Reviewerly/exHarmony huggingface dataset:
Tuning of conic parameters using Tikhonov regularization and L-Curve simulation

In this article, a method to infer the parameters of a conic given a set of rectangular coordinates that belong to the geometric entity is shown. The methodology consists of solving a Tikhonov regulation problem where the unregulated term introduces the non-linear nature of the conical body and the regulated the restriction associated to the discriminant of the quadratic equation, then the solution is computed minimizing the resulting cost function where the Regularization parameter is tuned using the L-Curve technique. The model was validated with synthetic and real data from digital images, as well as subject to comparison against other state of the art alternatives. The results show that the method is robust against atypical values and the phenomenon of occlusion present in the data.
Advanced Scheduling in IaaS Clouds

The complexity of modern software libraries and applications makes it hard to predict possible workloads generated by the software that may lead to significant underutilization of hardware in Infrastructure-as-a-Service (IaaS) clouds. In this paper, we give a review of an approach aimed to deal with resource underutilization in cloud environments, including description of a developed software framework and an example algorithm. IaaS clouds following this universal approach can help increase overall cloud resource utilization independently of the variety of cloud applications.
A Comparative Study of System Virtualization Performance

Virtualization presents an abstraction between the bare computer hardware (physical resource set) and the application running on top of it. Virtualization technology has become the defacto technology in cloud computing systems. The technique has become an enabling technology in cloud computing, which helps in the provisioning of resources on an on-demand basis, thereby addressing elastic resource requirements of organizations in their quest to scale. This paper seeks to investigate the effect of virtualization on system performance. The primary objective is to conduct an empirical analysis to compare and contrast the performance of Virtual Machines (VMs) and a Host machine running on different Operating Systems (OS). The effect of the use of different OS and VM configurations (Host and Guest systems) on system performance is also explored. The study shows that depending on the metric (i.e., throughput, jitter, and response time and packet loss ratio) used, virtualization technique results in a performance degradation between 21% and 39%. In particular, communication between systems with Linux (being either the Host or the Guest OS) performs better than Windows (as either the Guest or the Host) OS. Additionally, it is also observed that there is a performance loss ranging between 12% and 20% when communicating devices run heterogeneous Guest OS.
Pairwise Reviews Ranking and Classification for Medicine E-Commerce Application

E-Commerce applications provide an added advantage to customer to buy product with added suggestions in the form of reviews. Obviously, reviews are useful and impactful for customers those are going to a buy product. But these enormous amount of reviews create problem also for customers as they are not able to segregate useful ones. Therefore, there is a need for an approach which will showcase only relevant reviews to the customers. This same problem has been attempted in this research paper as this is a less explored area. Pairwise Review relevance ranking method is proposed in this research paper. This approach will sort reviews based on their relevance with the product and avoid showing irrelevant reviews. This work has been done in three phases- feature extraction, pairwise review ranking, and classification. The outcome is sorted list of reviews, review ranking accuracy and classification accuracy. Four classifiers- SVM, Random forest, Neural network, and logistic regression have been applied to validate ranking accuracy. Out of all four applied classification models, Random forest gives the best result. our proposed system is able to achieve 99.76% classification accuracy and 99.56% ranking accuracy for a complete dataset using random forest.
Digital readout optimization of the random resistive states in magnetic tunnel junction

True random number generators (TRNGs) provide a wide area of applications and can be fabricated on the basis of magnetic tunnel junctions (MTJs). This work represents the modeling of TRNG readout optimization, where the induced digital random bit is detected within only a single computational period. The period contains two sub-cycles: write and joined read & reset cycles. The system has a valuable potential to become stochastically independent after calibrating at the desired working point against the factors, which cause to the signal deviations: temperature-induced, material degradation or other problems.
Analysis on Early Warning Capability of Gansu Earthquake Early Warning Stations Network

Abstract This paper briefly introduces the structure and network layout of Gansu Earthquake Early Warning Stations Network, and discusses the relationship of the effective early warning time and the radius of early warning blind zone with consumed time for early warning. Based on the layout of the current and future earthquake early warning stations network of Gansu, the consumed time for early warning under three stations triggered and six stations triggered is calculated and analyzed. In addition, the contour map of consumed time for early warning in Gansu is drawn. The results show that the effective early warning time is negatively correlated with consumed time for early warning, and the radius of the early warning blind zone is positively correlated with consumed time. And the consumed time for early warning of the future earthquake early warning stations network under three triggered stations and six triggered stations in Gansu is shortened by 29.24% and 37.13% compared with those of the current earthquake early warning stations network. After the completion of the Gansu Subproject, the effective early warning time will be increased and the radius of the early warning blind zone will be reduced, then the early warning capability in Gansu is to be greatly improved.
유아교사의 근로여건이 전문성에 미치는 영향 분석 -교사의 웰빙과 효능감의 매개효과를 중심으로-

