• Detection of essential tremor at the S-band.

      Yang, Xiaodong; Shah, Syed Aziz; Ren, Aifeng; Fan, Dou; Zhao, Nan; Cao, Dongjian; Hu, Fangming; Ur-Rehman, Masood; Wang, Weigang; von Deneen, Karen M.; et al. (Institute of Electrical and Electronics Engineers (IEEE): OAJ / IEEE, 2018-01-24)
      Essential tremor (ET) is a neurological disorder characterized by rhythmic, involuntary shaking of a part or parts of the body. The most common tremor is seen in the hands/arms and fingers. This paper presents an evaluation of ETs monitoring based on finger-to-nose test measurement as captured by small wireless devices working in shortwave or [Formula: see text]-band frequency range. The acquired signals in terms of amplitude and phase information are used to detect a tremor in the hands. Linearly transforming raw phase data acquired in the [Formula: see text]-band were carried out for calibrating the phase information and to improve accuracy. The data samples are used for classification using support vector machine algorithm. This model is used to differentiate the tremor and nontremor data efficiently based on secondary features that characterize ET. The accuracy of our measurements maintains linearity, and more than 90% accuracy rate is achieved between the feature set and data samples.
    • Determination of optimal curing conditions for imaging single lung cancer cells by atomic force acoustic microscope

      Wang, Xuan; Zhao, Yujing; Zhang, Wenxiao; Wang, Ying; Tian, Liguo; Wang, Xinyue; Song, Zhengxun; Wang, Zuobin; Li, Dayou; Changchun University of Science and Technology; et al. (Institute of Electrical and Electronics Engineers Inc., 2018-11-29)
      This paper presents a method for the determination of optimal curing conditions for the imaging of single lung cancer cells by atomic force acoustic microscope (AFAM). The cellular morphology, height and surface roughness of the cells treated with different concentrations of paraformaldehyde and methanol and durations were observed using an AFAM. The experimental results showed that the A549 cells solidified with 4% paraformaldehyde for the period from 30min to 60min were close to the profiles of living cells. The cells solidified with 4% paraformaldehyde for 10min were beneficial to obtain subsurface structures.
    • A developed magnetic force microscope

      Liu, Jinyun; Wang, Zuobin; Li, Dayou; Changchun University of Science and Technology; University of Bedfordshire (Springer Verlag, 2017-06-13)
      In this paper, a magnetic force microscope (MFM) was developed for applications in liquid environment. The 3D structure of the developed MFM system was designed first and then the components of every part were machined and assembled. The laser beam horizontally reached the mirror and reflected vertically to the cantilever of the probe to reduce the effect of air, glass and liquid refraction. This research focuses on the design of a specific MFM system to obtain the magnetic force images in liquids.
    • Developing a novel water quality prediction model for a South African aquaculture farm

      Eze, Elias Chinedum; Halse, Sarah; Ajmal, Tahmina; University of Bedfordshire; Abagold Limited (MDPI, 2021-06-28)
      Providing an accurate prediction of water quality parameters for improved water quality management is a topical issue in the aquaculture industry. Conventional prediction methods have shown different challenges like a poor generalization, poor prediction accuracy, and high time complexity. Aiming at these challenges, a novel hybrid prediction model with ensemble empirical mode decomposition (EEMD) and deep learning (DL) long-short term memory (LSTM) neural network is proposed in this paper. In this innovative hybrid EEMD-DL-LSTM model, firstly, the integrity of the datasets is enhanced by applying moving average filtering and linear interpolation techniques of water quality parameter datasets pre-treatment. Secondly, the measured real sensor water quality parameters dataset is decomposed with the aid of the EEMD algorithm into disparate IMFs and a corresponding residual item. Thirdly, a multi-feature selection process is applied to make a careful selection of a strongly correlated group of IMFs with the measured real water quality parameter datasets and integrate them as inputs to the DL-LSTM neural network. The presented model is built on water quality sensor data collected from an Abalone farm in South Africa. The performance of the novel hybrid prediction model is validated by comparing the results against the real datasets. To measure the overall accuracy of the novel hybrid prediction model, different statistical indices, namely the Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), are used.
    • Development of a PEMFC dynamic model and the application to the analysis of fuel cell vehicle performance

