Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical timing, trigger and control distribution for LHC detectors

At CERN's future Large Hadron Collider, timing, trigger-accept and control signals must be distributed from a small number of sources to many thousands of front-end electronics destinations located on the ATLAS and CMS detectors. The LHC timing reference must be delivered with sub-nanosecond jitter and programmable phase. First-level trigger decisions must be broadcast from the central trigger processor to all the front-end pipeline controllers and delivered synchronously with the appropriate bunch identification, compensated for particle flight times and detector, electronics and propagation delays. In addition, broadcast control signals and individually-addressed controls and parameters such as calibration data have to be distributed. This paper describes how it is planned to broadcast all the signals over entirely passive multichannel optical fiber networks with uncontrolled path lengths. It reviews some of the technology options which are currently available and those which are likely to mature within the time frame of LHC preparation. It discusses how synchronization can be established over the system and describes how different distribution network configurations, laser transmitters and encoding methods can be used to deliver the signals using optoelectronic receivers which are becoming affordable for extensive deployment. >
A novel duplicate images detection method based on PLSA model

Web image search results usually contain duplicate copies. This paper considers the problem of detecting and clustering duplicate images contained in web image search results. Detecting and clustering the duplicate images together facilitates users' viewing. A novel method is presented in this paper to detect and cluster duplicate images by measuring similarity between their topics. More specifically, images are viewed as documents consisting of visual words formed by vector quantizing the affine invariant visual features. Then a statistical model widely used in text domain, the PLSA(Probabilistic Latent Semantic Analysis) model, is utilized to map images into a probabilistic latent semantic space. Because the main content remains unchanged despite small digital alteration, duplicate images will be close to each other in the derived semantic space. Based on this, a simple clustering process can successfully detect duplicate images and cluster them together. Comparing to those methods based on comparison between hash value of visual words, this method is more robust to the visual feature level alteration posed on the images. Experiments demonstrates the effectiveness of this method.
Fuzzy sets and semantic nets for on line assistance

We describe the theoretical aspects of the architecture of the whole experimental AI system we built in order to provide effective online assistance to users of new technological systems: the understanding of "how it works" and "how to complete tasks" from queries in natural languages. In our model, procedural semantic networks are used to describe the knowledge of an "ideal" expert while fuzzy sets are used both to describe the approximative and uncertain knowledge of novice users in fuzzy semantic networks which intervene to match fuzzy labels of a query with categories from our "ideal" expert. <<ETX>>
Evaluation of Reservation Mechanisms for Optical Burst Switching

Summary In this paper, we give an overview and classification of optical burst switching schemes and present burst reservation concepts. The performance of various basic reservation mechanisms proposed in literature is compared. Furthermore, a new analysis is introduced that allows to calculate the loss probabilities of a two-class system based on the reservation mechanism just-enough-time (JET) for arbitrary offsets. Finally, a variety of new results is presented including the dependence of burst loss probabilities on offset, burst length distribution, and interarrival distribution.
Polar Exponential Sensor Arrays Unify Iconic and Hough Space Representation

The log-polar coordinate system, inherent in both polar exponential sensor arrays and log-polar remapped video imagery, is identical to the coordinate system of its corresponding Hough transform parameter space. The resulting unification of iconic and Hough domains simplifies computation for line recognition and eliminates the slope quantization problems inherent in the classical Cartesian Hough transform. The geometric organization of the algorithm is more amenable to massively parallel architectures than that of the Cartesian version. The neural architecture of the human visual cortex meets the geometric requirements to execute "in-place" log-Hough algorithms of the kind described here.
Automatic inspection of simply patterned material in the textile industry

Automatic inspection allows the continuity of the quality of textiles manufacturing, and the optimization of the pinking according to the situation of the defects. A method for defect detection based on a periodicity breaking of the material densitometrical profile is proposed. After the explanation of the method, some important points like texture suppression, image block size choice, and defect characterization are detailed. Finally, the system configuration and the results obtained from the detection stage are introduced.
Formal Semantic of Architecture-Centric Component Model

Existing software development approaches construct component model in an unstructured and informal way, and the dependencies among components are implicit and lack rigorous semantic. They don't support top-down component reuse effectively. This paper tries to address these problems by using category theory to define the links between components, so that the links between components and the link compositions have rigorous meaning. The morphism composition is used to trace the relationships between components at different abstraction levels, and the architecture design pattern is used to define component composition and constrains precisely. Category theory supports the diagrammatic representation of component model that visualizes the relationships between components and the structural feature. The constructed component model is understandable, traceable, and
A low-power ROM using charge recycling and charge sharing techniques

