Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian selection of scaling laws for motion modeling in images

Based on scaling laws describing the statistical structure of turbulent motion across scales, we propose a multiscale and non-parametric regularizer for optic-flow estimation. Regularization is achieved by constraining motion increments to behave through scales as the most likely self-similar process given some image data. In a first level of inference, the hard constrained minimization problem is optimally solved by taking advantage of lagrangian duality. It results in a collection of first-order regularizers acting at different scales. This estimation is non-parametric since the optimal regularization parameters at the different scales are obtained by solving the dual problem. In a second level of inference, the most likely self-similar model given the data is optimally selected by maximization of Bayesian evidence. The motion estimator accuracy is first evaluated on a synthetic image sequence of simulated bi-dimensional turbulence and then on a real meteorological image sequence. Results obtained with the proposed physical based approach exceeds the best state of the art results. Furthermore, selecting from images the most evident multiscale motion model enables the recovery of physical quantities, which are of major interest for turbulence characterization.
Way Around Town 1 Running head: WAY AROUND TOWN Learning your way around town: Virtual taxicab drivers reveal the secrets of navigational learning

We designed a taxi-driver game to study how people learn the spatial structure of a complex environment. Participants drove a taxicab through a computer rendered town, searching for passengers and attempting to deliver them directly to their requested destinations. Experiment 1 demonstrated that as they gain experience within an environment, participants rapidly learn to find direct paths from random pickup locations to target destinations. Experiment 2 used a transfer-of-training procedure to probe the kinds of information that are important for spatial learning. Participants exhibited high degrees of transfer between towns that shared the same spatial layout even when all local views were changed. These results provide direct evidence for the rapid acquisition of a survey representation (analogous to a cognitive map (cf. Tolman, 1948)) of an environment and for the flexible reuse of that representation in perceptually novel environments. Participants in Experiment 2 also showed evidence of interference from previously learned associations among buildings, suggesting that the survey representation contains object-to-object associations in addition to layout information.
Evolution of the Pancaking Effect in a ΛCDM Cosmology

We explore the evolution of the large-scale anisotropy in the velocity field caused by the gravitational pancaking effect assuming a ΛCDM universe. The Millenium Run halo catalogs at four different redshifts, z = 0, 0.5, 1, and 2, are analyzed to find that the pancaking effect starts to affect the hierarchical structure formation at redshift z = 2 when a characteristic pancake scale is around 3 h-1 Mpc. It is also clearly shown how the degree and scale of the pancaking effect changes with time. An analytic model based on the Zel'dovich approximation is presented to explain quantitatively the evolution of the velocity-pancake alignment. A cosmological implication of our finding and a possibility of detecting a signal in real universe are discussed.
Compressed Correlation-Matching for Spectrum Sensing in Sparse Wideband Regimes

In this paper, we consider a novel compressed correlation-matching (CCM) approach for spectrum sensing of wideband sparse signals. We derive a general closed-form estimate of the wideband sparse signal level from compressed observations, while providing physical interpretation of the problem. The formulation allows straightforward application to signal processing problems of interest, such as generalized likelihood ratio test (GLRT) spectrum sensing for wideband cognitive radio. Simulation results are reported to assess the behavior of the CCM method.
Capacity evaluation for multi-layer GSM networks with voice and data traffic

GSM network planning requires frequent assessments of cell blocking probabilities in potential network variants under the prospective load, in order to identify a cost-efficient configuration meeting the coverage and capacity targets. Such assessments must take into account that in the prevailing multi-layer GSM network architectures, handover mechanisms balance the load among the layers in order to reduce blocking losses. In this work we propose an analytical way of calculating the overall blocking losses of multi-layer GSM networks with mixed voice and data traffic. Our approach ignores losses caused by interference and avoids snapshot simulations. In an example we show that the proposed capacity evaluation is fast enough to support site selection and cell optimization planning processes in GSM networks.
Ovarian Cancer Cell Adhesion/Migration Dynamics on Micro-Structured Laminin Gradients Fabricated by Multiphoton Excited Photochemistry

