Minimizing impact of bounded uncertainty on McNaughton's scheduling algorithm via interval programming

Uncertainty of data affects decision making process as it increases the risk and the costs of the decision. One of the challenges in minimizing the impact of the bounded uncertainty on any scheduling algorithm is the lack of information, as only the upper bound and the lower bound are provided without any known probability or membership function. On the contrary, probabilistic uncertainty can use probability distributions and fuzzy uncertainty can use the membership function. McNaughton's algorithm is used to find the optimum schedule that minimizes the makespan taking into consideration the preemption of tasks. The challenge here is the bounded inaccuracy of the input parameters for the algorithm, namely known as bounded uncertain data. This research uses interval programming to minimise the impact of bounded uncertainty of input parameters on McNaughton’s algorithm, it minimises the uncertainty of the cost function estimate and increase its optimality. This research is based on the hypothesis that doing the calculations on interval values then approximate the end result will produce more accurate results than approximating each interval input then doing numerical calculations.

Exploring second life as a learning environment for computer programming

Computer programming can be challenging for beginners because of the need to understand abstract programming concepts. In this paper, we study the use of the Second Life (SL) virtual world for learning computer programming concepts. We conduct an empirical study for learning computer programming in SL by addressing affordances of SL for experiential problem-based learning pedagogies. We present preliminary findings, the promises and the limitations of Second Life as an environment for learning computer programming.

Fetal programming of schizophrenia: select mechanisms

Mounting evidence indicates that schizophrenia is associated with adverse intrauterine experiences. An adverse or suboptimal fetal environment can cause irreversible changes in brain that can subsequently exert long-lasting effects through resetting a diverse array of biological systems including endocrine, immune and nervous. It is evident from animal and imaging studies that subtle variations in the intrauterine environment can cause recognizable differences in brain structure and cognitive functions in the offspring. A wide variety of environmental factors may play a role in precipitating the emergent developmental dysregulation and the consequent evolution of psychiatric traits in early adulthood by inducing inflammatory, oxidative and nitrosative stress (IO&NS) pathways, mitochondrial dysfunction, apoptosis, and epigenetic dysregulation. However, the precise mechanisms behind such relationships and the specificity of the risk factors for schizophrenia remain exploratory. Considering the paucity of knowledge on fetal programming of schizophrenia, it is timely to consolidate the recent advances in the field and put forward an integrated overview of the mechanisms associated with fetal origin of schizophrenia.

From ranking fuzzy numbers to solving fuzzy linear programming: a comprehensive review

Solving fuzzy linear programming (FLP) requires the employment of a consistent ranking of fuzzy numbers. Ineffective fuzzy number ranking would lead to a flawed and erroneous solving approach. This paper presents a comprehensive and extensive review on fuzzy number ranking methods. Ranking techniques are categorised into six classes based on their characteristics. They include centroid methods, distance methods, area methods, lexicographical methods, methods based on decision maker's viewpoint, and methods based on left and right spreads. A survey on solving approaches to FLP is also reported. We then point out errors in several existing methods that are relevant to the ranking of fuzzy numbers and thence suggest an effective method to solve FLP. Consequently, FLP problems are converted into non-fuzzy single (or multiple) objective linear programming based on a consistent centroid-based ranking of fuzzy numbers. Solutions of FLP are then obtained by solving corresponding crisp single (or multiple) objective programming problems by conventional methods.

Solving fuzzy programming with a consistent fuzzy number ranking

 Some illustrative examples are provided to identify the ineffective and unrealistic characteristics of existing approaches to solving fuzzy linear programming (FLP) problems (with single or multiple objectives). We point out the error in existing methods concerning the ranking of fuzzy numbers and thence suggest an effective method to solve the FLP. Based on the consistent centroid-based ranking of fuzzy numbers, the FLP problems are transformed into non-fuzzy single (or multiple) objective linear programming. Solutions of FLP are then crisp single or multiple objective programming problems, which can respectively be obtained by conventional methods.

Extending scheduling algorithms to minimise the impact of bounded uncertainty using interval programming

 This research proposed a new methodology to extend algorithms to accept interval-based uncertain parameters. The methodology is applied on scheduling algorithms, including heuristic and meta-heuristic algorithms and produced optimal results with higher accuracy. The research outcomes are effective for decision making process using uncertain or predicted data.