In a memory, most power is dissipated in high-capacitive lines such as predecoder lines, wordlines, and bitlines. To reduce the power dissipation in these high-capacitive lines, this paper proposes three techniques using charge recycling and charge sharing. The first is the charge recycling predecoder (CRPD), the second is the charge recycling wordline decoder (CRWD), and the last one is the charge sharing bitline (CSBL) for a ROM. The CRPD and the CRWD recycle the previously used charge in predecoder lines and wordlines. Theoretically, the power consumption in predecoder lines and wordlines are reduced to a half. The CSBL reduces the swing voltage in the ROM bitlines to very small voltage using a charge sharing technique with three small capacitors. The CSBL can significantly reduce the power dissipation in ROM bitlines. The CRPD, the CRWD, and the CSBL consume 82%, 72%, and 64%, respectively, of the power of previous ROM designs. A charge recycling and charge sharing ROM (CRCS-ROM) with the CRPD, the CRWD, and the CSBL is implemented. A CRCS-ROM with 8K /spl times/ 16 bits was fabricated in a 0.35-/spl mu/m CMOS process. The CRCS-ROM consumes 8.63 mW at 100 MHz with 3.3 V. The chip core area is 0.51 mm/sup 2/.
Long-acting injectable antipsychotics in patients with schizophrenia: systematic review and mixed treatment meta-analysis

Abstract Long-acting injectable antipsychotics (LAIs) are recommended for schizophrenic patients who cannot adhere to oral medication. We systematically reviewed randomized controlled trials of 6 LAIs available in Thailand including fluphenazine, flupentixol, haloperidol, zuclopenthixol, paliperidone, and risperidone in PubMed/ MEDLINE and the Cochrane library (1955-Nov 2013). Inclusion was limited to studies of schizophrenia ≥24 weeks duration published in English. We selected 17 of 1,245 articles including 1,904 patients. The number of patients ranged from 19 to 747 per study (median 54). Mean study duration was 52.3 weeks (24-96 weeks) and median quality score using a Jadad scoring method was 4 (2-5). We applied a Bayesian model with a mixed treatment comparison approach for 3 competing risk outcomes including relapse, and discontinuation because of adverse events or other reasons. Based on the random effect model preferred by a goodness of fit analysis, risperidone had the lowest 52 week probability of relapse (mean ± SD, 0.26 ± 0.321) followed by paliperidone (0.30 ± 0.314). Zuclopenthixol had the lowest probability of discontinuation because of an adverse event (0.07 ± 0.159) or other reasons (0.26 ± 0.295). Risperidone had the highest probability of preventing relapse (0.35 ± 0.476) or discontinuation for other reasons (0.31 ± 0.461). Zuclopenthixol had the highest probability of preventing discontinuation because of adverse effects (0.31 ± 0.464). All 6 LAIs tended to have a lower risk of relapse compared with placebo. Differences between LAIs preventing any treatment discontinuation or relapse were seen, but limited in our analysis.
SECRET KEYS AND THE PACKETS TRANSPORTATION FOR PRIVACY DATA FORWARDING METHOD IN CLOUD SERVER

The Cloud computing is the process of storing the data in the Remote server. This process doesn‘t speak much about confidentiality and robustness of the data. To improve the security and confidentiality the uploaded file from a data owner is splitted into multiple packets and stored in multiple cloud servers. These packets are encrypted using the primary key. These different keys are also distributed in multiple key servers. User id is appended for verification. If the data owner forwards the file then the keys are verified for the data access. In this we are proposing sending the secret key as SMS to the shared or forwarded nodes for the process of proper Security. This technique integrates the concepts of encryption, encoding and forwarding.
Karhunen-Loeve basis synthesis for great-capacity signal performance in optical processors

This paper describes in detail the effective procedure for Karhunen-Loeve basis synthesis, offered by the authors for statistical ensembles, permitting a limited size teaching set. Unlike the classical Karhunen-Loeve procedure, the main factor, restricting its application and determining the number of required calculations for basis formation, is not the dimension of the encoding signal itself but the number of elements in the input basic set. This allows us to apply this procedure to the objects of grate capacity (up to 106 - 108 counts), that is usual for optical processed signals. Examples of effective real signal coding are given.
Service discovery mechanism based on trustable DHT in MANET

