Binary Equivalents Research Articles

Implementation of Full adder in Multiple valued Logic for Performance Optimization

Multiple valued logic is now becoming more significant in real-world applications. Mathematical design blocks are essential in digital and mixed-signal systems. A system's arithmetic blocks often use the most power because of the high switching activity. Implementations of quaternary arithmetic may be a way to cut down on energy use while improving system performance. In this paper, quaternary adders are developed using three different approaches, and their binary equivalents are evaluated in terms of size, predicted logic depth, and performance estimation.

Prime-Field Masking in Hardware and its Soundness against Low-Noise SCA Attacks

A recent study suggests that arithmetic masking in prime fields leads to stronger security guarantees against passive physical adversaries than Boolean masking. Indeed, it is a common observation that the desired security amplification of Boolean masking collapses when the noise level in the measurements is too low. Arithmetic encodings in prime fields can help to maintain an exponential increase of the attack complexity in the number of shares even in such a challenging context. In this work, we contribute to this emerging topic in two main directions. First, we propose novel masked hardware gadgets for secure squaring in prime fields (since squaring is non-linear in non-binary fields) which prove to be significantly more resource-friendly than corresponding masked multiplications. We then formally show their local and compositional security for arbitrary orders. Second, we attempt to >experimentally evaluate the performance vs. security tradeoff of prime-field masking. In order to enable a first comparative case study in this regard, we exemplarily consider masked implementations of the AES as well as the recently proposed AESprime. AES-prime is a block cipher partially resembling the standard AES, but based on arithmetic operations modulo a small Mersenne prime. We present cost and performance figures for masked AES and AES-prime implementations, and experimentally evaluate their susceptibility to low-noise side-channel attacks. We consider both the dynamic and the static power consumption for our low-noise analyses and emulate strong adversaries. Static power attacks are indeed known as a threat for side-channel countermeasures that require a certain noise level to be effective because of the adversary’s ability to reduce the noise through intra-trace averaging. Our results show consistently that for the noise levels in our practical experiments, the masked prime-field implementations provide much higher security for the same number of shares. This compensates for the overheads prime computations lead to and remains true even if / despite leaking each share with a similar Signal-to-Noise Ratio (SNR) as their binary equivalents. We hope our results open the way towards new cipher designs tailored to best exploit the advantages of prime-field masking.

Color Cast Correction Mechanisms: Techniques and Innovations for Image Enhancement

This paper presents an in-depth examination of color cast in digital images, elucidating its fundamental principles, generation mechanisms, and real-world implications influenced by light absorption and scattering. The study explores diverse color cast correction methods and provides a detailed analysis of their respective outcomes. Foundational knowledge of color cast, rooted in the principles of light interaction, serves as the basis for understanding its manifestation in various real-world contexts. The research systematically investigates the intricate dynamics of color cast across diverse scenarios, shedding light on its complexities and impact. The paper evaluates a range of color cast correction techniques, including classic approaches such as the Gray World Algorithm, Max–RGB, and White Balance Correction, as well as advanced methods like Gamma Correction, Histogram-Based Method, and the Gray Edge Algorithm. Notably, simulation results underscore the consistent superiority of the Gray Edge Algorithm in effectively correcting color cast, showcasing its robustness across diverse scenarios. This comprehensive exploration contributes to a holistic understanding of color cast, covering its generation, consequences in real-world scenarios, and an in-depth analysis of correction methodologies. The findings provide valuable insights for professionals in image processing and computer vision seeking efficient correction strategies.

An Image Processing-Driven System for Fake Currency Detection

Fake currency is a critical factor affecting economies worldwide, including India. In this paper, a novel and structurally efficient approach for detecting and identifying duplication in currency notes is presented using Discrete Wavelet Transform (DWT). The system employs image processing algorithms to extract essential features such as security thread, intaglio printing (RBI logo), and identification mark, which serve as security measures for Indian currency. To identify fake portions in the currency notes and make informed decisions about their authenticity, the matching scores from all fake detection modules are fused together. A crucial aspect of the work lies in comparing the extracted features from various currency notes, enabling us to differentiate between fake and genuine notes effectively. To assess the performance, mean square error is employed as a metric for comparison between two images. A database is build containing authentic Indian notes of different denominations, extract their features, convert them into binary equivalents, and then calculate their mean square error. The proposed Fake Note Detection System takes a test currency note image, performs preprocessing operations to eliminate noise and negative artifacts, and then proceeds with the detection process. The system offers a promising solution to combat counterfeit currency issues and safeguard the integrity of the Indian economy.

