Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Distributed acceleration of mobile radio network optimisation algorithms

The past decade has witnessed explosive growth of mobile subscribers and services. With the purpose of providing better-swifter-cheaper services, radio network optimisation plays a crucial role but faces enormous challenges. The concept of Dynamic Network Optimisation (DNO), therefore, has been introduced to optimally and continuously adjust network configurations, in response to changes in network conditions and traffic. However, the realization of DNO has been seriously hindered by the bottleneck of optimisation speed performance. An advanced distributed parallel solution is presented in this paper, as to bridge the gap by accelerating the sophisticated proprietary network optimisation algorithm, while maintaining the optimisation quality and numerical consistency. The ariesoACP product from Arieso Ltd serves as the main platform for acceleration. This solution has been prototyped, implemented and tested. Real-project based results exhibit a high scalability and substantial acceleration at an average speed-up of 2.5, 4.9 and 6.1 on a distributed 5-core, 9-core and 16-core system, respectively. This significantly outperforms other parallel solutions such as multi-threading. Furthermore, augmented optimisation outcome, alongside high correctness and self-consistency, have also been fulfilled. Overall, this is a breakthrough towards the realization of DNO.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

Interference cancellation in two-path successive relay system with network coding

This paper proposes a novel interference cancellation algorithm for the two-path successive relay system using network coding. The two-path successive relay scheme was proposed recently to achieve full date rate transmission with half-duplex relays. Due to the simultaneous data transmission at the relay and source nodes, the two-path relay suffers from the so-called inter-relay interference (IRI) which may significantly degrade the system performance. In this paper, we propose to use the network coding to remove the IRI such that the interference is first encoded with the network coding at the relay nodes and later removed at the destination. The network coding has low complexity and can well suppress the IRI. Numerical simulations show that the proposed algorithm has better performance than existing approaches.

An introduction to radial basis functions for system identification: a comparison with other neural network methods

A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RBFs are firstly considered in detail themselves and are subsequently compared with a multi-layered perceptron (MLP), in terms of performance and usage.

A comparative study of multilayered and single layered neural network based predictive controllers

The authors compare the performance of two types of controllers one based on the multilayered network and the other based on the single layered CMAC network (cerebellar model articulator controller). The neurons (information processing units) in the multi-layered network use Gaussian activation functions. The control scheme which is considered is a predictive control algorithm, along the lines used by Willis et al. (1991), Kambhampati and Warwick (1991). The process selected as a test bed is a continuous stirred tank reactor. The reaction taking place is an irreversible exothermic reaction in a constant volume reactor cooled by a single coolant stream. This reactor is a simplified version of the first tank in the two tank system given by Henson and Seborg (1989).

Discrete demand side control performance under dynamic building simulation: a heat pump application

This study presents the findings of applying a Discrete Demand Side Control (DDSC) approach to the space heating of two case study buildings. High and low tolerance scenarios are implemented on the space heating controller to assess the impact of DDSC upon buildings with different thermal capacitances, light-weight and heavy-weight construction. Space heating is provided by an electric heat pump powered from a wind turbine, with a back-up electrical network connection in the event of insufficient wind being available when a demand occurs. Findings highlight that thermal comfort is maintained within an acceptable range while the DDSC controller maintains the demand/supply balance. Whilst it is noted that energy demand increases slightly, as this is mostly supplied from the wind turbine, this is of little significance and hence a reduction in operating costs and carbon emissions is still attained.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

Performance analysis of data transmissions in MPLS and non-MPLS networks

Basic Network transactions specifies that datagram from source to destination is routed through numerous routers and paths depending on the available free and uncongested paths which results in the transmission route being too long, thus incurring greater delay, jitter, congestion and reduced throughput. One of the major problems of packet switched networks is the cell delay variation or jitter. This cell delay variation is due to the queuing delay depending on the applied loading conditions. The effect of delay, jitter accumulation due to the number of nodes along transmission routes and dropped packets adds further complexity to multimedia traffic because there is no guarantee that each traffic stream will be delivered according to its own jitter constraints therefore there is the need to analyze the effects of jitter. IP routers enable a single path for the transmission of all packets. On the other hand, Multi-Protocol Label Switching (MPLS) allows separation of packet forwarding and routing characteristics to enable packets to use the appropriate routes and also optimize and control the behavior of transmission paths. Thus correcting some of the shortfalls associated with IP routing. Therefore MPLS has been utilized in the analysis for effective transmission through the various networks. This paper analyzes the effect of delay, congestion, interference, jitter and packet loss in the transmission of signals from source to destination. In effect the impact of link failures, repair paths in the various physical topologies namely bus, star, mesh and hybrid topologies are all analyzed based on standard network conditions.

