Reviewerly/exHarmony huggingface dataset:
Pilot study on medical translations in lay language : post-editing by language specialists, domain specialists or both?

Despite the rich history of research into medical translation, there is a notable lack of empirical studies on the best workflow for this task, especially in a modern translation setting involving post-editing of machine translation. This pilot study was conducted in preparation for a large translation project of medical guidelines for laypeople from Dutch into French. It is meant to shed light on how medical post-editing is best handled. How do medical specialists (doctors) versus language specialists (translators) perform on this task? How can their respective strengths lead to the highest quality translation? To gain more insight into these questions, errors in the machine translation output of medical guidelines were annotated and labelled. Based on these annotations, the product of doctors' and translators' post-editing could be analysed and classified into necessary changes (mistakes that were correctly solved), under-revisions (mistakes that were not corrected during post-editing), over-revisions (new errors introduced during post-editing) and hyper-revisions (preferential changes made by the post-editor). The results of this small-scale research illustrate the complexity of the task and reveal some surprising findings (e.g., doctors sometimes struggle with domain-specific terminology, and translators appear to be less efficient because they introduce many hyper-revisions).
A Survey of Load Balancing and Implementation of Clustering-Based Approach for Clouds

Background: Generally, it is observed that there is not a single algorithm that classifies the task using Quality of Service (QoS) parameters requested by the task but instead focuses on classifying resources and balancing the task's using the availability of resources. In past literature, authors divided the load balancing solutions in three main parts workload estimation, decision making, task transferring. Workload estimation deals with identifying requirements for the incoming tasks on the system. Decision making is done to analyze that whether or not load balancing should be performed for the given node. If the decision for load balancing has been made then third step deals with transferring task to appropriate node to reach a saturation point where the system will be in the stable state. Objective: To address this issue, our approach is more focused upon on workload estimation and its main objective is to cluster the incoming heterogeneous task into generic groups. Another issue for this approach is that the client demand varies for the number of tasks. Thus, some attributes may be much more critical to a user then the others and this demand changes from user to user. Methods: This paper classify the tasks using QoS parameters and focused on work-load estimation. The main objective is to cluster the incoming heterogeneous task into generic groups. For this, KMedoid based clustering approach for cloud computing is devised and implemented. This approach is then compared with its different iterations to analyses the workload execution more deeply. Results: The analysis of our approach is computed using cloudsim simulator. Results and computations shows that the data is very uneven in initial times, as some clusters have only four elements and others are having much more elements. Whereas after the 20th iteration data observed is more normally balanced, so the clusters formed after 20th iteration were more stable than clusters formed initially i.e. 1st iteration. The number of iterations is also minimized to do unnecessary clustering as after a few steps the changes in medoids are very less. Conclusion: A brief survey of various load balancing techniques in cloud computing is discussed. These approaches are meta-heuristic in nature and have complex behavior and can be implemented in cloud computing. In our paper, K-Medoid based clustering approach for identifying the task into similar groups has also been implemented. Implementation is done on cloudsim simulation package provided by Cloud Labs, which is a java based open source package. The results obtained in our approach are limited to classification of tasks into various clusters. It would also useful where new task arrives and simply assign it to a VM that was created for some other element of that class. In future, this work can be expanded to create an effective clustering based model for load balancing.
Multilevel Secure Digital Image Steganography Framework Using Random Function and Advanced Encryption Standard

One of the crucial aspects of processes and methodologies in the information and communication technology era is the security of information. The security of information should be a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies which are used, and they include steganography and cryptography. With cryptography, the secret message is converted into unintelligible text, but the existence of the secret message is noticed, nonetheless, steganography involves hiding the secret message in a way that its presence cannot be noticed. In this paper, a new secure image steganography framework which is known as an adaptive stego key LSB (ASK-LSB) framework is proposed. The construction of the proposed framework was carried out in four phases with the aim of improving the data-hiding algorithm in cover images by using capacity, image quality, and security. To achieve this, the Peak Signal-to-Noise Ratio (PSNR) of the steganography framework was maintained. The four phases began with the image preparation phase, followed by the secret message preparation phase, embedding phase and finally extraction phase. The secure image steganography framework that is proposed in this study is based on a new adaptive of least significant bit substitution method, combination random function, and encryption method. In the proposed work, the secret bits are inserted directly or inversely, thereby enhancing the imperceptibility and complexity of the process of embedding. Results from the experiment reveal that the algorithm has better image quality index, peak signal-to-noise ratio, and payload used in the evaluation of the stego image.
DaiMoN: A Decentralized Artificial Intelligence Model Network

