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In order to solve the accuracy problem of the conventional microgripper causing by the external vibration for the connecting power supply with wires, a novel opto-electrostatic repulsive actuation mechanism and mode for driving microgripper is proposed, which can achieve remotely non-contact control and wireless energy transfer. Firstly, the principle of opto-electrostatic repulsive mechanism is presented and introduced, the opto-electrostatic repulsive force activated by PLZT ceramic is derived. To obtain the maximum tip displacement of microgripper, the opto-electrostatic repulsive actuated unit is optimized. Based on which the parameters of the proposed light operated microgripper are determined, and then the optimized unit is simulated by COMSOL software.

In view of the dispersed distribution of distributed photovoltaic power generation system and the difficulty of centralized meter reading in traditional ways, we use infrared communication, 4G wireless communication and other Internet of things technology, and Netty network communication library as remote communication tools, and design a custom communication protocol that can be used for master station system and meter reading module. Combined with meter reading module and handheld debugger, remote installation and automatic reading of photovoltaic energy meter data can be realized to avoid the trouble of manual copying or building wired communication network in traditional meter reading mode, improve the management level and reduce operation cost of distributed photovoltaic power station. The results show that the photovoltaic infrared meter reading system based on Internet of things is easy to install and stable performance. A large number of energy meters can be read at the same time.

The propagation of electromagnetic waves in evaporation duct follows Maxwell's law. Theoretically, the electromagnetic wave propagation process can be solved in case of knowing electromagnetic wave source characteristics, propagation medium characteristics and boundary conditions. However, the calculation of evaporation duct profiles and Maxwell's equations is complex and slow. In most cases, it can only be solved by using numerical methods. A simple, fast and approximately accurate scheme of path loss calculation is needed to overcome this difficulty. Therefore, deep neural network is used to estimate the path loss of electromagnetic wave propagation in evaporation duct in this paper.

In this paper, the influence of antenna height on microwave propagation in evaporation duct is investigated, both from numerical simulation and experimental observation. Comparisons of microwave propagation with different antenna heights under different conditions, such as different evaporation duct heights (EDHs) and signal frequencies, are presented. At distinct conditions, the corresponding optimal antenna heights are not the same. When the EDH is low, microwaves cannot be trapped and propagate in the evaporation duct layer. The higher the antenna height, the smaller the path loss. For the case when the evaporation duct can trap microwaves well, a low antenna is more suitable for the propagation of microwaves in the evaporation duct layer. However, the optimal antenna height varies for different EDHs and frequencies. The influence of antenna height on microwave propagation was observed in the experiment held in the northern part of the South China Sea in December 2013. The experiment result shows that under good evaporation duct conditions, the path loss at antenna height 3 m are 10 dB lower in average than that at 6 m.

The Cuckoo Search Algorithm (CS) is a bio-inspired new swarm intelligent optimization algorithm. Aiming at the slow convergence speed and weak search ability of CS algorithm in the late stage of search, an improved cuckoo algorithm (APCS) for detecting the adaptive adjustment of probability parameters is proposed. Firstly, the state discriminant parameter P s is calculated by Pareto optimal solution and then the balance parameter P eb is calculated by exploring-exploiting the equilibrium state, finally the adaptive dynamic adjustment of the found probability P eb of the bird egg is realized. The performance of the two algorithms is analyzed by 10 benchmark functions in 10 and 30 dimensions. The results show that the convergence speed, optimization ability, stability and computation time of APCS algorithm are better than CS algorithm.

To evaluate and diagnose leaner's learning progress, assessment is important for teachers in their teaching. Recently, with widespread of information and technology developed, many teachers have strong intention to adopt computerized tests. In addition, in the test, a diagnostic information with remedial learning is also an essential mechanism in self-directed learning for learners. However, making computerized tests with diagnostic messages is a tedious and complex task for most teachers who have no sophisticated programming skills. This study aims to develop a construction tool for teachers to create their own web- based diagnostic multimedia tests. Once the test created with related concept structures followed by remedial resources, this tool automatically constructs a web-based module for testing. After an expert evaluation carried out later, this tool receives positive feedback from expected users in education.

This paper presents an inkjet printing and filling process to produce $250\mu \mathrm{m}$ deep Ag-based fully filled through silicon vias with the aspect ratio of via depth vs. diameter up to 5. With the optimization of the printing pattern, humidity control, and silver mirror reaction, the Ag TSV subjected to 400°C thermal anneal for 60 mins can exhibit a resistivity of $26\mu\Omega\bullet \mathrm{cm}$ , the lowest resistivity and highest AR ever reported. Process simplicity and no need of metal liners make the technique with great potential for 3D microsystem integration.

