APPLICATION OF WEARABLE CAMERAS IN STUDYING INDIVIDUAL BEHAVIORS IN BUILT ENVIRONMENTS

With the advent of the Fourth Industrial Revolution, people have begun to explore the potential for new technologies and new devices in studying the relationship between human behavior and urban design. The emergence of wearable cameras offers more possibilities for monitoring individual behavior in built environments as a kind of “lifelog.” This article explores the applications of wearable cameras in studying the relationship between individual behavior and built environments. Using manual image identification, image recognition with Computer Vision Application Programming Interface (API), and color calculation in Matlab, this study analyzed 8,598 photos recording the volunteer’s behaviors and activities during a week. Based on high-accuracy manual image identification results, the research analyzed the volunteer’s behavior, time use, movement path, and experiencing scenes. The study showed that the big data base of images collected by the wearable cameras contained rich individual activities and spatiotemporal information that could be used to effectively describe the individual behavior in space and further contribute to the study of the relationship between individual behaviors and built environments.     

Adaptive transfer learning framework for dense prediction of human activity recognition

Human activity recognition (HAR) for dense prediction is proven to be of good performance, but it relies on labeling every point in time series with the high cost. In addition, the performance of HAR model will show significant degradation when tested on the sensor data with different distribution from the training data, where the training data and the test data are usually collected from different sensor locations or sensor users. Therefore, the adaptive transfer learning framework for dense prediction of HAR is introduced to implement cross-domain transfer, where the proposed multi-level unsupervised domain adaptation (MLUDA) approach combines the global domain adaptation and the specific task adaptation to adapt the source and target domain in multiple levels. The multi-connected global domain adaptation architecture is proposed for the first time, which can adapt the output layer of the encoder and the decoder in dense prediction model. After this, the specific task adaptation is proposed to ensure alignment of each class centroid in source domain and target domain by introducing the cosine distance loss and the moving average method. Experiments on three public human activity recognition datasets demonstrate that the proposed MLUDA improves the prediction accuracy of target data by 20% compared to the source domain pre-trained model and it is more effective than the other three deep transfer learning methods with an improvement of 10% to 18% in accuracy.     

Highly active OMS-2 for catalytic ozone decomposition under humid conditions

Four kinds of cryptomelane-type octahedral molecular sieve(OMS)-2-X(the X represents the molar ratio of KMnO_4/MnAc_2) were prepared as catalytic materials for ozone decomposition through a one-step hydrothermal reaction of KMnO_4 and MnAc_2, by changing their molar ratios. These samples were characterized by N_2 adsorption–desorption, X-ray di raction(XRD), transmission electron microscopy(TEM), scanning electron microscopy(SEM), temperature programmed reduction by H_2(H_2-TPR) and X-ray photoelectron spectroscopy(XPS). Among them, the OMS-2-0.7 sample showed the best O_3 conversion of 92% under high relative humidity(RH) of 90% and gas hourly space velocity of 585,000 h-1. This was accordingly thought as a possible way for purifying ozone-containing waste gases under high RH atmospheres. The e ciency of ozone decomposition of the prepared OMS-2-X sample was found to be related to specific surface area, particle size, surface oxygen vacancies, and Mn~(3+) cation amounts. The one-step hydrothermal synthesis was shown to be a simple method to prepare the considerably active OMS-2 solids for ozone decomposition.     

Microwave-assisted catalyst-free hydrolysis of fibrous cellulose for deriving sugars and biochemicals

Microwave (MW) assisted catalyst-free hydrolysis of fibrous cellulose (FC, cellulolysis) at 200°C promoted a cellulose conversion of ca. 37.2% and quantitative production of valuable C5/C6 sugars (e.g., glucose) and the according platform biochemicals (e.g., 5-hydroxymethylfurfural), corresponding to an overall selectivity of 96.5%. Conversely, conventional hydrothermal cellulolysis under similar conditions was not effective, even after 24 h, carbonising the FC. Based on the systematic study of MW-assisted cellulolysis, the specific interaction between water molecules and macroscopic FC under the MW irradiation was proposed, accounting for the interpretation of the experimental observation. The kinetic energy of water molecules under the MW irradiation facilitated the C–C (in the non-hindered surface –CH₂OH groups) and C–O–C bond breaking (inside the cellulose cavities) in FC, producing primary cellulolysis products of xylose, glucose and cellobiose.     

Understanding enhancing mechanism of Pr6O11 and Pr(OH)3 in methanol electrooxidation

The presence of oxygen vacancies and hydroxyl groups are both favorable for the methanol electrooxidation on Pt-based catalysts.Understanding and differentiating the enhancing mechanism between oxygen vacancies and hydroxyl groups for high activity of Pt catalysts in methanol oxidation reaction(MOR)is essential but still challenging.Herein,we developed two kinds of co-catalyst for Pt/CNTs,Pr₆O₁₁is rich in oxygen vacancies but contains substantially no hydroxyl groups,while Pr(OH)₃ possesses abundant hydroxyl groups without oxygen vacancies.After a seque nce of designed experiments,it can be found that both oxygen vacancies and hydroxyl groups can improve the performance of Pt/CNTs electrocatalysts,but the enhancing mechanism and improving degree of oxygen vacancies and hydroxyl groups for the MOR are different.Since the oxygen vacancies are more conducive to increasing the intrinsic activity of the Pt catalyst,and the hydroxyl groups play a decisive role in dehydrogenation and deproto nation of methanol,the co-catalysts with both oxygen vacancies and hydroxyl groups mixed with Pt/CNTs have higher catalytic performance.Therefore,hydroxyl-rich Pr₆O₁₁·xH₂O was prepared and used as MOR electrocatalyst after mixed with Pt/CNTs.Benefiting from the synergistic effect of oxygen vacancies and hydroxyl groups,the Pr₆O₁₁·xH₂O/Pt/CNTs shows a high peak current density of 741 mA/mg,which is three times higher than that of Pt/CNTs.These new discoveries serve as a promising strategy for the rational design of MOR catalysts with low cost and high activity.     