      Liu, Wei; Peng, Zhijun; Kim, Bill; Gao, Bo; Pei, Yiqiang; Tianjin University; University of Bedfordshire; AVL Powertrain (Institute of Physics Publishing, 2019-12-31)
      In order to investigate basic output performances of PEMFC (Proton Exchange Membrane Fuel Cell) stack, a dynamic model of PEMFC stack has been developed by combining electrochemical sub-model and thermodynamic sub-model. With necessary validation, it demonstrates that modelling results and experimental data are in very good agreement in terms the U-I curve and power output. By applying the dynamic model to analyse performance outputs of PEMFC stack and applying the model for FC-Hybrid vehicle powertrain configuration, it demonstrates that improved PEMFC quality with increased maximum current density could increase the peak power output and also increase the working efficiency, although the increase of peak power is not linear relation with the increase of maximum current density. Higher working temperature of PEMFC would benefit the increases of both peak power output and efficiency. Compared to working temperature, ambient temperature's increase could also make positive influence on power output and efficiency, though the influence is weak. Coupling the dynamic model with a powertrain model of FC-Electric hybrid vehicle, the analysis suggests that both PEMFC stack and battery stack should have similar size for general driving condition. Too big either PEMFC stack or battery stack would increase the total weight then contaminate the fuel/energy economy.
    • Differential magnetic force microscope imaging

      Wang, Ying; Wang, Zuobin; Liu, Jinyun; Hou, Liwei (John Wiley and Sons Inc., 2015-02-04)
      This paper presents a method for differential magnetic force microscope imaging based on a two-pass scanning procedure to extract differential magnetic forces and eliminate or significantly reduce background forces with reversed tip magnetization. In the work, the difference of two scanned images with reversed tip magnetization was used to express the local magnetic forces. The magnetic sample was first scanned with a low lift distance between the MFM tip and the sample surface, and the magnetization direction of the probe was then changed after the first scan to perform the second scan. The differential magnetic force image was obtained through the subtraction of the two images from the two scans. The theoretical and experimental results have shown that the proposed method for differential magnetic force microscope imaging is able to reduce the effect of background or environment interference forces, and offers an improved image contrast and signal to noise ratio (SNR). SCANNING 37:112-115, 2015.
    • Digital forensics challenges to big data in the cloud

      Feng, Xiaohua; Zhao, Yuping; University of Bedfordshire; Peking University (2017-04-28)
      As a new research area, Digital Forensics is a subject in a rapid development society. Cyber security for Big Data in the Cloud is getting attention more than ever. Computing breach requires digital forensics to seize the digital evidence to locate who done it and what has been done maliciously and possible risk/damage assessing what loss could leads to. In particular, for Big Data attack cases, Digital Forensics has been facing even more challenge than original digital breach investigations. Nowadays, Big Data due to its characteristics of three “V”s (Volume, Velocity, and Variety), they are either synchronized with Cloud (Such as smart phone) or stored on the Cloud, in order to sort out the storage capacity etc. problems, which made Digital Forensics investigation even more difficult. The Big Data-Digital Forensics issue for Cloud is difficult due to some issues. One of them is physically identify specific wanted device. Data are distributed in the cloud, customer or the digital forensics practitioner cannot have a fully access control like the traditional investigation does. The Smart City technique is making use of ICT (information communications technology) to collecting, detecting, analysing and integrating the key information data of core systems in running the cities. Meantime, the control is making intelligent responses to different requirements that include daily livelihood, PII (Personally identifiable information) security, environmental protection, public safety, industrial and commercial activities and city services. The Smart City data are Big Data, collected and gathered by the IoT (Internet of Things). This paper has summerised our review on the trends of Digital Forensics served for Big Data. The evidence acquisition challenge is discussed. A case study of a Smart City project with the IoT collected services Big data which are stored at the cloud computing environment is represented. The techniques can be generalised to other Big Data in the Cloud environment.
    • Digital forensics model of smart city automated vehicles challenges

      Feng, Xiaohua; Dawam, Edward Swarlat; Amin, Saad; University of Bedfordshire; Coventry University (2017-04-28)
      The current cyber society is full of complications. Internet has brought so many convenient services to our society but Internet is also a mine field. Mass surveillance from smart phone to PC, from automated car to smart television, any online device seems could be turn to privacy breach toolkit. In order to protect privacy data, including PII, against Cyberstalking and other cybercrimes, a Digital Forensics Model is in progress served for Smart City Automated Vehicles. The proposed development is still on going. Here, an update is reported for discussions.
    • Digital patient: personalized and translational data management through the MyHealthAvatar EU project

