Reviewerly/exHarmony huggingface dataset:
Fast quasi-static beam steering via conformally-mapped gratings

Fast beam steering is useful in applications including free space optical switching and communications. Quasi-static beam steering, where the beam rapidly switches between discrete fixed directions, presents special challenges. Here we demonstrate a fast quasi-static ‘pinwheel’ scanner by conformally mapping linear blazed gratings into curved structures fabricated onto annular sections of a rotary disk. We use Matlab and Zemax to model the effects of the conformallymapped grating on the emitted optical beam. We show a specific two-dimensional (2D) ‘pinwheel’ scanner design with 56 gratings, each deflecting 1.31 &mu;m incident light by 11.3&deg; in one of four directions with 75% optical efficiency. The element was fabricated by optical grey-scale lithography on a 95 mm diameter substrate, coated with gold, and mounted onto the spindle of a 3.5” format 7200 rpm magnetic disk drive. We characterize the optical beam steering efficiency, pointing, and stability, and demonstrate microsecond switching speed of a single mode fiber signal.
Importance and Impact of Class Diagram in Software Development

Background/Objectives: This work mainly focuses on the role of UML Class diagram in different phases of software development cycle and shows the industry responses regarding its impact and importance. Methods/Statistical Analysis: we conducted industry survey and collected data from software practitioners. Participants were asked about their usage of UML for modeling software artifacts and most frequent diagram they use. Findings: Result shows that UML Class diagram is most important element of UML and it performed highly significant role in software development. It is most frequently used diagram. Application/Improvements: Usage of UML models during the software development improve the quality of software and UML Class diagram is most important part of UML and help practitioners to perform analysis and as well as design in a systematic way. Keywords: Software Class Development, Software Class Diagram, Software System
A NR-IQA based deep neural network for tone mapping HDR images

The most recent High Dynamic Range (HDR) standard, HDR10+, achieves good picture quality by incorporating dynamic metadata that carry frame-by-frame information for tone mapping while most HDR standards use static tone mapping curves that apply across the entire video. Since it is laborious to acquire hand-crafted best-fitting tone mapping curve for each frame, there have been attempts to derive the curves from input images. This paper proposes the neural network framework that generates tone mapping on a frame-by-frame basis. Although a number of successful tone mapping operators (TMOs) have been proposed over the years, evaluation of tone mapped images still remains a challenging topic. We define an objective measure to evaluate tone mapping based on Non-Reference Image Quality Assessment (NR-IQA). Experiments show that the framework produces good tone mapping curves and makes the video more vivid and colorful.
Fast robust feature-based template matching

We propose a template matching method based on feature matching between target image and template. Firstly, we extract two sets of feature points from two images by ORB algorithm and match the key points to get a number of matches. Secondly, we remove the wrong matches to leverage feature numbers to improve quality. Then, we use a grid framework to locate the target object. We demonstrate great performance of our method through experiments.
Category, Time, and Space: Structures in Cross-Media Design and Production

The purpose of this empirically informed, but mainly conceptual paper, is to understand what we might mean by the word ‘structure’ in cross-media design. The paper draws upon a workplace study in print and online news production at a Swedish local news publisher, where we observed the work of reporters, page planners and web editors. Structure in the context of cross-media design and production is initially defined as the pattern of arrangement of elements in the media. We identified three kinds of structure in our observations of the journalists’ work: category, time, and space. Category: how knowledge is ordered is foundational and explains how functions and content relate to each other. Time: the temporal structure is how functions and content are ordered in time (what comes before and after). Space: The spatial structure is the layout of functions and content in 2-dimensional or 3-dimensional space. These three kinds of structure have corresponding design representations in interaction design: concept maps, flow charts, and wireframes.
Designing Information Integrating Systems Based on Co-shared Ontologies

Data gathered by organisations have diverse architecture and are based on various data models. Cooperation between organisations often requires data exchanging which, in heterogeneous environment, is not easy task. So, various integrating systems have been proposed to overcome problems concerning data exchange in such diverse systems. The field of data integration has expanded in many directions, including schema matching, record linkage, data fusion, and many more [5, 8]. In this paper various approaches to data integration are discussed and tasks that have to be fulfilled by integrating systems are identified. Because among integrating systems are also those based on ontology, their characteristics are identified. Next, the architecture of proposed system is presented, actions performing by individual modules during the process of queries execution are characterized and the process of designing integrating systems based on the proposed model is described.
Random Multi-scale Gaussian Kernels Based Relevance Vector Machine

