Reviewerly/exHarmony huggingface dataset:
INTEGRATED STOCHASTIC MODELING OF PETROPHYSICAL PARAMETERS FOR THE ESTIMATION OF MINERALOGICAL COMPOSITION OF THE EARTH CRUST

The construction of a new algorithm for spatial modeling of the composition of rocks, which is consistent with the results of geophysical, petrophysical and geochemical studies, is considered. The probability distributions of the quantities simulated – volume concentrations of rockforming minerals and voids and the parameters of the thermally stressed state of the medium – pressure and temperature are used as input parameters of the model. The determination of probability distributions is carried out by statistical processing of the results of geological and geochemical studies for the composition and the introduction of confidence intervals for the results of geophysical studies. The method of conditional moment functions for the problem of seismic acoustics, thermometry, magnetometry and electrometry is used as calculation algorithms. The algorithm is based on a multicomponent matrix model of a medium with ellipsoidal inclusions and has no restrictions on the concentration of components. The algorithm makes it possible to take into account arbitrary symmetry of the medium. The result of the simulation is a statistically significant set of decisions that have a geological meaning and are limited to the probability distribution of the concentrations of rock-forming minerals.
Hand Gesture Recognition Based on Ultrasound Technology: Pre-processing Stage

This paper describes an approach, which can be used as a pre-processing stage for a hand detection and gesture recognition problem. The approach is based on noise cancellation using QRD Recursive Least Squares (RLS) algorithm with double precision arithmetic and exponential forgetting (EF). The paper discusses algorithmic techniques and presents experiments showing how it is possible to calculate the distance between a hand and a device. A series of experiments were performed. During them a time-variant environment regression model and a time-variant hand model as well as different values of the EF factor were used.
Performance comparison of various deep neural network architectures using Merlin toolkit for a Korean TTS system*

In this paper, we construct a Korean text-to-speech system using the Merlin toolkit which is an open source system for speech synthesis.In the text-to-speech system, the HMM-based statistical parametric speech synthesis method is widely used, but it is known that the quality of synthesized speech is degraded due to limitations of the acoustic modeling scheme that includes context factors.In this paper, we propose an acoustic modeling architecture that uses deep neural network technique, which shows excellent performance in various fields.Fully connected deep feedforward neural network (DNN), recurrent neural network (RNN), gated recurrent unit (GRU), long short-term memory (LSTM), bidirectional LSTM (BLSTM) are included in the architecture.Experimental results have shown that the performance is improved by including sequence modeling in the architecture, and the architecture with LSTM or BLSTM shows the best performance.It has been also found that inclusion of delta and delta-delta components in the acoustic feature parameters is advantageous for performance improvement.
Enhanced Fuzzy Assessment Methodology to Find Overlapping in Membership Function Using K Ratio to Find the Yield of Rice

Fuzzy expert systems are designed based on fuzzy logic and deal with fuzzy sets. Many fuzzy expert systems have been developed for diagnosis. Fuzzy expert systems are developed using fuzzification interface, enhanced fuzzy assessment methodology, and defuzzification interface. Fuzzification helps to convert crisp values into fuzzy values. By applying the enhanced fuzzy assessment methodology for rice, the yield parameters of rice can be diagnosed with number of tillers per hill, number of grains per panicle, and 1000 grain weight. Pest and disease incidence becomes simple for scientists. Enhanced fuzzy assessment methodology for rice uses triangular membership function with Mamdani's inference and K Ratio. Defuzzification interface is adopted to convert the fuzzy values into crisp values. Performance of the system can be evaluated using the accuracy level. Accuracy is the proportion of the total number of predictions that are correct. The proposed algorithm was implemented using MATLAB fuzzy logic tool box to construct fuzzy expert system for rice.
A Flexible Heuristic to Schedule Distributed Analytic Applications in Compute Clusters

This work addresses the problem of scheduling user-defined analytic applications, which we define as high-level compositions of frameworks, their components, and the logic necessary to carry out work. The key idea in our application definition, is to distinguish classes of components, including core and elastic types: the first being required for an application to make progress, the latter contributing to reduced execution times. We show that the problem of scheduling such applications poses new challenges, which existing approaches address inefficiently.
SMHC

