Reviewerly/exHarmony huggingface dataset:
Hipertensión portal por hiperaflujo: fístula arteriovenosa esplénica

In this paper, we present a new reversible data hiding method based on joint neighboring coding. The proposed method uses the side-match distortion (SMD) function to sort the codebook so as to make an index value become very close to its neighboring index values, then the residual value between the index and its neighboring index is obtained by bitwise exclusive-OR operation and the secret bits are embedded into the residual value according to our embedding rules based on joint neighboring coding. The experimental results show our proposed method outperforms the related existing data hiding methods in embedding performance.
MetaTableLite: An Efficient Metadata Management Scheme for Tagged-Pointer-Based Spatial Safety

A tagged-pointer-based memory spatial safety protection system utilizes the unused bits in a pointer to store the boundary information of an object. This paper proposed a hybrid metadata management scheme, MetaTableLite, for tagged-pointer-based protections. We observed that objects of a large size only take a minority part of all the objects in a program. However, recording their boundary metadata with traditional pointer tags will incur large memory overheads. Based on this observation, we introduce a small supplementary table to maintain metadata for these few large objects. For small ones, MetaTableLite represents their boundaries with a 14-bit pointer tag, well utilizing the unused 16 bits in a conventional 64-bit pointer. MetaTableLite can achieve a 6% average memory overhead without alternating the conventional pointer representation.
A Combination of DWT and QR Decomposition for Color Image Watermarking

For the purpose of protecting copyright of digital images, many published articles indicate that combining DWT with matrix decomposition can improve robustness of watermark. In this paper, a hybrid image watermarking scheme is represented by using a combination of 1-level <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$DWT$</tex> transform and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$QR$</tex> decomposition. The first, Haar transform is applied on the channel B of the host color image and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$LL$</tex> sub-band is partitioned in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4 \times 4$</tex> non-overlapping blocks. After that, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$QR$</tex> factorization is executed on each block where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Q$</tex> matrix and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R$</tex> matrix are calculated separately by our proposal. Watermark bits are embedded into the first element of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R$</tex> matrix instead of the whole row as previous published articles to improve the quality of watermarked image. In addition, the original watermark image is permuted by Arnold transform and it helps the proposed method is more secure. In this study, we also perform experiments to select the most suitable sub-band for embedding information. The experimental results show that this combination gives a better invisibility of watermarked image which is compared to the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$QR$</tex> decomposition based approach. Furthermore, the proposed algorithm is more effective to against many common attacks.
Calibration of a Dual-Telecentric Fringe Projection System Using a Planar Calibration Target

The development of modern manufacturing techniques increases the precision of tiny components. It is of great significance to accurately obtain the three-dimensional (3D) shape information of objects. In this paper, a telecentric fringe projection system for 3D measurement at micron-millimeter scales is constructed, and a calibration method for the system based on a planar calibration target is proposed. The calibration of the system is divided into two parts: the calibration of the telecentric camera and the calibration of the telecentric projector. Specifically, the telecentric camera parameters are obtained by using the characteristics of the rotation matrix and the repair marks of the positioning platform. The projector is calibrated by using the reversibility principle of the optical path. Experimental results show that the reprojection error of the calibration method is 0.2pixel, which proves its feasibility and high measurement accuracy. Application experiments show that the dense point cloud of small objects can be generated by using the proposed system, which shows that it has good potential application prospects in 3D measurements of small objects.
Corpus Studies of Syntax

Recent developments in the experimental syntax program have challenged some of the standard practices for collecting and analyzing linguistic evidence. In doing so, the methodological and theoretical gap between other areas of language science has begun to close. It is more common than ever before for research in theoretical syntax to incorporate multiple methodologies in the same study. Online elicitation methods, adopted from psycholinguistics, have been the most visible new addition to the theoretical syntactician’s toolbox. Yet observational data, in the form of corpora, has begun to play a larger role in contemporary syntactic investigation. The aim of this chapter is to contextualize the evolving role of corpus studies in syntactic investigation as a methodology that can be used to externally validate results from other methods as well as generate hypotheses. I highlight theoretical and practical advantages of employing corpora in tandem with other methods and point to future directions where gains can still be made.
Identity in Martin‐Löf type theory

