Cloud-oriented emotion feedback-based Exergames framework

Exergames platform can be more appealing to the users if they can interact with emotion. Therefore, in this paper, we propose an automatic emotion recognition system from speech to be embedded in the Exergames platform. While playing and doing exercise, the user expresses his or her feeling by uttering some phrases. The speech is recorded by an omnidirectional mic and transmitted to an emotion recognition server in a cloud environment, where the emotion (e.g. happy, sad or neutral) is recognized. For the recognition, we use MPEG-7 low-level audio features and a Gaussian mixture model based classifier. A tactile vibration is generated based on the emotion and feedback to the user for a real feeling. The user can thus have an instantaneous vibrational feeling based on his or her satisfaction. The recognized emotion can also be used as the user’s satisfaction of the framework on the fly without the need of a survey session. The experimental study and performance comparison show that the proposed framework has positive effects on the perception of physical activities.     

Information hiding in edges: A high capacity information hiding technique using hybrid edge detection

The multimedia security is becoming more and more important as the data being exchanged on the Internet is increasing exponentially. Though cryptography is one of the methods which is used to secure the data during transit, but the camouflaged appearance of the scrambled data alerts the adversary about some critical information being shared. In such a scenario, steganography has been used as an alternate solution to secure the secret information. In this paper a color image steganographic algorithm based on hybrid edge detection is proposed. The color image is partitioned into constituent Red (R), Green (G) and Blue (B) planes. Hybrid edge detection is used for finding the edge and non-edge pixels of Green and Blue planes of cover image. The Green and Blue planes are used for hiding the data while Red plane holds the pixel status (whether edge or non-edge) of these planes. The RC4 encryption algorithm is used to encrypt secret message before embedding it in the cover image to enhance security of the secret data. A fragile watermark/logo (whose size is less than 1% of total secret data) has been embedded, besides secret data in the cover image, to facilitate content authentication and early tamper detection. At the receiver, firstly logo is extracted. If it is same as one embedded at transmitter, indicating that secret data has not been altered during transit, secret data is extracted. Otherwise (if extracted logo is not same as used at input) the receiver does not waste critical time to extract compromised data but sends an automatic retransmission request. Experimental investigations reveal that the proposed scheme is capable of providing high quality of stego-images for a fairly high pay load. A comparison of the proposed technique with some state of art schemes substantiates the above arguments.     

Application of SNPs to improve yield of Pisum sativum L. (pea)

Nanotechnology opens an enormous scope of novel application in the fields of biotechnology and agricultural industries, because nanoparticles (NPs) have unique physicochemical properties, i.e. high surface area, high reactivity, tunable pore size and particle morphology. Present study was carried out to determine the role of silver NPs (SNPs) to improve yield of Pisum sativum L. SNPs (10–100 nm) were synthesised by green method using extract of Berberis lycium Royle. Pea seeds were soaked and seedling were foliage sprayed by 0, 30, 60 and 90 ppm SNPs. The experiment was arranged as split–split plot randomised complete block design with three replicates. The application of SNPs enhanced significantly number of seeds pod⁻¹, number of pods plant⁻¹, hundred seed weight, biological yield and green pod yield over control. The highest yield was found when 60 ppm SNPs were applied. However, exposure to 90 ppm SNPs, the yield of the pea decreased significantly as compared with 30 and 60 ppm. This research shows that SNPs have definite ability to improve growth and yield of crops. Nevertheless, a comprehensive experimentation is needed to establish the most appropriate concentration, size and mode of application of SNPs for higher growth and maximum yield of pea.Inspec keywords: nanobiotechnology, silver, nanoparticles, cropsOther keywords: Ag, foliage spraying, crop yield, crop growth, green pod yield, biological yield, seed weight, pod plant number, seed pod number, pea seeds, Berberis lycium Royle extract, green method, nanotechnology, Pisum sativum L, silver nanoparticles     

Electrochemical Mechanism Investigation of Cu2MoS4 Hollow Nanospheres for Fast and Stable Sodium Ion Storage

Sodium ion batteries (SIBs) are promising alternatives to lithium ion batteries with advantages of cost effectiveness. Metal sulfides as emerging SIB anodes have relatively high electronic conductivity and high theoretical capacity, however, large volume change during electrochemical testing often leads to unsatisfactory electrochemical performance. Herein bimetallic sulfide Cu₂MoS₄ (CMS) with layered crystal structures are prepared with glucose addition (CMS1), resulting in the formation of hollow nanospheres that endow large interlayer spacing, benefitting the rate performance and cycling stability. The electrochemical mechanisms of CMS1 are investigated using ex situ X‐ray photoelectron spectroscopy and in situ X‐ray absorption spectroscopy, revealing the conversion‐based mechanism in carbonate electrolyte and intercalation‐based mechanism in ether‐electrolyte, thus allowing fast and reversible Na⁺ storage. With further introduction of reduced graphene oxide (rGO), CMS1–rGO composites are obtained, maintaining the hollow structure of CMS1. CMS1–rGO delivers excellent rate performance (258 mAh g^?1 at 50 mA g^?1 and 131.9 mAh g^?1 at 5000 mA g^?1) and notably enhanced cycling stability (95.6% after 2000 cycles). A full cell SIB is assembled by coupling CMS1–rGO with Na₃V₂(PO₄)₃‐based cathode, delivering excellent cycling stability (75.5% after 500 cycles). The excellent rate performance and cycling stability emphasize the advantage of CMS1–rGO toward advanced SIB full cells assembly.     