Modern large-scale datacenters (DCs) consist of thousands of servers and the fine-grained heterogeneity of the hardware configurations among the machines becomes increasingly distinctive. This heterogeneity shows the differences between the machines with respect to their architecture, model, clock speed and caches, size and type of the memory, I/O speed of the disks, and so forth. However, current task-scheduling polices of today's cluster management systems are based on the coarse-grained metrics of resources such as the CPU cores and the size of memory. These policies obviously ignore the influence of the fine-grained heterogeneity between different servers on the task run-time and cannot achieve the optimization of task scheduling. In this paper, we propose SMHC, a synthetic metric which not only encompasses the coarse-grained resource metrics, but also considers the fine-grained heterogeneity of hardware resources to evaluate its impact on the task run-time. Based on SMHC, we propose a task-scheduling policy to schedule the jobs of Spark programs. The experiment results show that the task-scheduling policy with SMHC decreases the run-time of Spark tasks from Hibench by 16.7% on average.
Open Science, Business Analytics, and FAIR Digital Objects

The lack of data interoperability is hindering the emergence of Open Science and making data analytics considerably more expensive than it should be. A new technology, FAIR Digital Objects, is seeking to solve this problem along with several others. FAIR is an acronym for findable, accessible, interoperable, and reusable. Digital Object Architecture is a very general virtual layer to ride on top of any data system, which can solve the interoperability problem for heterogeneous data, much as the Internet solved the interoperability problem for heterogeneous networks. A specific project employing these technology will be described.
Small target tracking using KCF and adaptive thresholding

Recently, visual object tracking has become a vital role in many different applications. It spans various applications like robotics, video surveillance, and intelligent vehicle navigation. In the Counter-UAV (Unmanned Aerial Vehicle) system, in order to shoot down illegal UAVs flying in the sky, it is very important task to accurately track UAV by an image sensor. However, accurate target tracking is a difficult problem because the distance to the target is far, there are severe shape changes, and the target is often obscured. The remarkable method in object tracking is correlation filter based tracker like KCF (Kernelized Correlation Filter). Although the tracker is very competitive in terms of computation time and performance among the state-of-the-art trackers, it has problems related to target drift in tracking process. It comes from that target objects undergo significant appearance variation due to deformation, partial occlusion, camera shaking, and illumination changes. To mitigate the drift problem of the target in CUAV application, we propose a tracking method which uses KCF and adaptive thresholding. When the correlation response is less than a certain value during KCF process, the result of adaptive thresholding adjusts the tracking point. In the experiment, the proposed method was verified by using image sequence obtained by a monochrome camera on the CUAV system.
Fast-RCM: Fast Tree-Based Unsupervised Rare-Class Mining

Rare classes are usually hidden in an imbalanced dataset with the majority of the data examples from major classes. Rare-class mining (RCM) aims at extracting all the data examples belonging to rare classes. Most of the existing approaches for RCM require a certain amount of labeled data examples as input. However, they are ineffective in practice since requesting label information from domain experts is time consuming and human-labor extensive. Thus, we investigate the unsupervised RCM problem, which to the best of our knowledge is the first such attempt. To this end, we propose an efficient algorithm called Fast-RCM for unsupervised RCM, which has an approximately linear time complexity with respect to data size and data dimensionality. Given an unlabeled dataset, Fast-RCM mines out the rare class by first building a rare tree for the input dataset and then extracting data examples of the rare classes based on this rare tree. Compared with the existing approaches which have quadric or even cubic time complexity, Fast-RCM is much faster and can be extended to large-scale datasets. The experimental evaluation on both synthetic and real-world datasets demonstrate that our algorithm can effectively and efficiently extract the rare classes from an unlabeled dataset under the unsupervised settings, and is approximately five times faster than that of the state-of-the-art methods.
Optimization of Project Management Processes Using the A* Project Management System (AStarPM)

The management of complex application development such as video game development warrants a separate consideration. Recurring creative tasks or process chains must be handled simultaneously to tasks of the domains of programming, implementation and testing of all project-relevant results. These drastically divergent domains create a field of tension between inter-task dependencies and resulting temporary team- or competence-related bottlenecks. Current project management approaches such as Scrum, Kanban lack the focussed linearity und structurization of recurring process chains while on the other hand rigid project management systems impede the developer’s empowerment and through incorrect montitoring or prioritization hinder the solution efficiency within the project. This paper discusses a new approach that combines several project management methodologies to address the issues identified. Based on an analysis, a concept is developed and tested prototypically in the form of a project management system. The so called “AStar Project Management” incorporates specific areas from established agile project management methods combined with classic waterfall structures.
A n-out-of-n Sharing Digital Image Scheme by Using Color Palette