Abstract The logic of identity contains riches not seen through the coarse lens of predicate logic. This is one of several lessons to draw from the subtle treatment of identity in Martin‐Löf type theory, to which the reader will be introduced in this article. After a brief general introduction we shall mainly be concerned with the distinction between identity propositions and identity judgements. These differ from each other both in logical form and in logical strength. Along the way, connections to philosophical debates concerning identity are noted. Some use of logical symbolism is inevitable in any serious discussion of type theory, but the emphasis here is on basic ideas rather than technicalities.
Signature Scheme Based on The SM2 Algorithm in Fabric

Based on the analysis and research of the widely used Hyperledger Fabric alliance chain structure, this paper proposes a digital signature scheme based on the national cryptographic algorithm SM2 which can be applied to Hyperledger Fabric. Firstly, two elliptic curve public-key cryptography algorithms are analyzed, and the feasibility of the SM2 in Fabric system is studied. Secondly, the Fabric system using the SM2 algorithm is designed and implemented, and the generation process of the Fabric chain address using the SM2 algorithm is given. Finally, experimental verification of the availability and performance of the Fabric system after the replacement of national cryptography algorithms is carried out. The experimental results show that the SM2 interface of the new Fabric alliance chain has good usability, and the average latency is reduced by 51.8%, and the transaction throughput is increased by 33.1%.
Development of a Complex of Algorithms for Collecting and Marking Text Data for Identifying Destructive Messages

In the context of the problem of searching for destructive messages, the authors investigated the problem of lack of labeled data for training intelligent models and proposed an algorithm for automated collection and labeling of text data sets. This approach includes algorithms for collecting, processing and preparing text data, as well as training the classifier to simplify the subsequent process of marking and balancing by the target class in the final set of text data. On the example of real data, the authors evaluated the accuracy of the trained classification model using the F-measure, on the basis of which the applicability of the proposed algorithm for collecting and marking up textual data when the target class imbalance in the classification problem is proved.
Breaking Physical Barriers With Mobile Technologies

Considering the growing popularity of mobile technologies and therefore social media tools, the idea of this study is not to promote or romanticise a social media tool but to explore the potential of social media for educational use by presenting a specific example. The study also aims to bring a deeper understanding of how mobile applications could be used to foster language education and consider their possible potential in education. Unlike the common trend investigating English vocabulary in the field, this study does not expose students to word lists but attempts to support the curriculum that students have to follow in their formal education. In this context, this chapter suggests an example of going beyond the physical constraint of language classroom by providing learners informal opportunities to practise English outside school in various contexts by using one of the most popular tools, namely WhatsApp.
Communication Signal Modulation Recognition Based on Time-Frequency Domain Analysis and Bayesian optimized Decision Tree Algorithm

Communication signal modulation mode recognition technology plays a crucial role in communication confrontation in the modern war environment. Due to the low accuracy of the traditional communication signal recognition methods, this paper introduces a method to identify modulation modes of communication signals based on a Bayesian optimized decision tree. In this paper, a modulation mode recognition method of communication signals based on Bayesian optimization and decision tree is proposed. First, simulate the signals of different modulation modes, including frequency-shift keying modulation (FSK), frequency modulation (FM), amplitude modulation (AM). Then the signal data is processed by using the time and frequency domain feature extraction algorithm. Next, the obtained data is used to train and verify the decision tree. And the model parameters are optimized by the Bayesian method. The recognition of these three communication modulation signals is realized, and the accuracy is up to 94%.
Development of intelligent integrated design system for hydraulic plane steel gate

In this paper, the parametric programming language APDL of structural analysis software ANSYS and python object-oriented intelligent interface development tool pyqt5 are used to develop the intelligent integrated design system of plane steel gate. The system is composed of three parts. In the first part, the preliminary design module of plane gate based on design specification is developed by python. In the second part, APDL parametric language is used to build the database of gate components, loads, constraints and other parameters, and the three-dimensional finite element model of the overall gate is established. In the third part, the finite element structural calculation is carried out by using ANSYS software. According to the finite element calculation results, further optimization analysis is carried out to optimize the component parameters and optimize the stress state of the gate. In these parts, pyqt5 interface development tool, APDL parametric programming language and the powerful structural analysis function of ANSYS are integrated. The visual interface is used for integrated design. The data transmission of the three parts is seamlessly connected through the developed interface module, forming an intelligent and integrated plane steel gate design system, which greatly improves the design quality and design efficiency.
Secure Virtual Machine Migration using Ant Colony Algorithm

