varunr14/newsummary huggingface dataset:
Computational complexity and power consumption are prominent issues in wireless telemonitoring applications involving physiological signals . Because of its energy efficient data reduction procedure compressed sensing emerged as a promising framework to address these challenges . In this work a multi channel CS framework is explored for multi channel electrocardiogram signals . The work focuses on the successful joint recovery of the MECG signals using a low number of measurements by exploiting the correlated information across the channels . A CS recovery algorithm based on weighted mixed norm minimization is proposed that exploits the joint sparsity of MECG signals in the wavelet domain and recovers signals from all the channels simultaneously . The proposed WMNM algorithm follows a weighting strategy to emphasize the diagnostically important MECG features . Experimental results on various MECG databases show that the proposed method can achieve superior reconstruction quality with high compression efficiency as compared to its non weighted counterpart and other existing CS based ECG compression techniques . 


Summary: A weighted mixed norm minimization based joint sparse recovery algorithm is proposed for multichannel ECG signals. Algorithm aims to improve the joint signal recovery in compressed sensing based WBAN applications. It is based on a weighing rule that emphasizes the clinically important ECG features. Required measurements could be reduced significantly without compromise with the reconstruction accuracy. The approach leads to higher compression efficiency with reduced on node computations and power consumptions in resource constrained WBANs.
An economical and portable on line motor condition monitoring system based on an advanced microprocessor with a graphic user interface for abnormality detection is described. Both electrical and vibrational signal analysis for fault detection of motors were applied. A Cortex M4 microcontroller and its built in high speed analog to digital converter were used to process the on line voltage current and vibration signals of the motors during operation. The acquired signals were digitally filtered through an infinite impulse filter and then fast Fourier transform for spectral analysis was applied for abnormal pattern recognition. The analytic results were displayed in real time on an embedded touch screen monitor to instantly provide users with the motor s operational conditions. Finally a prototype was devised and verified through onsite experimentation. Comparing the results to commercial tools showed similar spectral characteristics the difference for electrical and vibration signals was less than 10 . Thus the system proposed shows promising ability and feasibility for online use. 


Summary: A set of economical handheld online real time data acquisition devices for motor abnormal detection based on vibrational and electrical detection methods was developed. The errors of analysis results from electrical and vibration signal were less than 10 comparing our proposed device with commercial industrial computer. This is a low cost small size and simple use motor condition monitoring system.
The main challenge in image denoising is how to preserve the information such as edges and textures to get satisfactory visual quality when improving the signal to noise ratio . In this paper we propose a hybrid filter bank for denoising based on wavelet filter bank and quincunx diamond filter bank . The noisy image is decomposed into different subbands of frequency and orientation using DMeyer wavelet . The quincunx diamond filter bank is designed from finite impulse response filters using Kaiser window which is applied on the detail subband of wavelet filter bank . The directional subband coefficients are modeled with Gaussian scale mixture model . The Bayes least squares estimator is used to obtain the denoised detail coefficients from the noisy image decomposition . Experimental results show that the new method performs spatial averaging without smoothing edges and thereby enhances the visual quality and peak signal to noise ratio . 


Summary: We propose a new denoising algorithm using wavelet and quincunx diamond filter bank. The subband coefficients are modeled with Gaussian scale mixture model. Bayes least means square is used to obtain the denoised coefficients. The new method does spatial averaging without smoothing the edges.
This paper explores the application of maximum entropy methods to time harmonic acoustic problems . Max ent basis functions are mesh free approximants that are constructed observing an equivalence between basis functions and discrete probability distributions and applying Jaynes s maximum entropy principle . They are continuous and therefore they are particularly suited for the resolution of Helmholtz problems where classical finite element methods show a poor accuracy in the high frequency region . In addition it was recently shown that max ent approximants can be blended with isogeometric basis functions on the boundary of the domain . This preserves the correct representation of the boundary like in Isogeometric Analysis with the advantage that the discretization of the interior of the domain is straightforward . In this paper the max ent mathematical formulation is reviewed and then some numerical applications are studied including a 2D car cavity geometry defined by B spline curves . In all cases if the same nodal discretization is used finite elements results are significantly improved . 


