Comparative Analysis of Different CPU Scheduling Algorithms with Respect to Average Waiting Time and Average Turnaround Time | Chapter 11 | Mathematics and Computer Science: Research Updates Vol. 5

CPU scheduling is one of the fundamental concepts of an Operating System. Most CPU scheduling algorithms concentrate on maximising CPU utilisation and throughput and minimising turnaround time, waiting time, response time and number of context switches for a set of requests. Some of the popular CPU scheduling algorithms are First-Come-First-Served (FCFS), Shortest Job First (SJF), Priority Based (PB) and Round Robin (RR). It has been found that CPU scheduling algorithms serve as the basis of multiprogramming. This paper presents the relationship between existing CPU scheduling algorithms with respect to their average waiting time and average turnaround time through different cases. There are five cases where each of which has four parts, and each part represents different existing CPU scheduling algorithms, i.e. FCFS, SJF, RR, and PB. Each part assumes that there are four different processes with different or the same priority and arrival time depending upon the particular case, as designed in the Section 4 of this paper. The goal of this paper is to find out the relationship with respect to average waiting time and average turnaround time, when different cases are implemented on the existing CPU scheduling algorithms and find the fastest algorithm amongst the existing CPU scheduling algorithms taken in this article.

Case Formulation-

·         In case 1, the CPU bursts taken are 4, 3, 5 and 2 for all the respective 4 processes.

·         In case 2, the CPU burst taken is an addition of 1 from the CPU burst of case 1 of each process.

·         In case 3, the CPU burst taken is the subtraction of 2 from the CPU burst of case 2 of each process.

·         In case 4, the CPU burst taken is an addition of 3 from the CPU burst of case 3 of each process.

·         In case 5, the CPU burst taken is the addition of 1 from the CPU burst of case 4 of each process.

 

Author (s) Details

 

Biswarup Samanta
Sarala Birla University, Ranchi, Jharkhand, India.

 

Arinjay Biswas
Adobe Systems, Noida, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcsru/v5/4919

Evaluation of the Biosorption Capacity of Saccharomyces cerevisiae for Heavy Metals in Milk| Chapter 2 | Emerging Challenges in Agriculture and Food Science Vol. 5

A biotechnological approach for removing heavy metals from the environment involves the use of biosorbents such as bacteria, yeast, and algae. Heavy metal decontamination in food and water can also be accomplished with these microbes. Using Saccharomyces cerevisiae as a model, our study team looked at heavy metal biosorption in milk. Initial heavy metals (Pb, Cd, and Hg) were introduced to milk, and the bioremoval process was tracked for four days. The goal of this study is to see how exposure duration, temperature, S. cerevisiae concentration, and beginning metal concentration affect the bioremoval process of heavy metals (Pb, Cd, and Hg) in milk. S. cerevisiae concentration, beginning metal concentration, and exposure duration were statistically substantially linked with heavy metals removal (p values 0.05) according to the ANOVA analysis. After 4 days with 30108 CFU S. cerevisiae in milk, the maximum biosorption (70%) was found. These findings added to the growing body of data that S. cerevisiae is an effective biosorbent for heavy metal removal from milk, as well as a potentially safe and environmentally friendly tool for ensuring a safe and healthy food supply.

Author(s) Details:

R. Masoud,
Department of Food Science and Technology, Iran National Standards Organization, Tehran, Iran.

F. Mirmohammad-Makki,
Department of Food Science & Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran.

A. Zoghi,
Department of Food Science and Technology, National Nutrition and Food Technology Research Institute, Faculty of Nutrition Science and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Please see the link here: https://stm.bookpi.org/ECAFS-V5/article/view/6977

Evaluating the Protective Effect of Taraxacum Officinale against Oxidative Demage Induced by Lead (Pb) in Rats Exposed to Contaminated Diet | Chapter 5 | New Visions in Biological Science Vol. 6

 The goal of this study is to see if dandelion (Taraxacum officinale) can protect you against lead poisoning. Lead is thought to be an oxidative stress inducer in several tissues and organs. Female wistar rats were fed a diet containing 600 mg lead acetate per kilogramme of food (Pb) or a diet containing 20 g fresh dandelion leaves per kilogramme of food (Pb-DD), and then compared to a control group for 6 weeks. The researchers looked into a number of haematological and serum biochemical markers. When compared to the control group, the Pb group had a large decrease in RBC and haemoglobin levels, but a considerable increase in methemoglobin. The Pb-DD group had the same RBC counts and haemoglobin levels as the control group, but the methemoglobin percentage was considerably greater. The activities of AST, ALT, and alkaline phosphate, as well as total bilirubin and uric acid levels, all increased significantly in the Pb group. Except for uric acid, dandelion supplementation has kept all of the preceding biochemical markers within normal limits. However, there were no significant alterations in albumin, cholesterol, creatinine, or calcium concentrations in Pb or Pb-DD treated mice. The Pb-DD-treated group and the control group had no significant changes in histological exams of the liver, kidney, or ovary. Pb, on the other hand, has been linked to cystic formations and vacuolization in the liver, as well as necrosis and microcalcifications in the kidney. Ovarian tissue degradation was also seen in the Pb group, including the absence of corona radiata and granulosa cell death. Finally, adding dendelion to a Pb-contaminated meal reduced metal toxicity in female rats considerably.

Author(S) Details

Mansouri Ouarda
Faculty of Medicine, Laboratory of Animal Ecophysiology, University Badji Mokhtar-Annaba BP 12, Annaba 23000, Algeria.

Cherif Abdennour
Faculty of Sciences, Department of Biology, Laboratory of Animal Ecophysiology, University Badji Mokhtar-Annaba BP 12, Annaba 23000, Algeria.

Kamel Khelili
Faculty of Sciences, Department of Biology, Laboratory of Animal Ecophysiology, University Badji Mokhtar-Annaba BP 12, Annaba 23000, Algeria.

Radia Berredjem
Faculty of Sciences, Department of Biology, Laboratory of Animal Ecophysiology, University Badji Mokhtar-Annaba BP 12, Annaba 23000, Algeria.

Mohamed Salah Boulakoud
Faculty of Sciences, Department of Biology, Laboratory of Animal Ecophysiology, University Badji Mokhtar-Annaba BP 12, Annaba 23000, Algeria.

View Book:- https://stm.bookpi.org/NVBS-V6/article/view/4859