Rajendra S. Gad

Noninvasive glucometer model using partial least square regression technique for human blood matrix

In this article, we have highlighted the partial least square regression (PLSR) model to predict the glucose level in human blood by considering only five variants. The PLSR model is experimentally validated for the 13 templates samples. The root mean square error analysis of design model and experimental sample is found to be satisfactory with the values of 3.459 and 5.543, respectively. In PLSR templates design is a critical issue for the number of variants participating in the model. Ensemble consisting of five major variants is simulated to replicate the signatures of these constituents in the human blood, i.e., alanine, urea, lactate, glucose, and ascorbate. Multivariate system using PLSR plays important role in understanding chemometrics of such ensemble. The resultant spectra of all these constituents are generated to create templates for the PLSR model. This model has potential scope in designing a near-infrared spectroscopy based noninvasive glucometer.

Low-cost multi-spectral face imaging for robust face recognition

Multi-spectral face recognition has acquired significant attention over a last few decades due to its potential of capturing spatial and spectral information across the electromagnetic spectrum. In this paper, we present a new imaging scheme that can obtain the multi-spectral face image at nine different spectra covering 530nm-1000nm. We prepared a new database comprising of 230 subjects using our new low-cost multi-spectral face imaging device. Extensive experiments are presented for evaluating the performance of the four different state-of-the-art face recognition algorithms on both individual bands and the fused spectral face image. Obtained results show the improved face recognition performance of Log-Gabor features with Collaborative Representation (CRC) as the classifier.

Extended multi-spectral face recognition across two different age groups: an empirical study

Face recognition has attained a greater importance in bio-metric authentication due to its non-intrusive property of identifying individuals at varying stand-off distance. Face recognition based on multi-spectral imaging has recently gained prime importance due to its ability to capture spatial and spectral information across the spectrum. Our first contribution in this paper is to use extended multi-spectral face recognition in two different age groups. The second contribution is to show empirically the performance of face recognition for two age groups. Thus, in this paper, we developed a multi-spectral imaging sensor to capture facial database for two different age groups (≤ 15years and ≥ 20years) at nine different spectral bands covering 530nm to 1000nm range. We then collected a new facial images corresponding to two different age groups comprises of 168 individuals. Extensive experimental evaluation is performed independently on two different age group databases using four different state-of-the-art face recognition algorithms. We evaluate the verification and identification rate across individual spectral bands and fused spectral band for two age groups. The obtained evaluation results shows higher recognition rate for age groups ≥ 20years than ≤ 15years, which indicates the variation in face recognition across the different age groups.

Performance Analysis of Gigabit Ethernet Standard for Various Physical Media Using Triple Speed Ethernet IP Core on FPGA

Gigabit Ethernet Standard provides 1 Gbps bandwidth and is backward compatible with 10 Mbps (Ethernet) and 100 Mbps (Fast Ethernet). It can also be installed with lower cost than other technologies having similar speed. The performance studies of Gigabit Ethernet is more complex than Ethernet or Fast Ethernet protocols. In this paper we have described the implementation of Gigabit Ethernet design on FPGA using Altera’s Triple Speed Ethernet IP Core. The performance analysis of Gigabit Ethernet Standard has been studied using various physical media. This analysis includes performance measurements with different number of frames and frame lengths.

Reliable and Scalable Architecture for Internet of Things for Sensors Using Soft-Core Processor

With significant technological developments as well as advances in sensors, wireless communications and Internet – a lot of research areas have emerged, such as wearable computing, context-aware homes, mobile phone sensing and smart vehicle systems. From those emerging areas, there is a clear trend to augment the physical devices/objects with sensing, computing & communication capabilities, connect them together to form a network and make use of the collective effect of networked smart things − the Internet of Things(IoT). This paper proposes the IoT architecture “Kaivalyam” for sensors/actuator. The configurable interface generates the identity of the ‘Thing’ and stores in 32-bit datagram. The various configuration of the 32-bit datagram from 4,8,12 and 16-bit device data and respective 14, 12, 10 and 8-bits duplicate identifier can scale the number of devices connected to design platform. These datagram’s read into FIFO of the Triple Speed Ethernet (TSE) for transmission using Low Density Parity Check (LDPC) encoder. Simulation studies for the system were performed for block length 512 bits, which is the minimum Ethernet frame length of 64 bytes. AWGN(Additive White Gaussian Noise) is introduced in the channel and BER(Bit Error Rate) is computed for different (1dB to 6dB) SNR(Signal to Noise Ratio) showing BER of 10-4 -4 to 10-5 can be achieved for SNR of 2.5 dB indicating the secured and reliable data transmission.

