Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaled multisensor inspection of extended surfaces for industrial quality control

Reliable real-time surface inspection of extended surfaces with high resolution is needed in several industrial applications. With respect to an efficient application to extended technical components such as aircraft or automotive parts, the inspection system has to perform a robust measurement with a ratio of less then 10-6 between depth resolution and lateral extension. This ratio is at least one order beyond the solutions that are offered by existing technologies. The concept of scaled topometry consists of arranging different optical measurement techniques with overlapping ranges of resolution systematically in order to receive characteristic surface information with the required accuracy. In such a surface inspection system, an active algorithm combines measurements on several scales of resolution and distinguishes between local fault indicating structures with different extensions and global geometric properties. The first part of this active algorithm finds indications of critical surface areas in the data of every measurement and separates them into different categories. The second part analyses the detected structures in the data with respect to their resolution and decides whether a further local measurement with a higher resolution has to be performed. The third part positions the sensors and starts the refined measurements. The fourth part finally integrates the measured local data set into the overall data mesh. We have constructed a laboratory setup capable of measuring surfaces with extensions up to 1500mm x 1000mm x 500mm (in x-, y- and z-direction respectively). Using this measurement system we will be able to separate the fault indicating structures on the surface from the global shape and to classify the detected structures according to their extensions and characteristic shapes simultaneously. The level of fault detection probability will be applicable by input parameter control.
ELECTROMAGNETIC HEATING AS A WAY OF CUTTING COSTS WHILE SAVING ENERGY: TIME EVOLUTION

In this review article, an electromagnetic heating time evolution is presented, stating a brief description of the main applications in some of the top fields regarding this technology and striving to indicate fields for further research in an area that becomes more important with each passing day. It was found that the food industry and that plasma related products are the most important branches of this technology, where a vast majority has focused on microwaves instead of using radiofrequency. Some other areas are also discussed and at the end possible future researches are outlined, such as a mixed heating dryer and a sulfur lamp.
Tuning Nonlinear Controllers with the Virtual Reference Approach

Abstract Virtual Reference Feedback Tuning (VRFT) is a well established method for data-driven tuning of linear controllers. In VRFT the design is performed in “one-shot”, that is, with only one batch of input-output data, without the need of iterative data collection procedures. Its core concept consists in treating input-output data collected from the plant to be controlled as if they had been obtained from a virtual experiment, in which a particular reference signal - the virtual reference - would have been applied to the closed-loop system. A key feature of the VRFT method is that it greatly simplifies the design procedure with respect to standard model reference design: for linear and linearly parametrized controllers, it results in convexification of the design, so that its solution can be found by a single least squares method. In this paper this paradigm is applied to the tuning of nonlinear controllers. We propose specific design procedures for two classes of nonlinear plants: rational plants and plants of the Wiener type. Statistical properties of the controllers thus designed in noisy environments are also illustrated.
Optimization Design of LED Display Front Shell Injection Mold on Moldflow

Warping and distortion in plastic parts has been a serious problem in mold-injection.Traditional solution is to first produce a mold and then test the moldrepeatedly. By employing Moldflow, it can be easily to offer a precise analysisand prediction of warping in products. Meanwhile, the results can be used toadjust the designed structure and process conditions of the mold. Finally, themold and its products are optimized.
Analysis and Design of an Exponential Charge Pump

This paper analyzed efficiency performance of two most popular charge pumps: Linear Dickson charge pump and the Exponential Dickson charge pump. The analysis result indicated that in a certain range, exponential charge pump had a much higher efficiency than the linear one. With this analysis result, a novel exponential charge pump was proposed. The simulation result shows the proposed charge pump has a 18.4% improvement in efficiency.
Mobile Technology Assisted Interventions Targeting Mental Health Among Pregnant and Postpartum Women: A Protocol for An Equity Focused Systematic Review

1. School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON 2. C.T. Lamont Primary Healthcare Centre, Bruyère Research Institute, Ottawa, ON 3. Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON 4. Department of Internal Medicine, Schulich School of Medicine, London, ON 5. School of Medicine, University of Ottawa, Ottawa, ON 6. Department of Psychiatry, University of Ottawa, Ottawa, ON 7. Pinecrest Queensway Community Health Centre, Ottawa, ON 8. Ottawa Newcomer Health Centre, Ottawa, ON 9. Department of Family Medicine, University of Ottawa, Ottawa, ON
Genetic diversity and introductions patterns of Lantana camara L. in the territory of Bangladesh as revealed by microsatellite profiles

