• Personally identifiable information security in cloud computing

      Feng, Xiaohua; Zhang, Xiangrui (2020-12-18)
      A cyber security application in Personally identifiable information) PII is attracting more and more attention and related to majority people’s everyday activities. The paper is introduced the trends of cyber security in cloud computing and in particular, focus on the responsibility of data privacy, especially in European Union countries. As the impact is on data protection which includes organisation based in the union, or has branches in the union or provides services to the union residents. The paper is also introduced the updated recent development content in our society which caused the impact that we have to deliver ISO standards; for instance, ISO/IEC 27018 and so on. A consequence of the standard is that regular practices of risk assessment need to be carried out in a regular base; such as an annually assessment. Keywords- Data protection, personal privacy, cryptography, cloud computing, cyber security, security policy, Trustworthiness, data service, personally identifiable information (PII), and ISO 27018
    • A study on the effects of tumor-derived exosomes on hepatoma cells and hepatocytes by atomic force microscopy

      Ju, Tuoyu; Wang, Shuwei; Wang, Jiajia; Yang, Fan; Song, Zhengxun; Xu, Hongmei; Chen, Yujuan; Zhang, Jingran; Wang, Zuobin; Changchun University of Science and Technology; et al. (Royal Society of Chemistry, 2020-12-07)
      Tumor-derived exosomes (exos) are closely related to the occurrence, development and treatment of tumors. However, it is not clear how the exosomes affect the physical properties, which lead to the deterioration of the target cells. In this paper, atomic force microscopy (AFM) was used to study the effects of exosomes in HCC-LM3 cells and other cells (SMMC-7721 and HL-7702). The results showed that the HCC-LM3-exos (the exosomes secreted by HCC-LM3 cells, 50 μg mL-1) significantly promoted the proliferation and migration of HCC-LM3 cells. HCC-LM3-exos also promoted the proliferation and migration of SMMC-7721 and HL-7702 cells at 1000 and 1500 μg mL-1, respectively. With an increase in time and concentration, the proliferation effect was more significant. On comparing the mechanical properties of the three types of cells (HCC-LM3, SMMC-7721 and HL-7702 cells), the degradation degree and migration ability of the cells were from high to low in the above order. In turn, the surface roughness of the cells decreased, and adhesion and elastic modulus increased. With an increase in treatment time, surface roughness increased, while adhesion and elastic modulus decreased. These suggested that the HCC-LM3-exos could change the mechanical properties of cells, leading to their deterioration, and enhance their migration and invasion ability. In this paper, the effects of exosomes were analyzed from the perspective of the physical parameters of cells, which provide a new idea to study cancer metastasis and prognosis.
    • Entity-aware capsule network for multi-class classification of big data: a deep learning approach

      Jaiswal, Amit Kumar; Tiwari, Prayag; Garg, Sahil; Hossain, M. Shamim; University of Bedfordshire; University of Padova; École de technologie supérieure, Montréal; King Saud University (Elsevier B.V., 2020-11-20)
      Named entity recognition (NER) is one of the most challenging natural language processing (NLP) tasks, as its performance is related to constantly evolving languages and dependency on expert (human) annotation. The diverse and dynamic content on the web significantly raises the need for a more generalized approach—one that is capable of correctly classifying terms in a corpus and feeding subsequent NLP tasks, such as machine translation, query expansion, and many other applications. Although extensively researched in recent times, the variety of public corpora available nowadays provides room for new and more accurate methods to tackle the NER problem. This paper presents a novel method that uses deep learning techniques based on the capsule network architecture for predicting entities in a corpus. This type of network groups neurons into so-called capsules to detect specific features of an object without reducing the original input unlike convolutional neural networks and their ‘max-pooling’ strategy. Our extensive evaluation on several benchmarked datasets demonstrates how competitive our method is in comparison with state-of-the-art techniques and how the usage of the proposed architecture may represent a significant benefit to further NLP tasks, especially in cases where experts are needed. Also, we explore NER using a theoretical framework that leverages big data for security. For the sake of reproducibility, we make the codebase open-source.
    • Counting calories without wearables: device-free human energy expenditure estimation