Evolution of network structure in polymer-stabilised liquid crystals

Experiments were performed to investigate the evolution of structure and morphology of the network in polymer-stabilised liquid crystals. In situ optical microscopy revealed that the morphology was significantly altered by extraction of the LC host, while scanning electron microscopy showed that the network morphology was also dependent on the polymerisation conditions and closely related to the depletion of monomer, as monitored by high performance liquid chromatography. Transmission electron microscopy allowed observation of internal structure, resolving microstructure on the order of 0. 1 μm.

Mid-term evaluation of African Technology Policy Studies Network Phase VI Strategic Plan: for the period January 1, 2009 to December 31, 2010

The African Technology Policy Studies Network (ATPS) is a multidisciplinary network of researchers, private sector actors, policymakers and civil society. ATPS has the vision to become the leading international centre of excellence and reference in science, technology and innovation (STI) systems research, training and capacity building, communication and sensitization, knowledge brokerage, policy advocacy and outreach in Africa. It has a Regional Secretariat in Nairobi Kenya, and operates through national chapters in 29 countries (including 27 in Africa and two Chapters in the United Kingdom and USA for Africans in the Diaspora) with an expansion plan to cover the entire continent by 2015. The ATPS Phase VI Strategic Plan aims to improve the understanding and functioning of STI processes and systems to strengthen the learning capacity, social responses, and governance of STI for addressing Africa's development challenges, with a specific focus on the Millennium Development Goals (MDGs). A team of external evaluators carried out a midterm review to assess the effectiveness and efficiency of the implementation of the Strategic Plan for the period January 1, 2009 to December 31, 2010. The evaluation methodology involved multiple quantitative and qualitative methods to assess the qualitative and quantitative inputs (human resources, financial resources, time, etc.) into ATPS activities (both thematic and facilitative) and their tangible and intangible outputs, outcomes and impacts. Methods included a questionnaire survey of ATPS members and stakeholders, key informant interviews, and focus group discussions (FGDs) with members in six countries. Effectiveness of Programmes Under all six strategic goals, very good progress has been made towards planned outputs and outcomes. This is evidenced by key performance indicators (KPIs) generated from desk review, ratings from the survey respondents, and the themes that run through the FGDs. Institutional and Programme Cost Effectiveness Institutional Effectiveness: assessment of institutional effectiveness suggests that adequate management frameworks are in place and are being used effectively and transparently. Also technical and financial accounting mechanisms are being followed in accordance with grant agreements and with global good practice. This is evidenced by KPIs generated from desk review. Programme Cost Effectiveness: assessment of cost-effectiveness of execution of programmes shows that organisational structure is efficient, delivering high quality, relevant research at relatively low cost by international standards. The evidence includes KPIs from desk review: administrative costs to programme cost ratio has fallen steadily, to around 10%; average size of research grants is modest, without compromising quality. There is high level of pro bono input by ATPS members. ATPS Programmes Strategic Evaluation ATPS research and STI related activities are indeed unique and well aligned with STI issues and needs facing Africa and globally. The multi-disciplinary and trans-boundary nature of the research activities are creating a unique group of research scientists. The ATPS approach to research and STI issues is paving the way for the so called Third Generation University (3GU). Understanding this unique positioning, an increasing number of international multilateral agencies are seeking partnership with ATPS. ATPS is seeing an increasing level of funding commitments by Donor Partners. Recommendations for ATPS Continued Growth and Effectiveness On-going reform of ATPS administrative structure to continue The on-going reforms that have taken place within the Board, Regional Secretariat, and at the National Chapter coordination levels are welcomed. Such reform should continue until fully functional corporate governance policy and practices are fully established and implemented across the ATPS governance structures. This will further strengthen ATPS to achieve the vision of being the leading STI policy brokerage organization in Africa. Although training in corporate governance has been carried out for all sectors of ATPS leadership structure in recent time, there is some evidence that these systems have not yet been fully implemented effectively within all the governance structures of the organization, especially at the Board and National chapter levels. Future training should emphasize practical application with exercises relevant to ATPS leadership structure from the Board to the National Chapter levels. Training on Transformational Leadership - Leading a Change Though a subject of intense debate amongst economists and social scientists, it is generally agreed that cultural mindsets and attitudes could enhance and/or hinder organizational progress. ATPS’s vision demands transformational leadership skills amongst its leaders from the Board members to the National Chapter Coordinators. To lead such a change, ATPS leaders must understand and avoid personal and cultural mindsets and value systems that hinder change, while embracing those that enhance it. It requires deliberate assessment of cultural, behavioural patterns that could hinder progress and the willingness to be recast into cultural and personal habits that make for progress. Improvement of relationship amongst the Board, Secretariat, and National Chapters A large number of ATPS members and stakeholders feel they do not have effective communications and/or access to Board, National Chapter Coordinators and Regional Secretariat activities. Effort should be made to improve the implementation of ATPS communication strategy to improve on information flows amongst the ATPS management and the members. The results of the survey and the FGDs suggest that progress has been made during the past two years in this direction, but more could be done to ensure effective flow of pertinent information to members following ATPS communications channels. Strategies for Increased Funding for National Chapters There is a big gap between the fundraising skills of the Regional Secretariat and those of the National Coordinators. In some cases, funds successfully raised by the Secretariat and disbursed to national chapters were not followed up with timely progress and financial reports by some national chapters. Adequate training in relevant skills required for effective interactions with STI key policy players should be conducted regularly for National Chapter coordinators and ATPS members. The ongoing training in grant writing should continue and be made continent-wide if funding permits. Funding of National Chapters should be strategic such that capacity in a specific area of research is built which, with time, will not only lead to a strong research capacity in that area, but also strengthen academic programmes. For example, a strong climate change programme is emerging at University of Nigeria Nsukka (UNN), with strong collaborations with Universities from neighbouring States. Strategies to Increase National Government buy-in and support for STI Translating STI research outcomes into policies requires a great deal of emotional intelligence, skills which are often lacking in the first and second generation universities. In the epoch of the science-based or 2GUs, governments were content with universities carrying out scientific research and providing scientific education. Now they desire to see universities as incubators of new science- or technology-based commercial activities, whether by existing firms or start-ups. Hence, governments demand that universities take an active and leading role in the exploitation of their knowledge and they are willing to make funds available to support such activities. Thus, for universities to gain the attention of national leadership they must become centres of excellence and explicit instruments of economic development in the knowledge-based economy. The universities must do this while working collaboratively with government departments, parastatals, and institutions and dedicated research establishments. ATPS should anticipate these shifting changes and devise programmes to assist both government and universities to relate effectively. New administrative structures in member organizations to sustain and manage the emerging STI multidisciplinary teams Second Generation universities (2GUs) tend to focus on pure science and often do not regard the application of their know-how as their task. In contrast, Third Generation Universities (3GUs) objectively stimulate techno-starters – students or academics – to pursue the exploitation or commercialisation of the knowledge they generate. They view this as being equal in importance to the objectives of scientific research and education. Administratively, research in the 2GU era was mainly monodisciplinary and departments were structured along disciplines. The emerging interdisciplinary scientific teams with focus on specific research areas functionally work against the current mono-disciplinary faculty-based, administrative structure of 2GUs. For interdisciplinary teams, the current faculty system is an obstacle. There is a need for new organisational forms for university management that can create responsibilities for the task of know-how exploitation. ATPS must anticipate this and begin to strategize solutions for their member institutions to transition to 3Gus administrative structure, otherwise ATPS growth will plateau, and progress achieved so far may be stunted.

