Reviewerly/exHarmony huggingface dataset:
Client Side-Server Side Load Balancing with Grasshopper optimization Mapreduce Enhancing Accuracy in Cloud Environment

Load balancing (LB) is a technique used to spread the workload among many computers or different resources using internet connections to attain maximum resource exploitation, optimize performance, reduces latency and overload. The introduction of cloud computing (CC) technology, resource handling, and LB is a major challenge. Some current scheduling models preserve load balancing and offer proficient mechanisms with effective job scheduling and resource assignment schemes. In our experiment. the proposed CS-SS load balancing and grasshopper optimization with ManReduce in order to avoid the issue in scheduling and improve throughput and resource consumption, thus improvising the whole results of the CC platform.
Securing the enterprise SAN with IBM Fibre Channel Endpoint Security

Controlling access to and privacy of data within the enterprise can prove to be a formidable task with increased complexity and management overhead encountered as the granularity of access control is increased. Fibre Channel is the premier enterprise storage transport, so an organization's most sensitive data flows over Fibre Channel links within and across datacenters. In this article, we discuss a new, easy way to deploy innovation for Fibre Channel connections that ensures data is exchanged only between trusted servers and storage controllers, while also enabling the integrity and confidentiality of the data in flight between the trusted entities. We explain how the components of IBM Fibre Channel Endpoint Security are configured to work together to provide protection from insider threats, requiring minimal steps to deploy, fully controlled via policy, and transparent to applications, middleware, and operating systems.
Path Kinematics for Combined Discrete and Continuous Event Simulation

Combined discrete and continuous event simulations provide a means of investigating the influence of the many factors affecting the productivity of complex electromechanical systems. This paper describes algorithms and methods for establishing the path kinematics of Cartesian axes of motion pick and place systems which must avoid varying obstacle profiles and which have the potential for path intersections with other pick and place systems within a shared working environment. Where intersections arise, one pick and place device must, in accordance with pre-established prioritization, decelerate and wait for another pick and place device to vacate the zone of conflict. Path kinematics represent a continuous event aspect of the simulation under development while awaiting permission to proceed represents a discrete event aspect of the simulation. A requirement of the research is that the kinematics only include periods of constant acceleration and constant velocity and that any deceleration must continue substantially along the original path. The algorithm and methods presented are concise and may be applicable and convenient to apply in the path control of Cartesian axis of motion devices.
IBM Z in a secured hybrid cloud

The IBM z15 is built to support users to deliver mission-critical workloads and services in a hybrid cloud environment. In this article, we describe the new capabilities that are intended to fit the platform into private and public cloud frameworks. This work is rooted in the broader IBM cloud strategy and point-of-view and based on ongoing efforts to identify and address critical pain-points for a key set of enterprise clients through applying Enterprise Design Thinking practices. By outlining the hardware, firmware, and software support added for z15, we show how we have been able to integrate the IBM Z platform into the IBM Cloud infrastructure. We also discuss how cloud-focused technologies and tooling enable users to access, deploy, and lifecycle manage z/OS resources and services for a seamless cloud experience.
Applications of Neural Networks for Classifying Images of Deaf Horses

Equine deafness profoundly impacts the ways owners can interact with their horses; while deafness prevents many auditory distractions, it also requires trainers to communicate differently than with other horses. While the splashed-white genes (SW-1 through SW-5) have been known to express themselves in near-full facial coverage with white hair in addition to blue eyes, it regularly entails deafness in the host. Current diagnoses of the SW-5 gene are primarily limited to proprietary genome analysis provided by equine diagnostics companies such as Etalon Diagnostics, which requires both money and time. Our approach to diagnosing SW-5 leverages the present phenotype-genotype relationship to convert this diagnosis into an image classification task. We propose a technique that uses a convolutional neural network in order to classify SW-5 horses solely based on physical attributes. Our classifier predicted the SW-5 gene with 97.49% accuracy and 5.88% loss, which provides an instantaneous prediction within margins of confidence.
Path Planning Using Particle Swarm Optimization and Fuzzy Logic