Objective: The goal of this study was to investigate the effects of early childhood teachers' current working conditions such as welfare and wages, working hours, ECEC center's environmental characteristics, and parental involvement and community engagement on the professionalism of teachers. Method...
An Information Theoretic Radar Tracker Performance Model

This paper describes a new information theoretic approach for modeling the performance of a radar Tracker. Our approach is based on computing the Posterior Cramér-Rao Lower Bound (the so-called “Tracker bound”) as a function of radar capabilities, locations, and target state. The main contribution of this paper is an extension to more closely model fielded trackers which exhibit a series of track-drop and re-initialization events during the target lifetime. We account for this phenomena by marginalizing the Posterior (Bayesian) information matrix with respect to the tracker start time. We show that this new approach allows us to very closely predict the behavior of a radar tracker by comparing the new performance prediction to Monte Carlo runs of a tracker on a model 3-radar tracking problem with centralized fusion.
‘Alla finfine sono daccordo’: A Corpus-Based Case Study on Italian Adverbial Phrases Grammaticalization

We present results of a corpus-based synchronic study on the grammaticalization of Italian adverbial phrases. In particular, we claim that spelling irregularities of adverbial constructions provide evidence of ongoing grammaticalization processes. Adverbial phrases are hence already decategorized analytic constructions that are undergoing paradigmaticization and subsequently lexicalization. We selected 40 adverbial phrases of different length (2–5 constituents) at different stages of the process: from completely non-alternating structures to phrases with two (or more) accepted standard spellings. By means of a corpus-based analysis we considered several properties of those constructions (i.e. frequency) and tested their significance with mixed effect modelling analysis. Specifically, we model the presence of spelling irregularities, its measure (i.e. partial or total univerbation), and frequency of irregular forms. Results of such a corpus-based statistical analysis, albeit preliminary, yield several interesting considerations on synchronic factors that facilitate or hinder processes of grammaticalization, especially the role of frequency and number of construction constituents. Findings support current usage-based literature on grammaticalization as constructionalization.
Commentary: Augmented Reality in Superficial Temporal Artery to Middle Cerebral Artery Bypass Surgery: Technical Note

Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona Correspondence: Vance L. Fredrickson, MD, c/o Neuroscience Publications, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, 350 W. Thomas Rd., Phoenix, AZ 85013. Email: [email protected]
Development of a Sharaf Table for Vocabulary in the Qur’an using Rule Based

Sharaf is one of the branch of the Arabic language that is study of word changes. Fi'il (verb) changes into several pattern into two ways, pronoun and type of verb. How to produce words with various types of fi'il and dhomir in one table-shaped wazan, which are only obtained from one verb in the Qur'an. In the process, the user only needs to enter the verb from a wazan, then the output is in the form of other verbs with various fi'il and dhomir from the wazan. The testing data used are two, the first data which contains a list of fi'il patterns that the author took from several book references and the second is data in the form of fi'il (verb) directly from the Qur'an through http://corpus.quran.com. The accuracy of the result 97% .
The Inner and Outer Algebras of Unified Concurrency

Algebras have always played a critical role in Unifying Theories of Programming, especially in their role in providing the “laws” of programming. The algebraic laws form a triad with two other forms, namely operational and denotational semantics. In this paper we demonstrate that algebras are not just for providing external laws for reasoning about programs. In addition, they can be very beneficial for assisting in the development of theoretical models, most notably denotational semantics. We refer to the algebras used to develop a denotational model as “inner algebras”, while the resulting algebraic semantics we consider to be an “outer algebra”. In this paper we present a number of inner algebras that arose in the development of a fully compositional denotational semantics, called UTCP, for shared-state concurrency. We explore how these algebras helped to develop (and debug!) the theory, and discuss how they may assist in the ultimate aim of exposing the outer algebra of UTCP, which we expect to be very similar to Concurrent Kleene Algebra.
Geology of Probable Areas and Its Petrology

