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This paper presents a nano-second scale dynamic voltage scaler (DVS) based on charge-pump and binary weighted Digital-to-Analog Converter (BW-DAC). The charge redistribution BW-DAC can rapidly generate the desired output voltage based on digital input code. Also, it enables us to generate fine-grain voltage steps based on the conversion ratio of the DAC. The charge-pump circuit maintains the output voltage of the DAC when the voltage decreases due to the load circuit is drawing current from the DAC. The proposed architecture has been implemented using a 130 nm CMOS process. The measurement results of the proposed 6-bit DVS architecture show an accurate 64 output voltage levels from 0V to 1.476 V with an input voltage of 1.5 V. It shows an efficiency of 84% and a ripple voltage of as small as 24.6 mV. It shows nano-second settling time of 83.6 nS.

This paper presents efficient double-noise suppression techniques for large form-factor mutual-capacitance touch screen panels (TSPs). Different carrier frequencies are applied to TSP concurrently using orthogonal frequency division multiplexing (OFDM), while the sensing lines are sensed sequentially. The proposed technique ensures a high frame scan rate by using simultaneous driving signals, and it provides a high signal to noise ratio (SNR) by avoiding frequency band with high noise power. The proposed instrumentation sensing circuit employs the recycling folded cascade (RFC) instrumentation amplifier, which has the benefits of rail-to-rail input and output swing, lower power consumption, with high DC gain compared to conventional FC. We designed and implemented the proposed sensing circuit in a 65 nm CMOS process technology. The experimental results show that the proposed technique improves the SNR of TSP by 28 dB compared to the conventional integrator based sensing circuits. Also, we show that the design consumes 6.9 mA with a supply voltage of 1.8 V.

This paper presents a new technique for reading out projected mutual capacitance touch screen panels. It models touch screen panel as a communication system. Orthogonal frequency division multiplexing (OFDM) is used along with time division multiplexing (TDM) to read out all channels of touch screen panels. Different carrier frequencies are applied to touch screen panel concurrently using OFDM, while the sensing lines are sensed sequentially using TDM. The proposed technique ensures a high frame scan rate by using simultaneous driving signals, and it provides high signal to noise ratio (SNR) by avoiding frequency band with high noise power. Simulation results demonstrate a SNR improvement of 8.2 dB by selecting adequate carrier frequencies.

This paper presents a new technique to improve noise immunity of the RX sensing circuit of mutual-capacitance large touch screen panel (TSP). A differentiator circuit is incorporated to effectively suppress the high frequency noise. The proposed architecture provides low-pass and high-pass filter functions to reduce the noise and improve SNR. It uses square wave as a driving signal and integrates the output signal after filtering out the noise. The sensing circuit is small enough so that we can duplicate it to achieve target frame scan rate. We implemented the proposed technique using a 65 nm CMOS process and evaluated its operations in response to various touch events. The experimental results shows that the proposed technique improves the SNR of TSP by 9.5 dB compared to the conventional integrator based sensing circuits. We show that the design consumes 2.7 mA per each sensing circuit with supply voltage of 1.2 V.

This paper presents a design of Low Noise Amplifier (LNA) for Cognitive Radios (CRs) receiver and it operates from 50 MHz to 5 GHz. The proposed design is consisted of two stages; the first one is a combination of cascode with common gate stage to improve the gain, power consumption, and the input matching. The second stage is a common source (CS) for cancelling the noise and distortion of CG of the first stage. This design achieves a noise figure 4.1–4.8 dB, input reflection coefficient less than −11 dB, output reflection coefficient below −10 dB, the power gain from 10.2 dB to 12.5 dB and the power consumption 7.14 mW supplied from 1 V. The proposed LNA is designed using 0.18 μm CMOS technology.

This research work studies the executive operating results of one of the major computer software concerned with the automatic identification/recognition of Quranic voice; this is the Hafs Tajweed Teacher Software. This is done through the monitoring of operational mechanisms and the results of testing the software before its approval. The experimentation was done in four countries (Egypt, Saudi Arabia, Kuwait and Libya). Over two hundred users participated in this study under the supervision of professional experts in different disciplines: Administration, Engineering, Language, Tajweed and Education. The statistical results has shown the effectiveness of this software and its featured role in accelerating the student's learning process and increase cognitive learning for the sample of students who were subjected to this pilot study compared to the realizable results of the controlled sample that received the same education in a traditional way .