Table 2. Performance summary of K-based sorbents capturing CO2

This article reviews the progress made in CO2 capture, storage, and utilization in Chinese Academy of Sciences (CAS). New concepts such as adsorption using dry regenerable solid sorbents as well as functional ionic liquids (ILs) for CO2 capture are thoroughly discussed. Carbon sequestration, such as geological sequestration, mineral carbonation and ocean storage are also covered. The utilization of CO2 as a raw material in the synthesis of chemicals and liquid energy carriers which offers a way to mitigate the increasing CO2 buildup is introduced.

Study of Liquid Desiccant Air-Conditioning for High Performance Greenhouses

Greenhouses have become an invaluable source of year-round food production. Further development of viable and efficient high performance greenhouses is important for future food security. Closing the greenhouse envelope from the environment can provide benefits in space heating energy savings, pest control, and CO2 enrichment. This requires the application of a novel air conditioning system to handle the high cooling loads experienced by a greenhouse. Liquid desiccant air-conditioning (LDAC) have been found to provide high latent cooling capacities, which is perfect for the application of a humid greenhouse microclimate. TRNSYS simulations were undertaken to study the feasibility of two liquid desiccant dehumidification systems based on their capacity to control the greenhouse microclimate, and their cooling performance. The base model (B-LDAC) included a natural gas boiler, and two cooling systems for seasonal operation. The second model (HP-LDAC) was a hybrid liquid desiccant-heat pump dehumidification system. The average tCOPdehum and tCOPtotal of the B-LDAC system increased from 0.40 and 0.56 in January to 0.94 and 1.09 in June. Increased load and performance during a sample summer day improved these values to 3.5 and 3.0, respectively. The average eCOPdehum and eCOPtotal values were 1.0 and 1.8 in winter, and 1.7 and 2.1 in summer. The HP-LDAC system produced similar daily performance trends where the annual average eCOPdehum and eCOPtotal values were 1.3 and 1.2, but the sample day saw peaks of 2.4 and 3.2, respectively. The B-LDAC and HP-LDAC results predicted greenhouse temperatures exceeding 30°C for 34% and 17% of the month of July, respectively. Similarly, humidity levels increased in summer months, with a maximum of 14% of the time spent over 80% in May for both models. The percentage of annual savings in space heating energy associated with closing the greenhouse to ventilation was 34%. The additional annual regeneration energy input was reduced by 26% to 526 kWhm-2, with the implementation of a heat recovery ventilator on the regeneration exhaust air. The models also predicted an electrical energy input of 245 kWhm-2 and 305 kWhm-2 for the B-LDAC and HP-LDAC simulations, respectively.

Performance Evaluation of a Statistical and a Neural Network Model for Nonrigid Shape-Based Registration

Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.

Assessment of the EEE-4 oral test: a discourse analysis based on complex networks.

With the development of information technology, the theory and methodology of complex network has been introduced to the language research, which transforms the system of language in a complex networks composed of nodes and edges for the quantitative analysis about the language structure. The development of dependency grammar provides theoretical support for the construction of a treebank corpus, making possible a statistic analysis of complex networks. This paper introduces the theory and methodology of the complex network and builds dependency syntactic networks based on the treebank of speeches from the EEE-4 oral test. According to the analysis of the overall characteristics of the networks, including the number of edges, the number of the nodes, the average degree, the average path length, the network centrality and the degree distribution, it aims to find in the networks potential difference and similarity between various grades of speaking performance. Through clustering analysis, this research intends to prove the network parameters’ discriminating feature and provide potential reference for scoring speaking performance.

Predicting Student Performance and Differences in Learning Styles based on Textual Complexity Indices applied on Blog and Microblog Posts

Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.

Evaluation of strontium-site-deficient Sr2Fe1.4Co0.1Mo0.5O6-δ-based perovskite oxides as intermediate temperature solid oxide fuel cell cathodes

In this paper strontium-site-deficient Sr₂Fe_1.4Co_0.1Mo_0.5O_6-δ-based perovskite oxides (S_xFCM) were prepared and evaluated as the cathode materials for intermediate temperature solid oxide fuel cells (IT-SOFCs). All samples exhibited a cubic phase structure and the lattice shrinked with increasing the Sr-deficiency as shown in XRD patterns. XPS results determined that the transition elements (Co/Fe/Mo) in S_xFCM oxides were in a mixed valence state, demonstrating the small polaron hopping conductivity mechanism existed. Among the samples, S_1.950FCM presented the lowest coefficient of thermal expansion of 15.62 × 10^-6 K^-1, the highest conductivity value of 28 S cm^-1 at 500 °C, and the lowest interfacial polarization resistance of 0.093 Ω cm² at 800 °C, respectively. Furthermore, an anode-supported single cell with a S_1.950FCM cathode was prepared, demonstrating a maximum power density of 1.16 W cm^-2 at 800 °C by using wet H₂ (3% H₂O) as the fuel and ambient air as the oxidant. These results indicate that the introduction of Sr-deficiency can dramatically improve the electrochemical performance of Sr₂Fe_1.4Co_0.1Mo_0.5O_6-δ, showing great promise as a novel cathode candidate material for IT-SOFCs.