      Kondylakis, Haridimos; Spanakis, Emmanouil G.; Sfakianakis, Stelios; Sakkalis, Vangelis; Tsiknakis, Manolis; Marias, Kostas; Zhao, Xia; Yu, Hong Qing; Dong, Feng; Foundation for Research and Technology - Hellas (FORTH); et al. (Institute of Electrical and Electronics Engineers Inc., 2015-11-05)
      The advancements in healthcare practice have brought to the fore the need for flexible access to health-related information and created an ever-growing demand for the design and the development of data management infrastructures for translational and personalized medicine. In this paper, we present the data management solution implemented for the MyHealthAvatar EU research project, a project that attempts to create a digital representation of a patient's health status. The platform is capable of aggregating several knowledge sources relevant for the provision of individualized personal services. To this end, state of the art technologies are exploited, such as ontologies to model all available information, semantic integration to enable data and query translation and a variety of linking services to allow connecting to external sources. All original information is stored in a NoSQL database for reasons of efficiency and fault tolerance. Then it is semantically uplifted through a semantic warehouse which enables efficient access to it. All different technologies are combined to create a novel web-based platform allowing seamless user interaction through APIs that support personalized, granular and secure access to the relevant information.
    • Direct imaging of antigen-antibody binding by atomic force microscopy

      Hu, Jing; Gao, Mingyan; Wang, Zuobin; Chen, Yujuan; Song, Zhengxun; Xu, Hongmei; Changchun University of Science and Technology; University of Bedfordshire (Springer, 2020-09-24)
      Direct observation of antigen-antibody binding at the nanoscale has always been a considerable challenging problem, and researchers have made tremendous efforts on it. In this study, the morphology of biotinylated antibody-specific Immunoglobulin E (IgE) immune complexes has been successfully imaged by atomic force microscopy (AFM) in the tapping-mode. The AFM images indicated that the individual immune complex was composed of an IgE and a biotinylated antibody. Excitingly, it is the first time that we have actually seen the IgE binding to biotinylated antibody. Alternatively, information on the length of IgE, biotinylated antibodies and biotinylated antibody-specific IgE immune complexes were also obtained, respectively. These results indicate the versatility of AFM technology in the identification of antigen-antibody binding. This work not only lays the basis for the direct imaging of the biotinylated antibody-IgE by AFM, but also offers valuable information for studying the targeted therapy and vaccine development in the future.
    • Direct imaging of IgE on the mica surface by tapping-mode atomic force microscopy

      Hu, Jing; Wang, Ying; Gao, Mingyan; Song, Zhengxun; Chen, Yujuan; Wang, Zuobin; Changchun University of Science and Technology; University of Bedfordshire (IEEE, 2020-02-02)
      Immunoglobulin E (IgE) antibody is essential in the functioning of the immune system, so the study of IgE has its practical and profound significance. Herein, the effect of protein concentration and adsorption time on IgE morphology of mica surface was investigated. For this purpose, atomic force microscopy (AFM) has been performed for monitoring protein morphology at different concentrations and adsorption times. In addition, the height and average roughness of IgE were also obtained. The changes of IgE molecule morphology including the shape, height and average roughness indicated that the interactions of protein-surface and protein-protein were varying with the protein concentration and adsorption time.
    • Direct laser interference technology and potential applications

      Yue, Yong; Wang, Dapeng; Zhang, Ziang; Maple, Carsten; Wang, Zuobin; Li, Dayou; Qiu, Renxi; Xi'an Jiaotong-Liverpool University; Changchun University of Science and Technology; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2015-03-12)
      Development of direct laser interference technology (DLIT) is reviewed in this paper. With the merits of being independent on the pretreatment, mask and pattern transfer processes, DLIT is demonstrated a facile and efficient method of producing sub-micro structures on various material surfaces. From a representative perspective, a number of past achievements, containing theoretical and practice aspects, attained by the nanosecond, picosecond, and femtosecond laser interference techniques are introduced. Advantages and limitations in comparison to one another are also addressed. With the progress of the emerging subwavelength structures (e.g. metasurfaces, plasmonic structures) offering the fascinating possibility of controlling the behaviour of light in an unprecedented way, the perspectives of potential applications benefited from DLIT are finally given.
    • Direct metal transfer printing on flexible substrate for fabricating optics functional devices

