Reviewerly/exHarmony huggingface dataset:
Speech Synthesis in the Translation Revision Process: Evidence from Error Analysis, Questionnaire, and Eye-Tracking

Translation revision is a relevant topic for translator training and research. Recent technological developments justify increased focus on embedding speech technologies—speech synthesis (text-to-speech) and speech recognition (speech-to-text)—into revision workflows. Despite some integration of speech recognition into computer-assisted translation (CAT)/translation environment tools (TEnT)/Revision tools, to date we are unaware of any CAT/TEnT/Revision tool that includes speech synthesis. This paper addresses this issue by presenting initial results of a case study with 11 participants exploring if and how the presence of sound, specifically in the source text (ST), affects revisers’ revision quality, preference and viewing behaviour. Our findings suggest an improvement in revision quality, especially regarding Accuracy errors, when sound was present. The majority of participants preferred listening to the ST while revising, but their self-reported gains on concentration and productivity were not conclusive. For viewing behaviour, a subset of eye-tracking data shows that participants focused more on the target text (TT) than the source regardless of the revising condition, though with differences in fixation counts, dwell time and mean fixation duration (MDF). Orientation and finalisation phases were also identified. Finally, speech synthesis appears to increase perceived alertness, and may prompt revisers to consult external resources more frequently.
The need for input control in mathematics at a higher education institution

The article deals with the problem of transition from one level of education (school) to another (highe education institution). Special attention is paid to the problem of mathematical training of future students. Test exam scores obtained by school graduates do not guarantee that the freshman understands the foundation of basic mathematical knowledge, and very often in practice it appears to be that a freshmen has significant gaps. The article deals with the input control as one of the elements of thepedagogic system that can give an idea of the actual state of the object. After analysing various sources, as well as summarising their practical experience with the experience of teachers at other higher education institutions, the authors come to the conclusion about the need for input control in order to determine the degree of readiness of the pupil to the next stage of educational activity – the development of competences at a higher education institution.
Sistem Monitoring Tanah Longsor Berbasis Internet of Things dan Geographic Information System

Landslide is one of the natural disasters that happens quite often in many parts of Indonesia. Landslide brings negative aspects to people because it causes material loss and loss of life. Landslides generally occur in the rainy season with high rainfall. In this research, a system is made to predict the chance of landslide to happen by measuring the level of rainfall, soil moisture, and soil displacement, and send the sensor data and position of a landslide to the database. According to this research, the system can predict the chance for the landslide to happen and give a warning with a 100% success rate.
Role of indistinguishability in interferometric phase estimation

We report a theoretical and experimental study on the role of indistinguishability in the estimation of an interferometric phase. In particular, we show that the quantum Fisher information, which limits the maximum precision achievable in the parameter estimation, increases linearly with respect to the degree of indistinguishability between the input photons in a two-port interferometer, in the ideal case of a pure probe state. We experimentally address the role played by the indistinguishability for the case of two photons entering a polarization-based interferometer, where the degree of indistinguishability is characterized by the overlap between two spatial modes. The experimental results support the fact that, even in the presence of white noise, a quantum enhancement in the interferometric phase estimation can be obtained from a minimum degree of indistinguishability.
Results of applicability analysis of satellite observations and reanalysis data for autonomous photovoltaic unit simulation

The accuracy analysis of energy performance prediction of autonomous photovoltaic units using various climate databases (NASA POWER, SARAH-E, CLARA-A, ERA5, Meteonorm, etc.) for some geographic points in Russia was performed by comparing with calculations using data of World Radiation Data Center. It is shown that the considered databases provide a spread of predictions of the required power of solar battery at the level of 10-20% only when solar fraction is less than 70%. For larger solar fraction, the prediction error of the required power of solar battery can reach hundreds of percent.
Self-Adaptation of mHealth Devices: The Case of the Smart Cane Platform

