Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-organization and information effect in financial market

The paper proposes a self-organization model for bid-ask spread transition in markets. In market microstructure theory, bid-ask spread has been explained as the result of an overall market players' intention. We focus on bid-ask spread transition after market opening and forward to closing, and interpret it by information effect. Our approach is based on a modeling methodology for viscoelastic material, that can consider the memory effect of information for a market system. Under the modeling process, we suggest 2 parameters that are related to a sensitivity effect and relaxation time effect of information into a market. Lastly, we empirically show the model explained as bid-ask spread transition in the Japanese equity market.
Efficient on-chip delay estimation for leaky models of multiple-source nets

An algorithm for efficiently computing an Elmore approximation in a leaky RC tree which may contain any number of uniformly distributed RC segments is presented. This algorithm works in the frequency domain, and it owes much of its efficiency to the fact that intermediate results leftover from computation of the driving-point admittance approximation are reused. The algorithm for computing an Elmore approximation starts at the output of the active source gate and proceeds downstream, in a finite sequence of steps, to the input of a specified load gate. <<ETX>>
Circulating type motor bearing current in inverter drives

Motor bearing currents in inverter drives have become an important issue as very fast turn-off switching devices have become available for medium horsepower applications (10-100 HP). In previous work a noncirculating type of bearing current caused by parasitic capacitive coupling from stator windings to the rotor was identified. In this paper a new circulating inductive type of bearing current is reported. A theory for the existence of this new type of bearing currents in inverter-motor drives is proposed. It identifies the fact that unbalanced currents flow in the two coil sides of a motor winding due to distribution of capacitive coupling currents. The current unbalance produces a high frequency magnetic flux surrounding the motor shaft and thus causes a bearing current to circulate in the conductive loop formed by the stator case, rotor shaft and end bearings. The amplitude of the circulating bearing current depends on the common mode component of capacitive coupling currents. The analysis is verified by experimental measurement or bearing currents. The findings also provide insight to determining solutions for attenuating these destructive bearing currents.
TOURIST DESTINATION DEVELOPMENT STRATEGIES AND THE IMPACT ON TOURIST VISITS CASE STUDY: PURA GUNUNG KAWI IN SEBATU VILLAGE, GIANYAR, BALI

Pura Gunung Kawi Sebatu is a tourist destination in Bali. The temple is located in Sebatu Village, Tegallalang, Gianyar Regency. However, unlike most tourist destinations in general, Gunung Kawi Temple is infrequently visited by both foreign and domestic tourists, especially when compared with similar destinations, such as Pura Tirta Empul Tampaksiring. The purpose of this study is to determine the development strategy of “Pura Gunung Kawi Sebatu” and the impact of tourist visits on the welfare of community in Sebatu Village. This study used qualitative descriptive approach which aims to describe, record, analyze, and interpret current conditions of Pura Gunung Kawi Sebatu. The results from this study is the development strategies of Pura Gunung Kawi relies on some factors such as: the stability of various levels, such as security, comfort, support facilities and infrastructure; the quality and quantity of human resources; partnerships with funding agencies; the linkage function development of tourism activities; increased community participation in tourism development; and programs implementation for effective promotion on an ongoing basis. These stabilities help increase the number of tourist visits, which leads to community’s welfare in the area surrounding Pura Gunung Kawi Sebatu.
Throughput optimization in single commodity slotted ALOHA multi-hop packet radio networks

The authors investigate the maximum throughput that can be supported between a pair of nodes in a multihop packet radio network using slotted ALOHA. The optimization problem can be formulated as a nonlinear programming problem. The authors study different topologies where source and destination are connected with a number of independent paths and consider the cases in which the flow from source to destination is equally split among all of the independent paths connecting them or optimally split in order to maximize the throughput. For the equal split case and networks with three or more independent s-d paths, it is possible to find a closed-form expression for the maximum throughput and the optimum transmitting probabilities for each node. For optimally splitting the flow among the alternate paths, the authors solve the optimization problem for some small configurations and find a singular behavior for the network with two independent paths two hops each in length. <<ETX>>
Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events

