In the last few decades, data communication has recorded massive improvements. These improvements were brought about by advancement in digital circuitry, its availability and persistent reduction in cost. Before the advancement of digital communication technology, analogue communication was the dominant means of transmitting data. As the internet expands across the globe, the need to transfer data over long distances increases. However, the major problem with analogue communication is that the quality of signals is lost with distance. Also, it has minimal security and does not support data integration. Digital communications provided an alternative to analogue communication. Today, digital modulations have become part and parcel of the present and future communication technologies. Despite the advantages of these schemes, the traditional channel impairments, such as noise, can affect their performance. Moreover, data transmission is mostly done over wireless channels, which are very unpredictable and are characterised by multipath fading effects. This paper presents a short research article that presents a study of digital modulation schemes (M-ary QAM and M-ary PSK) using MATLAB/Simulink under Additive White Gaussian Noise (AWGN). The result shows that, among the three modulation schemes compared, QAM has the best BER performance with minimal energy consumption.

This paper describes the typical process for monitoring surfaces contaminated by different sources, such as strontium ( 90 Sr), cobalt ( 60 Co) and chlorine ( 36 Cl), in a working environment. There are several detectors that are used to identify both the location and activity of a contamination source. In this report, the most effective detector to scan and monitor Beta-rays is the mini-monitor E, with an efficiency of 42.3%, 20% and 14% for detecting 90 Sr, 36 Cl and 60 Co, respectively. However, the NE BP/4A/4C scintillator detector was the most suitable for detecting Gamma-rays. In addition, a smear test was carried out by using a high-efficiency G-M tube and several different sources of 90 Sr. The decontamination process successfully reduced the contamination level to almost 2.1% of the original percentage of contamination when the first wipe was done.

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The technical details of RSA works on the idea that it is easy to generate the modulus by multiplying two sufficiently large prime numbers together, but factorizing that number back into the original prime numbers is extremely difficult. Suppose that \(N=p^r q^s\) are RSA modulus, where \(p\) and \(q\) are product of two large unknown of unbalance primes for \(2 \leq s<r\). The paper proves that using an approximation of \(\phi(N) \approx\) \(N-N^{\frac{r+8-1}{2 r}}\left(\lambda^{\frac{1-8}{2 r}}+\lambda^{\frac{-8}{2 r}}\right)+N^{\frac{r+8-2}{2 T}} \lambda^{\frac{1-8}{2 r}}\), private keys \(\frac{x^2}{y^2}\) can be found from the convergents of the continued fractions expansion of\[\left|\frac{e}{N-N^{\frac{r+8-1}{2 r}}\left(\lambda^{\frac{1-8}{2 r}}+\lambda^{\frac{-8}{2 r}}\right)+N^{\frac{r+8-2}{2 r}} \lambda^{\frac{1-8}{2 r}}}-\frac{y^2}{x^2}\right|<\frac{1}{2 x^4}\] which leads to the factorization of the moduli \(N=p^r q^s\) into unbalance prime factors p and q in polynomial time. The second part of this reseach report further, how to generalized two system of equations of the form \(e_ux^2\) - \(y^2_u\phi(N_u)\) = \(z_u\) and \(e_ux^2_u\) - \(y^2\phi(N_u)\) = \(z_u\) using simultaneous Diophantine approximation method and LLL algorithm to and the values of the unknown integers \(x,y_u\),\(\phi(N_u)\) and \(x_u\),y,\(\phi(N_u)\) respectively, which yeild to successful factorization of k moduli \(N_u=p^r_uq^s_u\) for u = 1,2, ... k in polynomial time.

This analysis examines a non-uniform heat source or sink, the flow of a power-law fluid induced by vertical parallel plates, and heat transfer using variable viscosity and thermal conductivity. Temperature likely exponentially changes viscosity and thermal conductivity. The implicit finite difference approach solves governing partial differential equations. Power-law index, Prandtl number, variable viscosity, and thermal conductivity are analysed. Skin friction, Nusselt number, and Sherwood number are graphically depicted to analyse channel fluid behaviour.