Mustansiriyah journal of pure and applied sciences

The problem of uniform Parallel Machine Scheduling (UPMS) in manufacturing system is considered with utilizing the aims of minimizing total completion time, total tardiness and total earliness. Multi objective functions have been developed to select optimal solution in uniform parallel machine scheduling. In the present study, our focus is on the NP-hard problem for scheduling n jobs on a uniform parallel machine. We develop the dominance properties are incorporated, is proposed and tested on a large set of randomly generated instances.

Zinc oxide nanoparticles (ZnO NPs) were successfully synthesized by a green method using Cumin and Curcuma and zinc acetate dihydrate [Zn (CH3COO)2. 2H2O]as salt precursors. The particle size and phase structure of zinc oxide were determined by X-ray diffraction and field emission scanning electron microscopy. The produced zinc oxide nano particles are crystalline with a grain size of 23–30 nm and agglomerated form. Energy Dispersive Spectrum (EDX) results affect the composition of Zinc and Oxygen, giving high energy signals of 76.9.4% and 23.1% for Oxygen and zinc, respectively. (FT-IR) spectroscopic analysis shows the absorption peak of Zinc and oxygen Zn–O bonding between 400 and 600 cm-1. The different characterization methods carried out prove the formation of nano Zinc oxide. The ZnO NPs were used as catalysts for the photodegradation of methylene blue under visible light radiation. The results indicate that the prepared ZnO material excellently removed MB methylene blue after 120 min, this green method of synthesis was found to be eco-friendly.

This work began by addressing the essential and sufficient requirements that must be met in order for a solution to the operator equation ß????????=????=????∗????ß∗ system to exist, where these operators are linear and bounded on a Hilbert space. Subsequently, the general solution for this system was formulated, and the work concluded by discussing the existence of the Hermitian solution under specific conditions.

The amount of rainfall appreciation is considered one of the most important data that affects many aspects of development and Sustainability in Iraq. Remote sensing (RS) is the study of gathering and analyzing data remotely using sensors that are not near the thing viewed. The dataset came from the UK's Natural Environment Research Council (NERC) and the US National Centre currently provides - the Department of Energy Long-term support for Atmospheric Science with high-resolution (120) satellite images. The study area was exposed to several climatic factors that led to a large difference in amounts of rainfall. It analyzed for the large period (2011 - 2020) to extract an annual average. The northwestern regions received the most rain, while the western and southern regions received the least. The images analyzed were widely used for the Geographic Information Systems (GIS) program that served digital analysis and kriging interpolation. The number of images provides a multi-image. Each image represented a month of the year for ten years and was collected to extract the annual rainfall as a ratio for one year. The results showed that the digital analysis method displayed for rainfall, the highest value recorded (729.22 mm); the lowest value was (79.48 mm). The kriging indicator showed values close to the first method while providing data for the amounts of rain in every part of the study area. Knowledge about the uncertainties may record the applicability of these items for quantifying and proceedings these items' behavior characteristics essential to make applications simplification. Whereas the comparison between the kriging indicators with observed annual rainfall yield performed by linear equation (LQ) the value of its constant was (8.49). The GIS was a very good and efficient tool for calculating the amount of rainfall from satellite images Predicting rainfall patterns and the assessment of the amount of rainfall in the general circulation contributes to a better understanding of the ecosystem, biodiversity, and treatment of key crisis issues.

Heavy rainfall is closely associated with atmospheric rivers (ARs), which are long, narrow bands and ephemeral corridors with significant water vapor flux. This paper study the relation between ARs and low pressure system (L). Since there isn't a specialized study for this relationship, extreme rainfall cases were selected for the years 2023/4/11 to 2023/4/13. Which encompass the majority of Iraq and its neighbouring regions. Based on statistics from the Iraq Meteorological Organization and seismology, the amount of rain that falls over Iraq in this instance ranges from 10 to 100 mm each day, ARs mechanisms and roles in the Middle East's flooding are not well known. The links between ARs and L have been investigated through the use of vertically integrated moisture flux transfer (IVT). The results of the analysis of surface pressure system maps and the use of IVT to determine ARs indicated that, in this instance, the type of AR was weak over the Arbian Peninsula and up towards Iraq. Additionally, there was a low pressure area over the Arbian Peninsula that developed into a L and added moisture to intensify the AR, in addition to enhanced moisture from the Red Sea and North Africa. The rain gets heavier than at the first when the AR gets stronger. The presence of L together with ARs causes an increase in moisture content, which intensifies and gave depth to the ARs. However, L by itself does not always imply the existence of ARs.