India has the fourth largest reserves of the coal in the world. Also, it’s the 3rd largest producer of the coal in the world. This chapter targets the assessment of Gondwana and tertiary coal fields of India, their location in Indian sub-continent, its petro-graphical analysis etc. The following work will also elaborate India’s activities in exploiting this unconventional hydrocarbon source.
Efficient Recognition for Non-Cooperative Target with Symmetric Feature

Efficient recognition for non-cooperative target plays a crucial role in on-orbit service missions. In this paper we proposed an improved feature matching method for efficiently recognizing space non-cooperative target by using its symmetric feature. The symmetric feature of the target model is detected by our proposed symmetry detection algorithm, and the redundant viewpoints are removed according to previous symmetry detection. Experiments were carried out and the result shows that the viewpoints removal procedure leads to significant savings both in computation time and storage occupancy while maintaining the recognition performance.
A Wavelet approach to extract main features from indirect immunofluorescence images

A number of previous studies have shown that IIF image analysis requires complex and sometimes heterogeneous and diversified methods. Robust solutions can be proposed but they need to orchestrate several methods from low-level analysis up to more complex neural networks or SVM for data classification. The contribution intends to highlight the versatility of Wavelet Transform (WT) and their use in various levels of analysis for the classification of IIF images in order to develop a system capable of performing: image enhancement, ROI segmentation and object classification. Therefore, WT was adopted in the de-noise section, segmentation and classification. This analysis allows frequencies characterization (low/high) and with the statistical distributions of the wavelet coefficients will be able to support the medical diagnosis process. In particular, the robustness and the goodness of the segmentation phase must be highlighted and its validation was reported in the section 3.2.1. From the depicted data it is possible to assert that the validation with ground truths produced an accuracy of 90% and that the method, to the best of our knowledge, is superior to other methods, which do not support WT (see Table 1). The advantage of using WT in all levels of abstraction of IIF data analysis lies robustness of the method, and in the rapid understanding, by the end user, of a single method that shows good average results in all levels of analysis.
Theoretical analysis of quantum random walks with stress-engineered optics

Quantum random walks (QRWs) are random processes in which the resulting probability density of the "walker" state, whose movement is governed by a "coin" state, is described in a non-classical manner. Previously, Q-plates have been used to demonstrate QRWs with polarization and orbital angular momentum playing the role of coin and walker states, respectively. In this theoretical analysis, we show how stress-engineered optics can be used to develop new platforms for complex QRWs through relative simple optical elements. Our work opens up new paths to speed up classical-to-quantum transitions in robust photonic networks.
Aporte desde la ESPAM MFL a organizaciones de la Zona 4, mediante el desarrollo de software

Universities have among their objectives to contribute to the society and its immediate environment. This contribution can be framed within a specific project, or be done through the work their students and teachers do. Students of the Faculty of Computing Sciences at ESPAM MFL carry out work related to their training, most of them oriented to the development of programs and systems that can be produced and implemented. This work aims to characterize the organizations in Zone 4 for which the faculty has created software. In this regard, the information of the work carried out by students during five years (2012-2016) was analyzed, applying a categorization based on the type of organization and the sector it belongs to. Besides, the literature search method was applied to determine the contribution of these systems to the development guidelines of the Zone 4. It was determined that 60.91% of the organizations for which systems or applications were developed were public, 35, 45% private, and 3.64% community. The Services area was where the work was mostly oriented with 80% of them. In addition, as part of the contribution to the strategic objectives of the area, 76.36% of the software developed can contribute to the increase of the percentage of people using TICs.
Implementation of a multiview passive-stereo-imaging system with SoC technology

Passive-stereo-imaging as a part of three-dimensional image processing can be applied for many use cases where a depth information is necessary. This is often the case when classical two dimensional image processing get to its borders. Passive-stereo needs at minimum two images of the same object of interest. An initial one-time system calibration is absolutely essential. The usage of more than two sensors offer more system stability and reduce hidden image elements. A variant of semi-global-matching algorithm is used to find the matching points in the image pair and is implemented in the FPGA. The lateral shift of two matching points is called disparity. All disparity values together result in a disparity image which is the basis for a point cloud. By using embedded technologies, a compact and portable acquisition system could be realized. Programmable system-on-chip (PSoC) combining FPGA and ARM computing power in one chip design. This technology is an ideal solution to so acquire the images from the image sensor and calculate the disparity images.
GAN Evaluation by Multi-Method Fusion