      Rahaman, Habibur; Dyo, Vladimir; University of Bedfordshire (2020-11-16)
      Maintaining certain physical activity levels is important to prevent or delay the onset of many medical conditions such as diabetes, or mental health disorders. Traditional calorie estimation methods require wearing devices, such as pedometers, smart watches or smart bracelets, which continuously monitor user activity and estimate the energy expenditure. However, wearable devices may not be suitable for some patients due to the need for periodic maintenance, frequent recharging and having to wear it all the time. In this paper we investigate a feasibility of a device- free human energy expenditure estimation based on RF-sensing, which recognises coarse-grained user activity, such as walking, standing, sitting or resting by monitoring the impact of a person’s activity on ambient wireless links. The calorie estimation is then based on Metabolic Equivalent concept that expresses the energy cost of an activity as a multiple of a person’s basal metabolic rate using Harrison-Benedict model. The experimental evaluation using low cost IEEE 802.15.4 transceivers demonstrated that the approach estimated energy expenditure within an indoor environment within 7.4% to 41.2% range when compared to a FitBit Blaze bracelet.
    • Artificial intelligence cyber security strategy

      Feng, Xiaohua; Feng, Yunzhong; Dawam, Edward Swarlat; University of Bedfordshire; Hebei Normal University (IEEE, 2020-11-11)
      Nowadays, STEM (science, technology, engineering and mathematics) have never been treated so seriously before. Artificial Intelligence (AI) has played an important role currently in STEM. Under the 2020 COVID-19 pandemic crisis, coronavirus disease across over the world we are living in. Every government seek advices from scientist before making their strategic plan. Most of countries collect data from hospitals (and care home and so on in the society), carried out data analysis, using formula to make some AI models, to predict the potential development patterns, in order to make their government strategy. AI security become essential. If a security attack make the pattern wrong, the model is not a true prediction, that could result in thousands life loss. The potential consequence of this non-accurate forecast would be even worse. Therefore, take security into account during the forecast AI modelling, step-by-step data governance, will be significant. Cyber security should be applied during this kind of prediction process using AI deep learning technology and so on. Some in-depth discussion will follow.AI security impact is a principle concern in the world. It is also significant for both nature science and social science researchers to consider in the future. In particular, because many services are running on online devices, security defenses are essential. The results should have properly data governance with security. AI security strategy should be up to the top priority to influence governments and their citizens in the world. AI security will help governments’ strategy makers to work reasonably balancing between technologies, socially and politics. In this paper, strategy related challenges of AI and Security will be discussed, along with suggestions AI cyber security and politics trade-off consideration from an initial planning stage to its near future further development.
    • Smart city lane detection for autonomous vehicle

      Dawam, Edward Swarlat; Feng, Xiaohua; University of Bedfordshire (IEEE, 2020-11-11)
      One of AI branch, Computer Vision-based recognition systems is necessary for security in Autonomous Vehicles (AVs). Traffic sign recognition systems are popularly used in AVs because it ensures driver safety and decrease vehicles accidents on roads. However, the inability of AVs to accurately detect road signs and pedestrian behaviour has led to road crashes and even death in recent times. Additionally, as cities become smarter, the traditional traffic signs dataset will change considerably, as theGoogle, 2020se vehicles and city infrastructure introduce modern facilities into their operation. In this paper, we introduce a computer vision based road surface marking recognition system to serve as an added layer of data source from which AVs will make decisions. We trained our detector using YOLOv3 running in the cloud to detect 25 classes of Road surface markings using over 25,000 images. The results of our experiment demonstrate a robust performance in terms of the accuracy and speed of detection. The results of which will consolidate the traffic sign recognition system, thereby ensuring more reliability and safety in AVs decision making. New algorithm using Deep Learning technology in Artificial intelligence (AI) application is implemented and tested successfully.
    • Battery-assisted electric vehicle charging: data driven performance analysis

      Ali, Junade; Dyo, Vladimir; Zhang, Sijing (2020-11-10)
      As the number of electric vehicles rapidly increases, their peak demand on the grid becomes one of the major challenges. A battery-assisted charging concept has emerged recently, which allows to accumulate energy during off-peak hours and in-between charging sessions to boost-charge the vehicle at a higher rate than available from the grid. While prior research focused on the design and implementation aspects of battery- assisted charging, its impact at large geographical scales remains largely unexplored. In this paper we analyse to which extent the battery-assisted charging can replace high-speed chargers using a dataset of over 3 million EV charging sessions in both domestic and public setting in the UK. We first develop a discrete-event EV charge model that takes into account battery capacity, grid supply capacity and power output among other parameters. We then run simulations to evaluate the battery-assisted charging performance in terms of delivered energy, charging time and parity with conventional high-speed chargers. The results indicate that in domestic settings battery-assisted charging provides 98% performance parity of high-speed chargers from a standard 3 kW grid connection with a single battery pack. For non-domestic settings, the battery-assisted chargers can provide 92% and 99% performance parity of high-speed chargers with 10 battery packs using 3kW and 7kW grid supply respectively.
    • 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.
    • Implantable antennas for bio-medical applications