Haptotaxis, i.e., cell migration in response to adhesive gradients, has been previously implicated in cancer metastasis. A better understanding of cell migration dynamics and their regulation could ultimately lead to new drug targets, especially for cancers with poor prognoses, such as ovarian cancer. Haptotaxis has not been well-studied due to the lack of biomimetic, biocompatible models, where, for example, microcontact printing and microfluidics approaches are primarily limited to 2D surfaces and cannot produce the 3D submicron features to which cells respond. Here we used multiphoton excited (MPE) phototochemistry to fabricate nano/microstructured gradients of laminin (LN) as 2.5D models of the ovarian basal lamina to study the haptotaxis dynamics of a series of ovarian cancer cells. Using these models, we found that increased LN concentration increased migration speed and also alignment of the overall cell morphology and their cytoskeleton along the linear axis of the gradients. Both these metrics were enhanced on LN compared to BSA gradients of the same design, demonstrating the importance of both topographic and ECM cues on the adhesion/migration dynamics. Using two different gradient designs, we addressed the question of the roles of local concentration and slope and found that the specific haptotactic response depends on the cell phenotype and not simply the gradient design. Moreover, small changes in concentration strongly affected the migration properties. This work is a necessary step in studying haptotaxis in more complete 3D models of the tumor microenvironment for ovarian and other cancers.
Spatial Dependence in Hedonic Property Models: Do Different Corrections For Spatial Dependence Result in Economically Significant Differences in Estimated Implicit Prices?

While data used in hedonic property models are inherently spatial in nature, to date the majority of past regression analyses have used OLS models that overlook possible spatial dependence in the data when estimating implicit prices for environmental hazards. This paper explicitly addresses spatial dependence in a hedonic property model. We use robust testing procedures to determine the existence and type of spatial dependence in our OLS model. After identifying the nature of the spatial dependence, OLS estimates of the implicit price of wildfire risk are compared to implicit prices obtained using a spatial error model with three different spatial weighting matrices. Spatially corrected estimates of implicit prices are often found to be nearly the same as those obtained using OLS. Our results indicate that the inefficiency of OLS in the presence of spatially correlated errors may not always be economically significant, suggesting nonspatial hedonic property models may provide results useful for policy analysis, and spatial and nonspatial hedonic property models may provide results useful for policy analysis, and spatial and nonspatial hedonic property models might be pooled in meta-analysis.
Predicting good fit students by correlating relevant personality traits with academic/career data

This paper discusses part of the main work in field of data science, mining and analytics. Family of algorithms is developed to predict the educational relevance of individuals' talents through lens of personality features (unstructured and semi-structured) and academic/career data. This paper presents progress of results in Good Fit Students (GFS) algorithms and math construct. This work addresses the problems of poor academic performances, low retention rates, drop outs, school transfers, costly readmissions, poor job performances, early job transfers and inefficient utilization/consideration of natural talents. GFS builds a framework and algorithms by correlating and blending social networking personality traits data with academic and career data. The results are promising at this stage of research and show improved predictions and relevant probabilities. Future work is focused on improving the results with more data and adding few more algorithms to the main research/framework.
STATE ESTIMATION IN CHROMATOGRAPHIC SMB PROCESSES WITH LINEAR ADSORPTION ISOTHERMS

Abstract Chromatographic separations are widespread in the fine chemicals and pharmaceutical industries for the downstream processing of complex mixtures with similar thermodynamic properties. In recent years, continuous chromatographic processes, in particular Simulated Moving Bed (SMB) processes are increasingly applied in industry. SMB processes are characterized by a counter-current movement of the liquid and the solid phase which is achieved by switching the inlet and the outlet ports of a closed loop of chromatographic columns periodically. Recent research has focused on the model-based optimization and control of SMB processes. In a model-based approach, plant/model mismatch has to be taken into account. In this paper, the issue of state estimation in SMB processes under plant/model mismatch is addressed. A Kalman filter is designed and successfully applied. The estimation is based on only one measurement device located in the recycle stream of the process.
ForceBoard: using force as input technique on size-limited soft keyboard

Various typing methods of qwerty-based keyboards on smartwatches have been proposed in recent years. However, since each key can only occupy limited input space and our fingers are too big, recent solutions are mainly two-step typing methods. Users have to navigate the desired key on an enlarged keyboard, and then select the target. The two-step process is distant from our physical keyboard experiences, and requires users to frequently change the keyboard layouts. The aim of this paper is to propose a single-step typing technique that allows users to key in a character with a single touch. We introduce ForceBoard, which combines two adjacent keys into one region and uses force as selecting mechanism. By using that, it not only provides more precise selection, but also allows users to type texts without changing the visual contents of keyboard. We conducted a study comparing the performance of ForceBoard with other two state-of-the-art two-step methods, ZoomBoard and SplitBoard. Our results showed that ForceBoard outperformed ZoomBoard significantly with 30.52% on average, and was slightly better than SplitBoard. Furthermore, ForceBoard also received higher preferences on text speed and satisfaction.
Fast food/organic food: Reflexive tastes and the making of 'yuppie chow'