This paper establishes random multi-scale Gaussian kernels based relevance vector machine (RMGK-RVM) for regression learning problems. The mixture of multiple Gaussian kernels with different scale parameters sampled from some predefined distribution is used as the model. Under the Bayesian inference framework, RMGK-RVM can learn the whole distribution of the prediction variable. In this way, the uncertainties of input data are fully considered and the prediction accuracy of the target variable is improved for complicated data. The experimental results on one simulation data and three real-life data sets show that the proposed method performs favorably.
Using wrapped phases for light-field three-dimensional imaging

In this paper, we proved that the correspondence cue focusing on the local angular variance of the structured light field could provide constraint conditions to deal with the phase ambiguity. A novel method of light-field depth estimation directly using wrapped phases was proposed, avoiding system calibration and adapting to the measurement environment and requirements.
Predicting open source programming language repository file survivability from forking data

Very few studies have looked at repositories' programming language survivability in response to forking conditions. A high number of repository programming languages does not alone ensure good forking performance. To address this issue and assist project owners in adopting the right programming language, it is necessary to predict programming language survivability from forking in repositories. This paper therefore addresses two related questions: are there statistically meaningful patterns within repository data and, if so, can these patterns be used to predict programming language survival? To answer these questions we analysed 47,000 forking instances in 1000 GitHub projects. We used Euclidean distance applied in the K-Nearest Neighbour algorithm to predict the distance between repository file longevity and forking conditions. We found three pattern types ('once-only', intermittent or steady) and propose reasons for short-lived programming languages.
Phase-shifting by polarizer rotations in a common-path cube beam-splitter interferometer

In this manuscript, a simple and low-cost method for phase-shifting interferometry by the rotation of a polarizer is presented. The principle of the proposal relies on the polarization aberration introduced by a cube beam-splitter due to its geometry, to the angular dependence with the coating and to the polarization angle of the input beam. The interferometric setup performs as a two-window common-path interferometer in which the added phase-shifting is achieved by simply rotating a polarizer at the interferometer output. The viability of the proposal is sustained with experimental results in which the phase-shift value and the resulting wavefront are calculated with Farrel’s technique and the Three-step PSI algorithm respectively.
Pump power in four-wave mixing polarization entanglement generation and its influence on quantum state tomography

For fiber-based polarization entangled photon pairs generated by four-wave mixing nonlinear effect, a common method to process coincidence counts and reconstruct density matrix of original quantum states is maximum likelihood estimation. Pump power is an essential parameter to investigate throughout the process of entanglement generation, correlation detection and quantum state tomography. Defined as the optical power of input laser pulses that enter dispersion-shifted fiber and generate entangled pairs, pump power directly affects single counts rates for both signal and idler. As noise rate changes accordingly, coincidence to accidental counts ratio does not necessarily increase with more detected counts. We derive relation between pump power and entangled correlation. Because different power is associated with different order of susceptibility, we also study its effect on entangled photon generation rate. Transmission rate through fibers, filters, polarizing beam splitters and other optical components as well as the detection efficiency at each avalanche photodiode are taken into consideration because they contribute to the reliability of photon counting statistics. System error such as measuring basis error is studied whether it is amplified, suppressed or remain invariant with pump power modification. Many parameters’ relations with pump power cannot be simply described as a one-line equation. Therefore, we explain those relations in detail and propose a method of finding a suitable pump power within given circumstances that would serve reconstructing the most accurate quantum state.
Explore Semantic Pixel Sets Based Local Pattern With Entropy Information for Face Recognition and Application in Backpropagation

Abstract In this paper, a combination of the Local Binary Pattern method with a semantic pixel set of entropy information is used on back propagation networks for face recognition. This method divides the sample data into NxM zones and calculates the feature value of each zone. In this paper the sample data is divided into 6x9 zones, ie 54 zones with the size of each zone is 10x10 pixels. The LBP method is a uniform pattern of each zone and makes comparisons to zones that have the most number of active pixels. Then from the LBP method the semantic method is used to extract the entropy information from each image. From the feature extraction, there are 107 feature values, 54 of LBP and 53 methods of semantic method. The value of the feature is used as input for classification using back propagation networks. 100 sample data were used for training and 60 different sample data were used for recognition level test. From the test conducted got the recognition rate using a combination of two methods of this extraction feature is 98%.
High Performance and Security Design for Cryptosystem Using Simultaneous Multiple Hardware Threads and Power Aware Technique