Path planning is one of the research axes in mobile robotics, it allows us to plan a path linked, the robot's starting point and the goal to guarantee autonomous navigation for the mobile robot. This work presents a quantitative methodology to compare the Particle Swarm Optimization algorithm and Fuzzy Logic, applied to solve the path-planning problem, taking into account their basic concepts and results obtained.
Fault Detection Technique for SMGF and Appearance Faults in Reversible Circuits using Matrix Model

Energy dissipation is a severe issue of present-day technology. The current scenario demands for moving beyond the traditional ways of computing. In this contrast, reversible circuit offers a possible solution to this problem. For confirming the correct behavior of the reversible circuits, a proper testing technique is required to detect and also locate the faults. In this paper, we have concentrated only on generating the test set for detecting the single missing-gate fault (SMGF) and appearance fault. For this purpose, we have investigated the correlation between the two fault models, and based on that an automatic test pattern generation (ATPG) method have been proposed to extract the required test set which is capable of detecting both the faults. In this work, the process of test set generation is developed by the concept of a matrix model by applying some well-defined constraints. Finally, experimental results are provided to verify our claim. Keywords: Appearance fault, ATPG, k-CNOT based reversible circuits, matrix model, SMGF, test set Cite this Article: Mousmee Nath, Abdul Hannan Laskar, Subham Chhetry, Mousum Handique. Fault Detection Technique for SMGF and Appearance Faults in Reversible Circuits using Matrix Model. International Journal of Computer Science and Programming Language. 2020; 6(1): 13–24p.
Examining the Differences of Readability Leveling of Chinese Popular Science Books by Experts and by CRIE System for Elementary School Children

Popular scientific reading books, as the bridge between scientific academic research and general public’s knowledge capital, could raise scientific literacy and facilitate comprehension for general public. Popular scientific reading books could attract children to read because of vivid exhibition of text and illustrating graphs. However, some scientific reading books are still too difficult for children to read since they are not designed for children particularly in Taiwan and reading capacity among children are heterogeneous. One promising education strategy is to recommend more scientific reading books corresponding to textbook lessons, which could raise children’s interest in exploring science and further reading. In US, Lexile framework for reading has been developed and applied for English books to assist in more efficient and objective text leveling. For recent years, Chinese Readability Index Explorer (CRIE) has been developed for Chinese text. The main research question here is, for Chinese scientific reading books, whether there are differences in text leveling between system’s (CRIE) and experts’ identification. In our research, we invite teacher librarians to recommend popular scientific reading books, identify the grade levels, and assign these books to corresponding textbook lessons. We not only discuss the principles and criteria of experts’ leveling, compare the different results between CRIE and experts’ opinions, but also investigate the reasons behind these differences.Keywords: Popular Scientific Reading Books; Readability; Text Leveling; Mathematical and Science Fields in Elementary Schools【摘要】科普作品主要做為科學論文與大眾文化間的橋樑，用淺白的言辭闡述科學立論，令大眾容易領會。科普書圖文並茂，然而並非全為兒童出版，即使以兒童為對象，因為學童之閱讀能力與科學知識差異大，無法閱讀相同程度的書籍。教師若能配合學習單元，推薦適當的科普延伸讀物，相信更能引起學童探索科學的好奇心。國外為兒童出版的英文書籍，常可在圖書封底看到分級標示，供讀者選書參考。近來我國發展之文本可讀性指標自動化分析系統（CRIE），亦可為中文圖書分級。本研究探討配合國小課程單元，由教師分級推薦之科普書，與CRIE系統的讀本可讀性分析是否有差異，及其產生差異的原因為何。關鍵字：科普書、可讀性、適讀性、國小數學與自然領域
CEF Data Marketplace: Powering a Long-term Supply of Language Data.

