Miracle-dz/UniFAR-FTUs huggingface dataset:
A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.
FILTERING OF TLS POINT CLOUDS FOR THE GENERATION OF DTM IN SALTMARSH AREAS .

Marshes are ubiquitous landforms in estuaries and lagoons, where important hydrological, morphological and ecological processes take place. These areas attenuate sea action on the coast and act as sediment trapping zones. Due to their ecosystem functions and effects on coastal stabilization, marshes are crucial structures in tidal environments, both biologically and geomorphologically, and fundamental elements in wetland restoration or coastal realignment schemes. The spatially-distributed study of the geomorphology of intertidal areas using remotely-sensed digital terrain models remains problematic, owing to their small relief, often of the order of a few tens of centimetres, and to the presence of short and dense vegetation, which strongly reduces the number of resolvable ground returns. Here, we present the results of the application of terrestrial laser scanning (TLS) for the generation of a DTM of the bare soil within a tidal marsh in the Venice lagoon. To this aim we apply a new filtering scheme to Terrestrial Laser Scanner data which selects the lowest values within moving windows, whose optimal size is determined with the aid of a limited number of ancillary Differential GPS data in order to maximize resolution while ensuring the identification of true ground returns. The accuracy of the filtered data is further refined using classifications of the intensity of the returns to extract additional information on the surface (ground or canopy) originating the returning laser beam. By using a low-pass filter with window size of the order of 1 m and the maximum likelihood classifier to further refine the detection of ground signals, laser returns coming from low vegetation (about 0.31.0m high) can be satisfactorily separated from those coming from the marsh surface. The overall result is a new observation technique producing DTMs and DSMs in areas with very small relief, which is shown to provide unprecedented high-resolution and high-accuracy characterizations of marsh morphology.
Bortezomib-Induced Unfolded Protein Response Increases Oncolytic HSV-1 Replication Resulting in Synergistic Antitumor Effects

Background: Bortezomib is an FDA-approved proteasome inhibitor, and oncolytic herpes simplex virus-1 (oHSV) is a promising therapeutic approach for cancer. We tested the impact of combining bortezomib with oHSV for antitumor efficacy. Experimental Design: The synergistic interaction between oHSV and bortezomib was calculated using Chou–Talalay analysis. Viral replication was evaluated using plaque assay and immune fluorescence. Western blot assays were used to evaluate induction of estrogen receptor (ER) stress and unfolded protein response (UPR). Inhibitors targeting Hsp90 were utilized to investigate the mechanism of cell killing. Antitumor efficacy in vivo was evaluated using subcutaneous and intracranial tumor xenografts of glioma and head and neck cancer. Survival was analyzed by Kaplan–Meier curves and two-sided log-rank test. Results: Combination treatment with bortezomib and oHSV (34.5ENVE), displayed strong synergistic interaction in ovarian cancer, head and neck cancer, glioma, and malignant peripheral nerve sheath tumor (MPNST) cells. Bortezomib treatment induced ER stress, evident by strong induction of Grp78, CHOP, PERK, and IRE1α (Western blot analysis) and the UPR (induction of hsp40, 70, and 90). Bortezomib treatment of cells at both sublethal and lethal doses increased viral replication (P < 0.001), but inhibition of Hsp90 ablated this response, reducing viral replication and synergistic cell killing. The combination of bortezomib and 34.5ENVE significantly enhanced antitumor efficacy in multiple different tumor models in vivo. Conclusions: The dramatic synergy of bortezomib and 34.5ENVE is mediated by bortezomib-induced UPR and warrants future clinical testing in patients. Clin Cancer Res; 20(14); 3787–98. ©2014 AACR.
Anonymous Voting by 2-Round Public Discussion

In 2006, Hao and Zieĺınski proposed a 2-round anonymous veto protocol (called AV-net), which provides exceptional efficiency compared to related techniques. In this paper, we add a self-tallying function to the AV-net, making it a general-purpose voting protocol. The new protocol works in the same setting as the AV-net it requires no trusted third parties or private channels, and participants execute the protocol by sending 2-round public messages. Compared with related voting protocols in past work, ours is significantly more efficient in terms of the number of rounds, computational cost and bandwidth usage.
Aspectizing Security Concerns

Most aspects of computer security revolve around rules preventing an entity from performing an action outside of its permitted sphere of influence and inside that of another. The paper discusses a number of different security augmentation methods, such as dynamic wrappers, dataflow analysis based on extensions of type systems, and history-based access control. In general, security checks are crosscutting concerns and are hard to modularize. The paper describes how most of existing methods can be implemented in a more modular and evolutionfriendly fashion with the help of aspect-oriented techniques. Additionally, it proposes how effectiveness of aspectized solutions can be validated and evaluated.
Novel Gating Technique in D-Latch for Low Power Application

