Reviewerly/exHarmony huggingface dataset:
A Systematic Review of the Effective Features of Augmented Reality and 3D Systems in High School as Learning Management Tools

Technological devices have been the spearheading pioneer of education improvement and innovation ever since the industrial revolution started. The rapid pace of the emergence of different technologies in the field of education and other fields paved the way for the creation of a new paradigm called augmented reality. This new paradigm and its features innovate education and offers learners with the opportunity to have additional intrigue and interest in learning. As such, this paper's primary objective is to study which feature/s of Augmented Reality or AR systems is/are the most applicable for the learning development of high school students by evaluating previous research papers, with the consideration of the study being a secondary data gathering procedure as its main limitation. This study utilized Nielsen's usability engineering heuristics in order to evaluate the features involved in the gathered studies and used systematic review analysis. Results of the study have shown that the most applicable feature for the learning development of high school students is the usability factor 2 or the “match between the real-world factor” with a mean of 14.5 and a standard deviation of 0.837, suggesting that end users prefer AR systems with features and functionalities that they are already familiar with.
Feasibility study of microbial organic waste processing business in Sukasari district, Bandung city

Abstract Modern waste management systems must be carried out comprehensively and provide economic benefits. Many business opportunities for processing inorganic waste have been carried out such as recycling paper and plastic, while conventional organic waste is made into organic fertilizer / compost. The demand for organic fertilizer / compost is increasing along with the development of organic agriculture. This research was conducted to analyze the business opportunities of microbial organic waste which is a breakthrough in making compost fertilizer. The location of the study was conducted in Sukasari District Bandung City with the method used was descriptive method with SWOT analysis. SWOT analysis is used to analyze strengths, weaknesses, opportunities and obstacles in processing organic waste so that direction or recommendations are obtained. The stages are by analyzing IFE (Internal Factor Evaluation) and EFE (External Factor Evaluation) and strategy analysis using the SWOT matrix. Based on the results of the IFE calculation get a score of 3.25 and the EFE score gets 3.10. Strategy analysis based on the SWOT matrix includes the importance of increasing the quality and quantity of production, recruitment of workers, addition of land area and marketing using information technology.
Lightweight optimization of convolutional neural network for multi-objective recognition in structured scene

There are many redundant parameters in Convolutional Neural Network(CNN) when it is used for target recognition in a specific scene, which will greatly occupy the calculation amount and affect the operating efficiency of software and hardware, and cannot meet the real-time target detection requirements of the algorithm in a specific scene. In this paper, channel pruning, layer pruning and their hybrid pruning experiments were carried out on you only look once version 3(YOLOv3), a typical CNN target recognition model. The result of the hybrid pruning can greatly reduce the model parameters and the amount of calculation, and can reduce the model of resource utilization through the comparative analysis. And the volume of the model after hybrid pruning was reduced 94.4% when mAP only loss 0.9%. The model inference time was reduced by 36.6%. This study could provide references for the optimization of object recognition model in structured scenes such as road and workshop.
Chaos-Based RNG using Semiconductor Lasers with Parameters Variation Tolerance

Random numbers play an essential role in guaranteeing secrecy in most cryptographic systems. A chaotic optical signal is exploited to achieve high-speed random numbers. It could be generated by using one or more semiconductor lasers with external optical feedback. However, this system faces two major issues, high peak to average power ratio (PAPR) and parameter variations. These issues highly affected the randomness of the generated bitstreams. In this paper, we use a non-linear compression technique to compand the generated signal before it is quantized to avoid the effects of the PAPR. Also, we develop the post-processing stage by using advanced encryption standard (AES) algorithm feeds from two different generated bitstreams. These two integrated stages, non-linear quantization, and post-processing are configured to achieve a generation of a efficient random number guaranteed by NIST and DIEHARD statistical test suites. Finally, the proposed system is verified at parameter variation of ±20% tolerance including external mirror reflectivity, external cavity length, and normalized injection current. The results show that the proposed system could generate truly random numbers even with parameters configuration tolerance.
Analysis Of Quality Of Service (QoS) Apache Open Meeting Video Conference Application And Bigbluebutton On Virtual Private Server