Method for extracting square and cube roots in the binary number system

The article describes in detail the methods of extracting square and cube roots in the binary number system. The method for extracting the square root of a binary number is similar to the corresponding method for decimal numbers, which is called the "column method". As for decimal numbers, when choosing the next digit of the root, twice the current value of the root, represented in the binary system, is used. When extracting the cube root (also "column"), there are two differences from the decimal system. The first is that instead of 300 (the product of 3 and 100), the binary number 1100 is used (that is, the product of the binary equivalents of the numbers 3 and 4). The second difference is that instead of the number 30 (the product of 3 and 10), the binary number 110 is used (that is, the product of binary analogs numbers 3 and 2). To facilitate the selection of the next root digit (0 or 1), a number of standard values have been calculated, depending on the current root value. Assignments for independent work of students are offered.

Alcohol Fuels for Spark-Ignition Engines: Performance, Efficiency, and Emission Effects at Mid to High Blend Rates for Ternary Mixtures

This paper follows on from an earlier publication on high-blend-rate binary gasoline-alcohol mixtures and reports results for some equivalent ternary fuels from several investigation streams. In the present work, new findings are presented for high-load operation in a dedicated boosted multi-cylinder engine test facility, for operation in modified production engines, for knock performance in a single-cylinder test engine, and for exhaust particulate emissions at part load using both the prototype multi-cylinder engine and a separate single-cylinder engine. The wide variety of test engines employed have several differences, including their fuel delivery strategies. This range of engine specifications is considered beneficial with regard to the “drop-in fuel” conjecture, since the results presented here bear out the contention, already established in the literature, that when specified according to the known ternary blending rules, such fuels fundamentally perform identically to their binary equivalents in terms of engine performance, and outperform standard gasolines in terms of efficiency. However, in the present work, some differences in particulate emissions performance in direct-injection engines have been found at light load for the tested fuels, with a slight increase in particulate number observed with higher methanol contents than lower. A hypothesis is developed to explain this result but in general it was found that these fuels do not significantly affect PN emissions from such engines. As a result, this investigation supplies further evidence that renewable fuels can be introduced simply into the existing vehicle fleet, with the inherent backwards compatibility that this brings too.

ON THE COMPARATIVE ANALYSIS OF THE COOLEY-TUKEY AND BLUESTEIN NUMERICAL FAST FOURIER TRANSFORMS ALGORITHMS FOR DIGITAL SIGNAL PROCESSING

ABSTRACT This study was designed to compare the computing efficiency of C-TNADSP and the BNADSP to ascertain a more efficient numerical algorithm necessary for the processing of digital signals. The faster numerical algorithm established in this study is abbreviated with RCC-TNADSP (Resultant Compared C-TBNADSP). The methodology adopted in this work was comparative analysis development design. The major technologies used in this work are the C-TNADSP and BNADSP, and the c++. The c++ served as a signal processing language simulator (SPLS). The execution times of the Cooley-Tukey and the Bluestein algorithms were 3.44 seconds and 3.50 seconds respectively. On comparing the speeds of the fast Cooley–Tukey and the fast Bluestein algorithms we observed that the Cooley-Tukey algorithm has 0.06 seconds speed improvement over the Bluestein algorithm. In line with this outcome, we concluded that the Cooley-Tukey algorithm (C-TNADSP) is faster than the Bluestein algorithm (BNADSP). In the same vein the Cooley-Tukey algorithm (C-TNADSP) is therefore the fastest DSP algorithm. This is however faster than the spectrum of FFT algorithms of O(nlogn) computing speed. The algorithms were tested on input block width 1000 units, and above, and can be implemented on input size of 100 000, and 1000 000 000 without the challenge of storage overflow. The input samples tested in this work was the discretized pulse wave form with undulating shape out of which the binary equivalents were extracted. Other forms of signals may also be tested in this fast algorithm provided they are interpreted in the digital wave type. KEYWORDS: Algorithm, FFT, Cooley-Tukey, Bluestein, Comparison, Analysis, FFT