Organic food consumption is one of several new trends in eating read as active opposition to industrialized food provision. While fast food consumption is characterized by compulsive gluttony, manifest in fat bodies, alternative consumption practices are seen to be driven by conscious reflexivity, such that consumers monitor, reflect upon and adapt their personal conduct in light of its perceived consequences. The purpose of this paper is two-fold. One is to examine the evolution of organic food from what Belasco called the 'counter-cuisine' to what organic growers call 'yuppie chow', to show how organic salad mix was the carrier of major changes in the organic system of provision, thereby calling into question the notion that organic food is necessarily an antidote to industrialized food. The other is to problematize the facile dichotomies between fast and slow, reflexive and compulsive, fat and thin, and, hence, good and bad eaters, to show where there is slippage and instability in these categories, in addition to a troubling politics of class and gender. To these ends, I showcase the changing provision of a particular organic commodity (salad mix, or mesclun) in California.
Digital Image Processing of The Ghent Altarpiece: Supporting the painting's study and conservation treatment

Hanging in the Saint Bavo Cathedral in Ghent, Belgium, is The Ghent Altarpiece, also known as The Adoration of the Mystic Lamb (see Figure 1). According to an inscription on the outer frames, it was painted by brothers Hubert and Jan van Eyck for Joos Vijd and? his wife Elisabeth Borluut in 1432. It is one of the most admired and influential paintings in the history of art and has given rise to many intriguing questions that have been puzzling art historians to date [11]. Moreover, the material history of the panels is very complicated. They were hidden, dismantled, moved away, stolen, and recovered during riots, fires and wars. The recovery of the panels by the U.S. Army in the Nazi hoards deep in the Altaussee salt mines has particularly marked memories. One panel was stolen in 1934 and never recovered. Besides varying conservation conditions, the panels underwent numerous restoration treatments and were even partially painted over.
A Study of the Impact of a National Project Based Learning Curriculum (PLTW) on Student Continuation to Postsecondary Institutions

Project based learning (PBL) has increasingly been promoted as a way to increase student interest in the STEM related fields. One such curriculum, Project Lead The Way (PLTW), has gained increasing popularity in middle schools and high schools. A key objective of the PLTW engineering curriculum is to create a more seamless transition for students from secondary school into science, technology, engineering, and mathematics post-secondary programs. PLTW has been implemented in all fifty states; however, there has been sparse research to-date that has rigorously measured the impact of PLTW or other PBL curricula on the student’s choice to persist into postsecondary education We used Iowa’s statewide longitudinal data system to follow multiple cohorts of PLTW participants and nonparticipants from 8 grade into secondary education. We derived a comparable treatment and control group by matching students based on their propensity to enter PLTW, permitting a stronger interpretation of the program’s impact than prior studies. Specifically, the students were matched based on 8 grade standardized test math and science scores, gender, ethnicity, and SES information. We found statistically significant evidence that PLTW increases the odds of a student attending a 2-year college by 64% (p = 0.007) and increases the odds that they attend a 4-year college or university by 52% (p = 0.024). Further studies are being carried out to examine the majors selected by these students and their persistence in post-secondary education. This study has implications for researchers, practitioners, and policy makers regarding the comprehensive evaluation design and the critical role that PBL curricula can play to increase the participation, both generally and within nontraditional groups, in postsecondary STEM education in the U.S.
Two new approaches to spatial interpolation with inherent sidelobe suppression for imaging riometers

Absorption images as obtained by imaging riometers such as IRIS are usually created by interpolating between absorption values for individual beams. For IRIS, the locations of the beam centres serve as grid points for subsequent linear interpolation. Although generally producing good results, the fact that the actual shape of the imaging beams is not considered, potentially introduces errors and can lead to misinterpretations. In this paper, two alternative interpolation methods are introduced. Method A is based on measuring the similarity between simulated reception of individual point sources and actually received data. Method B uses a mathematical model of the sky brightness distribution parametrised by the received data. All interpolation methods are applied to power data, as opposed to absorption data, in order to avoid any errors that might be introduced by intermediate processing steps, especially QDC (quiet-day curve) generation. We apply all methods to synthetically generated test data as well as to three exemplary real datasets which are also compared to a calculated sky brightness distribution obtained from a skymap.
An improved data flushing MAC protocol for IEEE 802.11 wireless ad hoc network

We propose a data flushing data transfer (DFDT) protocol. The distributed coordinate function (DCF) of IEEE 802.11 supports data transmissions using the data-ACK method and the request-to-send/clear-to-send (RTS/CTS) method. The data-ACK method has a low protocol overhead, however, the transmissions are prone to collision. Although the RTS/CTS mechanism reduces the probability of collisions of data packets, the handshaking generates extensive overhead. Another issue with the IEEE 802.11 DCF is the contention for channel access; much bandwidth is wasted with the contention, especially when the mean data length is short. DFDT is capable of sending out multiple data packets from the upper layer, after acquiring channel access by a successful contention, within one frame which we call compiled MPDU (cMPDU). Right after the transmission of the data frame, the destination nodes will reply an positive/negative acknowledgement in a consecutive manner. By using this method, the protocol overhead is relatively lowered while retaining service quality and the waste of bandwidth for contention is also reduced. Simulation results show that DFDT can handle higher traffic load and has better throughput then the IEEE 802.11 MAC protocol.
A software framework for 3 D reconstruction and fracture risk assessment of the proximal femur from dual-energy x-ray absorptiometry