Nonlinear and Adaptive Intelligent Control Techniques for Quadrotor UAV – A Survey

Parametric uncertainties and coupled nonlinear dynamics are inherent in quadrotor configuration and infer adaptive nonlinear approaches to be used for flight control system. Numerous adaptive nonlinear and intelligent control techniques, which have been reported in the literature for designing quadrotor flight controller by various researchers, are investigated in this paper. As a priori, each conventional nonlinear control technique is discussed broadly and then its adaptive/observer based augmentation is conferred along with all possible variants. Among conventional nonlinear control approaches, feedback linearization, backstepping, sliding mode, and model predictive control, are studied. Intelligent control approaches incorporating fuzzy logic and neural networks are also discussed. In addition to adaption based parametric uncertainty handling, various other aspects of each control technique regarding stability, disturbance rejection, response time, asymptotic, exponential and finite time convergence etc., are discussed in sufficient depth. The contribution of this paper is the provision of detailed and in depth discussion on quadrotor nonlinear control approaches to the flight control designers.     

A Composite State Convergence Scheme for Bilateral Teleoperation Systems

State convergence is a novel control algorithm for bilateral teleoperation of robotic systems. First, it models the teleoperation system on state space and considers all the possible interactions between the master and slave systems. Second, it presents an elegant design procedure which requires a set of equations to be solved in order to compute the control gains of the bilateral loop. These design conditions are obtained by turning the master-slave error into an autonomous system and imposing the desired dynamic behavior of the teleoperation system. Resultantly, the convergence of master and slave states is achieved in a well-defined manner. The present study aims at achieving a similar convergence behavior offered by state convergence controller while reducing the number of variables sent across the communication channel. The proposal suggests transmitting composite master and slave variables instead of full master and slave states while keeping the operator’s force channel intact. We show that, with these composite and force variables; it is indeed possible to achieve the convergence of states in a desired way by strictly following the method of state convergence. The proposal leads to a reduced complexity state convergence algorithm which is termed as composite state convergence controller. In order to validate the proposed scheme in the absence and presence of communication time delays, MATLAB simulations and semi-real time experiments are performed on a single degree-of-freedom teleoperation system.      

Development of a Predictive Equation for Modelling the Infiltration Process Using Gene Expression Programming

In this study, the soft computing technique of Gene expression programming (GEP) has been employed to generate a predictive equation of infiltration rate (f_p). Infiltration experiments were conducted at 124 different sites and soil samples were collected to assess various soil properties throughout the Himalayan lake catchment. Parameters determined from observed data using nonlinear-Levenberg Marquardt algorithm were substituted in Horton, Kostiakov and Philip infiltration models and f_p were predicted. Using soil data generated by laboratory investigation of soil samples, the GEP model was developed. Training and testing of the GEP model was performed using 70% and 30% of data respectively. Performance of GEP developed functional relationship was evaluated by comparing predictions from it and aforementioned infiltration models with field observed f_p, and by applying overall performance index (OPI) computed using Coefficient of Determination (R²), Nash–Sutcliffe Efficiency (E_NS), Willmott’s Index of Agreement (W), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). Expression developed using GEP indicated feasibility of developed equation with E_NS, R², W, RMSE and MAE of 0.84, 0.84, 0.96, 1.9, and 0.8, respectively for training data-set and 0.84, 0.85, 0.95, 1.2, and 0.95, respectively for testing data-set. Comparative analysis revealed that though with a slightly higher OPI value (0.7–0.8), the performance of conventional models is better compared to the GEP model (0.66) but the GEP model having satisfactory performance may be used for f_p prediction particularly in absence of observed data.

     

Conflict resolution using game theory and rough sets

Conflicts occur naturally in the real world at all levels of society, individually, in groups or society as a whole. Almost all the existing conflict resolution models are unilateral in their decision‐making process. They do not consider the actions of the involved parties simultaneously. Therefore, in this paper, we aim to design a novel conflict resolution model based on game‐theoretic rough sets by constructing a game between all the concerned parties (players), computing the payoff of different strategies and classifying them following equilibrium rules. The proposed model yields more realistic and accurate results as it explores all possibilities and is flexible in determining different threshold values relative to the complexities of real‐life problems. Three real‐life conflict situations are solved with the proposed model, and a comprehensive analysis is done to validate the effectiveness of the proposed approach.     

Digital Application of Second Order Generalized Integrator Based Grid Estimator Under Unbalanced and Distorted Voltage Conditions

Abstract

Frequency, amplitude, and phase information of the grid voltage are the main constraints for constructing a robust controller algorithm for grid connected applications under unbalanced and distorted voltage conditions. This paper narrates a simple, robust, straight forward method to estimate the instantaneous positive and negative sequence voltage components under unbalanced and distorted voltage circumstances. A second order generalized integrator (SOGI) is encapsulated to filter out the distorted voltage as well as to generate orthogonal voltage components for the three phases of AC grid. Furthermore, these filtered and orthogonal components are accounted for the calculation of instantaneous symmetrical components. Developed technique is more frequency adaptive compared to conventional phase locked loop (PLL) techniques. A set of test outcome results are provided in this paper based on MATLAB/Simulink simulations with real grid data captured from an industrial plant. Moreover, SOGI based estimator is digitally implemented by using dSPACE ds1103 digital controller to validate the numerical simulation results in accordance with the developed theoretical prediction.