We introduce DaiMoN, a decentralized artificial intelligence model network, which incentivizes peer collaboration in improving the accuracy of machine learning models for a given classification problem. It is an autonomous network where peers may submit models with improved accuracy and other peers may verify the accuracy improvement. The system maintains an append-only decentralized ledger to keep the log of critical information, including who has trained the model and improved its accuracy, when it has been improved, by how much it has improved, and where to find the newly updated model. DaiMoN rewards these contributing peers with cryptographic tokens. A main feature of DaiMoN is that it allows peers to verify the accuracy improvement of submitted models without knowing the test labels. This is an essential component in order to mitigate intentional model overfitting by model-improving peers. To enable this model accuracy evaluation with hidden test labels, DaiMoN uses a novel learnable Distance Embedding for Labels (DEL) function proposed in this paper. Specific to each test dataset, DEL scrambles the test label vector by embedding it in a low-dimension space while approximately preserving the distance between the dataset's test label vector and a label vector inferred by the classifier. It therefore allows proof-of-improvement (PoI) by peers without providing them access to true test labels. We provide analysis and empirical evidence that under DEL, peers can accurately assess model accuracy. We also argue that it is hard to invert the embedding function and thus, DEL is resilient against attacks aiming to recover test labels in order to cheat. Our prototype implementation of DaiMoN is available at https://github.com/steerapi/daimon.
Cyber Security Education for Liberal Arts Institutions

Cybersecurity is a broad, dynamic, and ever-changing field that is difficult to integrate into undergraduate Computer Science (CS) curriculum. The absence of sanitized labs coupled with the requirement of specialized faculty to teach the subject pose obstacles many primarily undergraduate colleges face in adopting cybersecurity education. In this paper we describe a set of labs that have been implemented using the Global Environment for Network Innovations (GENI) cloud infrastructure as a solution to teaching experientially with low overhead. These labs are developed for different levels of experience, based on Capture The Flag (CTF) competitions that include short questions and answers, scenario based exercises, and upper level research skills. Curriculum for Liberal Arts Institutions is presented starting from the core general education as a vehicle to bring cyber security to a diverse population of non-CS majors and moving to introductory and upper level CS courses. These labs and curriculum are part of the project CyberPaths (Cyber security Paths) with goal to broaden the path to cybersecurity profession for a diverse population of Liberal Arts students.
CLEAN Algorithm for Imaging Quality Enhancement

In ITS, radar plays an important role. Detection of the target and characterization is very important. Similarly, in dynamic channel condition, target image quality degrades considerable due to sidelobe enhancement and defocusing. The clean algorithm is introduced to eliminate sidelobes and significantly improves the target detection performance of radar signals. The experimental results demonstrate the effectiveness of the CLEAN algorithm.
ACTIVE DIRECTION OF THE COMMUNICATIVE AND COMPETENCE APPROACH IN TRAINING OF A FOREIGN LANGUAGE TEACHER

The article deals with the application of the activity approach in the preparation of a foreign language teacher. The relevance of the research is to uncover the relationship between communicative competence and activity approaches in solving the problem. The author substantiates the scheme of interrelation of the above approaches in the process of formation of cognitive activity, and outlines the basic components of cognitive activity, consciousness and strength of knowledge acquisition, purposefulness and organization in cognitive activity and didactic conditions of their realization.It is clear that the implementation of the activity approach is manifested in the development of students’ activity, their collaboration with the teacher, the individualization of learning activities, and the development of self-control.In order to expand the learning content in the development of the student’s personality, the study material is saturated with tasks that allow to predict the prospects of its use. This approach requires changes in teaching methods that enhance its impact on the individual.The students themselves manage the learning process. Problematic issues activate mental activity even in the most passive people; they are easy to become its participants.The peculiarities of applying an activity approach, combined with communicative, competent and cognitive goals, are aimed at the development and improvement of the individual, to reveal his reserve potential and creativity.Determining the level of cognitive activity of students confirms the effectiveness of implementation of the activity approach in the educational process. Prospects for further research are seen in the study of didactic skills of formation of cognitive activity.
Efficiency of Managing the Resource Potential of University Library