Currently one of the technologies that are trending in communication technology is video conferencing technology that can make it easier for humans to communicate over long distances. various applications offer video conferencing technology, some are open source and some are proprietary, one of the opensource video conferencing applications is Apache OpenMeetings and BigBlueButton. This study discusses the comparison of the two applications, by testing it with scenarios of user variations and variations in bandwidth used for both applications. The result of this research is that BigBlueButton application is better than Apache OpenMeetings based on 3 parameters tested, namely Packet Loss, Delay and Jitter.
Application of Piano Automatic Accompaniment System Based on Artificial Intelligence in Piano Enlightenment Education

The rapid development of contemporary science and technology has caused changes in the material and technical aspects of piano enlightenment teaching, which has played a role in promoting the innovation and development of educators' teaching mode and teaching theory. At the same time, this is also the challenge and impact brought to us by technology. This article mainly studies the application of artificial intelligence-based piano automatic accompaniment system in piano enlightenment education. The research methods of this thesis include literature analysis method, survey research method, observation method, comparative research method, practice method, etc. According to the development and popularization of artificial intelligence in today's social life, it has led to the research of the combination of artificial intelligence and piano enlightenment education. Through the research on the teaching situation of piano accompaniment in the piano enlightenment, the contemporary traditional piano teaching is innovated, so that children can be more interested in learning piano and comprehensively cultivate children's comprehensive qualities. Experimental studies have found that after using the artificial intelligence-based piano automatic accompaniment system, students' interest in piano learning has increased significantly, as demonstrated by an increase in concentration time by about 22% in class and an increase in practice time after class by 42%.
External Force Damage Detection Method of Buried Cable Based on Optical Fiber Sensing Technology

The safe and stable operation of high-voltage buried cable plays an important role in the development of energy. The damage of cable is mainly caused by external force. Aiming at the method of online monitoring of high-voltage buried cable operation by distributed optical fiber sensor, the XLPE high-voltage buried cable model is established by using optical fiber sensor technology and finite element software ANSYS, and the simulation analysis of buried cable damaged by external force is carried out, The change of internal physical quantity can provide reference for distributed optical fiber sensor to monitor the operation status of high voltage buried cable online.
A Compact and Low-cost VR Tooth Drill Training System using Mobile HMD and Stylus Smartphone

Drilling teeth is a significant technique for dental learners. However, the existing VR tooth drill training simulators are physically large and costly, which cannot be used at home or classroom for a private study. This work presents a novel low-cost mobile VR dental simulator using off-the-shelf devices, including a mobile HMD and a stylus smartphone. In this system, a 3D-printed physical teeth prop is placed on an EMR stylus smartphone where its stylus tracks the tip position of a physical drill. Unlike existing solutions using haptic/force devices, our approach involving physical contact between the prop and drill tip enables the user's natural teeth hardness sensation. The use of smartphone stylus would enable significantly more accurate drill position sensing around the teeth than HMD's accompanying controllers. We also developed VR software to simulate tooth drilling on this setup. This demo will show how our new mobile simulator offers a realistic feeling of drilling teeth.
Leveraging Enterprise Knowledge Graphs for Efficient Bridging Between Business Data with Large-Scale Web Data

The diversification of the web into social media and the Web of Data means that companies need to collect the necessary data to make the best-informed market decisions. To deal with this, the new concept of Enterprise Knowledge Graphs (EKGs) is emerging as a backbone for federating valuable open information on the web together with the information contained in internal enterprise documents and databases. This paper examines the current challenges in this area, discusses the limitations of some existing integration systems, and addresses them by proposing a set of tools for virtually integrating enterprise data with social and linked data at scale. The proposed framework’s implementation is a configurable middleware and user-friendly keyword faceted search web interface that retrieves its input data from internal enterprise data combined with popular SPARQL endpoints and social network web APIs. We conducted an evaluation study to test our approach’s effectiveness using various metrics and compare it to state-of-the-art systems. The evaluation results show a competitive accuracy and usability of the proposed approach, facilitating the integration of data into a knowledge graph.
Lossless Image/Video Embedded Compression for Memory Bandwidth Saving of AI Applications

Artificial Intelligence (AI) has gradually become a part of our daily life. Nevertheless, it also causes considerable memory bandwidth and memory access power especially for image/video AI applications. In this paper, an efficient lossless embedded compression (EC) is proposed to save the memory bandwidth of an AI system. It consists of two core techniques: Hybrid Prediction and Partition-based Grouping. Hybrid Prediction can transform all pixels of an 8x8 block to efficient residuals. Partition-based Grouping can further classify them into smaller groups for better compression ratio. The experiment results show that this study presents better performance than the other sophisticated EC algorithms. This study achieves a better lossless compression ratio of 2.21, saving the memory bandwidth of an AI system by 54.8%. In addition, the visual quality of image/video can be fully preserved.
A Quantum Parallel Markov Chain Monte Carlo

