Reviewerly/exHarmony huggingface dataset:
IDENTIFIKASI KEANEKARAGAMAN JENIS FAUNA DI GUA GARUNGGANG

The objective of this research is to get Index of species diversity and habitat habitat characteristic in Garunggang Cave in July 2017.  The method used is the method of moving observation and time search. A total of 302 individuals consisting of 5 groups of taxa found in Cave of Garunggang (entrance 3). Species diversity in Cave of Garunggang in relatively medium condition (1 <H '<3) with value of diversity index (H') 1,9 based on variable of diversity type using Shannon-Wiener index. Based on its dominance there are 6 faunas that dominate, namely Hipposideros galeritus, Karstarma jacobsoni, Rhaphidophora Sp, Stygophrynus dammermani, Long leg spiders, and Small spiders. The fauna inside the Cave of Garunggang has a unique habitat such as on the floor, walls and roof of the cave . Cave Garunggang is a horizontal cave with a cave mouth circumference of about 3.7 meters and aisle length about 209 meters. This cave is karst cave (limestone). The diameter of the alley of the cave varies with underground rivers with stone and soil substrate and clear watery. The hallway inside the cave is branched off with several ornaments. In the rainy season the aisles become full of water and become a large underground river, evidenced by the presence of litter on the walls and roof of the cave that was carried by the water during the rainy season. The habitat characteristic of the exokarst Cave of Garunggang is known that the Cave of Garunggang has four zones within it, ie bright zone (cave mouth), transition zone, dark zone and total dark zone. At the bright zone (cave mouth) the temperature ranges from 31.8 ° C - 29.9 ° C, the humidity (Rh) ranges from 67.7% - 76.2% and the light intensity ranges from 475.3 - 848 Lux. At the temperature transition zone ranging from 30.4 ° C - 32.2 ° C, the humidity (Rh) ranges from 72.8% - 77.7%, the light intensity shows 0 Lux and the pH indicator shows the number 7 (normal water). In the dark zone the temperature ranges from 31.4 ° C - 30.4 ° C, the humidity (Rh) ranges from 77.1% - 79.1%, the light intensity shows 0 Lux and the pH indicator shows the number 6 (normal water). The final zone is a total dark zone with temperatures ranging from 30.1 ° C - 30.8 ° C, the humidity (Rh) ranges from 79.7% - 79.2%, the light intensity shows 0 Lux, and the pH indicator shows the number 6 (normal water).
The Impact of Blockchain Technology on Trust in the Supply Chain

Background: Trust is a main issue in supply chain collaboration. Since the Blockchain technology has received lots of attention, researchers and industries started to ask what the impact of BCT on supply chain collaboration is, and how they can benefit from BCT in supply chain relationships. This research is about exploring the impact of Blockchain technology on trust in supply chain relationships. Different interviews were conducted with different companies about the effects of the blockchain on the supply chain. The companies included: Arya Hakim and Nestle, Zalando, VESRES and Modum. Purpose: The aim of this thesis is to identify the impact of private BCT applications on trust in the supply chain.Methodology: The methodology of this study was divided into three phases. The first phase was a literature review that provide the investigated model. The second phase was interviews for the selected cases. In this study, cross-case analysis was done using within-group similarities and intergroup differences technique to analyze the data and to understand the situation of trust. For instance, similarities between different companies were evaluated with regards to blockchain technology, motives and challenges. The third phase was the conclusion and answering the thesis questions. Conclusion: Many researchers pointed out that trust in SC is a major issue as it needs information sharing of sensitive data and openness between the different parties. This report has discussed the importance of technology in influencing behavioral intention. It is mentioned that BCT improves the level of trust in the relationships within SC; however, one hundred percent trust in the records may not be achieved due to human errors in inputting data. As one of its main conclusions, the research especially points out the relationship between trust and information sharing among partners in SC. The degree of information sharing between partners in different industries is varied. Trust is mentioned as an important aspect of managing both positive and negative issues such as increasing profits and reducing risks. One of the drivers to shift traditional information sharing toward BCT i consumers' trust. Nowadays consumers show an increasing interest in knowing the background of products. Therefore, they need to get clear information, for instance, about production and delivery conditions. Companies try to respond to this need by being more transparent in their supply chain. By facilitating transparency and traceability, BCT is a solution for improving supply chain trust. In this thesis, trust is discussed from two different perspectives, trust between SC partners and trust in the platform. The companies presented in the study are at different levels of trust and our investigation model in this thesis showed that investment in BCT can improve the level of trust.
On a method of applied symbolic dynamics for investigation of dynamical systems