Recently, all the electrical device frequency becomes higher and higher in order to enable electronic products have better performance and become much faster such as CPUs, cellphones, smart watches $\dots$ etc. Almost all the products you can see around yourself contains electronic circuit. With generations of Internet of things(IOT) coming, electronic products will everywhere in our lives in the near future.It also means that the circuit in integrated circuit (IC) and printed circuit board (PCB) must become shorter and shorter. With the size of PCB and IC shrinking, measurement in near field system becomes more and more difficult due to the limitation of the magnetic probe resolution.Thus, we reduce the width of the probe and build the model in ANSYS HFSS to see the resolution. (Fig.1. is our simulation structure in ANSYS HFSS) However, according to Faraday’s law, with the area of sensitive loop reducing, the induced electromotive force must be decreased. In a near field measurement system, we usually connect a low noise amplifier (LNA) on the top of the magnetic probe, and the inductance signal of the probe must to be large enough (At least greater than the dynamic range of the LNA) for a LNA to be recognized. All in all, we have to find the balance between resolution and inductance.

With the rapid application of social media, hot topic detection is an essential issue on mining content and public opinion analysis. As some traditional topic models, such as probability latent semantic analysis (PLSA), latent dirichlet allocation (LDA), cannot mine the short texts effectively for the serious sparse problems, this paper proposes a micro-blog topic detection model based on the semantic dependency parsing. The proposed model parses micro-blog by semantic dependency parsing and analyzes the effect of semantic dependency relationships on topic detection. Furthermore, according to the previous works on analyzing and removing the irrelevant semantic dependency relationships for topic detection, this model makes use of the advantages of the BTM, and then combines the traditional BTM with semantic dependency relationships. The evaluation shows that the proposed model can obtain a more coherent topic in topic detection.

This study reported an integrated microfluidic system for automating multiplex detection of allergy microarrays. Allergy has become a common disease worldwide. However, detection for allergy on microarrays requires tedious manual operation, well-trained technicians and a relatively labor-intensive process. In this study, an integrated microfluidic system combining the microfluidic techniques and the microarray chips was developed to advance the detection of allergy. Experimental results showed that it could be realized within a shorter period of time (from 2 hours to 70 min) while implemented on integrated microfluidic system. The development of the automatic microsystem could increase the applicability of allergy microarray chips.

Enzyme-linked immunosorbent assay (ELISA) is a popular detection method which employs two antibodies. In this study, we presented a new method which used electromagnetically-driven microdevices to form an integrated microfluidic chip for automating ELISA-like dual aptamer assay. First, an electromagnetic micropump was designed and fabricated by using composite membranes. It was formed by mixing iron particles with polydimethylsiloxane (PDMS) which could be deflected when a magnetic field was applied. The characterization of membrane deflections with different applied magnetic fields was measured. The electromagnets were made with cores surrounding 800 turns of brass coils which could produce a strong magnetic field to actuate the microdevice. The flow rate was measured to be 73.6 µl/min with an applied voltage of 8.0 V. Furthermore, we presented a design of an integrated microfluidic chip for automating dual aptamer assay. The chip integrated magnetically-driven micro-devices such as micropumps, microvalves and micromixers to automate the assay. It is promising for point-of-care applications.

Underwater sensors will diverge from the initial position because of the ocean current when the underwater sensors are deployed in the deep ocean. Assuming that the xy-plane coincides with the sea surface, a local Cartesian x-y coordinates system is set up in such a way that, when the sensors and sources are projected onto the local xy-plane, its origin coincides with the initial point of the sensors and the x-axis is parallel with east direction and positive y-axis is parallel with north direction. The depth of sensors can be obtained from press transducers, and the accurate position of the sources can be obtained from the GPS receiver attached to the ship and depths of the sources are preset. When the minimum time arrivals are snapped to a certain name, multipath time delay arrivals relative to the minimum time arrivals can be extracted from the measured signal and results of standard ray approach. The horizontal distance between the sensors and the sources can be estimated by matched time delays measured with ones calculated by BELLHOP model. Then the position of underwater sensors can be estimated by three points distance intersection method. Simulations and experiments are performed to demonstrate the feasibility of the method in the deep ocean. With the proposed method, the position of the underwater sensors can be localized in the deep ocean successfully.

The Fresnel lens arrays, which can be used as the alternative of microlens arrays for integral imaging, were designed and fabricated. Their imaging properties for different colors were investigated, and a design based on the Fresnel lens arrays with chromatic dispersion is proposed.

The coupling modes and their field intensities of remote grating plasmonic nanostructures with periodic and quasi-periodic arrangements are studied numerically by comparing their transmissions, reflections, and extinctions.

Different structures of the silver nanoparticles embedded in the silica layer atop the silicon substrate are simulated by the finite-difference time-domain method. The effects of nanoparticle size, period, and the silica layer thickness are studied and the comparisons of the structures with and without the silica layers are given. It is found that the optical transmissions are enhanced for the cases with the silver nanoparticles embedded in the silica layer.