A study was conducted on cauliflower and broccoli which were fermented to isolate and characterize lactic acid bacteria that are consumed in these fermented foods by people. One –hundred eighty isolates belong to the lactic acid bacteria were taken from 120 samples of different parts of cauliflower and broccoli were obtained from different markets of Baghdad city. Only 20 isolates were bacteriocin producers thus showed antibacterial activity against indicator bacterial isolates (S. aureus, S. agalactiae, E. coli and P. aeruginosa). The lactic acid bacteria (LabBr no. 28) isolate had the highest activity against indicator bacteria with inhibition zones of (22 mm) against S. aureus, (16.5 mm) against S. agalactiae ,(18mm) against P. aeruginosa and (19mm) against E.coli. This isolate was identified by using conventional methods then by VITEK®2 System .The identification was confirmed by16sRNA sequencing to characterize and describe the new species Leuconostoc carnosum .
The aim of this study: Recognition of lactic acid bacteria species that found in cauliflower and broccoli, which have ability to produce the bacteriocin by detection their ability to inhibit growth of pathogenic bacteria.

The aim of this study is to prepare lead oxide nanoparticles using a laser ablation method. Nanoparticles are prepared with different pulse numbers, ranging from 100 to 400 pulses. This study focuses on the difference in nanoparticle production with varying pulse numbers. The optical properties were studied using UV-Visible examination, and the results showed that increasing the number of laser pulses leads to an increase in both the optical absorption and the energy gap of lead oxide. Increasing the number of pulses leads to an increase in the average surface roughness of lead oxide. The presence of lead and oxide was confirmed in

The increasing importance of securing digital data in diverse applications requires the development of advanced encryption algorithms. This paper presents a hybrid encryption algorithm that combines the lightweight encryption algorithms Speck and PRESENT, specifically designed for limited devices in the Web of Things (WoT) environment. The proposed method is based on a chaotic key generation system to enhance security and performance. The algorithm aims for high-speed encryption, increasing complexity to protect data transmission in WoT. The hybrid model is implemented and tested in the Python programming language, focusing on textual data collected by sensors. Randomness was evaluated using the NIST statistical test suite, where the proposed method was compared to the Speck and PRESENT algorithms. The results showed superior performance in most NIST tests, indicating higher safety. In addition, the proposed algorithm showed significantly faster execution times across different file sizes compared to the individual SPECK and PRESENT algorithms.

In this research the nuclear structure each of isotopes even-even 134Ce and 136Nd within a frame Interaction Boson Model (IBM:1), Model (IBM – code, IBMT−cod, and IBMP−code) was studied. Based on the calculation of energy ratios (????+41/????+21) (????†61/????+21) and,(????+81/????+21), The probability of an electric transition ????(????2) is reduced, the electric quadrupole moments ????+for first positive parity level (2+), and potentiel enargy surfaces ????.????.????.The results of the current study were confirmed by comparison with the practical results of the latest dissolution schemes that can be obtained, every one of 134Ce and 136Nd they are located within the transitional region between the limit a Gamma-unstable ????(6)and SU(3) .This has a small effect ????0 parameter and cancel effect ???? parameter,according to the contour shapes of the nuclei using Interaction Boson Geometric (GBM) ,The nuclei are clearly deformed.

With the increasing use of antibiotics around the world, the study and appreciation of antibiotics has become essential. An antibiotic formulation may include one or added active ingredients depending on the type and method of manufacturing the antibiotic. Antibiotics can only combat diseases of bacterial origin. As for viral diseases such as the common cold and influenza, antibiotics will not be able to combat them. The objective of this review is to digest the literature related to estimation of antibiotics and to show the methods that have been used in the estimation of the antibiotics (amoxicillin, ampicillin, cephalothin, carbenicillin, and cefotaxime) in medicinal preparations and a biological fluid for example blood and urine of humans as well as animals. It is important to check the quality of drugs to confirm the composition of drugs used in pharmaceutical preparations. Many analytical procedures have been used to estimation of antibiotics, counting gas chromatography, high pressure liquid chromatography, spectroscopic and electrochemical methods, as well as flow injection, to assaying of antibiotics in several insets like tablets, capsules, and others. Here we conduct a quick narrative review that discusses and compares the different analytical methods for the estimation of antibiotic drugs.