A secret image sharing (SIS) scheme inserts a secret message into shadow images in a way that if shadow images are combined in a specific way, the secret image can be recovered. A 2-out-of-2 sharing digital image scheme (SDIS) adopts a color palette to share a digital color secret image into two shadow images, and the secret image can be recovered from two shadow images, while any one shadow image has no information about the secret image. This 2-out-of-2 SDIS may keep the shadow size small because by using a color palette, and thus has advantage of reducing storage. However, the previous works on SDIS are just 2-out-of-2 scheme and have limited functions. In this paper, we take the lead to study a general n-out-of-n SDIS which can be applied on more than two shadow. The proposed SDIS is implemented on the basis of 2-out-of-2 SDIS. Our main contribution has the higher contrast of binary meaningful shadow and the larger region in color shadows revealing cover image when compared with previous 2-out-of-2 SDISs. Meanwhile, our SDIS is resistant to colluder attack.
Directing a Target Person Among Multiple Users Using the Motion Effects of an Image-Based Avatar

We investigate whether an image-based avatar with motion can smoothly direct a target person who has requested guidance. Existing methods that use an avatar generally assume a one-to-one interaction with the user and did not fully consider how the avatar should direct a target person, which is important in interactions with multiple users. When the target person feels that the image-based avatar is facing them and feels that the avatar is directing them, the person judges that the requested guidance has been given. When a nontarget person feels that the image-based avatar is not facing them and also feels that the avatar is not directed towards them, the nontarget person then judges that the requested guidance has not come to them. To direct the target person smoothly, the action-type motion of the image-based avatar and the rotational motion of the video sequence itself relative to the display are important. We performed a subjective assessment of how the target person and the nontarget person feel about the direction by comparing the case where motions were added with the case where motions were not added. The results show that the image-based avatar with the action-type and rotation-type motions is effective for the target person but is not effective for the nontarget person.
Website Analysis: Search Engine Optimization Approach

Search engines play an important role in the popularity of the business. For business to reach masses its website link should appear on the first page of search engine result set. This requires SEO (Search Engine Optimization) focused design of website. Unfortunately website developers do not consider this factor seriously due to this there is lack of search engine optimization tools in designing the websites. One of the crucial website everyone deals with is their bank website and to make bank officials aware about SEO status of their website a dataset of 115 bank website was created for SEO analysis. This analysis resulted in downtrend pattern. Results have shown that banks in India need to focus on search engine optimization while designing their websites. Developers need to consider how Google sort their search results (RankBrain and drain time), CTR (click through rate) etc.
Aspect-based Review Summary Generation with Diversification

With the popularity of online purchases and user feedback system, huge number of reviews about products, services and social issues enable us to judge items through others' experience. However, generating comprehensive and diversified review summaries usually consumes extensive manual efforts. To solve this problem, we propose a generalized automatic pipeline to generate diversified review summary on different aspects. With the certain review corpus, word embedding matrix can be trained and entities in all aspects will be enlarged accordingly. Combining entities and syntax parsing method, adjectives in every aspect are extracted and divided given their sentiments. The final summary is generated by diverse sampling given aspect and sentiment. This pipeline could be transferred to other review corpora in other languages only if new aspects are specified.
Neural-network assistance to calculate precise eigenvalue for fitness evaluation of real product design

When applying genetic algorithms (GAs) in the design real products, reducing the computational cost of fitness functions is one of the major challenges. In some cases, the computational cost of calculating specific eigenvalues is a predominant factor and needs to be reduced. We proposed the use of a GA with "neural-network (NN) assistance," which enables this computational cost to be reduced. With this GA, the NN assistance infers the approximate eigenvalues. Then, these approximate eigenvalues are used when starting the convergence calculation to obtain the precise eigenvalues. This procedure is effective in reducing the total computational cost of some of the fitness functions of real products. In addition, the precision of the eigenvalue is retained because the precise eigenvalues are obtained by the convergence calculation. The results of our case study show that the GA using our method achieves a 3x speed-up in fitness computation while maintaining equivalent solution quality.
Empirical analysis of undergraduates’ satisfaction with access to the University Library Websites

This study examined undergraduate students’ satisfaction with the access to the University Library Websites. Through a survey research approach, the study distributed questionnaire to a sample of 54 final-year Library and Information Science undergraduate students selected from two Library schools in two different universities. Five research questions were answered and the results demonstrated that respondents are satisfied with the University Library Website, particularly the output (contents) followed by the accuracy of information on the Websites; respondents were mostly satisfied with the layout and design, and ease of navigation while mostly dissatisfied with the esthetic interface. Undergraduates visit their University Library Websites because they find it interesting relating with the librarians on social media (Facebook, Twitter, Linkdl), accessed e-resources, and information related to their disciplines. University Library Website is useful as it provides help line, information/news that is enlighten and educating, for downloading material and for having frequently asked questions. Respondents most likely want to see being added to the Websites Information on scholarship, grants and sponsorship locally and internationally, resources, and referrals specific to relevant situations. The study recommended improvement of the esthetic interface of the University Library Websites to increase the level of satisfaction of the undergraduates with the Websites.
Computational Models of Expertise