Service discovery mechanism is a core technique for getting a desired service in MANET (Mobile Ad-Hoc NETwork) environment. However, As feature of MANET, existing mechanisms have some problem that service requester search for trustable service. Also it can not support scalability, in this paper, how to reliably support applications such as service discovery on top of MANET. We are firstly finding a trustable service provider and configure DHT (Distributed Hash Table). P2P (Peer-to-Peer)'s DHT can be adopted to service discovery mechanism because P2P and MANET share certain similarities, primarily the fact that both are instances of self-organizing decentralized systems. Especially, Proposed DHT systems used for P2P overlay network can be effective in reducing the communication overhead in service discovery. So proposed mechanism can support for reliably searching required service and scalability. Simulation results show that our mechanism is scalable and outperforms existing service discovery mechanism.
A motion region estimation technique for Web camera application

This paper presents the steps involved in processing the output image obtained from image subtraction. A Web camera or Web cam is used as a video clip capture device and MATLAB version 6.01 with Image Processing Toolbox is used as the analysis software. Image frames extracted from the video clips undergo image subtraction for motion detection purposes. The continuous steps presented in this paper are thresholding, noise removal and motion region estimation. Thresholding determines the areas of output images (from subtraction) consisting of pixels with values lying within the threshold value range. Threshold value also indicates the sensitivity of motion to detection. The image still contains a small amount of noise after thresholding. Noise is removed using a median filtering method. Motion region estimation is done by executing an AND or OR operation on two subtracted images from three successive frames. Both the output image from AND and OR operations will estimate the motion region in a different time frame.
Using Video Clips as Test Questions: The Development and Use of a Multimedia Exam

SUMMARY Innovations in multimedia provide new formats for delivering and scoring tests and for constructing test items. This article presents a case study of the development of a multimedia exam that assesses child protective services supervisor competence. It describes the need, design, development, validity, standardization, use, status, issues, problems, and lessons learned. While multimedia offers potentials, it also makes modifications, enhancements, and delivery more complicated. By examining this experience, others can avoid mistakes and pitfalls when undertaking future multimedia assessment endeavors.
A vector handheld frequency-domain sensor for UXO identification

The GEM-3D+ sensor developed by Geophex, Ltd. is a new incarnation of their widely known GEM-3. The sensor provides the analyst with all three vector components of the secondary magnetic field over a wide range of frequencies. The GEM-3D+ features an innovative "beacon-based" positioning system that provides a full description of its location and orientation at every point without requiring any on-sensor hardware beyond an electronic compass. This enhances the usefulness of the instrument for dynamic surveying, This paper presents some methods and results related to UXO identification using the GEM-3D+. Our analyses exploit data provided by the sensor in both grid-based and dynamic measurements to characterize different objects, including metal spheres and actual UXO. For the data analysis we alternate between the dipole model and the more rigorous standardized excitation approach. We review some ill-conditioning issues encountered with the latter model and the different approaches that we use to overcome them. In applications, the availability of horizontal field components in the data allow us to identify UXO vs. non-UXO items while minimizing the nonnegligible effects of ground response.
Identification of metallic objects with various sizes and burial depths

In this study, identification of the different metallic objects with various burial depths was considered. Metal Detector (MD) and Ground Penetrating Radar (GPR) were used to obtain metallic content and dielectric characteristic of the buried objects. Discriminative features were determined and calculated for data set. Six features were selected for metal detector and one for Ground Penetrating Radar. Twenty classification algorithms were examined to obtain the best classification method, for this data set. A Meta learner algorithm completed the classification process with 100% performance.
The IRIS Development Platform and Proposed Object-Oriented Data Base

Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3]; however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.
Social Ties and Generalized Trust, Online and in Person

Results of the present survey (n = 888) suggest that having strong social ties (or bonding social capital) fosters generalized trust, in support of conflict theory. There was no link between bridging social capital, or one’s more diverse ties, and trust. Facebook use was found to have an indirect but positive influence on trust through levels of bonding social capital. Civic engagement was also positively related to trust through the same measure of bonding social capital, allowing like-minded members of civic groups to connect, which spilled over to trust. Neither Facebook use nor civic engagement directly influenced generalized trust. This study suggests the viability of both physical (civic) and digital (Facebook) modes of reengaging trust in an ever-diversifying society. The “virtuous circle,” in which social trust and civic engagement prop one another up in a reciprocal fashion, instead looks like a figure eight here. Each measure indirectly boosted the other by first growing bonding social capital. When considered alongside divergent findings from Canada, this appears to be an American response to the increasing size of racial minority groups. Hispanic citizens make up the same portion of the American population as do all minority groups in Canada combined. These findings then represent a White reaction to an increasing Hispanic presence in America. Bounded solidarity in the form of strong, homogenous ties is shown as the path to trust in this setting.
Adaptive ground bounce removal