      Malik, Nabeel A.; Sant, Paul; Ajmal, Tahmina; Ur-Rehman, Masood; University of Bedfordshire; University of Glasgow (Institute of Electrical and Electronics Engineers Inc., 2020-10-08)
      Biomedical telemetry has gained a lot of attention with the development in the healthcare industry. This technology has made it feasible to monitor the physiological signs of patient remotely without traditional hospital appointments and follow up routine check-ups. Implantable Medical Devices(IMDs) play an important role to monitor the patients through wireless telemetry. IMDs consist of nodes and implantable sensors in which antenna is a major component. The implantable sensors suffer a lot of limitations. Various factors need to be considered for the implantable sensors such as miniaturization, patient safety, bio-compatibility, low power consumption, lower frequency band of operation and dual-band operation to have a robust and continuous operation. The selection of the antenna is a challenging task in implantable sensor design as it dictates performance of the whole implant. In this paper a critical review on implantable antennas for biomedical applications is presented.
    • Dynamic mechanics of HK-2 cell reaction to HG stimulation studied by atomic force microscopy

      Yang, Fan; Wang, Jiajia; Qu, Kaige; Yang, Xue; Liu, Chuanzhi; Wang, Ying; Song, Zhengxun; Xu, Hongmei; Chen, Yujuan; Wang, Zuobin; et al. (Royal Society of Chemistry, 2020-10-02)
      Renal tubular cell injury by exposure to high glucose (HG) stimulation mainly accounts for diabetic nephropathy (DN). To understand the mechanism of injury by HG, quantitative characterization has commonly focused on the cells that are already impaired, which ignores the signals for the process of being injured. In this study, the architecture and morphology of HK-2 cells were observed dynamically by multiple imaging methods. AFM (atomic force microscopy)-based single-cell force spectroscopy was employed to investigate the dynamic mechanics quantitatively. The results showed that the Young's modulus increased continuously from 2.44 kPa up to 4.15 kPa for the whole period of injury by HG, while the surface adhesion decreased from 2.43 nN to 1.63 nN between 12 h and 72 h. In addition, the actin filaments of HK-2 cells exposed to HG depolymerized and then nucleated with increasing Young's modulus. The absence of cell pseudopodia coincided with the reduced cell adhesion, strongly suggesting close relationships between the cell architecture, morphology and mechanical properties. Furthermore, the stages of cell reactions were identified and assessed. Overall, the dynamic mechanics of the cells facilitate the identification of injured cells and the assessment of the degree of injury for accurate diagnoses and treatments.
    • A compact size implantable antenna for bio-medical applications

      Malik, Nabeel A.; Ajmal, Tahmina; Sant, Paul; Ur-Rehman, Masood; University of Bedfordshire; University of Glasgow (Institute of Electrical and Electronics Engineers Inc., 2020-09-29)
      Implantable antennas play a vital role in implantable sensors and medical devices. In this paper, we present the design of a compact size implantable antenna for biomedical applications. The antenna is designed to operate in ISM band at 915 MHz and the overall size of the antenna is 4 imes 4 imes 0.3 mm {3}. A shorting pin is used to lower the operating frequency of the antenna. For excitation purpose a 50-ohm coaxial probe feed is used in the design. A superstrate layer is placed on the patch to prevent the direct contact between the radiating patch and body tissues. The antenna is simulated in skin layer model. The designed antenna demonstrates a gain of 3.22 dBi while having a-10 dB bandwidth of 240 MHz with good radiation characteristics at 915 MHz. The simulated results show that this antenna is an excellent candidate for implantable applications.
    • Security challenges in cyber systems