Summary: Time harmonic acoustic problems are simulated with maximum entropy meshless methods. Maximum entropy basis functions handle dispersion errors better than finite elements. Short wavelength propagation problems can be studied with coarser discretizations. A blending with Isogeometric functions is possible on the boundary of the domain. Several examples are studied including a 2D car cavity model defined by B Splines.
The multifaceted nature of cyber physical systems needs holistic study methods to detect essential aspects and interrelations among physical and cyber components . Like the systems themselves security threats feature both cyber and physical elements . Although to apply divide et impera approaches helps handling system complexity to consider just one aspect at a time does not provide adequate risk awareness and hence does not allow to design the most appropriate countermeasures . To support this claim in this paper we provide a joint application of two model driven techniques for physical and cyber security evaluation . We apply two UML profiles namely SecAM and CIP VAM in combination . In such a way we demonstrate the synergy between both profiles and the need for their tighter integration in the context of a reference case study from the railway domain . 


Summary: Cyber physical systems need holistic methods to discover relationships between physical and cyber components. Security threats attempt to both physical and cyber elements. Model driven techniques accounting for joint physical and cyber security modelling and evaluation are explored. Synergies between physical and cyber security UML profiles remarked in a case study of the railway domain.
To enhance confidentiality and reduce the number of arrayed waveguide grating routers a dynamic scrambling scheme is proposed in which cyclic and free spectral range properties of AWG routers are employed to use a maximal length sequence code as the signature address code . In this paper a changing codeword mechanism is presented in which a flexible dynamic scrambling algorithm is embedded in the encoding and decoding codebook to control the state of both the wavelength and spatial optical switch matrices . Hence the code family and code changing flexibility of the proposed scheme increases substantially because of the multiple effects of the wavelength and spatial switch matrices . Compared with the existing dynamic reconfigurable AWG based schemes without multiple changing codewords in the FSR groups and spatial domains the confidentiality of the proposed scheme is approximately 104 times higher than that of schemes without scrambling codeword mechanisms . 


Summary: Scrambling cryptography with 2 D wavelength spatial scheme in physical layer. Increasing cardinality with cyclic and FSR property of shared AWG router. Evaluating the power assumption to prove feasible wavelength spatial network. Larger cardinality and dynamic scrambling improve significantly FTTx security. Dynamic scrambling is superior to traditional scheme using confidential analysis.
In this paper the performance of a turbo coded triply Polarized multiple input multiple output MIMO aided Code Division Multiple Access CDMA is investigated for Stanford University Interim SUI and Long term Evolution LTE channel model specifications. The minimum mean square error algorithm based on ordered successive interference cancellation OSIC Multi user detection MUD technique is implemented at each mobile station for diminishing the effects of multi stream interference MSI . We observe from the simulation results that a better bit error rate BER performance with less signal to noise ratio SNR is exhibited by our considered coded system in comparison with an un coded system. The simulation results reveal that the MIMO CDMA system with triply Polarized antenna structure requires a higher SNR than a uni Polarized antenna system for achievement of the same BER. However it provides the advantage of replacement of three uni polarized antennas by a single triply Polarized antenna thereby achieves a higher data rate with reduced size of MS. 


Summary: We investigate the BER performance of turbo coded MIMO CDMA system using polarization diversity for DL transmission. Performance is analyzed using MMSE OSIC algorithm when communicating over SUI and LTE channel models specifications. BER Performance of turbo coded MIMO system is compared with uncoded system and Found that coded system provides superior performance. Our considered coded triply Polarized MIMO CDMA system achieves higher data rate with reduced size of Mobile unit.
Modalities other than GPS need to be employed to localize mobile sensor node enabled subjects in indoor conditions . The location of some mobile nodes needs to be computed precisely while this may not be essential for the remaining nodes . We have proposed the concept of graded precision localization which allows mobile nodes to localize themselves to heterogeneous precision levels in a common framework . With graded precision localization we define a modular node for the subjects specify deployment strategies customizable for each site and propose a framework for evaluating site specific localization performance . We comprehensively evaluate graded precision localization with experiments and simulation for indoor conditions and highlight its advantages over similar systems . 