Configurable CRC Error Detection Model for Performance Analysis of Polynomial: Case Study for the 32-Bits Ethernet Protocol

Almost every form of digital information exchange can introduce communication errors. In order to overcome the inherent inaccuracy of information transmission, a few methods for error detection and correction have been developed. Cyclic Redundancy check Codes (CRCs) are used in embedded networks for effective error detection. Paper discusses the development of the simulation model for the configurable CRC-polynomials performance analysis over Binary Symmetric Channels (BSCs). This paper presents a novel model which can be used to investigate several classes of CRC polynomials codes with ‘n’ parity bits varying from ‘1’ to ‘64’. It also discuss the hardware implementation on Altera’s FPGA Stratix II GX device ‘EP2SGX90FF1508C3’ for CRC-32 ‘IEEE-802’ and suggest the indirect methodology of CRC-performance using Packet Error Rate (PER) parameter using Altera TSE MegaCore function that supports 10/100/1000 Mbps Ethernet over 1000Base-LX physical media. It is proposed to search good CRC codes of 32, 40 and 64 bit and studying performance for maximum payload over Ethernet protocol.

Human tissue diagnostics for physiological information using Hyperspectral Image model

Hyperspectral imaging is a novel technology for obtaining both spatial and spectral information in the area of aerospace and military industries for last 20 years. The multifusion, multispectral, hyperspectral and polarimetric imaging can provide both anatomical and physiological or metabolic information; it can play an important role in the development of molecular imaging technologies with enhanced specificity and sensitivity, capable of identifying the presence versus absence of cancer, detection of margins, stage, distribution, and type of cancer, but most importantly, techniques capable of assessing the progress of the disease and its response to treatment. Hyperspectral Image modeling provides practical alternatives for the field measurements in human tissue sample due to sample coupling problems and heavy absorption due to protein and water in UV and NIR regions respectively in the region of therapeutic window. In this paper we have proposed the Lorentz Oscillators techniques to generate the multivariate signal for a pixel signature over spectrum channel of interest. The model has been demonstrated to synthesize the image with proper signature for the pixel. The spectra having customized signatures are generated using proper values of the central frequency, Strength of Oscillators and Width of oscillators. These models can be customized for the specific vision under observation and serialized for the quality, intrusion or diagnostics using pattern recognition principle for both anatomical and physiological information in human tissue.

Note: Multivariate system spectroscopic model using Lorentz oscillators and partial least squares regression analysis.

Multivariate system spectroscopic model plays important role in understanding chemometrics of ensemble under study. Here in this manuscript we discuss various approaches of modeling of spectroscopic system and demonstrate how Lorentz oscillator can be used to model any general spectroscopic system. Chemometric studies require customized templates design for the corresponding variants participating in ensemble, which generates the characteristic matrix of the ensemble under study. The typical biological system that resembles human blood tissue consisting of five major constituents i.e., alanine, urea, lactate, glucose, ascorbate; has been tested on the model. The model was validated using three approaches, namely, root mean square error (RMSE) analysis in the range of ±5% confidence interval, clerk gird error plot, and RMSE versus percent noise level study. Also the model was tested across various template sizes (consisting of samples ranging from 10 up to 1000) to ascertain the validity of partial least squares regression. The model has potential in understanding the chemometrics of proteomics pathways.

Genesis of PLD’s, Market Players, and Tools

“Genesis of PLD’s, market players, and tools” discuss the microprocessor, microcontroller, and PLD devices and also talk about how to select these devices for desired application. This chapter gives the family tree of PLD devices and helps designer to select best PLD devices based on application. The chapter also gives the overview of major PLD market players and programming aspect of VHDl, Verilog, and ABEL. There are several separate books available in the market which discusses in detail about VHDL, Verilog, and ABEL programming. Here, we simply focused more on the basic part of hardware descriptive programming language.

Case Studies Using Altera Nios II

This chapter will further boost the interest as it covers lots of interesting case studies designed around Nios II soft core processor such as blinking of LEDs in different patterns, displaying scrolling text on LCD, interfacing camera for acquiring images, multiprocessor communication, Ethernet-based robotic arm control, matrix crunching problem for multivariate analysis, and reading flash for Web application.