We consider a method of applied symbolic dynamics which may be used to obtain wide spectrum of characteristics of complex dynamical systems: approximation of invariant sets, estimation of topological entropy and approximation of invariant measures. The method has received wide acceptance in studying complex dynamical systems. The main idea of the method is to describe the system behaviour approximately by means of an oriented graph (called symbolic image). Such a graph is a representation of symbolic dynamical system which is more appropriately known as topological Markov chain. There exists a correspondence between trajectories of a given system and paths on the graph, which allows us to design algorithms for estimation of topological entropy, approximate invariant measures of a given system by using stationary flows on the graph and calculate corresponding metric entropies. These values characterize complex behaviour of dynamical systems such as the existence of trajectories with large periods and chaotic regimes. The results of experiments are given for systems with chaotic dynamics.
LibGuides: CIS 311 - Management Information Systems: for Randy McCoy's students: Reference Sources

This is a core class for the Bachelor of Business Administration in which most students get their first experience with using library research tools relating to business.
Qualitative Methods in Information Research

The paper is aimed at review of qualitative methods in information research. Theoretical sources of the qualitative research style are identified, using methodologies applied from psychology, social psychology and phenomenography. Analytical procedures in qualitative methods are explained, namely the content analyses, interpretations, concept mapping. Examples of our qualitative studies of relevance, information ecology and information horizons mapping are mentioned. Findings of a recent qualitative study of information behavior of researchers with respect to research creativity are mentioned in detail. The methodology of semi-structured interviews with 19 selected top researchers in Slovakia was applied. Research creativity is determined and visualized by a conceptual map representing the collective discourse of researchers. Perception of research creativity includes innovations, bird´s-eye view, new ideas, overlaps. Differences in domains are considered (interpretations, problem solving, discovery). Support of creativity as part of ecological information interactions is proposed with the emphasis on methodological creativity. Significance of the qualitative style of research in information science is summarized, namely understanding contexts, human experience, intuition, emotions and development of new methodologies.
SUPER-RESOLUTION BASED ON BACK-PROJECTION OF INTERPOLATED IMAGE

Image upscaling to obtain high quality digital image is one of the active research topics as it is applicable in the consumer electronics industries. Traditional image upscaling techniques have low computational complexity and applicable for real-time processing, but reconstructed image often contains artifacts and undesirable visual effect. The relationship between image interpolation and super-resolution leads our assumption that the interpolated image can be further optimized and may be considered as a part of super-resolution algorithm. In this paper, we propose a new image super-resolution method to combine fast image interpolation with iterative back-projection. This method does not require any external pre-trained datasets and has low computation time while the quality of the reconstructed image can be measured up to the high programming complexity methods such as the dictionary and deep convolutional neural networks.
Practically Human. : Performing Social Robots and Feminist Aspects on Agency, Body and Gender.

Through an experimental theatre play, this thesis explores the development of human-like agency in contemporary “social robot” technology. The entrance point of this study is the gender gap and lac ...
Sequential Monte Carlo method for training Neural Networks on non-stationary time series

In this thesis, we study the sequential Monte Carlo method for training neural networks in the context of time series forecasting. Sequential Monte Carlo can be particularly useful in problems in which the data is sequential, noisy and non-stationary. We compare this algorithm against a gradient-based method known as stochastic gradient descent (SGD), a commonly used method for training neural networks. The performance of SGD on forecasting non-stationary, noisy time series can be poor due to the possibility of overfitting on the data. The sequential Monte Carlo method may offer a solution for the problems that arise in forecasting non-stationary time series with SGD neural networks. At the same time, neural networks trained with SGD give deterministic predictions, and there is a need for quantification of the uncertainty in the prediction. Sequential Monte Carlo sequentially samples the weights of the neural network, providing a posterior distribution on the weights and thus the outcome. In this work, the sequential Monte Carlo algorithm is tested and analyzed, with different parameter settings, on four time series to give an overview of the behavior. Furthermore, we apply the SMC algorithm on a convolutional neural network known as WaveNet. We show that the SMC algorithm is very well-suited for forecasting non-stationary time series, and can significantly outperform the gradient-based SGD method. Additionally, we show that for specific time series the SMC algorithm on a convolutional neural network outperforms the SMC algorithm on a fully-connected neural network.
Normalized Convolution Network and Dataset Generation for Refining Stereo Disparity Maps

Finding disparity maps between stereo images is a well studied topic within computer vision. While both classical and machine learning approaches exist in the literature, they frequently struggle t ...
Emotion Extraction from Video Fragments using Gaze Tracking and AdaBoost Classifier