This paper is presented with the comparison of gating techniques which are being applied in the dynamic latch comparator circuit. Clock gating techniques are being applied in the circuit is used for the reduction of leakage and other power consumption in the circuit designed. Clock consumes about 70% of power in any circuit, so the controlling of clock signal is required. By controlling the clock signal using the desired technique in the dynamic latch comparator design a better output with higher performance is observed. Controlling of the clock signal reduces the dynamic power in the circuit. Using the clock gating technique in the circuit the switching of the clock signal is controlled. A better performance is observed in the parameters like power consumption, voltage gain, efficiency, delay, leakage power. The circuit is simulated in the cadence virtuoso tool in 45nm technology.
Soft-Constrained Random Walk Propagation for Hierarchical Image Matting

For image matting, the affinity-based algorithms adore the hierarchical propagation to handle the memory problem. But they rely heavily on the accuracy of the pre-segmentation, and the hard input constrains may lead to the detail missing or foreground error. In this paper, we present a random walk based hierarchical algorithm with extended Dirichlet function. Regarding constrains as regularization, the new random walk framework can receive the guidance information from the known or pre-computed regions, while respect the image context as much as possible. Based on this framework, we perform the two levels affinity propagation. First, we conduct the regularized random walk in the superpixel-based graph and obtain the coarse matte which will be served as the soft constraints in the following propagation. Then in the pixel-based graph, the improved random walk is carried out the second time to recover more details for the final matte. Experimental results reveal that the soft constrained approach can propagate more efficiently and preserve more details, which make the proposed method perform better in accuracy and robustness.
IT Governance and Firm Performance: Empirical Study From Saudi Arabia

This study provides additional evidence on information technology (IT) governance and its relationship to firm performance in emerging markets. It aims primarily to determine the level of IT governance in Saudi Arabian companies; it also aims at examining the impact of IT governance on the firm performance. The study target sample is 131 companies taken from 20 sectors of the Saudi financial market; during the year 2017. The researchers have used the IT-related backgrounds of the members of the board of directors as an indicator of IT governance. The researchers have also used another group of corporate governance indicators in addition to a set of control variables. The performance of the companies has been referred to as the operational performance which is represented as Return on Assets (ROA) and the financial performance as the Return on Equity (ROE). The descriptive results have been shocking. The study has shown a sharp decline in IT governance in Saudi companies; only 15% of companies have members of the board of directors with IT-related backgrounds, and the IT governance is not adopted or used in many important sectors. However, the regression analysis shows that there is a positive impact on IT governance only on the operational performance of Saudi companies. The results of this study provide a significant indicator of IT governance in Saudi companies. These results can be also used to develop the corporate governance code to focus more on IT governance.
Local Smoothness Pattern for content based image retrieval

Local binary pattern (LBP), which efficiently summarizes the local structure of images has been very successful in image retrieval applications. In this paper, we propose a Local Smoothness Pattern (LSP) for image retrieval applications which captures the smoothness over the curve directions in a local region. To compare its performance, this technique is applied to a database of 1180 sub-images from the twenty different classes of Brodatz database and is compared with the LBP. Result shows that the proposed technique achieves good retrieval rate.
A quotient subspace algorithm for testing controllability and computing Brunovsky's outputs

An algorithm is proposed for testing controllability and computing the Brunovsky output of a single input system. Rather than computing explicitly the controllability matrix, it operates by building successive images of the input matrix in specific quotient subspaces. The algorithm can be used to test controllability to a higher degree of numerical accuracy than standard controllability tests.
Imaging for new radiotherapy techniques