Diarrhea is the second most important disease that cause death in children under 5 years old. This research aimed to investigate the prevalence of Enteroinvasive E. coli (EIEC) and Enterotoxogenic E. coli (ETEC) associated with diarrhea among children less than 5 years. One hundred stool samples have been collected from children under 5 years old whom suffering from acute diarrhea. All samples are cultured on MacConkey agar and Eosin Methylene Blue (EMB) for detection of Diarrheagenic E. coli (DEE). DNA extraction was carried out and PCR technique. was used for amplification of stp gene for detection of ETEC and ipaH gene for detection of EIEC. The results showed wide distribution of DEC (45%) among male and female where a high percentage of infection occurred among male (60%) in Compression with female (40%). The results of Agarose gel electrophoresis observed that 33% of isolates were possess ipaH which revealed that these isolates were belong to EIEC while 22% of isolates were possess stp gene which revealed that these isolates were belong to EHEC. In conclusion, diarrhea may associate with EIEC and EHEC in addition to EPEC.

The primary goal of this study is to explore the Triple Action of Representation Lie Algebras (ATHS) with unique characteristics on Lie algebra using Schur's lemma, which states that the action of the tensor product of Lie algebras representation has interesting property. This involves examining the interaction of Lie algebra representations, focusing on specific actions within Lie algebras. A new approach to the tensor product and direct sum for Lie algebra representations has been introduced. Additionally, this study explores the relationship between actions of Hom space and tensor product. The main goal is to achieve results on Lie algebra representations by using a new structure of six representations and their corresponding actions.

Image processing plays an important rule of the modern emerging research areas that based on discrete wavelet transforms due to their abilities to represent images at multiple resolutions efficiently. This multiple resolution analysis is so useful in many applications such as image compression, denoising, texture analysis, and feature extraction.
In this work, A newfound proposed LabVIEW2023 simulation is designed to produce a comparative study between several test images using different types of the most common discrete wavelet transforms (DWT).
The comparison is based on calculation of the total evaluation time needed for process and in addition making a study for image edge detection in terms of different threshold ratios. The discrete wavelets transform (DWT) that used to achieve these comparisons analysis are the orthogonal and biorthogonal wavelets families.
The new LabView 2023 simulation design enviroments exemplified that it is a simple, typical and speedy tool to give the best of the desired results. The final results showed the effectiveness of biorthogonal wavelet transform (bior6-8) over the other discrete wavelets transforms.

A building security surveillance system typically refers to a comprehensive setup designed to monitor and enhance security within a specific building. This system typically integrates various technologies and components to detect, assess, and respond to potential security threats. The ability of deep learning systems to draw informed conclusions has made them very popular in the field of security monitoring systems. However, centralized servers in many current deep learning systems prevent providing essential features such as verified data provenance, operational transparency, traceability, and reliability. On the other side, blockchain technology is a distributed and decentralized digital system composed of a series of blocks that include encrypted transaction data that can be shared among network users. Therefore, the integration of deep learning and blockchain technologies into security surveillance systems is an important area that provides improvements in data analysis, privacy, security, and overall efficiency of surveillance systems. This article reviews the significance of integrating deep learning algorithms and blockchain technology to develop a building security monitoring system. Furthermore, research related to integrating deep learning techniques with blockchain technology will be presented. Therefore, topics such as deep convolutional neural networks, blockchain concepts, and the measurements used to link these two technologies will be investigated and discussed. Finally, we present a comprehensive discussion of the state-of-the-art articles that must be investigated for building a robust deep learning system based on blockchain technology for security monitoring systems.

One of the ways that can be exercised in autoregressive model order chosen is to select the order that reduces the error of prediction. The final prediction error criterion employs this technique in order selection. Regrettably, this criterion has poor performance in case of finite samples. Karimi 2007 derived a criterion to address this problem. In this research, the Karimi criterion will be evaluated through the use of some distributions. These distributions are Discrete Uniform, Cauchy, t and Log normal, in addition to Gaussian distribution which is the basis of the Karimi criterion.

Nowadays, finding a free parking slot can be very stressful in densely populated areas like Karbala, especially in visiting days. Such parking process takes a long time, wastes significant gasoline and emits extra vehicle exhaust that harms the environment. The problem becomes even more significant when entering a multilevel parking lot, only to discover that there are no free spaces. This results in wasted time and frustration. To address this problems, an efficient smart parking management system is needed in all multilevel parking lots to ensure confusion-free and convenient parking. In this paper, we design a smart multilevel parking system using an Arduino microcontroller. This system will enable drivers to quickly identify available parking spaces, thereby reducing time, energy consumption, and air pollution. Also, we propose a predictive mathematical model to expect the state of the parking lot, thus enhancing the proposed management system in terms of reducing waiting time of the Arduino action for getting a free space from the IR parking sensor of the parking floors.