Histogram Test Research Articles

Ab. No. 75 Innovative Device for Superficial Sensory Examination; An Exploratory Multiphasic Study

Introduction: To design and develop the single device for assessing the superficial sensation. All the physiotherapists and any healthcare professionals who are dealing with the patient have neuropathies- diabetes, mononeuropathy, polyneuropathy, etc., neurological disorders – spinal cord injury and stroke, etc. are in used sensory examination with the use of fingertip, cotton, test-tube, and pin prick. Method: Designed and developed an innovative device to assess the qualitative superficial sensory examination. Then total 10 healthy physiotherapists are recruited for the study who are matched with the inclusion and exclusion criteria. There written informed concert was taken. Then to check the validity, traditional methods and innovative devices to check the superficial sensation. Then the scores were given according to sensory examination grade. Then the feasibility score was checked via the QUEST 2.0 score. The score was given by the physiotherapist. Result: After collecting the data the statistical tool SPSS 20 was used. The level of significance was kept 0.05 and the Confidence interval was 95%.To assess the normality we used the skewness, kurtosis, histogram, and Shapiro-Wilk test and data were normally distributed. After applied the paired t-test for feasibility and validity scores. They were significant in Pearson correlation of QUEST components which are dimension, weight, adjusting, easy to use, and comfort in innovative device. Conclusion: So, it is concluded that our innovative device is feasible, easy to use, comfort, effective and valid for testing the superficial sensation.

Precision of the transfer function estimation of analog to digital converters in the presence of additive noise

Analog-to-digital converters are essential components in modern systems which gather data from the real world to be used, after signal processing, in many ubiquitous applications. This work addresses the effect of the presence of additive noise in the test setup when characterizing these electronic devices using the Histogram Test method. The precision with which the converter transfer function is estimated is directly related to the amount of noise present, the number of data samples acquired and the sinusoidal stimulus signal amplitude. Here an analytical expression that quantifies this precision as a function of the test parameters is given to be used by the engineer when designing the test.

Better approximation for the precision of the number of counts in the histogram test of ADCs

Here one proposes a new analytical expression that can be used to estimate the precision of the estimates made with the histogram test of analog-to-digital converters as a function of the additive noise standard deviation present in the test setup. This can be advantageously used to determine the minimum samples that should be acquired in order to achieve a certain level of precision on the estimates made. A more rigorous choice of the number of samples makes the characterization more efficient and less time consuming.

Automated microaneurysms detection in retinal images using SSA optimised U-NET and Bayesian optimised CNN

ABSTRACT Diabetic retinopathy (DR) is a cause of vision loss and blindness, and early detection of red lesions, particularly microaneurysms (MAs), is crucial to prevent its progression. In this study, we propose an effective deep learning-based DR segmentation and classification method that leverages hyper-parameter optimisation to achieve high detection accuracy. In our proposed method, we first pre-processed retinal images to reduce background variability. Then, we employed a squirrel search optimised bidirectional ConvLSTM U-net with an attention gate for DR segmentation in the main processing step. Finally, we used a Bayesian-optimised Convolutional Neural Network for classification. We selected the optimal architectures for our proposed CNNs and optimised their hyper-parameters using the Bayesian optimisation technique.Our study demonstrates that the proposed CNNs effectively classify diabetic retinopathy in fundus images when model hyper-parameters are tuned with the help of Bayesian optimisation. We conducted statistical tests based on the receiver operating characteristic curve, histogram, and ANOVA test to verify the effectiveness of our suggested models.We proposed a deep learning-based DR segmentation and classification method that leverages hyper-parameter optimisation to achieve high detection accuracy. This study highlights the potential of Bayesian optimisation as an effective technique to optimise hyper-parameters of deep learning networks for disease classification tasks.

