• ECG encryption and identification based security solution on the Zynq SoC for connected health systems

      Zhai, Xiaojun; Ait Si Ali, Amine; Amira, Abbes; Bensaali, Faycal; University of Derby; Qatar University; Qatar University (Elsevier, 2017-08)
      Connected health is a technology that associates medical devices, security devices and communication technologies. It enables patients to be monitored and treated remotely from their home. Patients’ data and medical records within a connected health system should be securely stored and transmitted for further analysis and diagnosis. This paper presents a set of security solutions that can be deployed in a connected health environment, which includes the advanced encryption standard (AES) algorithm and electrocardiogram (ECG) identification system. Efficient System-on-Chip (SoC) implementations for the proposed algorithms have been carried out on the Xilinx ZC702 prototyping board. The Achieved hardware implementation results have shown that the proposed AES and ECG identification based system met the real-time requirements and outperformed existing field programmable gate array (FPGA)-based systems in different key performance metrics such as processing time, hardware resources and power consumption. The proposed systems can process an ECG sample in 10.71ms and uses only 30% of the available hardware resources with a power consumption of 107mW.
    • ECG security identification system on the Zynq SoC Platform

      Zhai, Xiaojun; Amira, Abbes; Bensaali, Faycal; University of Derby (IEEE, 2015-10-26)
      Electrocardiogram (ECG) is one of the most safety-relevant biometrics due to its live indication and the unique specific waveform. This paper presents an approach for a security identification system and its System-on-Chip (SoC) implementation. The design of the proposed solution has been validated using both MATLAB and Vivado high-level synthesis tools. The achieved implementation results show that the proposed ECG identification method has not only met the real-time processing requirements, but it also consumes only 33% of the available on-chip logic resources of a Xilinx Zynq 7010 SoC with a high identification accuracy.
    • Edge enhanced deep learning system for large-scale video stream analytics.

      Ali, Muhammad; Anjum, Ashiq; Yaseen, M. Usman; Zamani, A. Reza; Balouek-Thomert, Daniel; Rana, Omer; Parashar, Manish; University of Derby; Rutgers University; University of Cardiff (IEEE, 2018-05-14)
      Applying deep learning models to large-scale IoT data is a compute-intensive task and needs significant computational resources. Existing approaches transfer this big data from IoT devices to a central cloud where inference is performed using a machine learning model. However, the network connecting the data capture source and the cloud platform can become a bottleneck. We address this problem by distributing the deep learning pipeline across edge and cloudlet/fog resources. The basic processing stages and trained models are distributed towards the edge of the network and on in-transit and cloud resources. The proposed approach performs initial processing of the data close to the data source at edge and fog nodes, resulting in significant reduction in the data that is transferred and stored in the cloud. Results on an object recognition scenario show 71\% efficiency gain in the throughput of the system by employing a combination of edge, in-transit and cloud resources when compared to a cloud-only approach.
    • Editorial note: Innovation is the only pathway for manufacturer, visionary and scholars, to improve the quality of human beings daily life

      Shafik, Mahmoud; University of Derby (UNSYS Digital, 2014-06)
      Innovation is the only pathway for manufacturer, visionary and scholars, to improve the quality of human beings daily life. This is where robotics and mechatronics engineering has been adopted since 1984, as one of the most pioneering solutions to many of our industrial challenges. The distinction about such resolution is its flexibility to meet the well-known innovation platforms, i.e. empowering, sustainable and efficient innovation. It’s the creatively of applied research to implement some superintendent roles rather than creation ones. Industrial market has become very challenging to secure businesses, maintain products development, and sustain its growth, since it is not any more about knowledge and existing know-how. It is nowadays about what industrialist can embed into their evolving products using cutting edge emerging technology and how they manufacture it. This is where the International Journal of Robotics and Mechatronics (IJRM) will play a vital role, through the exchange of the innovative ongoing research and development in this area of intelligence and automation across the world.
    • Editorial note: Robotics and industrial automation technology

