Scheduling tools to reduce the cost of cane railway transport

Cane railway systems provide empty bins for harvesters to fill and full bins of cane for the factory to process. These operations need to be conducted in a timely fashion to minimise delays to harvesters and the factory and to minimise the cut-to-crush delay, while also minimising the cost of providing this service. A range of tools has been provided over the years to assist in this process. This paper reviews the objectives of the cane transport system and the tools available to achieve those objectives. The facilities within these tools to assist in the control of costs are highlighted.

Rural first year university students: As engaged, aspirational and motivated as anyone – but different science ‘choices’ in year 12 and university

This paper reports on findings from the Interests and Recruitment in Science study, which explored the experiences of first year students studying science, technology, engineering and mathematics (STEM) courses in Australian universities. First year STEM students who went to school in rural or regional areas were as engaged, aspirational and motivated as their more metropolitan counterparts. However, they were less likely to have studied physics or advance mathematics, and more likely to have enrolled in an Agricultural or Environmental Science degree. The relationships between these results and broader contextual issues such as employment and Higher Education budgetary and policy settings are discussed.

A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

Enhancing Physics Education in the National Defence University : A design based research approach in the production of learning material

This research is connected with an education development project for the four-year-long officer education program at the National Defence University. In this curriculum physics was studied in two alternative course plans namely scientific and general. Observations connected to the later one e.g. student feedback and learning outcome gave indications that action was needed to support the course. The reform work was focused on the production of aligned course related instructional material. The learning material project produced a customized textbook set for the students of the general basic physics course. The research adapts phases that are typical in Design Based Research (DBR). The research analyses the feature requirements for physics textbook aimed at a specific sector and frames supporting instructional material development, and summarizes the experiences gained in the learning material project when the selected frames have been applied. The quality of instructional material is an essential part of qualified teaching. The goal of instructional material customization is to increase the product's customer centric nature and to enhance its function as a support media for the learning process. Textbooks are still one of the core elements in physics teaching. The idea of a textbook will remain but the form and appearance may change according to the prevailing technology. The work deals with substance connected frames (demands of a physics textbook according to the PER-viewpoint, quality thinking in educational material development), frames of university pedagogy and instructional material production processes. A wide knowledge and understanding of different frames are useful in development work, if they are to be utilized to aid inspiration without limiting new reasoning and new kinds of models. Applying customization even in the frame utilization supports creative and situation aware design and diminishes the gap between theory and practice. Generally, physics teachers produce their own supplementary instructional material. Even though customization thinking is not unknown the threshold to produce an entire textbook might be high. Even though the observations here are from the general physics course at the NDU, the research gives tools also for development in other discipline related educational contexts. This research is an example of an instructional material development work together the questions it uncovers, and presents thoughts when textbook customization is rewarding. At the same time, the research aims to further creative customization thinking in instruction and development. Key words: Physics textbook, PER (Physics Education Research), Instructional quality, Customization, Creativity

A generalized Linear Programming based approach to optimal divisible load scheduling

In this paper we propose a general Linear Programming (LP) based formulation and solution methodology for obtaining optimal solution to the load distribution problem in divisible load scheduling. We exploit the power of the versatile LP formulation to propose algorithms that yield exact solutions to several very general load distribution problems for which either no solutions or only heuristic solutions were available. We consider both star (single-level tree) networks and linear daisy chain networks, having processors equipped with front-ends, that form the generic models for several important network topologies. We consider arbitrary processing node availability or release times and general models for communication delays and computation time that account for constant overheads such as start up times in communication and computation. The optimality of the LP based algorithms is proved rigorously.

Scheduling parallel batch processors with incompatible job families using ant colony optimization

The present work concerns with the static scheduling of jobs to parallel identical batch processors with incompatible job families for minimizing the total weighted tardiness. This scheduling problem is applicable in burn-in operations and wafer fabrication in semiconductor manufacturing. We decompose the problem into two stages: batch formation and batch scheduling, as in the literature. The Ant Colony Optimization (ACO) based algorithm called ATC-BACO algorithm is developed in which ACO is used to solve the batch scheduling problems. Our computational experimentation shows that the proposed ATC-BACO algorithm performs better than the available best traditional dispatching rule called ATC-BATC rule.

Utilization bounds for RM scheduling on uniform multiprocessors

Utilization bounds for Earliest Deadline First(EDF) and Rate Monotonic(RM) scheduling are known and well understood for uniprocessor systems. In this paper, we derive limits on similar bounds for the multiprocessor case, when the individual processors need not be identical. Tasks are partitioned among the processors and RM scheduling is assumed to be the policy used in individual processors. A minimum limit on the bounds for a 'greedy' class of algorithms is given and proved, since the actual value of the bound depends on the algorithm that allocates the tasks. We also derive the utilization bound of an algorithm which allocates tasks in decreasing order of utilization factors. Knowledge of such bounds allows us to carry out very fast schedulability tests although we are constrained by the fact that the tests are sufficient but not necessary to ensure schedulability.

