Reviewerly/exHarmony huggingface dataset:
An Underwater Image Enhancement Benchmark Dataset and Beyond

Underwater image enhancement has been attracting much attention due to its significance in marine engineering and aquatic robotics. Numerous underwater image enhancement algorithms have been proposed in the last few years. However, these algorithms are mainly evaluated using either synthetic datasets or few selected real-world images. It is thus unclear how these algorithms would perform on images acquired in the wild and how we could gauge the progress in the field. To bridge this gap, we present the first comprehensive perceptual study and analysis of underwater image enhancement using large-scale real-world images. In this paper, we construct an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images. We treat the rest 60 underwater images which cannot obtain satisfactory reference images as challenging data. Using this dataset, we conduct a comprehensive study of the state-of-the-art underwater image enhancement algorithms qualitatively and quantitatively. In addition, we propose an underwater image enhancement network (called Water-Net) trained on this benchmark as a baseline, which indicates the generalization of the proposed UIEB for training Convolutional Neural Networks (CNNs). The benchmark evaluations and the proposed Water-Net demonstrate the performance and limitations of state-of-the-art algorithms, which shed light on future research in underwater image enhancement. The dataset and code are available at https://li-chongyi.github.io/proj_benchmark.html.
A Memory-Efficient FM-Index Constructor for Next-Generation Sequencing  Applications on FPGAs

FM-index is an efficient data structure for string search and is widely used in next-generation sequencing (NGS) applications such as sequence alignment and de novo assembly. Recently, FM-indexing is even performed down to the read level, raising a demand of an efficient algorithm for FM-index construction. In this work, we propose a hardware-compatible Self-Aided Incremental Indexing (SAII) algorithm and its hardware architecture. This novel algorithm builds FM-index with no memory overhead, and the hardware system for realizing the algorithm can be very compact. Parallel architecture and a special prefetch controller is designed to enhance computational efficiency. An SAII-based FM-index constructor is implemented on an Altera Stratix V FPGA board. The presented constructor can support DNA sequences of sizes up to 131,072-bp, which is enough for small-scale references and reads obtained from current major platforms. Because the proposed constructor needs very few hardware resource, it can be easily integrated into different hardware accelerators designed for FM-index-based applications.
Motion Planning and Manoeuvring in Self Driving Cars

Lane keeping, path planning and decision making are the most important features of self-driving cars. Cooperative adaptive cruise control and platooning are notable applications in autonomous cars. It expands the use of street foundation assets through composed control and platooning of individual vehicles with the capability of improving both traffic wellbeing and productivity. In this study, end-to-end lane keeping and path planning are explored. Self-driving cars are presently recognised as the core of industry research because of its multi-faceted quality vehicle benefits which includes advanced security, reduced blocking, minor manufacturing and improved mobility. When transporting people or commodities from one location to another, motion planning methods include locating a track to follow, avoiding roadblocks and designing the optimum route that ensures security, ease and effectiveness. The purpose of this study is to review present approaches and evaluate the different techniques for the motion planning of self-directed on-road driving that consists of locating a lane, finding for the safest manoeuvre and shaping the main possible route. The study demonstrates a critical evaluation of each of these processes in terms of their benefits and drawbacks.
Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance

Learning from Interpretation Transition (LFIT) is an unsupervised learning algorithm which learns the dynamics just by observing state transitions. LFIT algorithms have mainly been implemented in the symbolic method, but they are not robust to noisy or missing data. Recently, research works combining logical operations with neural networks are receiving a lot of attention, with most works taking an extraction based approach where a single neural network model is trained to solve the problem, followed by extracting a logic model from the neural network model. However most research work suffer from the combinatorial explosion problem when trying to scale up to solve larger problems. In particular a lot of the invariance that hold in the symbolic world are not getting utilized in the neural network field. In this work, we present a model that exploits symbolic invariance in our problem. We show that our model is able to scale up to larger tasks than previous work.
Create System-Wide Accessible AR Content: Quick Look with USDZ

What if you can allow your users to preview your AR content without downloading your app? And what if your users can preview AR content directly from the Web? With the Quick Look framework, these features are available.
Automatic Conjecturing of P-Recursions Using Lifted Inference

Recent progress in lifted inference algorithms has made it possible to solve many non-trivial counting tasks from enumerative combinatorics in an automated fashion, by casting them as first-order model counting problems. Algorithms for this problem typically output a single number, which is the number of models of the first-order logic sentence in question on a given domain. However, in the combinatorics setting, we are more interested in obtaining a mathematical formula that holds for any given structure size. In this paper, we show that one can use lifted inference algorithms to conjecture linear recurrences with polynomial coefficients, one such class of formulas of interest.
Customer Experience Model for Communication Service Provider Digital Twin