The Evolution of 'Design Build Fly' Led Teaching in Aerospace Engineering

This paper describes the evolution of a ‘Design - Build-Fly’ (DBF) approach to the delivery and assessment of a Stage Three Aircraft Design module. It focuses on the primary learning outcomes around the design and manufacturing functions associated with the development of a remotely controlled aircraft. The work covers a six year period from 2011 to present mapping the transformation of the module from report based assessment to a more hands on approach resulting in a fully functioning remotely controlled aircraft. Results show that both the staff and student experience improved across key performance metrics including student feedback, learning and competency development. Challenges still remain in methods of placing students within teams and maintaining technical rigour in reporting as students develop vocational skills and more reflective writing styles.

FPGA-based soft-core processors for image processing applications

With security and surveillance, there is an increasing need to process image data efficiently and effectively either at source or in a large data network. Whilst a Field-Programmable Gate Array (FPGA) has been seen as a key technology for enabling this, the design process has been viewed as problematic in terms of the time and effort needed for implementation and verification. The work here proposes a different approach of using optimized FPGA-based soft-core processors which allows the user to exploit the task and data level parallelism to achieve the quality of dedicated FPGA implementations whilst reducing design time. The paper also reports some preliminary
progress on the design flow to program the structure. An implementation for a Histogram of Gradients algorithm is also reported which shows that a performance of 328 fps can be achieved with this design approach, whilst avoiding the long design time, verification and debugging steps associated with conventional FPGA implementations.

Tailoring Magnetic, Mechanical and Dielectric Properties of Magnetorheological Elastomers based on Natural Rubber and Iron by Magnetic Field Assisted Curing for Possible Applications

If magnetism is universal in nature, magnetic materials are ubiquitous. A life without magnetism is unthinkable and a day without the influence of a magnetic material is unimaginable. They find innumerable applications in the form of many passive and active devices namely, compass, electric motor, generator, microphone, loud speaker, maglev train, magnetic resonance imaging, data recording and reading, hadron collider etc. The list is endless. Such is the influence of magnetism and magnetic materials in ones day to day life. With the advent of nanoscience and nanotechnology, along with the emergence of new areas/fields such as spintronics, multiferroics and magnetic refrigeration, the importance of magnetism is ever increasing and attracting the attention of researchers worldwide. The search for a fluid which exhibits magnetism has been on for quite some time. However nature has not bestowed us with a magnetic fluid and hence it has been the dream of many researchers to synthesize a magnetic fluid which is thought to revolutionize many applications based on magnetism. The discovery of a magnetic fluid by Jacob Rabinow in the year 1952 paved the way for a new branch of Physics/Engineering which later became magnetic fluids. This gave birth to a new class of material called magnetorheological materials. Magnetorheological materials are considered superior to electrorheological materials in that magnetorheology is a contactless operation and often inexpensive.Most of the studies in the past on magnetorheological materials were based on magnetic fluids. Recently the focus has been on the solid state analogue of magnetic fluids which are called Magnetorheological Elastomers (MREs). The very word magnetorheological elastomer implies that the rheological properties of these materials can be altered by the influence of an external applied magnetic field and this process is reversible. If the application of an external magnetic field modifies the viscosity of a magnetic fluid, the effect of external magnetic stimuli on a magnetorheological elastomer is in the modification of its stiffness. They are reversible too. Magnetorheological materials exhibit variable stiffness and find applications in adaptive structures of aerospace, automotive civil and electrical engineering applications. The major advantage of MRE is that the particles are not able to settle with time and hence there is no need of a vessel to hold it. The possibility of hazardous waste leakage is no more with a solid MRE. Moreover, the particles in a solid MRE will not affect the performance and durability of the equipment. Usually MR solids work only in the pre yield region while MR fluids, typically work in the post yield state. The application of an external magnetic field modifies the stiffness constant, shear modulus and loss modulus which are complex quantities. In viscoelastic materials a part of the input energy is stored and released during each cycle and a part is dissipated as heat. The storage modulus G′ represents the capacity of the material to store energy of deformation, which contribute to material stiffness. The loss modulusG′′ represents the ability of the material to dissipate the energy of deformation. Such materials can find applications in the form of adaptive vibration absorbers (ATVAs), stiffness tunable mounts and variable impedance surfaces. MREs are an important material for automobile giants and became the focus of this research for eventual automatic vibration control, sound isolation, brakes, clutches and suspension systems

Design and implementation of a non-destructive defect detection technique based on UWB-SAR imaging

In the last twenty years aerospace and automotive industries started working widely with composite materials, which are not easy to test using classic Non-Destructive Inspection (NDI) techniques. Pairwise, the development of safety regulations sets higher and higher standards for the qualification and certification of those materials. In this thesis a new concept of a Non-Destructive defect detection technique is proposed, based on Ultrawide-Band (UWB) Synthetic Aperture Radar (SAR) imaging. Similar SAR methods are yet applied either in minefield [22] and head stroke [14] detection. Moreover feasibility studies have already demonstrated the validity of defect detection by means of UWB radars [12, 13]. The system was designed using a cheap commercial off-the-shelf radar device by Novelda and several tests of the developed system have been performed both on metallic specimen (aluminum plate) and on composite coupon (carbon fiber). The obtained results confirm the feasibility of the method and highlight the good performance of the developed system considered the radar resolution. In particular, the system is capable of discerning healthy coupons from damaged ones, and correctly reconstruct the reflectivity image of the tested defects, namely a 8 x 8 mm square bulge and a 5 mm drilled holes on metal specimen and a 5 mm drilled hole on composite coupon.

Optics-Based Quantum Information and Sensing Platforms Utilizing the Nitrogen-Vacancy Center in Diamond

Thesis (Ph.D.)--University of Washington, 2016-08