Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-histogram and its application in video analysis

The tool for video analysis addressed in this paper is called co-histogram, which is a statistic graph generated by counting the corresponding pixel pairs of two images. A co-histogram shows how the pixels are distributed among combinations of two image pixel values. By means of the co-histogram, we can have a visual perception of a widely used metric, peak signal-to-noise ratio (PSNR), and the symmetry (or weighted symmetry) of a co-histogram is also good for video shot boundary detection and object entering-exiting detection. Co-histogram symmetry is insensitive to camera zooming, which is good for reducing false detection. Co-histogram symmetry is also easily computable and directly intercomparable
A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest

A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived.
Contact Measurement of Flatness of Parts with Low Rigidity

An article deals with a measurement of flatness of thin-walled parts with low rigidity. The flatness is important for quality thin-walled parts made by milling. Measurement of the variation in the flatness of thin-walled components conventional 3-axis, high-speed 3-axis milling was done. In the first part is description of flatness and definition of thin-walled parts. Second part characterizes the measuring system, the principle of measurement and experimental setup. The last part of this work is evaluation of the experiment, which compares different factors to determinate flatness during machining of thin-walled parts.
Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability

This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes according to the time they need to reach a stable state after coronary bypass surgery: less or more than nine hours. On the basis of five physiological variables different dynamic features were extracted. These sets of features served subsequently as inputs for a Gaussian process and the prediction results were compared with the case where only admission data was used for the classification. The dynamic features, especially the cepstral coefficients (aROC: 0.749, Brier score: 0.206), resulted in higher performances when compared to static admission data (aROC: 0.547, Brier score: 0.247). In all cases, the Gaussian process classifier outperformed logistic regression.
Bruch's Membrane Opening Minimum Rim Width Measurement with SD-OCT: A Method to Correct for the Opening Size of Bruch's Membrane

A precise evaluation of the retinal nerve fiber layer thickness (RNFLT) is key for diagnosing and monitoring glaucoma. The Bruch's membrane opening minimum rim width (BMO-MRW) has been proposed as a reproducible assessment of the optic nerve. The BMO-MRW measures the minimum distance from the BMO to the internal limiting membrane. We propose an approach to correct the BMO-MRW using the BMO size for increased accuracy in interindividual comparisons in future studies. Eighty-one healthy patients received SPECTRALIS spectral domain optical coherence tomography measurements for the peripapillary RNFLT and BMO-MRW. We calculated a BMO size-corrected BMO-MRW using the mean BMO size of our cohort. BMO size was defined using the manufacturer-provided BMO area and manually measured BMO perimeter. We observed that the BMO-MRW correlated highly with the perimeter (r = −0.553, p < 0.0001) and the area of the BMO (r = −0.546, p < 0.0001). Using these parameters, we provided a corrected BMO size-adjusted BMO-MRW which was better correlated with the RNFLT compared to the noncorrected one (z = −3.3495, p = 0.0004). We demonstrated the dependency of the BMO-MRW on ONH size. Furthermore, we showed the superiority of the corrected BMO-MRW using either the manually measured optic nerve head perimeter or the automatically provided ONH for future studies.
The Extracellular N Terminus of the Endothelin B (ETB) Receptor Is Cleaved by a Metalloprotease in an Agonist-dependent Process*

The extracellular N terminus of the endothelin B (ETB) receptor is susceptible to limited proteolysis (cleavage at R64↓S65), but the regulation and the functional consequences of the proteolysis remain elusive. We analyzed the ETB receptor or an ETB-GFP fusion protein stably or transiently expressed in HEK293 cells. After incubation of cells at 4 °C, only the full-length ETB receptor was detected at the cell surface. However, when cells were incubated at 37 °C, N-terminal cleavage was observed, provided endothelin 1 was present during the incubation. Cleavage was not inhibited by internalization inhibitors (sucrose, phenylarsine oxide). However, in cells incubated with both internalization inhibitors and metalloprotease inhibitors (batimastat, inhibitor of TNFα-convertase) or metal chelators (EDTA, phenanthroline), the cleavage was blocked, indicating that metalloproteases cleave the agonist-occupied ETB receptor at the cell surface. Functional analysis of a mutant ETB receptor lacking the first 64 amino acids ([Δ2–64]ETB receptor) revealed normal functional properties, but a 15-fold reduced cell surface expression. The results suggest a role of the N-terminal proteolysis in the regulation of cell surface expression of the ETB receptor. This is the first example of a multispanning membrane protein, which is cleaved by a metalloprotease, but retains its functional activity and overall structure.
Multivariable confounding adjustment in distributed data networks without sharing of patient‐level data