      Jiang, Yingjie; Zhou, Xiaohong; Zhang, Feng; Shi, Zhenwu; Chen, Linsen; Peng, Changsi; Soochow University (SPIE, 2015-12-31)
      New functional materials and devices based on metal patterns can be widely used in many new and expanding industries,such as flat panel displays, alternative energy,sensors and so on. In this paper, we introduce a new transfer printing method for fabricating metal optics functional devices. This method can directly transfer a metal pattern from a polyethylene terephthalate (PET)supported UV or polydimethylsiloxane (PDMS) pattern to another PET substrate. Purely taking advantage of the anaerobic UV curing adhesive (a-UV) on PET substrate, metal film can be easily peeled off from micro/nano-structured surface. As a result, metal film on the protrusion can be selectively transferred onto the target substrate, to make it the metal functional surface. But which on the bottom can not be transferred. This method provides low cost fabrication of metal thin film devices by avoiding high cost lithography process. Compared with conventional approach, this method can get more smooth rough edges and has wider tolerance range for the original master mold. Future developments and potential applications of this metal transfer method will be addressed.
    • Direct numerical simulation of methane turbulent premixed oxy-fuel combustion

      Zhong, Shenghui; Peng, Zhijun; Li, Yu; Li, Hailin; Zhang, Fan (SAE International, 2017-10-08)
      A 3-D DNS (Three-Dimensional Direct Numerical Simulation) study with detailed chemical kinetic mechanism of methane has been performed to investigate the characteristics of turbulent premixed oxy-fuel combustion in the condition relevant to Spark Ignition (SI) engines. First, 1-D (one-dimensional) laminar freely propagating premixed flame is examined to show a consistent combustion temperature for different dilution cases, such that 73% H2O and 66% CO2 dilution ratios are adopted in the following 3-D DNS cases. Four 3-D DNS cases with various turbulence intensities are conducted. It is found that dilution agents can reduce the overall flame temperature but with an enhancement of density weighted flame speed. CO2 dilution case shows the lowest flame speed both in turbulent and laminar cases. Reaction path analysis based on an in-house post-processing tool is performed to show that the chemical effect of dilution agent H2O leads to an increase of the key elementary reactions; however the total effect is endothermic compared with the counterparts for air condition case. This also results in a lower temperature of the oxy-fuel combustion. Furthermore, weak and strong levels of turbulent intensities 0.8 and 2.4 m/s are studied to show that the higher turbulent intensity leads to higher pressure rise rate, more flame surface wrinkling and higher displacement speed.
    • Displacement error analysis of 6-DoF virtual reality

      Aksu, Ridvan; Chakareski, Jacob; Velisavljevic, Vladan; University of Alabama; University of Bedfordshire (ACM, 2019-12-31)
      Virtual view synthesis is a critical step in enabling Six-Degrees of Freedom (DoF) immersion experiences in Virtual Reality (VR). It comprises synthesis of virtual viewpoints for a user navigating the immersion environment, based on a small subset of captured viewpoints featuring texture and depth maps. We investigate the extreme values of the displacement error in view synthesis caused by depth map quantization, for a given 6DoF VR video dataset, particularly based on the camera settings, scene properties, and the depth map quantization error. We establish a linear relationship between the displacement error and the quantization error, scaled by the sine of the angle between the location of the object and the virtual view in the 3D scene, formed at the reference camera location. In the majority of cases the horizontal and vertical displacement errors induced at a pixel location of a reconstructed 360° viewpoint comprising the immersion environment are respectively proportional to 3/5 and 1/5 of the respective quantization error. Also, the distance between the reference view and the synthesized view severely increases the displacement error. Following these observations: displacement error values can be predicted for given pixel coordinates and quantization error, and this can serve as a first step towards modeling the relationship between the encoding rate of reference views and the quality of synthesized views.
    • A disulfiram-loaded fibers scaffold fabricated via electrospinning method

      Xie, Chenchen; Ding, Ran; Wang, Xinyue; Yan, Jin; Wang, Ying; Zhang, Wenxiao; Qu, Yingmin; Wang, Zuobin; Changchun University of Science and Technology; University of Bedfordshire (IEEE, 2020-01-02)
      In this study, we developed a disulfiram-loaded fibers scaffold via the electrospinning method for enhancing the stability of disulfiram and facilitating the appropriate distribution in tumor tissues. The drug release profile of the disulfiram-loaded fibers scaffold was examined by high-performance liquid chromatography. The results showed that both the initial burst release and the subsequent sustainable release of the drug were suitable for cancer treatments. The results of an MTT assay, which tested the therapeutic efficacy of electrospun fibers in vitro, showed that the DSF-PVDF fibers exhibited their anticancer activity due to the incorporation of DSF. It indicates that DSF is successfully incorporated into the electrospun fibers and the resultant electrospun fibers are highly promising for cancer treatments.
    • Double threshold authentication using body area radio channel characteristics