We describe the CEF Data Marketplace project, which focuses on the development of a trading platform of translation data for language professionals: translators, machine translation (MT) developers, language service providers (LSPs), translation buyers and government bodies. The CEF Data Marketplace platform will be designed and built to manage and trade data for all languages and domains. This project will open a continuous and longterm supply of language data for MT and other machine learning applications.
Reflections on China's Marine Sports Development Strategy in the New Era

Xiang, Y., 2020. Reflections on China's marine sports development strategy in the new era. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 160-162. Coconut Creek (Florida), ISSN 0749-0208.Sports games are a teaching method that can help students promote physical exercise and entertain themselves. In the current economic situation and social environment, we should pay more attention to sports teaching activities. If they can be applied to the teaching and training of marine sports, it will greatly help middle school students to improve the level of marine sports. Physical education teachers should make full use of the competitive spirit of sports competitions, starting from the basis of marine sports teaching and training, explaining marine sports skills to students, so that they can understand the important value of marine sports.
Procedural Content Generation via Machine Learning in 2D Indoor Scene

The article proposes a method of combining multiple deep forward neural networks to generate a distribution of objects in a 2D scene. The main concepts of machine learning, neural networks and procedural content generation concerning this intention are presented here. Additionally, these concepts are put into the context of computer graphics and used in a practical example of generating an indoor 2D scene. A method of vectorization of input datasets for training forward neural networks is proposed. Scene generation is based on the consequent placement of objects of different classes into the free space defining a room of a certain shape. Several evaluate methods have been proposed for testing the correctness of generation.
Use of social media in Indian Council of World Affairs (ICWA) library: A case study

The social media has become an important channel for communication and services provider for the user community. The paper highlights the conceptual framework of social media, and various forms of social media used by the ICWA user's community. The users are interested in the growing field of social media, which can be useful for information creation, sharing and dissemination of information.
Linear Recurring Sequences and Explicit Factors of x2nd−1 in 𝔽<sub><i>q</i></sub>[<i>x</i>]

Let 𝔽 q be a finite field of odd characteristic containing q elements, and n be a positive integer. An important problem in finite field theory is to factorize x n − 1 into the product of irreducible factors over a finite field. Beyond the realm of theoretical needs, the availability of coefficients of irreducible factors over finite fields is also very important for applications. In this paper, we introduce second order linear recurring sequences in 𝔽 q and reformulate the explicit factorization of [Formula: see text] over 𝔽 q in such a way that the coefficients of its irreducible factors can be determined from these sequences when d is an odd divisor of q + 1.
The Cost Control Optimization Model of Marine Emission Environment Based On Efficiency and Cost Constraint

Han, B.; Zhou, Y., and Pan, X., 2020. The cost control optimization model of marine emission environment based on efficiency and cost constraint. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 469-472. Coconut Creek (Florida), ISSN 0749-0208.Marine emission control Workshop scheduling problem not only needs to optimize performance indexes such as maximizing completion time and machine load, but also should consider cost control. Based on the double constraint of environmental efficiency and cost, the performance index with the lowest processing cost in workshop scheduling was proposed for the purpose of cost control optimization, and the genetic algorithm optimization model was constructed based on this objective function. The coding mechanism based on process and cost is adopted, and the crossover operation and mutation operation aiming at coding scheme are improved to ensure the diversity of the population in the evolutionary search process of the algorithm, so that the optimization effect of model cost control can be further improved. By an example experiment, the feasibility and effectiveness of the cost control optimization model are verified, which provides a new idea for solving the dilemma between the efficiency and the cost in the marine emission environmental control.
DAC 6: Developing a Common Notification Platform