Development of an Extended Improvement on the Simplified-Bluestein Algorithm

This research was designed to develop an extended improvement on the simplified Bluestein algorithm (EISBA). The methodology adopted in this work was iterative and incremental development design. The major technologies used in this work are the numerical algorithms and the C++ programming technologies and the wave concept technology. The C++ served as a signal processing language simulator (SPLS). In the EISBA, the DSP input is encountered first. It is subjected to some numerical processing which included testing for efficiency on the C++ platform. This test platform provided the basis for comparison leading to the desired EISBA. The approach adopted in the study was the re-indexing, decomposing, and simplifying the default SBFFT algorithm. The computing speed of the default algorithms was tested on the C++ platform. The average execution time of the SBFFT was 3.50 seconds. Similarly, the average execution time of the EISBA was 1.74 ms. this result therefore shows that a version of algorithm with computing speed that is faster than that of SBFFT algorithm exist. The algorithms were tested on input block of width 1000 units, and above, and can be implemented on input size of 100 000, and 1000 000 000 without the challenge of storage overflow. The input samples tested in this work was the discretized pulse wave form with undulating shape out of which the binary equivalents were extracted. Other forms of signals may also be tested in the EISBA provided they are interpreted in the digital wave type.

Fast low energy RNS comparators for 4-moduli sets {2n±1, 2n, m} with m∈{2n+1±1, 2n−1−1}

Comparison is a difficult operation in residue number systems (RNS). Besides the straightforward comparison of binary equivalents of RNS numbers, shortcut methods for moduli-set τ={2n−1, 2n, 2n+1} have been proposed that only slightly improve the corresponding figures of merit. On the other hand, we have encountered only one hardware realization of 4-moduli RNS comparison, where the corresponding moduli-set does not include any power-of-two modulo. In this paper, we examine and provide shortcut RNS comparators for three moduli-sets with four modulus, all containing τ as a subset. Evaluation results show 15–136% speed-up and 39–366% less energy in comparison to the straightforward reverse-and-compare comparators.

Asymmetric supercapacitors with metal-like ternary selenides and porous graphene electrodes

Asymmetric supercapacitors provide a promising approach to fabricate capacitive energy storage devices with high energy and power densities. In this work, asymmetric supercapacitors with excellent performance have been fabricated using ternary (Ni, Co)0.85Se on carbon fabric as binder-free positive electrode and porous free-standing graphene film as negative electrode. Owing to their metal-like conductivity (~1.67×106Sm−1), significant electrochemical activity, and superhydrophilic nature, our nanostructured ternary nickel cobalt selenides result in a much higher areal capacitance (2.33Fcm−2 at 4mAcm−2), better rate performance and cycling stability than their binary selenide equivalents, and other ternary oxides and chalcogenides. Those hybrid supercapacitors can afford impressive areal capacitance and stack capacitance of 529.3mFcm−2 and 6330mFcm−3 at 1mAcm−2, respectively. More impressively, our optimized asymmetric device operating at 1.8V delivers a very high stack energy density of 2.85mWhcm−3 at a stack power density of 10.76mWcm−3, as well as 85% capacitance retention after 10,000 continuous charge–discharge cycles. Even at a high stack power density of 1173mWcm−3, this device still deliveries a stack energy density of 1.19mWhcm−3, superior to most of the reported supercapacitors.

ON THE COMPARATIVE ANALYSIS OF THE FAST BLUESTEIN AND FAST COOLEY-TUKEY NUMERICAL ALGORITHMS FOR DIGITAL AND ANALOG SIGNALS PROCESSING

