Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and Tribological Study of Biodegradable Lubrication Films on Si Substrate

A novel method for preparing eco-biodegradable lubricant based on hydroxypropyl methylcellulose (HPMC) via hydration process is demonstrated. The smooth and homogeneous HPMC coating has a uniform thickness (~35 μm). It has been demonstrated that the preparation parameters play a critical role in controlling the lubricating behavior of the coating; in addition, excess HPMC and water concentration suppress the tribology properties. Nevertheless, a remarkable friction-reduction and anti-wear performance has been obtained. Impressively, the preparation parameter of 5% HPMC + 30 mL water significantly improves lubricant performance and durability. A simple approach for the water-degradability evaluation of HPMC is proposed.
Effect of shear on the rheology and crystallization of palm oil.

UNLABELLED This article reports on the impact of shear on crystallization upon cooling of palm oil. Samples were cooled down under shear from 70 to 10 degrees C, then kept at this temperature, while performing rheological measurements using a controlled shear rate rheometer and rheo-optical observations using optical microscopy and small-angle light scattering. Shear rates between 1 and 300 s(-1) were investigated. Two crystallization steps were observed, characterized by associated viscosity increases. The effect of shear on these 2 crystallization processes was investigated. Shear was shown to influence almost all of the steps of the structuring process of the crystallizing palm oil. The spherulite size and growth rate during the 1st crystallization are affected by shear. The onset time of the 2nd crystallization process strongly depends on the extent of shear. The steady state structures after the 1st and 2nd crystallization processes constituted of a suspension of aggregates of spherulites are controlled by the applied shear rate. PRACTICAL APPLICATION The texture of crystallized vegetal fats and subsequent end product properties depend on the structure developed during the crystallization process. This structuring process is strongly influenced by the thermo-mechanical history applied to the product (cooling rate, degree of undercooling, annealing time, application of flow). This article shows how the shear rate as well as extent of shear affects the different steps of the crystallization and aggregation processes in the case of palm oil after the 1st crystallization.
The Feedback Control Cycle of Mineral Supply, Increase of Raw Material Efficiency, and Sustainable Development

Sustainable development with regard to non-renewable resources can best be defined in terms of the inter-generational challenge of the Brundtland commission and the intra-generational challenge worked out in Agenda 21 of the 1992 Rio de Janeiro conference of United Nations Conference on Environment and Development (UNCED). In meeting these challenges, the trilemma of security of supply under conditions of economic viability and environmental sustainability also needs to be addressed in order to achieve sustainable development. To fulfil the natural resources needs of future generations we have three resources at our disposal: (1) the geosphere or primary resources; (2) the technosphere or secondary resources and (3) human ingenuity and creativity driving innovation. Man does not need natural resources as such, only the intrinsic property of a material that enables the fulfilment of a function is required. Any material that can perform the same function more efficiently or cheaply can replace any other material. In our constant drive to secure the supply of efficient raw materials, the feedback control cycle plays an indispensable role by virtue of it reacting to price signals on both the supply and demand sides. The feedback cycle of course goes hand in hand with a continuous learning process. On the supply side, the learning effects are in technology development around primary resources and the increased use of secondary resources; on the demand side with thriftier use of raw materials.
Query-based Music Recommendations via Preference Embedding

A common scenario considered in recommender systems is to predict a user's preferences on unseen items based on his/her preferences on observed items. A major limitation of this scenario is that a user might be interested in different things each time when using the system, but there is no way to allow the user to actively alter or adjust the recommended results. To address this issue, we propose the idea of "query-based recommendation" that allows a user to specify his/her search intention while exploring new items, thereby incorporating the concept of information retrieval into recommendation systems. Moreover, the idea is more desirable when the user intention can be expressed in different ways. Take music recommendation as an example: the proposed system allows a user to explore new song tracks by specifying either a track, an album, or an artist. To enable such heterogeneous queries in a recommender system, we present a novel technique called "Heterogeneous Preference Embedding" to encode user preference and query intention into low-dimensional vector spaces. Then, with simple search methods or similarity calculations, we can use the encoded representation of queries to generate recommendations. This method is fairly flexible and it is easy to add other types of information when available. Evaluations on three music listening datasets confirm the effectiveness of the proposed method over the state-of-the-art matrix factorization and network embedding methods.
Consistency of Risk Measure Estimates

Recently there has been renewed debate about the relative merits of VaR and CVaR as measures of financial risk. VaR is not coherent and does not quantify the risk beyond VaR, while CVaR shows some computational instabilities and is not 'elicitable' (Gneiting 2010, Ziegel 2013). It is argued in this paper that such questions are best addressed from the point of view of probability forecasting or Dawid's 'prequential statistics. ' We introduce a concept of 'consistency' of a risk measure, which is close to Dawid's 'strong prequential principle,' and show that VaR indeed has special properties not shared by any other risk measure.
Long range image enhancement

