Digital system algorithms such as FFT algorithms, convolution, image processing algorithm, etc. deploy Multiply and Accumulate (MAC) unit as an evaluative component. The efficiency of a MAC typically relies on the speed of operation, power dissipation, and chip area along with the complexity level of the circuit. In this research paper, a power-delay-efficient signed-floating-point MAC (SFMAC) is proposed using Universal Compressor based Multiplier (UCM). Instead of having a complex design architecture, a simple multiplexer-based circuit is used to achieve a signed-floating output. The 8£8 SFMAC can take 8-bit mantissa and 3-bit exponent and therefore, the input to the SFMAC can be in the range of –(7.96875)₁₀ to +(7.96875)₁₀. The design and implementation of the proposed architecture is executed on the Cadence Spectre tool in GPDK 90 nm and TSMC 130 nm CMOS, which proves as power and delay efficient.

In this paper, a low power highly sensitive Triple Metal Surrounding Gate (TM-SG) Nanowire MOSFET photosensor is proposed which uses triple metal gates for controlling short channel effects and III–V compound as the channel material for effective photonic absorption. Most of the conventional FET based photosensors that are available use threshold voltage as the parameter for sensitivity comparison but in this proposed sensor on being exposed to light there is a substantial increase in conductance of the GaAs channel underneath and, thereby change in the subthreshold current under exposure is used as a sensitivity parameter (i.e., I_illumination/I_Dark). In order to further enhance the device performance it is coated with a shell of Al_xGa_1-xAs which effectively passivates the GaAs surface and provides a better carrier confinement at the interface results in an increased photoabsorption. At last performance parameters of TM-SG Bare GaAs Nanowire MOSFET are compared with TM-SG core-shell GaAs/AlGaAs Nanowire MOSFET and the results show that Core-Shell structures can be a better choice for photodetection in visible region.

This study attempted to examine the impacts of academic locus of control and metacognitive awareness on the academic adjustment of the student participants. The convenient sampling was applied to select the sample of 368 participants comprising 246 internals with age ranging from 17 to 28 years (M = 20.52, SD = 2.10) and 122 externals with age spanning from 17 to 28 years (M = 20.57, SD = 2.08). The findings indicated that there were significant differences in the various dimensions of metacognition, academic lifestyle and academic achievement of the internals and externals except for academic motivation and overall academic adjustment. There were significant gender differences in declarative knowledge, procedural knowledge, conditional knowledge, planning, information management, monitoring, evaluation and overall metacognitive awareness. Likewise, the internals and externals differed significantly in their mean scores of declarative knowledge, procedural knowledge, conditional knowledge, planning, information management, monitoring, debugging, evaluation and overall metacognitive awareness, academic lifestyle and academic achievement. The significant positive correlations existed between the scores of metacognitive awareness and academic adjustment. It was evident that the internal academic locus of control and metacognitive awareness were significant predictors of academic adjustment of the students. The findings have been discussed in the light of recent findings of the field. The findings of the study have significant implications to understand the academic success and adjustment of the students and thus, relevant for teachers, educationists, policy makers and parents. The future directions for the researchers and limitations of the study have also been discussed.

The goal of this research is to achieve close to real-time dynamics performance for allowing auto-pilot in-the-loop testing of unmanned ground vehicles (UGV) for urban as well as off-road scenarios. The overall vehicle dynamics performance is governed by the multibody dynamics model for the vehicle, the wheel/terrain interaction dynamics and the onboard control system. The topic of this paper is the development of computationally efficient and accurate dynamics model for ground vehicles with complex suspension dynamics. A challenge is that typical vehicle suspensions involve closed-chain loops which require expensive DAE integration techniques. In this paper, we illustrate the use the alternative constraint embedding technique to reduce the cost and improve the accuracy of the dynamics model for the vehicle.