Nowadays, more than one billion people are in need of one or more assistive technologies, and this number is expected to increase beyond two billion by 2050. The majority of assistive technologies are supported by battery-operated devices like smartphones and wearables. This means that battery weight is an important concern in such assistive devices because it may affect negatively its ergonomics. Saving power in these assistive devices is of utmost importance for its potential twofold benefits: extend the device life and reduce the global warming aggravated by billion of these devices. Dynamic Software Product Lines (DSPLs) are a suitable technology that supports system adaptation, in this case, to reduce energy consumption at runtime, considering contextual information and the current state of the device. However, a reduction in battery consumption could negatively affect other quality of service parameters, like response time. Therefore, it is important to trade-off battery saving and these other concerns. This work illustrates how to approach the self-adaptation of smart assistive devices by means of a DSPL-based strategy that optimizes battery consumption taking into account other QoS parameters at the same time. We illustrate our proposal with a real case study: a Smart Cane that is integrated with a DSPL platform, Tanit. Experimentation shows that it is possible to make a trade-off between different quality concerns (energy consumption and relative error). The results of the experiments allow us to conclude that the Tanit approach elongates battery duration of the Smart Cane in one day (an increase of a 6% with a relative error of 1%), so we improve the user quality of experience and reduce the energy footprint with a reasonable relative error.
Detecting ${\boldsymbol~A}{\boldsymbol~B}{\boldsymbol~\rightarrow}{\boldsymbol~C}$ steering in tripartite quantum systems

In this paper, the detection problem of $AB\\rightarrow~C$ steering is discussed. Firstly, we give some relationships between the $AB\\rightarrow~C$ steering of $\\rho^{ABC}$ and $A\\rightarrow~C$ steering of the reduced state $\\rho^{AC}$ as well as $B\\rightarrow~C$ steering of the reduced state $\\rho^{BC}$ based ontheir definitions. Secondly, by deducing an inequality (called an steering inequality) for $AB\\rightarrow~C$ unsteerable states, a necessary condition for a quantum state to be $AB\\rightarrow~C$ unsteerable is obtained. Furthermore, the steering radius $S(\\rho)$ of a state $\\rho$ is defined and it is proved that when $\\rho$ is $AB\\rightarrow~C$ unsteerable, $S(\\rho)\\le1$ and that when $S(\\rho)>1$, $t\\rho+(1-t)\\eta$ is $AB\\rightarrow~C$ steerable for each $t_0<t\\le1$ and for each $AB\\rightarrow~C$ unsteerable state $\\eta$ where $t_0=\\frac{2}{S(\\rho)+1}$.Finally, $AB\\rightarrow~C$ steerability of the “partial convex combinations of the GHZ state, generalized GHZ state and the W-state with a $AB\\rightarrow~C$ unsteerable state are detected, respectively by using the obtained steering inequality.
Learning From Students’ Experiences in Writing Paragraph

&lt;p&gt;This article aims to describe the students' ability in writing a paragraph. It is a descriptive qualitative in which the number of respondents is 60 students. All samples are taken from the guided writing class as the first subject series of a writing class. The data collection is obtained through a number of assignments they did and uploaded in a blog. From all assignments of writing task, only six assignments of writing task were taken and analyzed, based on top ones in writing quality starting from topic sentence, supporting sentences, and concluding sentence. Based on the analysis result, students’ ability is located on weakness in determining the topic sentence, starting the topic sentence, and writing supporting sentences. Their weakness appears because of the inability to formulate the topic, topic sentence, and difficulty to find the relevant supporting sentences to write for supporting the topic sentence. The inability of formulating topic, topic sentence, and supporting sentences contributes towards inability to apply the unity knowledge in making supporting sentences united.&lt;/p&gt;
Novel visual tracking approach via ant lion optimiser

Ant lion optimiser (ALO) is a new nature-inspired swarm intelligence optimisation algorithm that mimics the hunting mechanism of antlions in nature. ALO has been proved to have the merits of high exploitation and convergence speed benefiting from adaptive boundary shrinking mechanism and elitism. In this work, visual tracking is expressed as searching for object in whole search space by interaction between antlions and ants. A novel ALO-based visual tracking framework is proposed and the adaptation and sensitivity of the parameters in ALO are discussed to improve tracking performance. In addition, considering that ALO tracker needs a lot of iteration consumption, kernel correlation filter with deep feature is integrated into the ALO tracking framework (ALOKCF) to improve track efficiency. Extensive experimental results prove that the ALO tracker is very competitive compared to other trackers, especially for abrupt motion tracking. At the same time, two visual tracking benchmarks are used to verify ALOKCF tracker achieves state-of-the-art performance.
Functional semantics annotation of assembly model using the fusion of bag of relationships model and spectral technology