Lantana camara L. is one of the worst invasive species associated with biodiversity loss and ecosystem desolation. The present study aimed to understand the pattern of introduction and the genetic diversity of L. camara populations in Bangladesh to gain insight into the hypothesis concerning the role of multiple introductions in genetic diversity elevation. Plants were collected from different locations under the major administrative divisions namely Dhaka, Sylhet, Rajshahi, Mymensingh and Chattogram of Bangladesh. Genomic DNA was extracted using CTAB extraction buffer. Presence of private alleles and high genetic diversity was revealed by analysis of 8 microsatellites with a total of 30 alleles from 17 samples. Higher (79%) among population genetic variation, multiple divergent genetic clusters and a significant positive correlation between genetic and geographic distances along with moderately strong signal of isolation by distance delineated that multiple introduction of L. camara L. population occurred in different RESEARCH Vol. 21, Issue 67, 2020 Species ISSN 2319–5746 EISSN 2319–5754
An Empirical Comparison between API Tutorials and API Crowd Documentation

API documentation is critical for developers to learn APIs. However, it is unclear whether diﬀerent types of API documentation have distinct eﬀects on the API learnability for developers. Thus, we conduct an empirical study to compare the API learnability between oﬃcial API tutorials and API crowd documentation based on three aspects, i
Agent-whistleblower Technology for Secure Internet of Things

Abstract— The paper investigates the causes of widespread use by cybercriminals of the Internet of Things for organizing network attacks and other illegal use. An analysis of existing approaches and technologies for protecting networked computer devices is presented, as well as the main factors that prevent their use in the world of Internet of Things. An approach is suggested that ensures the integration of protective mechanisms directly into the composition of Things. Various variants of technology implementation are considered. Key aspects and potential ways of implementing the proposed approach are noted. Tóm tắt— Bài báo nghiên cứu về các phương thức được tội phạm mạng sử dụng rộng rãi trong Internet vạn vật (IoT), để tổ chức các tấn công mạng và các hành vi bất hợp pháp khác. Bài báo phân tích các phương pháp và công nghệ hiện có để bảo vệ các thiết bị kết nối mạng, cũng như các yếu tố chính để ngăn chặn việc sử dụng chúng trong IoT. Cách tiếp cận được đề xuất là đảm bảo việc tích hợp các cơ chế bảo vệ trực tiếp vào cấu trúc của IoT. Bài báo cũng xem xét các biến thể khác của việc thực hiện công nghệ này. Từ đó, đưa ra lưu ý về các khía cạnh chính và cách thức cài đặt tiềm năng để thực hiện phương pháp được đề xuất.
A Key Management Technique for Cloud Storage Using Semi Trusted Policy Preservation

: One of the major challenge in cloud computing is providing security for the data. The main aim of this project is to provide a security for data in cloud and also to propose a proper key management system using key sharing technique with multiple key managers. To avoid unauthorized access to cloud data, access control mechanism must be enforced. Moreover, data leakage and data privacy strategies must be employed so that only authorized users can access and utilize data. Encryption techniques provide a solution to ensure privacy and confidentiality of stored data. Key management becomes a prime issue in the case of encryption. Cryptographic keys need to be stored and protected. Compromise or failure of a key storage facility may lead to the loss of data. Another issue in security for cloud data is that there is a man-in-the-middle attack. The intruder may access the user files illegally due to improper authentication system. This can be overcome by using proper authentication between user and cloud. The security concerns of outsourcing data to public clouds, serves as a motivation to work for the development of data security technique. We aim for a technique capable of addressing the aforementioned critical issues. We proposed a data security scheme that uses key manager servers for the management of cryptographic keys
Deep networks for image super-resolution using hierarchical features

To better extract feature maps from low-resolution (LR) images and recover high-frequency information in the high-resolution (HR) images in image super-resolution (SR), we propose in this paper a new SR algorithm based on a deep convolutional neural network (CNN). The network structure is composed of the feature extraction part and the reconstruction part. The extraction network extracts the feature maps of LR images and uses the sub-pixel convolutional neural network as the up-sampling operator. Skip connection, densely connected neural networks and feature map fusion are used to extract information from hierarchical feature maps at the end of the network, which can effectively reduce the dimension of the feature maps. In the reconstruction network, we add a 3 × 3 convolution layer based on the original sub-pixel convolution layer, which can allow the reconstruction network to have better nonlinear mapping ability. The experiments show that the algorithm results in a signiﬁcant improvement in PSNR, SSIM, and human visual effects as compared with some state-of-the-art algorithms based on deep learning.
GLANDULAR CUTICLE FORMATION IN CANNABIS ( CANNABACEAE ) 1