The application of communication between human and computer has been emerging as an important matter in communication with the surrounding environment. If the computer could sense the human’s emotion, it would be easier to establish a connection between the computer and human. Therefore, the extraction of emotions is an important topic in communication between them. For extracting an emotion, which is absolutely undeniable, various biological signals are used. One of the simple and high-precision methods to acquire data from these signals is to implement the eye tracking and the concentration on the screen technique. In this paper, the eye tracking technique is used to extract emotions for the communication between the human and computer. According to the acquired data from the persons and videos, some of the characteristics of signals, including focus areas, pupil diameter, statistical features, and features of videos are extracted. In addition, in order to improve the results, combining the features are proposed. Afterwards, based on two distinct outputs i.e. Arousal and Valence, and employing a linear combination and reducing the dimension, some features are selected separately. Finally, to classify the two-axes associated with the Arousal and Valence in the range of 0 to 9, which is divided into three equal parts; special types of KNN and SVM methods combined with AdaBoost classifier are used. The numerical studies have shown that the average extraction accuracy is 68.66% for Arousal axis, and 74.66% for Valence axis. As a result, the overall accuracy is improved 5.5% compared to the previous works, respectively.
Identifying finite mixture models in the presence of moment-generating function: application in medical care using a zero-inflated binomial model

This study presents a simple method to identify the parameters in finite mixture models when a moment-generating function (MGF) is present. We obtain the model conditions using a zero-inflated binomial model, a simple form of the finite mixture binary model, and analyze the results using the Monte Carlo simulation. Using the zero-inflated and standard binomial models, we compare the marginal effects of health care usage.
LibGuides: Getting Started with OER: Creative Commons Licensing

This guide is your one-stop-shop for getting started with OER. You will learn the basics, learn about Creative Commons licensing, where to find OER and how to evaluate it, and what's happening with the University of Hartford's OER Initiative.
Sub Bottom Profiler Data Analysis to Identify the Thickness of Sediments (Study Case: Alur Pelayaran Timur Surabaya)

One of the acoustic instruments were used for the measurement of the seabed is the Sub Bottom Profiler. This instrument uses a low-frequency acoustic signal which has the ability to penetrate the layers of the ocean bottom up to a depth of several meters. The purpose of the survey using the Sub Bottom Profiler that is to conduct the investigation and identification of coating the ocean floor so that the retrieved information related to seabed stratigraphy. The location of research are on Alur Pelayaran Timur Surabaya. Secondary data is Raw data Sub bottom profiler, RAW data of single beam, SVP and tide data has been processed. The data retrieved from the District Navigasi kelas 1 Surabaya. The location of the research is classified as waters of the shallow waters. There are three layers of sediment. The pattern of seismic reflection data are parallel and subparallel. Thickness between the base of the sea surface with the first layer has a constituent sediments form the sandy mud. Thickness of the layer of sediment volume values the greatest there is between the first and second layers of 8.009.815.18 m³. The total volume of the thickness of the layer sediment 17,945,928.40 m³.
Forecasting Bitcoin Prices: ARIMA and Seasonal Decomposition Approach

The research is done to forecast the Bitcoin prices, the study considered Bitcoin prices. The data has been collected in an hourly basis from 1st July 2017 to 1st July 2018. The data is of high frequency. The forecast has been made for a period of 12 months from 31st July 2018 to 31st July 2019. The forecasted data has two different periods, one to calculate the error and the other to have an idea of the future price changes. The study uses Autoregressive Integrated Moving Average(ARIMA) and Seasonal Decomposition method for forecasting the Bitcoin prices. This article also helps the investors to have an idea about the future prices of Bitcoin. The forecasted prices also act as a factor for investor decision making, based on the forecast further choices can be made based on the Bitcoin price changes and invest accordingly. The results of this paper have has sown that, between the two models used, ARIMA has resulted to be the best model compared to the seasonal decomposition model as, the Mean Absolute Error, Mean Absolute Percentage Error and Root Mean Square Error is lower in ARIMA forecasting model, which satisfies the objective of the paper and the best model is selected.
Informationsarkitektur, en fråga om designprinciper : En studie av Content Management Systems informationsarkitektur

This study aims to answer the questions whether Content Management Systems follow basic information architecture principles whilst designing and developing its systems. The study outlines the three ...
A Fabry–Pérot Cavity for Rare-Earth-Ion-Doped Nanocrystals

This thesis work contributes to the effort of detecting single rare earth ions doped into crystals,an operation crucial for the development of rare earth quantum computer hardware. Dopingcrystals with rare earth elements, their trivalent ions substitute some of the crystal’s originalbonds. These ions have a partially filled 4f shell, protected by the full 5s and 5p shell from theenvironment which makes them good candidates for qubits.Because not every ion experiences the same electric field from the imperfect crystal, their totallinewidth is inhomogeneously broadened. If the doping is sufficiently low and the crystal sufficiently small, each ion undergoes a different optical shift and can thus be addressed separately.Communication between ions happens due to their permanent dipole moments which changeaccording to their energy level.So far no single ions could be detected in Lund because highly doped bulk crystals were used.It was nevertheless tried to construct quantum logic gates using qubits that consisted of anensemble of ions. Constructing logic gates with these means that every single ion of one qubitneeds to be able to communicate with every single ion of another qubit, a method that becomesincreasingly difficult when more and more qubits are to be entangled. Connecting as manyqubits as possible is a crucial step in building a quantum computer that could outperformclassical computers and this could be facilitated if every qubit consisted of only one ion whichis the reason for the recent explorations towards nano crystals. This development also makesit possible to address another problem of rare earth ions, their low probability of spontaneousemission.Placing nano crystals into an optical cavity promises the enhancement of spontaneous emissionby the Purcell effect. Ideal cavities are Fiber Fabry-Perot resonators of which one side consistsof a mirror coated fiber tip and the other of a plane mirror functioning as the substrate for thenano crystals. It was the aim of this thesis to build a cryostat holder that would bring these twomirrors together with high stability and would allow for vertical and horizontal scanning.
한국 대학생들의 영어 학습 동기 및 탈동기 요인: 영어학습의향, 영어선호도, 영어성취도에 따라