This study was designed to compare the computing efficiency of FC-TNADSP and the FBNADSP.to ascertain a faster numerical algorithm necessary for the processing of digital signals. The faster numerical algorithm established in this study is abbreviated with RCFC-TNADSP (Compared Resultant-TNADSP). The methodology adopted in this work was comparative analysis development design. The major technologies used in this work are the FC-TNADSP and FBNADSPwhich were hitherto simulated on the c++ programming technologies. The c++ served as a signal processing language simulator (SPLS). The execution times of the fast Cooley-Tukey and the fast Bluestein algorithms were 1.70 seconds and 1.74 seconds respectively. On comparing the speeds of the fast Cooley–Tukey and the fast Bluestein algorithms we observed that the fast Cooley-Tukey algorithm has 0.04 seconds speed improvement over the fast Bluestein algorithm. In line with this outcome, we concluded that the fast Cooley-Tukey algorithm (FC-TNADSP) is faster than the fast Bluestein algorithm (FBNADSP). In the same vein the fast Cooley-Tukey algorithm (FC-TNADSP algodsp-2) is therefore the fastest DSP algorithm. This is however faster than the spectrum of FFT algorithms of O(nlogn) computing speed, a speed considered to be the fastest hitherto. The result of this study shows we can have faster numerical algorithms other than the traditional spectrum of FFT algorithms of O(nlogn) computing speed. The algorithms were tested on input block of width 1000 units, and above, and can be implemented on input size of 100 000, and 1000 000 000 without the challenge of storage overflow. The input samples tested in this work was the discretized pulse wave form with undulating shape out of which the binary equivalents were extracted. Other forms of signals may also be tested in this fast algorithm provided they are interpreted in the digital wave type. In order to optimized the advantage of the developed algorithms, the frequency index, K should be as defined in this study, that is

Triggering rare earth texture modification in magnesium alloys by addition of zinc and zirconium

Two Mg alloys, Mg–1Zn–1Ce–0.6Zr and Mg–1Zn–1Gd–0.6Zr (wt.%), were subjected to large strain hot rolling treatment, followed by annealing at different temperatures. Nucleation of recrystallization initiated inside shear bands and in the vicinity of particles, resulting in a panorama of orientations with varying stored energies. Recrystallization resulted in the evolution of new, softer orientations, in terms of slip, accompanied by significant texture weakening. On comparison with their respective binary counterparts, the quaternaries established the significant role played by the additional presence of non-rare earth (non-RE) elements (Zn, Zr) in augmenting the RE texture modification effect. Contrary to Mg–1Ce, deformation/recrystallization texture modification in Mg–1Zn–0.6Zr–1Ce was governed by a complex interplay between precipitate redissolution and segregation events. Moreover, compared to Mg–1Gd, the Mg–1Zn–0.6Zr–1Gd alloy revealed deformation/recrystallization texture transition at lower annealing temperature. Such a behavior was attributed to an increased tendency of RE–non-RE solute-pairing/clustering in the latter, thereby amplifying solute drag and magnifying selective growth events. Tensile tests conducted post-annealing revealed remarkable ductility improvement in the quaternary alloys over their binary equivalents.

Design Methodology for Relational Databases : Issues Related to Ternary Relationships in Entitiy-Relationship Model and Higher Normal Forms

Entity-Relationship (ER) modeling plays a major role in relational database design. The data requirements are conceptualized using an ER model and then transformed to relations. If the requirements are well understood by the designer and then if the ER model is modeled and transformed to relations, the resultant relations will be normalized. However the choice of modeling relationships between entities with appropriate degree and cardinality ratio has a very severe impact on database design. In this paper, we focus on the issues related to modeling binary relationships, ternary relationships, decomposing ternary relationships to binary equivalents and transforming the same to relations. The impact of applying higher normal forms to relations with composite keys is analyzed. We have also proposed a methodology which database designers must follow during each phase of database design.

Reduced complexity analogue-to-residue conversion employing folding number system

Digital signal processing (DSP) algorithms are computationally intensive and require recursive multiplication and addition. Residue number systems (RNS) offer significant advantages over conventional number systems when used in the design of special purpose DSP architectures. However, conversion of analogue signals into their residue equivalents requires first converting the signal to binary equivalents and subsequently using modular circuits to convert the resultant binary to residues. A new number system called the folding number system (FNS) is proposed and used as the basis for residue conversion. Since FNS has one-to-one correspondence with RNS, the proposed method converts the analogue signal to its RNS equivalents using concealed symmetrical residues in FNS domain. The conversion is simple and uses analogue folding circuits, comparators and combinatorial logic circuits. High-frequency analogue signals can be efficiently converted thus enabling RNS to be implemented in high-speed signal processing architectures.