The quasi-periodic remote-grating plasmonic nanostructures are studied and compared with the periodic structures. The multiple coupling wavelengths can be obtained by combination of different grating periods and their physical mechanisms are described in this paper.

With the rapid development of the Internet of things, in order to ensure the safety of special cargo transportation and solve vehicle trajectory tracking problem, the paper designs and develops the intelligent terminal for special cargo monitoring system. The terminal consists of two parts—the acquisition node (Node) and the aggregation node (Sink), a combination of digital high-precision sensor technology, low-power short-range wireless communications technology, GPS technology, GPRS technology and low-power embedded system design and management technology. The acquisition node can detect the temperature, humidity and other environmental information of goods during the transporting process. The aggregation node is responsible for the collection of all the information from each acquisition nodes and can obtain the GPS location information, meanwhile it can use GPRS and remote monitoring center for information exchange. Testing results indicate that the terminal is running good. It is small in size, reliable to transmit, widely used and low-power, with satisfying installation flexibility, scalability, and anti-interference ability.

We study the light transmissions for periodic and non-periodic arrangements of the nanoparticle distributions atop the silicon substrate by finite-difference time-domain method. Our results give the guidelines of the nanoparticle distribution for better light transmission.

The resistance characteristics of the inertial stage with different blade distances had been researched with numerical simulation method, and the resistance characteristic computation curves of the inertial stage with the blade distances of 9mm, 11mm and 13mm had been obtained. Then it contrasted the D=11mm situation with the actual value from experiments, and the tally of the situations turned out to be good. It has provided the data foundation of the resistance characteristic estimate for developing the new gas water separator.

The research of the exhaust gas injection of a gas turbine has been done with the numerical simulation and experimental study method in this thesis. It comes to the proposal of adding diversion bell mouth to the mixing section entrance. And then it determines three kinds of plans by changing the distance from nozzle to the injection section entrance, in order to observe the changes of the injection coefficient. The experiments also have been done to validate the numerical simulation results, and the tally situation is good.

The Hanavan's fifteen rigid multi-body human model was simplified into the six rigid multi-body model, and then the six degrees of freedom The Kane dynamic model was set up. With the human body parameters and muscle parameters, the six degrees of freedom Kane formula and restriction conditions were used to obtain the movement status of gymnasts' free fall to landing with hands. The initial rotation speed of each part of the body can be calculated. After that, the free fall to landing with hands of gymnasts was stimulated and the impact force from the ground surface to the wrists was obtained.

A computational modeling and simulation method for rhythmic gymnastics jump based on sport biomechanics was improved. Taking arched jump as example, the entire jump phase was separated into four parts: taking off from bending the knees, airborne, posturing and landing. Then the formulas were developed for modelling. Finally, computational simulation experiment was done with the formulas. The simulation outcomes showed that this method is effective in rhythmic gymnastics jump analysis.

In this paper, collusion cooperation game theory is applied to optimize a linear passive vehicle suspension model with eight DOF, including six vertical and two rotation motions. Comprehensive considering road surface damage and ride comfort, taking stiffness and damping of seat and suspension system as design variables; and taking seat acceleration RMS, tire's relative dynamic load and suspension's maximum dynamic stroke as objective functions, we establish tri-objective optimization design model and present the optimal methods. Taking tri-objective as three players, by calculating the affecting factors of the design variables to objective functions and fuzzy clustering, the design variables are divided into different strategic spaces owned by each player. Adopting collusion cooperation game model and obeying “you're within me and I'm in yours” protocol, the absolute gains and relative gains are combined as the payoff functions of players. Each game player takes its payoff as mono-objective to optimize its own strategic spaces and obtains the best strategy to deal with the others. All the best strategies are combined as a game strategy set. By multi-gaming, the final solution meeting given convergence of criterion is obtained. From practical calculation example, tri-objective game design, the results prove this algorithm is effective.

A modeling and simulation method for trampoline movement based on sport biomechanics was developed. Taking tuck jump as example, the entire movement phase was divided into four parts: taking off from bending the knees, airborne, posturing and landing. Then the formulas were generated for modelling. Finally, simulation experiment was done with these formulas. The simulation results showed that this method is effective in trampoline movement research.

Cellular Manufacturing is one of the major applications of group technology. It requires an effective part clustering approach to execute preliminary manufacturing cell design. One of famous approaches is the cluster analysis method, which uses similarity coefficients and clustering methods to group similarity parts into part families. Clustering methods are divided into two categories: hierarchical and nonhierarchical methods. Hierarchical methods often suffer from chaining effects, while nonhierarchical methods need a predetermined cluster number. The research proposes a part clustering algorithm that is based on an artificial ant clustering model. The algorithm utilizes the characteristics of ants, congregation and randomness, to prevent grouping results from being fixed during clustering processes and to reduce the effects of noisy data.