Objective. The paper investigates the resource potential of higher education institution libraries as a tool for effective management of their activity. Methods. The author pays attention to the difference between the concepts of "resource pool" and "resource potential", which is in involving the latter in the process of library information production and service. Results. The composition of the university library's resource potential is determined. It is stated that the effective management of the resource potential requires the managers to fully evaluate the factors of the internal and external environment of the library functioning. Characterization of individual components of the university library resource potential is given, and the need for their integrated use is emphasized. Much attention is paid to library staff as a leading resource of the management system, the formation of their cognitive potential. Conclusions. It is stated that the efficiency of the activity of the modern library of the higher education institution is largely determined by the available resource potential aimed at the achievement of scientifically and educationally significant goals and objectives of strategic character. The main results of the research can be used in the process of managing the activities of the university library.
PENCIPTAAN LAYANAN PRIMA MELALUI PENERAPAN SISTEM INFORMASI MANAJEMEN DI PERPUSTAKAAN IAIN PURWOKERTO

This study aimed to find out how the Creation of Excellent Services through the application of Management Information Systems at the IAIN Purwokerto Library. This study has a qualitative approach with the conclusion that the Creation of Excellent Services through Management Information Systems in the Purwokerto IAIN Library cannot be separated from the theory of management functions, namely planning, organizing, implementing, and monitoring. The management functions that are applied in the Creation of Excellent Services through the implementation of Management Information Systems are as follows (1) Planning, procurement of Management Information System devices, even though they already exist but continue to be developed in supporting excellent services. (2) Organizing, through the implementation of a Management Information System that runs well because of the support of qualified human resources in each field, so that the use of tools or software can be in accordance with its function. (3) Implementation, excellent services run in accordance with operational standards, especially the use of Management Information Systems support the improvement of Prime Services in the Library. (4) Supervision, carried out by the head of the library by reviewing the performance of excellent service both direct supervision and indirect supervision.
Modulation recognition method of time-frequency aliasing signals in single-channel

In the field of modern wireless communication, electromagnetic spectrum resources are increasingly tight, and it is becoming more and more common for one single antenna to receive multiple communication signals. High-order cumulant can suppress noise well, it has been widely used for modulation recognition of single signal in single-channel but seldom used for time-frequency aliasing signals in single-channel. This is because we need to use estimated carrier frequency for down-conversion to obtain the baseband signal before calculating high-order cumulant. But there will be more than one carrier frequencies when they are time-frequency aliasing signals. So it focuses to select the suitable carrier frequency to improve the calculation accuracy of high-order cumulant and recognition performance. In this paper, an algorithm of selecting suitable carrier frequency which uses the nature of high-order cumulant is proposed. And also two high-order features have been analyzed and constructed. Then they are used to classify seven kinds of timefrequency aliasing signals randomly combined by the digital modulated signals including BPSK, QPSK, 8PSK and 4ASK. The simulation results show that the algorithm has better recognition performance.
Two Birds with One Stone: Investigating Invertible Neural Networks for Inverse Problems in Morphology

Most problems in natural language processing can be approximated as inverse problems such as analysis and generation at variety of levels from morphological (e.g., cat+Plural↔cats) to semantic (e.g., (call + 1 2)↔“Calculate one plus two.”). Although the tasks in both directions are closely related, general approach in the field has been to design separate models specific for each task. However, having one shared model for both tasks, would help the researchers exploit the common knowledge among these problems with reduced time and memory requirements. We investigate a specific class of neural networks, called Invertible Neural Networks (INNs) (Ardizzone et al. 2019) that enable simultaneous optimization in both directions, hence allow addressing of inverse problems via a single model. In this study, we investigate INNs on morphological problems casted as inverse problems. We apply INNs to various morphological tasks with varying ambiguity and show that they provide competitive performance in both directions. We show that they are able to recover the morphological input parameters, i.e., predicting the lemma (e.g., cat) or the morphological tags (e.g., Plural) when run in the reverse direction, without any significant performance drop in the forward direction, i.e., predicting the surface form (e.g., cats).
Pertumbuhan dan Perkembangan Anak Usia 3-6 Tahun