The ultimate goal of the study is the built digital twin of a telecom operator. One of the important components of a communication service provider (CSP) digital twin is the customer’s digital twin. Building a customer’s digital twin is an extremely difficult task, because a number of properties of a real customer are difficult to formalize. We offer a customer experience model, which will become part of the general customer digital twin model, complementing the behavioral aspect of a real customer. General model of fuzzy cognitive maps (FCMs) was chosen as the mathematical basis for this model. For this study, we used data from two big CSPs. Based on these data, two models of FCMs were developed.
Body Motion Capture

One of the most overpowered moves in fiction is the Sharingan from the Uchiha clan in Naruto. The Sharingan allows an individual to outright copy every action a person does. In this chapter, you’ll give your device the Sharingan ability. You’ll have a rigged model that does exactly as you move.
People Occlusion

People occlusion is the effect of hiding virtual content when accounting for the relative distance between physical human and virtual content. When a person stands in front of virtual content, he/she should hide the parts of the content which he/she covers. When the same person stands behind the virtual content, the virtual content should conceal the human’s parts that the virtual content covers. That’s the gist of people occlusion.
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits

In many real-world applications, the i.i.d. assumption does not hold and thus capturing the interactions between instances is essential for the task at hand. Recently, a clear connection between predictive modelling such as decision trees and probabilistic circuits, a form of deep probabilistic model, has been established although it is limited to propositional data. We introduce the first connection between relational rule models and probabilistic circuits, obtaining tractable inference from discriminative rule models while operating on the relational domain. Specifically, given a relational rule model, we make use of Mixed Sum-Product Networks (MSPNs)—a deep probabilistic architecture for hybrid domains—to equip them with a full joint distribution over the class and how (often) the rules fire. Our empirical evaluation shows that we can answer a wide range of probabilistic queries on relational data while being robust to missing, out-of-domain data and partial counts. We show that our method generalizes to different distributions outperforming strong baselines. Moreover, due to the clear probabilistic semantics of MSPNs we have informative model interpretations.
Other Quasi-Interpolants and Wavelets

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Simultaneously Integrate Face Tracking and World Tracking

Creating augmented reality experiences for face tracking and the virtual world are fun things to do. Hence, it only makes sense to double the fun by combining the face tracking and the virtual world into a bigger fun packaged experience!
Advancing AR Quick Look for Commerce on the Web

Oh iOS developers, today you’re going to advance AR Quick Look on the Web. AR Quick Look is a system-wide AR content preview framework, and it’s definitely not limited to just your app. Particularly with websites that want to leverage AR content in commerce, your iOS device can leverage some magic.
Detecting Horizontal Planes and Adding 3D Objects with Raycast in SceneKit

Augmented reality has the power to amplify the world in ways never possible before. How we interact with our world may never be the same again. With the release of iPhone X, the world is ready to embrace AR now more than ever. We are at a special time in history and just at the beginning of something huge. The potential of AR is endless.
Reality Composer: Creating AR Content

Reality Composer can help you generate gorgeous and performant AR experiences easier than most existing 3D content creation tools. Prior to the release of Reality Composer, developers and designers would have to make design or performance trade-offs.
Scanning 3D Objects

There’s image recognition and there’s object recognition. Unlike image recognition, object recognition is more complex since it is three-dimensional. Being at a three-dimensional state carries higher variabilities than a two-dimensional image. Variables include
Hand Gesture Recognition for Real-Time Game Play Using Background Elimination and Deep Convolution Neural Network

In recent scenarios, Gaming Technology is on the surge of the utmost extent of technical advancement. Contemporary gaming using game controllers limits its reach due to various economic issues. The game programmers are making efforts towards developing games without a game controller. The expensive game controllers restrict the usage of gaming among users. In this research work, a mobile-based human–computer interaction system has been developed which enables users to control video games with more physical interaction and without more restrictions. The novelty of work is to play games using any good quality mobile/web camera instead of the game controller. A Convolution Neural Network (CNN) is combined with background elimination to detect different hand gestures and further uses these gestures to control video games. In the first instance, a background elimination algorithm is used to extract the hand gesture image captured through a mobile/web camera. These hand images have been used to train as well as predict the type of gesture. CNN is used to detect gestures and to render the appropriate motion in the game. The designed human–computer interaction system concludes 98.2% accuracy of hand gesture recognition for considered hand gestures. The measured latency is also adequate while game play.
Building Your First ARKit App with SceneKit