In clinical routine, osteoporosis diagnosis is performed using the areal Bone Mineral Density (aBMD) computed from two-dimensional Dual-energy X-ray Absorptiometry (DXA) images. This measurement of the "projected density" gives a global marker of osteoporosis but is insufficient for an accurate quantification of non-uniform mineral deficiencies. Quantitative Computed Tomography (QCT) is one possible modality for retrieving shape and bone mineral density measurements in 3D, leading to a better characterization of the local bone quality and the fracture risk. However, due to high financial costs and a high radiation dose for the patient, this modality is rarely used in clinical routine for the follow-up of osteoporosis. In this work we show how state-of-the-art techniques and methods for fracture risk assessment of the proximal femur using 3D analysis from single-view DXA images were brought to the research and clinical end-user, through the use of an existing open source framework for fast prototyping of clinical applications.
Determination of the linear mass power spectrum from the mass function of galaxy clusters

We develop a new method to determine the linear mass power spectrum using the mass function of galaxy clusters. We obtain the rms mass fluctuation a (M) using the expression for the mass function in the Press & Schechter, Sheth, Mo & Tormen and Jenkins et al. formalisms. We apply different techniques to recover the adimensional power spectrum Δ 2 (k) from a(M) namely the k e f f approximation, the singular value decomposition and the linear regularization method. The application of these techniques to the rCDM and ACDM GIF simulations shows a high efficiency in recovering the theoretical power spectrum over a wide range of scales. We compare our results with those derived from the power spectrum of the spatial distribution of the same sample of clusters in the simulations obtained by application of the classical Feldman, Kaiser & Peacock (FKP) method. We find that the mass function based method presented here can provide a very accurate estimate of the linear power spectrum, particularly for low values of k. This estimate is comparable to, or even better behaved than, the FKP solution. The principal advantage of our method is that it allows the determination of the linear mass power spectrum using the joint information of objects of a wide range of masses without dealing with specific assumptions on the bias relative to the underlying mass distribution.
Exploiting UML and acceleo for developing Semantic Web Services

Semantic Web Services (SWS) purports to extend traditional Web services with semantic descriptions - leading to services that are machine processable and interpretable. To date, the implementation of semantic services has remained minute both in academia and industry. This is commonly attributed to barriers, such as the complex and heterogeneous semantic description languages, and a lack of mature methods and unified tools that aim to facilitate the development of such services. Moreover, the current solutions that assert to facilitate the development of semantic services are fragmented (i.e. developers are required to use a combination of disconnected tools to realize semantic services). This usually leads to a number of challenges, such as prolonged service development time. Furthermore, existing semantic service development platforms are tightly-coupled to specific semantic description languages, leading to restrictive development environments. This paper proposes a generic and unified approach for designing and developing semantic web services exploiting the Eclipse platform. The key is in using common techniques such as UML - for modelling a variety of semantic services' artefacts, and Acceleo - for automatic code generations of semantic services' artefacts. The main contributions in the proposed solution are: (1) support for the specification and generation of semantic services using multiple semantic description languages, (2) seamless modelling and development of services within a unified environment, and (3) minimization of the barriers associated with the development of semantic services through complexity hiding; decoupling; and extensibility.
Extracting morphemes to improve sentiment analysis for Chinese fund reviews

Fund reviews on the Web can help people to make investment decisions and their size is relatively small comparing with other products, which lowers PMI algorithm performance. Replacing words by morphemes can improve system capability in Chinese language environment, but defining the SO (sentiment orientation) of morphemes is generally a kind of heavy handwork. We propose a methodology to do this job automatically, whose basic idea is to introduce some outside language and statistical resources to assist polarity calculation. Experiments show that the algorithm is effective and the system get better performance.
International Journal of Emerging Technologies in Computational and Applied Sciences ( IJETCAS ) www . iasir

__________________________________________________________________________________________ Abstract:-Nowdays due to easily available hardware and availability of unlicensed frequency spectrum the use of WLANS has increased tremendously. Such WLANS are set up by untrained system administrators with no topology planning. The Access Points are also placed haphazardly. The performance of such Uncoordinated WLANs is greatly affected due to availability of limited number of non-overlapping channels. The Cognitive Radio provides the clients to make use of free channels from licensed spectrum when they are not in use by primary users. Thus in Cognitive environment more channels are available to the clients. This paper describes a novel channel assignment scheme for Cognitive Radios.