Heuristic algorithms are used solve the VM consolidation. One of the well-known approaches to solve this issue is bin packing method. This method is considered as NP-hard. There are quite number of other heuristics algorithm available to address this issue. This problem can be handled effortlessly with one dimensional bin packing m. In Bin Packing there are few methods used to pack the empty bins efficiently. First Fit (FF) Bin packing algorithm is one of most popular and efficient method to pack the empty bins. Here, FF algorithm packs available items into first bin where it aptly accommodates. Best Fit algorithm places an item into a maximum load instead of placing in the first bin like First Fit algorithm. These two methods are enhanced by making small alteration in the algorithm which are named as First Fit Decreasing (FFD) method and Best Fit Decreasing (BFD) method. These methods could not be implemented straightaway for VM consolidation. This must me altered appropriately before applying for this issue. In addition, consider that physical machines (PM) don’t have any virtual machines (VM) before executing the migration algorithm and also the utilization of the datacenters is managed by the number of VM’s request and server’s request. The energy consumption of the VM’s is majorly considers the CPU utilization instead of bandwidth and memory. The authors concentrate on CPU utilization rate to minimize the energy consumption.
Availability and security analysis of business‐critical systems: A case study of e‐commerce business process

Abstract Business critical systems (BCS) are those systems whose failure may lead to loss of business or damage to reputation in the market. This is often due to the interruption of service caused by the system being unusable. Therefore, non functional requirements (NFRs) such as availability and security play a crucial role during the development of BCS to mitigate impact to the risk. Nowadays, E‐commerce businesses contribute a significant amount to the GDP of any country. Availability of such systems should be high as well as these systems should be secured against threats. Therefore, in this work, a framework is proposed for the availability analysis during the design phase of the BCS. Also, an approach is used for the security analysis of BCS. A case study of the E‐commerce business system is taken to illustrate our framework.
Geometric estimates of variations in space geodetic data

Abstract Well-known statistical parameters have some disadvantages when analyzing space geodetic data. Geometric parameters are proposed here for estimating the variation properties of samples for various discrete datasets. The proposed parameters are logically related to each other and are based on the simplest well-known statistical parameters; they do not depend on the type of distribution of the sample under study. “Variation asymmetry” shows the shift of the arithmetic mean relative to the center of the variation interval in the units of the studied sample. “Density of variation” characterizes the level of average variability in sample units. This parameter has several times greater discriminatory sensitivity to extremely different types of variations than linear and standard deviations. The relative parameter “proportion of maximum density” shows the closeness of variation to a uniform distribution in the ranked sample and complements the indicator of variation density. An algorithm for separating different structural levels of the useful signal from emissions (noise) is proposed here based on the calculation of geometric characteristics. The iterations of dividing the sample into structurally homogeneous segments can be stopped at the level of the proportion of maximum density ≥0.9 when analyzing real GPS coordinates.
Face Recognition Using Shallow Age-Invariant Data

Face aging is a challenging research area in face recognition and verification. However, recognizing identical faces with an immense age gap gives rise to various difficulties because of the diversity in face appearance caused by aging. In real-world applications, the pre-training dataset is very limited (e.g only two age-invariant face images) are present for each identity. We define this term as Shallow Age-Invariant Face Learning, and find it difficult with existing methods. Different from large-scale and shallow face data, the age-invariant dataset is lacking intra-class distance. Thus, mostly face recognition algorithms are collapsed, feature dimensions easily gets into over-fitting and degeneration problems. To examine such discrepancies and evaluate recent state-of-the-art methods (SOTA), we investigate the performance of SOTA models on different metrics learning approaches. Further, we re-organize three age-invariant datasets into negative and positive pairs with a mixed interval of ages. We select the face aging dataset (FG-NET) to cover all age groups with aging and occlusion, the longitudinal dataset (MORPH-Album 2) for illumination and low-resolution, and the age database (Age-DB) for pose and noise. Although for major factors, Arc-Face and Face-Net outperform others. Another interesting finding of our research, the training performance on age-invariant pairs is still saturated with a clear margin. This research provides further directions for future research and insights.
Content-Based Image Retrieval: Impact of image resolution on the search accuracy and results ordering