Turbulent pockets of air in the atmosphere blur and disrupt the Point Spread Function (PSF) of a surveillance system. The PSF peak is offset in location, changed in size and in short exposures (or mild conditions) noticeably fragmented or speckled. These effects result in what is called heat shimmer or scintillation. The turbulence also causes the effective PSF convolution kernel to vary over time as well as across the image. When doing long range surveillance even mild turbulence can significantly degrade the surveillance system performance. This paper discusses an image processing method that tracks the behaviour of the PSF and then de-warps the image to reduce the disruptive effects of turbulence. Optical flow, an average image filter and a simple unsharp mask is employed to respectively track the centre of the PSF, de-speckle the image and regain the sharpness of the image. The algorithm is efficient enough to process 720p video at 10 frames per second on low power CPU-only platforms such as an Intel i5 NUC.
Beyond dominant plane assumption: Moving objects detection in severe dynamic scenes with Multi-Classes RANSAC

We consider the problem of solving moving objects detection in severe dynamic videos captured by a freely moving camera. In complex scenes, especially in indoor scenes, traditional single layer homography and affine transformation model are not strong enough to describe the background motion. This paper utilizes multiple 2D affine transformations to describe the background motion caused by moving camera. Multi-Classes RANSAC is presented to estimate the parameters of the motion model. With an iterative step, it can attempt RANSAC parameters several times(in previous only once), thus fit various data. Background/foreground analysis is also presented, avoiding computing background motion model by foreground motion information. Experiments and comparisons to other motion compensation methods demonstrate the better and more stable performance of the proposed method.
Are Consumers Forward Looking? Evidence from Fiscal Experiments

How changes in current and future income affect consumer spending is a perennial question in macroeconomics and public finance. Theoretical constructs such as the permanent income hypothesis are of limited assistance in resolving this issue, because they neglect borrowing constraints and other market imperfections that can significantly affect the marginal propensity to spend out of current income. Recent empirical work has also proven inconclusive, since whether consumption responds to income fluctuations by more or less than the permanent income hypothesis predicts turns critically upon whether disposable income follows a random walk or is stationary around a longrun trend (see John Campbell and Angus Deaton, 1987). This controversy is unlikely to be resolved conclusively, because it is notoriously difficult to distinguish a stationary but highly persistent time-series from one that is nonstationary. These difficulties suggest the importance of searching for "natural experiments," income shocks with predictable and well-understood effects on future income, to test models of consumer behavior. Changes in federal tax and transfer policy during the last two decades provide several episodes of this type. ' Analyzing the effects of these tax changes is also central to understanding the role of fiscal policy in affecting national saving. This paper examines two aspects of consumer response to tax changes. Section I argues that consumption responds to temporary income tax shocks by more than the permanent income hypothesis would suggest. Results from the 1975 tax rebate in particular suggest that a $1 increase in transitory income raises spending by about 20 cents. Section II examines consumption responses to tax announcements. Although the results are not conclusive, they suggest that some consumers do not adjust consumption in anticipation of tax changes. The final section sketches some implications for analyzing fiscal policy.
Organizing Self‐Organizing Systems

Industrial symbiosis examines cooperative management of resource flows through networks of businesses known in the literature as industrial ecosystems. These industrial ecosystems have previously been portrayed as having characteristics of complex adaptive systems, but with insufficient attention to the internal and external phenomena describing their genesis. Drawing on biological, ecological, organizational, and systems theory, a discontinuous three‐stage model of industrial symbiosis is presented. The model proceeds from a random formative stage involving numerous actors engaging in material and energy exchanges, to conscious recognition and intentional pursuit of network benefits, to institutionalization of beliefs and norms enabling successful collaborative behavior. While there is much variation, with no single path to this outcome, the recognition of benefits is seen as an emergent property characteristic of these self‐organized systems that move beyond the initial stage.
On the Delay-Dependent Stability and Stabilization of Linear Neutral Time-Delay Systems

In this paper, both problems of the stability and stabilization analysis for linear neutral time-delay systems are respectively investigated. The time-delays considered here are assumed bounded but no information to be available. Using Lyapunov functional method, delay-dependent conditions for the stability and stabilization of the systems are presented in terms of linear matrix inequality (LMI). A numerical example is given to illustrate the main results of this paper and make a comparison with the results presented in literatures
Combining Color and Shape Features for Efficient Indexing and Image Retrieval