For downward looking GPR landmine detection systems, the return from the ground surface, i.e., the ground bounce, often surpasses the actual mine return and makes it almost impossible to detect the landmines, especially the buried plastic landmines. The ground bounce is difficult to remove due to the roughness of the ground surface and/or the changing soil conditions. In this paper, a robust and efficient ground bounce removal algorithm, referred to as ASaS (Adaptive Shift and Scale), is presented. ASaS takes into account the variations of the ground bounce by adaptively selecting a reference ground bounce. The shifted and scaled version of the reference ground bounce is used as the estimate of the ground bounce in the current scan. Two adaptive reference selection schemes for ASaS are given and compared with each other. Experimental results based on the data collected by the PSI GPSAR system are used to demonstrate the effectiveness of the adaptive schemes.
An improved object tracking algorithm based on image correlation

Regarding common problems existing in current object tracking algorithms based on image matching, such as large computational cost, long matching time and difficulty to realize in real time, this paper provides an improved algorithm which is able to achieve an accurate and rapid tracking. The new algorithm firstly computes the object prediction position by constructing a novel Kalman predictor, and then an adaptive optimized matching is performed in a neighborhood of this prediction position so as to get the real object position rapidly. The experimental results show this algorithm is tractable and readily realizable. What's more important is that it decreases computational cost significantly but meanwhile shows better performance than traditional correlation-based tracking algorithms.
Traffic Accident Analysis Using Decision Trees and Neural Networks

This work employed Artificial Neural Networks and Decision Trees data analysis techniques to discover new knowledge from historical data about accidents in one of Nigeria"s busiest roads in order to reduce carnage on our highways. Data of accidents records on the first 40 kilometres from Ibadan to Lagos were collected from Nigeria Road Safety Corps. The data were organized into continuous and categorical data. The continuous data were analysed using Artificial Neural Networks technique and the categorical data were also analysed using Decision Trees technique . Sensitivity analysis was performed and irrelevant inputs were eliminated. The performance measures used to determine the performance of the techniques include Mean Absolute Error (MAE), Confusion Matrix, Accuracy Rate, True Positive, False Positive and Percentage correctly classified instances. Experimental results reveal that, between the machines learning paradigms considered, Decision Tree approach outperformed the Artificial Neural Network with a lower error rate and higher accuracy rate. Our research analysis also shows that, the three most important causes of accident are Tyre burst, loss of control and over speeding.
Short‐term electricity load and price forecasting based on clustering and next symbol prediction

Short‐term electricity load and price forecasting is an important issue in competitive electricity markets. In this paper, we propose a new direct time series forecasting method based on clustering and next symbol prediction. First, the cluster label sequence is obtained from time series clustering. Then a lossless compression algorithm of prediction by partial match version C coder (PPMC) is applied on this obtained discrete cluster label sequence to predict the next cluster label. Finally, the whole time series values of one‐step‐ahead can be directly forecast from the predicted cluster label. The proposed method is evaluated on electricity time series datasets, and the numerical experiments show that the proposed method can achieve promising results in day‐ahead electricity load and price forecasting. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Preconditioned Block‐Iterative Methods on GPUs

An implementation of the incomplete‐LU/Cholesky preconditioned block‐iterative methods on the Graphics Processing Units (GPUs) using the CUDA parallel programming model is presented. In particular, we focus on the tradeoffs associated with the sparse matrix‐vector multiplication with multiple vectors, sparse triangular solve with multiple right‐hand‐sides (rhs) as well as incomplete factorization with 0 fill‐in. We use these building blocks to implement the block‐CG and BiCGStab iterative methods for the symmetric positive definite (s.p.d.) and nonsymmetric linear systems, respectively. Also, in our numerical experiments we show that the implementation of the preconditioned block‐iterative methods using the CUSPARSE library on the GPU achieves an average of 3× speedup over their MKL implementation on the CPU. (© 2012 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)