Miracle-dz/UniFAR-FTUs huggingface dataset:
A Parallel Algorithm Based on Dividing of Closure System for Structuring Concept Lattice

With the increasing of the context, the time complexity and the space complexity of structuring concept lattice will be dramatically increased accordingly. The new method of enhancing the structuring efficiency has been paid much attention because it is the premise for being used in a large and complicated data system. So far, there are mainly two structuring methods, collocation and overlay of context and folding search space partition of context. Based on the idea of closure division, this paper introduces a new parallel structuring algorithm termed Para Pruning algorithm. The algorithm can eliminate the redundancy and loss of information during the process of the dividing of the closure system. The experiment result showed the accuracy and validity of the present method by comparing with the Next Closure algorithm.
Yield improvement of exopolysaccharides by screening of the Lactobacillus acidophilus ATCC and optimization of the fermentation and extraction conditions

Exopolysacharides (EPS) produced by Lactobacillus acidophilus play an important role in food processing with its well-recognized antioxidant activity. In this study, a L. acidophilus mutant strain with high-yielding EPS (2.92±0.05 g/L) was screened by chemical mutation (0.2 % diethyl sulfate). Plackett-Burman (PB) design and response surface methodology (RSM) were applied to optimize the EPS fermentation parameters and central composite design (CCD) was used to optimize the EPS extraction parameters. A strain with high-yielding EPS was screened. It was revealed that three parameters (Tween 80, dipotassium hydrogen phosphate and trisodium citrate) had significant influence (P < 0.05) on the EPS yield. The optimal culture conditions for EPS production were: Tween 80 0.6 mL, dipotassium hydrogen phosphate 3.6 g and trisodium citrate 4.1 g (with culture volume of 1 L). In these conditions, the maximum EPS yield was 3.96±0.08 g/L. The optimal extraction conditions analyzed by CCD were: alcohol concentration 70 %, the ratio of material to liquid (M/L ratio) 1:3.6 and the extraction time 31 h. In these conditions, the maximum EPS extraction yield was 1.48±0.23 g/L. It was confirmed by the verification experiments that the EPS yield from L. acidophilus mutant strains reached 5.12±0.73 g/L under the optimized fermentation and extraction conditions, which was 3.8 times higher than that of the control (1.05±0.06 g/L). The results indicated that the strain screening with high-yielding EPS was successful and the optimized fermentation and extraction conditions significantly enhanced EPS yield. It was efficient and industrially promising.
Protecting Against Velocity-Based, Proximity-Based, and External Event Attacks in Location-Centric Social Networks

Mobile devices with positioning capabilities allow users to participate in novel and exciting location-based applications. For instance, users may track the whereabouts of their acquaintances in location-aware social networking applications (e.g., Foursquare). Furthermore, users can request information about landmarks in their proximity. Such scenarios require users to report their coordinates to other parties, which may not be fully trusted. Reporting precise locations may result in serious privacy violations, such as disclosure of lifestyle details, sexual orientation, and so forth. A typical approach to preserve location privacy is to generate a cloaking region (CR) that encloses the user position. However, if locations are continuously reported, an attacker can correlate CRs from multiple timestamps to accurately pinpoint the user position within a CR. In this work, we protect against a broad range of attacks that breach location privacy using knowledge about (1) maximum user velocity, (2) external events that may occur outside the process of self-reporting locations (e.g., social network posts tagged by peers), and (3) information about mutual proximity between users. Assume user u who reports two consecutive cloaked regions A and B. We consider two distinct protection scenarios: in the first case, the attacker does not have information about the sensitive locations on the map, and the objective is to ensure that u can reach some point in B from any point in A; in the second case, the attacker knows the placement of sensitive locations, and the objective is to ensure that u can reach any point in B from any point in A. We propose spatial and temporal cloaking transformations to preserve user privacy, and we show experimentally that privacy can be achieved without significant quality-of-service deterioration.
4. Pyramidal Relaxation 2. Pyramidal Representation 3. Temporal Processing Non-linear Multiresolution Relaxation for Alerting *