Adaptive noise cancellation with fast tunable RBF network

This paper describes a novel adaptive noise cancellation system with fast tunable radial basis function (RBF). The weight coefficients of the RBF network are adapted by the multi-innovation recursive least square (MRLS) algorithm. If the RBF network performs poorly despite of the weight adaptation, an insignificant node with little contribution to the overall performance is replaced with a new node without changing the model size. Otherwise, the RBF network structure remains unchanged and only the weight vector is adapted. The simulation results show that the proposed approach can well cancel the noise in both stationary and nonstationary ANC systems.

Online modeling with tunable RBF network

In this paper, we propose a novel online modeling algorithm for nonlinear and nonstationary systems using a radial basis function (RBF) neural network with a fixed number of hidden nodes. Each of the RBF basis functions has a tunable center vector and an adjustable diagonal covariance matrix. A multi-innovation recursive least square (MRLS) algorithm is applied to update the weights of RBF online, while the modeling performance is monitored. When the modeling residual of the RBF network becomes large in spite of the weight adaptation, a node identified as insignificant is replaced with a new node, for which the tunable center vector and diagonal covariance matrix are optimized using the quantum particle swarm optimization (QPSO) algorithm. The major contribution is to combine the MRLS weight adaptation and QPSO node structure optimization in an innovative way so that it can track well the local characteristic in the nonstationary system with a very sparse model. Simulation results show that the proposed algorithm has significantly better performance than existing approaches.