Abstract Radiotherapy could be considerably improved by the recent development of three-dimensional intensity-modulated radiation therapy. This technique allows the concept of so-called dose painting or adaptive dose distribution to be implemented with improved aligning of the dose distribution along the complex geometric arrangements of the tumour and the surround healthy critical structures. This enables the radiation dose in the tumour to be increasingly enhanced while sparing the normal tissue. Furthermore, many subfields enable the dose distribution within the tumour to be varied considering local differences in the functional tumour characteristics. Tumour heterogeneity or even variations in tumour volume and viability during radiotherapy may be considered. However, the success of the treatment increasingly depends on the capability of oncologic imaging tools to precisely localize and delineate the tumour and to provide information about its functional heterogeneity. The challenge in oncologic imaging is to improve and further develop novel concepts for precise tumour delineation and characterization. Important achievements in biologic imaging with morphologic functional computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET)/CT have the potential to modify the delineation of target volumes and to increase the dose in selected subvolumes. For example, novel PET markers of tumour hypoxia or proliferation have been developed for functional characterization of various tumour entities. Information from several other modalities such as dual energy CT, functional MRI (dynamic contract-enhanced MRI, diffusion-weighted imaging, arterial spin labelling, magnetic resonance spectroscopic imaging (MRSI), etc.) as well as from novel technological advances such as MR/PET may also be integrated in the radiotherapy plan. Data postprocessing with precise spatial coregistration of multimodal morphologic and functional imaging data as well as quality assurance aspects are still challenging. To overcome these problems novel concepts for hardware integration of CT and MRI with linear accelerators (CT/Linac, MR/Linac) are currently under development. The presentation outlines the current concepts of dose painting in radiotherapy for better planning and control of the final dose distribution and discusses the challenges and the potential of modern oncologic imaging in this context.
Overexpression of complement inhibitor Crry does not prevent cryoglobulin-associated membranoproliferative glomerulonephritis.

BACKGROUND Mice overexpressing thymic stromal lymphopoietin (TSLP) develop mixed cryoglobulinemia with renal disease closely resembling human cryoglobulin-associated membranoproliferative glomerulonephritis (MPGN), including glomerular deposits of immunoglobulins and complement. We assessed the effect of complement inhibition through overexpression of Crry (complement receptor-1 related gene/protein Y), which blocks the classic and alternative pathway of complement activation through inhibition of the C3 convertase, in cryoglobulinemia-associated immune complex glomerulonephritis. METHODS TSLP transgenic mice were crossbred with animals overexpressing Crry. Mice were sacrificed after 50 days (females) or 120 days (males), and kidneys, blood, and urine were collected from seven mice of each experimental group (wild type, Crry transgenic, TSLP transgenic, and Crry/TSLP doubly transgenic). RESULTS TSLP/Crry doubly transgenic animals demonstrated expected serum levels of Crry. Renal involvement, both in TSLP transgenic and TSLP/Crry doubly transgenic animals, was characterized by glomerular matrix expansion, macrophage influx, activation of mesangial cells, and deposition of immunoglobulins and complement. Overexpression of Crry did not result in significant improvement of renal pathology or laboratory findings. Expression of recombinant soluble Crry was confirmed by enzyme-linked immunosorbent assay (ELISA) in Crry transgenic animals. However, formation of the membrane attack complex C5b-9 as a marker of terminal active complement components and represented by glomerular C9 staining could not be inhibited in Crry transgenic TSLP mice. CONCLUSION These results indicate that overexpression of Crry was not sufficient to prevent renal injury in TSLP transgenic mice. We suggest that the inhibitory capacity of Crry may be overwhelmed by chronic complement activation. Further studies need to address the role of complement in cryoglobulinemic glomerulonephritis before therapeutic complement inhibition can be attempted.
Measurements of Indirect CP Asymmetries in D

Asymmetries in D[superscript 0] K[superscript K[superscript +] and D[superscript 0] [superscript ][superscript +] Decays. Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters.
Gamma Oscillations as a Neural Signature of Shifting Times in Narrative Language

Verbs and other temporal expressions allow speakers to specify the location of events in time, as well as to move back and forth in time, shifting in a narrative between past, present and future. The referential flexibility of temporal expressions is well understood in linguistics but its neurocognitive bases remain unknown. We aimed at obtaining a neural signature of shifting times in narrative language. We recorded and analyzed event-related brain potentials (ERPs) and oscillatory responses to the adverb ‘now’ and to the second main verb in Punctual (‘An hour ago the boy stole a candy and now he peeled the fruit’) and Iterative (‘The entire afternoon the boy stole candy and now he peeled the fruit’) contexts. ‘An hour ago’ introduces a time frame that lies entirely in the past, ‘now’ shifts the narrative to the present, and ‘peeled’ shifts it back to the past. These two referential shifts in Punctual contexts are expected to leave very similar traces on neural responses. In contrast, ‘The entire afternoon’ specifies a time frame that may encompass past, present and future, such that both ‘now’ and ‘peeled’ are consistent with it. Here, no time shift is required. We found no difference in ERPs between Punctual and Iterative contexts either at ‘now’ or at the second verb. However, reference shifts modulated oscillatory signals. ‘Now’ and the second verb in Punctual contexts resulted in similar responses: an increase in gamma power with a left-anterior distribution. Gamma bursts were absent in Iterative contexts. We propose that gamma oscillations here reflect the binding of temporal variables to the values allowed by constraints introduced by temporal expressions in discourse.
File Exchange in Cloud