Abstract This chapter provides an introduction to and overview of both foundational and contemporary research using computational modeling to aid in the scientific understanding of human expertise. The authors note the distinction between computational models constructed within some molar or unified cognitive architecture and models that are more domain or task specific in their psychological assumptions, and present numerous examples of each type. The authors also provide their assessment of this body of research, one that highlights the need for extensive analysis, and even expert-level knowledge of both tasks and the environments in which expert behavior is manifest as a key requirement for successfully modeling high levels of skill or expert performance. Finally, the authors provide their thoughts about promising future directions for research using computational modeling, together with other emerging methodological techniques such as neuroimaging, to provide a comprehensive approach to advance the scientific understanding of human expertise.
Implementation of automatic map based on saliency detection

Abstract As one of the key technologies in film special effects production, virtual reality, augmented reality and digital image editing, image matting has been widely applied. In computer vision, art design and other aspects have played a very important role. In view of the limitations of traditional matting technology on background and the need for a large number of human interactions, this paper adopts an automatic matting algorithm based on saliency detection to solve this problem. Experimental results show that the improved RC algorithm can automatically mat out the images, and has a good effect and high efficiency in detail processing.
Rebecca Horn: devising intersubjective connections

German artist Rebecca Horn (b. 1944) produced some of her most innovative and consequential work during the 1970s, yet the body sculptures she designed have not received the attention they deserve, especially when compared with her later feature films, installations, and machine-like pieces. Horn created her works during the seventies while recovering from a severe lung poisoning that isolated her in a hospital for a long time. Looking closely at the works themselves, Horn’s own statements, and existing art-historical and theoretical commentaries, this study argues that her artistic production of this time articulated a longing for communication that followed her isolation, and considers her pieces to have the potential to transcend one’s own subjectivity in order to explore that of the other and create intersubjective connections between the performers. Her sculptural costumes will thus be interpreted as enabling their wearers to reconsider the perception of their surroundings in a less rational and more intersubjective way. In this paper, Horn’s work makes powerful contact with that of her teacher Franz Erhard Walther, Joseph Beuys, and artist and therapist Lygia Clark.
Preliminary Assessment of the Local Solar Energy Conditions in the Health Resort of Rabka-Zdrój—As a Potential for Using Photovoltaic Micro-Installations

Rabka-Zdrój is a health resort municipality located in Southern Poland. According to data from the European Commission, the yearly sum of global horizontal irradiation in the health resort of Rabka-Zdrój equals 1100 kWh∙m−2. For this analysis, it was taken into consideration databases from three different sources. It was agreed that the Typical Meteorological Year (TMY) for Kraków city would act as reference data as it was elaborated based on years of observation. This data was compared with PVGIS-CMSAF satellite data as well as with our data received from a ground measurement station (LB-714) located in Rabka-Zdrój. The observations of data from the station LB-714 has shown that 70% of measurements obtained in December falls within the range 0–100 W∙m−2. The results of verification show that differences of distribution of average daily horizontal irradiance are significantly smaller than in the case of an inclined plane at a given angle. The dissimilarity between the PVGIS and TMY data could be a result of the application of the estimated model (for PVGIS) for calculating the values of solar irradiance on the inclined plane and also a reference to another measurement period. Values of total solar irradiance obtained for LB-714 after applying the correction factor, present a similar distribution of values to PVGIS, however, they differ significantly to TMY data. The correction factor for the total solar irradiance on the inclined plane, calculated from TMY data, should be used only for estimated calculations.
An Interaction Design Approach of Fitness APP

At present, the number of App users in China is soaring, but it still faces the problem of low user stickiness. The interactive design approach of fitness App is proposed to improve the App and motive users to form the habit of permanent use of fitness App, and ultimately achieve the goal of increasing the fitness App’s stickiness. The ideal fitness App lifecycle can be divided into three stages: the initial trial stage, the habit-forming stage, and the habit-keeping stage. It is proposed that fitness App should improve user experience in three stages of the ideal lifecycle by improving interaction design at the three levels of “instinct level, behavior level and reflective level”. The specific interaction design approach at the instinct level, behavior level and reflective level are also put forward.