It is increasingly necessary to analyze data from multiple sources when conducting public health safety surveillance or comparative effectiveness research. However, security, privacy, proprietary, and legal concerns often reduce data holders' willingness to share highly granular information. We describe and compare two approaches that do not require sharing of patient‐level information to adjust for confounding in multi‐site studies.
Preliminary Report on the Use of Contrast Media in Orbital Radiography *

THE use of contrast media in the orbit dates from 1927, when Staunig and Herrenschwand injected air into the episcleral space, and since that time various media have been used. The ideal medium should provide good contrast in small quantities, be non-irritant, and have suitable qualities of permeation and absorption. The following media will be considered: (1) Air or other gas, (2) Oily media, (3) Water-soluble media, of which it is known that the least irritant is diodone.
Gain-Constrained Recursive Filtering With Stochastic Nonlinearities and Probabilistic Sensor Delays

This paper is concerned with the gain-constrained recursive filtering problem for a class of time-varying nonlinear stochastic systems with probabilistic sensor delays and correlated noises. The stochastic nonlinearities are described by statistical means that cover the multiplicative stochastic disturbances as a special case. The phenomenon of probabilistic sensor delays is modeled by introducing a diagonal matrix composed of Bernoulli distributed random variables taking values of 1 or 0, which means that the sensors may experience randomly occurring delays with individual delay characteristics. The process noise is finite-step autocorrelated. The purpose of the addressed gain-constrained filtering problem is to design a filter such that, for all probabilistic sensor delays, stochastic nonlinearities, gain constraint as well as correlated noises, the cost function concerning the filtering error is minimized at each sampling instant, where the filter gain satisfies a certain equality constraint. A new recursive filtering algorithm is developed that ensures both the local optimality and the unbiasedness of the designed filter at each sampling instant which achieving the pre-specified filter gain constraint. A simulation example is provided to illustrate the effectiveness of the proposed filter design approach.
An adaptive noise mechanism for walkSAT

Stochastic local search algorithms based on the WalkSAT architecture are among the best known methods for solving hard and large instances of the propositional satisfiability problem (SAT). The performance and behaviour of these algorithms critically depends on the setting of the noise parameter, which controls the greediness of the search process. The optimal setting for the noise parameter varies considerably between different types and sizes of problem instances; consequently, considerable manual tuning is typically required to obtain peak performance. In this paper, we characterise the impact of the noise setting on the behaviour of WalkSAT and introduce a simple adaptive noise mechanism for WalkSAT that does not require manual adjustment for different problem instances. We present experimental results indicating that by using this self-tuning noise mechanism, various WalkSAT variants (including WalkSAT/SKC and Novelty<sup>+</sup>) achieve performance levels close to their peak performance for instance-specific, manually tuned noise settings.
Nanofibrous gelatin–silica hybrid scaffolds mimicking the native extracellular matrix (ECM) using thermally induced phase separation

We herein propose a novel way of producing nanofibrous gelatin–silica hybrid scaffolds through thermally induced phase-separation (TIPS) particularly using mixtures of gelatin solution and silica sol, which can mimic the physical structure, chemical composition, and eventually functions of the native bone extracellular matrix (ECM). The gelatin solutions were homogeneously hybridized with various contents of a silica sol using simple magnetic stirring, which enabled the construction of a nanofibrous structure with a uniform distribution of the silica in the gelatin nanofibers. The nanofibrous gelatin–silica hybrid scaffolds showed much better mechanical properties and in vitro biodegradation stability and apatite-forming ability than the nanofibrous pure gelatin scaffold, which were achieved by the presence of a stiff, bioactive silica phase in the nanofibers and the interaction between the silica hydroxyls and the amino group in the gelatin polymer. In addition, the nanofibrous gelatin–silica hybrid scaffold with a silica content of 30 wt% showed reasonably high in vitro biocompatibility. These findings suggest that the highly porous, nanofibrous hybrid structure mimicking the bone ECM can provide an excellent matrix for bone tissue regeneration.
Efficient regionalization techniques for socio‐economic geographical units using minimum spanning trees