Formation of the cuticle from components of the secretory cavity and subcuticular wall was studied by transmission electron microscopy of glandular trichomes of Cannabis prepared by high pressure cryofixation-cryosubstitution. Secretory vesicles in the secretory cavity resembled those localized in the subcuticular wall as well as the vesicle-related material associated with the irregular inner surface of the cuticle and appeared to provide precursors for thickening of the cuticle. Some contiguous vesicles in the secretory cavity and subcuticular wall lacked a surface feature at their point of contact, supporting an interpretation of vesicle fusion. Fibrillar matrix from the secretory cavity contributed fibrillar matrix to the subcuticular wall, and persisted as residual fibrillar matrix associated with secretory materials coalesced to the thickened inner surface of the cuticle. Elongated fibrils arranged in uniformly spaced parallel pairs contributed to the organization of fibrillar matrix in the subcuticular wall. Striae were evident in the outer portion of the cuticle, and appeared to represent sites of degraded residual fibrillar matrix associated with secretory materials coalesced to the inner cuticular surface. This study supports an interpretation that contents of secretory vesicles from the secretory cavity contribute to formation of glandular cuticle.
Median and ulnar nerve injuries in cyclists: A narrative review

Cycling is popular internationally as a mode of transport and sport. Cyclists often report sensory and motor changes in the hands during rides. In the past, assessment of these symptoms was based on clinical history, physical examination and neurophysiology. The aim of this narrative review was to evaluate existing publications and determine if there are areas for further improvement in the clinical setting. Methods Searches were undertaken in accordance with the PRISMA guidelines using four online databases: PUBMED, OVID, CINAHL and WEB OF SCIENCE. Articles were evaluated using adapted versions of guidelines for case and cohort studies. Results 2630 articles were found and 13 were included in the review. 2 considered median, 9 considered ulnar and 2 assessed both nerves. 11 were case and 2 were cohort studies. 7 discussed neurophysiology and 1 mentioned ultrasound as a modality of investigation. Interventions were described in 3 articles. Conclusion The quality of evidence is generally low when considering this problem. Clinical assessment and neurophysiology are commonly regarded as the method for assessing nerve symptoms amongst cyclists. Advances in musculoskeletal ultrasound add to our early investigative repertoire and may help expedite management and limit future disability. In addition, further research is required into screening and preventative measures amongst cyclists.
EFFECT OF AMMONIA STRESS ON GROWTH, HEMATOLOGICAL, BIOCHEMICAL, AND REPRODUCTIVE HORMONES PARAMETERS OF NILE TILAPIA (Oreochromis niloticus)

The present study was conducted to evaluate the ammonium hydroxide stress on Nile tilapia (Oreochromis niloticus) growth, health, and reproductive hormones. However, fish (70 ± 4 g) were exposed to different levels of ammonium hydroxide (0.0, 150, 250 and 350 pg/L) for 90 days. The results showed that fish growth was retarded as ammonium hydroxide levels increased and lowest growth was observed with fish exposed to 350 pg/L of ammonia. The highest growth was observed with the control group (0.0 ammonium hydroxide). Glucose and cortisol in fish plasma increased significantly, while total protein and total lipids decreased significantly due to ammonia stress. The obtained results show also that ammonium hydroxide stress was harmful to the fish liver and kidney where plasma aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, uric acid, and creatinine values were significantly increased with increasing ammonium hydroxide levels compared to the control one. It was also noticed that lysozyme increased with increasing ammonia levels as compared with the control one. But immunoglobulin M activities of Nile tilapia decreased with increasing ammonia levels as compared with the control one. plasma follicular stimulating hormones (FSH), 17B estradiol (E2) and testosterone (T) were decreased significantly at fish with increasing ammonia levels. On the other hand, the measurements in most parameters of the male fish were larger than the measurements of the female fish that exposed to 150, 250 and 350 pg L-1 ammonium hydroxide for 90 days.
Drain efficiency amplifier of 50% with optimized power range for CDMA base station