      Shafik, Mahmoud; University of Derby (UNSYS Digital, 2015-06-15)
      There is no doubt that robotics and industrial automation technology is evolving quiet fast. However, the end user expectation of the technology realisation is still far from what expected. This is due to the limited development of intelligence, typical human brain cells, 3-Dimensional (3D) visual, audible and dynamic movement systems that have the same abilities and self-learning as human, to help in decision making in various environment. There are number of applied research programmes underdevelopment around the world that addresses some of these aforementioned developments. Vision is one of the most important sense and the future robot/autonomous systems proficiency will significantly depend on the ability to see, recognise, distinguish objects and estimate distances. Most jobs depend on the talent of visual perception and it must acknowledge that today's manufacture technologies and applications more and more often broaden well beyond the limits of human visual capacities. This is where robot and autonomous machine vision technology comes in. It is one of the constantly growing areas of applied research that dealing with processing and analysing of visual digital data capture. It plays a key role in the development of intellectual systems and empowers decision making for some of the future robot, autonomous systems, industrial process and manufacturing.
    • Editorial note: The key elements of the future smart cities

      Shafik, Mahmoud; University of Derby (UNSYS Digital, 2016-12)
      One of the key elements of the future smart cities is automation and utilisation of robotic system technology. It is believed that not in the far future that home automation, healthcare, telecare, digitised technology and assisted living technology will make a real impact in our quality of life, especially for older adults with long term condition. Older adults to live independently and have a good quality of life is quite a challenge, since the majorly of them have long term health condition diseases. Health services providers across EU and overall the world, informal and formal carer plays major roles in providing the necessary services and support. Diseases on older adults society are one of the leading causes of death, from which thousands of people die every year. Many of the non-communicable diseases can be prevented by tackling associated risk factors. The cost of treatment of such diseases in the EU only is estimated to be over 70% of the Health Service budget. Treatment includes home-care, medication, consultation and many other relevant services. However, these services are still not adequate, due to the lack of implemented automation and robotic systems technology that enable the older adults to manage their daily life activities independently, taking medications, receive the necessary health services on time, which, in many cases leads to loss of lives and waste of NHS resources. Daily life activities management and telehealth remote monitoring system is one of the potential innovative approaches, to improve the older adult’s quality of life, help live independently, improve NHS services, sustain its economic growth and improve social development. It is a rapidly developing concept where daily life activities, health condition, medical information is transferred through interactive data, and audio visual media and shared between services provider, informal and formal carer. In this 4th issue and 2nd issues the journal a selection of some of these technological challenges facing the automation industry are presented and some of the inventive researcher pioneering solutions and findings are introduced.
    • Editorial note: why we fail to ignite and sustain innovation in the majority of our business organisations?

      Shafik, Mahmoud; University of Derby (UNSYS Digital, 2014-12)
      It is the big question that every small to medium and large enterprise industrialist face every day, why we fail to ignite and sustain innovation in the majority of our business organisations? It is indeed the fact that culture of innovation it does not happen by accident. It must be created, adopted and rewarded. Changing the way our organisations do business requires imagination and creativity. An innovative organisation is run by, employees who can see all new opportunities, risks, technological challenges and are willing to accept and respond to every challenges in a professional conduct. The International Journal of Robotics and Mechatronics is the gate and online access data base for these organisations, to share, exchange knowledge and finding the possible innovative solutions for these challenges.
    • Editorial: What can we expect from data scientists?

      Murtagh, Fionn; Englmeier, Kurt; University of Derby (Facultad de Ingeniería Universidad de Talca, 2017-01-01)
      Data scientist is probably the most trendy job in Information Technology (IT) nowadays. This new profession emerged with the Big Data wave. Even though there is no such thing like an exact job profile, we expect that the data scientist can handle all the Big Data challenges that are novel to us. Without being a magician she or he shall help to deliver us all the magic Big Data promises. The data scientist capitalizes on unstructured data without taking the roles of a programmer, database expert, statistician, or content manager. All these professions are around for decades. So, why invent a new one?
    • Educating digital forensic investigators at Newport

      Vidalis, Stilianos; Llewellyn, Eric; Angelopoulou, Olga; University of Wales, Newport, Centre for Information Operations; University of Glamorgan, Information Security Research Group (2010-09)
      Digital forensics is a multi-disciplinary applied science governed by strict and rigorous rules and regulations. Individuals pursuing a career in this discipline are required to have an interdisciplinary background drawing elements of practical experience from fields as varied as sociology, psychology, forensic science, computing and the law. Despite the above, there is no professional body or QA benchmarks that specifically govern education in this science. The subject area has proved popular and where the profession has traditionally been limited to a select circle of individuals from specific industry sectors, it is now open to all. To meet this demand, many product vendors and Higher Education establishments have developed programmes ranging from short training courses to full undergraduate and postgraduate degree programmes. All these educational offerings promote the fact that individuals will be trained to an appropriate level, however without clear benchmark or regulatory guidance, students face the risk of being ill-equipped for the challenges presented in industry. The challenge faced by educators is to train individuals, many of whom have no prior theoretical or practical experience in the aforementioned fields, to become digital forensic investigators. This paper discusses the approach used at the University of Wales, Newport to overcome this challenge. It demonstrates how industry requirements have influenced and shaped the learning styles adopted by the teaching team in order to produce high calibre graduates that are ready to engage in a career in digital forensics.
    • Effect of crosslinking in cartilage-like collagen microstructures