Today, cryptography plays an important role for data security and integrity and is widely adopted. The implementation of the cryptography is useful in wireless security like military communication and mobile telephony which have a greater emphasis on the speed of communication, high security and low power consumption. Therefore, we propose a novel architecture for Cryptosystem that enhances the level security and speeds up the data processing using simultaneous multiple hardware threads (SMHT). Moreover, in each hardware thread, we employ two techniques: (1) the pipeline technique to speed up the encryption/decryption data processing; (2) power aware technique to reduce the power consumption. The experimental results show that our proposed architecture not only achieves the high performance for realtime processing of 5.806 Gbps throughput and consumed low-power with 222.75 mW, but also enhances the level of data security. As compared with those founds in the literature, our design was superior in terms of performance, low power consumption and data security.
Autonomous Track Designing Approach in a Settled and Unsettled Environment

This paper presents an approach that is used to amend the issues appears during trajectory designing for a mobile material handling robot in settled and dynamic/unsettled environment. Algorithms like artificial potential field approach (APF) is employed to eradicate the issues arises in deciding the shortest possible track in unsettled surrounding. Curtail track length, computational time, travel time, track smoothness, feasibility and crash free track are addressed in this paper. Two distinctive surrounding setups are designed in this paper. One involves only stationary/settled obstacles. While second surrounding involves both stationary and unsettled obstacles. The simulation practice indicates that Artificial Potential field technique is found appropriate when the surrounding involves both static and dynamic obstacles. Also track generated by this approach not only shorter but also requires less computational time for generating the optimal track. The selected approach is also capable for generating the travel time needed to chase the optimal path, as the speed of the robot is defined in the program. So the travel time associated with that track is determined. Some experimental trials are also performed to determine the value of actual travel length and time. From the study, it is concluded that the path generated by this approach in unsettled environment not only crash free, but also smooth and requires less computational and travel time.
Electromagnetic analysis of three-dimensional shape measurement method based on speckle interferometry for fine structure by detecting phase distribution

In the measurement of three-dimensional structure beyond the diffraction limit of the objective using the speckle interferometry, it has been reported that the shape of a measurement object can be measured by detecting the change of phase distribution generated by a lateral shift of the object. In this method, it is a feature that the focused image of the measured object is not required by using a scattering light. In this paper, the principle of this method is investigated by using electromagnetic analysis. Even if the three-dimensional structure is beyond the diffraction limit of the objective lens, it is confirmed that the three-dimensional shape can be measured by using the scattering light as the illumination light.
Mechanical deformations in a graphene-reinforced cellulose sample

The ever-increasing requirements of product quality and reliability demand more efficient measuring and test methods that must be online, nondestructive, wholefield and without contact. Optical methods seem to be ideal for such purposes. The interferometric technique of ESPSI (Electronic Speckle Pattern Shearing Interferometry), or Shearography, is a coherent-optical measuring and test method that is similar to holographic interferometry. However, this method displays many advantages for industrial applications, due to its relative insensitivity to environmental disturbances. Shearography measures the gradient of the deformation, not the deformation itself as holography does. Consequently, shearography measures strain information directly. Based on the above, Shearography was adapted for the surface strain measurement in graphene-reinforced composite materials; the information was evaluated at each point from our sample observed area. Defect inspections with shearography on fiber-reinforced plastics parts, widely used in aircrafts, ships, chemical and oil and gas industries, are often performed outside of the lab. An optical system capable of measuring the strain fields in and out of plane was developed based on electronic speckle interferometry. The obtained interferogram images were processed using the phase-stepping technique. A specific specimen geometry and an optical arrangement based on the Michelson interferometer are proposed to measure the deformation along two orthogonal axes due to sensibility in and out of plane. The advantages of the system include its high sensitivity and stability. The experimental setup and approach for estimating the strain fields was validated using a membrane based on polylactic acid reinforced with cellulose microcrystalline as sample with and without graphene.
Lifting based Block-FrWF (BFrWF)for DWT computation of HR-images over WMSNs and IoT Platforms