Hydrophobic organic coating based water--solid TENG for water-flow energy collection and self-powered cathodic protection

Water–solid triboelectric nanogenerators (TENGs), as new energy collection devices, have attracted increasing attention in ocean energy harvesting and self-powered sensing. Polyacrylic acid (PAA) coating, usually used on the surface of marine equipment, has the property of anti-aging and anti-wear but limits triboelectrical output when used with TENGs. In this paper, polyacrylic acid coating was modified with fluorinated polyacrylate resin (F-PAA) to increase its triboelectrical output, by 6 times, and also to increase its anti-corrosion property. In addition, the corrosion resistance property can be further enhanced by cathodic protection using the electrical output generated by the water-flow triboelectrical energy transfer process. Given their easy fabrication, water-flow energy harvesting, and corrosion resistance, PAA/F-PAA coating-based TENGs have promising applications in river and ocean energy collection and corrosion protection.     

SmartPipe: Towards Interoperability of Industrial Applications via Computational Reflection

With the advancement of new information technologies,a revolution is being taken place to bring the industry into a new era of intelligent manufacturing.One of the key requirements of intelligent manufacturing is the interoperability of industrial applications.However,it is challenging to realize the interoperability for legacy industrial applications due to 1)the deficient semantic information of data transmitted over heterogeneous communication protocols,2)the difficulty to understand the complex process of business logic with no source code,and 3)the high cost and potential risk of reengineering the applications.To address the issues,in this paper,we propose an approach named SmartPipe to exposing existing functionalities of an industrial application as APIs without source code while simultaneously allowing the application to remain unchanged.We design a behavioral runtime model(BRM)as the self-representation of the industrial applications,based on which a computational reflection framework is designed to flexibly construct the model and generate APIs that encapsulate specific functionalities.We validate SmartPipe on a real industrial application that controls the spin-draw winding machine.Results show that our approach is effective and more suitable for industrial scenes compared with traditional approaches.     

Synthesis of covalently bonded reduced graphene oxide-Fe3O4 nanocomposites for efficient electromagnetic wave absorption

High-performance electromagnetic (EM) wave absorbers,covalently bonded reduced graphene oxide-Fe3O4 nanocomposites (rGO-Fe3O4),are synthesized via hydrothermal reaction,amidation reaction and reduction process.The microstructure,surface element composition and morphology of rGO-Fe3O4 nanocomposites are characterized and corresponding EM wave absorption properties are analyzed in great detail.It demonstrates that Fe3O4 nanoparticles are successfully covalently grafted onto graphene by amide bonds.When the mass ratio of rGO and Fe3O4 is 2∶1 (sample S2),the absorber exhibits the excellent EM wave absorption performance that the maximum reflection loss (RL) reaches up to-48.6 dB at 14.4 GHz,while the effective absorption bandwidth (RL＜-10 dB) is 6.32 GHz (11.68-18.0 GHz) with a matching thickness of 2.1 mm.Furthermore,radar cross section (RCS) simulation calculation is also adopted to evaluate the ability of absorbers to scatter EM waves,which proves again that the absorption performance of absorber S2 is optimal.The outstanding EM wave absorption performance is attributed to the synergistic effect between dielectric and magnetic loss,good attenuation ability and excellent impedance matching.Moreover,covalent bonds considered to be carrier channels can facilitate electron migration,adjust EM parameters and then enhance EM wave absorption performance.This work provides a possible method for preparing efficient EM wave absorbers.     

Composition optimization of high-strength Mg-Gd-Y-Zr alloys based on the structural unit of Mg-Gd solid solution

Mg-Gd-Y-Zr alloys with high strength fall within narrow composition range.The present paper explains their composition rule by establishing the cluster-plus-glue-atom unit ofGd-containing Mg solid solution with the aid of Mg matrix and MgsGd precipitate phase.First,based on the structural homologue between Gd-containing Mg solid solution and MgsGd precipitate phase and in combination with our previously established method for calculating the glue atoms,[Gd-Mg12]Mgs is obtained as the chemical unit of Gd-containing Mg solid solution.Then,seven compositions are designed using different combinations of this unit and that of pure Mg[Mg-Mg12]Mg3.After a systematic experimental investigation on the microstructure and mechanical property evolutions as a function of the unit proportions,it is revealed that the Mg-10.1Gd-3.3Y-0.9Zr alloy,being issued from equi-proportion mixing of the two units,shows the strongest tendency of precipitation and reaches the highest strength of 374 MPa after aging.The composition and strength of this alloy are quite close to GW103K which is well recognized for its general mechanical performance in Mg-Gd-Y-Zr system.