Development of a new MC Fast Dose Engine for small compact radiation fields generated by the CyberKnifeⓇ Iris medical linac

MC-based computerized TPS is an essential tool for improving treatment quality in external radiation therapy chains. However, incorporating these systems into clinical TPS is challenging due to their long computation time. To address this problem, Phase Spaces (PhSp) can be utilized, which reduce the computation time of such simulations while maintaining accuracy levels comparable to full simulations. Since PhSps can only generate a finite number of particles, recycling the same PhSp several times during a simulation will increase statistical uncertainty. To carry out this disadvantage, the present study employs a numerical reconstruction model to develop a novel generation of MC Fast Dose Engine (MC-FDE) that relies on the Cyberknife linac parameters publicly available in the IAEA database. The MC-FDE model’s performance is evaluated based on the precision of the reconstructed parameters and the accuracy of dose calculation in the 3D BEAMSCAN water phantom and patient CT datasets. In contrast to the recently published Wasserstein Generative Adversarial Networks (WGAN), the MC-FDE reconstruction model produces significant agreement with measured data, IAEA PhSp files and TPS Accuray, as determined by marginal distributions, correlation metrics, 2-3D gamma indexes and the Dose Volume Histogram (DVH) test. Regarding calculation speed, MC-FDE has a very fast process and can generate an infinite number of particles, unlike the limited number of particles recorded in IAEA PhSp files. According to the findings of this study, the proposed MC-FDE model is considered suitable for use as part of clinical TPS.

Choosing optimal input and sampling frequencies for analog to digital converter testing

The main objective of this paper is to study of the ideal input and sampling frequencies, as well as determining the necessary number of samples for achieving coherent sampling. This aspect holds significant importance when it comes to testing analog-to-digital converters (ADCs) using various techniques such as the Histogram Test Method, Discrete Fourier Transform Method, or Sine-Fitting Method. The study conducted in this paper sheds light on a crucial consideration, which is the trade-off between testing duration and the proximity to the required frequencies. This trade-off is determined by the number of acquired samples. The balance between the amount of time spent on testing and the accuracy achieved in terms of the frequencies being targeted is of great importance. By exploring the ideal input and sampling frequencies, along with the determination of the necessary number of samples for coherent sampling, this research contributes to enhancing the understanding of ADC testing methodologies. It provides valuable information for researchers and practitioners in the field, enabling them to make informed decisions regarding the selection of appropriate testing techniques and algorithms based on their specific requirements and constraints. Ultimately, the findings presented in this paper have the potential to improve the efficiency and effectiveness of ADC testing processes, leading to more accurate and reliable results.

Bias of the independently based gain and offset error in ADC testing using the histogram method

When normally distributed additive noise is present on the test setup, it leads to a bias on the values of estimated gain and offset error of analog-to-digital converters when estimated using the Histogram Test Method. It is shown that the offset estimation is unbiased while the gain estimation can have up to 5% bias for values of signal-to-noise ratio as low as 10 dB. It is also shown that this bias is not dependent on the number of samples acquired. An approximate analytical expression, in closed form, is proposed for rapid estimation of gain error. It considers the signal-to-noise ratio as well as the amount of overdrive used. The analytical derivations made are validated using simulated data using a Monte Carlo procedure. The same procedure is used with experimental data obtained with a real data acquisition system to validate the results obtained.

HASIL ANALISIS STATISTIK, DIFERENSIAL, DAN KUALITAS CITRA TERHADAP KOMPOSISI LOGISTIC CIRCLE MAP

The problem of data security is still a matter of concern in the digital era like today. An effective security method is needed and it is difficult to break into. Encryption is an effective method of ensuring data security. The encryption algorithm is built using a chaotic cipher base so that performance in securing data and information increases. The new chaotic composition resulting from two chaotic maps will have better randomness. Logistic Map and Circle Map were chosen because they have good randomness. The new chaotic composition is called the Logistic Circle Map (LC Map). By bifurcation diagram test, Lyapunov Exponent, and NIST random test, the best density occurs at X_0=0.9 , K = 1000, r = 3.7 and Ω = 0.4. The new chaotic composition parameters have passed all 16 NIST (National Institute of Standards and Technology) tests. There are four parameters used in this study in order to obtain a sufficiently high key space, namely 1.296 ×〖 10〗^84 combinations and having a high level of lock sensitivity of 10−17. The image encryption algorithm of the LC Map function has high resistance against various attacks. This can be proven by carrying out key space tests, sensitivity tests for key spaces, histogram tests, entropy, correlation coefficients, and differential tests using the UACI NPCR. The test results on digital image decryption using the Mean Square Error (MSE) show a result of 0 and the Peak Signal to Noise Ratio (PSNR) shows a result of ∞. That is, the encrypted image is similar to the original image.