      Zhao, Nan; Ren, Aifeng; Hu, Fangming; Zhang, Zhiya; Ur-Rehman, Masood; Zhu, Tianqiao; Yang, Xiaodong; Alomainy, Akram; Xidian University, China; University of Bedfordshire; et al. (Institute of Electrical and Electronics Engineers Inc., 2016-06-06)
      The demand of portable and body-worn devices for remote health monitoring is ever increasing. One of the major challenges caused by this influx of wireless body area network (WBAN) devices is security of user's extremely vital and personal information. Conventional authentication techniques implemented at upper layers of the Open System Interconnection (OSI) model usually consumes huge amount of power. They also require significant changes at hardware and software levels. It makes them unsuitable for inherently low powered WBAN devices. This letter investigates the usability of a double threshold algorithm as a physical layer security measure in these scenarios. The algorithm is based on the user's behavioral fingerprint extracted from the radio channel characteristics. Effectiveness of this technique is established through experimental measurements considering a variety of common usage scenarios. The results show that this method provides high level of security against false authentication attacks and has great potential in WBANs.
    • Dual core photonic crystal fiber based sensor Çift çekirdekli fotonik kristal fiber tabanli sensor

      Ademgil, Huseyin; Eze, Festus Uchenna; Arca, Ahmet; Haxha, Shyqyri; Lefke Avrupa Üniversitesi; University of Bedfordshire (IEEE Computer Society, 2014-06-12)
      In this study, the relative sensitivity coefficient of the proposed hexagonal shaped photonic crystal fiber (PCF) has been investigated by employing the full vectorial finite element method (FEM). Propagation loss of the three different liquid analyte with 35 elliptical air holed PCF over wide wavelength range has been investigated. Also, the applications and the propagation characteristics of the proposed PCF structure which occurs with the interaction of the fundamental mode and the liquid filled holes have been discussed. © 2014 IEEE.
    • Durotaxis behavior of bEnd.3 cells on soft substrate with patterned platinum nanoparticle array

      Wu, Xiaomin; Li, Li; Lei, Zecheng; Yang, Fan; Liu, Ri; Wang, Lu; Zhu, Xinyao; Wang, Zuobin; Changchun University of Science and Technology; University of Bedfordshire; et al. (Springer Science and Business Media, 2020-11-17)
      The directional arrangement of cells has crucial effect in tissue engineering fields such as wound healing and scar repair. Studies have shown that continuous nanostructures have directional regulatory effect on cells, but whether discontinuous nanostructures have the same regulatory effect on cells is also worthy of further study. Here, a series of discontinuous platinum nanoparticles (PtNPs) patterned on the surface of PDMS (PtNPs-PDMS&Glass) and glass (PtNPs-Glass) substrates were developed to investigate the effect on bEnd.3 cell durotaxis. The laser interference lithography and nanotransfer printing method were employed to fabricate the substrates. It was found that about 80% cells orderly arranged on the PtNPs-PDMS&Glass substrate, but only 20% cells orderly arrangement on the PtNPs-Glass substrate, and the number of cells on the PtNPs-PDMS&Glass substrate was five times more than that on the PDMS coated glass substrate (PDMS&Glass). The results suggested that patterning PtNPs on the PDMS substrate not only provided the topographical guidance for cells just like continuous nanostructures, but also promoted cell adhesion and growth. In addition, an improved whole cell coupling model was used to investigate and explain the cell durotaxis from the perspective of mechanism. These findings show the possibility of discontinuous nanostructures in regulating cell arrangement, and offer a useful method for the design of biological functional substrate, as well as help to understand the mechanism of cell durotaxis.
    • Dynamic causality knowledge graph generation for supporting the chatbot healthcare system

      Yu, Hong Qing; University of Bedfordshire (Springer Science and Business Media Deutschland GmbH, 2020-10-31)
      With recent viruses across the world affecting millions and millions of people, the self-healthcare information systems show an important role in helping individuals to understand the risks, self-assessment, and self-educating to avoid being affected. In addition, self-healthcare information systems can perform more interactive tasks to effectively assist the treatment process and health condition management. Currently, the technologies used in such kind of systems are mostly based on text crawling from website resources such as text-searching and blog-based crowdsourcing applications. In this research paper, we introduce a novel Artificial Intelligence (AI) framework to support interactive and causality reasoning for a Chatbot application. The Chatbot will interact with the user to provide self-healthcare education and self-assessment (condition prediction). The framework is a combination of Natural Language Processing (NLP) and Knowledge Graph (KG) technologies with added causality and probability (uncertainty) properties to original Description Logic. This novel framework can generate causal knowledge probability neural networks to perform question answering and condition prediction tasks. The experimental results from a prototype showed strong positive feedback. The paper also identified remaining limitations and future research directions.