Data Driven Vibration Control:A Review

With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic communities.Input shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC methods.It convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration separately.Based on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of DDVC.By doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue.

Biomedical applications of Jones-matrix tomography to polycrystalline films of biological fuids

Algorithms for reconstruction of linear and circular birefringence-dichroism of optically thin anisotropic biological layers are presented.The technique of Jones matrix tomography of poly-crystalline films of biological fuids of various human organs has been developed and experimentally tested.The coordinate distributions of phase and amplitude anisotropy of bile films and synovial fuid taken from the knee joint are determined and statistically analyzed.Criteria(statistical moments of 3rd and 4th orders)of differential diagnostics of early stages of cholelithiasis and septic arthritis of the knee joint with excellent balanced accuracy were determined.Data on the diagnostic fficiency of the Jones matrix tomography method for polyerystalline plasma(liver disease),urine(albuminuria)and cytological smears(cervical cancer)are presented.

Research and development in agricultural robotics:A perspective of digital farming

Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievements in agricultural robotics,specifically those that are used for autonomous weed control,field scouting,and harvesting.Object identification,task planning algorithms,digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming.The concepts of multi-robots,human-robot collaboration,and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming.It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information.For the case of robotic harvesting,an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators.While robots are becoming the inseparable parts of the modern farms,our conclusion is that it is not realistic to expect an entirely automated farming system in the future.

Simulation software and virtual environments for acceleration of agricultural robotics:Features highlights and performance comparison

Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplinary collaborations between different research groups for effective task delivery in unstructured crops and plants environments.With the exception of milking robots,the extensive research works that have been carried out in the past two decades for adaptation of robotics in agriculture have not yielded a commercial product to date.To accelerate this pace,simulation approach and evaluation methods in virtual environments can provide an affordable and reliable framework for experimenting with different sensing and acting mechanisms in order to verify the performance functionality of the robot in dynamic scenarios.This paper reviews several professional simulators and custom-built virtual environments that have been used for agricultural robotic applications.The key features and performance efficiency of three selected simulators were also compared.A simulation case study was demonstrated to highlight some of the powerful functionalities of the Virtual Robot Experimentation Platform.Details of the objects and scenes were presented as the proof-of-concept for using a completely simulated robotic platform and sensing systems in a virtual citrus orchard.It was shown that the simulated workspace can provide a configurable and modular prototype robotic system that is capable of adapting to several field conditions and tasks through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment.This review suggests that an open-source software platform for agricultural robotics will significantly accelerate effective collaborations between different research groups for sharing existing workspaces,algorithms,and reusing the materials.

An Industrial Internet Platform for Massive Pig Farming (IIP4MPF)

Pig farming is becoming a key industry of China’s rural economy in recent years. The current pig farming is still relatively manual, lack of latest Information and Communication Technology (ICT) and scientific management methods. This paper proposes an industrial internet platform for massive pig farming, namely, IIP4MPF, which aims to leverage intelligent pig breeding, production rate and labor productivity with the use of artificial intelligence, the Internet of Things, and big data intelligence. We conducted requirement analysis for IIP4MPF using software engineering methods, designed the IIP4MPF system for an integrated solution to digital, interconnected, intelligent pig farming. The practice demonstrates that the IIP4MPF platform significantly improves pig farming industry in pig breeding and productivity.

Multi-layered tissue head phantoms for noninvasive optical diagnostics

Extensive research in the area of optical sensing for medical diagnostics requires development of tissue phantoms with opt ical properties similar to those of living human tissues.Development and improvement of in vivo optical measurement systems requires the 1use of stable tissue phantoms with known characteristics,which are mainly used for calibration of such systems and testing their performance over time.Optical and mechanical properties of phantoms depend on their purpose.Nevertheless,they must accurately simulate specific tssues they are supposed to mimic.Many tsues and organs including head possess a multi-layered structure,with specifie optical properties of each layer.However,such a structure is not always addressed in the present-day phantoms.In this paper,we focus on the development of a plain-parallel multi-layered phantom with optical properties(reduced scattering oofficientμ'and absorption cofficientμa)corresponding to the human head layers,such as skin,skul,and gray and white matter of the brain tissue.The phantom is intended for use in noninvasive diffuse near-infrared spectroscopy(NIRS)of humnan brain.Optical parameters of the fabricated phantoms are reconstructed using spectrophotometry and inverse adding-doubling calculation method.The results show that polyinyl chloride plastisol(PVCP)and zinc oxide(ZnO)nanoparticles are suitable materials for fabrication of tissue mimicking phantoms with controlled scattering properties.Good matching was found between optical properties of phantoms and the corresponding values found in the literature.