      Chen, Ying-chun; Chen, Minsi; Gaffney, Eamonn A.; Brown, Cameron P.; University of Oxford; University of Derby; University of Oxford (Elsevier, 2016-10-15)
      The mechanical performance of biological tissues is underpinned by a complex and finely balanced structure. Central to this is collagen, the most abundant protein in our bodies, which plays a dominant role in the functioning of tissues, and also in disease. Based on the collagen meshwork of articular cartilage, we have developed a bottom-up spring-node model of collagen and examined the effect of fibril connectivity, implemented by crosslinking, on mechanical behaviour. Although changing individual crosslink stiffness within an order of magnitude had no significant effect on modelling predictions, the density of crosslinks in a meshwork had a substantial impact on its behaviour. Highly crosslinked meshworks maintained a ‘normal’ configuration under loading, with stronger resistance to deformation and improved recovery relative to sparsely crosslinked meshwork. Stress on individual fibrils, however, was higher in highly crosslinked meshworks. Meshworks with low numbers of crosslinks reconfigured to disease-like states upon deformation and recovery. The importance of collagen interconnectivity may provide insight into the role of ultrastructure and its mechanics in the initiation, and early stages, of diseases such as osteoarthritis.
    • Effect of lossy networks on stereoscopic 3D-video streams

      Torres Vega, Maria; Perra, Cristian; Mocanu, Decebal Constantin; Liotta, Antonio (2017)
    • The effect of performance stages on subwoofer polar and frequency responses

      Hill, Adam J.; Paul, Joe; University of Derby (Institute of Acoustics, 2016-11-17)
      Precise control of low-frequency energy is a common requirement at large-scale live events, whereby sound energy transmitted into performance areas and outside event grounds must be limited. Industry-standard sound system design and prediction software typically omits any acoustical effect a performance stage will have on the overall system response (both in terms of polar and frequency response).This research highlights the significant effect a stage can have on subwoofer performance, where in particularly poor cases directionality is lost and the frequency response is strongly colored by resonances. This work puts forward recommendations for subwoofer system configurations that avoid unwanted stage effects as much as possible to maintain the desired (and predicted) system performance.
    • Effects of rain attenuation on satellite communication links

      Ezeh, G. N.; Chukwuneke, N.S.; Ogujiofor, N.C.; Diala, Uchenna; Federal University of Technology, Owerri, Nigeria (Interdisciplinary Centre for Mathematical and Computational Modelling, 2014-06-05)
      Rain attenuation is a major challenge to microwave satellite communication especially at frequencies above 10 GHz, causing unavailability of signals most of the time. Rain attenuation predictions have become one of the vital considerations while setting up a satellite communication link. In this study, rain attenuation models, cumulative distribution curves and other analytical tools for successful prediction of rain attenuation are presented. A three year Rain rate data was obtained from the Nigeria Meteorological Agency (NIMET) database in addition to experimental data. Of the three prediction models used in the study, Ajayi model gave the range of values closest to the experimental data. A correctional factor was determined as 1.0988 and used to modify the Ajayi model. This modification to Ajayi’s model enabled its rain attenuation values conform more closely to the experimental result.
    • Efficient acoustic modelling of large acoustic spaces using finite difference methods.

      Durbridge, Simon E.; Hill, Adam J.; Bowers and Wilkins; University of Derby (Institute of Acoustics, 2017-11-23)
      Time domain methods for solving wave based acoustic models have been of continued interest and development since early work by key figures such as Bottledooren, as these methods can provide a simple and flexible approach for simulating a wide range of acoustic phenomena such as room modes. The nature of many time domain difference methods present significant computational resource requirements, as the size, sampling rate and inherent stability of the simulation has a distinct impact on the memory and execution time required for the simulation to give a satisfactory result. In this study the execution speed is analysed, for variations of the finite difference time domain method that may provide some increase in computation speed for large domains. It is suggested that leveraging a dynamic windowing method may reduce total computation time for some simulations, by decreasing the number of computations per time-step in the early stage of a simulation.
    • An efficient algorithm for partially matched services in internet of services