Attack resistant chaos-based cryptosystem by modified baker map and logistic map

In this paper, a new substitution-diffusion type chaos-based cryptosystem is proposed, which can encrypt greyscale images having arbitrary resolution. In substitution, image pixels are permuted using a modified form of the discretised 2-D Baker map, followed by a two-step diffusion approach, which employs a chaotic logistic map. The proposed cryptosystem is resistant to brute force attacks (measured by key-space and key-sensitivity analysis), statistical attacks (tested by histogram and chi-square test) and differential attacks (measured against NPCR, UACI, and hamming distance); the proposed method has also been tested for encryption quality, correlation analysis, entropy analysis, and performance analysis by measuring encryption speed as well as time complexity. Therefore, it is sufficiently secured to be used in real-world applications. To prove the unparalleled outcome of the proposed system, four sets of comparisons have been presented with respect to NPCR and UACI, Encryption throughput, and, lastly, with similar and non-similar existing cryptosystems.

High-sensitivity stereo coded aperture gamma camera for three-dimensional localization of radioactive hotspots

This work presents a novel stereo coded aperture gamma camera based on four detection modules placed within four quadrants. Each module includes 48 × 48 strips of Bi4Ge3O12 scintillators, 24 × 24 pieces of silicon photomultipliers (SiPMs), and a set of data acquisition circuits. All signals from the SiPMs are individually extracted and finally simplified into 144 outputs to calculate the positions and energies of gamma-rays. Two masks of modified uniformly redundant arrays are fixed in the front of the top-right and bottom-left modules and two anti-masks are fixed in the top-left and bottom-right modules to achieve simultaneous imaging without dual measure. Once the projections of radioactive sources are determined, their source-to-detector distances can be estimated by our new multocular ranging algorithm. A series of lab and field experiments, including flood histogram and energy spectrum testing, field-of-view and angular resolution testing, real-time imaging, long-distance imaging, and ranging ability testing, with different radioactive sources, such as 137Cs, 22Na, 241Am, 60Co, 133Ba, and 75Se, have been completed to evaluate the comprehensive ability of the stereo gamma camera. The results show that the stereo gamma camera has a strong ability for the three-dimensional localization of radioactive sources over long distances with a high image sensitivity. So far, the stereo gamma camera has been successfully used in practical nuclear security and safety tasks although the angular resolution and the ranging algorithm robustness should be more optimized in the future.

Reference Interval of Thyroxine and Thyroid Stimulating Hormone in Cord Blood in Tertiary Care Hospital, Kerala

Introduction: Even though Congenital hypothyroidism (CH) is one of the most common causes of preventable mental retardation, diagnosis at birth is difficult due to absent or delayed clinical manifestations, owing to the transplacental transfer of maternal thyroid hormones. Delayed diagnosis and treatment can cause irreversible damage to the developing brain. The occurrence of cognitive dysfunction due to CH has reduced significantly in countries where Newborn Screening (NBS) is routinely practiced. Cord blood screening is considered to be an effective method to diagnose congenital hypothyroidism. Aim: To establish reference interval for thyroxine (T3 and T4) and Thyroid Stimulating Hormone (TSH) in cord blood Medical College, Thrissur. Materials and Methods: In the present cross-sectional observational hospital based study, the cord blood samples from 252 deliveries collected over a period of three months from May 2011 at in Government Medical College, Thrissur, Kerala, India. A 5 mL of cord blood samples were collected in a plain non vacuum tube with clot activator from umbilical cord incised 15-20 cm at the time of birth. T3, T4 and TSH was estimated by Enzyme Linked Immuno-sorbent Assay (ELISA) using kits of ELISA reader and Washer. Normality check done by visual inspection of histogram, Q-Q plot, box plot and Kolmogorov-Smirnov test. Results: In total of 153 cord blood samples considered, and final analysis was done on 151 samples (69 males and 82 females) after excluding the samples of babies delivered by Lower Segment Cesarean Section (LSCS). The gestational age was mean 38.48 weeks and mean age of mothers was 24.22 years. More than 90% of the values for TSH is less than 12 mIU/mL and 90% of T4 values is less than 20 µg/dL. Reference interval determined by non parametric ascending rank order. Reference interval established is 0.63-17.033 mIU/L and 9.45-27.173 for TSH and T4 respectively, lower than those reported from studies in other parts of India. The mean value of TSH was 5.084 mIU/L and 87.5% of babies are having TSH values <10 mIU/L. Conclusion: The study was conducted to establish reference intervals for cord blood TSH, T4 and T3 and confirms to the use of cut off values for the screening of CH for TSH as >20 mIU/L.