A novel high‐efficiency Doherty amplifier is presented here.A carrier amplifier and a peak amplifier are set to asymmetrical drain voltages to extend the power range where a high efficiency of the amplifier is maintained. In Doherty amplifier, matching circuits of the carrier amplifier and peak amplifier are designed for each drain voltage so that the efficiency and signal linearity of the amplifier at a 7.2 dB back‐off point from its saturated output power become higher than those of a conventional amplifier. A Doherty amplifier containing laterally‐diffused metal‐oxide semiconductor field‐effect transistors achieves an adjacent channel leakage power ratio of −30.89 dBc and a drain efficiency of 50% at an output power of 49.3 dBm. This is the highest drain efficiency of a Doherty amplifier for a CDMA signal to the best of the authors' knowledge. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 1244–1246, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25195
DETERMINANTS OF INVESTMENT INTENTIONS: AN INDIVIDUAL RETAIL INVESTOR’S PERSPECTIVE FROM NAIROBI SECURITIES EXCHANGE

The purpose of this study was to assess the determinants of investment intentions of individual stock market investors in Nairobi Securities Exchange. The specific objectives of this study were to investigate the effect of expected investment value, expected sacrifices, subjective investment knowledge, compatibility and perceived behavioral control on investment intention of individual investors in Kenya. In addition, the study sought to build a theoretical model to explain investment intentions in financial securities by individual investors by examining the relationships between subjective investment knowledge, expected sacrifice, expected investment value, compatibility, perceived behavioral control and investment intentions. A cross sectional survey, multi-stage sampling technique involving 423 randomly selected individual investors participated. Data was collected using structured questionnaires and interview guides. Using hierarchical regression analysis, empirical results showed that subjective investment knowledge, expected investment value, compatibility, perceived behavioral control had a positive and statistically significant effect on investment intentions of individual investors. The effect of expected sacrifices on investment intention of individual investors was positive but statistically not significant.
A Noisy Infrared and Visible Light Image Fusion Algorithm

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image’s high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high-and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.
Velocity Sensorless Control of Uncertain Load Using RKF Tuned with an Evolutionary Algorithm and Mu-Analysis

Abstract In case of a velocity control scheme for a load directly driven by an actuator, large variations of its parameters are problematic due to possible instability and large variations of the final performances. This performances are then decreasing if a sensorless control is implemented due to cost, reliability or application constraints. This paper proposes solutions to quickly and accurately tune an observer with a lower computer time consumption and lower conception time. A previous calculated state feedback is used as base for a Kalman filter with special noise matrices. An evolutionary algorithm optimizes the observers degrees of freedom all over the variations. The mu-analysis theory helps to cancel known unstable set of parameters before running iterations in the optimization algorithm. Experiments show that the stability and the performance are effectively maintained.
Discrepancy and Sparsity

We study the connections between the notions of combinatorial discrepancy and graph degeneracy. In particular, we prove that the maximum discrepancy over all subgraphs $H$ of a graph $G$ of the neighborhood set system of $H$ is sandwiched between $\Omega(\log\mathrm{deg}(G))$ and $\mathcal{O}(\mathrm{deg}(G))$, where $\mathrm{deg}(G)$ denotes the degeneracy of $G$. We extend this result to inequalities relating weak coloring numbers and discrepancy of graph powers and deduce a new characterization of bounded expansion classes. Then, we switch to a model theoretical point of view, introduce pointer structures, and study their relations to graph classes with bounded expansion. We deduce that a monotone class of graphs has bounded expansion if and only if all the set systems definable in this class have bounded hereditary discrepancy. Using known bounds on the VC-density of set systems definable in nowhere dense classes we also give a characterization of nowhere dense classes in terms of discrepancy. As consequences of our results, we obtain a corollary on the discrepancy of neighborhood set systems of edge colored graphs, a polynomial-time algorithm to compute $\varepsilon$-approximations of size $\mathcal{O}(1/\varepsilon)$ for set systems definable in bounded expansion classes, an application to clique coloring, and even the non-existence of a quantifier elimination scheme for nowhere dense classes.
Locally Enhanced Self-Attention: Combining Self-Attention and Convolution as Local and Context Terms

Self-Attention has become prevalent in computer vision models. Inspired by fully connected Conditional Random Fields (CRFs), we decompose self-attention into local and context terms. They correspond to the unary and binary terms in CRF and are implemented by attention mechanisms with projection matrices. We observe that the unary terms only make small contributions to the outputs, and meanwhile standard CNNs that rely solely on the unary terms achieve great performances on a variety of tasks. Therefore, we propose Locally Enhanced Self-Attention (LESA), which enhances the unary term by incorporating it with convolutions, and utilizes a fusion module to dynamically couple the unary and binary operations. In our experiments, we replace the self-attention modules with LESA. The results on ImageNet and COCO show the superiority of LESA over convolution and self-attention baselines for the tasks of image recognition, object detection, and instance segmentation. The code is made publicly available.