm can optimize the energy consumption much better than those previously mentioned algorithms.
Forecast and Energy Management System (F-EMS) Framework for Optimal Operation of Sewage Treatment Plants

Aeration processes at Gujarat Infrastructure and Financial Tec (GIFT) city's sewage treatment plant (STP) account upto 40% of entire STP's energy demand. Solar photovoltaic (PV) rooftop rated 15kW and 10kWh battery energy storage system (BESS) will be installed to address the energy demand of aeration blower locally. In this paper an extreme gradient boost (XGboost) based solar PV forecast algorithm together with linear programming (LP) based energy management system (EMS) algorithm is developed as a framework namely “F-EMS” to optimally charge or discharge BESS to address varying energy demand of aeration blower. The analysis is carried out considering realistic load data of aeration blower and constraint of aeration process, BESS, and utility grid. The efficiency of EMS algorithm depends on accuracy of solar PV forecast where the XGboost based forecast algorithm predicts the solar PV generation with good accuracy i.e. less than 4% of root mean square error (RMSE) during worst fluctuating day. On analysis it was found that by implementing the F-EMS framework, a maximum of savings upto 20% on aeration blower's electricity bills can be achieved.
Case study: To identify the students that participating in the Cheer activity of the Faculty of Engineering, KMITL by using Near Field Wireless communication

This article presents wireless communication technology with NFC. In this case study, it is about using the NFC to identify the freshmen one by one that participating in the Cheer activity of the Faculty of Engineering, KMITL of the first-year students of 800 students, duration ten days. From the experiment results, when using the application, it can be used to check the names of students who have participated in the activity with 100 percent accuracy.