5.9 GHz Vehicular Channels Comparisons Between Two Traffic Status for Dense Urban Area

This study focused on differences in vehicle-to-vehicle radio channel character- istics in the same region but different traffic density and speeds at 5.9 GHz （congestion and non-congestion）. The continuous measurement campaign was conducted on a city expressway through the complex dense urban area in Wu- hart, China. Small-scale channel characteris- tics including power delay profile, amplitude fading distribution, K-factor, delay spread and Doppler shift were obtained, respectively. Spe- cifically, the cumulative distribution function of root mean square delay spreads and root mean square Doppler spreads in the non-con- gested scenario and congested scenario were all fitted well with Lognormal distribution. We also found out that different intensity of traffic and speed of vehicles have little effect on root mean square delay spreads, but have a big im- pact on root mean square Doppler spreads and level crossing rate. According to estimation outcomes, the V2V channel characteristics for urban areas in Chinese big city were differ- ent from the previous measured results under similar scenarios in Europe. Delay spread and level crossing rate in this study can provide significant references to design the wireless communication system for vehicle-to-vehicle channel.

Guest editorial:Special issue on data intelligence for IoT

The Internet of Things(IoT)is increasingly deployed to enable smart applications.Various types of data are accumulated continuously during the running of these applications.Managing and using these IoT data to derive intelligence for making the smart world reality is attracting both industrial and academic efforts.Though quite some progress has been made in this area,there is still a need for high data intelligence in IoT applications.

Advances in greenhouse automation and controlled environment agriculture:A transition to plant factories and urban agriculture

Greenhouse cultivation has evolved from simple covered rows of open-fields crops to highly sophisticated controlled environment agriculture(CEA)facilities that projected the image of plant factories for urban agriculture.The advances and improvements in CEA have promoted the scientific solutions for the efficient production of plants in populated cities and multi-story buildings.Successful deployment of CEA for urban agriculture requires many components and subsystems,as well as the understanding of the external influencing factors that should be systematically considered and integrated.This review is an attempt to highlight some of the most recent advances in greenhouse technology and CEA in order to raise the awareness for technology transfer and adaptation,which is necessary for a successful transition to urban agriculture.This study reviewed several aspects of a high-tech CEA system including improvements in the frame and covering materials,environment perception and data sharing,and advanced microclimate control and energy optimization models.This research highlighted urban agriculture and its derivatives,including vertical farming,rooftop greenhouses and plant factories which are the extensions of CEA and have emerged as a response to the growing population,environmental degradation,and urbanization that are threatening food security.Finally,several opportunities and challenges have been identified in implementing the integrated CEA and vertical farming for urban agriculture.

Mathematical models for assessing vaccination scenarios in several provinces in Indonesia

To mitigate casualties from the COVID-19 outbreak,this study aims at assessing the optimal vaccination scenarios,considering several existing healthcare conditions and assumptions,by developing SIQRD(Susceptible-Infected-Quarantine-Recovery-Death)models for Jakarta,West Java,and Banten,in Indonesia.The models include an age-structured dynamic transmission model that naturally allows for different treatments among different age groups of the population.The simulation results show that the timing and period of the vaccination should be well planned and prioritizing particular age groups will give a significant impact on the total number of casualties.

LJItrasensitive H2S gas sensors based on p-type WS2 hybrid materials

Owing to their higher intrinsic electrical conductivity and chemical stability with respect to their oxide counterparts, nanostructured metal sulfides are expected to revive materials for resistive chemical sensor applications. Herein, we explore the gas sensing behavior of WS2 nanowire-nanoflake hybrid materials and demonstrate their excellent sensitivity （0.043 ppm-1） as well as high selectivity towards H2S relative to CO, NH~, H2, and NO （with corresponding sensitivities of 0.002, 0.0074, 0.0002, and 0.0046 pprn-1, respectively）. Gas response measurements, complemented with the results of X-ray photoelectron spectroscopy analysis and first-principles calculations based on density functional theory, suggest that the intrinsic electronic properties of pristine WS2 alone are not sufficient to explain the observed high sensitivity towards H2S. A major role in this behavior is also played by O doping in the S sites of the WS2 lattice. The results of the present study open up new avenues for the use of transition metal disulfide nanomaterials as effective alternatives to metal oxides in future applications for industrial process control, security, and health and environmental safety.