Augmented reality is here. It is coming in a big way. Remember Pokémon Go? Well, that’s just a taste of augmented reality. Apple is bringing augmented reality to the masses, starting with iOS 11. With iOS 11, hundreds of millions of iPhones and iPads are going to be AR capable. This will make ARKit the largest AR platform in the world—overnight. Yes—overnight. If you are interested in building augmented reality apps for iOS 11 and above, then you are in the right place.
Working with SpriteKit and ARKit

ARKit interacts with the physical world. With augmented reality experiences taking place in a 3D space, it’s often easy to forget/neglect that 2D content also plays a role in the 3D world.
Working with SwiftUI and ARKit

With the introduction of SwiftUI, iOS developers have the ability to create apps using declarative syntax. SwiftUI doesn’t support ARKit in the declarative format. Nonetheless, this shouldn’t stop developers from working with the latest technologies even when ARKit is built primarily for UIKit.
On Convergence of Tabu-Enhanced Quantum Annealing Algorithm

The convergence of a recently proposed tabu-enhanced quantum annealing algorithm depends critically on the finiteness of memory of the related stochastic process. We discuss the background of quantum annealing and the convergence issues of the tabu-enhanced algorithm. Given the details of the tabu data structure, the so-called tabu matrix, we consider the sequences of solutions that result in a tabu matrix collisions. As such, convergence of the algorithm is related to the problem of studying the so-called matrix kernel, which we investigate and give an example of such a collision as well.
Exploration and practice of effective implementation of online teaching during the epidemic period

Abstract: During the epidemic period, teachers will not only be affected by the network environment and teaching software, but also face the challenge of how to improve the classroom teaching effect of online teaching. Taking the course of international business document practice as an example, PDCA is applied The circulation concept is introduced into online teaching. According to the four links of planning, implementation, inspection and feedback, it is carried out through the "vocational education cloud" platform, and combined with the individual entrance test, multi-dimensional interaction, exit test, after-school remedial exercise, challenge questions and group work, the accurate assessment method is adopted to improve the quality of classroom teaching and students' learning effect. Some suggestions are put forward The direction of online and offline hybrid course teaching in the future is discussed.
Design of Glasses Products Based on Artificial Intelligence

With the rapid development of artificial intelligence and information technology, the way people obtain and process information has changed from a single way to a differentiated and personalized multiple way. As a means of transmitting and exchanging man-machine information, smart glasses have developed rapidly in recent years and have been widely reported by the media. The purpose of this article is to study the design of glasses products based on artificial intelligence. This article summarizes the functional requirements of smart glasses products through the questionnaire survey method, and explains the relevant module design of the products. Then carry out the design practice and usability evaluation of the product, by 3D printing the smart glasses product, carrying out the usability test on the printed white mold, and adjusting the design plan accordingly through the test results. According to survey data, 82.44%, 69.89%, 46.95%, and 59.86% of the number of people who believe that products should have the characteristics of durability, strong equipment, face recognition, and voice recognition account for 82.44%, 69.89%, 46.95%, and 59.86%. Therefore, durable, strong equipment, voice recognition, the feature of firm wearing are the main design requirements in the design practice of smart glasses products, and these features or functions need to be met first in the design.
Characteristics of planning actions in elementary school

The article presents a study of the features of the action of planning in schoolchildren of 2-4 grades. Two types of planning are characterized - formal and substantive. It is shown that in the third year of primary school there is a transition of most children from formal to meaningful planning.
Processing Method and System of Artificial Intelligence Application Based on Open Source Deep Learning Framework

With the rapid development of computer technology, artificial intelligence has become a very important topic in the field of information technology in the world. In our living and working environment, machine learning is one of the methods with strong ability to process and understand information and high accuracy. It can transform complex data into simple and easy to store and manage algorithm tools that are characteristic of human brain memory and can quickly identify the behavior rules of target objects. It can also integrate and analyze a large number of original data to solve some practical problems. Therefore, based on the open source deep learning framework, this paper designs an artificial intelligence application processing system. Firstly, this paper introduces the concept and principle of deep learning, studies its application law, then expounds the application processing method of artificial intelligence, designs the framework of artificial intelligence application processing system, and tests its performance. Finally, the experimental results show that the artificial intelligence processing system based on deep learning algorithm has good performance in all aspects, the operation time and delay time are within 2–3 s, the occupied memory is about 3400k, and the CPU occupation rate is about 2%. This shows that the performance of the system has met the requirements.
MTUP: Multi-Task CNN with Uncertainty and Probability for No-Reference Image Quality Assessment