The strain dependence of the dynamic moduli of short fiber reinforced thermoplastic blends

In the present work we relate the microstructure of a distinct type of short fiber reinforced blends (SFRBs) to their melt rheology. These systems consist of polyamide-6 (PA6) and short glass fiber (GF) reinforcement dispersed in a polyethylene (PE) matrix. An appropriate choice of the components, their interfacial characteristics, and the processing route led to the formation of a continuous network, percolating throughout the matrix. The network consisted of fibers (GF) “welded” together by bridges of the dispersed phase material (PA6). A strong strain softening of the melts of the SFRBs was observed at strain amplitudes below 3%, which was absent for their binary equivalents with the same fiber loading and no second thermoplastic component. Based on the specific microstructure of the blends, a model is proposed that accounts for their strain softening behavior. The model considers the “capillary” forces acting between the fibers participating in the network. These capillary forces arise from the deformation of the PA6 bridges “welding” the fibers together. We propose that the macroscopic deformation process produces points of locally concentrated and magnified deformation. The deformation at these points is sufficient to produce the strain softening of the system. The three parameters that appear in the model have a clear physical meaning. The theoretical results are in good qualitative agreement with the experiments.

Risk Attitude and Market Behavior: Evidence from Experimental Asset Markets

In this paper we relate individual risk attitude as elicited by binary lotteries and certainty equivalents to market behavior. By analyzing 26 independent markets with a total of 280 participants we show that binary lottery choices and certainty equivalents are poorly correlated. Only lottery choices are related to market behavior: the higher the degree of risk aversion the lower the observed market activity. Females are more risk averse than males according to binary lotteries, submit fewer offers and engage less often in trades.

Binary Equivalents of Ternary Relationships in Entity-Relationship Modeling

Little work has been completed which addresses the logical composition and use of ternary relationships in entity-relationship modeling. Many modeling notations and most CASE tools do not allow for ternary relationships. Alternative methods and substitutes for ternary relationship structures do not necessarily reflect the original logic, semantics or constraints of a given situation. Furthermore, it has been shown that ternary relationships can be constrained by additional implicit binary constraints which do not occur in the logic of binary relationships. This paper develops an analytical perspective of ternary relationships. We investigate the logical relationships implicit to the ternary structure and then identify potential simplification through decomposition into binary equivalents. These alternative binary equivalents allow retention of the implicit logical structure, and consequently also retain the semantics of the original structure. The analysis investigates equivalency of lossless decompositions, preservation of functional dependencies and finally the ability to preserve update constraints (insertions and deletions). We identify which ternary relationships have true, fully equivalent, binary equivalents and those which do not. We provide an exhaustive analysis of cardinality combinations found in ternary relationships which practitioners can use to guide the way in which they deal with ternary relationships in conceptual modeling.

Recursive algorithm with C++ program for floating-point arithmetic

Floating point Arithmetic is a topic included in virtually all textbooks for Computer Systems (CS 3: ACM's Curriculum Recommendation) or for Computer Organization (CS 4: ACM's Curriculum Recommendation). This paper presents a mathematical optimization model for the topic. The problem of converting real (float) numbers into binary equivalents is first modeled as a Zero-One Integer Programming problem. Then, a Recursive Algorithm is formulated for Floating-Point Formats. Computer programs are written in both C and C++ for a 32-bit floating-point format, using the recursive algorithm. [The computer programs are available at the email

High-speed and low-cost reverse converters for the (2n-1, 2n, 2n+1) moduli set

In this brief, new architectures are presented for the conversion of residues to binary equivalents in the (2n-1, 2n, 2n+1) moduli set. Both of the architectures presented are based on a new algorithm, which eliminates a multiplication. In the design of the architectures, speed and cost are considered as the principal factors. The proposed architectures use fewer multipliers and adders of smaller size. A comparison in terms of hardware requirements, delay estimates, and complexity is made to establish the advantages of the proposed design.

Residue-to-binary arithmetic converter for the moduli set (2/sup k/, 2/sup k/-1, 2/sup k-1/-1)

This paper presents a new algorithm which converts moduli (2/sup k/, 2/sup k/-1, 2/sup k-1/-1) residue numbers to their binary equivalents; it is the first converter which has been dedicated to this particular moduli set. The complexity of conversion has been greatly reduced using new compact forms for the multiplicative inverses and the properties of modular arithmetic. A hardware implementation which utilizes adders only is also proposed. With a pipelined system, the throughput rate is that of a single (2k-1)-bit binary adder. Comparison results showed that the hardware requirements and the execution time of the new converter are less than half that needed by other converters.