The authors provide a brief overview over the challenges introduced by the EU mandatory tax disclosure rules known as DAC 6 and offer an outlook on potential solutions for these challenges. The starts with background on who is affected by DAC 6 and the consequences of non-compliance. Thereafter, the authors discuss the practical issues with DAC 6 disclosures due to the different implementation into national law in the respective Member States and elaborate the different effects of DAC 6 on different types of businesses. The authors than introduce a possible process for a DAC 6 transaction assessment around the disclosure of a reportable cross border arrangements. Finally the article concludes with the proposal for a common Notification Platform, an innovative solution that could minimize the risk of non-compliance due to error prone manual tasks.
PosEdiOn: Post-editing assessment in PythOn

There is currently an extended use of post-editing of machine translation (PEMT) in the translation industry. This is due to the increase in the demand of translation and to the significant improvements in quality achieved by neural machine translation (NMT). PEMT has been included as part of the translation workflow because it increases translators’ productivity and it also reduces costs. Although an effective post-editing requires enough quality of the MT output, usual automatic metrics do not always correlate with post-editing effort. We describe a standalone tool designed both for industry and research that has two main purposes: collect sentence-level information from the post-editing process (e.g. post-editing time and keystrokes) and visually present multiple evaluation scores so they can be easily interpreted by a user.
Streaming Complexity of SVMs

We study the space complexity of solving the bias-regularized SVM problem in the streaming model. In particular, given a data set (x_i,y_i) ∈ ℝ^d× {-1,+1}, the objective function is F_λ(θ,b) = λ/2‖(θ,b)‖₂² + 1/n∑_{i=1}ⁿ max{0,1-y_i(θ^Tx_i+b)} and the goal is to find the parameters that (approximately) minimize this objective. This is a classic supervised learning problem that has drawn lots of attention, including for developing fast algorithms for solving the problem approximately: i.e., for finding (θ,b) such that F_λ(θ,b) ≤ min_{(θ',b')} F_λ(θ',b')+e.One of the most widely used algorithms for approximately optimizing the SVM objective is Stochastic Gradient Descent (SGD), which requires only O(1/λe) random samples, and which immediately yields a streaming algorithm that uses O(d/λe) space. For related problems, better streaming algorithms are only known for smooth functions, unlike the SVM objective that we focus on in this work.We initiate an investigation of the space complexity for both finding an approximate optimum of this objective, and for the related problem of sketching the data set to evaluate the function value F_λ on any query (θ, b). We show that, for both problems, for dimensions d = 1,2, one can obtain streaming algorithms with space polynomially smaller than 1/λe, which is the complexity of SGD for strongly convex functions like the bias-regularized SVM [Shalev-Shwartz et al., 2007], and which is known to be tight in general, even for d = 1 [Agarwal et al., 2009]. We also prove polynomial lower bounds for both point estimation and optimization. In particular, for point estimation we obtain a tight bound of Θ(1/√{e}) for d = 1 and a nearly tight lower bound of Ω(d/{e}²) for d = Ω(log(1/e)). Finally, for optimization, we prove a Ω(1/√{e}) lower bound for d = Ω(log(1/e)), and show similar bounds when d is constant.
Quantitative Analysis of Post-Editing Effort Indicators for NMT

The recent improvements in machine translation (MT) have boosted the use of post-editing (PE) in the translation industry. A new machine translation paradigm, neural machine translation (NMT), is displacing its corpus-based predecessor, statistical machine translation (SMT), in the translation workflows currently implemented because it usually increases the fluency and accuracy of the MT output. However, usual automatic measurements do not always indicate the quality of the MT output and there is still no clear correlation between PE effort and productivity. We present a quantitative analysis of different PE effort indicators for two NMT systems (transformer and seq2seq) for English-Spanish in-domain medical documents. We compare both systems and study the correlation between PE time and other scores. Results show less PE effort for the transformer NMT model and a high correlation between PE time and keystrokes.
Moment-Based Parameterization of Evolving Cyclograms on Gradually Changing Slopes