This is due partly because the head does not move widely. Localization is accurate: her head, hair, shoulder and neck are segregated from the background. We are grateful to R. Kumar and H.S. Sawhney at University of Massachusetts for providing the image sequence. We would like to thank Michael Unser for his advice and his generous help. We also thank Harry Wechsler for his helpful comments and suggestions. A model for the estimate of local image velocity by cells in the visual cortex " , Figure 4: Results of the relaxation process: (a) first frame of the sequence, (b) the estimate E(x,y,σ); (c) the binary masks; (d) the product between the mask and the first frame of the sequence (full resolution images). (a) (b) (c) (d) As a function of D(x,y,σ k), ∆ 1 corresponds to a parabolic arc for values below T and to a sig-moid arc for values exceeding T (see Figure 3). In order to increment the values of D(2x+i, 2y+j,σ k-1) without changing their dynamic range, a second factor ∆ 2 is computed according to the following expression: (7) where M = max D(x,y,σ k-1). Therefore ∆ 2 represents the maximum allowed increment. If ∆ 1 represents a negative increment, ∆ 2 corresponds to the maximum decrement, i.e. the value of D(2x+i, 2y+j,σ k-1) itself. The relaxation process using ∆ = ∆ 1 * ∆ 2 is repeated until convergence is reached. A small number of iterations are necessary (1-3) to reach stability. Convergence is forced by decreasing the size of the Gaussian operator for the diffusion process. In this way, the values are allowed to change rapidly during the first iterations and then become more stable as the size of the spatial neighborhood is reduced. Two real image sequences are used to show the results of the relaxation algorithm. Two frames were used to compute E(x,y,σ), 4 resolution levels where used to build the pyramid and the full resolution images size is 256 x 256. The first sequence shown in the first row of Figure 4 contains four toy-cars on a carpet, three of which are moving towards the center of the image. Also, the carpet illumination changes dramatically at the top-left corner of the image, creating an illusion of motion. Although objects are well contrasted the sequence is very noisy. The aperture problem appears clearly for the upper-right car since high motion estimates are …
A Soft Vector Control for Transportation Systems by a Neuro-Fuzzy Solution

The paper deals with the synthesis of a speed controller by the neuro-fuzzy techniques. Because the associated electrical drive system (with asynchronous motor and a vector control strategy) is used for a transportation system, the main concern is for obtaining a smooth motion and a robust behavior of the whole system. The fuzzy solution is analyzed comparatively with the standard structure that generated it by training the neural network Different training conditions are taken into account. The influence of the motor parameters, load characteristics, reference value and tuning parameters are considered.
Economic growth and social welfare in the European regions

The differences among the regions of Europe are not only those of income and employment, but there are many other important and different circumstances affecting social welfare: education, health, justice or public satisfaction with government institutions. the purpose of this paper will be to analyse the differences among regions by means of social welfare and economic indicators. Furthermore, with the use of econometric models, we will identify the causal factors underlying these varying circumstances.
Biomarker and competing endogenous RNA potential of tumor-specific long noncoding RNA in chromophobe renal cell carcinoma

Background Accumulating evidence suggests long noncoding RNAs (lncRNAs) play important roles in the initiation and progression of cancers. However, their functions in chromophobe renal cell carcinoma (chRCC) are not fully understood. Methods We analyzed the expression profiles of lncRNA, microRNA, and protein-coding RNA, along with the clinical information of 59 primary chRCC patients collected from The Cancer Genome Atlas database to identify lncRNA biomarkers for prognosis. We also constructed an lncRNA–microRNA–mRNA coexpression network (competitive endogenous RNAs network) by bioinformational approach. Results One hundred and forty-two lncRNAs were found to be differentially expressed between the cancer and normal tissues (fold change ≥1.5, P<0.001). Among them, 12 lncRNAs were also differentially expressed with the corresponding clinical characteristics (fold change ≥1.5, P<0.01). Besides, 7 lncRNAs (COL18A1-AS, BRE-AS1, SNHG7, TMEM51-AS1, C21orf62-AS1, LINC00336, and LINC00882) were identified to be significantly correlated with overall survival (log-rank P<0.05). A competitive endogenous RNA network in chRCC containing 16 lncRNAs, 18 miRNAs, and 168 protein-coding RNAs was constructed. Conclusion Our results identified specific lncRNAs associated with chRCC progression and prognosis, and presented competing endogenous RNA potential of lncRNAs in the tumor.
‘Everything just seems much more right in nature’: How veterans with post-traumatic stress disorder experience nature-based activities in a forest therapy garden

Available evidence shows that an increasing number of soldiers are seeking help for post-traumatic stress disorder. The post-traumatic stress disorder condition has big emotional and psychological consequences for the individual, his/her family and the society. Little research has been done to explore the impact of nature-based therapy for veterans with post-traumatic stress disorder although there is a growing amount of evidence pointing towards positive outcome. This qualitative study aims to achieve a deeper understanding of this relationship from the veteran’s perspective. Eight Danish veterans participated in a 10-week nature-based therapy. Qualitative interviews were conducted and analysed using the interpretative phenomenological method. The results indicated that the veterans have achieved tools to use in stressful situations and experienced an improvement in their post-traumatic stress disorder symptoms.
Wind power forecasting using fuzzy neural networks enhanced with on-line prediction risk assessment