Impact of Assurance of Learning (AOL) in programming course for novices

One of the aims of any higher education institution is to align its curriculum with program learning goals. Programs which ensure proper learning have positive effects on students, instructors, departments and also on the higher education institution itself. This paper discusses the implementation and effects of Assurance Of Learning (AOL) processes on introductory programming (IP) courses. It elaborates five stages of AOL to align program learning goals with IP curriculum. Then, it discusses how the AOL process identifies shortcomings in the assessment methods of IP courses. Furthermore, it enlightens how the assessment findings, as a result of the AOL process, provide mechanisms to address the drawbacks during the delivery of such courses. Feedback on

Investigating the effects of personality traits on pair programming in a higher education setting through a family of experiments

Evidence from our systematic literature review revealed numerous inconsistencies in findings from the Pair Programming (PP) literature regarding the effects of personality on PP's effectiveness as a pedagogical tool. In particular: i) the effect of differing personality traits of pairs on the successful implementation of pair-programming (PP) within a higher education setting is still unclear, and ii) the personality instrument most often used had been Myers-Briggs Type Indicator (MBTI), despite being an indicator criticized by personality psychologists as unreliable in measuring an individual's personality traits. These issues motivated the research described in this paper. We conducted a series of five formal experiments (one of which was a replicated experiment), between 2009 and 2010, at the University of Auckland, to investigate the effects of personality composition on PP's effectiveness. Each experiment looked at a particular personality trait of the Five-Factor personality framework. This framework comprises five broad traits (Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), and our experiments focused on three of these - Conscientiousness, Neuroticism, and Openness. A total of 594 undergraduate students participated as subjects. Overall, our findings for all five experiments, including the replication, showed that Conscientiousness and Neuroticism did not present a statistically significant effect upon paired students' academic performance. However, Openness played a significant role in differentiating paired students' academic performance. Participants' survey results also indicated that PP not only caused an increase in satisfaction and confidence levels but also brought enjoyment to the tutorial classes and enhanced students' motivation.

Endurance training in early life results in long-term programming of heart mass in rats

Being born small for gestational age increases the risk of developing adult cardiovascular and metabolic diseases. This study aimed to examine if early-life exercise could increase heart mass in the adult hearts from growth restricted rats. Bilateral uterine vessel ligation to induce uteroplacental insufficiency and fetal growth restriction in the offspring (Restricted) or sham surgery (Control) was performed on day 18 of gestation in WKY rats. A separate group of sham litters had litter size reduced to five pups at birth (Reduced litter), which restricted postnatal growth. Male offspring remained sedentary or underwent treadmill running from 5 to 9 weeks (early exercise) or 20 to 24 weeks of age (later exercise). Remarkably, in Control, Restricted, and Reduced litter groups, early exercise increased (P < 0.05) absolute and relative (to body mass) heart mass in adulthood. This was despite the animals being sedentary for ~4 months after exercise. Later exercise also increased adult absolute and relative heart mass (P < 0.05). Blood pressure was not significantly altered between groups or by early or later exercise. Phosphorylation of Akt Ser(473) in adulthood was increased in the early exercise groups but not the later exercise groups. Microarray gene analysis and validation by real-time PCR did not reveal any long-term effects of early exercise on the expression of any individual genes. In summary, early exercise programs the heart for increased mass into adulthood, perhaps by an upregulation of protein synthesis based on greater phosphorylation of Akt Ser(473).

Adaptivity in programming languages

A programming style can be seen as a particular model of shaping thought or a special way of codifying language to solve a problem. An adaptive device is made up of an underlying formalism, for instance, an automaton, a grammar, a decision tree, etc., and an adaptive mechanism, responsible for providing features for self-modification. Adaptive languages are obtained by using some programming language as the device’s underlying formalism. The conception of such languages calls for a new programming style, since the application of adaptive technology in the field of programming languages suggests a new way of thinking. Adaptive languages have the basic feature of allowing the expression of programs which self-modifying through adaptive actions at runtime. With the adaptive style, programming language codes can be structured in such a way that the codified program therein modifies or adapts itself towards the needs of the problem. The adaptive programming style may be a feasible alternate way to obtain self-modifying consistent codes, which allow its use in modern applications for self-modifying code.

Adaptive device with underlying mechanism defined by a programming language

An adaptive device is made up of an underlying mechanism, for instance, an automaton, a grammar, a decision tree, etc., to which is added an adaptive mechanism, responsible for allowing a dynamic modification in the structure of the underlying mechanism. This article aims to investigate if a programming language can be used as an underlying mechanism of an adaptive device, resulting in an adaptive language.

Conception of adaptive programming languages

Adaptive devices show the characteristic of dynamically change themselves in response to input stimuli with no interference of external agents. Occasional changes in behaviour are immediately detected by the devices, which right away react spontaneously to them. Chronologically such devices derived from researches in the field of formal languages and automata. However, formalism spurred applications in several other fields. Based on the operation of adaptive automata, the elementary ideas generanting programming adaptive languages are presented.

Adaptive languages and a new programming style

A programming style can be seen as a particular model of shaping thought or a special way of codifying language to solve a problem. Adaptive languages have the basic feature of allowing the expression of programs which self-modifying through adaptive actions at runtime. The conception of such languages calls for a new programming style, since the application of adaptive technology in the field of programming languages suggests a new way of thinking. With the adaptive style, programming language codes can be structured in such a way that the codified program therein modifies or adapts itself towards the needs of the problem. The adaptive programming style may be a feasible alternate way to obtain self-modifying consistent codes, which allow its use in modern applications for self-modifying code.