Branch and Bound Algorithm for Multiprocessor Scheduling

The multiprocessor task graph scheduling problem has been extensively studied asacademic optimization problem which occurs in optimizing the execution time of parallelalgorithm with parallel computer. The problem is already being known as one of the NPhardproblems. There are many good approaches made with many optimizing algorithmto find out the optimum solution for this problem with less computational time. One ofthem is branch and bound algorithm.In this paper, we propose a branch and bound algorithm for the multiprocessor schedulingproblem. We investigate the algorithm by comparing two different lower bounds withtheir computational costs and the size of the pruned tree.Several experiments are made with small set of problems and results are compared indifferent sections.

Using ant colonies for solve the multiprocessor task graph scheduling

The problem of scheduling a parallel program presented by a weighted directed acyclic graph (DAG) to the set of homogeneous processors for minimizing the completion time of the program has been extensively studied as academic optimization problem which occurs in optimizing the execution time of parallel algorithm with parallel computer.In this paper, we propose an application of the Ant Colony Optimization (ACO) to a multiprocessor scheduling problem (MPSP). In the MPSP, no preemption is allowed and each operation demands a setup time on the machines. The problem seeks to compose a schedule that minimizes the total completion time.We therefore rely on heuristics to find solutions since solution methods are not feasible for most problems as such. This novel heuristic searching approach to the multiprocessor based on the ACO algorithm a collection of agents cooperate to effectively explore the search space.A computational experiment is conducted on a suit of benchmark application. By comparing our algorithm result obtained to that of previous heuristic algorithm, it is evince that the ACO algorithm exhibits competitive performance with small error ratio.

University Scheduling using Genetic Algorithm

The automated timetabling and scheduling is one of the hardest problem areas. This isbecause of constraints and satisfying those constraints to get the feasible and optimizedschedule, and it is already proved as an NP Complete (1) [1]. The basic idea behind this studyis to investigate the performance of Genetic Algorithm on general scheduling problem underpredefined constraints and check the validity of results, and then having comparative analysiswith other available approaches like Tabu search, simulated annealing, direct and indirectheuristics [2] and expert system. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems and later analysis will prove this argument. The programis written in C++ and analysis is done by using variation in various parameters.

Communication in Smoking Cessation and Self-management : a study at Nurse-led COPD-clinics in Primary Health Care

ABSTRACTThe general aim of this thesis was to investigate behavioral change communication at nurse-led chronic obstructive pulmonary disease (COPD) clinics in primary health care, focusing on communication in self-management and smoking cessation for patients with COPD.Designs: Observational, prospective observational and experimental designs were used.Methods: To explore and describe the structure and content of self-management education and smoking cessation communication, consultations between patients (n=30) and nurses (n=7) were videotaped and analyzed with three instruments: Consulting Map (CM), the Motivational Interviewing Treatment Integrity (MITI) scale and the Client Language Assessment in Motivational Interviewing (CLAMI). To examine the effects of structured self-management education, patients with COPD (n=52) were randomized in an intervention and a control group. Patients’ quality of life (QoL), knowledge about COPD and smoking cessation were examined with a questionnaire on knowledge about COPD and smoking habits and with St. George’s Respiratory Questionnaire, addressing QoL. Results: The findings from the videotaped consultations showed that communication about the reasons for consultation mainly concerned medical and physical problems and (to a certain extent) patients´ perceptions. Two consultations ended with shared understanding, but none of the patients received an individual treatment-plan. In the smoking cessation communication the nurses did only to a small extent evoke patients’ reasons for change, fostered collaboration and supported patients’ autonomy. The nurses provided a lot of information (42%), asked closed (21%) rather than open questions (3%), made simpler (14%) rather than complex (2%) reflections and used MI non-adherent (16%) rather than MI-adherent (5%) behavior. Most of the patients’ utterances in the communication were neutral either toward or away from smoking cessation (59%), utterances about reason (desire, ability and need) were 40%, taking steps 1% and commitment to stop smoking 0%. The number of patients who stopped smoking, and patients’ knowledge about the disease and their QoL, was increased by structured self-management education and smoking cessation in collaboration between the patient, nurse and physician and, when necessary, a physiotherapist, a dietician, an occupational therapist and/or a medical social worker.Conclusion The communication at nurse-led COPD clinics rarely involved the patients in shared understanding and responsibility and concerned patients’ fears, worries and problems only to a limited extent. The results also showed that nurses had difficulties in attaining proficiency in behavioral change communication. Structured self-management education showed positive effects on patients’ perceived QoL, on the number of patients who quit smoking and on patients’ knowledge about COPD.