Regionalization is a classification procedure applied to spatial objects with an areal representation, which groups them into homogeneous contiguous regions. This paper presents an efficient method for regionalization. The first step creates a connectivity graph that captures the neighbourhood relationship between the spatial objects. The cost of each edge in the graph is inversely proportional to the similarity between the regions it joins. We summarize the neighbourhood structure by a minimum spanning tree (MST), which is a connected tree with no circuits. We partition the MST by successive removal of edges that link dissimilar regions. The result is the division of the spatial objects into connected regions that have maximum internal homogeneity. Since the MST partitioning problem is NP‐hard, we propose a heuristic to speed up the tree partitioning significantly. Our results show that our proposed method combines performance and quality, and it is a good alternative to other regionalization methods found in the literature.
An Indoor Location Algorithm Based on Taylor Series Expansion and Maximum Likelihood Estimation

With Taylor series expansion, the effect of indoor shadowing fading is approximate to additional Gaussian errors of measured propagation distances. Further the average of multiple measurements is expected to decrease the variance of the Gaussian errors. By this means, the key issue in wireless indoor location, large shadowing fading, can be handled. Both simulations and experimental results reveal that this algorithm is effective
Role Mining Using Boolean Matrix Decomposition with Hierarchy

With the increasing adoption of role-based access control (RBAC) in business security, how to apply role mining technology to aid the process of migrating a non-RBAC system to a RBAC system has become an important problem. Numerous approaches have been proposed to use data mining techniques to discover the roles. However, the Boolean matrix decomposition is still little used in role mining, because Boolean matrix decomposition without hierarchy can not express the hierarchical relationships of the RBAC model. In this paper, we propose a new method of Boolean matrix decomposition which can clearly express the hierarchical relationships of the RBAC model. Then, we introduce the cost-utility analysis method in economics to guide the role mining. Our optimization goal is not only to minimize the administration costs, but also to maximize the utility of RBAC configuration in the meanwhile. We further propose a heuristic algorithm to find the optimal solution with the Boolean matrix decomposition. The experimental results demonstrate the effectiveness of our approach.
An Equity-Interest Rate Hybrid Model with Stochastic Volatility and the Interest Rate Smile

We define an equity-interest rate hybrid model in which the equity part is driven by the Heston stochastic volatility [Hes93], and the interest rate (IR) is generated by the displaced-diffusion stochastic volatility Libor Market Model [AA02]. We assume a non-zero correlation between the main processes. By an appropriate change of measure the dimension of the corresponding pricing PDE can be greatly reduced. We place by a number of approximations the model in the class of affine processes [DPS00], for which we then provide the corresponding forward characteristic function. We discuss in detail the accuracy of the approximations and the efficient calibration. Finally, by experiments, we show the effect of the correlations and interest rate smile/skew on typical equity-interest rate hybrid product prices. For a whole strip of strikes this approximate hybrid model can be evaluated for equity plain vanilla options in just milliseconds.
International Adaptations of the Millon Clinical Multiaxial Inventory: Construct Validity and Clinical Applications

This article examines the influence of the Millon Clinical Multiaxial Inventory (MCMI) as a clinical and research instrument beyond the borders of the United States. The MCMI's theoretical and empirical grounding, its alignment with the Diagnostic and Statistical Manual of Mental Disorders (DSM), and scales that can be interpreted both categorically and dimensionally, are the primary features that make the test attractive. We begin with studies that evaluated the construct equivalence of the different language adaptations. Data from the most widely researched non English-language forms (Danish, Dutch, and Spanish) show excellent comparability with Millon's original. Nevertheless, significant problems were noted in efforts to create clinical groups that would allow for equivalence of diagnostic accuracy when using the cutoff scores. Although dimensional aspects of the scale scores were not affected by this, the adapted measures might show attenuated diagnostic accuracy compared with Millon's original. Next, we present MCMI studies conducted in clinical settings to document where the adapted tests have made their greatest impact in the international literature. A wide variety of clinical applications demonstrated broad utility, and given the high number of issues addressed, we think Millon's influence will certainly stand the test of time in different domains and settings.
Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible–infected–recovered (SIR) model, and several attributes of the originating vertices, considering Erdös–Rényi (ER), Barabási–Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.
EFFECTS OF VARIOUS INGREDIENTS ON THE TEXTURE OF MILK JELLY