This study investigates the differences in English-learning motivational and demotivational factors according to learners’ intentions to participate...
Design of pedestrian detectors using combinations of scale spaces and classifiers

With the increasing demand for surveillance applications, pedestrian detection has been a topic of interest for many researchers in recent time. The quality of a pedestrian detector is decided in terms of detection accuracy and rate of detection. This paper presents new pedestrian detectors based on two types of classifiers, linear support vector machine and cascade of boosted classifier. These classifiers are trained by using a feature set comprising of the histogram of oriented gradients and dense local difference binary features. Both the image pyramid and non-linear scale space are used to detect pedestrians of various sizes. In order to combine the benefits of the two classifiers, a new two-stage detection scheme is also presented. The detection accuracies of the proposed detectors are studied in terms of miss-rate versus false positive per image and miss-rate versus false positive per window. The performances of the detectors are also compared with the performances of existing detectors of similar type.
Chip hall of fame: SID 6581: This synthesizer chip defined the sound of a generation - [Resources_Geek Life]

This year's inductee into IEEE Spectrum's Chip Hall of Fame is the chip that filled millions of living rooms and bedrooms in the 1980s with a sound that some modern musicians go to great lengths to replicate. For an expanded version of the SID 6581's entry, and to see earlier inductees, visit the hall of fame online.
Ine Vanoeveren, Tomorrow's Music in Practice Today: A Practical Guide Towards Deciphering Contemporary Music. University Press Antwerp, 2018. €32.95

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Effects of Soccer Kicking Training Using Virtual Reality on Kicking Performance in Boy Soccer Players

PURPOSE: Adoption of virtual reality (VR) into sports, games, and educational settings has become popular in recent years, but no evidence regarding VR’s effects on athlete’s performance has been elucidated. This study evaluated an efficacy of VR soccer kicking training system for kicking performance in young soccer players. METHODS: A total of 24 experienced boy soccer players enrolling in a elementary school soccer team was recruited for the 6 months study, and divided into two groups; VR training group (VR-G; n=13, 11.8±1.0 yrs, 148±7.5 cm, 39.0±7.9 kg) and outdoor training group (OT-G; n=11, 11.4±3.4 yrs, 152±9.7 cm, 45.2±10.2 kg). Before (M0) and after (M6) the study, they were tested. For the test, they kicked a ball, in which a sensor was installed, to a curtain screen on which targets were marked by a beam. The VR room was sized 12×8 meter. Using the data of ball speed and target hitting accuracy, a scoring point was calculated for kicking accuracy (Ka) and speed (Ks). They were also tested on a soccer field for measurement of kicking accuracy (Kfa). For the test, they practiced twice and kicked 5 times for measurement. During the study, they were trained for two phases; regular and extra training. For the regular training, the team was trained 4 times/week in a soccer field for 120 min/session. For a total of 15 sessions of extra training, OT-G practiced only kicking on the field, while VR-G did in a VR room. RESULTS: For VR-G, Ka, Ks, and Kfa increased from 53.6±9.5, 26.1±11.8, and 18.6±14.9 at M0 to 62.9±10.0 (t=-6.138, p<.001), 38.0±13.2 (t=-2.396, p<0.05), and 31.9±16.0 unit (t=-2.442, p<0.05), respectively. For OT-G, Ka, Ks, and Kfa were not changed from 58.8±8.9, 35.9±15.5, and 19.6±13.6 at M0 to 63.1±5.7, 29.1±10.0, 22.2±12.8 unit, respectively. No differences were found in 3 kicking variables at M0 and M6 between two groups. CONCLUSION: The regular soccer training and the extra kicking training improved the kicking speed and accuracy in VR-G, while OT-G maintained their performance. VR soccer kicking training program could be a potential substitutional and additional training model for young soccer players. (This research project was supported by the Spors Promotion Fund of Seoul Olympic Sports Promotion Foundation from Ministry of Culture, Sports and Tourism, project # s072016122016)