A Genetic Algorithm for Power-Aware Virtual Machine Allocation in Private Cloud

Energy efficiency has become an important measurement of scheduling algorithm for private cloud. The challenge is trade-off between minimizing of energy consumption and satisfying Quality of Service (QoS) (e.g. performance or resource availability on time for reservation request). We consider resource needs in context of a private cloud system to provide resources for applications in teaching and researching. In which users request computing resources for laboratory classes at start times and non-interrupted duration in some hours in prior. Many previous works are based on migrating techniques to move online virtual machines (VMs) from low utilization hosts and turn these hosts off to reduce energy consumption. However, the techniques for migration of VMs could not use in our case. In this paper, a genetic algorithm for power-aware in scheduling of resource allocation (GAPA) has been proposed to solve the static virtual machine allocation problem (SVMAP). Due to limited resources (i.e. memory) for executing simulation, we created a workload that contains a sample of one-day timetable of lab hours in our university. We evaluate the GAPA and a baseline scheduling algorithm (BFD), which sorts list of virtual machines in start time (i.e. earliest start time first) and using best-fit decreasing (i.e. least increased power consumption) algorithm, for solving the same SVMAP. As a result, the GAPA algorithm obtains total energy consumption is lower than the baseline algorithm on simulated experimentation.Comment: 10 page

New scheduling problems with interfering and independent jobs

33 pages. Paper submitted to Journal of scheduling the 8 September 2009.We consider the problems of scheduling independent jobs, when a subset of jobs has its own objective function to minimize. The performance of this subset of jobs is in competition with the performance of the whole set of jobs and compromise solutions have to be found. Such a problem arises for some practical applications like ball bearing production problems. This new scheduling problem is positioned within the literature and the differences with the problems with competing agents or with interfering job set problems are presented. Classical and regular scheduling objective functions are considered and epsilon-constraint approach and linear combination of criteria approach are used for finding compromise solutions. The study focus on single machine and identical parallel machine environments and for each environment, the complexity of several problems is established and some dynamic programming algorithms are proposed

DIFFICULTIES WITH WORD CHOICE IN ACADEMIC WRITING AND SOLUTIONS: A RESEARCH ON ENGLISH-MAJORED STUDENTS AT CAN THO UNIVERSITY, VIETNAM

Writing, especially academic writing, is highly valued in foreign language acquisition, particularly for English majors. Nevertheless, using academic terminology might be difficult for students still developing their academic language abilities. The purpose of this research is to understand students' difficulties in selecting appropriate words in academic writing and offer solutions to overcome such difficulties. The participants were 78 English majors (high-quality program, course 45) and three lecturers at the Department of English Language and Culture, School of Foreign Languages, Can Tho University. Questionnaires were used to measure their difficulties in word choice in academic writing and semi-structured interviews were utilized to find solutions. The results show that most participants had a basic knowledge of academic vocabulary, which was demonstrated through their ability to select the appropriate word choice. However, students found it difficult to choose the right words in their academic writing. The reasons are that academic words are not easy to remember and not successfully used in the context of the meaning of the word and do not have an effective method of learning academic vocabulary. Based on the results, several specific approaches have been proposed to help students find the most suitable strategies for learning and using academic vocabulary for their writing.  Article visualizations

Neighborhood search for solving personal scheduling problem in available time windows with split-min and deadline constraints

The scheduling of individual jobs with certain constraints so that efficiency is a matter of concern. Jobs have deadlines to complete, can be broken down but not too small, and will be scheduled into some available time windows. The goal of the problem is to find a solution so that all jobs are completed as soon as possible. This problem is proved to be a strongly $NP$-hard problem. The implementation of the proposed MILP model using a CPLEX solver was also conducted to determine the optimal solution for the small-size dataset. For large-size dataset, heuristic algorithms are recommended such as First Come First Served (FCFS), Earliest Deadline (EDL), and neighborhood search including  Stochastic Hill Climbing (SHC), Random Restart Hill Climbing (RRHC), Simulated Annealing (SA) to determine a good solution in an acceptable time. Experimental results will present in detail the performance among the groups of exact, heuristic, and neighborhood search methods

Minimizing makespan of Personal Scheduling problem in available time-windows with split-min and setup-time constraints