Computing systems trust and reputation representation have been widely discussed and applied in a lot of information technology scenarios, becoming subject of scientific researches both from a theoretical and practical point of view. This paper proposes the development of a trust model to ensure a reliable files exchange among users in a private cloud, as well as the calculation process of trust among these users, according to the metrics previously established. The simulation result shows that this trust model is robust because it successfully access node reliable under Private Cloud Computing environment.
Impact of transceiver hardware impairments on the ergodic channel capacity for Rayleigh-product MIMO channels

This paper aims at a realistic evaluation of Rayleigh-product multiple-input multiple-output (MIMO) systems. Specifically, by considering the residual transceiver hardware impairments into account, we derive the ergodic channel capacity of a MIMO system with optimal receivers in the case of insufficient scattering. Actually, motivated by the increasing interest for massive MIMO systems, we investigate the impact of transceiver hardware imperfections in systems with both finite (conventional) and large number of antennas under rank deficient channel matrix conditions by varying the severity of hardware quality. Among the interesting outcomes, we emphasize that the residual hardware transceiver impairments result to a saturation of the ergodic channel capacity within the high signal-to-noise ratio (SNR) regime. Furthermore, we observe that the higher the “richness” of the scattering environment, the higher the ergodic channel capacity till it gets saturated.
An automatic image quality assessment technique incorporating higher level perceptual factors

We present an objective image quality assessment technique which is based on the properties of the human visual system (HVS). It consists of two major components: an early vision model (multi-channel and designed specifically for complex natural images), and a visual attention model which indicates regions of interest in a scene through the use of importance maps. Visible errors are then weighted, depending on the perceptual importance of the region in which they occur. We show that this technique produces a high correlation with subjective test data (0.93), compared to only 0.65 for PSNR. This technique is particularly useful for images coded with spatially varying quality.
A pre-training strategy for convolutional neural network applied to Chinese digital gesture recognition

In this paper, we present an approach to classify Chinese digital gesture based on convolutional neural network (CNN). Principal Component Analysis (PCA) is employed to learn convolution kernels as the pre-training strategy. The learned convolution kernels are used for extracting features instead of the random convolution kernels. The convolutional layers can be directly implemented without any further training, such as Back Propagation (BP). For better understanding, we name the proposed architecture for PCA-based Convolutional Neural Network (PCNN). The dataset is divided into six gesture classes including 14500 gesture images, with 12000 images for training and 2500 images for testing. We examine the robustness of the PCNN against noises and distortions. In addition, the MNIST database of handwritten digits is employed to assess the suitability of the PCNN. Different from the CNN, the PCNN reduces the high computational cost of convolution kernels training. About one-fifth of the training time is shortened. The result shows that our approach classifies six gesture classes with 99.92% accuracy. Multiple experiments manifest the PCNN serving as an efficient approach for image processing and object recognition.
Statistical Mechanics of Semiflexible Chains: A Meanfield Variational Approach

We describe a simple meanfield variational approach to study a number of properties of intrinsically stiff chains which are appropriate models for a large class of biopolymers. We present the calculation of the distribution of end-to-end distance and the elastic response of stiff chains under tension using this approach. In the former example we find that the simple expression almost quantitatively fits the results of computer simulation. For the case of the stiff chain under tension we recover analytically all the known limits. We obtain quantitative agreement with recent experiments on the stretching of DNA. The limitations of our approach are also discussed.
A new algorithm for frequency estimation based on frequency searching

The precise estimation of the frequency of the signal is of great significance in many areas of application. In this paper, a new algorithm for estimating the frequency of one real tone in noise from a block of N uniformly spaced samples is proposed. This algorithm is based on the fundamental principle of the DFT. As a stand-alone algorithm, this estimator provides excellent performance but the computation is more complex comparatively when operate independently. This estimator can also cooperate with other estimators, which reduces the computational complexity efficiently without performance reduction.
Identification of Asymptotic Decay to Self-Similarity for One-Dimensional Filtration Equations

The objective of this paper is the derivation and the analysis of a simple explicit numerical scheme for general one-dimensional filtration equations. It is based on an alternative formulation of the problem using the pseudoinverse of the density's repartition function. In particular, the numerical approximations can be proven to satisfy a contraction property for a Wasserstein metric. Various numerical results illustrate the ability of this numerical process to capture the time-asymptotic decay towards self-similar solutions even for fast-diffusion equations.