Steganography based on quotient value differencing and pixel value correlation

Pixel value differencing (PVD) steganography techniques produce imperceptible stego-images. Most PVD-based techniques have a fall-off boundary problem (FOBP). To avoid FOBP, a steganographic scheme is presented that combines the quotient value difference (QVD) with pixel value correlation (PVC). It performs data embedding in two stages on 3 × 3 size pixel blocks. The first stage of the embedding procedure performs QVD and remainder substitution on five pixels. These five pixels are central pixel and it's neighbours on the left, right, upper, and lower sides. Based on the new values of these five pixels, the PVC embedding procedure is applied on the remaining four corner pixels of the block. The experimental results are found to be improved. The hiding capacity is high that is 3.92 bits per byte with an acceptable peak signal-to-noise ratio value. A security check was performed using two tests: (i) a regular-singular (RS) test, (ii) a pixel difference histogram (PDH) test. The experimental outcomes demonstrate that PDH curves of the stego-images do not have a zigzag shape, that means the PDH test could not detect this steganography technique. Furthermore, the RS curves show that the RS test could not detect this steganography technique.

Synchronization of chaotic artificial neurons and its application to secure image transmission under MQTT for IoT protocol

Artificial neurons are quite useful to generate chaotic behavior, and they can be implemented on embedded systems like Raspberry Pi that include WiFi network connectivity. In this manner, this paper shows the use of some artificial neurons to generate chaotic binary sequences whose randomness is enhanced by post-processing approaches and measured by performing statistical NIST SP 800-22 tests. The chaotic neurons are synchronized by different methods and each neuron is implemented on a Raspberry Pi, which allows connectivity to a machine-to-machine (M2M) broker. This wireless connectivity advantage is exploited herein to develop a lightweight cryptographic application under the message queueing telemetry transport (MQTT) for Internet of Things (IoT) protocol. The synchronized neurons have a topology in which one Raspberry Pi works as publisher and can send encrypted information to multiple subscribers. Due to the chaotic behavior of the neurons, the Raspberry Pi acting as subscriber can recover the encrypted information if and only if it has the right key, i.e., the correct random binary sequence generated by the publisher. To augment the security against attacks, the chaotic neurons have different initial conditions before M2M synchronization is accomplished, and the color image encryption under MQTT for IoT is evaluated by performing correlation, histogram, variance, entropy, and NPCR tests.

Efficient and Secure Bit-Level Chaos Security Algorithm for Orbital Angular Momentum Modulation in Free-Space Optical Communications

Currently, secure multimedia applications are becoming a very hot research topic, specifically over the Internet and wireless communication networks due to their rapid progress. Several researchers have implemented various chaotic image and video encryption algorithms to achieve data stability and communication security. This paper presents a novel bit-level video frame cryptosystem that is dependent on the piecewise linear chaotic maps (PWLCMs). It is implemented for orbital angular momentum (OAM) modulation over different turbulence channels. Firstly, the mathematical model for the bit error rate (BER) of OAM modulation is derived over the gamma-gamma turbulence channel. After that, a comparison between the theoretical results from Mathematica and the simulation results from MATLAB for different turbulence strengths, signal-to-noise ratios (SNRs), and propagation distance values is presented to assure that there is a perfect match. The proposed video cryptosystem is checked using entropy analysis, histogram testing, attack analysis, time analysis, correlation testing, differential analysis, and other quality and security evaluation metrics. The simulation results and the performance analysis confirm that the proposed cryptosystem is reliable and secure for video frame encryption, and communication with different turbulence conditions in free space.