The paper presents an advanced wind forecasting system that uses on-line SCADA measurements, as well as numerical weather predictions (NWP) as input, to predict the power production of wind parks 48 hours ahead. The prediction system integrates models based on adaptive fuzzy-neural networks configured either for short-term (1-10 hours) or long-term (1-48 hours) forecasting. The paper presents detailed one-year evaluation results of the models on the case study of Ireland, where the output of several wind farms is predicted using HIRLAM meteorological forecasts as input. A method for the online estimation of confidence intervals of the forecasts is developed together with an appropriate index for assessing online the risk due to the inaccuracy of the numerical weather predictions.
Efficiently handling clone data: RCF and cyclone

Exchange and inspection of clone information is an essential building block of successful clone management. Until now, a variety of different formats and tools for handling clone data has evolved. This paper presents two of our tools, both of which work closely together. We introduce the Rich Clone Format, which we have developed to standardize and ease the exchange of clone data. Furthermore, we describe our tool cyclone, which fosters the multi-perspective analysis of clone information.
Delay effects on stability of interconnected systems. A control perspective

It is well-known that the interconnection of two or more dynamical systems leads to an increasing complexity of the overall system's behavior due to the effects induced by the emerging dynamics (in the presence or not of feedback loops) in strong interactions (sensing, communication) with the environment changes. One of the major problems appearing in such interconnection schemes is related to the propagation, transport, and communication delays acting "through" and/or "inside" the interconnections. Without any loss of generality, the origin of such delays can be: the physical separation between the systems defining the interconnections, the presence of the human factor in the decision process, or finally the existence of some hierarchy, and/or synchronization at the lowest levels in the decision process in real-time. The aim of this paper is to present briefly some "user-friendly" methods and techniques (only frequency-domain approaches) for the analysis and control of the dynamical systems in presence of time- delays. The presentation focuses more on the main intuitive (algebraic, geometric) ideas to develop theoretical results, and their potential use in applications.
Real-time filter decimator for the Spaceborne Fourier Transform Spectrometer

Large amount of data will be produced by sampling FPAs on the SBFTS instrument, which will be a heavy burden for the following data transferring. Decreasing data rate becomes necessary and beneficial to data transfer and archive. This paper presents an approach to reduce infrared interferometric data rate by real-time filter decimator. The input infrared interferometric data is moved down to base-band by DDC, then passed through low-pass FIR filter. Data rate is down sampled by CIC decimator to a manageable level. The implementation of the whole decimation processing has been designed to use Xilinx FPGA (XC1800A) at present time. The result shows signal processing speed is guaranteed and hardware cost is acceptable. Data rate has been decreased from 114.688 Mbps to 28.672 Mbps. Information has been retained in the band of interest. Although this preliminary investigation is still at laboratory level, both the simulation and hardware test give us confidence to go on with our research further.
Development of RFLP-PCR method for the identification of medically important Aspergillus species using single restriction enzyme MwoI

In this study we attempted to modify the PCR-RFLP method using restriction enzyme MwoI for the identification of medically important Aspergillus species. Our subjects included nine standard Aspergillus species and 205 Aspergillus isolates of approved hospital acquired infections and hospital indoor sources. First of all, Aspergillus isolates were identified in the level of species by using morphologic method. A twenty four hours culture was performed for each isolates to harvest Aspergillus mycelia and then genomic DNA was extracted using Phenol-Chloroform method. PCR-RFLP using single restriction enzyme MwoI was performed in ITS regions of rDNA gene. The electrophoresis data were analyzed and compared with those of morphologic identifications. Total of 205 Aspergillus isolates included 153 (75%) environmental and 52 (25%) clinical isolates. A. flavus was the most frequently isolate in our study (55%), followed by A. niger 65(31.7%), A. fumigatus 18(8.7%), A. nidulans and A. parasiticus 2(1% each). MwoI enabled us to discriminate eight medically important Aspergillus species including A. fumigatus, A. niger, A. flavus as the most common isolated species. PCR-RFLP method using the restriction enzyme MwoI is a rapid and reliable test for identification of at least the most medically important Aspergillus species.
Residual life prediction of rolling bearings for rail vehicles based on Proportional Hazard Model

Condition monitoring data and reliability data were fused, and the residual life prediction method was proposed based on Proportional Hazard Model (PHM) for rolling bearings of rail vehicles. This method can provide basic data support for rail vehicles' operation security and provide guidance for the optimization of maintenance strategy. Firstly, rolling bearings of rail vehicles was briefly introduced. And then, three specific steps of the proposed life prediction method were described in detail, which including sample data collection, parameter estimation and life prediction. Finally, the experiment was carried out which used vibration data and failure event data of the rolling bearings' full life cycle, and the results show that the correlation coefficient between PHM outputs and the targets was greater than 0.9. The experiment results verify the effectiveness and feasibility of the proposed residual life prediction approach based on PHM.
Neuro-Fuzzy Approach for solvıng communıcatıon Network Problems