Block-based fractional filter (BFrWF) is a low-memory technique for computing discrete wavelet transform of image. However, its complexity is high which makes it unsuitable for low-cost visual sensor nodes used in wireless multimedia sensor networks (WMSNs)/Internet of things (IoT). Moreover, BFrWF does not consider proper overlapping of image blocks, leading to blocking artifacts. This paper proposes a novel lifting-based implementation of BFrWF. Experimental results demonstrate that proposed implementation reduces the complexity of BFrWF by approximately 30% with negligible increase (of 32 bytes) in memory requirement. The proposed implementation considers proper overlapping of boundaries of image-blocks in order to remove the blocking artifacts. Moreover, the proposed implementation when combined with a coding algorithm has better coding efficiency compared to BFrWF combined with the same coding algorithm. Thus, propose lifting-based implementation is suitable for WMSNs/IoT.
Lens rim points stitching algorithm based coaxial alignment micro assembly

Abstract Optical lens assemblies are used more and more widely, and assembly and alignment processes are key to affecting lens accuracy. Considering that the common way of assembling lenses was manual, the coaxial alignment for intermediate-scale parts was considered to be a good alternative, which could improve the accuracy of assembly effectively. But it was difficult to capture the full edge of the lens in one image because of the limit of the CCD camera field of view. To solve this problem, a rim points stitching algorithm was proposed, and the barrel and lens were imaged by the camera at three different position. After the rim points were extracted from the three images, all the rim points were stitched according to the position of the camera at three locations. The rim points stitched were fitted to two circles by using the least squares method. Finally, according to the adjustment algorithm, the adjustment amount of the lens with respect to the lens barrel was calculated. Experimental results showed that this method could align lenses with the diameter greater than 60mm. The technique has the potential to be applied in automated alignment of lens assemblies.
Channelized Hotelling observer assessing microcalcification detectability on 2D mammography: a first application to study the impact of tube voltage

Abstract This work was aimed to assess the detectability of microcalcifications as a function of tube voltage in 2D mammography using an in-house developed Channelized Hotelling Observer (CHO). The images of a 3D structured phantom, containing acrylic beads of different diameters in water and inserted signals (microcalcifications, spiculated and non-spiculated mass models) were assessed. Images had been acquired on a Siemens Mammomat Inspiration system at 5 different tube voltage levels (28-32 kVp) under AEC setting. The detectability of microcalcifications was analyzed in terms of percentage correctly detected signals (PC) as well as diameter threshold (d tr ), using the CHO and human observers. Two Laguerre-Gauss and 8 Gabor channels were included in the two-layers CHO. The model and human observer results were retrieved from a 4-alternative forced choice (4-AFC) study. At 28 kVp and 32 kVp, the diameter thresholds d tr of microcalcifications together with their 95% confidence intervals (CI95) were 0.114 [0.110-0.118] mm and 0.119 [0.116-0.122] mm for the CHO, and 0.110 [0.093-0.127] mm and 0.123 [0.111-0.134] mm for the human observers. The Pearson correlation (r) between the PC values of model and human observer was more than 0.934. The in-house developed CHO and the human observer scores correlated very well for the application on 2D digital mammography acquired with different tube voltages. The overlapping range of CI95 of the d tr for the tested kVp shows that the tube voltage setting does not significantly affect the detectability of microcalcifications neither by the CHO nor by the human observers.
Real-time multi-criteria classification of facial images

We proposes a practical technique for the classification of facial images across multiple criteria, such as: gender, age, ethnicity, expression, and others. The technique uses a novel form of Gabor-based features followed by the application of the PCA and LDA algorithms. The computation of class scores in the context of nearest centroid classification is also novel, and relies, in part, on properties of the proposed features. We demonstrate that the proposed form of Gabor features is particularly suitable for achieving simultaneous classification. The reported results are obtained using a set of standard databases and include comparisons against known state-of-the-art algorithms. The utility of the proposed scheme is demonstrated by practical applications requiring multiple classification results to be obtained in real time while using typical consumer devices (cellphones, tablets, PCs) as computing platforms.
Autonomous navigation for a differential drive robot in a partially known environment

This paper presents a proposed algorithm with the implementation of the A* algorithm for path planning in a partially known environment. By using a differential mobile robot, the navigation is accomplished with a LiDAR sensor that detects any potential changes in the environment. The proposed algorithm estimates a safety path-planning trajectory from the origin of the robot to a target coordinate given by the user. If the robot encounters an unknown obstacle that does not belong to the known environment it will update the map, and recalculate the trajectory, executing it and proceed with the new path. Experimental results were considered in an indoors cluttered environment given by unknown obstacles, and partially known maps.