We propose a novel hybrid quantum computing strategy for parallel MCMC algorithms that generate multiple proposals at each step. This strategy makes the rate-limiting step within parallel MCMC amenable to quantum parallelization by using the Gumbel-max trick to turn the generalized accept-reject step into a discrete optimization problem. When combined with new insights from the parallel MCMC literature, such an approach allows us to embed target density evaluations within a well-known extension of Grover's quantum search algorithm. Letting PdenotethenumberofproposalsinasingleMCMCiteration,thecombinedstrategyreducesthenumberoftargetevaluationsrequiredfrom풪(P)to풪P1/2. In the following, we review the rudiments of quantum computing, quantum search and the Gumbel-max trick in order to elucidate their combination for as wide a readership as possible.
Blockchain for Agri-Food Supply Chain and Logistics Management

Today, the globalization of the supply chain in the food industry has surged remarkably; hence, food safety and quality certification have become critical. Blockchain is recognized as a promising technology in the agri-foods industry where it can act as a systematic and robust mechanism for increasing the food traceability and provide a transparent and efficient way to assure quality, safety, and sustainability of agri-foods. By lowering the cost and increasing value, this digital technology has the potential to increase profitability of agricultural produce along the value chain. This chapter aims to investigate the potential utilization of blockchain technology in the agri-food industry, where it can be used to address issues of trust and transparency and to facilitate sharing of information sharing among stakeholders. The technology is still in a preliminary stage; thus, this chapter is written to examine its implication in the agri-food supply chain, existing initiatives, challenges, and potential.
SPIL: A Shape Preserving Method for Improving Lane Width Accuracy of HD Maps

The characteristic of high accuracy of HD maps is critical to ensure safety for autonomous driving. However, this accuracy evaluation on entire data is mostly infeasible by the measurements of absolute and relative accuracy due to the fact that the ground truth data is not easily obtained over a large geographical range. This paper proposes an alternate method using lane with accuracy for its expected or designed value is available in most occasions. Furthermore, we identify optimization opportunities and design a shape preserving algorithm SPIL for improving the accuracy of lane width through the adjustment of endpoints of assignable boundary line segments. Finally experiments are performed on a real typical urban road dataset, and experimental results demonstrate that SPIL algorithm achieves above fifty percent accuracy performance improvement.
Research and Design of Decimal Network DDNS

Internet domain name is consists of characters, numbers, or both of them. when a client access to a website, it first send a request to local domain name server (DNS), if there is no record, local DNS request to higher authorities, until the root name servers, and get the correct record after return to local, and the cache to the local server, the process logic is complex. It's expensive in time and space. Decimal Network digital domain name system(DDNS) can directly find the target network terminal through the routing rules, without the need for domain name resolution and other conversion process, and then quickly establish the connection, reducing the scale of routing table of each forwarding node in the network, thus saving huge time and space costs. This paper introduces the concept of digital domain name system, the structure of digital domain name system, the grammar and extension of digital domain name system, the mapping of digital domain name system and IP address, and the resource record in digital domain name system. It will show the characteristics and advantages of digital domain name in a more comprehensive and detailed way.
Information Visualization from the Perspective of Big Data Analysis and Fusion

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&amp;I), with the diversification of data sources and the growth of data volume. However, there are several defects with the research on information association of L&amp;I visualization network: the lack of optimization of network layout algorithms, and the absence of L&amp;I information fusion and comparison in multiple disciplines, in the big data environment. To overcome these defects, this paper explores the visualization of L&amp;I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&amp;I visualization network, and calculated the metrics for the construction of L&amp;I visualization topology map. Next, the importance of meta-paths of the L&amp;I visualization network was calculated. Finally, a complex big data L&amp;I visualization network was established, and the associations between information nodes were analyzed in details. Experimental results verify the effectiveness of the proposed algorithm
Natural walking speed prediction in Virtual Reality while using target selection-based locomotion

Travelling speed plays an essential role in the overall user experience while navigating inside a virtual environment. Researchers have used various travelling speed that matches the user speed profile in order to give a natural walking experience. However, predicting a user’s instantaneous walking speed can be challenging when there is no continuous input from the user. Target selection-based techniques are those where the user selects the target to reach there automatically. These techniques also lack naturalness due to their low interaction fidelity. In this work, we have proposed a mathematical model that can dynamically compute the instantaneous natural walking speed while moving from one point to another in a virtual environment. We formulated our model with the help of user studies.
On the Application of Computer Digital Teaching Resources in the Design of English Teaching Curriculum