Image resolution plays an important role in content-based image retrieval (CBIR) systems since both the query and the images being added to the database are processed pixel by pixel. Higher resolutions need more processing time, where the dependence is not linear, but quadratic. However, it is uncertain if high resolutions actually lead to more accurate search and better order of retrieved results. The purpose of this research is to determine the impact of image resolution on the search accuracy and results ordering. If it has a little influence on them, then it is quite appropriate to resize images before adding them to the image database. That could significantly speed up the insertion process. To test the impact of image resolution, we conduct a series of experiments using the same image dataset but pre-replicated in resolutions starting from 32x32 px to the images’ original resolutions, sometimes higher than 5000x3000 px. Results show that resolution of 128x128 px provides quite similar order to the reference one, having a correlation of about 0.97 between the two orderings. So it is worthy to resize all high resolution images (Full HD and especially 4K, 8K and higher) to 128 px in order to reduce the processing time while keeping the search accuracy and the order of results almost the same.
Implementation and Acceleration of Image Recognition Algorithm under Limited Resources

In recent years, with the development of artificial intelligence and Internet of Things technology, more and more neural network models need to run on the mobile terminals. In order to better run the neural network model on the embedded chip with limited resources, we propose a method for efficiently transplanting and implementing MobileNet model, and utilize C66xDSP for model inference acceleration. We decompose the neural network model into multiple layer groups, which are loaded and computed by different C66xDSP modules in parallel. Experiments have proved that our method effectively reduces the scale of the MobileNet parameters, and improves the recognition speed of MobileNet on the embedded platform under the premise of taking into account the computational cost and the accuracy of image recognition. Our code is open source in https://gitee.com/njupt-b523/oph-robot.
Dice Combat: Development of a dice combat video game for mobile devices Using Ensemble Interactions patterns

Having more than one mobile device at home or a person using more than one device to perform the same activity are trends that have become common these days. In view of this, it is useful that more applications today allow interconnectivity and complementarity between more than one device to improve the experience when performing a particular activity, however, this popularity has not yet fully permeated the mobile gaming sector. Applying these features to mobile video games would result in a better gaming experience by allowing to take advantage of each device in the home. This article proposes a video game for Android mobile devices called Dice Combat, which has the theme of conquest of empires, where the units are made up of dice and three Android mobile devices connected to the same local network are required to carry out a game. With this proposal it is expected to demonstrate that the use of several connected devices, as well as the use of the accelerometer to exchange information between them through the shaking gesture, can enrich the gaming experience.
Personal Protective Equipment Kit Detection using Yolo v5 and TensorFlow

Object detection has application in numerous sectors. It is very crucial in the areas of security and surveillance. The Personal Protective Equipment (PPE) object detection Software can be used to detect people wearing masks in public places. In this paper we used the MobileNet SSD, a TensorFlow model, and Yolo v5, a Pytorch framework, to achieve PPE object identification. Many studies in the Object Detection domain focus only on accuracy. In our study we have also focused on the deployability of the model. We have obtained the “COVID-19 Personal Protective Equipment (PPE) Detection Dataset” from Kaggle. Furthermore, we have used performance metrics such as mAP, Loss Function and Learning Rate and a comparison between TensorFlow Object Detection API and Yolo v5. These metrics would give us a deeper insight into the models. The classification loss for the Yolo v5 model is significantly lower than that of a TensorFlow model, as can be seen from the observed data. The minimum classification for the Yolo v5 model is 3.719e-3 at 500 epochs, whereas the lowest classification for TensorFlow is 0.0881 at 20250 steps. This indicates that the Yolo v5 model is more effective at categorising data.
Improving Soft Law Governance of the Internet of Things

<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">From smart cities</b> to smart homes to smart factories, the Internet of Things (IoT) is the underlying technology that is powering a sea change in human-technological interaction. The IoT consists of an ever-expanding network of “things” that are connected to the Internet. These connected “things” go beyond the ubiquitous Internet and mobile platforms currently in existence, such as laptops and smartphones, and now include medical devices <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , smart meters <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , home personal assistants <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> , smart home appliances, and motor vehicles <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> , to name some examples. With an estimated 22 billion IoT connected devices in use around the world as of 2018 <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> , there are already more “things” connected to the Internet than people, and forecasts are that there will be between 40 and 50 billion connected “things” by 2025 <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref> .