Visual Object Tracking and Servoing Control of a Nano-Scale Quadrotor:System,Algorithms,and Experiments

There are two main trends in the development of unmanned aerial vehicle(UAV)technologies:miniaturization and intellectualization,in which realizing object tracking capabilities for a nano-scale UAV is one of the most challenging problems.In this paper,we present a visual object tracking and servoing control system utilizing a tailor-made 38 g nano-scale quadrotor.A lightweight visual module is integrated to enable object tracking capabilities,and a micro positioning deck is mounted to provide accurate pose estimation.In order to be robust against object appearance variations,a novel object tracking algorithm,denoted by RMCTer,is proposed,which integrates a powerful short-term tracking module and an efficient long-term processing module.In particular,the long-term processing module can provide additional object information and modify the short-term tracking model in a timely manner.Furthermore,a positionbased visual servoing control method is proposed for the quadrotor,where an adaptive tracking controller is designed by leveraging backstepping and adaptive techniques.Stable and accurate object tracking is achieved even under disturbances.Experimental results are presented to demonstrate the high accuracy and stability of the whole tracking system.

Design of Intelligent Mosquito Nets Based on Deep Learning Algorithms

An intelligent mosquito net employing deep learning has been one of the hotspots in the field of Internet of Things as it can reduce significantly the spread of pathogens carried by mosquitoes,and help people live well in mosquito-infested areas.In this study,we propose an intelligent mosquito net that can produce and transmit data through the Internet of Medical Things.In our method,decision-making is controlled by a deep learning model,and the proposed method uses infrared sensors and an array of pressure sensors to collect data.Moreover the ZigBee protocol is used to transmit the pressure map which is formed by pressure sensors with the deep learning perception model,determining automatically the intention of the user to open or close the mosquito net.We used optical flow to extract pressure map features,and they were fed to a 3-dimensional convolutional neural network(3D-CNN)classification model subsequently.We achieved the expected results using a nested cross-validation method to evaluate our model.Deep learning has better adaptability than the traditional methods and also has better anti-interference by the different bodies of users.This research has the potential to be used in intelligent medical protection and large-scale sensor array perception of the environment.

Improving Language Translation Using the Hidden Markov Model

Translation software has become an important tool for communication between different languages.People’s requirements for translation are higher and higher,mainly reflected in people’s desire for barrier free cultural exchange.With a large corpus,the performance of statistical machine translation based on words and phrases is limited due to the small size of modeling units.Previous statistical methods rely primarily on the size of corpus and number of its statistical results to avoid ambiguity in translation,ignoring context.To support the ongoing improvement of translation methods built upon deep learning,we propose a translation algorithm based on the Hidden Markov Model to improve the use of context in the process of translation.During translation,our Hidden Markov Model prediction chain selects a number of phrases with the highest result probability to form a sentence.The collection of all of the generated sentences forms a topic sequence.Using probabilities and article sequences determined from the training set,our method again applies the Hidden Markov Model to form the final translation to improve the context relevance in the process of translation.This algorithm improves the accuracy of translation,avoids the combination of invalid words,and enhances the readability and meaning of the resulting translation.

Sensitive Information Protection Model Based on Bayesian Game

A game measurement model considering the attacker’s knowledge background is proposed based on the Bayesian game theory aiming at striking a balance between the protection of sensitive information and the quality of service.We quantified the sensitive level of information according to the user’s personalized sensitive information protection needs.Based on the probability distribution of sensitive level and attacker’s knowledge background type,the strategy combination of service provider and attacker was analyzed,and a game-based sensitive information protection model was constructed.Through the combination of strategies under Bayesian equilibrium,the information entropy was used to measure the leakage of sensitive information.Furthermore,in the paper the influence of the sensitive level of information and the attacker’s knowledge background on the strategy of both sides of the game was considered comprehensively.Further on,the leakage of the user’s sensitive information was measured.Finally,the feasibility of the model was described by experiments.

A Survey on Cryptographic Security and Information Hiding Technology for Cloud or Fog-Based IoT System

Internet of Things(IoT)is an emerging paradigm involving intelligent sensor networks that incorporates embedded technology for collecting data,communicating with external environments.Recently,cloud computing together with fog computing has become an important research area of the Internet of Things because of big data processing capabilities.It is a promising technology that utilizes cloud or fog computing/architecture to improve sensor computing,storage,and communication capabilities.However,recently it has been shown that this computing/architecture may be vulnerable to various attacks because of the openness nature of the wireless network.Therefore,it becomes more and more important to ensure the security and privacy in these scenes.Encryption security and information hiding technology can provide authentication,confidentiality,integrity,anti-eavesdropping,availability and so on for these computing models or architectures.The purpose of this review is to look for original articles with novel ideas and solutions to address encryption security and information hiding technologies in cloud or fog-based Internet of Things systems.We hope this review will provide an opportunity for scientists,researchers and industry engineers to study original manuscripts and know developments in all aspects of security,privacy,trust,and covert communication issues in cloud or fog computing/architecture Internet of Things systems.