Summary: Graded precision localization GPL offers a range of localization precision levels. GPL for user modules is achieved with an infrastructure of hotspots and radio nodes. A user module prototype is built with a laptop a Cricket node and a mobile phone. Performance of GPL for indoor spaces is discussed with simulation and experiments. An analytical Markov model for evaluating GPL for constrained spaces is proposed.
The wireless sensor networks deployed in hostile environments suffer from a high rate of node failures . Such failures may convert a fully connected sensor network into multiple disjoint sub networks leading to the network partition problem . The placement of relay nodes is the only way to restore the lost connectivity because these devices compared to the sensor nodes have a higher energy backup with a longer communication range . In this paper a new solution is proposed to heal the network partition problem in the wireless sensor network . The solution is based on a zero gradient point inside the convex hull polygon . The proposed solution is compared with various naive approaches along with existing state of the art solutions that is the Spider Web 1C heuristic and Steiner minimum tree based optimal relay node placement algorithm . The simulation experiment results confirm the effectiveness of our proposed approach . 


Summary: Two naive approaches and two state of the art heuristics are implemented along with our proposed solution to recover the lost connectivity of the partitioned WSN. The proposed solution considers a global zero gradient point inside the convex hull polygon. The proposed solution works perfectly for any number of disjoint segments. The proposed solution shows better performance compared to the other well known state of the art approaches.
Service composition is an evolving approach that increases the number of applications of cloud computing by reusing existing services . However the available methods focus on generating composite services from a single cloud which limits the benefits that are derived from other clouds . This paper proposes a novel COMbinatorial optimization algorithm for cloud service COMposition that can efficiently utilize multiple clouds . The proposed algorithm ensures that the cloud with the maximum number of services will always be selected before other clouds which increases the possibility of fulfilling service requests with minimal overhead . The experimental results demonstrate that the COM2 successfully competes with previous multiple cloud service composition algorithms by examining a small number of services which directly relates to execution time without compromising the number of combined clouds . 


Summary: The COM2 algorithm efficiently considers multiple clouds while composing services. The proposed algorithm successfully competes with previous algorithms. Low examined service number is achieved without impacting the combined cloud number.
This work studies a digital hardware implementation of a radial basis function neural network RBF NN Firstly the architecture of the RBF NN which consists of an input layer a hidden layer of nonlinear processing neurons with Gaussian function an output layer and a learning mechanism is presented. The supervising learning mechanism based on the stochastic gradient descent SGD method is applied to update the parameters of RBF NN. Secondly a very high speed IC hardware description language VHDL is adopted to describe the behavior of the RBF NN. The finite state machine FSM is applied for reducing the hardware resource usage. Thirdly based on the electronic design automation EDA simulator link a co simulation work by Simulink and ModelSim is applied to verify the VHDL code of RBF NN. Finally some simulation cases are tested to validate the effectiveness of the proposed digital hardware implementation of the RBF NN. 


Summary: A high accuracy method to compute the Gaussian function in the radial basis function neural network RBF NN is proposed. The computational accuracy of the propose method in the Gaussian function and the overall RBF NN can reach up10 6 10 7. Fast computational ability for a complicated RNF NN is presented by using the digital hardware implementation. Succeed in making the co simulation environment between Simulink and ModelSim to verify the correctness and the effectiveness of the VHDL Very high speed IC Hardware Description Language code for a 3 5 1 RBF NN. The application of the VHDL code for a 3 5 1 RBF NN to the dynamic identification in the linear system and the PMSM drive system are successfully demonstrated.
This paper introduces a new fast integer based algorithm to convert the RGB color representation to HSV and vice versa . The proposed algorithm is as accurate as the classical real valued one . The use of only integer operations increases performance and portability . Performance measurement results show a speed gain of about two times when compared with the classical C language implementation on PC platforms . Lookup tables are not involved thus the memory usage is minimal . The resulting HSV color can be packed into 48 bits . The proposed method can safely replace the commonly used floating point implementation . 


Summary: Conversion algorithm between 24 bit RGB and integer HSV is proposed. The algorithm is as accurate as the classical real valued one. Performance measurement results show a speed gain of about two times. The resulting HSV color can be packed into 48 bits. Floating point variables and Lookup tables are not used.
Cognitive radio is an emerging technology in wireless communications for dynamically accessing under utilized spectrum resources . In order to maximize the network utilization vacant channels are assigned to cognitive users without interference to primary users . This is performed in the spectrum allocation module of the cognitive radio cycle . Spectrum allocation is a NP hard problem thus the algorithmic time complexity increases with the cognitive radio network parameters . This paper addresses this by solving the SA problem using Differential Evolution algorithm and compared its quality of solution and time complexity with Particle Swarm Optimization and Firefly algorithms . In addition to this an Intellectual Property of DE based SA algorithm is developed and it is interfaced with PowerPC440 processor of Xilinx Virtex 5 FPGA via Auxiliary Processor Unit to accelerate the execution speed of spectrum allocation task . The acceleration of this coprocessor is compared with the equivalent floating and fixed point arithmetic implementation of the algorithm in the PowerPC440 processor . The simulation results show that the DE algorithm improves quality of solution and time complexity by 29.9 and 242.32 19.04 and 46.3 compared to PSO and Firefly algorithms . Furthermore the implementation results show that the coprocessor accelerates the SA task by 76.79 105 and 5.19 6.91 compared to floating and fixed point implementation of the algorithm in PowerPC processor . It is also observed that the power consumption of the coprocessor is 26.5mW . 