We present a method for image retrieval by color and shape similarity matching using metric indexing. We extract color features into the HSV color and for shape features extraction we use Fourier descriptors. We index the combined color and shape features vectors into a M-tree. We complement the use of the M-tree with a filtering technique that also permits partial-image matching. We use a similarity measure calculated as an affine linear combination of L1 and L2 metrics. In the refinement query step for color extraction we use a special histogram with a uniform color transition which enables a window-based smoothing during retrieval. Our experimental results show that our technique is both correct and efficient. 2000 Mathematics Subject Classification. Primary 68U10; Secondary 68P20.
A Tour of Modern Image Filtering

Recent developments in computational imaging and restorat ion have heralded the arrival and convergence of several powerful methods for adaptive processing o f multidimensional data. Examples include Moving Least Square (from Graphics), the Bilateral Filter a nd Anisotropic Diffusion (from Machine Vision), Boosting, Kernel, and Spectral Methods (from Mach ine Learning), Non-local Means and its variants (from Signal Processing), Bregman Iterations (fr om Applied Math), Kernel Regression and Iterative Scaling (from Statistics). While these approach es found their inspirations in diverse fields of nascence, they are deeply connected. In this paper: • I present a practical and accessible framework to understan d ome of the basic underpinnings of these methods, with the intention of leading the reader to a broad u nderstanding of how they interrelate. I also illustrate connections between these techniques and more classical (and empirical) Bayesian approaches. • The proposed framework is used to arrive at new insights and m ethods, both practical and theoretical. In particular, several novel optimality properties of algo rithms in wide use such as BM3D, and methods for their iterative improvement (or non-existence thereof) are discussed. • A general approach is laid out to enable the performance anal ysis and subsequent improvement of many existing filtering algorithms. While much of the material discussed is applicable to the wid er class of linear degradation models beyond noise (e.g. blur,) in order to keep matters focused, we consi der the problem of denoising here. ∗Electrical Engineering Department, University of Califor nia, Santa Cruz CA, 95064 USA. e-mail: milanfar@ee.ucsc. edu, Phone:(650) 322-2311, Fax : (410) 322-2312 . with Some New Insights. An earlier version of this manus cript was titled “A Tour of Modern Image Processing”. To learn more, view my talk based on this paper, available at htt p://tinyurl.com/moderntour September 19, 2011 DRAFT
3 D scene stereo reconstruction with the use of epipolar restrictions

In the present paper a new approach to scene digital model reconstruction from pair of stereo images is considered. We propose to perform image matching with use of weight coefficient as a penalty function for the distance from the point to the correspondent epipolar line. Technology implementation for unknown camera parameters is also considered. In this case, identification of the fundamental matrix from corresponding points is performed on the initial stage. The main advantage of this technology is the absence of the image rectification stage which causes additional distortions due to image interpolation. There is an example of scene reconstruction from pair of test images and a digital model reconstruction from satellite images.
INTEGRATION OF ARTIFICIAL NEURAL NETWORK AND GEOGRAPHIC INFORMATION SYSTEM FOR AGRICULTURAL YIELD PREDICTION

The main objective of this study was to develop the Artificial Neural Network (ANN) modules for agricultural yield prediction as an extension of the ArcMap software. The Object-Oriented methodology was used for both design and programming. The application coding was done in VB.NET. The ANN modules developed were tested with longan yield prediction in Chiang Mai and Lamphun provinces. The ANN input data are soil group and climate data for the years 2006 – 2008, which relate to longan yield in 2007 and 2008. All data were normalized in the same range of 0-1 to be suitable as the input of the ANN model. The normalized weekly highest, lowest, and average temperature, average sunlight, and rainfall were interpolated. They were then averaged to spatially represent districts in the study area, which corresponded to the longan yield districts. These data were varied with several input variations. The cross validation process was applied to each variation. The optimal parameters including learning rate, number of nodes in the hidden layer, and number of iterations obtained from testing were 0.4, 6, and 3,000 respectively. These parameters were applied for all training and testing processes. The best accuracy achieved is 99%. The ANN modules developed for the ArcMap environment worked well for longan yield prediction with accurate results despite the limitations of the data set.
A modified Ant Colony Algorithm with local search for capacitated vehicle routing problem

The ant system is a metaheuristic developed for the solution of hard combinatorial optimization problems. Capacitated vehicle routing problem(CVRP) is an important combinatorial optimization problem which has received considerable attention in the last decades. In this paper, through an analysis of the constructive procedure of the solution in the Ant Colony Algorithm (ACA), a CVRP is examined and a hybrid ant colony system coupled with a stochastic local search algorithm(ACAPLS), is proposed. We compare our approach with ACA, some other classic, powerful meta-heuristics and show that our results are competitive.
AdaGEP - An Adaptive Gene Expression Programming Algorithm

Many papers focused on fine-tunning the gene expression programming (GEP) operators or their application rates in order to improve the performances of the algorithm. Much less work was done on optimizing the structural parameters of the chromosomes (i.e. number of genes and gene size). This is probably due to the fact that the no free lunch theorem states that no fixed values for these parameters will ever suit all problems. To counteract this fact, this paper presents a modified GEP algorithm, called AdaGEP, which automatically adapts the number of genes used by the chromosome. The adaptation process takes place at chromosome level, allowing chromosomes in the population to evolve with different number of genes.
In vivo imaging of the bronchial wall microstructure using fibered confocal fluorescence microscopy.