Adaptive diagnostic machine learning technique for classification of cell decisions for AKT protein

Artificial intelligence techniques can unravel clinically consistent information in clinical data which in turn assist in decision-making. With the help of state-of-the-art techniques, diagnostic systems are used to identify various diseases by using different machine learning (ML) techniques. In this paper, a combination of ML techniques such as Radial Basis Function (RBF) and Multiple Layer Perceptron (MLP) was used to predict cell decisions (cell survival/death) of AKT protein. AKT signalling networks have various downstream consequences on cellular metabolism either directly through the regulation of nutrient transporters, metabolic enzymes or indirectly through the control of transcription factors that regulate the expression of metabolic pathways which determine cell survival, cell growth, and cell death. Experimental analysis was performed in this work to examine the signalling networks that determine cell survival/death decisions by using an amalgamation of three proteins for ten different combinations in 13 different slices for a period of 0–24 h. P-P plot, Q-Q plot, and histogram tests were used for data visualization to determine which distribution the data fits. In addition, goodness of fit test was also employed using distribution functions such as Weibull, Exponential, and Normal distribution to determine whether the data fits a distribution of a certain population. The results were validated by calculating the MTTF values. The results of the analysis performed show that the Weibull distribution yields remarkable results. Also the results obtained with the Multiple Layer Perceptron, MLP 10-8-1 was found to perform better than other techniques giving an accuracy of 99.33% when the exponential activation function was used. The results of the experimental study indicate that it is possible to create self-consistent cell-signalling compendia based on AKT protein data that have been computationally simulated to provide valuable insights for cell survival/death regulation.

Validation of American Association of Physicists in Medicine TG 43 Dosimetry Data in Commercial Treatment Planning System.

AimsThis study aimed to validate the dosimetric data of low-energy photon-emitting low-dose rate (LE-LDR) brachytherapy seed sources in commercial treatment planning system (TPS).Materials and MethodsThe LE-LDR seed sources dosimetric data were published in the American Association of Physicists in Medicine (AAPM) Task Group reports TG-43 (1995), TG-43U1 (2004), TG-43U1S1 (2007), and TG-43U1S2. The Bhabha Atomic Research centre (BARC) 125I Ocu-Prosta seed dosimetry data are also available in the literature. The commercially available TPSs are using both two-dimensional (cylindrically symmetric line-source) and one-dimensional (1D) (point source) dose-calculation formalisms. TPS used in this study uses only 1D dose-calculation formalism for permanent implant dosimetry. The point-dose calculation, dose summation, isodose representation, and dose–volume histogram quality assurance tests were performed in this study. The point-source dose-calculation tests were performed for all the available sources in the literature. The others tests were performed for the I-125 BARC Ocu-Prosta seeds. The TPS-calculated doses were validated using manual calculation.Results and DiscussionIn point-source calculation test, the TPS-calculated point-dose values are within ±2% agreement with manually calculated dose for all the seeds studied. The agreement between the TPS and manually calculated dose is 0.5% for the dose summation test. The isodose line pass through the grid points at an equal distance was verified visually on the computer screen for seed used clinically. In dose–volume histogram test, the TPS-determined volume was compared with the real volume.ConclusionMisinterpretation of the TPS test and/or misunderstanding of the TG-43 dose-calculation formalism may cause large errors. It is very important to validate the TPS using literature provided dosimetric data. The dosimetric data of BARC 125I Ocu-Prosta Seed are validated with other AAPM TG-43-recommended seeds. The dose calculation of Best® NOMOS permanent implant TPS is accurate for all permanent implant seeds studied.