More than half of the global land area undergoes seasonal frozen and thawed conditions that constrain eco-hydrological processes. The freeze-thaw (FT) retrieval from satellite microwave remote sensing detects landscape changes between frozen and non-frozen conditions due to the strong dependence of surface microwave emissions on liquid water abundance. We conducted an assessment of the latest version (R16) of the NASA Soil Moisture Active Passive (SMAP) Level 3 FT (L3_FT) global product. The L3_FT product provides a global FT classification with 3-day mean temporal fidelity derived using SMAP L-band (1.4 GHz) microwave brightness temperature (Tb) retrievals. The R16 product uses both normalized polarization ratio (NPR) and single channel vertically-polarized Tb (FT-SCV) algorithms to obtain FT retrievals over land areas where frozen temperatures are a significant ecological constraint. The L3_FT product is generated in a standard global grid with similar grid cell resolution (36-km) as the SMAP radiometer footprint. An enhanced 9-km global grid L3_FT product is also produced from optimally interpolated SMAP Tb retrievals. The resulting L3_FT products span a larger domain and longer period (2015–present) than earlier product releases. The L3_FT 36-km results showed a respective global mean annual FT classification accuracy of approximately 78 and 90 percent for descending (AM) and ascending (PM) orbit observations in relation to independent surface air temperature-based FT estimates from ~5000 global weather stations. The FT accuracy was lower in areas with greater terrain complexity, open water and vegetation cover; where the combined land cover factors explained 29–53% of the variability in the SMAP FT global accuracy. The L3_FT 9-km product showed an apparent enhancement of FT spatial patterns, but with ~4% lower accuracy than the 36-km product; the lower 9-km accuracy was attributed to stronger degradation from land cover heterogeneity, particularly in coastal areas, and artifact noise introduced from the spatial interpolation of SMAP Tb retrievals. Selected regional applications indicated product utility in capturing anomalous frost events over Australia and seasonal thaw and spring onset patterns over Alaska. Overall, the L3_FT global accuracy meets or exceeds the FT product science requirements established by the mission, while enabling studies of dynamic FT and water mobility constraints influencing hydrological and ecosystem processes, and global water-carbon-energy cycle linkages.
MORAL UPBRINGING IN THE PROCESSES OF RELIGIOUS EDUCATION

The article is aimed at showing the meaning of moral education in the processes of religious education. The authors pay attention to the meaning of moral values influencing man’s behaviour, attitudes to Self, other people, world, and God. Experience obtained in the relationship with Self, others and God has a significant role in the trajectory of educational processes, particularly the process of moral upbringing of a person. Attention paid to natural cognition and cognition rooted in God can help underlining the sense of religious education, also religious education of a child. Moral imagination producing moral images becomes the subject for analysis in terms of teacher’s responsibility concerning the selection of literature items, or ways of their analysis. Moral upbringing tightly connected with religious education elicits the meaning of work upon own character and catechesis as a tool enhancing its quality. The research question of this article can be posed: How does moral upbringing participate in the processes of religious education?
Feature Usage Explorer: Usage Monitoring and Visualization Tool in HTML5 Based Applications

Feature Usage Explorer is a JavaScript library, which automatically detects features in HTML5 based applications and monitors their usage. The collected information can be visualized in a Feature Usage Diagram, which is automatically generated from an input json file. Currently, the users of Feature Usage Explorer have to design their own tool in order to generate the json file from collected usage information. This option remains viable when using the library in order not to constraint the user’s choice of preferred data storage. Feature Usage Explorer can be reused in any HTML5 based applications where an understanding of how users interact with the system is required (i.e. user experience and usability studies, human computer interaction field, or requirement prioritization area).
STRUCTURAL PROPERTIES OF PARASITE - HOST INTERACTIONS NETWORKS

The last decade has been marked by a great revolution on understanding of a substantial variety of systems by the application of the complex networks approach. Inside modern ecology, applications range from epidemiology and spatial ecology to species interaction webs (Bascompte, 2003). Notably, by focusing on interaction patterns among species it is possible to describe communities properties more precisely, rather than simply its richness and abundance, thus allowing for a better understanding of the complex trophic relations or even coevolutionary patterns among them. In these networks, each species can be treated as a single node and trophic or mutualistic interactions can be represented by links between nodes. This approach is particularly interesting because even simple characterizations of its structure allow us to retrieve a great deal of information about these systems. Therefore, more precise descriptions of the underlying networks allow more accurate predictions about environmental disturbance consequences, habitat loss, climatic changes and species invasions (Ings, 2009). Coevolutionary networks are better represented as bipartite networks, a specific type of graph. In other worlds, they have two kinds of node, in which interactions occur exclusively among different nodes (Albert e Barabasi, 2001). Each node will have an own number of degree (number of interactions with other nodes). An irregular distribution of these degrees characterizes such networks as complex ones. Basic network metrics can be retrieved from these systems, such as species richness, connectance and linkage density. Also, many coevolutionary networks share common characteristics as a free scale topology. This topology is represented by a distinct degree distribution that fits in a power law function (Barabasi & Albert, 1999) The most studied species networks so far involve predator prey, mutualistic and parasitoid host webs. Only recently new efforts are being made to include parasites in food webs and network analysis (Lafferty, 2008a). This kind of investigation is of major importance, given that parasites play essential roles in communities functioning. Parasitism is also one of the most diffused consuming strategies among all organisms (Lafferty, 2008b). Their biomass is significantly high and may surpass that of top predators (Juris et al., 2008). Through modifications of its host’s physiology and behavior, they consequently alter the influence of these over the dynamic of communities (Wood et al., 2007).
A Linear Regression Approach to Numerical Simplication in Tree-Based Genetic Programming