      Safdar, Ghazanfar Ali; Kalsoom, Tahera; Ramzan, Naeem; University of Bedfordshire; University of the West of Scotland (Institute of Electrical and Electronics Engineers Inc., 2020-09-29)
      CPS (Cyber-Physical Systems) is proposed by the NSF (National Scientific Foundation) to describe a type of necessities which conglomerates hardware and software components and being the next step in development of embedded systems. CPS includes a wide range of research topics from signal processing to data analysis. This paper contains a brief review of the basic infrastructure for CPS including smart objects and network aspects in relation to TCP/IP stack. As CPS reflect the processes of the physical environment onto the cyber space, virtualisation as important tool for abstraction plays crucial role in CPS. In this context paper presents the challenges associated with mobility and vritualisation; accordingly, three main types of virtualisation, namely network, devices and applications virtualisation are presented in the paper. The main focus of the paper is made on security. Different threats, attack types and possible consequences are discussed as well as analysis of various approaches to cope with existing threats is introduced. Furthermore, needs and requirements for safety-critical CPS are reviewed.
    • A tri-band implantable antenna for biotelemetry applications

      Malik, Nabeel A.; Ajmal, Tahmina; Sant, Paul; Ur-Rehman, Masood; University of Bedfordshire; University of Glasgow (Institute of Electrical and Electronics Engineers Inc., 2020-09-29)
      In this paper we propose a compact size rectangular implantable tri-band patch antenna for biotelemetry applications. Rogers RT6010 is used as substrate and superstrate material. The resonant frequency is further lowered by using a shorting pin which also reduces patch resistance. For excitation 50-ohm microstrip line is used. The antenna operates in MICS band (402405) MHz, ISM band (902-928) MHz and (2.4-2.48) GHz at 402 MHz, 915 MHz and 2.4 GHz. The gain of the antenna is 2.05 dBi, 2.67 dBi and 5.39 dBi with bandwidth of 120 MHz, 166 MHz and 190 MHz at relevant frequencies when simulated in a fat layer box. SAR values are within allowable limits. The simulated results show that the antenna is an excellent choice for implantable applications as it can be used for data transmission, wakeup signal and wireless power transfer by using three frequency bands.
    • 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.
    • Application of atomic force microscope in diagnosis of single cancer cells

      Lu, Zhengcheng; Wang, Zuobin; Li, Dayou; ; University of Bedfordshire; Changchun University of Science and Technology (American Institute of Physics Inc., 2020-09-04)
      Changes in mechanical properties of cells are closely related to a variety of diseases. As an advanced technology on the micro/nano scale, atomic force microscopy is the most suitable tool for information acquisition of living cells in human body fluids. AFMs are able to measure and characterize the mechanical properties of cells which can be used as effective markers to distinguish between different cell types and cells in different states (benign or cancerous). Therefore, they can be employed to obtain additional information to that obtained via the traditional biochemistry methods for better identifying and diagnosing cancer cells for humans, proposing better treatment methods and prognosis, and unravelling the pathogenesis of the disease. In this report, we review the use of AFMs in cancerous tissues, organs, and cancer cells cultured in vitro to obtain cellular mechanical properties, demonstrate and summarize the results of AFMs in cancer biology, and look forward to possible future applications and the direction of development.
    • Design an asymmetrical three-beam laser interference lithography for fabricating micro- and nano-structures

      Dong, Litong; Zhang, Ziang; Wang, Zuobin; Li, Dayou; Liu, Mengnan; Changchun University of Science and Technology; University of Bedfordshire; Changchun Observatory (Japan Laser Processing Society, 2020-09-01)
      Multi-beam laser interference lithography (LIL) has become one of the most important techniques and shown significant advantages in the fabrication of micro- and nano-structures. Controlling inten-sity ratio of optical distributions is a key issue in LIL for fabricating micro- and nano-structures. This paper presents an asymmetrical three-beam LIL system which effectively improves the intensity ratio of optical distributions. Comparing with the symmetrical three-beam interference, the asymmetrical three-beam LIL achieved the high intensity ratio of optical distribution when producing the similar interference pattern. In addition, this system also avoids modulation patterns in multi-beam LIL sys-tems and reduces the difficulty of actual LIL processing. A fast Fourier Transform (FFT) analysis used to study the pattern distributions of the asymmetrical three-beam interference from frequency spectra which shows that the pattern with a high-intensity array can be obtained by adjusting the parameter settings of incident laser beams. The asymmetrical three-beam LIL system was verified through fab-ricating patterns. The experimental results are in good agreement with the theoretical analyses.
    • Fabrication of biomimetic superhydrophobic and anti-icing Ti6Al4V alloy surfaces by direct laser interference lithography and hydrothermal treatment