Security Analysis for a VANET Privacy Protection Scheme

Vehicular ad hoc network(VANET)is a self-organizing wireless sensor network model,which is extensively used in the existing traffic.Due to the openness of wireless channel and the sensitivity of traffic information,data transmission process in VANET is vulnerable to leakage and attack.Authentication of vehicle identitywhile protecting vehicle privacy information is an advantageous way to improve the security of VANET.We propose a scheme based on fair blind signature and secret sharing algorithm.In this paper,we prove that the scheme is feasible through security analysis.

石家庄新型冠状病毒肺炎疫情新型冠状病毒分子流行病学特征

目的从分子层面分析石家庄新型冠状病毒的流行病学特征,揭示此次传播链的源头,为新型冠状病毒肺炎疫情防控提供科学依据。方法收集2021年1月2—8日来自石家庄市第五医院170例新型冠状病毒感染者共计404份新型冠状病毒核酸阳性样本,采用多重聚合酶链反应靶向测序技术对样本进行深度测序获得病毒一致性序列。采用PANGOLIN分类系统对170个毒株序列进行分析,采用T-test对数据进行统计学分析。结果在404份新型冠状病毒核酸阳性样本中,356份获得病毒的全长基因组序列(>95%,100×测序深度),剔除重复取样,得到170株全基因组序列,所有样本均属于B.1.1分支。病毒突变数18~22个,大部分突变不改变氨基酸信息。根据基因组突变个数和种类,所有毒株分为48个亚型,其中2个毒株占主导(分别为66株和31株)。结论本研究中所有新型冠状病毒肺炎患者来自单一源头的境外输入性病例,病毒在社区隐匿传播了一段时间,并且在传播的过程中发生了变异。

One-step method to enhance biotribological properties and biocompatibility of DLC coating by ion beam irradiation

A one-step method was developed to create a highly biocompatible micropatterned surface on a diamond-like carbon(DLC)through irradiation with a nitrogen ion beam and thus enhance the biocompatibility of osseointegrated surfaces and biotribological performance of articular surfaces.The biocompatibility and biotribological mechanisms were analyzed in terms of the structure and morphology of DLC.It was demonstrated that a layer enriched in sp^(3) C-N bonds was formed on the surface of the DLC after nitrogen ion beam irradiation.Moreover,with an increase in the radiation dose,the content of sp^(3) C-N on the DLC surface increased significantly,and the biocompatibility was positively correlated with it.The adhesion of the MC3T3 osteoblasts increased significantly from 32%to 86%under an irradiation dose of 8×10^(15) ions/cm^(2).In contrast,the micropattern had a significant negative effect on the adhesion of the osteoblasts as it physically hindered cell expansion and extension.The micropattern with a depth of 37 nm exhibited good friction properties,and the coefficient of friction was reduced by 21%at relatively high speeds.

Influence of modified light dispersion theory on fermion tunneling radiation in the Einstein–Maxwell–dilaton–axion black hole

Based on a light dispersion relationship derived from string theory and quantum gravitational theory,we make an accurate modification to the quantum tunneling radiation rate and black hole temperature at an event horizon in a stationary axial-symmetric Einstein–Maxwell–dilaton–axion black hole.We also analyze our new results and carry out some significant discussions.This work enriches the research content and methods of the frontiers of black hole physics.

Dual in-situ observation of tribochemical and morphological evolution of single-layer WS_(2)and multi-layer WS_(2)/C coatings

The outstanding tribological performance of transition metal dichalcogenides(TMDs)is attributed to their unique sandwich microstructure and low interlayer shear stress.This advantageous structure allows TMDs to demonstrate exceptional friction reduction properties.Furthermore,the incorporation of TMDs and amorphous carbon(a-C)in multi-layer structures shows excellent potential for further enhancing tribological and anti-oxidation properties.Amorphous carbon,known for its high ductility,chemical inertness,and excellent wear resistance,significantly contributes to the overall performance of these multi-layer coatings.To gain an in-depth understanding of the tribological mechanism and evolution of TMDs’multi-layer coatings,a dual in-situ analysis was carried out using a tribometer equipped with a 3D laser microscope and a Raman spectrometer.This innovative approach allowed for a comprehensive evolution of the tribological,topographical,and tribochemical characteristics of both single-layer WS_(2)and multi-layer WS_(2)/C coatings in real time.The findings from the dual in-situ tribotest revealed distinct failure characteristics between the single-layer WS_(2)coating and the multi-layer WS_(2)/C coating.The single-layer WS_(2)coating predominantly experienced failure due to mechanical removal,whereas a combination of mechanical removal and tribochemistry primarily influenced the failure of the multi-layer WS_(2)/C coating.The tribological evolution process of these two coatings can be classified into four stages on the basis of their tribological behavior:the running-in stage,stable friction stage,re-deposition stage,and lubrication failure stage.Each stage represents a distinct phase in the tribological behavior of the coatings and contributes to our understanding of their behavior during sliding.