RATIONALE Fibered confocal fluorescence microscopy (FCFM) is a new technique that produces microscopic imaging of a living tissue through a 1-mm fiberoptic probe that can be introduced into the working channel of the bronchoscope. OBJECTIVES To analyze the microscopic autofluorescence structure of normal and pathologic bronchial mucosae using FCFM during bronchoscopy. METHODS Bronchial FCFM and spectral analyses were performed at 488-nm excitation wavelength on two bronchial specimens ex vivo and in 29 individuals at high risk for lung cancer in vivo. Biopsies of in vivo FCFM-imaged areas were performed using autofluorescence bronchoscopy. RESULTS Ex vivo and in vivo microscopic and spectral analyses showed that the FCFM signal mainly originates from the elastin component of the basement membrane zone. Five distinct reproducible microscopic patterns were recognized in the normal areas from the trachea down to the more distal respiratory bronchi. In areas of the proximal airways not previously biopsied, one of these patterns was found in 30 of 30 normal epithelia, whereas alterations of the autofluorescence microstructure were observed in 19 of 22 metaplastic or dysplastic samples, five of five carcinomas in situ, and two of two invasive lesions. Disorganization of the fibered network could be found on 9 of 27 preinvasive lesions, compatible with early disruptions of the basement membrane zone. FCFM alterations were also observed in a tracheobronchomegaly syndrome and in a sarcoidosis case. CONCLUSIONS Endoscopic FCFM represents a minimally invasive method to study specific basement membrane alterations associated with premalignant bronchial lesions in vivo. The technique may also be useful to study the bronchial wall remodeling in nonmalignant chronic bronchial diseases.
The Long-Run Performance of German Stock Mutual Funds

We examine the risk-adjusted performance of open-end mutual funds which invest mainly in German stocks. After briefly discussing the institutional environment in which these funds operate, we focus on the benchmark problem and the risk adjustment problem. Our data set includes all German funds sold to the public in 1972, our performance analysis covers the time period 1973 to 1998. In our empirical analysis, we first look at the rates of return of individual funds and at the unweighted average rates of return of all funds in our sample. When we apply the Sharpe and Jensen measure to the latter time series in the traditional way, the funds underperform the appropriate benchmarks by approximately 1.5% per year, which is significant both from the statistical and the economic perspective. Applying the Sharpe and the Jensen measure in the traditional way creates a bias from the perspective of long-term investors, because the analysis is based on the arithmetic, not the geometric mean return. To avoid this bias we look, in a second step, at the returns of investors who risk adjust their fund investments ex-ante by borrowing or lending with the objective, that the future risk of his levered portfolio matches that of the chosen benchmark. When we again apply the Sharpe and the Jensen measure to the unweighted average rates of return, the underperformance is reduced by 40%. For large funds, on the average, the underperformance is less than for small funds. When we look at the value-weighted means of individual fund returns, the underperformance nearly disappears.
Anonymous Payment in a Client Centric Model for Digital Ecosystems

Most of the payment protocols designed in recent years for mobile payment systems are based on a scenario where all the entities are directly connected to one another. This scenario (formally called "full connectivity scenario") offers advantages to protocol's designers because it allows them to simplify the design and development of payment protocols without losing security guarantees. However, the "full connectivity" scenario does not consider those situations in which the merchant cannot communicate with the acquirer due to absence of Internet access in his/her infrastructure, and the use of other communication technologies is unaffordable due to the inconveniences and costs associated. In order to overcome this restriction and contribute to the progress of m-commerce, in this paper we propose a novel anonymous protocol for a mobile payment system based on a client centric model that employs a digital signature scheme with message recovery using self-certified public keys. As a result, our proposal illustrates how a merchant can sell goods in a secure way even if she can not directly communicate with the acquirer.
Hiring Risk and Labour Market Equilibrium

This paper introduces asymmetric information about workers' abilities into the turnover-training model of Phelps (1994) and Salop (1979). This makes hiring an investment under uncertainty. We show that an increase in the level of uncertainty reduces the rate of hiring, increases the optimal wage, and reduces steady-state employment. We conclude that the optimal rate of hiring by firms with hiring pools that have a proportionately high number of young workers is lower, and the rate of employment among these workers lower, since it is more difficult to predict their future performance. Also, the use of statistical discrimination is shown to increase employment because it reduces uncertainty about the ability of new hires. Conversely, anti-discrimination laws and quotas increase the rate of unemployment in this model.