GRASP and statistical bounds for heuristic solutions to combinatorial problems

The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few metaheuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds has previously been found reliable when obtained from the Genetic algorithm whereas in this work they found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.

University Timetabling using Genetic Algorithm

The field of automated timetabling and scheduling meeting all the requirementsthat we call constraints is always difficult task and already proved as NPComplete. The idea behind my research is to implement Genetic Algorithm ongeneral scheduling problem under predefined constraints and check the validityof results, and then I will explain the possible usage of other approaches likeexpert systems, direct heuristics, network flows, simulated annealing and someother approaches. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems. The program written in C++ and analysisis done with using various tools explained in details later.

Flipped classroom and learning strategies

This paper seeks to answer the research question "How does the flipped classroom affect students’ learning strategies?" In e-learning research, several studies have focused on how students and teachers perceive the flipped classroom approach. In general, these studies have reported pleasing results. Nonetheless, few, if any, studies have attempted to find out the potential effects of the flipped classroom approach on how students learn. This study was based on two cases: 1) a business modelling course and 2) a research methodology course. In both cases, participating students were from information systems courses at Dalarna University in Sweden. Recorded lectures replaced regular lectures. The recorded lectures were followed by seminars that focused on the learning content of each lecture in various ways. Three weeks after the final seminar, we arranged for two focus group interviews to take place in each course, with 8 to 10 students participating in each group. We asked open questions on how the students thought they had been affected and more dedicated questions that were generated from a literature study on the effects of flipped classroom courses. These questions dealt with issues about mobility, the potential for repeating lectures, formative feedback, the role of seminars, responsibility, empowerment, lectures before seminars, and any problems encountered. Our results show that, in general, students thought differently about learning after the courses in relation to more traditional approaches, especially regarding the need to be more active. Most students enjoyed the mobility aspect and the accessibility of recorded lectures, although a few claimed it demanded a more disciplined attitude. Most students also expressed a feeling of increased activity and responsibility when participating in seminars. Some even felt empowered because they could influence seminar content. The length of and possibility to navigate in recorded lectures was also considered important. The arrangement of the seminar rooms should promote face-to-face discussions. Finally, the types of questions and tasks were found to affect the outcomes of the seminars. The overall conclusion with regard to students’ learning strategies is that to be an active, responsible, empowered, and critical student you have to be an informed student with possibilities and mandate to influence how, where and when to learn and be able to receive continuous feedback during the learning process. Flipped classroom can support such learning.

Health problems in elderly patients during the first post-stroke year

BACKGROUND: A wide range of health problems has been reported in elderly post-stroke patients. AIM: The aim of this study was to analyse the prevalence and timing of health problems identified by patient interviews and scrutiny of primary health care and municipality elderly health care records during the first post-stroke year. METHODS: A total of 390 consecutive patients, ≥65 years, discharged alive from hospital after a stroke event, were followed for 1 year post-admission. Information on the health care situation during the first post-stroke year was obtained from primary health care and municipal elderly health care records and through interviews with the stroke survivors, at 1 week after discharge, and 3 and 12 months after hospital admission. RESULTS: More than 90% had some health problem at some time during the year, while based on patient record data only 4-8% had problems during a given week. The prevalence of interview-based health problems was generally higher than record-based prevalence, and the ranking order was moderately different. The most frequently interview-reported problems were associated with perception, activity, and tiredness, while the most common record-based findings indicated pain, bladder and bowel function, and breathing and circulation problems. There was co-occurrence between some problems, such as those relating to cognition, activity, and tiredness. CONCLUSIONS: Almost all patients had a health problem during the year, but few occurred in a given week. Cognitive and communication problems were more common in interview data than record data. Co-occurrence may be used to identify subtle health problems.