We propose a novel approach to simplication in tree-based Genetic Programming to com- bat program bloat, based upon numerical relaxations of algebraic rules. We also separate proposal of simplications (using linear regression, removing redundant children, and replacing small ranges with a constant) from an acceptance criterion that checks the effect of proposed simplications on the evaluation of training examples, looking several levels up the tree. We test our simplication method on three classication datasets and conclude that the success of linear regression is dataset depen- dent, that looking further up the tree can catch unwanted bad case simplications, and that CPU time can be signicantly reduced while maintaining classication accuracy on unseen examples.
Examining the social networks of malware writers and hackers

A substantive body of research has emerged exploring the social dynamics and subculture of computer hacking. Few, however, have considered the structure of social networks in the hacker community due in part to the lack of visible information about active hackers or malware writers. Our research focuses on the rarely studied subject of underground networks of computer hackers. Thus, this study explores the social networks of a group of Russian hackers using publicly accessible data to understand the nature of social relationships and the ways that they affect information sharing and action. The findings demonstrate that there are a limited number of highly skilled hackers relative to those with some knowledge of computers. Additionally, those hackers with substantive technical skills are centrally located within friendship networks and are the focus of greater attention overall. The impact of these findings for our understanding of computer hacking, and peer networks generally are considered in detail.
Hydraulic conductivity of peat in Western Siberia

The paper aims at estimating hydraulic conductivity of peat. It is a complicated process since peat has some unique properties that are not typical for mineral soils. Other difficulties involve the lack of elaborated procedure for laboratory testing and data processing, high sensitivity of peat soils to external and internal factors; which leads to considerable fluctuation in peat hydraulic conductivity values. The specific properties of hydraulic conductivity in peat soils are proved by numerous experimental data. The article also provides the permeability values for the most typical peat species in Western Siberia. The obtained data allow forecasting peat soil response to the development of peatlands.
Domain Adaptation in Machine Learning and Speech Processing

Logistics There will be a 15-minute break at 10:15. Domain adaptation wiki: Please visit it for more information and references. Mismatch between the training data and what the model encounters in real life. but in use, it receives data from a different, target distribution What are the strategies? In this tutorial, we discuss three major paradigms Select instances Transform features Adapt models Many methods have been proposed and shown to be effective. θ k : parameter vector for the k-th model/task Θ: collection of all θ k in a matrix p(x) : marginals of x p(x, y): joint probability of x and y p(y|x; θ): posterior of y, parameterized by θ E p(x) [x]: expectation of x S: denote the source domain T : denote the target domain
Design and Implementation of Network Public Opinion Analysis System

Network public opinion analysis is an important way of information analysis processing. This paper based on the research of the related technologies, designs and realizes a new network public opinion analysis system. System mainly includes network data fetching part, fetching the data processing part, analyzes the processed data part and display part of the public opinion analysis results. In the document extraction part, used the web crawler technology, Larbin web crawler to realize the collection of web content; In public opinion information analysis part, the implementation of the new topic adopts an improved Single - Pass clustering algorithm. This algorithm is using of multi-center, using the title and body of the vector to compared two-way ,that is better reflect the dynamics of public opinion topics. Finally, in the network environment of a university, we have the tests repeatedly. The results show that the new public opinion analysis system running is stable and has good efficiency. The thesis has certain value for the development of other information analysis systems in the Internet.
Finite State Machine Based ReconfigurableArchitecture For Image Processor