The problem under study is the systematic characterization of a series of gradually evolving cyclograms with a small number of features. The mathematical quantities derived from the geometric properties of the hip-knee cyclograms are the main features considered in this study. Our thesis is that the gradual evolution of gait on inclined planes, which is manifested by progressive shape change of these closed-contour curves can be tracked by observing the evolution of their geometric moments. Experimental slope-walking data obtained for each 1° interval within the range of −13° to +13° (±23.1%) on a variable-inclination treadmill was used in this study. The parameterization procedure presented here is fairly general in nature and maybe employed without restriction to any closed curve such as the phase diagram and the moment-angle diagram of human gait. The technique may be utilized for the quantitative characterization of normal gait, global comparison of two different gaits, clinical identification of pathological conditions and for the tracking of progress of patients under rehabilitation program.
Data Visualization and Statistical Literacy for Open and Big Data

"Data Visualization and Statistical Literacy for Open and Big Data." Journal of Statistical Computation and Simulation, 90(15), pp. 2858–2859
System Recovery Boost on IBM z15

System Recovery Boost on the IBM z15 server expedites planned operating system shutdown, either planned or unplanned operating system initial program load (IPL), middleware and workload restart and recovery, and the client workload execution that follows, to accelerate service restoration around downtime. It does this by providing limited-duration “boost periods” that deliver significant usable additional processor capacity and parallelism. On subcapacity machine models, it provides a boost in processor speed by running the general-purpose processors at full-capacity speed, for the boosting LPARs only, and only during the boost periods. It makes all available processing capacity defined to the boosting images available to process any kind of work, “blurring” general-purpose processor and specialty processor capacity together during the boost period. System Recovery Boost also expedites and parallelizes processor reconfiguration actions that may be part of the client's overall restart and recovery process, as orchestrated by Geographically Dispersed Parallel Sysplex (GDPS) automation. Optionally, System Recovery Boost provides the ability to add additional processor capacity from the client's unused “dark cores” via activation of a new type of temporary capacity record. All of this can be accomplished without increasing the client's IBM software billing costs or the processor consumption associated with the client's workload during these boost periods.
Off-Line Writer Verification Using Segments of Handwritten Samples and SVM

This works presents a method to verify a person identity based on off-line handwritten strokes analysis. Its main contribution is that the descriptors are obtained from the constitutive segments of each grapheme, in contrast with the complexity of the handwritten images used in signature recognition system or even with the graphemes themselves. In this way, only few handwriting samples taken from a short text could be enough to identify the writer. The descriptor is based on an estimation of the pressure of the stroke grayscale image. In particular, the average of the gray levels on the perpendicular line to the skeleton is used. A semi-automatic procedure is used to extract the segments from scanned images. The repository consists of 3.000 images of 6 different segments. Binary-output Support Vector Machine classifiers are used. Two types of cross validation, K-fold and Leave-one-out, are implemented to objectively evaluate the descriptor performance. The results are encouraging. A hit rate of 98% in identity verification is obtained for the 6 segments studied.
Motivating Students of SMK Muhammadiyah 1 Palu for Increasing English Language Vocabulary

Main issue of this commuity service is Motivating Students. Its objective was Increasing Vocabulary of English Language. Its specific target is SMK Muhammadiyah 1 Palu has students who have more vocabulary so that they can easily understand and express sentences of the EFL (English as a Foreign Language). They can be global students if they can increase vocabulary to express the internatonal language. Commuicative method was used to reach the objective. Formerly they were shy and unconfident in expressing the language vocabulary, but after being motivated to increase the global language vocabulary they then were confident to practice it by interacting with the community service team and have spirits better better than before to increase the vocabulary of English so that they can express the lingua franca words. The team motivated them to increase their English vocabulary practically and accompanied them to apply the practical ways of increasing the EFL vocabulary so that they have been able to express its words. They can be motivated to increase the vocabulary by telling them status and significances of English in Indonesia.Keywords: Motivating, Increasing, English, Language, Vocabulary