Academic Science Journal

Cache design in multiprocessor systems usually involves maintaining data consistency between
these processors that are achieved through implementation one of most important protocols
used for this purpose which are snooping protocol and directory-based protocol. It also includes
improved memory access time by reducing the time spent in three cases which are: miss rate,
miss penalty and time to hit in the cache. Generally, there exist three critical attributes that have
an impact on the performance of any coherence protocol in the cache which are low-latency
cache-to-cache misses, bandwidths efficiency and scalability challenges. In this research, a new
protocol has been proposed for coherent caches named PMOESI protocol. This protocol has
the same states of a standard MOESI protocol but the difference is in adding a new state named
Premier "P" and also an exclusive reference buffer is designed to be added to Level1 cache.
The MOESI protocol is a version of the snooping coherence protocol which each block in the
cache memory can have one of five (Modified, Owned, Exclusive, Shared, Invalid) states. From
using the proposed protocol, the performance is enhanced as a result of reducing latency time
in comparison with MOESI protocol. The reason behind this improvement is in using low
latency cache to cache transfer to deliver the desired block instead of fetching this block from
main memory for responding to request writing of remote processors.

The aim of this study was to identify immunomodulatory, apoptosis inducing and anticancer
activities of aqueous and alcoholic extracts of T. purpurea, regarding the size of tumor mass
and immunohistochemical detection of caspase 8 expressions and apoptotic index in mice
inoculated with HepG2, mouse hepatocellular carcinoma as therapeutic experimental system
for human. Forty-eight Balb / C albino mice were injected at legs with HepG2 cells. Tumor size
was measured twice a week, note that the measurement time period is one month.
Administration of aqueous extract (0.3,0.6,1.2) mg / kg and alcoholic extract of in (0.25,0.5,1)
mg/kg to HepG2 tumor-bearing mice showed a significant difference (P≤0.01) in tumor size
compared with control group. Inhibitory activity of aqueous and alcoholic extracts was dose
and duration dependent. The effective doses in reduction of tumor size were 1.2 mg / kg for
aqueous and 1mg/kg for alcoholic extract in which HepG2 tumor mass reduced in size for up
to 87.9 %. HepG2 bearing mice treated with T. purpurea aqueous and alcoholic extracts showed
significant increase (P ≤ 0.05) in apoptotic index compared with untreated control group.

This paper presents a proposed algorithm for removing undesired reflections from a single
mixture image captured in front of transparent glass mediums. The proposed algorithm
separates the single input image into background layer (actual scene) and the reflection layer
by clustering mixture image pixels, using the prior knowledge that the background edges are of
larger magnitude than reflection edges and the model of dichromatic reflection. Experimental
results on real-world images proved that the proposed algorithm gets a result of the background
image with reflections removed as much as possible. A quantitative and visual quality
comparison between the proposed algorithm and state of the art algorithms is performed.

In this work, new compounds, (S1-S17) were synthesized through the reaction of 5-amino-1,3,4
thiadiazole-2-thiol with different aromatic aldehyde by using fusion method. The newly
synthesized compounds were confirmed by FT-IR-spectra and 1H-NMR, the biological activity
of some new compound tested in vitro, against some bacterial positive and negative

Satellite image classification is a valuable technique for producing worthy information. This
paper deal with high-resolution satellite for scene classification. In this research presents three
algorithms were used to extract the features which are local binary patterns, gray level co
occurrence matrix, and color histogram features. The classification process included the use of
two types of data mining techniques belongs to supervisor classification which are support
vector machines, and k-nearest neighbor. Test results explain that the proposed classification
method obtains a very auspicious performance.

In this paper, an enhancement of LSB audio steganography is presented. This enhancement is
based on the mathematical foundations of the magic cube and magic square. Magic cube is a
branch of mathematical combinatorics. It is one of the different arrays in magic number
arrangements. The proposed technique focuses on normal magic cubes of order (3, 4, … n).
The values inside the designed magic cube are used as an index to audio cover locations. These
scrambled locations (according to the keys of the magic cube) in the audio cover are used to
(LSB) embed secret text message. In order to increase the security of the proposed system, the
starting number, the difference value, the dimension, and the values inside the magic cube are
kept as a secret key. The NIST package is successfully used to test the randomness of the magic
cube's keys values. The PSNR values of audio stego-covers are (62.65743352-79.57336476)
dB in which the size of secret text message (256-16) bits.

Nowadays, due to the accelerated advancement of internet and multimedia technology,
transmission and spreading of multimedia data have become very easy work. This has become
a thoughtful threat to the owners of multimedia content. Therefore, a major attention has been
given to multimedia data copyright security. In this paper, the proposal of an audio
watermarking algorithm that is secure, robust, and blind for copyright security was presented.
Decomposing the audio signal is made first with Discrete Wavelet Transform (DWT), thereafter
selecting the coefficient of low-frequency which then made into frames. Next, on each frame,
Discrete Cosine Transform (DCT) is directed. The essential features are concluded from the
entered audio signal, then these features are encoded to produce Quick Response (QR) code to
produce the watermark image, and by a novel technique which utilizes Rubik's cube, this
watermark image is next encrypted. Later the watermark bits are implemented into DCT
coefficient by Quantization Index Modulation )QIM( determined by frame number. The results
of experiments imply that this algorithm is strong against numerous signal strikes, unnoticeable
and has an elevated average Signal to Noise Ratio (SNR) value reaches 61 dB.

Discriminatory analysis is one of the most widely used statistical methods in the field of data
analysis and classification, which can be used as linear models in the field of data classification.
One of the basic conditions that must be available in the qualitative analysis is that the
homogeneity of the matrix of variance and the common covariance and the test of the normal
distribution of the data. We also note that the analysis of distinction is outlier of the same;
Including the test (Kolmogorov Smirnov) and this test exists in the statistical program SPSS.
The important objective of using the differential analysis method is to test the significance of
differences between groups for independent variables as well as to differentiate the independent
variables that share as much differences as possible between the dependent variable groups.

In this study, a nanocomposite cobalt ferrite / graphene, CoFe2O4-G was prepared by sol-gel
method, and was identified by (XRD, AFM, and SEM) techniques. The composite was used to
remove sulfur from the Iraqi kerosene (Al-Doura refinery) with a concentration of 500 ppm of
sulfur. Oxidative desulfurization was used in the sulfur removal from kerosene and the
composite appeared to have good effectiveness in the removal of sulfur from this kerosene
under various conditions (Time, temperature, O/S ratio, and catalyst weight) as it showed a high
removal activity of sulfur at optimum conditions which exceed 90 %

Particle swarm optimization (PSO) has magnetized different investigators who are concerned
in dealing with different optimization problems, due to its ease of implementation and
reasonable performance. However, PSO algorithm is trapped in the local optima easily because
of the quick loss of the population variance. Hence, enhancement of the performance of PSO
and detraction the relaying on factors are led to significant variants of SPSO. One important
variant is the quantum behavior of particle swarm optimization (QPSO), which is dependent on
the dynamical analysis of SPSO and quantum mechanics. This paper presents a notion for the
optimization of nonlinear functions using swarm methodology and a comparison between
SPSO and QPSO are given. These two algorithms are analyzed on both unimodal and
multimodal, high and low dimensional continuous functions. The results on eight benchmark
functions show that the QPSO algorithm can perform much better than the SPSO.