Intermetallic growth between lead-free solders and palladium

Intermetallic growth between Pd and the lead-free solders Sn-Ag and Sn-Ag-Cu has been studied. Diffusion couples were prepared by reflowing the solders on Pd and then aging the couples at 156°C, 175°C, 195°C, and 210°C. At the higher temperatures of 175°C, 195°C, and 210°C, PdSn₄ made up most of the layer that grew between the solders and the Pd, although small regions of second phases were always found in the PdSn₄ matrix, and it was sometimes possible to identify discontinuous regions of PdSn₃ next to the Pd. The thickness of the intermetallic layer increased with the square root of time, consistent with diffusion-controlled growth. In couples annealed at 156°C, the morphology of the PdSn₃ phase and growth kinetics differed depending on the composition of the solder.     

Effect of Primary Silicon Refinement on Mechanical and Wear Properties of a Hypereutectic Al-Si Alloy

Silicon - This study explores the effect of primary silicon refinement of hypereutectic Al-Si alloy on the mechanical and wear properties. Refinement has been carried out by purging N2 into...     

A hierarchy in mutation of genetic algorithm and its application to multi-objective analog/RF circuit optimization

This paper presents a multi-objective analog circuit design optimization tool using genetic algorithm based on hierarchical mutation scheme. The idea is to improve the convergence and diversity of genetic algorithm by incorporating hierarchy during polynomial mutation operation. In this regard, a theoretical framework of proposed genetic algorithm is presented using Markov chain principle. To investigate the effectiveness of hierarchy in polynomial mutation operator, the scheme is compared with six different mutation strategies. Experiments are performed for different function evaluations to evaluate the performance of hierarchical polynomial mutation operator. Further, to showcase the improvement in genetic algorithm, numerous experiments are performed on twelve different test functions and two design examples. The proposed genetic algorithm shows competitive performance over other standard optimization techniques in terms of both convergence and diversity of solutions.     

Low power analog comb filter for biomedical applications

An analog topology is proposed to implement a comb filter for removal of power-line interference from various low-amplitude biomedical signals. In this proposed methodology, an n-number of all-pass filters (APFs) and an adder circuit are used to suppress n-number of frequencies. All the APFs as well as the adder circuit are designed using a current conveyor to utilize the various properties of the current-mode circuits. The active and passive components used to design the comb filter include second-generation current conveyor (CCII±), resistor, and capacitor. The circuit is designed for n?=?4 to remove the power-line frequency of 50 Hz, and its three odd harmonics such as 150 Hz, 250 Hz, and 350 Hz. A PSPICE simulation is done to verify the performance of the proposed circuit. In simulation, all CCII±?are designed using macro model of commercially-available current feedback operational amplifier integrated circuit (IC) AD844 as well as dynamic threshold voltage metal oxide semiconductor technology. The proposed circuit is also implemented also using commercially available IC AD844 on breadboard for n?=?3. The output result on digital storage oscilloscope confirm the effectiveness of the proposed comb filter circuit in removing the power line interference i.e. the power-line frequency and its odd harmonics.     

QoE Aware IoT Application Placement in Fog Computing Using Modified-TOPSIS

Mobile Networks and Applications - Over the years, fog computing has emerged as a paradigm to complement the cloud computing in handling the delay sensitive IoT applications in a better manner....     

Publicly verifiable watermarking scheme for intellectual property protection using quantum Chaos and bit plane complexity slicing

Intellectual Property such as music, painting, videos and other similar works being broadcasted on web need to be protected against copyright infringement to ensure the rights of their legitimate owners. Moreover, their users must also be sure of the originality of these artefacts. Both these problems can be solved through proper authentication on behalf of the creator. For this purpose, various publicly verifiable watermarking schemes have been available in literature. Recent proposal, in this domain, is based on chaos theory and Secured Hashing Algorithms SHA-2. Due to tremendous growth in the availability of Intellectual Property on the web and associated breaches it becomes a mandatory requirement to update these authenticating schemes. This paper proposes the usage of some more secure, reliable and efficient components in watermarking schemes than being used at present. Proposed changes include the deployment of encryption scheme based on Quantum Logistic maps instead of current Chaos encryption based on peter de-jong map, in order to optimise randomness, correlation and time complexity. For better security and efficiency in hardware implementation SHA-3 is a better choice than SHA-2. Data embedding can be done in regions where imperceptibility is quite high. The proposed changes can result in the creation of more reliable and efficient system. To test the hypothesis, proposed mechanism has been implemented in MATLAB-16a and various performance metrics such as correlation coefficient, PSNR, UIQI, SSIM have been measured. The results show that proposed scheme outperforms its counterpart in terms of all the performance metrics.     