      Liu, Ri; Chi, Zhengdong; Cao, Liang; Weng, Zhankun; Wang, Lu; Li, Li; Saeed, Sadaf; Lian, Zhongxu; Wang, Zuobin; Changchun University of Science and Technology; et al. (Elsevier, 2020-08-17)
      Nature gives us a large number of inspirations in designing functional materials. Many plant leaves with self-cleaning properties are ubiquitous in nature. These plants have hierarchical structures, which have extreme repellency to liquids and have considerable technical potential in various applications. Herein, we present a method for fabricating bionic taro leaf surfaces by direct laser interference lithography (DLIL) and hydrothermal treatment. The micro-pillar array structure (MPA) was fabricated by DLIL, and a layer of nano-grass structure (NG) was grown on it by hydrothermal treatment. Experiments indicate that the hierarchical composite structures not only have a satisfactory superhydrophobic function with the apparent contact angle (CA) of 172° and sliding angle (SA) of 4°, but also have a strong anti-icing ability with the delay time (DT) of 3723 s. The method is simple and high-efficient for fabricating bionic self-cleaning and anti-icing surfaces.
    • Investigating effects of silicon nanowire and nanohole arrays on fibroblasts via AFAM

      Liu, Yan; Li, Li; Yang, Yang; Tian, Liguo; Wu, Xiaomin; Weng, Zhankun; Guo, Xudong; Lei, Zecheng; Qu, Kaige; Yan, Jin; et al. (Springer Verlag (Germany), 2020-07-30)
      Understanding the cell–substrate interactions has great significance in tissue regeneration therapies. However, the cell–substrate interactions are not well understood because the interface of cell–substrate is typically buried beneath the cells. This research investigated the subsurfaces of fibroblasts cultured on hybrid nanoarrays using atomic force acoustic microscopy (AFAM). We fabricated hybrid silicon nanowires (SiNWs) and silicon nanoholes (SiNHs) on Si substrates to serve as biomimetic nanoarrays by employing laser interference lithography and the metal-assisted chemical etching (MacEtch) method. After the L929 cells were cultured on the nanoarrays, scanning electron microscopy (SEM) and AFAM were employed to investigate the surface and subsurface of L929 cells. It was suggested that fibroblasts could sense the morphology of the hybrid nanoarrays and membrane damage of fibroblasts on the hybrid nanoarrays were related to the nanostructures. This study can help guide the design of biointerfaces and provide a useful tool for the study of cell subsurfaces in diverse biological fields.
    • BIRDS-bridging the gap between information science, information retrieval and data science

      Frommholz, Ingo; Liu, Haiming; Melucci, Massimo; University of Bedfordshire; University of Padova (Association for Computing Machinery, Inc, 2020-07-30)
      The BIRDS workshop aimed to foster the cross-fertilization of Information Science (IS), Information Retrieval (IR) and Data Science (DS). Recognising the commonalities and differences between these communities, the proposed full-day workshop brought together experts and researchers in IS, IR and DS to discuss how they can learn from each other to provide more user-driven data and infor-mation exploration and retrieval solutions. Therefore, the papers aimed to convey ideas on how to utilise, for instance, IS concepts and theories in DS and IR or DS approaches to support users in data and information exploration.
    • Effects of alternating electric field on the imaging of DNA double-helix structure by atomic force microscope

      Wang, Ying; Ma, Ke; Wang, Jiajia; Li, Li; Liu, Ziyu; Hu, Jing; Gao, Mingyan; Wang, Zuobin (Springer, 2020-07-22)
      The effects of alternating electric field on the imaging of DNA double-helix structure were explored by atomic force microscope (AFM). First, the DNA sample was located under an alternating electric field in a fixed direction and dried. Then, AFM was used to obtain the DNA images under different alternating electric fields with the voltage range from 0.5 to 6.0 V and the frequency of 50 kHz. Thus, the DNA double-helix structures with different extensions were observed when the DNA molecules were gradually stretched under different field intensities. The distributions of DNA molecules in solution were random if there were no external forces, and the curved DNA molecules were observed in the AFM image. With the increase in alternating electric voltage (0.5–4.0 V), the DNA structure was shifted from random to oriented conformation and the DNA grooves were further unfolded. While the higher voltage (5.0–6.0 V) resulted in the rupture of DNA chains due to the excessive stretching force. It showed that the optimal voltage was 1.0 V, and the double-helix structure was observed. This method provides an efficient way for monitoring and measuring bio-macromolecules. It may also enable the exploration of the DNA–protein binding and DNA molecular self-assembly processes.