Increasing attention has been paid to the effective management and reuse of CAD model resources. Aiming at the problems of low efficiency of model reuse and poor accuracy in the function labeling process of assembly models, this paper presents an effective probability-based model labeling strategy for complex assemblies. It is a proper method to realize automatic labeling of assembly functional semantics through active learning. Different from part model retrieval, an assembly model is described through graph theory and a bag-of-relationships model. The assembly relationships of assembly model and the information of key functional parts are considered synthetically. Then a two-tiered model retrieval mechanism is constructed to reduce the computation time cost and improve retrieval efficiency. Further, the concept of functional ontology is introduced to establish the normalized expression of the key functional semantics of the assembly model. The functional semantic annotation of the key parts of the CAD assembly model is carried out through a probability-based labeling framework to map the model shape structure to functional semantics, thus mitigating the “semantic gap” problem. Experimental results demonstrated that this method could improve the accuracy of functional semantic annotation of the assembly model, reduce the difficulty of labeling, and improve the reusability of 3D CAD models as a design resource.
PERANCANGAN APLIKASI CATALOG WISATA DI SUMATERA UTARA MENGGUNAKAN ALGORITMA RABIN-KARP

String matching is the process of finding all occurrences of a query or called a pattern into a string or text. String matching is a string or word matching that is used in the problem to find the pattern of string characters in a sentence. String matching is a technique in determining the accuracy of a given text pattern. Attractions in North Sumatra is one of the most popular tourist destinations in North Sumatra, Lake Toba because of the beautiful scenery of many outsiders or foreigners also visit the tour. Lack of information about North Sumatra tourism objects, the authors designed a tourism catalog to help the community in finding the latest attractions in North Sumatra such as natural attractions, historical tourism, religious tourism and many more can we visit the attractions around North Sumatra. The Rabin-Karp algorithm is a hashing function to find patterns in a string. In searching a travel catalog with the Rabin-Karp algorithm, it is very suitable to use because the Rabin-Krap algorithm is used to search for a word contained in a travel search. So that the testing phase requires eclipse software in the design of making travel catalogs.Keywords: String Matching, Attraction, Tourism Catalog, Rabin-Karp Algorithm, Eclipse
PROFESSIONAL COMPETENCE AS A KEY FACTOR IN IMPROVING THE QUALITY OF ENGINEERING EDUCATION

The integration of Ukraine into the European community is impossible without changes in the education sphere. The implementation of such projects of the European Union as "Horizon 2020” provides the collaboration between experts in Agriculture and Engineering. The results of the questionnaire conducted by “Agro Survey” agency showed the lack of student’s practical knowledge in Ukrainian Engineering and Agricultural universities. It is obvious that the quality of education in Ukrainian technical universities doesn't meet the requirements of the European labour market. Getting theoretical knowledge has no value until students can apply it for practical purposes. We suggest that a subject like Physics should be practice-oriented. If the Physics course at technical universities integrates theory with practice, students will be better prepared for their future career. The purpose of the study is to define the basic principles of professional competence as the key factor for improving the quality of future engineer’s training in the process of studying Physics. To select and interpret the factual material, concepts and theories the theoretical analysis of philosophical, psychological and pedagogical literature on research was used in the paper. The pedagogical experiment was carried out on the basis of 4 universities in different regions of Ukraine and involved 159 respondents (151 students and 8 university teachers). To determine the strategies for implementation of the profession-based tasks in Physics course we carried out specially designed questionnaires for students majoring in Agrarian Engineering and university teachers. One of the necessary conditions for future engineer training is professional orientation in studying. We suppose that to consider the relationship between a comprehensive Physics course and the disciplines of professional and practical training the in-depth analysis should be performed. First of all, it will help to determine Physics knowledge, abilities and skills that should be used in student’s further professional training. Second of all, it will enable the most effective use of engineering-based tasks in Physics classes. However, knowledge of basic Engineering and General Theoretical subjects is not applied by the students of Technical High School for a long-period of university study. The results of the survey have shown that studying major subjects at a later stage doesn’t motivate students to learn Natural Science and Engineering disciplines. We can conclude that profession-based tasks in Physics class contribute to the formation of a system of natural knowledge, practical skills and abilities. They stimulate the students’ cognitive interest in Physics as a science, help to better absorb material of other disciplines, develop creative abilities and influence the formation of persistent motifs for obtaining knowledge of professional disciplines.
SYSTEM FOR DIFFERENTIAL CORRECTION AND MONITORING AS THE BASE OF THE NEXT GENERATION NATIONAL INFRASTRUCTURE FOR NAVIGATION AND HIGH-PRECISION POSITIONING

The Russian System for Differential Correction and Monitoring (SDCM) is introduced. The current role of SDCM as a provider of positioning navigation and timing services is described. It is shown that the next generation infrastructure for high-precision positioning can be based on SDCM.
Testing Artificial Intelligence