Enhanced Ultrafast Nonlinear Optical Response in Ferrite Core/Shell Nanostructures with Excellent Optical Limiting Performance

Nonlinear optical nanostructured materials are gaining increased interest as optical limiters for various applications, although many of them suffer from reduced efficiencies at high‐light fluences due to photoinduced deterioration. The nonlinear optical properties of ferrite core/shell nanoparticles showing their robustness for ultrafast optical limiting applications are reported. At 100 fs ultrashort laser pulses the effective two‐photon absorption (2PA) coefficient shows a nonmonotonic dependence on the shell thickness, with a maximum value obtained for thin shells. In view of the local electric field confinement, this indicates that core/shell is an advantageous morphology to improve the nonlinear optical parameters, exhibiting excellent optical limiting performance with effective 2PA coefficients in the range of 10^?12 cm W^?1 (100 fs excitation), and optical limiting threshold fluences in the range of 1.7 J cm^?2. These values are comparable to or better than most of the recently reported optical limiting materials. The quality of the open aperture Z‐scan data recorded from repeat measurements at intensities as high as 35 TW cm^?2, indicates their considerably high optical damage thresholds in a toluene dispersion, ensuring their robustness in practical applications. Thus, the high photostability combined with the remarkable nonlinear optical properties makes these nanoparticles excellent candidates for ultrafast optical limiting applications.     

Performance enhancement of BPSK-SIM- and DPSK-SIM-based FSO downlink over atmospheric turbulence using aperture averaging and receiver diversity

In this paper, we evaluate the bit error rate (BER) performance of a free-space optical satellite downlink by considering the atmospheric turbulence effects using binary shift keying subcarrier intensity modulation and differential phase shift keying subcarrier intensity modulation (DPSK-SIM). The performance of the link is enhanced using aperture averaging and receiver diversity. The closed form mathematical expressions of BER for BPSK-SIM and DPSK-SIM schemes are derived and analyzed. It is observed that on varying the turbulence level, the performance of the link degrades when the turbulence level increases. The improved BER of 10^?12 and 10^?10 at signal-to-noise ratio of 30 dB of the link for both BPSK-SIM and DPSK-SIM is obtained by using aperture averaging (aperture diameter, D?=?10 cm) and receiver diversity with optimal combining.

     

An effective implementation and assessment of a random forest classifier as a soil spatial predictive model

Mapping the spatial distribution of soil classes is important for informing soil use and management decisions. This study aimed to effectively implement Random Forest (RF) model and to evaluate the behaviour and performance of the model for soil classification of Indian districts. Soil-forming factors, known as ‘scorpan,’ are selected as environmental covariates to tune RF model to classify 11 different soil categories. Thirty-five digital layers are prepared using different satellite data [ALOS (Advanced Land Observing Satellite) digital elevation model, Landsat-8, Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index product, RISAT-1 (Radar Imaging Satellite-1), Sentinel-1A] and climatic data (precipitation and temperature) to represent scorpan environmental covariates in the study area. The RF parameters corresponding to highest Cohen’s kappa coefficient (κ) value and lowest number of random split variables are considered optimum values for RF model. Model behaviour evaluation is based on mapping accuracy, sensitivity to data set size, and noise. Two other machine-learning methods, CART (Classification and Regression Tree) decision tree (CDT) and CART ensemble bagger (CEB), are used to provide the comparative study. To access behaviour of models to the false data set, noise in training set is produced by assigning a false class to the training set in 5% increment. Comparative performance of RF model is based on quality assessment measures. To evaluate the performance of models, marginal rates, F-measure, and Jaccard’s coefficient of the community, classification success index and agreement coefficients are selected under quality assessment measures. The score is calculated to rank the algorithm. RF model shows high stability against data set reduction in comparison to other methods. The results show that the abrupt change in accuracy is only observed after 60% training data reduction in RF model; however, significant decrease in accuracy can be noted after 45% and 25% data reduction in CEB and CDT, respectively. The RF model shows comparatively the greater resistance to noise. Overall, RF model has performed better than CDT and CEB to classify soil categories in the study area. The results of this research provide new insights into the performance of RF in the context of soil class mapping.     

Learning Uncertainty in Ocean Current Predictions for Safe and Reliable Navigation of Underwater Vehicles

Operating autonomous underwater vehicles (AUVs) near shore is challenging—heavy shipping traffic and other hazards threaten AUV safety at the surface, and strong ocean currents impede navigation when underwater. Predictive models of ocean currents have been shown to improve navigation accuracy, but these forecasts are typically noisy, making it challenging to use them effectively. Prior work has explored the use of probabilistic planners, such as Markov decision processes (MDPs), for planning in these scenarios, but prior methods have lacked a principled way of modeling the uncertainty in ocean model predictions, which limits applicability to cases in which high fidelity models are available. To overcome this limitation, we propose using Gaussian processes (GPs) augmented with interpolation variance to provide confidence measures on predictions. This paper describes two novel planners that incorporate these confidence measures: (1) a stationary risk‐aware GPMDP (for low‐variability currents), and (2) a nonstationary risk‐aware NS‐GPMDP (for faster and high‐variability currents). Extensive simulations indicate that the learned confidence measures allow for safe and reliable operation with uncertain ocean current models. Field tests of the planners on Slocum gliders over several weeks in the ocean demonstrate the practical efficacy of our approach.