University Students' Approaches to Learning, Self-Regulation, and Cognitive and Attributional Strategies : Connections with Well-Being and Academic Success

This dissertation empirically explores the relations among three theoretical perspectives: university students approaches to learning, self-regulated learning, as well as cognitive and attributional strategies. The relations were quantitatively studied from both variable- and person-centered perspectives. In addition, the meaning that students gave to their disciplinary choices was examined. The general research questions of the study were: 1) What kinds of relationships exist among approaches to learning, regulation of learning, and cognitive and attributional strategies? What kinds of cognitive-motivational profiles can be identified among university students, and how are such profiles related to study success and well-being? 3) How do university students explain their disciplinary choices? Four empirical studies addressed these questions. Studies I, II, and III were quantitative, applying self-report questionnaires, and Study IV was qualitative in nature. Study I explored relations among cognitive strategies, approaches to learning, regulation of learning, and study success by using correlations and a K-means cluster analysis. The participants were 366 students from various faculties at different phases of their studies. The results showed that all the measured constructs were logically related to each other in both variable- and person-centered approaches. Study II further examined what kinds of cognitive-motivational profiles could be identified among first-year university students (n=436) in arts, law, and agriculture and forestry. Differences in terms of study success, exhaustion, and stress among students with differing profiles were also looked at. By using a latent class cluster analysis (LCCA), three groups of students were identified: non-academic (34%), self-directed (35%), and helpless students (31%). Helpless students reported the highest levels of stress and exhaustion. Self-directed students received the highest grades. In Study III, cognitive-motivational profiles were identified among novice teacher students (n=213) using LCCA. Well-being, epistemological beliefs, and study success were looked at in relation to the profiles. Three groups of students were found: non-regulating (50%), self-directed (35%), and non-reflective (22%). Self-directed students again received the best grades. Non-regulating students reported the highest levels of stress and exhaustion, the lowest level of interest, and showed the strongest preference for certain and practical knowledge. Study IV, which was qualitative in nature, explored how first-year students (n = 536 ) in three fields of studies, arts, law, and veterinary medicine explained their disciplinary choices. Content analyses showed that interest appeared to be a common concept in students description of their choices across the three faculties. However, the objects of interest of the freshmen appeared rather unspecified. Veterinary medicine and law students most often referred to future work or a profession, whereas only one-fifth of the arts students did so. The dissertation showed that combining different theoretical perspectives and methodologies enabled us to build a rich picture of university students cognitive and motivational predispositions towards studying and learning. Further, cognitive-emotional aspects played a significant role in studying, not only in relation to study success, but also in terms of well-being. Keywords: approaches to learning, self-regulation, cognitive and attributional strategies, university students

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Dimensions of University Student Learning in Medicine and Pharmacy

Study orientations in higher education consist of various dimensions, such as approaches to learning, conceptions of learning and knowledge (i.e. epistemologies), self-regulation, and motivation. They have also been measured in different ways. The main orientations typically reported are reproducing and meaning orientations. The present study explored dimensions of study orientations, focusing in particular on pharmacy and medicine. New versions of self-report instruments were developed and tested in various contexts and in two countries. Furthermore, the linkages between study orientations and students epistemological development were explored. The context of problem-based (PBL) small groups was investigated in order to better understand how collaboration contributes to the quality of learning. The participants of Study I (n=66) were pharmacy students, who were followed during a three-year professionally oriented program in terms of their study orientations and epistemologies. A reproducing orientation to studying diminished during studying, whereas only a few students maintained their original level of meaning orientation. Dualism was found to be associated with a reproducing orientation. In Study II practices associated with deep and surface approaches to learning were measured in two differing ways, in order to better distinguish between what students believed to be useful in studying, and the extent to which they applied their beliefs to practice when preparing for examinations. Differences between domains were investigated by including a sample of Finnish and Swedish medical students (n=956) and a Finnish non-medical sample of university students (n=865). Memorizing and rote learning appeared as differing components of a surface approach to learning, while understanding, relating, and critical evaluation of knowledge emerged as aspects of a deep approach to learning. A structural model confirmed these results in both student samples. Study III explored a wide variety of dimensions of learning in medical education. Swedish medical students (n=280) answered the questionnaire. The deep approach to learning was strongly related to collaboration and reflective learning, whereas the surface approach was associated with novice-like views of knowledge and the valuing of certain and directly applicable knowledge. PBL students aimed at understanding, but also valued the role of memorization. Study IV investigated 12 PBL tutorial groups of students (n=116) studying microbiology and pharmacology in a medical school. The educational application was expected to support a deep approach to learning: Group members course grades in a final examination were related to the perceived functioning of the PBL tutorial groups. Further, the quality of cases that had been used as triggers for learning, was associated with the quality of small group functioning. New dimensions of study orientations were discovered. In particular, novel, finer distinctions were found within the deep approach component. In medicine, critical evaluation of knowledge appeared to be less valued than understanding and relating. Further, collaboration appeared to be closely related to the deep approach, and it was also important in terms of successful PBL studying. The results of the studies confirmed the previously found associations between approaches to learning and study success, but showed interesting context- and subgroup-related differences in this respect. Students ideas about the nature of knowledge and their approaches to learning were shown to be closely related. The present study expanded our understanding of the dimensions of study orientations, of their development, and their contextual variability in pharmacy and medicine.

Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.