The purpose of this study was to determine the picture of the growth and development of children aged 3-6 years in Pertiwi Metro City PAUD. This research method is descriptive, with a sample of 120 people, from playgroups, TK A and TK B PAUD Pertiwi Metro City. The sampling technique used is randomization. Results showed that almost all children had good nutritional status, which was 95%, 96.66% of children had normal head circumference, almost all (96.23%) child development was appropriate, 98.73% of children had normal vision, 97, 5% of children have normal hearing power. Nearly all (94.17%) of children have normal emotional behavior problems, and 95.83% of children do not experience the possibility of impaired concentration and hyperactivity. Conclusions looking at the results of this study are suggested that educational institutions work together with puskesmas, to detect early deviations of child development in a continuous, continuous manner, and are expected to be a reference for other schools in the school health business program (UKS) because PAUD Pertiwi Metro City has become national level UKS champion.
Competitive Advantage: Exploring the Role of Partnership with suppliers, Customer Relationship and Information Sharing as Antecedents

The objective of the present research is to explore the impact of information sharing, supplier partnership and customer relationship with a competitive advantage in the Indonesian rubber industry. Moreover, current study also explored the mediating role of flexibility of the supply chain among of information sharing, supplier partnership and customer relationship and competitive advantage. Moreover, of information sharing, supplier partnership and customer relationship are studied as the independent variables in the present study. Survey based approach was adopted for the collection of data whereas SEM-PLS was used for the analysis of the data. The findings of the study pointed out that customer relationship and supplier partnership have significant impact on the flexibility of the supply chain and to develop competitive advantage. Moreover, the results of the study do not support the relationship of information sharing with flexibility and competitive advantage. The findings of the present study are beneficial for the policy makers of the Indonesian rubber industry. By the findings of the study, they can adopt different strategies to develop a competitive advantage. The present study will increase the past literature of the supply chain.
Between Freedom and Fixity : Artistic Reflections on Composition and Improvisation

Between Freedom and Fixity: Artistic Reflections on Composition and Improvisation is a practice-based research project that aims to highlight the role of freedom and fixity in music and to develop a discourse based on these two concepts. The research suggests a creative approach based on the interrelationship between freedom and fixity, for example their combination, juxtaposition, and tension, and describes them as abstractions or placeholders for musical agents such as rhythm, notes, structure, timeline, and interactive computer systems. Another important notion is the inherent coexistence of the two concepts, and proposing the constant oscillating between them as a creative musical approach. Furthermore, the research aims to establish the use of freedom and fixity as a productive paths for extra-musical disciplines. Four works by the author are used as case studies to examine the integration of the research concepts as tangible musical forms. In each of the case studies the concepts are embodied differently, thus different relationships develop between them in each piece. This study relies on the author's experience and experimentation as a composer, performer, improviser, and electronic-music practitioner, and draws inspiration from works by other musicians and scholars.
Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Brain science and brain-inspired artificial intelligence have the potential for strengthening business and management. Brain-inspired artiï¬cial intelligence (AI) uses principles of brain science to build algorithms and AI systems with human-like intelligence. Some concepts (e.g., cognition, inference, memory, and intelligence) and principles of brain science are introduced in this paper. The research progress in several topics are also presented that include brain-inspired artiï¬cial intelligence and brain-inspired computing, project management and brain-inspired management, the integration of brain science into leadership (especially crisis leadership), and brain-inspired decision-making for business. Future research and trends in some topics are introduced.
Concertina Gait Learning for Snake Robot using Artificial Neural Network

In this project we have tested evolutionary process on concertina motion of snake robot. Concertina motion is a type of gait in snake in which it draws its body into sine curve then motion begins by extending its head and forward parts of the body by using frictional forces. This type of gait enable snake to move in narrow spaces. Here we have designed our snake robot in Bullet-Physics environment while Hill-Climber algorithm which is a genetic algorithm has been used to optimize the Artificial Neural Network for to give our robot the evolving capability. A multi-objective Fitness Function is designed in bullet-physics engine which reinforces learning of sinusoidal curve in snake and also reinforces forward motion in it. This multi-objective function seems to be promising as compare to single-objective as it considers the shape of the robot and takes into account the distance as well. Here in our experiment the locomotion controller quickly evolved and the desired behaviors have been obtained. Concertina motion with the proposed evolving capabilities make it a good solution for designing basic motion pattern for snake robots.