Optical and digital double color-image encryption algorithm using 3D chaotic map and 2D-multiple parameter fractional discrete cosine transform

This paper proposes a new encryption and decryption method for optical and digital double color-images using 2D-multiple parameter fractional discrete cosine transform (MPFrDCT) and 3D-logistic chaotic map (3D-LCM). The double color-images to be encrypted are converted to their indexed formats by extracting their color maps. A 3D-LCM is used for generate a keystream and this keystream is used in scrambling the indexed images. The second scrambled image is normalized and then multiplied by a random phase mask (RPM) generated by 3D-LCM. The first scrambled image and the second modified image are treated as amplitude and phase of a complex signal and this complex signal is encrypted using 2D-MPFrDCT. The Encrypted image is obtained after separating the amplitude and phase parts of this signal. To enhance security, a substitution method is applied in the intermediate image using another keystream generated by 3D-LCM. The decryption method is the same but in reverse order. We have also given a setup for the encryption and decryption of optical double images using this method. The keyspace for the proposed method is also discussed in this paper. The experimental results and the security analysis of the proposed method are given to validate the feasibility and robustness of the proposed method. The statistical analysis like histogram, correlation, entropy analysis, and randomness test confirm the robustness of the proposed method against statistical attacks. The experimental results also show that the proposed method is resistant to a brute-force attack. The proposed method has the ability to resist the occlusion attack, differential attack, and Gaussian random noise attack.

Consideration on Input Signal for ADC Histogram Test in Short Time

This paper describes two algorithms for generating test signals to efficiently test the linearity of ADCs. Linearity is an important testing item for ADCs, and it takes a long time (hence is costly) to test especially low-sampling-rate, high-resolution ADCs. We have proposed to generate a test signal consisting of multiple-sine waves, to precisely test the linearity for specific important codes (such as around the center of the output codes), using an arbitrary waveform generator (AWG) and an analog filter in our previous studies. Here, we formulate them for general use. Their verification is performed on a single sine wave, and good results are obtained to show the validity of the derivation algorithm.

Efficient and secure opto-cryptosystem for color images using 2D logistic-based fractional Fourier transform

Nowadays, secure multimedia applications become a hot research issue because of rapid evolution in the application of multimedia over the Internet and wireless communications networks. Several researchers have introduced many chaos-based encryption methods to achieve data robustness and security communication. But, there exist several issues encountered in those methods regarding their fragility against differential attacks, delayed throughput, and inadmissible data expansibility. From this perspective, the paper presents an effective and secure opto color image cryptosystem using 2D Fractional Fourier Transform (2D FrFT) and 2D logistic mapping (2D LM). The proposed opto 2D LM-based 2D FrFT color image cryptosystem employed two confusion stages in the time and optical-based 2D FrFT using the 2D LM for color RGB images. Initially, the 2D LM is employed to shuffle the pixel positions of the RGB plainimage. After that, the optical-based FrFT is employed on the 2D LM-based shuffled RGB image. The complex transformed RGB image is again shuffled using the 2D LM, and finally, optically transformed using the FrFT. Furthermore, the encryption characteristics are enhanced by utilizing the 2D-FrFT angles and orders as extra encryption keys in addition to double random phase masks. The proposed opto 2D LM-based 2D FrFT color image cryptosystem is tested through the known security key indicators such as visual inspecting, entropy testing, histogram testing, cipher quality measures, noise testing, computational time analysis, occlusion attack analysis, and differential testing. The simulation results illustrated a superiority improvement in the proposed opto 2D LM-based 2D FrFT color image cryptosystem compared to the recent state-of-the-art related works.

A Time-Domain 147fsrms 2.5-MHz Bandwidth Two-Step Flash-MASH 1-1-1 Time-to-Digital Converter With Third-Order Noise-Shaping and Mismatch Correction

A 50 MS/s two-step flash-MASH 1-1-1 time-to-digital converter (TDC) employing a two-channel time-interleaved time-domain register with an implicit adder/subtractor realizes an error-feedback topology. Such an error-feedback unit of 1st-order noise-shaping TDC can be cascaded as a multi-stage noise shaping (MASH) configuration to achieve higher-order noise-shaping and, thereby high resolution. This paper also discusses different noise sources, linearity and noise tradeoffs in noise-shaping TDC and then demonstrates a histogram testing technique to correct the mismatch of 1st stage flash TDC. An on/off-chip delay modulation (DM) measurement technique is presented to characterize the TDC linearity and noise performance. Fabricated in 40-nm CMOS technology, the proposed TDC consumes 1.32 mW from a 1.1 V supply. At frequency below 2.5 MHz, the TDC error integrates to 147fsrms, which is equal to equivalent flash resolution of 1.6 ps.