Generative adversarial networks (GAN) have made great progress in areas, such as computer vision, but evaluation of GAN models is still a daunting task. Numerous researchers have proposed many methods for GAN model evaluation. However, most methods have strong pertinence, which leads to large deviations in the results of different evaluation methods. To date, no consensus has been reached on which method best captures the advantages and limitations of GAN models. In this study, a multi-method fusion approach is proposed to evaluate GAN models from many aspects, such as accuracy, diversity of the images generated by the model, and similarity with the training images. This method provides a new idea for GAN model assessment. Meanwhile, a strategy similar to ensemble learning is used to analyze the generalization of multi-method fusion for GAN assessment. This method and the human eye cognitive assessment model are used on celebA benchmarks and self-acquired image data sets to generate results. Through human eye cognition and comparison with the latest GAN model assessment method, showing that the multi-method fusion GAN evaluation method proposed in this paper has strong robustness and effectiveness.
Train Carriage Warning System Based on Zigbee Wireless Sensor Network

In order to realize the timely and accurate alarm for abnormal conditions in train carriage, a scheme of safety warning system based on zigbee technology is proposed. The hardware and software architecture of the system are designed. Meanwhile, the workflow and implementation process of each node are elaborated in detail. The system is composed of five parts: sensor node, zigbee router, coordinator, video module and the intelligent terminal. Firstly, the decibels received by the sound sensor are judged through threshold and sent to the coordinator through zigbee router module. Secondly, the video module analyzes the video of the alarming carriage by means of artificial intelligence. Finally, the detailed alarm information is sent to the intelligent terminal. The development cost of the system is low and its installation and maintenance is convenient. It improves the monitoring facilities of train carriages, which can guarantee the accuracy and real-time of the warning. It has good expansibility and portability, which is of practical significance for improving the safety of train operation.
Marketing of Library Management Software Products

Marketing is a human activity and it is the process of developing, promoting, and distributing products in order to satisfy customer needs and wants. Products include both goods and services. Goods are also known as tangible products. Services are things which one may not be able to touch, smell, or taste and are called intangible products. The traditional marketing concept focuses on the flow of goods and services from producer to consumer or user. In modern times, marketing is viewed as the anticipation, management, and satisfaction of demand through the exchange process. Product marketing and service marketing are essentially the same. The basic task of marketing remains the same irrespective of the products or services involved in the deal. Service is an activity or benefit that one party can offer to another that is essentially intangible and does not result in the ownership of anything.
An Ergonomic Framework for Researching and Designing Speech Recognition Technologies in Health Care with an Emphasis on Safety

Automatic speech recognition (ASR) systems and speech interfaces are becoming increasingly prevalent. This includes increases in and expansion of use of these technologies for supporting work in health care. Computer-based speech processing has been extensively studied and developed over decades. Speech processing tools have been fine-tuned through the work of Speech and Language Researchers. Researchers have previously and continue to describe speech processing errors in medicine. The discussion provided in this paper proposes an ergonomic framework for speech recognition to expand and further describe this view of speech processing in supporting clinical work. With this end in mind, we hope to build on previous work and emphasize the need for increased human factors involvement in this area while also facilitating the discussion of speech recognition in contexts that have been explored in the human factors domain. Human factors expertise can contribute through proactively describing and designing these critical interconnected socio-technical systems with error-tolerance in mind.
Obstacle avoidance algorithms for mobile robots

In order to achieve autonomous work of mobile robots in everyday living environments and to achieve sophisticated cognitive functions of robot intelligence, they are required to perform complex movements, taking into account the location of the surrounding static objects, the movement of the mobile objects and the achievement of the predetermined goal. This article discusses the most important approaches in this direction, some of which are shown as an example: Common brain-computer interface (BCI) systems that use EEG and EMG signals; motion planning algorithms, situation understanding and decision making algorithms; Learning from Demonstration paradigm for robust motion control achievement; Connectionist (Deep learning) approach for sophistication object grasping and manipulation behaviors and tools using.
Forecasting Yield Strength of IF Steel based on ANFIS

This paper builds the forecasting model between the yield strength of interstitial free steel and its microstructure. Firstly, feature selection method based on mutual information is used in this paper to choose the input feature of forecasting model. As the results show the size of ferrite grain, shape factor of ferrite grain, size of the second-phase particle, average spacing of the second-phase particle are the key factors affecting yield strength of interstitial free steel. Then, the structure of adaptive neural fuzzy inference system (ANFIS) is identified by subtractive clustering algorithm and the network parameters are trained by hybrid learning algorithm. The result of simulation proves that the proposed forecasting model is superior to the traditional BP neural network in terms of speed of convergence and accuracy of modeling.