Summary: To maximize the network utilization spectrum allocation technique fairly allocates the channels to secondary users. SA problem is solved by Differential Evolution algorithm and compared the performance with PSO and FA. DE improved the quality of solution and time complexity by 29.9 242.32 and 19.04 46.3 compared to PSO and FA. We propose FPGA based coprocessor for DE SA IP and interfaced to PowerPC. The coprocessor accelerates SA task by 76.79 105x and 5.19 6.91x compared to float and fixed DE SA software.
Graphical abstract Image graphical abstract interfacial area gas concentration drag coefficient bubble induced turbulence parameter bubble induced turbulence parameter first experimental model constant for dissipation rate second experimental model constant for dissipation rate gas bubble diameter diffusion coefficient E tv s number gravity vector Henry s constant turbulent kinetic energy mass transfer coefficient mass transfer rate from gas to liquid gas molecular weight bubbles per volume pressure reference pressure ideal gas constant bubble induced turbulence temperature gas phase velocity liquid phase velocity slip velocity volume fraction of gas volume fraction of the liquid phase gradient operator gas density liquid density liquid dynamic viscosity turbulent or eddy viscosity surface tension coefficient Prandtl number for kinetic energy Prandtl number for dissipation rate turbulent dissipation rate 


Summary: The Euler Euler method was used to model the flow mixing inside a carbonating tank. Carbonation process increased at high gas and water inlet velocities. L shaped nozzle design increased the carbonation process. Mass transfer coefficient increased with the increase of the inlet gas velocities. Carbonation process was improved with the use of small gas bubbles.
The analysis of the surface Electrocardiogram is the most extended non invasive technique in cardiological diagnosis . The ectopic beats are heart beats remarkably different to the normal beat morphology that provoke serious disturbances in electrocardiographic analysis . These beats are very common in atrial fibrillation causing important residua when ventricular activity has to be removed for atrial activity analysis . These beats may occur in both normal subjects and patients with heart disease and their presence represents an important source of error which must be handled before any other analysis . In this work a method is proposed to cancel out ectopics by classification between normal and abnormal beats . The systems is based on Radial Basis Function Neural Network . This new approach is compared to state of the art techniques for the ectopic classification and cancellation in the MIT database . The results clearly demonstrated the improved ECG beats classification accuracy compared with other alternatives and a very accurate reduction of ectopic beats together with low distortion of the QRST complex . 


Summary: A method based on radial basis function system for cancelling out ectopic beat by classification between normal and abnormal beats is proposed. The proposed solution addresses for ECG recordings. Several experiments have demonstrated the enhancement of the proposed method in comparison to other techniques. The results suggest that clinical information can be maintained. This method provides the best approach for obtaining both ectopic beat reduction and low distortion of the signal recordings.
Nowadays intelligent and pervasive environments are characterized by a great number of devices and sensors that develop continuously and capture enormous amounts of data . Designing a context aware system able to provide the most tailored services to users according to their behaviors preferences and needs is still a research challenge . In such environments although the context is very complex dynamic and full of data captured and produced users aspire to automatically receive contextualized services . The Cultural Heritage domain represents a domain where exchanged and produced data can be opportunely exploited by a set of applications and services in order to transform a static space into a smart environment . In this perspective this paper presents a context aware system named Context Evolution System able to represent and manage the evolution of the context through its instances such an evolution is driven by occurring events and opportunely modeled by a graph structure . To assess the proposed solution a Cultural Heritage case study of a real temporary art exhibition named the Beauty or the Truth and located in Naples is presented and discussed . 


Summary: Model the context evolution by means of a graph approach. Design a Context Evolution System CES to manage the context evolution and the consequently tailoring of data and services. Improve user experience by means of this kind of system. Our apporach is suitable within the Cultural Heritage domain.