Current CNN-based image quality assessment (IQA) metrics treat all image patches equally. We observed that when the distortions do not appear or not noticeable in the image patch, its predicted quality score is usually away from the subjective score. In this paper, we argue that not all image patches equally matter for the IQA task and present a multi-task convolutional neural network (CNN) model with uncertainty and probability for no-reference IQA (MTUP). We also present a probability-aware average (PAA) method for pooling the image quality-score from the scores of the image patches. Because the loss functions of image quality-score prediction and distortion-type identification tasks have quantities with different units and scales, we further use a multi-task learning method that automatically weights the loss functions of multiple tasks with task uncertainty to solve the challenge of relative weights tune. Experimental results show that the proposed MTUP model achieved a superior performance as compared with state-of-the-art NR-IQA metrics.
Sports Quality Test Recognition System Based on Fuzzy Clustering Algorithm

Deepening the understanding of the fuzzy clustering algorithm, expanding the scope of application of the fuzzy clustering algorithm, and promoting its integration with sports quality testing will help promote the innovation of the sports quality testing recognition system. The purpose of this article is to study the physical fitness test and recognition system based on fuzzy clustering algorithm. First, the performance evaluation index of fuzzy clustering algorithm and the group visualization method based on Sammon mapping are introduced. The structure of CAPTES system and the function of each subsystem are introduced and analyzed. The system is a highly implemented professional system whose main function is to identify and analyze sports qualities. The fuzzy cluster analysis module makes statistical analysis simple and easy. After the successful development of the sports quality test and recognition system based on the fuzzy clustering algorithm, it was tested in M Academy in time. The experimental results show that the average data of the students with good performance in the shoulder rotation test is 110.6 cm, which is higher than the students with excellent performance in the shoulder rotation test. Therefore, the feasibility of the shoulder rotation test as a test of physical fitness remains to be studied. The scoring test on the data of the first and second grades of M College proved that the software system is stable and effective, and it has been well received by the school's physical education department.
Better Modeling Out-of-Distribution Regression on Distributed Acoustic Sensor Data Using Anchored Hidden State Mixup

Generalizing the application of machine learning models to situations where the statistical distribution of training and test data are different has been a complex problem. Our contributions in this article are threefold: 1) we introduce an anchored-based out-of-distribution (OOD) Regression Mixup algorithm, leveraging manifold hidden state mixup and observation similarities to form a novel regularization penalty; 2) we provide a first of its kind high-resolution distributed acoustic sensor dataset that is suitable for testing OOD regression modeling, allowing other researchers to benchmark progress in this area; and 3) we demonstrate with an extensive evaluation the generalization performance of the proposed method against existing approaches and then show that our method achieves state-of-the-art performance. We also demonstrate a wider applicability of the proposed method by exhibiting improved generalization performances on other types of regression datasets, including Udacity and Rotation-MNIST datasets.
HUMAN AND NON-HUMAN BEINGS. POSSIBILITIES OF INTERACTION

The paper presents an analysis of the ways for interaction between man and non-human beings. Those ways are considered in anthropological and philosophical-ecological methodical approaches. The approaches imply rejecting the anthropocentrism as actual ontological basis of the Western cultural tradition. T. Morton models a coexistence of humans and non-human beings as a network uniting all living creatures. Human and non-human beings are now placed in a single process of coexistence and the human ends to be at the top of the natural hierarchy. One of the options to revise the system of interaction of human and non-human beings is to rely on the non-Western (Chinese) philosophical tradition. The anthropological approach to rethinking the position of human in the world is presented in E. Cohn’s project. He considers the human being in the framework of his interactions with the world of non-human often crucial for survival. Based on the semiotics by C. Pierce, Cohn postulates that all living beings are capable to represent the world around them using certain signs for that. A way to establish interspecies communication is animism and concept of perspectivism, which clarifies it. Animism is about the internal similarity of living beings, with a difference in external characteristics. Perspectivism allows to add that every living creature is able to understand the other by accepting his or her point of view, his or her perspective. Thus, the rejection of the anthropocentrism enables development of equal relations of human and non-human beings. Such equal coexistence may have a positive impact on sustainability.
Getting Started

If you don’t have the prerequisites, you can still be very successful with this system. Almost all other literature on running flexible, modern engineering projects specifies these roles be filled by someone full time. This is just not reality. Teams all over are strapped for time and resources and having a product owner separate from a product manager is rarer than it sounds when reading online articles.