This paper deals with personal scheduling problem in available time-windows with split-min and setup-time constraints. The jobs are splitable into sub-jobs and a common lower bound on the size of each sub-job is imposed. The objective function aims to find a feasible schedule that minimizes the maximum completion time of all jobs. The proposed scheduling problem was proved to be strongly NP-hard by a reduction to 3-SAT problem in the preliminary results. We propose in this paper an exact method based on MILP model to find optimal solution, some heuristics to find feasible solution and a meta-heuristic based on tabu search algorithm to find good solution. The computational results show the performance of proposed exact method, some heuristics and tabu search algorithm

Antibacterial activities of ethanolic extract of four species of Rutaceae family

In this study, the antibacterial activity of ethanolic extract from the leaves of four Rutaceae species, including Acronychia pedunculata, Clausena excavata, Glycosmis pentaphylla and Luvunga scandens, were performed using the agar disk diffusion method for the first time. The ethanolic extracts from the leaves of A. pedunculata and G. pentaphylla were able to resist against all six bacterial strains with zones of inhibition for Bacillus cereus (17.3±2.1 mm, 20.8±1.0 mm) Staphylococcus aureus (8.5±0.5 mm, 17.6±0.3 mm) Escherichia coli (16.7±2.1 mm, 15.3±1.2 mm), Pseudomonas aeruginosa (11.7±0.6 mm, 14.0±1.7 mm), Salmonella enteritidis (22.3±0.6 mm, 24.6±0.5 mm) and Salmonella typhimurium (9.5±0.9 mm, 8.3±0.6 mm). On the other hand, the ethanolic extract of C. excavata leaf was resistant to B. cereus (12.3±0.6 mm), S. aureus (11.6±0.5 mm), E. coli (11.5±2.1 mm), P. aeruginosa (10.6±0.3 mm) while B. cereus (8.2±0.3 mm), S. aureus (9.3±0.6 mm), E. coli (8.5±0.5 mm) and S. typhimurium (8.3±0.6 mm) were inhibited by the ethanolic extract of L. scandens leaf. This study could provide necessary information for further application of these species in medicine

Single-machine Scheduling with Splitable Jobs and Availability Constraints

This paper deals with a single machine scheduling problem with availability constraints. The jobs are splitable and lower bound on the size of each sub-job is imposed. The objective is to find a feasible schedule that minimizes the makespan. The proposed scheduling problem is proved to be NP-hard in the strong sense. Some effective heuristic algorithms are then proposed. Additionally, computational results show that the proposed heuristic performs well

Students’ Perceptions on Blended Synchronous Learning in the Postcrisis Era

With the severe impacts of the Covid-19 pandemic, the educational systems have to be reformed and evolved. Blended synchronous learning has become an attractive tendency in education worldwide as the technology has mushroomed recently and attracts a vast number of users and researchers. Therefore, the current study was conducted to investigate students’ overall perceptions of blended synchronous learning as well as its benefits and challenges. 163 participants in the study have experienced ENT courses in a blended synchronous learning environment for 105 hours within 7 weeks. The instrument employed in the quantitative phase was 27 items adapted from studies by Rahman et al. (2015), López-Pérez et al. (2011), and Wu et al. (2010). Additionally, semi-structured interviews were used to have a deeper understanding of the research issues. Results indicate that more than half of participants had good perceptions about the blended synchronous learning environment and perceived various benefits as well as challenges of it. Moreover, these findings are supplemented with illustrative quotes from interview transcripts to compare and contrast with previous findings reported in the literature, and therefore this study contributes to the field by offering the learners\u27 voices

Chemical composition and antibacterial activities of the ethanol extracts from the leaves and tubers of Amorphophallus pusillus

Amorphophallus pusillus is a rare species which is found only in Binh Chau-Phuoc Buu Nature Reserve. In this study, we determined 7 flavonoid compounds in tuber and leaf of A. pusillus, including of vitexin, orientin, vitexin 2?-O-glucoside, cyanidin 3-O-rutinoside, pelargonidin 3-O-glucoside, schaftoside, and peonidin 3-O-rutinoside via liquid chromatography-mass spectrometry (LC-MS). Furthermore, we have proved the antibacterial activities of ethanol extracts obtained from A. pusillus leaves and tubers in the first time. The data revealed that ethanol extracts could inhibit the growth of 6 tested microorganisms, such as Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Salmonella enteritidis, Salmonella typhimurium, and Staphylococcus aureus. These data suggested the potential application of ethanol extracts isolated from this species as natural antimicrobial agents for treatment of infection caused by bacteria, especially in dermatologic and enteric infections