-- In this paper, traffic control of the communication systems is examined over the ATM (Asynchronous transfer mode) networks. Fuzzy mechanism and adaptive neuro fuzzy mechanism are designed to controlling flow rate on an ATM switch using a specific method of the ABR (Available Bit Rate) service of the ATM technology. Two models are compared in various cases to evaluate performance in traffic control over the network. Results are discussed within the framework of today’s technology requirements and problems.
Airborne Ultrasonic Tactile Display Brain-computer Interface - A Small Robotic Arm Online Control Study

We report on an extended robot control application of a contact-less and airborne ultrasonic tactile display (AUTD) stimulus-based brain-computer interface (BCI) paradigm, which received last year The Annual BCI Research Award 2014. In the award winning human communication augmentation paradigm the six palm positions are used to evoke somatosensory brain responses, in order to define a novel contactless tactile BCI. An example application of a small robot management is also presented in which the users control a small robot online.
A Behavior Based Modeling Process and Verification

The correctness of software behaviors determines whether the software underdevelopment could meet the goal of stockholders and developers. Developing requirements models effectively for large scale and complex systems and describing their behaviors precisely are both obstacles in Requirements Engineering (RE) domain. Based on our research on software behaviors, we put forward a formal language—Behavior Description Language (BDL) to specify the behaviors of applications. A modeling process is outlined based on BDL to model large and complex systems. A set of behavior characteristics are proposed to describe the correctness of the model and a series of verification methods are illustrated to verify these characteristics.
A Systematic Understanding of Successful Web Searches in Information-based Tasks

The purpose of this study is to research how Chinese university students solve information-based problems. With the Search Performance Index as the measure of search success, participants were divided into high, medium and low-performing groups. Based on their web search logs, these three groups were compared along five dimensions of the search process for answers to the assigned tasks: frequency counts of different activities during search process, time allocation on each search activity, search patterns, search query as well as selection of information. The results documented students’ varying abilities to search. The key factor that determines search performance is the effective use of search queries. Successful searchers made use of advanced search options such as extracting relevant and effective key terms from further reading, in contrast with simpler strategies by unsuccessful searchers like adding, removing unimportant words, or using synonyms. Highperforming students also showed more monitoring awareness and strategy, such as changing search engines, reformulation of existing search queries as well as backtracking to task questions.
Spectral disentangling of the triple system DG Leo: orbits and chemical composition

DG Leo is a spectroscopic triple system composed of three stars of late-A spectral type, one of which was suggested to be a δ Scuti star. Seven nights of observations at high spectral and high time-resolution at the Observatoire de Haute-Provence with the ELODIE spectrograph were used to obtain the component spectra by applying a Fourier transform spectral disentangling technique. Comparing these with synthetic spectra, the stellar fundamental parameters (effective temperature, surface gravity, projected rotation velocity and chemical composition) are derived. The inner binary consists of two Am components, at least one of which is not yet rotating synchronously at the orbital period though the orbit is a circular one. The distant third component is confirmed to be a δ Scuti star with normal chemical composition.
Comparison of Information Theory Based and Standard Methods for Exploration in Reinforcement Learning

Exploration is a key part of reinforcement learnning. In the classic setting, autonomous agents are supposed to learn a model of their environment to succesfuly complete a task. Recent works in the field and in related fields have suggested the use of quantities based on Shannon’s information theory to enable agents to do so. The underlying concepts of exploration vary between those works. In this thesis, these different notions of exploration will be introduced and compared. Further, two algorithms based on established dynamic programming methods are introduced to maximize two information theoretic quantities, the entropy of the state distribution and predictive information, a quantity relating the past and the future of the agent. These algorithms are evaluated in two settings: planning with the true world model and in interaction with the environment without prior knowledge. Entropy maximation proved to be possible in both settings while predictive information maximization was only succesful in the first. The behavior resulting from maximizing these quantities is also analyzed.
Semantics in storytelling in Swedish fiction

In this paper, we aim to define foundations and research questions for future large scale exploration of various types of semantic relationships in literature, namely Swedish prose fiction. More specifically, we are interested to get an in-depth understanding of storytelling in Swedish fiction by analyzing and mining the narrative discourse in a small sample of such data, focusing on interpersonal relationships and answering various questions such as how to recognize and assess gender patterns. Our intention is to apply our findings into a much larger scale in the near future in order to obtain useful insights about the social relations, structures, behavior and everyday life of characters found in literary works, thus enhancing the use of prose fiction as a source for research within the humanities and social sciences. Our work is inspired by the notions of distant reading and macroanalysis, a relatively new and often contested paradigm of literary research. In order to achieve our goal we strive for a combination of natural language processing techniques and simple visualizations that allow the user to rapidly focus on key areas of interest and provide the ability to discover latent semantic patterns and structures.