Effects of various ingredients on the texture of milk jellies prepared from gellan gum, milk powder, sweetener were examined using a sensory test and physical measuring apparatus. The data were analyzed by use of the modification ofScheffe's mixture experiment method in rectangular experimental area in the Scheffe's triangle. “Hardness” and “smoothness” of milk jellies estimated by a subjective method were influenced by the content of gellan gum. The evaluations of “milk flavor” and “sweetness” estimated by a subjective method were varied with the content of sweetener and evaluated as higher for softer milk jellies. The correlation coefficients between “hardness” estimated by a subjective method and “smoothness”, “milk flavor”, and “sweetness” estimated by a subjective method were negative.
QC-LDPC codes and their performance on Power Line Communications Channel

In this paper Low Density Parity Check Codes (LDPC) are introduced in the Power Line Communications Channel (PLC). We investigate how different decoding algorithms, which are applied on LDPC codes, affect the system's performance. Therefore, an iterative belief propagation decoding algorithm as well as a proposed variation of the original bit flipping algorithm are exploited. In addition, a hybrid technique combining these two algorithms is proposed. Irregular LDPC codes of various code rates are studied. Specifically, the cases of 1/2, 1/3, 2/3, 3/4 and 4/5 code rates are investigated. Regarding the irregular LDPC codes, they are constructed in a Quasi-Cyclic form. The system's performance is expressed in terms of the resultant Bit Error Rate (BER) versus the Signal to Noise Ratio (SNR). In order to design the power line communications channel, Middleton's class A noise model is used to account for the system's background and impulsive noise, while Zimmermann's channel model is also used. The OFDM transmission technique is taken into account. Results are derived via computer simulations.
Building multi-layer social knowledge maps with Google Maps API

Google Maps is an intuitive online-map service which changes people’s way of navigation on Geo-maps. People can explore the maps in a multi-layer fashion in order to avoid information overloading. This paper re- ports an innovative approach to extend the “power” of Google Maps to adaptive learning. We have designed and implemented a navigator for multi-layer social knowledge maps, namely ProgressiveZoom, with Google Maps API. In our demonstration, the knowledge maps are built from the Interactive System De- sign (ISD) course at the School of Information Science, University of Pitts- burgh. Students can read the textbooks and reflect their individual and social learning progress in a context of pedagogical hierarchical structure.
Semi-passive dynamic walking for humanoid robot using controllable spring stiffness on the ankle joint

The bipedal humanoid robot WABIAN-2R is developed to simulate human locomotion. Performing a walking motion requires a high torque at the ankle joint. WABIAN-2R consists of harmonic gears in its driveline system which increases the weight of each leg and respectively decreases the energy economy. Therefore, a new idea is proposed and developed in this paper through computer simulation to modify the design of the ankle joint by adding a spring mechanism instead of high gear ratio transmission. The spring stiffness could be controlled by twisting the joint to set the required torque. This helps reduce the energy consumed while walking; by storing and returning part of the energy. Research presented in this paper proposes an important step toward developing the passive dynamics walking into the advanced complex humanoid robots.
P‐155: OLED Display Attached by Patterned Microlens Array for Light Extraction with Negligible Image Blur

We demonstrate a 51.9% luminance enhancement with keeping the image quality index of the display as high as 94%, by attaching a patterned microlens array film on a commercial 2.0‐inch OLED display. By removing the microlens upon the emitting area, light rays in the glass substrate less than critical angle was effectively extracted, which increases the optical intensity and reduces the image blur at the same time.