With the development of information technology such as computer technology, network technology and multimedia technology and its application in education, digital teaching resources are increasingly being favored by people. Digital teaching resources are an important foundation for the implementation of education informatization, and the richness and effective application of digital teaching resources have increasingly attracted the attention of educational technology workers. This article aims to study the application of computer digital teaching resources in English curriculum design. Based on the analysis of the advantages and disadvantages of traditional English teaching, the advantages and problems of digital teaching, the existing problems and the improvement strategies of teachers using digital teaching resources, the questionnaire survey method is used. A survey of teachers in a middle school showed that only 17% of the teachers can complete their own courseware. Most teachers rely on the help of others or download their own multimedia courseware through the download of network resources. Among them, because the school does not provide a corresponding resource platform, some (8%) teachers even choose to pay for the relevant platform to download courseware to support their teaching.
DC-Deblur: A Dilated Convolutional Network for Single Image Deblurring

Single image deblurring is a significant and challenging task in image processing vision and machine learning. Convolutional Neural Network (CNN) based models for deblurring often have a complex structure and a considerable number of parameters compared with those for other image restoration tasks such as image denoising, dehazing and super-resolution. The main reason is the requirement of large reception fields, which are important to image deblurring due to possible large blur kernels. Dilated convolution is a useful way to increase reception field without adding extra parameters. In this paper, we propose a novel network by adopting a dilated convolution structure, and we further improve the training process by combining L1 loss, MS-SSIM loss and MSE loss. The proposed network is light and fast. Quantitative and qualitative experiments indicate that our method outperforms state-of-the-art models, in terms of performance and speed.
Seeds of SEED: Building and Verifying Foundationally Isolated Hardware Architectures

The increased sharing of hardware resources to meet the system performance of the semiconductor industry’s next generation applications is continuing to drive significant growth in new weaknesses and vulnerabilities. This paper reinforces the need for building foundationally isolated hardware that can be verified based on information flow guarantees. It gives a unique perspective on the problem, describes some important initiatives, and provides some guidance on what processes can be implemented to help combat it.
Research on Active Visual Tracking Based on Vestibulo-Ocular Reflex

Tracking moving objects is an important research direction in the field of robot vision. Tracking failure is still a challenging problem when the object tracking system is disturbed by the outside world or itself. In this paper, based on the theory of vestibulo-ocular reflex and its adaptive characteristics, fuzzy control is introduced to compensate the control parameters of the system, which leads to reduction of the external interference to the system and improvement of the tracking control system of the object. By imitating and learning the mechanism of human visual system, the performance of object tracking can be improved. In this paper, a "head-eye" structure is built. By experimenting with different interferences on the system, the sight is fixed on the target, which verifies the effectiveness of the algorithm.
Comparison of Tensile Properties of Carbon/Epoxy Composite Materials with Different Fiber Orientation Using Digital Image Correlation

Due to its remarkable qualities, carbon fiber epoxy composite sandwich panels are used in a variety of engineering applications. The goal of this research is to use tensile testing and a full-field non-contact 3D Digital Image Correlation (DIC) method to characterize carbon fiber reinforced composite sandwich panels with varied fiber orientations (0°/90° and ± 45°). The tested materials were composed of carbon fiber prepregs with epoxy resin systems and Aramid synthetic fiber. The properties of the materials were determined using full-field data derived from 3D DIC measurements and a set of experiments by according to ASTM standards. Values of maximum stress and strain at entire areas, break stress and strain, and toughness at entire areas and, modulus of elasticity of both structures were compared. The adherend's full-field, out-of-plane deformation, strain distribution, and strain evolution along the bond line were captured using a digital image correlation method, allowing the fracture mechanism to be visually defined. Since DIC produces the displacement field, the strain field must be deduced from it. The orientation of the fibers had a significant impact on the tensile properties of the tested materials. The results revealed that the specimen with 0°/90° fiber orientation had higher break stress and brittle fracture, whereas the specimen with ± 45° fiber orientation twisted in the fiber direction had higher elongation values while carrying the applied load. In order to complement previously obtained results, scanning electron microscopy (SEM) analysis of the fibers and core, as well as fracture surfaces was performed.