      Ahmed, Mariwan; Liu, Lu; Hardy, James; Yuan, Bo; Antonopoulos, Nikolaos; University of Derby (Springer, 2016-05-11)
      Internet of Things (IoT) connects billions of devices in an Internet-like structure. Each device encapsulated as a real-world service which provides functionality and exchanges information with other devices. This large-scale information exchange results in new interactions between things and people. Unlike traditional web services, internet of services is highly dynamic and continuously changing due to constant degrade, vanish and possibly reappear of the devices, this opens a new challenge in the process of resource discovery and selection. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase in number of service consumers and consequent diversity of quality of service (QoS) available. Increase in both sides’ leads to the diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. This paper proposed an IoT service ranking and selection algorithm by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. One of the applications of IoT sensory data that attracts many researchers is transportation especially emergency and accident services which is used as a case study in this paper. Experimental results from real-world services showed that the proposed method achieved significant improvement in the accuracy and performance in the selection process.
    • Efficient and scalable search on scale-free P2P networks

      Liu, Lu; Xu, Jie; Russell, Duncan; Townend, Paul; Webster, David (2009-01-14)
    • Efficient computation of hashes

      Lopes, Raul; Franqueira, Virginia N. L.; Hobson, Peter; Brunel University; University of Central Lancashire (IOP Publishing Ltd, 2014-06-11)
      The sequential computation of hashes at the core of many distributed storage systems and found, for example, in grid services can hinder efficiency in service quality and even pose security challenges that can only be addressed by the use of parallel hash tree modes. The main contributions of this paper are, first, the identification of several efficiency and security challenges posed by the use of sequential hash computation based on the Merkle-Damgard engine. In addition, alternatives for the parallel computation of hash trees are discussed, and a prototype for a new parallel implementation of the Keccak function, the SHA-3 winner, is introduced.
    • Efficient data-processing algorithms for wireless-sensor-networks-based planetary exploration

      Zhai, Xiaojun; Vladimirova, Tanya; University of Derby; University of Leicester (American Institute of Aeronautics and Astronautics, Inc., 2016-01)
      The Space Wireless Sensor Networks for Planetary Exploration project aims to design a wireless sensor network that consists of small wireless sensor nodes dropped onto the moon surface to collect scientific measurements. Data gathered from the sensors will be processed and aggregated for uploading to a lunar orbiter and subsequent transmission to Earth. In this paper, efficient data-processing/fusion algorithms are proposed, the purpose of which is to integrate the scientific sensor data collected by the wireless sensor network, reducing the data volume without sacrificing the data quality to satisfy energy constraints of wireless-sensor-network nodes operating in the extreme moon environment. The results of an extensive simulation experiment targeted at the Space Wireless Sensor Networks for Planetary Exploration lunar exploration mission are reported, which quantify the performance efficiency of the data-processing scheme. It is shown that the proposed data-processing algorithms can reduce the wireless-sensor-network node energy consumption significantly, decreasing the data transmission energy up to 91%. In addition, it is shown that up to 99% of the accuracy of the original data can be preserved in the final reconstructed data.
    • An efficient evolutionary user interest community discovery model in dynamic social networks for internet of people

      Jiang, Liang; Shi, Leilei; Lu, Liu; Yao, Jingjing; Yuan, Bo; Zheng, Yongjun; University of Derby (IEEE, 2019-01-17)
      Internet of People (IoP), which focuses on personal information collection by a wide range of the mobile applications, is the next frontier for Internet of Things (IoT). Nowadays, people become more and more dependent on the Internet, increasingly receiving and sending information on social networks (e.g., Twitter, etc.); thus social networks play a decisive role in IoP. Therefore, community discovery has emerged as one of the most challenging problems in social networks analysis. To this end, many algorithms have been proposed to detect communities in static networks. However, microblogging social networks are extremely dynamic in both content distribution and topological structure. In this paper, we propose a model EEUICD (Efficient Evolutionary User Interest Community Discovery) which employs a nature-inspired genetic algorithm to improve the quality of community discovery. Specifically, a preprocessing method based on HITS (Hypertext Induced Topic Search) improves the quality of initial users and posts, and a label propagation method is used to restrict the conditions of the mutation process to further improve the efficiency and effectiveness of user interest community detection. Finally, the experiments on the real datasets validate the effectiveness of the proposed model.