Adaptively evolvable systems require some reconfigurable capabilities, habituated within the FPGA. FPGA’s can be integrated with either Dynamic Partial Reconfiguration (DPR) or Virtual Reconfiguration Circuits (VRC). Since DPR allows lesser resource utilization on the FPGA available logic, which has a positive repercussion in power consumption compared to VRC’s, we are using FPGA’s with native DPR as our reconfigurable hardware. Evolvable hardware system has been employed to ease automation, in which the reconfiguration is driven by an evolutionary algorithm. Choosing evolutionary algorithm for DPR over the optimization algorithms is because these algorithms are incremental, and hence the processing circuit will be affected only by small changes reducing the reconfiguration times. One of the problems of the evolvable systems is that, they have to be trained to the conditions in which the system will operate. The generation of this training data is done offline, reducing the system’s autonomy. We have proposed the enhancement of this evolvable system by injecting the concept of Finite State Machine which reduces its dependence. Considering that our system concentrates on adaptive image processing, we have utilized the Self Tuning Architecture (STA) based on FSM and combined them with the evolutionary algorithm, to implement the image processor.
Exploring accreditation from the front lines: A qualitative study of staff experiences & perceptions of hospital accreditation

Objective: Relative to the global investment in hospital accreditation programs overall, both the total amount and methodological quality of existing accreditation research is mediocre. To address this apparent gap in knowledge, we undertook a study of the experiences and perspectives of hospital staff, those most underrepresented in the accreditation research literature, including those working on the front lines and non-leaders who may or may not have been directly involved in the preparation for the accreditation survey visit.Methods: Design: Qualitative descriptive interview study. Setting: Tertiary care teaching hospital in Toronto, Ontario Canada. Study Participants: Program directors, unit managers, physicians, nurses, health discipline professionals (HDP), and non-clinical staff.Results: We have grouped what we heard from the data into three major groups of findings which we have titled: a) perceptions of the purpose of accreditation; b) the “work” of accreditation; and c) dissemination gaps regarding results. Informative finding from this study include the fact that participants put surprising value on the accreditation process, although mistaken feel it is mandatory; that the “work” of accreditation can be disappointing and feels disconnected from the bigger QI picture, and that the disconnect also exists in terms of their knowledge of and belief in the actual results of the process.Conclusions: These findings point to potential gaps in the accreditation culture which can be detrimental to the impact of the accreditation process. Such gaps likely exist in other health care organizations and could inform similar evaluations in other settings.
Fractal assessment of wavelet based techniques for improving the predictions of the artificial neural network

Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in great effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. More than 38 years monthly discharge time series of Ghar-e-Aghaj River in Iran are preprocessed using continuous and discrete wavelet transforms in this study. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment. A multi-layer perceptron neural network model was used as the predicting model. The performance evaluation criteria of the models depict the predictability enhancement of the preprocessed time series. The fractal based predictability index also depicted the improvement in the river flow time series prediction. A windowing fractal technique, as a new idea, is employed to evaluate the minimum sufficient length of time series needed for prediction and the maximum valid predicted length of the time series before and after the preprocessing. Results indicated that in case of using the processed time series, while the maximum valid lengths of predictions increase the minimum sufficient lengths for prediction decrease. Results also showed remarkable increase in the preprocessed time series correlation and persistency.
Efficacy of Language Experience Approach on Reading Performance of Dyslexic Students

The aim of this research was investigating the efficacy of language experience approach on reading performance of dyslexic students in fourth grade elementary school in Esfahan. In order to administer this study, 30 students (boys) were selected via random cluster sampling method and assigned randomly to experimental and control groups (each group consists of 15 students). Reading and dyslexia test that its permanence and fluency was confirmed, is using to gather information, the data was analyzed by statistical method of MANCOVA and utilizing the SPSS software, and analyzed by Multivariate Covariance analysis of variance. Findings indicate that language experience approach can improve Reading performance of students with dyslexia. According to the findings, there is meaningful difference between two control and experimental groups on reading performance (P<0.001). Thus, this difference is showing that language experience approach influences improving reading performance of dyslexic students and this approach can be used to enhance reading skill of students.
A Simple CCD Based Lane Tracking System

A low cost system has been developed to measure a vehicle’s lateral position relative to the lane markings on a roadway. The system is capable of tracking white or orange lines, solid or dashed edge lines, while operating in daylight or at night. The tracking system is comprised of two “off-the-shelf” black and white charge coupled device (CCD) video cameras along with commonly available electronic components. The lane tracking system is capable of outputting real time data at 30Hz through an analog output. Using the data from this sensor system it is possible to detect lane changes, determine the magnitude and duration of lane exceedances, and other metrics commonly used by researchers in the transportation community. This paper will discuss the design and performance of the system, processing of the raw lane tracker data, and the benefits and limitations of the technology.