In AI, the algorithm is not coded but produced by a combination of training data, labelling (concepts) and the neural network. This is the essence of machine learning. The algorithm is not directly insightful and cannot be bug-fixed directly: it is “black box development”. AI systems are used in contexts with diverse data and usage. Choice in training data and labels brings risks in bias and transparency with possible high impact on real people. Testing AI focusses on these risks. An AI tester needs moral, social and worldly intelligence and awareness to bring out the users, their expectations and translate these in test cases that can be run repetitively and automated. AI testing includes setting up metrics that translate test results in a meaningful and quantifiable evaluation of the system in order for developers to optimize the system.
Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists

Language Models (LMs) are important components in several Natural Language Processing systems.Recurrent Neural Network LMs composed of LSTM units, especially those augmented with an external memory, have achieved state-of-theart results.However, these models still struggle to process long sequences which are more likely to contain long-distance dependencies because of information fading and a bias towards more recent information.In this paper we demonstrate an effective mechanism for retrieving information in a memory augmented LSTM LM based on attending to information in memory in proportion to the number of timesteps the LSTM gating mechanism persisted the information.
An embedded C language Target Code level Unit Test method based on CPU Simulator

Abstract For the 8bit MCU of RISC architecture which is widely used at present, the internal resources such as Rom Ram stack are all limited. If written in C language, a C language instruction will become a lot of machine code after compiling, and it is easy to find that the ROM space is not enough. Stack overflow, etc. One of the biggest advantages of C is that it has nothing to do with any particular hardware or system. This allows a user to write programs that run on almost all machines without any modification. This paper presents an embedded C language target code level unit test method based on CPU simulator.
An Improved Discrete Cosine Transformation Block Based Scheme for Copy-move Image Forgery Detection

Copy-moved forgery is a common method to manipulate images. Several attempts of image forgery have been discovered and involves a region been duplicated and copied and pasted on another region of the same image in other to achieve selfish gain. Generally, there are two classification of copy-move forgery detection technique such as the block-based and key point-based. The block-based division is mostly used and divides image into blocks during the stage of image pre-processing before features are extracted, whereas key-point based technique skips the division of image into blocks and directly extracts different local feature from the image. In this paper, we review various block based and key point approach which has been proposed by various researchers. There is a problem of achieving a balance between improving the detection accuracy and having minimal computational complexity. The proposed technique is based on an improved DCT based copy-move image forgery detection (IDB-CFD), which involves using an octagonal block to reduce the number of features for matching, thereby improving detection accuracy while having minimal complexity. The analysis of this work as compared to previous proposed works which is based on a robust detection algorithm for copy-move image forgery (RDA-CF) and involves using circle block to reduce the number of features, results show that previous work represents about 79% of the quantized DCT coefficients on each image block and this proposed work represents about 85% of quantized DCT coefficients, therefore, recovery of about 6% more features using the IDB-CFD technique was observed as the improvement over the previously proposed RDA-CF.
Research on Spatial Conceptual Modeling of Natural Language Processing Based on Deep Learning Algorithms

Abstract From the point of view of computer science, especially artificial intelligence, the task of natural language understanding is to establish a computer model. This computer model can give the result of understanding natural language like human. An important aspect of natural language understanding lies in how to express knowledge to the computer, how to express knowledge, and how to establish the connection and reasoning between knowledge, that is, how to apply the brain’s association, reasoning and selection process to the model of language processing. The physical structure and logical structure of modern computers are very clear, but what we need is a set of feasible formal thinking mechanism to enable machines to process natural language information. Deep learning is one of the areas of machine learning that is close to AI. It is analyzed by simulating human brain learning nerves. Deep learning is derived from the study of artificial neural networks and is a structure for learning deep nonlinear networks. By presenting complex function approximations, the input data is distributed and represented, and the ability of the data samples to focus on the essential characteristics of the data set is revealed.
Research on the Impact of Internet Evolution on Accounting Information System Based on Data Mining

Abstract The evolution of accounting is influenced by the accounting environment, and the most important one is the Internet environment. At present, the Internet is gradually moving towards the direction of cloud computing. Therefore, the author based on data mining on the evolution of the Internet on the impact of accounting information system to carry out research. The control weakness and risk of accounting information system based on Internet are analyzed. The research results show that the Internet itself has the characteristics of openness, globality, low cost and high efficiency. It will first change the business operation and management activities of the enterprise, which will affect the economic operation of the whole society. Therefore, enterprises must make revolutionary changes in accounting and other aspects to adapt to the requirements of the network era. This study has important practical significance for clarifying the direction of development, optimizing the construction of accounting information systems, and achieving sustained and comprehensive development.